diff --git a/methods/permafrost/Generate_Hyp3_Interferograms.ipynb b/methods/permafrost/Generate_Hyp3_Interferograms.ipynb index 40082e5..4799969 100644 --- a/methods/permafrost/Generate_Hyp3_Interferograms.ipynb +++ b/methods/permafrost/Generate_Hyp3_Interferograms.ipynb @@ -7,18 +7,9 @@ "source": [ "## Generate Hyp3 interferogram stack\n", "\n", - "This notebook will queue up processing jobs in Hyp3 and then download and prepare them for use in Mintpy. Code adapted from [Hyp3 tutorial](https://nbviewer.org/github/ASFHyP3/hyp3-docs/blob/main/docs/tutorials/hyp3_insar_stack_for_ts_analysis.ipynb).\n" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "7d0d11d9-c26b-481a-bb32-9f4fb56722eb", - "metadata": {}, - "outputs": [], - "source": [ - "site = 'NorthSlopeEastD102'\n", - "year = 2023" + "This notebook will queue up processing jobs in Hyp3 and \n", + "then download and prepare them for use in Mintpy. \n", + "Code adapted from [Hyp3 tutorial](https://nbviewer.org/github/ASFHyP3/hyp3-docs/blob/main/docs/tutorials/hyp3_insar_stack_for_ts_analysis.ipynb)." ] }, { @@ -33,7 +24,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "id": "36e4d218-7be9-44df-991f-695860da7322", "metadata": {}, "outputs": [], @@ -47,34 +38,36 @@ "from osgeo import gdal\n", "from solid_utils import permafrost_utils as pu\n", "import asf_search as asf\n", - "import hyp3_sdk as sdk" + "import hyp3_sdk as sdk\n", + "import json" ] }, { "cell_type": "code", - "execution_count": 3, - "id": "4ad0d3e6-8845-4f40-ae9e-4c96ffe41edb", + "execution_count": null, + "id": "658aa85e-27d0-4738-bee9-e2e3628e68c1", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Current directory: /home/jovyan/NISAR_cal\n", - "Work directory: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023\n", - " Hyp3 dir: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/products\n", - " MintPy dir: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/MintPy\n" - ] - } - ], + "outputs": [], "source": [ - "################# Set Directories ##########################################\n", - "print('\\nCurrent directory:',os.getcwd())\n", + "################# Set Directories, get site info ##############################\n", + "site = 'NorthSlopeEastD102'\n", + "requirement = 'permafrost'\n", + "dataset = 'Hyp3_S1'\n", + "year = 2025\n", + "start_directory = 'default'\n", "\n", - "if 'work_dir' not in locals():\n", - " work_dir = Path.cwd()/'work'/'permafrost_ouputs'/site/str(year)\n", + "custom_sites = \"/home/jovyan/my_sites.txt\" # Path to custom site metadata\n", + "try:\n", + " with open(custom_sites, \"r\") as f:\n", + " sitedata = json.load(f)\n", + " site_info = sitedata[\"sites\"][site]\n", + "except (FileNotFoundError, json.JSONDecodeError) as e:\n", + " raise RuntimeError(f\"Failed to load site metadata from {custom_sites}: {e}\")\n", + "except KeyError:\n", + " raise ValueError(f\"Site ID '{site}' not found in {custom_sites}\")\n", "\n", + "scratch_path = \"/scratch/nisar-st-calval-solidearth/permafrost/Hyp3_S1\"\n", + "work_dir = Path(f'{scratch_path}/{site}/{str(year)}')\n", "print(\"Work directory:\", work_dir)\n", "work_dir.mkdir(parents=True, exist_ok=True)\n", "# Change to Workdir \n", @@ -86,69 +79,7 @@ " \n", "mintpy_dir = work_dir/'MintPy' \n", "mintpy_dir.mkdir(parents=True, exist_ok=True)\n", - "print(\" MintPy dir:\", mintpy_dir)\n", - "############################################################################\n", - "### List of CalVal Sites:\n", - "'''\n", - "Set NISAR calval sites:\n", - " NorthSlopeEastD102 : North Slope of Alaska including Dalton highway, Sentinel-1 descending path (track) 102. \n", - " : The field validation sites are located in this frame.\n", - " NorthSlopeWestD44 : Western area of the North Slope of Alaska, Sentinel-1 descending path (track) 44.\n", - " NorthwestTerritoriesA78 : North east of Yellowknife, Sentinel-1 ascending path (track) 78.\n", - "\n", - "\n", - "Hyp3 & MintPy parameters:\n", - " calval_location : name\n", - " region_identifier : WTK string with latlon point for identifying image in Hyp3\n", - " subset_region : subset analysis area, in UTM. Given in '[ymin:ymax,xmin:xmax]' or 'none'\n", - " download_start_date : download start date as YYYMMDD \n", - " download_end_date : download end date as YYYMMDD\n", - " mintpy_ref_loc : reference point for use in mintpy in UTM Y,X order. Projection must be that of the Hyp3 images.\n", - " tempBaseMax : maximum number of days, don't use interferograms longer than this value \n", - " ifgExcludeList : default is not to exclude any interferograms\n", - " maskWater : interior locations don't need to mask water\n", - " sentinel_path : asfPath number for identifying image. Also called track.\n", - " sentinel_frame : asfFrame number for identifying image\n", - "'''\n", - "sites = {\n", - " ########## NORTH SLOPE EAST (DALTON/TOOLIK) ##############\n", - " 'NorthSlopeEastD102' : {'calval_location' : 'NorthSlopeEastD102',\n", - " 'region_identifier' : 'POINT(-149.37 69.09)',\n", - " 'subset_region' : '[7620213:7686754, 641941:679925]', \n", - " 'download_start_date' : '20230525',\n", - " 'download_end_date' : '20230910',\n", - " 'mintpy_ref_loc' : '7651392, 666923',\n", - " 'tempBaseMax' : '36',\n", - " 'ifgExcludeList' : 'auto',\n", - " 'maskWater' : 'True',\n", - " 'sentinel_direction' : 'DESCENDING',\n", - " 'sentinel_path' : '102',\n", - " 'sentinel_frame' : '362'},\n", - " 'NorthSlopeWestD44' : {'calval_location' : 'NorthSlopeWestD44',\n", - " 'region_identifier' : 'POINT(-160.25 68.82)',\n", - " 'subset_region' : 'none',\n", - " 'download_start_date' : '20230525',\n", - " 'download_end_date' : '20230910',\n", - " 'mintpy_ref_loc' : '7684081, 437118',\n", - " 'tempBaseMax' : '36',\n", - " 'ifgExcludeList' : 'auto',\n", - " 'maskWater' : 'True',\n", - " 'sentinel_direction' : 'DESCENDING',\n", - " 'sentinel_path' : '44',\n", - " 'sentinel_frame' : '362'},\n", - " 'NorthwestTerritoriesA78' : {'calval_location' : 'NorthwestTerritoriesA78',\n", - " 'region_identifier' : 'POINT(-111.35 63.20)',\n", - " 'subset_region' : 'none',\n", - " 'download_start_date' : '20230525',\n", - " 'download_end_date' : '20230910',\n", - " 'mintpy_ref_loc' : '6980804, 522414',\n", - " 'tempBaseMax' : '36',\n", - " 'ifgExcludeList' : 'auto',\n", - " 'maskWater' : 'True',\n", - " 'sentinel_direction' : 'ASCENDING',\n", - " 'sentinel_path' : '78',\n", - " 'sentinel_frame' : '204'}, \n", - "}" + "print(\" MintPy dir:\", mintpy_dir)" ] }, { @@ -163,424 +94,47 @@ }, { "cell_type": "code", - "execution_count": 6, - "id": "23734b35-31b0-4551-8867-e60a4915459a", + "execution_count": null, + "id": "59b78039-a20c-4e72-8660-c80b6cf78cff", "metadata": {}, "outputs": [], "source": [ - "lonlat = sites[site]['download_region']\n", - "frame = sites[site]['sentinel_frame']\n", - "if sites[site]['sentinel_direction']=='ASCENDING':\n", - " direction = asf.ASCENDING\n", - "elif sites[site]['sentinel_direction']=='DESCENDING':\n", - " direction = asf.DESCENDING\n", + "lonlat = site_info['region_identifier']\n", + "frame = site_info['sentinel_frame']\n", + "if site_info['sentinel_direction']=='ASCENDING':\n", + " direction = asf.constants.ASCENDING\n", + "elif site_info['sentinel_direction']=='DESCENDING':\n", + " direction = asf.constants.DESCENDING\n", "\n", - "stack_start = parse_date(f'{year}-05-25 00:00:00Z')\n", - "stack_end = parse_date(f'{year}-09-10 00:00:00Z')\n", + "stack_start = parse_date(f'{year}-05-20 00:00:00Z')\n", + "stack_end = parse_date(f'{year}-09-20 00:00:00Z')\n", "\n", - "search_results = asf.geo_search(platform=asf.SENTINEL1, intersectsWith=lonlat, start=stack_start,\n", - " end=stack_end, processingLevel=asf.SLC,beamMode=asf.IW,flightDirection=direction,asfFrame=frame)" + "search_results = asf.geo_search(platform=asf.constants.SENTINEL1, \n", + " intersectsWith=lonlat, \n", + " start=stack_start,\n", + " end=stack_end,\n", + " processingLevel=asf.constants.SLC,\n", + " beamMode=asf.constants.IW,\n", + " flightDirection=direction,\n", + " asfFrame=int(frame))" ] }, { "cell_type": "code", - "execution_count": 7, - "id": "8ab1aeb4-ec0b-428d-9cf1-8c0e34ef20c1", + "execution_count": null, + "id": "4927ef76-8002-4dd0-b44f-8cfd48033f67", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "9\n" - ] - }, - { - "data": { - "text/html": [ - "
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9 rows × 30 columns

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DESCENDING \n", - "\n", - " groupID granuleType ... \\\n", - "182 S1A_IWDV_0361_0368_048824_102 SENTINEL_1A_FRAME ... \n", - "183 S1A_IWDV_0361_0368_048999_102 SENTINEL_1A_FRAME ... \n", - "184 S1A_IWDV_0361_0368_049174_102 SENTINEL_1A_FRAME ... \n", - "185 S1A_IWDV_0361_0368_049349_102 SENTINEL_1A_FRAME ... \n", - "186 S1A_IWDV_0361_0368_049524_102 SENTINEL_1A_FRAME ... \n", - "187 S1A_IWDV_0361_0368_049699_102 SENTINEL_1A_FRAME ... \n", - "188 S1A_IWDV_0361_0368_049874_102 SENTINEL_1A_FRAME ... \n", - "189 S1A_IWDV_0361_0368_050049_102 SENTINEL_1A_FRAME ... \n", - "190 S1A_IWDV_0361_0368_050224_102 SENTINEL_1A_FRAME ... \n", - "\n", - " sceneName sensor \\\n", - "182 S1A_IW_SLC__1SDV_20230603T164401_20230603T1644... C-SAR \n", - "183 S1A_IW_SLC__1SDV_20230615T164402_20230615T1644... C-SAR \n", - "184 S1A_IW_SLC__1SDV_20230627T164402_20230627T1644... C-SAR \n", - "185 S1A_IW_SLC__1SDV_20230709T164403_20230709T1644... C-SAR \n", - "186 S1A_IW_SLC__1SDV_20230721T164404_20230721T1644... C-SAR \n", - "187 S1A_IW_SLC__1SDV_20230802T164404_20230802T1644... C-SAR \n", - "188 S1A_IW_SLC__1SDV_20230814T164405_20230814T1644... C-SAR \n", - "189 S1A_IW_SLC__1SDV_20230826T164406_20230826T1644... C-SAR \n", - "190 S1A_IW_SLC__1SDV_20230907T164407_20230907T1644... C-SAR \n", - "\n", - " startTime stopTime \\\n", - "182 2023-06-03 16:44:01+00:00 2023-06-03T16:44:29.000Z \n", - "183 2023-06-15 16:44:02.311000+00:00 2023-06-15T16:44:30.221Z \n", - "184 2023-06-27 16:44:02.446000+00:00 2023-06-27T16:44:30.361Z \n", - "185 2023-07-09 16:44:03.895000+00:00 2023-07-09T16:44:31.808Z \n", - "186 2023-07-21 16:44:04.486000+00:00 2023-07-21T16:44:32.398Z \n", - "187 2023-08-02 16:44:04.784000+00:00 2023-08-02T16:44:32.697Z \n", - "188 2023-08-14 16:44:05.666000+00:00 2023-08-14T16:44:33.581Z \n", - "189 2023-08-26 16:44:06.579000+00:00 2023-08-26T16:44:34.495Z \n", - "190 2023-09-07 16:44:07.029000+00:00 2023-09-07T16:44:34.946Z \n", - "\n", - " url \\\n", - "182 https://datapool.asf.alaska.edu/SLC/SA/S1A_IW_... \n", - "183 https://datapool.asf.alaska.edu/SLC/SA/S1A_IW_... \n", - "184 https://datapool.asf.alaska.edu/SLC/SA/S1A_IW_... \n", - "185 https://datapool.asf.alaska.edu/SLC/SA/S1A_IW_... \n", - "186 https://datapool.asf.alaska.edu/SLC/SA/S1A_IW_... \n", - "187 https://datapool.asf.alaska.edu/SLC/SA/S1A_IW_... \n", - "188 https://datapool.asf.alaska.edu/SLC/SA/S1A_IW_... \n", - "189 https://datapool.asf.alaska.edu/SLC/SA/S1A_IW_... \n", - "190 https://datapool.asf.alaska.edu/SLC/SA/S1A_IW_... \n", - "\n", - " fileName frameNumber \\\n", - "182 S1A_IW_SLC__1SDV_20230603T164401_20230603T1644... 362 \n", - "183 S1A_IW_SLC__1SDV_20230615T164402_20230615T1644... 362 \n", - "184 S1A_IW_SLC__1SDV_20230627T164402_20230627T1644... 362 \n", - "185 S1A_IW_SLC__1SDV_20230709T164403_20230709T1644... 362 \n", - "186 S1A_IW_SLC__1SDV_20230721T164404_20230721T1644... 362 \n", - "187 S1A_IW_SLC__1SDV_20230802T164404_20230802T1644... 362 \n", - "188 S1A_IW_SLC__1SDV_20230814T164405_20230814T1644... 362 \n", - "189 S1A_IW_SLC__1SDV_20230826T164406_20230826T1644... 362 \n", - "190 S1A_IW_SLC__1SDV_20230907T164407_20230907T1644... 362 \n", - "\n", - " temporalBaseline perpendicularBaseline \\\n", - "182 0 0.0 \n", - "183 12 -16.0 \n", - "184 24 -172.0 \n", - "185 36 -107.0 \n", - "186 48 -23.0 \n", - "187 60 -107.0 \n", - "188 72 -110.0 \n", - "189 84 -118.0 \n", - "190 96 -163.0 \n", - "\n", - " geometry \n", - "182 {'coordinates': [[[-149.293701, 67.836151], [-... \n", - "183 {'coordinates': [[[-149.29332, 67.835739], [-1... \n", - "184 {'coordinates': [[[-149.289795, 67.835335], [-... \n", - "185 {'coordinates': [[[-149.291443, 67.835373], [-... \n", - "186 {'coordinates': [[[-149.293121, 67.835464], [-... \n", - "187 {'coordinates': [[[-149.29213, 67.83564], [-14... \n", - "188 {'coordinates': [[[-149.290665, 67.835297], [-... \n", - "189 {'coordinates': [[[-149.291, 67.83493], [-148.... \n", - "190 {'coordinates': [[[-149.28894, 67.836067], [-1... \n", - "\n", - "[9 rows x 30 columns]" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "baseline_results = asf.baseline_search.stack_from_product(search_results[-1])\n", "\n", "columns = list(baseline_results[0].properties.keys()) + ['geometry', ]\n", - "data = [list(scene.properties.values()) + [scene.geometry, ] for scene in baseline_results]\n", + "data = [list(scene.properties.values()) + [scene.geometry, ] \n", + " for scene in baseline_results]\n", "\n", "stack = pd.DataFrame(data, columns=columns)\n", "stack['startTime'] = stack.startTime.apply(parse_date)\n", "\n", - "# stack_start = parse_date(f'{year}-05-25 00:00:00Z')\n", - "# stack_end = parse_date(f'{year}-09-10 00:00:00Z')\n", - "\n", "stack = stack.loc[(stack_start <= stack.startTime) & (stack.startTime <= stack_end)]\n", "\n", "stack" @@ -588,17 +142,18 @@ }, { "cell_type": "code", - "execution_count": 8, - "id": "dd86d2e4-9b9b-4e2f-a238-d4479e584e82", + "execution_count": null, + "id": "e61a5947-61f5-494f-a59f-2917286a432c", "metadata": {}, "outputs": [], "source": [ "sbas_pairs = set()\n", "\n", - "for reference, rt in stack.loc[::-1, ['sceneName', 'temporalBaseline']].itertuples(index=False):\n", + "for reference, rt in stack.loc[::-1, ['sceneName', 'temporalBaseline']].itertuples(\n", + " index=False):\n", " secondaries = stack.loc[\n", " (stack.sceneName != reference)\n", - " & (stack.temporalBaseline - rt <= int(sites[site]['tempBaseMax']))\n", + " & (stack.temporalBaseline - rt <= int(site_info['tempBaseMax']))\n", " & (stack.temporalBaseline - rt > 0)\n", " ]\n", " for secondary in secondaries.sceneName:\n", @@ -628,18 +183,10 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "id": "86270ef1-dd29-42bb-9e1e-e2e4e5b4d7ca", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Jobs were set to be processed by this command!\n" - ] - } - ], + "outputs": [], "source": [ "\n", "jobs = sdk.Batch()\n", @@ -659,31 +206,18 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "id": "bf4cbadf-6264-446f-b720-eb463a592ce0", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "No jobs running, all clear\n" - ] - } - ], + "outputs": [], "source": [ - "class stillrunningError(Error):\n", - " \"\"\"raised when jobs are still running\"\"\"\n", - " pass\n", - "\n", "running = len(hyp3.find_jobs(status_code=[\"RUNNING\"]))\n", - "running += len(hyp3.find_jobs(status_code=[\"PENDING\"]))\n", + "pending = len(hyp3.find_jobs(status_code=[\"PENDING\"]))\n", "\n", - "if running > 0:\n", - " print('Jobs still running!')\n", - " raise stillrunningError\n", + "if running+pending ==0:\n", + " print('No jobs running, all clear')\n", "else:\n", - " print('No jobs running, all clear')" + " print(f'Jobs still running!\\n{pending} pending, {running} running')" ] }, { @@ -695,11 +229,9 @@ ] }, { - "cell_type": "code", - "execution_count": null, - "id": "5631bb4a-d9ac-46b1-861c-4cd28d8c836a", + "cell_type": "markdown", + "id": "0586588a-94ee-47e2-a2f5-dc1cfa7b8008", "metadata": {}, - "outputs": [], "source": [ "\n", "h3projname = f\"{site}_NCV_{year}\"\n", @@ -718,8 +250,8 @@ }, { "cell_type": "code", - "execution_count": 11, - "id": "5f7b516e-c104-48b1-b14c-9406a6168367", + "execution_count": null, + "id": "c659c967-bfe5-4325-a39d-e63a8a63ba38", "metadata": {}, "outputs": [], "source": [ @@ -728,13 +260,77 @@ "overlap = pu.get_common_overlap(files)\n", "pu.clip_hyp3_products_to_common_overlap(hyp3_dir, overlap)" ] + }, + { + "cell_type": "markdown", + "id": "f1192d9a-2716-4093-b3ae-a34df331fa13", + "metadata": {}, + "source": [ + "## Generate MintPy Config file" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ac7a86d3-7a04-4c4a-925c-8998103fad8f", + "metadata": {}, + "outputs": [], + "source": [ + "def writenumpyconfig(config_file,data_dir,reflalo = None, subset = None):\n", + " \"\"\"Write a mintpy config file.\n", + " config_file: file name to write to\n", + " data_dir: directory of .tif files\n", + " reflalo (optional): 'y,x' of reference point in tif proj\n", + " subset (optional): '[ymin:ymax,xmin:xmax]' in tif proj\n", + " \n", + " Note: hyp3 provides images in a utm projection, so \n", + " lalo here refers to y,x in map coords\"\"\"\n", + " \n", + " cfgtext = f\"\"\"\n", + " mintpy.load.processor = hyp3\n", + " ##---------interferogram datasets:\n", + " mintpy.load.unwFile = {data_dir}/*/*_unw_phase_clipped.tif\n", + " mintpy.load.corFile = {data_dir}/*/*_corr_clipped.tif\n", + " ##---------geometry datasets:\n", + " mintpy.load.demFile = {data_dir}/*/*_dem_clipped.tif\n", + " mintpy.load.incAngleFile = {data_dir}/*/*_lv_theta_clipped.tif\n", + " mintpy.load.azAngleFile = {data_dir}/*/*_lv_phi_clipped.tif\n", + " mintpy.load.waterMaskFile = {data_dir}/*/*_water_mask_clipped.tif\"\"\"\n", + "\n", + " if reflalo:\n", + " cfgtext+=f\"\"\" \n", + " mintpy.reference.lalo = {reflalo}\"\"\" #should be 'y,x' in map coords\n", + " \n", + " if not subset:\n", + " subset = 'no'\n", + " cfgtext+=f\"\"\"\n", + " mintpy.subset.lalo = {subset}\"\"\" #should be '[ymin:ymax,xmin:xmax]'\n", + " #in map coords\n", + " \n", + " mintpy_config = config_file\n", + " mintpy_config.write_text(cfgtext)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f2dcce3c-9773-4d3a-bc08-d44915833a1c", + "metadata": {}, + "outputs": [], + "source": [ + "config_file = mintpy_dir/f\"{site_info['calval_location']}_{str(year)}.cfg\"\n", + "writenumpyconfig(config_file,\n", + " hyp3_dir,\n", + " reflalo=site_info['mintpy_ref_loc'],\n", + " subset = site_info['subset_region'])" + ] } ], "metadata": { "kernelspec": { - "display_name": "insar_analysis [conda env:.local-insar_analysis]", + "display_name": "solid_earth_atbd", "language": "python", - "name": "conda-env-.local-insar_analysis-py" + "name": "solid_earth_atbd" }, "language_info": { "codemirror_mode": { @@ -746,7 +342,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.16" + "version": "3.12.5" } }, "nbformat": 4, diff --git a/methods/permafrost/HappyValleyEast_level.png b/methods/permafrost/HappyValleyEast_level.png new file mode 100644 index 0000000..837cfde Binary files /dev/null and b/methods/permafrost/HappyValleyEast_level.png differ diff --git a/methods/permafrost/Permafrost_Requirement_Validation.ipynb b/methods/permafrost/Permafrost_Requirement_Validation.ipynb index 62225cb..fccea22 100644 --- a/methods/permafrost/Permafrost_Requirement_Validation.ipynb +++ b/methods/permafrost/Permafrost_Requirement_Validation.ipynb @@ -10,39 +10,10 @@ "### Workflow to Validate NISAR L2Permafrost Displacement Requirement\n", "\n", "**Code authored by:** Andrew Johnson, Simon Zwieback, Franz Meyer, Jie Chen
\n", - "2024\n", - "\n", - "
\n", - "UPDATE THIS Both the initial setup (Prep A section) and download of the data (Prep B section) should be run at the start of the notebook. And all subsequent sections NEED to be run in order.\n", - "
\n", "\n", "
" ] }, - { - "cell_type": "markdown", - "id": "62b7d49b-d1bd-4df3-8942-2e2f512c3969", - "metadata": {}, - "source": [ - "Define CalVal Site" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "14433f09-e124-44f9-ab7f-06cf811babf6", - "metadata": {}, - "outputs": [], - "source": [ - "# Choose a site and track direction\n", - "# Available permafrost displacement validation sites: \n", - "# NorthSlopeEastD102 : North Slope of Alaska including Dalton highway, Sentinel-1 path (track) 102. The\n", - "# field validation sites are located in this frame.\n", - "\n", - "site='NorthSlopeEastD102'\n", - "year=2023" - ] - }, { "cell_type": "markdown", "id": "f4e250f0-bb27-4b5f-8271-91006349bfe9", @@ -85,205 +56,91 @@ "id": "d41fe611-1ac0-47d3-98bf-838d5a413bd1", "metadata": {}, "source": [ + "
\n", "\n", - "## Prep A. Environment Setup" + "\n", + "### Environment Setup\n", + "\n", + "#### Load Python Packages" ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "id": "47d008b0-7433-49ef-8bbc-962d39444a6a", - "metadata": {}, + "metadata": { + "tags": [] + }, "outputs": [], "source": [ - "\n", - "#do imports\n", "import numpy as np\n", - "from matplotlib import pyplot as plt\n", "import pandas as pd\n", + "import json\n", "import os\n", + "import subprocess\n", + "import h5py\n", + "\n", + "from datetime import datetime as dt\n", + "from matplotlib import pyplot as plt\n", "from pathlib import Path\n", - "from solid_utils import permafrost_utils as pu\n", - "# from mintpy import view, tsview, plot_network, plot_transection, plot_coherence_matrix\n", "from mintpy import plot_network,view\n", "from mintpy.utils import readfile\n", - "import subprocess\n", - "import h5py\n", - "from datetime import datetime\n", - "from solid_utils.sampling import load_geo_utm, samp_pair,load_geo_utm\n" + "from solid_utils import permafrost_utils as pu\n", + "from solid_utils.sampling import load_geo_utm, samp_pair,load_geo_utm\n", + "from solid_utils.plotting import display_permafrost_validation \n", + "from solid_utils.plotting import display_validation_table\n", + "from solid_utils.saving import save_results" ] }, { "cell_type": "code", - "execution_count": 3, - "id": "c719721d-177a-4560-8845-fa1419b3a59b", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Current directory: /home/jovyan/NISAR_cal\n", - "Work directory: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023\n", - " Hyp3 dir: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/products\n", - " MintPy dir: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/MintPy\n", - "\n", - "Selected site: NorthSlopeEastD102\n", - " calval_location : NorthSlopeEastD102\n", - " region_identifier : POINT(-149.37 69.09)\n", - " subset_region : [7620213:7686754, 641941:679925]\n", - " download_start_date : 20230525\n", - " download_end_date : 20230910\n", - " mintpy_ref_loc : 7651392, 666923\n", - " tempBaseMax : 36\n", - " ifgExcludeList : auto\n", - " maskWater : True\n", - " sentinel_direction : DESCENDING\n", - " sentinel_path : 102\n", - " sentinel_frame : 362\n" - ] - } - ], - "source": [ - "################# Set Directories ##########################################\n", - "print('\\nCurrent directory:',os.getcwd())\n", - "\n", - "#Base directory for working on projects\n", - "if 'base_dir' not in locals():\n", - " base_dir = Path.cwd()\n", - " \n", - "# work_dir = Path.cwd()/'work'/'permafrost_ouputs'/site/str(year)\n", - "work_dir = base_dir/'work'/'permafrost_ouputs'/site/str(year)\n", - "print(\"Work directory:\", work_dir)\n", - "work_dir.mkdir(parents=True, exist_ok=True)\n", - "\n", - "# Change to Workdir \n", - "os.chdir(work_dir)\n", - " \n", - "hyp3_dir = work_dir/'products' #aka gunwdir\n", - "hyp3_dir.mkdir(parents=True, exist_ok=True)\n", - "print(\" Hyp3 dir:\", hyp3_dir) \n", - " \n", - "mintpy_dir = work_dir/'MintPy' \n", - "mintpy_dir.mkdir(parents=True, exist_ok=True)\n", - "print(\" MintPy dir:\", mintpy_dir)\n", - "############################################################################\n", - "### List of CalVal Sites:\n", - "'''\n", - "Set NISAR calval sites:\n", - " NorthSlopeEastD102 : North Slope of Alaska including Dalton highway, Sentinel-1 descending path (track) 102. \n", - " : The field validation sites are located in this frame.\n", - " NorthSlopeWestD44 : Western area of the North Slope of Alaska, Sentinel-1 descending path (track) 44.\n", - " NorthwestTerritoriesA78 : North east of Yellowknife, Sentinel-1 ascending path (track) 78.\n", - "\n", - "\n", - "Hyp3 & MintPy parameters:\n", - " calval_location : name\n", - " region_identifier : WTK string with latlon point for identifying image in Hyp3\n", - " subset_region : subset analysis area, in UTM. Given in '[ymin:ymax,xmin:xmax]' or 'none'\n", - " download_start_date : download start date as YYYMMDD \n", - " download_end_date : download end date as YYYMMDD\n", - " mintpy_ref_loc : reference point for use in mintpy in UTM Y,X order. Projection must be that of the Hyp3 images.\n", - " tempBaseMax : maximum number of days, don't use interferograms longer than this value \n", - " ifgExcludeList : default is not to exclude any interferograms\n", - " maskWater : interior locations don't need to mask water\n", - " sentinel_path : asfPath number for identifying image. Also called track.\n", - " sentinel_frame : asfFrame number for identifying image\n", - "'''\n", - "sites = {\n", - " ########## NORTH SLOPE EAST (DALTON/TOOLIK) ##############\n", - " 'NorthSlopeEastD102' : {'calval_location' : 'NorthSlopeEastD102',\n", - " 'region_identifier' : 'POINT(-149.37 69.09)',\n", - " 'subset_region' : '[7620213:7686754, 641941:679925]', \n", - " 'download_start_date' : '20230525',\n", - " 'download_end_date' : '20230910',\n", - " 'mintpy_ref_loc' : '7651392, 666923',\n", - " 'tempBaseMax' : '36',\n", - " 'ifgExcludeList' : 'auto',\n", - " 'maskWater' : 'True',\n", - " 'sentinel_direction' : 'DESCENDING',\n", - " 'sentinel_path' : '102',\n", - " 'sentinel_frame' : '362'},\n", - " 'NorthSlopeWestD44' : {'calval_location' : 'NorthSlopeWestD44',\n", - " 'region_identifier' : 'POINT(-160.25 68.82)',\n", - " 'subset_region' : 'none',\n", - " 'download_start_date' : '20230525',\n", - " 'download_end_date' : '20230910',\n", - " 'mintpy_ref_loc' : '7684081, 437118',\n", - " 'tempBaseMax' : '36',\n", - " 'ifgExcludeList' : 'auto',\n", - " 'maskWater' : 'True',\n", - " 'sentinel_direction' : 'DESCENDING',\n", - " 'sentinel_path' : '44',\n", - " 'sentinel_frame' : '362'},\n", - " 'NorthwestTerritoriesA78' : {'calval_location' : 'NorthwestTerritoriesA78',\n", - " 'region_identifier' : 'POINT(-111.35 63.20)',\n", - " 'subset_region' : 'none',\n", - " 'download_start_date' : '20230525',\n", - " 'download_end_date' : '20230910',\n", - " 'mintpy_ref_loc' : '6980804, 522414',\n", - " 'tempBaseMax' : '36',\n", - " 'ifgExcludeList' : 'auto',\n", - " 'maskWater' : 'True',\n", - " 'sentinel_direction' : 'ASCENDING',\n", - " 'sentinel_path' : '78',\n", - " 'sentinel_frame' : '204'}, \n", - "}\n", - "\n", - "permafrost_available_sites = ['NorthSlopeEastD102','NorthSlopeWestD44','NorthwestTerritoriesA78']\n", - "\n", - "if site not in permafrost_available_sites:\n", - " msg = '\\nSelected site not available! Please select one of the following sites:: \\n{}'.format(permafrost_available_sites)\n", - " raise Exception(msg)\n", - "else:\n", - " print('\\nSelected site: {}'.format(site))\n", - " for key, value in sites[site].items():\n", - " print(' '+ key, ' : ', value)" - ] - }, - { - "cell_type": "markdown", - "id": "2aef582e-248c-4e91-ac56-7fdfde48cc66", - "metadata": {}, + "execution_count": null, + "id": "13365f02-7935-4e51-b2e0-93eab593130b", + "metadata": { + "tags": [] + }, + "outputs": [], "source": [ - "\n", - "## Prep B: Data staging\n", - "\n", - "Author's note: processed Sentinel-1 interferograms may be staged in a S3 bucket in the future. They are not staged yet however, so ```Use_Staged_Data``` must remain false, and the interferograms must be obtained from Hyp3. \n", - "\n", - "See [Section 1](#permafrost_infgs) for details on creating and downloading this data." + "site = 'NorthSlopeEastD102'\n", + "requirement = 'permafrost'\n", + "dataset = 'Hyp3_S1'\n", + "year = 2025\n", + "start_directory = 'default'\n", + "\n", + "custom_sites = \"/home/jovyan/my_sites.txt\" # Path to custom site metadata\n", + "try:\n", + " with open(custom_sites, \"r\") as f:\n", + " sitedata = json.load(f)\n", + " site_info = sitedata[\"sites\"][site]\n", + "except (FileNotFoundError, json.JSONDecodeError) as e:\n", + " raise RuntimeError(f\"Failed to load site metadata from {custom_sites}: {e}\")\n", + "except KeyError:\n", + " raise ValueError(f\"Site ID '{site}' not found in {custom_sites}\")" ] }, { "cell_type": "code", - "execution_count": 4, - "id": "9fb2c2d2-17de-43ca-9757-5b4fc8c77bc9", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Not using staged data. You must use Hyp3 to produce the interferograms.\n", - "Field validation data is currently included in the git repo at the moment,\n", - "but will be moved to the cal/val database\n" - ] - } - ], + "execution_count": null, + "id": "64e5fa73-dd76-4d2e-83cd-453777e469f2", + "metadata": { + "tags": [] + }, + "outputs": [], "source": [ - "# option to control the use of pre-staged data; [False/True]\n", - "Use_Staged_Data = False\n", + "################# Set Directories ##########################################\n", + "print('\\nCurrent directory:',os.getcwd())\n", "\n", - "######### DO NOT CHANGE LINES BELOW ########\n", + "start_directory = Path(f'/scratch/nisar-st-calval-solidearth/permafrost')\n", + "work_dir = os.path.join(start_directory,dataset,site,str(year))\n", + "field_dir = os.path.join(start_directory,'fielddata')\n", "\n", - "if Use_Staged_Data:\n", - " #No data included in staging yet.\n", - " print('This section has yet to be added.\\nNo data has been staged yet.')\n", - "else:\n", - " #Data must be processed from Hyp3\n", - " print('Not using staged data. You must use Hyp3 to produce the interferograms.')\n", - " print('Field validation data is currently included in the git repo at the moment,\\nbut will be moved to the cal/val database')" + "gunw_dir = os.path.join(work_dir,'products')\n", + "mintpy_dir = os.path.join(work_dir,'MintPy')\n", + "os.makedirs(mintpy_dir,exist_ok=True)\n", + "print(\" MintPy dir:\", mintpy_dir)\n", + "\n", + "# # Change to Workdir \n", + "os.chdir(mintpy_dir)" ] }, { @@ -301,7 +158,7 @@ }, { "cell_type": "markdown", - "id": "02006ccd-c048-42c3-96b9-d5c7071da061", + "id": "4b81b3ee-f6fa-42c1-981b-282b1c0497a8", "metadata": {}, "source": [ "\n", @@ -312,184 +169,17 @@ "Note: this code is currently set up to run on MintPy version 1.5.1." ] }, - { - "cell_type": "markdown", - "id": "22342944-60cb-4cfc-a878-9bd4e72d6e07", - "metadata": {}, - "source": [ - "\n", - "## 2.1 Set Up MintPy configuration file\n", - "\n", - "Mintpy will be configured to use the hyp3 processor. A function is defined here, to allow for future subsetting and adjustment of reference pixel location." - ] - }, { "cell_type": "code", - "execution_count": 5, - "id": "2c0b3cc0-e3b1-47f9-8471-8a66d03a393b", + "execution_count": null, + "id": "d89886a4-2fd4-4da1-b5a6-03deb83f4bd5", "metadata": {}, "outputs": [], "source": [ - "def writenumpyconfig(config_file,data_dir,reflalo = None, subset = None):\n", - " \"\"\"Write a mintpy config file.\n", - " config_file: file name to write to\n", - " data_dir: directory of .tif files\n", - " reflalo (optional): 'y,x' of reference point in tif proj\n", - " subset (optional): '[ymin:ymax,xmin:xmax]' in tif proj\n", - " \n", - " Note: hyp3 provides images in a utm projection, so lalo here refers to y,x in map coords\"\"\"\n", - " \n", - " cfgtext = f\"\"\"\n", - " mintpy.load.processor = hyp3\n", - " ##---------interferogram datasets:\n", - " mintpy.load.unwFile = {data_dir}/*/*_unw_phase_clipped.tif\n", - " mintpy.load.corFile = {data_dir}/*/*_corr_clipped.tif\n", - " ##---------geometry datasets:\n", - " mintpy.load.demFile = {data_dir}/*/*_dem_clipped.tif\n", - " mintpy.load.incAngleFile = {data_dir}/*/*_lv_theta_clipped.tif\n", - " mintpy.load.azAngleFile = {data_dir}/*/*_lv_phi_clipped.tif\n", - " mintpy.load.waterMaskFile = {data_dir}/*/*_water_mask_clipped.tif\"\"\"\n", - "\n", - " if reflalo:\n", - " cfgtext+=f\"\"\" \n", - " mintpy.reference.lalo = {reflalo}\"\"\" #should be 'y,x' in map coords\n", - " \n", - " if not subset:\n", - " subset = 'no'\n", - " cfgtext+=f\"\"\"\n", - " mintpy.subset.lalo = {subset}\"\"\" #should be '[ymin:ymax,xmin:xmax]' in map coords\n", - "\n", - " mintpy_config = config_file\n", - " mintpy_config.write_text(cfgtext)\n", - "\n", - "config_file = mintpy_dir/f\"{sites[site]['calval_location']}_{str(year)}.cfg\"\n", - "writenumpyconfig(config_file,hyp3_dir,reflalo=sites[site]['mintpy_ref_loc'])" - ] - }, - { - "cell_type": "markdown", - "id": "e271300e-3223-4ae8-978d-8bda7659d6fd", - "metadata": {}, - "source": [ - "\n", - "## 2.2 Load Data into MintPy\n", - "\n", - "The output of this step is an \"inputs\" directory in 'calval_directory/calval_location/MintPy/' containing two HDF5 files:\n", - "\n", - "* ifgramStack.h5: This file contains 6 dataset cubes (e.g. unwrapped phase, coherence, connected components etc.) and multiple metadata\n", - "* geometryGeo.h5: This file contains geometrical datasets (e.g., incidence/azimuth angle, masks, etc.)\n" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "046f1678-a112-4be9-925d-8df51f2824d0", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MintPy version 1.5.1, date 2023-01-03\n", - "--RUN-at-2024-03-22 18:20:12.105258--\n", - "Current directory: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023\n", - "Run routine processing with smallbaselineApp.py on steps: ['load_data']\n", - "Remaining steps: ['modify_network', 'reference_point', 'quick_overview', 'correct_unwrap_error', 'invert_network', 'correct_LOD', 'correct_SET', 'correct_troposphere', 'deramp', 'correct_topography', 'residual_RMS', 'reference_date', 'velocity', 'geocode', 'google_earth', 'hdfeos5']\n", - "--------------------------------------------------\n", - "Project name: NorthSlopeEastD102_2023\n", - "Go to work directory: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023\n", - "read custom template file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/MintPy/NorthSlopeEastD102_2023.cfg\n", - "update default template based on input custom template\n", - "No new option value found, skip updating /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg\n", - "read default template file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg\n", - "\n", - "\n", - "******************** step - load_data ********************\n", - "\n", - "load_data.py --template /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/MintPy/NorthSlopeEastD102_2023.cfg --project NorthSlopeEastD102_2023\n", - "processor : hyp3\n", - "SAR platform/sensor : unknown from project name \"NorthSlopeEastD102_2023\"\n", - "--------------------------------------------------\n", - "prepare metadata files for hyp3 products\n", - "prep_hyp3.py \"/home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/products/*/*_unw_phase_clipped.tif\"\n", - "prep_hyp3.py \"/home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/products/*/*_corr_clipped.tif\"\n", - "prep_hyp3.py \"/home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/products/*/*_dem_clipped.tif\"\n", - "prep_hyp3.py \"/home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/products/*/*_lv_theta_clipped.tif\"\n", - "prep_hyp3.py \"/home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/products/*/*_lv_phi_clipped.tif\"\n", - "prep_hyp3.py \"/home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/products/*/*_water_mask_clipped.tif\"\n", - "--------------------------------------------------\n", - "updateMode : True\n", - "compression: None\n", - "multilook x/ystep: 1/1\n", - "multilook method : nearest\n", - "--------------------------------------------------\n", - "searching geometry files info\n", - "input data files:\n", - "height : /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/products/S1AA_20230603T164401_20230615T164402_VVP012_INT80_G_ueF_C9F1/S1AA_20230603T164401_20230615T164402_VVP012_INT80_G_ueF_C9F1_dem_clipped.tif\n", - "incidenceAngle : /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/products/S1AA_20230603T164401_20230615T164402_VVP012_INT80_G_ueF_C9F1/S1AA_20230603T164401_20230615T164402_VVP012_INT80_G_ueF_C9F1_lv_theta_clipped.tif\n", - "azimuthAngle : /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/products/S1AA_20230603T164401_20230615T164402_VVP012_INT80_G_ueF_C9F1/S1AA_20230603T164401_20230615T164402_VVP012_INT80_G_ueF_C9F1_lv_phi_clipped.tif\n", - "waterMask : /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/products/S1AA_20230603T164401_20230615T164402_VVP012_INT80_G_ueF_C9F1/S1AA_20230603T164401_20230615T164402_VVP012_INT80_G_ueF_C9F1_water_mask_clipped.tif\n", - "All datasets exists in file geometryGeo.h5 with same size as required, no need to re-load.\n", - "--------------------------------------------------\n", - "searching interferogram pairs info\n", - "input data files:\n", - "unwrapPhase : /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/products/*/*_unw_phase_clipped.tif\n", - "coherence : /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/products/*/*_corr_clipped.tif\n", - "number of unwrapPhase : 17\n", - "number of coherence : 17\n", - "All date12 exists in file ifgramStack.h5 with same size as required, no need to re-load.\n", - "--------------------------------------------------\n", - "searching ionosphere pairs info\n", - "input data files:\n", - "WARNING: No data files found for the required dataset: ['unwrapPhase']! Skip loading for ionosphere stack.\n", - "--------------------------------------------------\n", - "searching offset pairs info\n", - "input data files:\n", - "WARNING: No data files found for the required dataset: ['rangeOffset', 'azimuthOffset']! Skip loading for offset stack.\n", - "time used: 00 mins 0.3 secs.\n", - "\n", - "No lookup table (longitude or rangeCoord) found in files.\n", - "Input data seems to be geocoded. Lookup file not needed.\n", - "Loaded dataset are processed by InSAR software: hyp3\n", - "Loaded dataset are in GEO coordinates\n", - "Interferogram Stack: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5\n", - "Geometry File : /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/geometryGeo.h5\n", - "Lookup Table File : None\n", - "--------------------------------------------------\n", - "updating metadata based on custom template file NorthSlopeEastD102_2023.cfg for file: ifgramStack.h5\n", - "updating metadata based on custom template file NorthSlopeEastD102_2023.cfg for file: geometryGeo.h5\n", - "Go back to directory: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023\n", - "\n", - "################################################\n", - " Normal end of smallbaselineApp processing!\n", - "################################################\n", - "Time used: 00 mins 0.7 secs\n", - "\n", - "Mintpy input files:\n" - ] - }, - { - "data": { - "text/plain": [ - "['ifgramStack.h5', 'geometryGeo.h5', 'ERA5.h5']" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#Delete any existing water masks. This is done in case later sections of this notebook\n", - "#have already been run, as their masks will only include a subset of the region.\n", - "watermask = work_dir/'waterMask.h5'\n", - "if watermask.exists():\n", - " watermask.unlink()\n", - "\n", + "# Loading data into mintpy, if not done already\n", + "config_file = os.path.join(mintpy_dir,site + f'_{year}.cfg')\n", "command = 'smallbaselineApp.py ' + str(config_file) + ' --dostep load_data'\n", - "process = subprocess.run(command, shell=True)\n", - "print('Mintpy input files:')\n", - "[x for x in os.listdir('inputs') if x.endswith('.h5')]" + "process = subprocess.run(command, shell=True)" ] }, { @@ -498,67 +188,21 @@ "metadata": {}, "source": [ "\n", - "## 2.3 Validate/Modify Interferogram Network\n" + "## 2.1 Validate/Modify Interferogram Network\n" ] }, { "cell_type": "code", - "execution_count": 45, - "id": "232c8040-8ab1-428b-a060-d05d844b9c33", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MintPy version 1.5.1, date 2023-01-03\n", - "--RUN-at-2024-03-22 19:19:27.365999--\n", - "Current directory: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023\n", - "Run routine processing with smallbaselineApp.py on steps: ['modify_network']\n", - "Remaining steps: ['reference_point', 'quick_overview', 'correct_unwrap_error', 'invert_network', 'correct_LOD', 'correct_SET', 'correct_troposphere', 'deramp', 'correct_topography', 'residual_RMS', 'reference_date', 'velocity', 'geocode', 'google_earth', 'hdfeos5']\n", - "--------------------------------------------------\n", - "Project name: NorthSlopeEastD102_2023\n", - "Go to work directory: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023\n", - "read custom template file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/MintPy/NorthSlopeEastD102_2023.cfg\n", - "update default template based on input custom template\n", - "No new option value found, skip updating /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg\n", - "read default template file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg\n", - "\n", - "\n", - "******************** step - modify_network ********************\n", - "Input data seems to be geocoded. Lookup file not needed.\n", - "generate /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/waterMask.h5 from /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/geometryGeo.h5 for conveniency\n", - "['/home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/waterMask.h5'] exists and is newer than ['/home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/geometryGeo.h5'] --> skip.\n", - "\n", - "modify_network.py /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5 -t /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg\n", - "read options from template file: smallbaselineApp.cfg\n", - "No lookup table (longitude or rangeCoord) found in files.\n", - "No input option found to remove interferogram\n", - "Keep all interferograms by enable --reset option\n", - "--------------------------------------------------\n", - "reset dataset 'dropIfgram' to True for all interferograms for file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5\n", - "All dropIfgram are already True, no need to reset.\n", - "\n", - "plot_network.py /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5 -t /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg --nodisplay -d coherence -v 0.2 1.0\n", - "['/home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/network.pdf'] exists and is newer than ['/home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5', '/home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/coherenceSpatialAvg.txt', '/home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg'] --> skip.\n", - "Go back to directory: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023\n", - "\n", - "################################################\n", - " Normal end of smallbaselineApp processing!\n", - "################################################\n", - "Time used: 00 mins 0.9 secs\n", - "\n" - ] - } - ], + "execution_count": null, + "id": "586b16f1-7ea3-4979-a612-a7b728b7fe50", + "metadata": { + "tags": [] + }, + "outputs": [], "source": [ + "config_file = os.path.join(mintpy_dir,site + f'_{year}.cfg')\n", "command = 'smallbaselineApp.py ' + str(config_file) + ' --dostep modify_network'\n", - "process = subprocess.run(command, shell=True)\n", - "\n", - "# Currently I cannot get plot_network to work properly (suggestions welcome).\n", - "# There seems to be a class object called inps which is supposed to contain metadata \n", - "# and numerous plotting options, but I do not know how to create this object.\n", - "# plot_network.plot_network(inps)" + "process = subprocess.run(command, shell=True)" ] }, { @@ -567,28 +211,19 @@ "metadata": {}, "source": [ "\n", - "## 2.4 Reference interferograms to common Lat/Lon\n", + "## 2.2 Reference interferograms to common Lat/Lon\n", "\n", "Note: The printed ```REF_LAT``` and ```REF_LON``` from this step will be the UTM y and x coordinates, respectively. ```REF_X``` and ```REF_Y``` are the j and i (column and row) indices of the reference." ] }, { "cell_type": "code", - "execution_count": 14, + "execution_count": null, "id": "f328e727-7bc2-4451-b9f6-8607bf04db6c", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " REF_LAT 7651400.0\n", - " REF_LON 666920.0\n", - " REF_X 3308\n", - " REF_Y 1435\n" - ] - } - ], + "metadata": { + "tags": [] + }, + "outputs": [], "source": [ "command = 'smallbaselineApp.py ' + str(config_file) + ' --dostep reference_point'\n", "process = subprocess.run(command, stdout=subprocess.PIPE, stderr=subprocess.STDOUT, text=True, shell=True)\n", @@ -601,7 +236,7 @@ "metadata": {}, "source": [ "\n", - "## 2.5 Invert for SBAS Line-of-Sight Timeseries\n", + "## 2.3 Invert for SBAS Line-of-Sight Timeseries\n", "\n", "Run the network inversion to generate the timeseries file.\n", "\n", @@ -610,247 +245,12 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": null, "id": "e410c440-06ce-4565-bac3-a02c5f153fdd", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MintPy version 1.5.1, date 2023-01-03\n", - "--RUN-at-2024-03-22 00:44:21.552387--\n", - "Current directory: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023\n", - "Run routine processing with smallbaselineApp.py on steps: ['invert_network']\n", - "Remaining steps: ['correct_LOD', 'correct_SET', 'correct_troposphere', 'deramp', 'correct_topography', 'residual_RMS', 'reference_date', 'velocity', 'geocode', 'google_earth', 'hdfeos5']\n", - "--------------------------------------------------\n", - "Project name: NorthSlopeEastD102_2023\n", - "Go to work directory: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023\n", - "read custom template file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/MintPy/NorthSlopeEastD102_2023.cfg\n", - "update default template based on input custom template\n", - "No new option value found, skip updating /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg\n", - "read default template file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg\n", - "\n", - "\n", - "******************** step - invert_network ********************\n", - "Input data seems to be geocoded. Lookup file not needed.\n", - "\n", - "ifgram_inversion.py /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5 -t /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg --update\n", - "read input option from template file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg\n", - "use dataset \"unwrapPhase\" by default\n", - "--------------------------------------------------\n", - "update mode: ON\n", - "1) output files already exist: ['timeseries.h5', 'temporalCoherence.h5', 'numInvIfgram.h5'].\n", - "2) output files are NOT newer than input dataset: unwrapPhase.\n", - "run or skip: run.\n", - "save the original settings of ['OMP_NUM_THREADS', 'OPENBLAS_NUM_THREADS', 'MKL_NUM_THREADS', 'NUMEXPR_NUM_THREADS', 'VECLIB_MAXIMUM_THREADS']\n", - "set OMP_NUM_THREADS = 1\n", - "set OPENBLAS_NUM_THREADS = 1\n", - "set MKL_NUM_THREADS = 1\n", - "set NUMEXPR_NUM_THREADS = 1\n", - "set VECLIB_MAXIMUM_THREADS = 1\n", - "reference pixel in y/x: (1435, 3308) from dataset: unwrapPhase\n", - "-------------------------------------------------------------------------------\n", - "least-squares solution with L2 min-norm on: deformation velocity\n", - "minimum redundancy: 1.0\n", - "weight function: var\n", - "calculate covariance: False \n", - "mask: no\n", - "-------------------------------------------------------------------------------\n", - "number of interferograms: 17\n", - "number of acquisitions : 10\n", - "number of lines : 2979\n", - "number of columns : 3671\n", - "--------------------------------------------------\n", - "create HDF5 file: timeseries.h5 with w mode\n", - "create dataset : date of |S8 in size of (10,) with compression = None\n", - "create dataset : bperp of in size of (10,) with compression = None\n", - "create dataset : timeseries of in size of (10, 2979, 3671) with compression = None\n", - "close HDF5 file: timeseries.h5\n", - "--------------------------------------------------\n", - "create HDF5 file: temporalCoherence.h5 with w mode\n", - "create dataset : temporalCoherence of in size of (2979, 3671) with compression = None\n", - "close HDF5 file: temporalCoherence.h5\n", - "--------------------------------------------------\n", - "create HDF5 file: numInvIfgram.h5 with w mode\n", - "create dataset : mask of in size of (2979, 3671) with compression = None\n", - "close HDF5 file: numInvIfgram.h5\n", - "calculating weight from spatial coherence ...\n", - "reading coherence in (0, 0, 3671, 2979) * 17 ...\n", - "convert coherence to weight in chunks of 100000 pixels: 110 chunks in total ...\n", - "convert coherence to weight using inverse of phase variance\n", - " with phase PDF for distributed scatterers from Tough et al. (1995)\n", - " number of independent looks L=41\n", - "chunk 1 / 110\n", - "chunk 2 / 110\n", - "chunk 3 / 110\n", - "chunk 4 / 110\n", - "chunk 5 / 110\n", - "chunk 6 / 110\n", - "chunk 7 / 110\n", - "chunk 8 / 110\n", - "chunk 9 / 110\n", - "chunk 10 / 110\n", - "chunk 11 / 110\n", - "chunk 12 / 110\n", - "chunk 13 / 110\n", - "chunk 14 / 110\n", - "chunk 15 / 110\n", - "chunk 16 / 110\n", - "chunk 17 / 110\n", - "chunk 18 / 110\n", - "chunk 19 / 110\n", - "chunk 20 / 110\n", - "chunk 21 / 110\n", - "chunk 22 / 110\n", - "chunk 23 / 110\n", - "chunk 24 / 110\n", - "chunk 25 / 110\n", - "chunk 26 / 110\n", - "chunk 27 / 110\n", - "chunk 28 / 110\n", - "chunk 29 / 110\n", - "chunk 30 / 110\n", - "chunk 31 / 110\n", - "chunk 32 / 110\n", - "chunk 33 / 110\n", - "chunk 34 / 110\n", - "chunk 35 / 110\n", - "chunk 36 / 110\n", - "chunk 37 / 110\n", - "chunk 38 / 110\n", - "chunk 39 / 110\n", - "chunk 40 / 110\n", - "chunk 41 / 110\n", - "chunk 42 / 110\n", - "chunk 43 / 110\n", - "chunk 44 / 110\n", - "chunk 45 / 110\n", - "chunk 46 / 110\n", - "chunk 47 / 110\n", - "chunk 48 / 110\n", - "chunk 49 / 110\n", - "chunk 50 / 110\n", - "chunk 51 / 110\n", - "chunk 52 / 110\n", - "chunk 53 / 110\n", - "chunk 54 / 110\n", - "chunk 55 / 110\n", - "chunk 56 / 110\n", - "chunk 57 / 110\n", - "chunk 58 / 110\n", - "chunk 59 / 110\n", - "chunk 60 / 110\n", - "chunk 61 / 110\n", - "chunk 62 / 110\n", - "chunk 63 / 110\n", - "chunk 64 / 110\n", - "chunk 65 / 110\n", - "chunk 66 / 110\n", - "chunk 67 / 110\n", - "chunk 68 / 110\n", - "chunk 69 / 110\n", - "chunk 70 / 110\n", - "chunk 71 / 110\n", - "chunk 72 / 110\n", - "chunk 73 / 110\n", - "chunk 74 / 110\n", - "chunk 75 / 110\n", - "chunk 76 / 110\n", - "chunk 77 / 110\n", - "chunk 78 / 110\n", - "chunk 79 / 110\n", - "chunk 80 / 110\n", - "chunk 81 / 110\n", - "chunk 82 / 110\n", - "chunk 83 / 110\n", - "chunk 84 / 110\n", - "chunk 85 / 110\n", - "chunk 86 / 110\n", - "chunk 87 / 110\n", - "chunk 88 / 110\n", - "chunk 89 / 110\n", - "chunk 90 / 110\n", - "chunk 91 / 110\n", - "chunk 92 / 110\n", - "chunk 93 / 110\n", - "chunk 94 / 110\n", - "chunk 95 / 110\n", - "chunk 96 / 110\n", - "chunk 97 / 110\n", - "chunk 98 / 110\n", - "chunk 99 / 110\n", - "chunk 100 / 110\n", - "chunk 101 / 110\n", - "chunk 102 / 110\n", - "chunk 103 / 110\n", - "chunk 104 / 110\n", - "chunk 105 / 110\n", - "chunk 106 / 110\n", - "chunk 107 / 110\n", - "chunk 108 / 110\n", - "chunk 109 / 110\n", - "chunk 110 / 110\n", - "reading unwrapPhase in (0, 0, 3671, 2979) * 17 ...\n", - "use input reference value\n", - "convert zero value in unwrapPhase to NaN (no-data value)\n", - "skip pixels (on the water) with zero value in file: waterMask.h5\n", - "skip pixels with unwrapPhase = NaN in all interferograms\n", - "skip pixels with zero value in file: avgSpatialCoh.h5\n", - "number of pixels to invert: 6853086 out of 10935909 (62.7%)\n", - "estimating time-series via WLS pixel-by-pixel ...\n", - "[==================================================] 6853086/6853086 pixels 1597s / 32s \n", - "converting LOS phase unit from radian to meter\n", - "--------------------------------------------------\n", - "open HDF5 file timeseries.h5 in a mode\n", - "writing dataset /timeseries block: [0, 10, 0, 2979, 0, 3671]\n", - "close HDF5 file timeseries.h5.\n", - "--------------------------------------------------\n", - "open HDF5 file temporalCoherence.h5 in a mode\n", - "writing dataset /temporalCoherence block: [0, 2979, 0, 3671]\n", - "close HDF5 file temporalCoherence.h5.\n", - "--------------------------------------------------\n", - "open HDF5 file numInvIfgram.h5 in a mode\n", - "writing dataset /mask block: [0, 2979, 0, 3671]\n", - "close HDF5 file numInvIfgram.h5.\n", - "--------------------------------------------------\n", - "update values on the reference pixel: (1435, 3308)\n", - "set temporalCoherence on the reference pixel to 1.\n", - "set # of observations on the reference pixel as 17\n", - "roll back to the original settings of ['OMP_NUM_THREADS', 'OPENBLAS_NUM_THREADS', 'MKL_NUM_THREADS', 'NUMEXPR_NUM_THREADS', 'VECLIB_MAXIMUM_THREADS']\n", - "remove env variable OMP_NUM_THREADS\n", - "remove env variable OPENBLAS_NUM_THREADS\n", - "remove env variable MKL_NUM_THREADS\n", - "remove env variable NUMEXPR_NUM_THREADS\n", - "remove env variable VECLIB_MAXIMUM_THREADS\n", - "time used: 27 mins 16.1 secs.\n", - "\n", - "Input data seems to be geocoded. Lookup file not needed.\n", - "\n", - "generate_mask.py /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/temporalCoherence.h5 -m 0.7 -o /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/maskTempCoh.h5\n", - "update mode: ON\n", - "run or skip: run\n", - "input temporalCoherence file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/temporalCoherence.h5\n", - "read /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/temporalCoherence.h5\n", - "create initial mask with the same size as the input file and all = 1\n", - "all pixels with nan value = 0\n", - "exclude pixels with value < 0.7\n", - "delete exsited file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/maskTempCoh.h5\n", - "create HDF5 file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/maskTempCoh.h5 with w mode\n", - "create dataset /mask of bool in size of (2979, 3671) with compression=None\n", - "finished writing to /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/maskTempCoh.h5\n", - "time used: 00 mins 0.1 secs.\n", - "number of reliable pixels: 4633486\n", - "Go back to directory: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023\n", - "\n", - "################################################\n", - " Normal end of smallbaselineApp processing!\n", - "################################################\n", - "Time used: 27 mins 17.2 secs\n", - "\n" - ] - } - ], + "metadata": { + "tags": [] + }, + "outputs": [], "source": [ "command = 'smallbaselineApp.py ' + str(config_file) + ' --dostep invert_network'\n", "process = subprocess.run(command, shell=True)" @@ -886,9 +286,11 @@ }, { "cell_type": "code", - "execution_count": 92, - "id": "de9d9efc-28d0-4ba9-a17f-84e325d913b3", - "metadata": {}, + "execution_count": null, + "id": "27027503-4513-4bf5-97b7-81b7b8a81d20", + "metadata": { + "tags": [] + }, "outputs": [], "source": [ "do_tropo_correction = False\n", @@ -900,15 +302,18 @@ "\n", "if do_tropo_correction:\n", " if not Use_Staged_Data and not os.path.exists(Path.home()/'.cdsapirc'):\n", - " print('NEEDED to download ERA5, link: https://cds.climate.copernicus.eu/user/register')\n", + " print('NEEDED to download ERA5, \\\n", + " link: https://cds.climate.copernicus.eu/user/register')\n", " UID = input('Please type your CDS_UID:')\n", " CDS_API = input('Please type your CDS_API:')\n", " \n", " cds_tmp = '''url: https://cds.climate.copernicus.eu/api/v2\n", " key: {UID}:{CDS_API}'''.format(UID=UID, CDS_API=CDS_API)\n", - " os.system('echo \"{cds_tmp}\" > ~/.cdsapirc; chmod 600 ~/.cdsapirc'.format(cds_tmp = str(cds_tmp)))\n", + " os.system('echo \"{cds_tmp}\" > ~/.cdsapirc; chmod 600 ~/.cdsapirc'\n", + " .format(cds_tmp = str(cds_tmp)))\n", " \n", - " command = 'smallbaselineApp.py ' + str(config_file) + ' --dostep correct_troposphere'\n", + " command = 'smallbaselineApp.py ' + str(config_file) + ' --dostep \\\n", + " correct_troposphere'\n", " process = subprocess.run(command, shell=True)\n", " \n", " # view.main(['inputs/ERA5.h5'])\n", @@ -917,6 +322,18 @@ " timeseries_filename = 'timeseries.h5'" ] }, + { + "cell_type": "markdown", + "id": "ab8f7bad-d66e-4b9e-b5b8-61719af7157e", + "metadata": { + "tags": [] + }, + "source": [ + "
\n", + " Note: The rest of the notebook is using the variable timeseries_filename as InSAR result. Make sure timeseries_filename is set to the correct file\n", + "
" + ] + }, { "cell_type": "markdown", "id": "05c05662-be0b-467a-9c85-e0da83520ac5", @@ -929,40 +346,10 @@ }, { "cell_type": "code", - "execution_count": 66, + "execution_count": null, "id": "fca01319-5d06-45cb-b38e-99b18f5acc44", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MintPy version 1.5.1, date 2023-01-03\n", - "--RUN-at-2024-03-14 21:26:21.379358--\n", - "Current directory: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023\n", - "Run routine processing with smallbaselineApp.py on steps: ['deramp']\n", - "Remaining steps: ['correct_topography', 'residual_RMS', 'reference_date', 'velocity', 'geocode', 'google_earth', 'hdfeos5']\n", - "--------------------------------------------------\n", - "Project name: NorthSlopeEastD102_2023\n", - "Go to work directory: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023\n", - "read custom template file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/MintPy/NorthSlopeEastD102_2023.cfg\n", - "update default template based on input custom template\n", - "No new option value found, skip updating /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg\n", - "read default template file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg\n", - "\n", - "\n", - "******************** step - deramp ********************\n", - "No phase ramp removal.\n", - "Go back to directory: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023\n", - "\n", - "################################################\n", - " Normal end of smallbaselineApp processing!\n", - "################################################\n", - "Time used: 00 mins 0.0 secs\n", - "\n" - ] - } - ], + "outputs": [], "source": [ "command = 'smallbaselineApp.py ' + str(config_file) + ' --dostep deramp'\n", "process = subprocess.run(command, shell=True)" @@ -980,107 +367,10 @@ }, { "cell_type": "code", - "execution_count": 64, + "execution_count": null, "id": "0043acd7-4ab4-47cd-87c6-d1e2e50580eb", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MintPy version 1.5.1, date 2023-01-03\n", - "--RUN-at-2024-03-14 20:53:37.487243--\n", - "Current directory: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023\n", - "Run routine processing with smallbaselineApp.py on steps: ['correct_topography']\n", - "Remaining steps: ['residual_RMS', 'reference_date', 'velocity', 'geocode', 'google_earth', 'hdfeos5']\n", - "--------------------------------------------------\n", - "Project name: NorthSlopeEastD102_2023\n", - "Go to work directory: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023\n", - "read custom template file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/MintPy/NorthSlopeEastD102_2023.cfg\n", - "update default template based on input custom template\n", - "No new option value found, skip updating /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg\n", - "read default template file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg\n", - "\n", - "\n", - "******************** step - correct_topography ********************\n", - "Input data seems to be geocoded. Lookup file not needed.\n", - "\n", - "dem_error.py /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseries_ERA5.h5 -t /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg -o /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseries_ERA5_demErr.h5 --update -g /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/geometryGeo.h5\n", - "read options from template file: smallbaselineApp.cfg\n", - "--------------------------------------------------\n", - "update mode: ON\n", - "1) output file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseries_ERA5_demErr.h5 already exists.\n", - "2) output file is NOT newer than input file: ['/home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseries_ERA5.h5', '/home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/geometryGeo.h5'].\n", - "run or skip: run.\n", - "save the original settings of ['OMP_NUM_THREADS', 'OPENBLAS_NUM_THREADS', 'MKL_NUM_THREADS', 'NUMEXPR_NUM_THREADS', 'VECLIB_MAXIMUM_THREADS']\n", - "set OMP_NUM_THREADS = 1\n", - "set OPENBLAS_NUM_THREADS = 1\n", - "set MKL_NUM_THREADS = 1\n", - "set NUMEXPR_NUM_THREADS = 1\n", - "set VECLIB_MAXIMUM_THREADS = 1\n", - "open timeseries file: timeseries_ERA5.h5\n", - "--------------------------------------------------------------------------------\n", - "correct topographic phase residual (DEM error) (Fattahi & Amelung, 2013, IEEE-TGRS)\n", - "ordinal least squares (OLS) inversion with L2-norm minimization on: phase\n", - "temporal deformation model: polynomial order = 2\n", - "--------------------------------------------------------------------------------\n", - "add/update the following configuration metadata to file:\n", - "['polyOrder', 'phaseVelocity', 'stepFuncDate', 'excludeDate']\n", - "--------------------------------------------------\n", - "create HDF5 file: demErr.h5 with w mode\n", - "create dataset : dem of in size of (832, 475) with compression = None\n", - "close HDF5 file: demErr.h5\n", - "--------------------------------------------------\n", - "grab dataset structure from ref_file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseries_ERA5.h5\n", - "create HDF5 file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseries_ERA5_demErr.h5 with w mode\n", - "create dataset : bperp of float32 in size of (10,) with compression = None\n", - "create dataset : date of |S8 in size of (10,) with compression = None\n", - "create dataset : timeseries of float32 in size of (10, 832, 475) with compression = None\n", - "close HDF5 file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseries_ERA5_demErr.h5\n", - "--------------------------------------------------\n", - "grab dataset structure from ref_file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseries_ERA5.h5\n", - "create HDF5 file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseriesResidual.h5 with w mode\n", - "create dataset : bperp of float32 in size of (10,) with compression = None\n", - "create dataset : date of |S8 in size of (10,) with compression = None\n", - "create dataset : timeseries of float32 in size of (10, 832, 475) with compression = None\n", - "close HDF5 file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseriesResidual.h5\n", - "open geometry file: geometryGeo.h5\n", - "read 2D incidenceAngle, slantRangeDistance from geometry file: geometryGeo.h5\n", - "read mean bperp from timeseries file\n", - "skip pixels with ZERO in ALL acquisitions\n", - "skip pixels with NaN in ANY acquisitions\n", - "skip pixels with ZERO temporal coherence\n", - "skip pixels with ZERO / NaN value in incidenceAngle / slantRangeDistance\n", - "number of pixels to invert: 0 out of 395200 (0.0%)\n", - "--------------------------------------------------\n", - "open HDF5 file demErr.h5 in a mode\n", - "writing dataset /dem block: [0, 832, 0, 475]\n", - "close HDF5 file demErr.h5.\n", - "--------------------------------------------------\n", - "open HDF5 file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseries_ERA5_demErr.h5 in a mode\n", - "writing dataset /timeseries block: [0, 10, 0, 832, 0, 475]\n", - "close HDF5 file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseries_ERA5_demErr.h5.\n", - "--------------------------------------------------\n", - "open HDF5 file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseriesResidual.h5 in a mode\n", - "writing dataset /timeseries block: [0, 10, 0, 832, 0, 475]\n", - "close HDF5 file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseriesResidual.h5.\n", - "roll back to the original settings of ['OMP_NUM_THREADS', 'OPENBLAS_NUM_THREADS', 'MKL_NUM_THREADS', 'NUMEXPR_NUM_THREADS', 'VECLIB_MAXIMUM_THREADS']\n", - "remove env variable OMP_NUM_THREADS\n", - "remove env variable OPENBLAS_NUM_THREADS\n", - "remove env variable MKL_NUM_THREADS\n", - "remove env variable NUMEXPR_NUM_THREADS\n", - "remove env variable VECLIB_MAXIMUM_THREADS\n", - "time used: 00 mins 0.3 secs.\n", - "Go back to directory: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023\n", - "\n", - "################################################\n", - " Normal end of smallbaselineApp processing!\n", - "################################################\n", - "Time used: 00 mins 0.4 secs\n", - "\n" - ] - } - ], + "outputs": [], "source": [ "command = 'smallbaselineApp.py ' + str(config_file) + ' --dostep correct_topography'\n", "process = subprocess.run(command, shell=True)" @@ -1088,305 +378,45 @@ }, { "cell_type": "markdown", - "id": "fd5c3fe6-1867-4b05-a086-e1ab47036460", - "metadata": {}, - "source": [ - "\n", - "# 4. Data noise analysis A: InSAR-only structure fucntions\n", - "\n", - "The NISAR permafrost validation requirement states that at least 80% of the time, the difference in surface displacement for two given points over 90 days should be no greater than $4(1+\\sqrt{\\text{L}})$ mm for points of L km apart, with $\\text{L} \\leq 50$ km.\n" - ] - }, - { - "cell_type": "code", - "execution_count": 56, - "id": "481d32f3-656e-4133-b2e8-374ed70defe0", - "metadata": {}, - "outputs": [], - "source": [ - "#Permafrost requirements:\n", - "dist_th = np.linspace(0.1,50,100) # distances for evaluation (km)\n", - "acpt_error = 4*(1+np.sqrt(dist_th)) # permafrost threshold in mm, for dist in km\n", - "acpt_error_cm = acpt_error/10. #cm" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "9a624d4f-df59-46d6-8969-f14e2d4a60e9", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "#show displacements at end of the timeseries\n", - "if 'timeseries_filename' not in locals():\n", - " timeseries_filename = 'timeseries.h5'\n", - "\n", - "with h5py.File(work_dir/timeseries_filename, 'r') as f:\n", - " dispmap = np.array(f['timeseries'][-1])*100\n", - "\n", - "vmax = np.nanmax(np.abs(dispmap))\n", - "plt.figure()\n", - "plt.imshow(dispmap,vmin=-vmax,vmax=vmax,cmap='RdBu')\n", - "plt.colorbar(label='96 day displacement (cm)')" - ] - }, - { - "cell_type": "markdown", - "id": "4a6c472a-ab64-47d4-96ec-27eaa7a1dfef", - "metadata": {}, - "source": [ - "\n", - "## 4.1 Use structure functions to identify pixel pairs\n", - "\n", - "We sample a large set of pixel pairs to compare relative displacements with. We use a water mask from the Hyp3 processing to mask out locations to not use. Information about how that water mask is developed can [be found here](https://storymaps.arcgis.com/stories/485916be1b1d46889aa436794b5633cb)." - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "22a9ca40-2496-4872-a9bf-2339866bdc01", + "id": "c085d640-9434-426b-93f3-e0f3f053dd1f", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Text(0, 0.5, 'Frequency')" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], "source": [ - "__,atrib = readfile.read(work_dir/timeseries_filename)\n", - "\n", - "X0,Y0 = load_geo_utm(atrib)\n", - "X0_2d,Y0_2d = np.meshgrid(X0,Y0)\n", - "\n", - "M2dist = []; rel_measure = []\n", - "\n", - "tsmap = dispmap\n", - "tsmap[tsmap==0]=np.nan\n", - "\n", - "wmask = pu.get_watermask(hyp3_dir)\n", - "tsmap[wmask==0]=np.nan\n", - "\n", - "#deramping will remove linear spatial trends in the displacement data, currently disabled\n", - "dist_i, rel_measure_i = samp_pair(X0_2d,Y0_2d,tsmap,num_samples=1000000,deramp=False)\n", - "\n", - "M2dist.append(dist_i) #distance of pair, in m\n", - "rel_measure.append(rel_measure_i) #relative displacement of pair, in cm \n", - " \n", - "M2dist,rel_measure = np.array(M2dist),np.array(rel_measure)\n", - "\n", - "#use only pixel pairs within 50 km\n", - "rel_measure = rel_measure[M2dist<=50e3]\n", - "M2dist=M2dist[M2dist<=50e3]\n", - "\n", - "M2km = [i/1e3 for i in M2dist] #convert distance to km\n", - "rmcm = [i for i in rel_measure] #relative measure in cm\n", - "\n", - "fig, ax = plt.subplots(figsize=[9, 5.5])\n", - "img1 = ax.hist(M2km, bins=100)\n", - "ax.set_title(f\"Histogram of distance\")\n", - "ax.set_xlabel(r'Distance ($km$)')\n", - "ax.set_ylabel('Frequency')\n", + "" ] }, { "cell_type": "markdown", - "id": "b1e8a991-2cf1-456e-b769-05af0c00b366", - "metadata": {}, - "source": [ - "\n", - "## 4.2 Compare pair displacements to requirement" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "1b14bb21-1def-4952-9524-24e0c2b51e89", + "id": "a53eff19-7abb-45a1-93be-37f686a4c66a", "metadata": {}, - "outputs": [], "source": [ - "#Here we define a function to help with the plotting in this section.\n", - "\n", - "from matplotlib import cm\n", - "from matplotlib.colors import Normalize \n", - "from scipy.interpolate import interpn\n", + "\n", + "# 4. Validation Method 1: Comparison to ground truth displacements\n", "\n", - "def arraypercentile(arr,p,axis=0,bounds=None):\n", - " \"\"\"for a given array arr, returns the index of where that percentile\n", - " is reached.\"\"\"\n", - " \n", - " if axis==0:\n", - " arr= np.transpose(arr)\n", - " \n", - " ilen,jlen = np.shape(arr)\n", - "\n", - " if bounds==None:\n", - " bounds=[0,ilen]\n", - " boundlen = bounds[1]-bounds[0]\n", - " targets = np.sum(arr,axis=0)*p\n", - " perindex = np.zeros(jlen)\n", - " pervals = np.zeros(jlen)\n", - " \n", - " for j in range(jlen):\n", - " currsum = 0\n", - " curri = -1\n", - " jtarget = targets[j]\n", - " while currsum<=jtarget:\n", - " oldsum=currsum\n", - " curri += 1\n", - " currsum += arr[curri,j]\n", - "\n", - " overfrac = (jtarget-oldsum)/(currsum-oldsum)\n", - " perindex[j] = (curri-1)+overfrac\n", - " pervals[j]=bounds[0]+perindex[j]/ilen*(boundlen)\n", - " return pervals" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "id": "21a2acfc-7295-4f0a-991c-2f749e68bb36", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Requirement success rate: 88.5%\n" - ] - }, - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "#requirements in mm (needs M2dist in km):\n", - "rel_req = 4*(1+np.sqrt(M2dist/1e3)) / 10 #req in cm\n", - "\n", - "n_samples = len(M2dist)\n", - "n_met = np.sum(rel_measure<=rel_req)\n", - "\n", - "print(f'Requirement success rate: {n_met/n_samples*100:.1f}%')\n", - " \n", - "# Color plotted points by density. This is what interpn from scipy is required for.\n", - "# Code inspired by https://stackoverflow.com/questions/20105364/how-can-i-make-a-scatter-plot-colored-by-density-in-matplotlib/53865762#53865762\n", - "x,y = np.array(M2km), np.array(rmcm)\n", - "nbins = 30\n", - "data , x_e, y_e = np.histogram2d(x,y, bins=(nbins,nbins), density = True )\n", - "z = interpn( ( 0.5*(x_e[1:] + x_e[:-1]) , 0.5*(y_e[1:]+y_e[:-1]) ) , data , np.vstack([x,y]).T,\n", - " method = \"linear\",fill_value=None, bounds_error = False)\n", - "\n", - "# Sort the points by density, so that the densest points are plotted last\n", - "idx = z.argsort()\n", - "x, y, z = x[idx], y[idx], z[idx]\n", + "![Survey at Happy Valley East](HappyValleyEast_level.png)\n", + "Photo: Level survey being conducted at Happy Valley East in Sept., 2025. Credit: Andrew Johnson\n", "\n", - "fig, ax = plt.subplots(figsize=[9, 5.5])\n", - "ax.scatter( x, y, c=z,s=1,label='Relative displacement for pixel pair')\n", - "\n", - "ax.set_xlim(0,50)\n", - "ax.set_ylim(0,7)\n", - "norm = Normalize(vmin = np.min(z), vmax = np.max(z))\n", - "cbar = fig.colorbar(cm.ScalarMappable(norm = norm), ax=ax)\n", - "cbar.ax.set_ylabel('Density',fontsize=14)\n", - "ax.plot(dist_th, acpt_error_cm, '--', color='r',label='Permafrost requirement')\n", - "\n", - "#go through data again to make 80th percentile line\n", - "nbins = 70\n", - "data , x_e, y_e = np.histogram2d(x,y, bins=(nbins,nbins), density = True )\n", - "pervec = arraypercentile(data,.8,bounds=[y_e[0],y_e[-1]])\n", - "xmid = [.5*(x_e[i]+x_e[i+1]) for i in range(len(x_e)-1)]\n", - "ax.plot(xmid,pervec,color='C01',label='80th percentile')\n", - "\n", - "ax.set_title(f\"Relative measurements between pixel pairs\")\n", - "ax.set_ylabel(r'Relative measurement ($cm$)')\n", - "ax.set_xlabel('Distance of pair (km)')\n", "\n", - "plt.legend(loc='upper left')\n", "\n", - "out_fig = os.path.abspath('permafrost_insar_vs_distance.png')\n", - "fig.savefig(out_fig, bbox_inches='tight', transparent=True, dpi=300)" - ] - }, - { - "cell_type": "markdown", - "id": "a53eff19-7abb-45a1-93be-37f686a4c66a", - "metadata": {}, - "source": [ - "\n", - "# 5. Validation method B: Comparison to ground truth displacements\n", "\n", - "We can compare the Interferometric displacements to the measured displacements at the field sites. The locations of the field sites are as follows (XY values in UTM, EPSG 32605):\n", + "" ] }, { "cell_type": "code", - "execution_count": 19, + "execution_count": null, "id": "a8d846ac-f1b1-4c50-9ff3-5dd5c0de943b", - "metadata": {}, + "metadata": { + "tags": [] + }, "outputs": [], "source": [ "pointnames = ['HV','HVE','IC','SM']\n", @@ -1401,7 +431,7 @@ "metadata": {}, "source": [ "\n", - "## 5.1 Load field data\n", + "## 4.1 Load field data\n", "\n", "Field observations of summer subsidence were taken for several areas of interest on the North Slope of Alaska, along the Dalton Highway. The ground in this area is snow-free for approximately three months each summer, usually from late May to late August. Measurements from leveling (surveying) and GNSS were taken at the beginning and end of this summer time period. Each field area of interest has 153 sampled points over a 100 m square on the ground.\n", "\n", @@ -1412,13 +442,15 @@ }, { "cell_type": "code", - "execution_count": 20, - "id": "1bb3200f-6807-4a25-abdc-25e238d43ce6", - "metadata": {}, - "outputs": [], - "source": [ - "#Load in observed data\n", - "fielddata_file = work_dir/'fielddata'/'field_results.csv'\n", + "execution_count": null, + "id": "1854b3e7-14b8-4060-bbae-003a88f09026", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "#Load in observed data\n", + "fielddata_file = Path(work_dir)/'field_results.csv'\n", "\n", "obsdata = pd.read_csv(fielddata_file) #ground truth observations\n", "obsdisp = obsdata['rel_change'][:]\n", @@ -1433,8 +465,8 @@ " #use sum of squares to propagate error of subtracted measurements\n", " obsdiffstd[i,j] = np.sqrt(obsstd[i]**2+obsstd[j]**2)\n", " \n", - " date1 = datetime.strptime(str(obsdata['date1'][i]),'%Y%m%d')\n", - " date2 = datetime.strptime(str(obsdata['date2'][i]),'%Y%m%d')\n", + " date1 = dt.strptime(str(obsdata['date1'][i]),'%Y-%m-%d')\n", + " date2 = dt.strptime(str(obsdata['date2'][i]),'%Y-%m-%d')\n", " fielddates.append([date1,date2])" ] }, @@ -1444,448 +476,10 @@ "metadata": {}, "source": [ "\n", - "## 5.2 Prepare InSAR for field comparison\n", - "\n", - "\n", - "In order to perform double differencing of InSAR displacements in a way that will be comparable to the field observations, we run the mintpy inversion several times, with the reference point set to a different field validation site each time, and also using a spline fitting function to fit the InSAR timeseries to the exact dates of the field measurements.\n", + "## 4.2 Prepare InSAR for field comparison\n", "\n", - "**Mintpy subsetting**\n", "\n", - "Below is an example of running Mintpy with a small area subset, using the same reference point." - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "id": "7fb5facd-a542-463d-94b0-5fcbb24ac657", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "___________________________________________________________\n", - "\n", - " /## /## /## /## /#######\n", - " | ### /###|__/ | ## | ##__ ##\n", - " | #### /#### /## /####### /###### | ## \\ ## /## /##\n", - " | ## ##/## ##| ##| ##__ ##|_ ##_/ | #######/| ## | ##\n", - " | ## ###| ##| ##| ## \\ ## | ## | ##____/ | ## | ##\n", - " | ##\\ # | ##| ##| ## | ## | ## /##| ## | ## | ##\n", - " | ## \\/ | ##| ##| ## | ## | ####/| ## | #######\n", - " |__/ |__/|__/|__/ |__/ \\___/ |__/ \\____ ##\n", - " /## | ##\n", - " | ######/\n", - " Miami InSAR Time-series software in Python \\______/\n", - " MintPy 1.5.1, 2023-01-03\n", - "___________________________________________________________\n", - "\n", - "--RUN-at-2024-03-22 23:07:57.364369--\n", - "Current directory: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023\n", - "Run routine processing with smallbaselineApp.py on steps: ['load_data', 'modify_network', 'reference_point', 'quick_overview', 'correct_unwrap_error', 'invert_network', 'correct_LOD', 'correct_SET', 'correct_troposphere', 'deramp', 'correct_topography', 'residual_RMS', 'reference_date', 'velocity', 'geocode', 'google_earth', 'hdfeos5']\n", - "Remaining steps: ['modify_network', 'reference_point', 'quick_overview', 'correct_unwrap_error', 'invert_network', 'correct_LOD', 'correct_SET', 'correct_troposphere', 'deramp', 'correct_topography', 'residual_RMS', 'reference_date', 'velocity', 'geocode', 'google_earth', 'hdfeos5']\n", - "--------------------------------------------------\n", - "Project name: NorthSlopeEastD102_2023\n", - "Go to work directory: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023\n", - "read custom template file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/MintPy/NorthSlopeEastD102_2023.cfg\n", - "update default template based on input custom template\n", - " mintpy.subset.lalo: no --> [7620213:7686754, 641941:679925]\n", - "copy NorthSlopeEastD102_2023.cfg to inputs directory for backup.\n", - "copy smallbaselineApp.cfg to inputs directory for backup.\n", - "copy NorthSlopeEastD102_2023.cfg to pic directory for backup.\n", - "copy smallbaselineApp.cfg to pic directory for backup.\n", - "read default template file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg\n", - "\n", - "\n", - "******************** step - load_data ********************\n", - "\n", - "load_data.py --template /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/MintPy/NorthSlopeEastD102_2023.cfg --project NorthSlopeEastD102_2023\n", - "processor : hyp3\n", - "SAR platform/sensor : unknown from project name \"NorthSlopeEastD102_2023\"\n", - "--------------------------------------------------\n", - "prepare metadata files for hyp3 products\n", - "prep_hyp3.py \"/home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/products/*/*_unw_phase_clipped.tif\"\n", - "prep_hyp3.py \"/home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/products/*/*_corr_clipped.tif\"\n", - "prep_hyp3.py \"/home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/products/*/*_dem_clipped.tif\"\n", - "prep_hyp3.py \"/home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/products/*/*_lv_theta_clipped.tif\"\n", - "prep_hyp3.py \"/home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/products/*/*_lv_phi_clipped.tif\"\n", - "prep_hyp3.py \"/home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/products/*/*_water_mask_clipped.tif\"\n", - "--------------------------------------------------\n", - "updateMode : True\n", - "compression: None\n", - "multilook x/ystep: 1/1\n", - "multilook method : nearest\n", - "input bounding box of interest in lalo: (641941.0, 7686754.0, 679925.0, 7620213.0)\n", - "box to read for datasets in y/x: (2996, 993, 3471, 1825)\n", - "--------------------------------------------------\n", - "searching geometry files info\n", - "input data files:\n", - "height : /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/products/S1AA_20230603T164401_20230615T164402_VVP012_INT80_G_ueF_C9F1/S1AA_20230603T164401_20230615T164402_VVP012_INT80_G_ueF_C9F1_dem_clipped.tif\n", - "incidenceAngle : /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/products/S1AA_20230603T164401_20230615T164402_VVP012_INT80_G_ueF_C9F1/S1AA_20230603T164401_20230615T164402_VVP012_INT80_G_ueF_C9F1_lv_theta_clipped.tif\n", - "azimuthAngle : /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/products/S1AA_20230603T164401_20230615T164402_VVP012_INT80_G_ueF_C9F1/S1AA_20230603T164401_20230615T164402_VVP012_INT80_G_ueF_C9F1_lv_phi_clipped.tif\n", - "waterMask : /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/products/S1AA_20230603T164401_20230615T164402_VVP012_INT80_G_ueF_C9F1/S1AA_20230603T164401_20230615T164402_VVP012_INT80_G_ueF_C9F1_water_mask_clipped.tif\n", - "--------------------------------------------------\n", - "create HDF5 file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/geometryGeo.h5 with w mode\n", - "create dataset /height of in size of (832, 475) with compression = lzf\n", - "create dataset /incidenceAngle of in size of (832, 475) with compression = lzf\n", - " convert incidenceAngle from Gamma (from horizontal in radian) to MintPy (from vertical in degree) convention.\n", - "create dataset /azimuthAngle of in size of (832, 475) with compression = lzf\n", - " convert azimuthAngle from Gamma (from east in radian) to MintPy (from north in degree) convention.\n", - "create dataset /waterMask of in size of (832, 475) with compression = lzf\n", - "prepare slantRangeDistance ...\n", - " geocoded input, use incidenceAngle from file: S1AA_20230603T164401_20230615T164402_VVP012_INT80_G_ueF_C9F1_lv_theta_clipped.tif\n", - " convert incidence angle from Gamma to MintPy convention.\n", - "create dataset /slantRangeDistance of in size of (832, 475) with compression = lzf\n", - "update LENGTH, WIDTH, Y/XMAX\n", - "update/add SUBSET_XMIN/YMIN/XMAX/YMAX: 2996/993/3471/1825\n", - "update Y/X_FIRST\n", - "Finished writing to /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/geometryGeo.h5\n", - "--------------------------------------------------\n", - "searching interferogram pairs info\n", - "input data files:\n", - "unwrapPhase : /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/products/*/*_unw_phase_clipped.tif\n", - "coherence : /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/products/*/*_corr_clipped.tif\n", - "number of unwrapPhase : 17\n", - "number of coherence : 17\n", - "--------------------------------------------------\n", - "create HDF5 file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5 with w mode\n", - "create dataset /unwrapPhase of in size of (17, 832, 475) with compression = None\n", - "[==================================================] 20230907_20230919 5s / 0s \n", - "create dataset /coherence of in size of (17, 832, 475) with compression = None\n", - "[==================================================] 20230907_20230919 4s / 0s \n", - "create dataset /date of in size of (17, 2)\n", - "create dataset /bperp of in size of (17,)\n", - "create dataset /dropIfgram of in size of (17,)\n", - "add extra metadata: {'PROJECT_NAME': 'NorthSlopeEastD102_2023'}\n", - "update metadata due to subset\n", - "update LENGTH, WIDTH, Y/XMAX\n", - "update/add SUBSET_XMIN/YMIN/XMAX/YMAX: 2996/993/3471/1825\n", - "update Y/X_FIRST\n", - "Finished writing to /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5\n", - "--------------------------------------------------\n", - "searching ionosphere pairs info\n", - "input data files:\n", - "WARNING: No data files found for the required dataset: ['unwrapPhase']! Skip loading for ionosphere stack.\n", - "--------------------------------------------------\n", - "searching offset pairs info\n", - "input data files:\n", - "WARNING: No data files found for the required dataset: ['rangeOffset', 'azimuthOffset']! Skip loading for offset stack.\n", - "time used: 00 mins 14.3 secs.\n", - "\n", - "No lookup table (longitude or rangeCoord) found in files.\n", - "Input data seems to be geocoded. Lookup file not needed.\n", - "Loaded dataset are processed by InSAR software: hyp3\n", - "Loaded dataset are in GEO coordinates\n", - "Interferogram Stack: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5\n", - "Geometry File : /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/geometryGeo.h5\n", - "Lookup Table File : None\n", - "--------------------------------------------------\n", - "updating metadata based on custom template file NorthSlopeEastD102_2023.cfg for file: ifgramStack.h5\n", - "updating metadata based on custom template file NorthSlopeEastD102_2023.cfg for file: geometryGeo.h5\n", - "\n", - "\n", - "******************** step - modify_network ********************\n", - "Input data seems to be geocoded. Lookup file not needed.\n", - "generate /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/waterMask.h5 from /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/geometryGeo.h5 for conveniency\n", - "delete exsited file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/waterMask.h5\n", - "create HDF5 file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/waterMask.h5 with w mode\n", - "create dataset /waterMask of bool in size of (832, 475) with compression=None\n", - "finished writing to /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/waterMask.h5\n", - "\n", - "modify_network.py /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5 -t /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg\n", - "read options from template file: smallbaselineApp.cfg\n", - "No lookup table (longitude or rangeCoord) found in files.\n", - "No input option found to remove interferogram\n", - "Keep all interferograms by enable --reset option\n", - "--------------------------------------------------\n", - "reset dataset 'dropIfgram' to True for all interferograms for file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5\n", - "All dropIfgram are already True, no need to reset.\n", - "\n", - "plot_network.py /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5 -t /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg --nodisplay -d coherence -v 0.2 1.0\n", - "read options from template file: smallbaselineApp.cfg\n", - "read temporal/spatial baseline info from file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5\n", - "open ifgramStack file: ifgramStack.h5\n", - "calculating spatial mean of coherence in file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5 ...\n", - "read mask from file: waterMask.h5\n", - "[==================================================] 17/17 0s / 0s\n", - "write average value in space into text file: coherenceSpatialAvg.txt\n", - "number of acquisitions: 10\n", - "number of interferograms: 17\n", - "shift all perp baseline by -85.71686553955078 to zero mean for plotting\n", - "--------------------------------------------------\n", - "number of interferograms marked as drop: 0\n", - "number of interferograms marked as keep: 17\n", - "number of acquisitions marked as drop: 0\n", - "save figure to pbaseHistory.pdf\n", - "save figure to coherenceMatrix.pdf\n", - "save figure to coherenceHistory.pdf\n", - "max perpendicular baseline: 170.70 m\n", - "max temporal baseline: 24.0 days\n", - "showing coherence\n", - "data range: [0.63075197, 0.9469921]\n", - "display range: [0.2, 1.0]\n", - "save figure to network.pdf\n", - "\n", - "\n", - "******************** step - reference_point ********************\n", - "Input data seems to be geocoded. Lookup file not needed.\n", - "\n", - "generate_mask.py /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5 --nonzero -o /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/maskConnComp.h5 --update\n", - "input ifgramStack file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5\n", - "--------------------------------------------------\n", - "update mode: ON\n", - "1) output file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/maskConnComp.h5 already exists.\n", - "2) output file is NOT newer than input dataset: unwrapPhase.\n", - "run or skip: run.\n", - "calculate the common mask of pixels with non-zero unwrapPhase value\n", - "[==================================================] 17/17 0s / 0s\n", - "delete exsited file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/maskConnComp.h5\n", - "create HDF5 file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/maskConnComp.h5 with w mode\n", - "create dataset /mask of bool in size of (832, 475) with compression=None\n", - "finished writing to /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/maskConnComp.h5\n", - "time used: 00 mins 0.1 secs.\n", - "\n", - "temporal_average.py /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5 --dataset coherence -o /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/avgSpatialCoh.h5 --update\n", - "--------------------------------------------------\n", - "update mode: ON\n", - "1) output file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/avgSpatialCoh.h5 already exists.\n", - "2) output file is NOT newer than input dataset: coherence.\n", - "run or skip: run.\n", - "calculate the temporal average of coherence in file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5 ...\n", - "[==================================================] lines 832/832 0s / 0s\n", - "delete exsited file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/avgSpatialCoh.h5\n", - "create HDF5 file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/avgSpatialCoh.h5 with w mode\n", - "create dataset /coherence of float32 in size of (832, 475) with compression=None\n", - "finished writing to /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/avgSpatialCoh.h5\n", - "time used: 00 mins 0.1 secs\n", - "\n", - "Input data seems to be geocoded. Lookup file not needed.\n", - "\n", - "reference_point.py /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5 -t /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg -c /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/avgSpatialCoh.h5\n", - "--------------------------------------------------\n", - "reading reference info from template: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg\n", - "input reference point in lat/lon: (7651392.0, 666923.0)\n", - "input reference point in y/x: (442, 312)\n", - "mask: maskConnComp.h5\n", - "--------------------------------------------------\n", - "calculate the temporal average of unwrapPhase in file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5 ...\n", - "[==================================================] lines 832/832 0s / 0s\n", - "Add/update ref_x/y attribute to file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5\n", - "{'REF_Y': '442', 'REF_X': '312', 'REF_LAT': '7651400.0', 'REF_LON': '666920.0'}\n", - "touch avgSpatialCoh.h5\n", - "touch maskConnComp.h5\n", - "\n", - "\n", - "******************** step - quick_overview ********************\n", - "Input data seems to be geocoded. Lookup file not needed.\n", - "\n", - "temporal_average.py /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5 --dataset unwrapPhase -o /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/avgPhaseVelocity.h5 --update\n", - "--------------------------------------------------\n", - "update mode: ON\n", - "1) output file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/avgPhaseVelocity.h5 already exists.\n", - "2) output file is NOT newer than input dataset: unwrapPhase.\n", - "run or skip: run.\n", - "calculate the temporal average of unwrapPhase in file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5 ...\n", - "[==================================================] lines 832/832 0s / 0s\n", - "delete exsited file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/avgPhaseVelocity.h5\n", - "create HDF5 file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/avgPhaseVelocity.h5 with w mode\n", - "create dataset /velocity of float32 in size of (832, 475) with compression=None\n", - "finished writing to /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/avgPhaseVelocity.h5\n", - "time used: 00 mins 0.1 secs\n", - "\n", - "\n", - "unwrap_error_phase_closure.py /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5 --water-mask /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/waterMask.h5 --action calculate --update\n", - "update mode: ON\n", - "1) output file \"/home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/numTriNonzeroIntAmbiguity.h5\" already exists\n", - "2) output file is NOT newer than input dataset\n", - "3) NOT all key configurations are the same: ['REF_Y', 'REF_X']\n", - "run or skip: run.\n", - "open ifgramStack file: ifgramStack.h5\n", - "number of interferograms: 17\n", - "number of triplets: 8\n", - "calculating the number of triplets with non-zero integer ambiguity of closure phase ...\n", - " block by block with size up to (830, 475), 2 blocks in total\n", - "reference pixel in y/x: (442, 312) from dataset: unwrapPhase\n", - "[==================================================] line 830 / 832 0s / 0s\n", - "mask out pixels with zero in file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/waterMask.h5\n", - "mask out pixels with zero in file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/avgSpatialCoh.h5\n", - "write to file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/numTriNonzeroIntAmbiguity.h5\n", - "delete exsited file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/numTriNonzeroIntAmbiguity.h5\n", - "create HDF5 file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/numTriNonzeroIntAmbiguity.h5 with w mode\n", - "create dataset /mask of float32 in size of (832, 475) with compression=None\n", - "finished writing to /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/numTriNonzeroIntAmbiguity.h5\n", - "plot and save figure to file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/numTriNonzeroIntAmbiguity.png\n", - "time used: 00 mins 1.3 secs\n", - "Done.\n", - "\n", - "\n", - "******************** step - correct_unwrap_error ********************\n", - "phase-unwrapping error correction is OFF.\n", - "\n", - "\n", - "******************** step - invert_network ********************\n", - "Input data seems to be geocoded. Lookup file not needed.\n", - "\n", - "ifgram_inversion.py /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5 -t /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg --update\n", - "read input option from template file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg\n", - "use dataset \"unwrapPhase\" by default\n", - "--------------------------------------------------\n", - "update mode: ON\n", - "1) output files already exist: ['timeseries.h5', 'temporalCoherence.h5', 'numInvIfgram.h5'].\n", - "2) output files are NOT newer than input dataset: unwrapPhase.\n", - "run or skip: run.\n", - "save the original settings of ['OMP_NUM_THREADS', 'OPENBLAS_NUM_THREADS', 'MKL_NUM_THREADS', 'NUMEXPR_NUM_THREADS', 'VECLIB_MAXIMUM_THREADS']\n", - "set OMP_NUM_THREADS = 1\n", - "set OPENBLAS_NUM_THREADS = 1\n", - "set MKL_NUM_THREADS = 1\n", - "set NUMEXPR_NUM_THREADS = 1\n", - "set VECLIB_MAXIMUM_THREADS = 1\n", - "reference pixel in y/x: (442, 312) from dataset: unwrapPhase\n", - "-------------------------------------------------------------------------------\n", - "least-squares solution with L2 min-norm on: deformation velocity\n", - "minimum redundancy: 1.0\n", - "weight function: var\n", - "calculate covariance: False \n", - "mask: no\n", - "-------------------------------------------------------------------------------\n", - "number of interferograms: 17\n", - "number of acquisitions : 10\n", - "number of lines : 832\n", - "number of columns : 475\n", - "--------------------------------------------------\n", - "create HDF5 file: timeseries.h5 with w mode\n", - "create dataset : date of |S8 in size of (10,) with compression = None\n", - "create dataset : bperp of in size of (10,) with compression = None\n", - "create dataset : timeseries of in size of (10, 832, 475) with compression = None\n", - "close HDF5 file: timeseries.h5\n", - "--------------------------------------------------\n", - "create HDF5 file: temporalCoherence.h5 with w mode\n", - "create dataset : temporalCoherence of in size of (832, 475) with compression = None\n", - "close HDF5 file: temporalCoherence.h5\n", - "--------------------------------------------------\n", - "create HDF5 file: numInvIfgram.h5 with w mode\n", - "create dataset : mask of in size of (832, 475) with compression = None\n", - "close HDF5 file: numInvIfgram.h5\n", - "calculating weight from spatial coherence ...\n", - "reading coherence in (0, 0, 475, 832) * 17 ...\n", - "convert coherence to weight in chunks of 100000 pixels: 4 chunks in total ...\n", - "convert coherence to weight using inverse of phase variance\n", - " with phase PDF for distributed scatterers from Tough et al. (1995)\n", - " number of independent looks L=41\n", - "chunk 1 / 4\n", - "chunk 2 / 4\n", - "chunk 3 / 4\n", - "chunk 4 / 4\n", - "reading unwrapPhase in (0, 0, 475, 832) * 17 ...\n", - "use input reference value\n", - "convert zero value in unwrapPhase to NaN (no-data value)\n", - "skip pixels (on the water) with zero value in file: waterMask.h5\n", - "skip pixels with unwrapPhase = NaN in all interferograms\n", - "skip pixels with zero value in file: avgSpatialCoh.h5\n", - "number of pixels to invert: 359143 out of 395200 (90.9%)\n", - "estimating time-series via WLS pixel-by-pixel ...\n", - "[==================================================] 359143/359143 pixels 82s / 1s\n", - "converting LOS phase unit from radian to meter\n", - "--------------------------------------------------\n", - "open HDF5 file timeseries.h5 in a mode\n", - "writing dataset /timeseries block: [0, 10, 0, 832, 0, 475]\n", - "close HDF5 file timeseries.h5.\n", - "--------------------------------------------------\n", - "open HDF5 file temporalCoherence.h5 in a mode\n", - "writing dataset /temporalCoherence block: [0, 832, 0, 475]\n", - "close HDF5 file temporalCoherence.h5.\n", - "--------------------------------------------------\n", - "open HDF5 file numInvIfgram.h5 in a mode\n", - "writing dataset /mask block: [0, 832, 0, 475]\n", - "close HDF5 file numInvIfgram.h5.\n", - "--------------------------------------------------\n", - "update values on the reference pixel: (442, 312)\n", - "set temporalCoherence on the reference pixel to 1.\n", - "set # of observations on the reference pixel as 17\n", - "roll back to the original settings of ['OMP_NUM_THREADS', 'OPENBLAS_NUM_THREADS', 'MKL_NUM_THREADS', 'NUMEXPR_NUM_THREADS', 'VECLIB_MAXIMUM_THREADS']\n", - "remove env variable OMP_NUM_THREADS\n", - "remove env variable OPENBLAS_NUM_THREADS\n", - "remove env variable MKL_NUM_THREADS\n", - "remove env variable NUMEXPR_NUM_THREADS\n", - "remove env variable VECLIB_MAXIMUM_THREADS\n", - "time used: 01 mins 24.9 secs.\n", - "\n", - "Input data seems to be geocoded. Lookup file not needed.\n", - "\n", - "generate_mask.py /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/temporalCoherence.h5 -m 0.7 -o /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/maskTempCoh.h5\n", - "update mode: ON\n", - "run or skip: run\n", - "input temporalCoherence file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/temporalCoherence.h5\n", - "read /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/temporalCoherence.h5\n", - "create initial mask with the same size as the input file and all = 1\n", - "all pixels with nan value = 0\n", - "exclude pixels with value < 0.7\n", - "delete exsited file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/maskTempCoh.h5\n", - "create HDF5 file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/maskTempCoh.h5 with w mode\n", - "create dataset /mask of bool in size of (832, 475) with compression=None\n", - "finished writing to /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/maskTempCoh.h5\n", - "time used: 00 mins 0.0 secs.\n", - "number of reliable pixels: 215460\n", - "\n", - "\n", - "******************** step - correct_LOD ********************\n", - "Input data seems to be geocoded. Lookup file not needed.\n", - "No local oscillator drift correction is needed for Sen.\n", - "\n", - "\n", - "******************** step - correct_SET ********************\n", - "Input data seems to be geocoded. Lookup file not needed.\n", - "No solid Earth tides correction.\n", - "\n", - "\n", - "******************** step - correct_troposphere ********************\n", - "Input data seems to be geocoded. Lookup file not needed.\n", - "Atmospheric correction using Weather Re-analysis dataset (PyAPS, Jolivet et al., 2011)\n", - "Weather Re-analysis dataset: ERA5\n", - "--------------------------------------------\n", - "Use existed tropospheric delay file: ./inputs/ERA5.h5\n", - "\n", - "diff.py /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseries.h5 ./inputs/ERA5.h5 -o /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseries_ERA5.h5 --force\n", - "/home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseries.h5 - ['./inputs/ERA5.h5'] --> /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseries_ERA5.h5\n", - "the 1st input file is: timeseries\n", - "WARNING: ['./inputs/ERA5.h5'] does not contain all dates in /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseries.h5\n", - "Continue and enforce the differencing for their shared dates only.\n", - "\twith following dates are ignored for differencing:\n", - "['20230919', '20230615', '20230709', '20230603', '20230627', '20230907', '20230721', '20230814', '20230826', '20230802']\n", - "--------------------------------------------------\n", - "grab metadata from ref_file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseries.h5\n", - "grab dataset structure from ref_file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseries.h5\n", - "create HDF5 file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseries_ERA5.h5 with w mode\n", - "create dataset : bperp of float32 in size of (10,) with compression = None\n", - "create dataset : date of |S8 in size of (10,) with compression = None\n", - "create dataset : timeseries of float32 in size of (10, 832, 475) with compression = None\n", - "close HDF5 file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseries_ERA5.h5\n", - "Traceback (most recent call last):\n", - " File \"/home/jovyan/.local/envs/insar_analysis/bin/smallbaselineApp.py\", line 10, in \n", - " sys.exit(main())\n", - " File \"/home/jovyan/.local/envs/insar_analysis/lib/python3.8/site-packages/mintpy/cli/smallbaselineApp.py\", line 208, in main\n", - " run_smallbaselineApp(inps)\n", - " File \"/home/jovyan/.local/envs/insar_analysis/lib/python3.8/site-packages/mintpy/smallbaselineApp.py\", line 1117, in run_smallbaselineApp\n", - " app.run(steps=inps.runSteps)\n", - " File \"/home/jovyan/.local/envs/insar_analysis/lib/python3.8/site-packages/mintpy/smallbaselineApp.py\", line 898, in run\n", - " self.run_tropospheric_delay_correction(sname)\n", - " File \"/home/jovyan/.local/envs/insar_analysis/lib/python3.8/site-packages/mintpy/smallbaselineApp.py\", line 642, in run_tropospheric_delay_correction\n", - " mintpy.cli.diff.main(iargs)\n", - " File \"/home/jovyan/.local/envs/insar_analysis/lib/python3.8/site-packages/mintpy/cli/diff.py\", line 81, in main\n", - " diff_file(\n", - " File \"/home/jovyan/.local/envs/insar_analysis/lib/python3.8/site-packages/mintpy/diff.py\", line 119, in diff_file\n", - " ref_val = readfile.read(file2[0],\n", - " File \"/home/jovyan/.local/envs/insar_analysis/lib/python3.8/site-packages/mintpy/utils/readfile.py\", line 276, in read\n", - " dsname4atr = datasetName[0].split('-')[0]\n", - "IndexError: list index out of range\n" - ] - } - ], - "source": [ - "subsetstr = '[7620213:7686754, 641941:679925]'\n", - "writenumpyconfig(config_file,hyp3_dir,reflalo=sites[site]['mintpy_ref_loc'],subset = subsetstr)\n", - "!smallbaselineApp.py --dir {work_dir} {config_file}" + "In order to perform double differencing of InSAR displacements in a way that will be comparable to the field observations, we run the mintpy inversion several times, with the reference point set to a different field validation site each time, and also using a spline fitting function to fit the InSAR timeseries to the exact dates of the field measurements.\n" ] }, { @@ -1893,30 +487,21 @@ "id": "202ab2d3-43b3-40b3-aceb-b87c5d89594e", "metadata": {}, "source": [ - "**Time series reconstruction**\n", + "### 4.2.1 Perform timeseries reconstruction\n", "\n", "The displacement time series from mintpy is reconstruted here by spline-fitting it the time series to a set of basis functions, following Zwieback et al. (2020). The basis functions represent typical summer permafrost surface subsidence patterns, due melting ice in the active layer. The spline fitting reconstruction both reduces the noise from individual acquisitions, and also allows us to identify the InSAR displacement for arbitrary dates within the period.\n" ] }, { "cell_type": "code", - "execution_count": 22, + "execution_count": null, "id": "05af50d9-daa5-4afa-9213-d7fcc73fb637", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "metadata": { + "tags": [] + }, + "outputs": [], "source": [ - "ts = pu.Timeseries.from_file(fn = work_dir/timeseries_filename)\n", + "ts = pu.Timeseries.from_file(fn = Path(mintpy_dir)/timeseries_filename)\n", "sm = pu.SplineModel(dates_o=ts.dates)\n", "\n", "#perform the reconstruction\n", @@ -1936,38 +521,20 @@ }, { "cell_type": "code", - "execution_count": 55, + "execution_count": null, "id": "64c82a84-3540-4a7c-b5f3-1b5da0f30049", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 55, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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FJkGHDx8mOjoat9uN2+0mOjqaI0eOFHmMMYZJkyYRERFB7dq16dOnD5s2bcpTJj09nQceeIDGjRtTp04dBg8ezO7du737d+7cyR133EGrVq2oXbs2rVu3ZuLEiWRkZFRENZ1n36bTNhjABcum2hGNiIhImVRoEjRixAji4+OJjY0lNjaW+Ph4oqOjizzm2WefZdq0aUyfPp3Vq1cTFhZG3759SU1N9ZaJiYlhwYIFzJs3jx9++IGjR48ycOBAsrOzAdi6dSs5OTm8/vrrbNq0iRdeeIHXXnuNJ554oiKr6xwHtxew0cDBXys9FBERkbJyGWNMRbzwli1biIyMJC4uju7duwMQFxdHVFQUW7dupW3btvmOMcYQERFBTEwMjz32GGD1+oSGhjJ16lTuvvtuPB4PTZo0Yfbs2QwbNgyAvXv30qxZMz7//HOuuuqqAuP517/+xYwZM/jtt99KFH9KSgputxuPx0O9evXK0gQ114we1iUwTjt1Gp0DD6yxJSQREREo3d/vCusJWrFiBW6325sAAVx88cW43W5+/PHHAo9JSEggKSmJfv36ebcFBATQu3dv7zFr164lMzMzT5mIiAg6dOhQ6OsCeDweGjZsWOj+9PR0UlJS8jykEL0fx3sJ7FTHD4Fnjx0RiYiIlFqFJUFJSUmEhITk2x4SEkJSUlKhxwCEhobm2R4aGurdl5SUhL+/Pw0aNCi0zOl27NjBK6+8wj333FNovFOmTPGOXXK73TRr1qzwyjld5GAYOhtCzwO/AGjSHuqGw4mDMOd6KxkSERGp4kqdBE2aNAmXy1XkY80a65KIy+XKd7wxpsDtpzp9f0mOKazM3r176d+/PzfddBN33nlnocdPmDABj8fjfezatavI93O8yMEwdjn8NRnui4M7l0JwBOzfCu8Ng4xjdkcoIiJSJL/SHnD//fczfPjwIsu0bNmSDRs2sG/fvnz79u/fn6+nJ1dYWBhg9faEh4d7tycnJ3uPCQsLIyMjg8OHD+fpDUpOTqZHjx55Xm/v3r1cdtllREVF8cYbbxQZc0BAAAEBAUWWkSLUb2Ytr/F2f9i9Cj4cBTe/D7617I5MRESkQKXuCWrcuDHt2rUr8hEYGEhUVBQej4dVq1Z5j125ciUejydfspKrVatWhIWFsXTpUu+2jIwMli1b5j2mS5cu1KpVK0+ZxMRENm7cmOd19+zZQ58+fejcuTPvvPMOPj6aEqnChbS3ltfwqw3bl8Kn92l5DRERqbIqLDNo3749/fv3Z8yYMcTFxREXF8eYMWMYOHBgnjvD2rVrx4IFCwDrMlhMTAxPP/00CxYsYOPGjYwePZqgoCBGjBgBgNvt5o477uDhhx/m66+/Zv369YwcOZLzzz+fK6+8ErB6gPr06UOzZs147rnn2L9/P0lJSYWOGZJy1KzbKctrfABL/goVcwOiiIjIGSn15bDSmDt3LuPGjfPeyTV48GCmT5+ep8y2bdvweDze5+PHj+fEiRPce++9HD58mO7du7NkyRKCg4O9ZV544QX8/PwYOnQoJ06c4IorrmDmzJn4+voCsGTJErZv38727dtp2rRpnveroBkB5FTn9oNrX4UFd0Pcv6FuE+j5f3ZHJSIikkeFzRNU3WmeoHKw4t/w5Z8TVA5+BTrfam88IiJS41WJeYJEiLrvZA/Qogdhy2J74xERETmFkiCpWFdMhE4jweTAx7fDzuV2RyQiIgIoCZKK5nLBwJeg7QDITof3b4akn+2OSkREREmQVAJfP7jxbWjeA9I9MOcGOJRgd1QiIuJwSoKkctSqbU2eGNoBju6D2dfB0WS7oxIREQdTEiSVp3Z9GDkf6reAwwlWj1CaFqoVERF7KAmSyhUcBtELoE4TSNoA80ZAZprdUYmIiAMpCZLK16g13PIx+AfDzu/hkzshJ9vuqERExGGUBIk9IjrCze+Brz9sWQSfPaTlNUREpFIpCRL7tOoFN/wHcMHamfDtU3ZHJCIiDqIkSOwVOQQGTrO+/9+/YOXr9sYjIiKOoSRI7Nf1drjsr9b3X4yHnz+2Nx4REXEEJUFSNfR6BLrdZX2/4G7Y/pW98YiISI2nJEiqBpcL+k+FDjdAThZ8cCvsXmt3VCIiUoMpCZKqw8cHrn0NWl8Omcdg7o2w/xe7oxIRkRpKSZBULX7+MHQ2nNUFThyyltfw7LE7KhERqYGUBEnVE1AXRnwEjc6BlN1WInT8kN1RiYhIDaMkSKqmOo0g+hMIjoAD2+C9oZBxzO6oRESkBlESJFVX/eZWIhRYH3avhg9HQXam3VGJiEgNoSRIqraQ9nDLR+BXG7YvhU/vg5wcu6MSEZEaQEmQVH3NusHQWeDyhQ0fwJK/aJ0xERE5Y0qCpHo4tx9c+6r1fdyr8MML9sZTxWTnGFbsOMin8XtYseMg2TlKEkVEiuNndwAiJXbhcDh+EL58Ar6eDHUaQ+db7Y7KdrEbE5m8aDOJnjTvtnB3IBMHRdK/Q7iNkYmIVG3qCZLqJeo+uCTG+n7Rg7Blsa3h2C12YyJj56zLkwABJHnSGDtnHbEbE22KTESk6lMSJNXPlZOg00gwOfDx7bBzud0R2SI7xzB50WYKuvCVu23yos26NCYiUgglQVL9uFww8CVoOwCy0+H9myHpZ7ujqnSrEg7l6wE6lQESPWmsStBEkyIiBVESJNWTrx/c+DY07wHpHphzAxxKsDuqSpWcWngCVJZyIiJOoyRIqq9ateHm9yG0AxzdZy2vcTTZ7qgqTUhwYLmWExFxGiVBUr3Vrg8j51uzSx9OsHqE0lLsjqpSdGvVkHB3IK5C9ruw7hLr1qphZYYlIlJtKAmS6i84DKL/C3WaQNIGmDcCMmv+JSBfHxcTB0UC5EuEcp9PHBSJr09haZKIiLMpCZKaoVFruOVj8A+Gnd/DJ3dCTrbdUVW4/h3CmTGyM2HuvJe8wtyBzBjZWfMEiYgUwWWM1h8oSEpKCm63G4/HQ7169ewOR0oq4X/WJbHsDOgyGga+aN1NVsNl5xhWJRwiOTWNkGDrEph6gETEiUrz91szRkvN0qoX3PAfa8X5tTOtS2SX/9XuqCqcr4+LqNaN7A5DRKRa0eUwqXkih8DAadb3//sXrHzd3nhERKRKUhIkNVPX2+GyP3uAvhgPP39sbzwiIlLlKAmSmqvXI9DtLuv7BXfD9q/sjUdERKoUJUFSc7lc0H8qdLgBcrLgg1th91q7oxIRkSpCSZDUbD4+cO1r0PpyyDwGc2+E/b/YHZWIiFQBSoKk5vPzh6GzIaIznDhkLa/h2WN3VCIiYjMlQeIMAXXhlo+g0TmQsttKhI5rdXURESdTEiTOUacxRH8CwRFwYBu8NxQyjtkdlYiI2ESTJYqz1G9uJUJv94fdq62vOVlwaAc0agO9H4fIwXZHKSIilUA9QeI8Ie2tS2M+/taCq8mbISsd9m2GD6Nh80K7IxQRkUqgJEicqVk3qBd22kYDuGDZVDsiEhGRSqYkSJzr6L4CNho4+GulhyIiIpVPSZA4V6M2QAErrddvWdmRiIiIDZQEiXP1fhzvJbBTpeyBncvtiEhERCpRhSZBhw8fJjo6GrfbjdvtJjo6miNHjhR5jDGGSZMmERERQe3atenTpw+bNm3KUyY9PZ0HHniAxo0bU6dOHQYPHszu3bsLfL309HQ6duyIy+UiPj6+nGomNULkYLJvmsWxBu3I9vHnuLsNpkFLyDgKswbD2pl2RygiIhWoQpOgESNGEB8fT2xsLLGxscTHxxMdHV3kMc8++yzTpk1j+vTprF69mrCwMPr27Utqaqq3TExMDAsWLGDevHn88MMPHD16lIEDB5KdnZ3v9caPH09ERES5102qv9iNifRcWJfzEv9G6+Mzidz3dy47NoXEpgOs2+YXPQifPwrZWXaHKiIiFcBljDEV8cJbtmwhMjKSuLg4unfvDkBcXBxRUVFs3bqVtm3b5jvGGENERAQxMTE89thjgNWTExoaytSpU7n77rvxeDw0adKE2bNnM2zYMAD27t1Ls2bN+Pzzz7nqqqu8r/fFF1/w0EMPMX/+fM477zzWr19Px44dSxR/SkoKbrcbj8dDvXr1zrA1pKqJ3ZjI2DnrOP3kty6MGb7ssppzN71obWzVG26aCUENKzNEEREpg9L8/a6wnqAVK1bgdru9CRDAxRdfjNvt5scffyzwmISEBJKSkujXr593W0BAAL179/Yes3btWjIzM/OUiYiIoEOHDnled9++fYwZM4bZs2cTFBRUbLzp6emkpKTkeUjNlJ1jmLxoc74ECPhzm4tR23uRPXQO1KoDCcvgP1fA/m2VG6iIiFSoCkuCkpKSCAkJybc9JCSEpKSkQo8BCA0NzbM9NDTUuy8pKQl/f38aNGhQaBljDKNHj+aee+6ha9euJYp3ypQp3rFLbrebZs2aleg4qX5WJRwi0ZNW6H4DJHrSWBXQA+5YAu7mcOg3ePMK+GVJ5QUqIiIVqtRJ0KRJk3C5XEU+1qxZA4DLlf/2Y2NMgdtPdfr+khxzaplXXnmFlJQUJkyYUOJ6TZgwAY/H433s2rWrxMdK9ZKcWngClK9cWAe461tocQlkpFrrjS1/CSrmKrKIVIDsHMOKHQf5NH4PK3YcJDtHP79iKfXaYffffz/Dhw8vskzLli3ZsGED+/bln4xu//79+Xp6coWFWTP4JiUlER4e7t2enJzsPSYsLIyMjAwOHz6cpzcoOTmZHj16APDNN98QFxdHQEBAntfv2rUrt9xyC++++26+9w4ICMhXXmqmkODA0pWr0xii/wtfPGrdMbb0SWuJjUEvQa2SvZaI2CN2YyKTF23O0/sb7g5k4qBI+ncIL+JIcYJS9wQ1btyYdu3aFfkIDAwkKioKj8fDqlWrvMeuXLkSj8fjTVZO16pVK8LCwli6dKl3W0ZGBsuWLfMe06VLF2rVqpWnTGJiIhs3bvSWefnll/npp5+Ij48nPj6ezz//HIAPPviAp556qrRVlhqmW6uGhLsDC5omEbAGR4e7A+nW6pSB0H7+MPBFuPpf4PKFDfNg5jWQWvClXRGxX+4NEKdf/k7ypDF2zjpiNybaFJlUFRU2Jqh9+/b079+fMWPGEBcXR1xcHGPGjGHgwIF57gxr164dCxYsAKzLYDExMTz99NMsWLCAjRs3Mnr0aIKCghgxYgQAbrebO+64g4cffpivv/6a9evXM3LkSM4//3yuvPJKAJo3b06HDh28j3PPPReA1q1b07Rp04qqslQTvj4uJg6KBPLPF537fOKgSHx9TtvrckH3u6xV6APrw5418MZlsGddRYcsIqVU/A0QMHnRZl0ac7gKnSdo7ty5nH/++fTr149+/fpxwQUXMHv27Dxltm3bhsfj8T4fP348MTEx3HvvvXTt2pU9e/awZMkSgoODvWVeeOEFrr32WoYOHcoll1xCUFAQixYtwtfXtyKrIzVI/w7hzBjZmTB33stZYe5AZozsXHQ3+dl9YMw30LgtpO6Fd66Gnz+u2IBFpFRKfANEwqHKC0qqnAqbJ6i60zxBzpCdY1iVcIjk1DRCgq1LYPl6gAqT5oH5d8Kvf94xdunDcNlfwUer0YjY7dP4PTw4L77Yci8N78iQjmdVfEBSaUrz97vUA6NFahJfHxdRrRuV7eBAN9w8D76ebN0x9v3zkLwVrn8dAoKLP15EKkypb4AQR9K/rCJnwscX+v4drnsdfANg22fwVj84vNPuyEQcrUw3QIjjKAkSKQ8XDofbPoe6oZC82RowvfMHu6MScawy3wAhjqIkSKS8NO0KY76F8I5w4hDMGgJr3rY7KhHHOqMbIMQRNDC6EBoYLWWWeQI+vQ82zreeXzQG+k8B31r2xiXiUGd0A4RUOxoYLWKnWrXhhrcgJBK++QesfhMObIOb3tVK9CI2OKMbIKRG0+UwkYrgckGvR2D4e+BfFxL+B29ebt09JiIiVYKSIJGK1O4aayX6+s3hcAL850r45Uu7oxIREZQEiVS80PNgzHfQouefK9EPgx9e1Er0IiI2UxIkUhnqNILoBdDlNsDAVxNhwT2QWfi0/iIiUrGUBIlUFj9/GPQiDHjulJXoB2glehERmygJEqls3cZYvUK1G8CetfBGH61ELyJiAyVBInY4u7e1En2TdpCaqJXoRURsoCRIxC4Nz4Y7lsK5/SErDebfAV//HXJy7I5MRMQRlASJ2CmwnjWX0CUx1vPvn4cPboH0VFvDEhFxAiVBInbz8YW+k+H6N/9cif5zrUQvIlIJlASJVBUXDIXbvoC6YSdXok/43u6oRERqLCVBIlVJ0y5w17cQ0claiX72tbD6LbujEhGpkZQEiVQ19SKsHqHzb4KcLPjsIfjsYcjOtDsyEZEaRUmQSFVUq7Y1RuiKiYALVv8HZl8Hxw/ZHZmISI2hJEikqnK54NKH4Ob3rZXod34Pb14GyVvsjkxEpEZQEiRS1bW9Gu78Chq0tO4Y+09f2BZrd1QVIjvHsGLHQT6N38OKHQfJztEisyJScVzGaCnrgqSkpOB2u/F4PNSrV8/ucESsS2Ef3mr1COGCKyda8wu5XHZHVi5iNyYyedFmEj0nF5UNdwcycVAk/TuE2xiZiFQnpfn7rZ4gkeoiqKG15ljXO7BWop8En9wFmSfsjuyMxW5MZOycdXkSIIAkTxpj56wjdmOiTZGJSE2mJEikOvGtBQOnwTXPg48f/PwhvDMAUqpvkpCdY5i8aDMFdUnnbpu8aLMujYlIufOzOwARKYOL7oTG51qXx/aug1cvtnqKUvZAozbQ+3GIHGx3lCWyKuFQvh6gUxkg0ZPGqoRDRLVuVHmBiUiNp54gkeqqVS8Y8y3UOwvSjsCh3yArHfZthg+jYfNCuyMskeTUwhOgspQTESkpJUEi1VnDVhBw+sA/A7jguyl2RFRqIcGB5VpORKSklASJVHeHfytgo7HWH/tuKhw7WOkhlUa3Vg0JdwdS2D1uLqy7xLq1aliZYYmIAygJEqnuGrWBwlKI756GF86DxQ/BwR2VGlZJ+fq4mDgoEshfi9znEwdF4utTM6YCEJGqQ0mQSHXX+3G8l8Dg5Neo+yC8I2SdgDVvwStdYN4t8MdKe+IsQv8O4cwY2Zkwd95LXmHuQGaM7Kx5gkSkQmiyxEJoskSpVjYvhGVT4eCv0Ogc6PM4tB8ExsDvy+HHV+CXU2aZbnoR9HgA2g0EH1/74j5Ndo5hVcIhklPTCAm2LoGpB0hESqM0f7+VBBVCSZDUOPu3wYrp8NM8yM6wtjVoCVH3Q8cR4F/H1vBERMqDkqByoCRIaqyjybDqTVj9Jpw4bG2r3cCae6jbXVA3xN74RETOgJKgcqAkSGq8jGMQ/x6s+DccTrC2+frDhcOt3qEmbe2NT0SkDJQElQMlQeIYOdmw9TP48WXYvfrk9nP7W+OGWlxSYxZpFZGaT0lQOVASJI70x0orGdr6Gd6Vu8I7WslQ5LXgq5V2RKRqUxJUDpQEiaMd3AFxr8L6udYt9gDu5nDxWOgcDQHB9sYnIlIIJUHlQEmQCNZs02vegpWvw/ED1rYAN3S9DbrfDfUi7I1PROQ0SoLKgZIgkVNknoANH8CP0625iAB8asH5N0GP+yH0PHvjExH5k5KgcqAkSKQAOTnw65fW5Iu/Lz+5vfUV1rihs/toELWI2EpJUDlQEiRSjN1rYcUrsPlTMDnWttAOVjJ03vXg529vfCLiSEqCyoGSIJESOrwT4l6DdbMg85i1LTgCLr4HuoyGQLed0YmIwygJKgdKgkRK6cRhWPOONYj6aJK1zT8YuoyC7vdA/Wb2xicijqAkqBwoCRIpo6x0+Plja9zQ/i3WNpcvdLjemok6oqOt4YlIzaYkqBwoCRI5Q8bA9q+tyRcTlp3c3qoX9BgHba7UIGoRKXdKgsqBkiCRcpT4k3V7/cb5YLKtbU3aWT1DFwwFvwB74xORGkNJUDlQEiRSATy7IW4GrH0XMlKtbXVDrdXru94OO3+AZc/Awe3QqA30fhwiB9sbs4hUK6X5++1TkYEcPnyY6Oho3G43breb6Ohojhw5UuQxxhgmTZpEREQEtWvXpk+fPmzatClPmfT0dB544AEaN25MnTp1GDx4MLt37873Wp999hndu3endu3aNG7cmOuvv748qycipeVuClc9BQ9tgn7/hHpnwdF98M0/4Pm28GE07NtsjSvat9l6vnmh3VGLSA1VoUnQiBEjiI+PJzY2ltjYWOLj44mOji7ymGeffZZp06Yxffp0Vq9eTVhYGH379iU1NdVbJiYmhgULFjBv3jx++OEHjh49ysCBA8nOzvaWmT9/PtHR0dx222389NNPLF++nBEjRlRYXUWkFALd1nxCD/4E178JYedDdsafO80pX12wbKpNQYpITVdhl8O2bNlCZGQkcXFxdO/eHYC4uDiioqLYunUrbdu2zXeMMYaIiAhiYmJ47LHHAKvXJzQ0lKlTp3L33Xfj8Xho0qQJs2fPZtiwYQDs3buXZs2a8fnnn3PVVVeRlZVFy5YtmTx5MnfccUeZ4tflMJFKZAz8ownkZBaw0wWX/QXOvcpKljSYWkSKUCUuh61YsQK32+1NgAAuvvhi3G43P/74Y4HHJCQkkJSURL9+/bzbAgIC6N27t/eYtWvXkpmZmadMREQEHTp08JZZt24de/bswcfHh06dOhEeHs7VV1+d77LaqdLT00lJScnzEJFK4nJBk3OBghIcA9/+E16/FKZFwqIHYevnkHGssqMUkRqmwpKgpKQkQkJC8m0PCQkhKSmp0GMAQkND82wPDQ317ktKSsLf358GDRoUWua3334DYNKkSfz1r39l8eLFNGjQgN69e3Po0KEC33vKlCnesUtut5tmzTSxm0il6v043ktgcPJr19uh7QCoFQSpe2HtTJh3M0xtBXNugJVvWLNWi4iUUqmToEmTJuFyuYp8rFmzBgBXAd3WxpgCt5/q9P0lOebUMjk51jpGf/nLX7jhhhvo0qUL77zzDi6Xi48++qjA4ydMmIDH4/E+du3aVeT7iUg5ixwMQ2dbK9L7BVhfh82BgS/Aze/D+AQYOd+6k6x+C8hOh+1fwRePwksXwr+7w9InYedyyM6yuzYiUg34lfaA+++/n+HDhxdZpmXLlmzYsIF9+/bl27d///58PT25wsLCAKu3Jzw83Ls9OTnZe0xYWBgZGRkcPnw4T29QcnIyPXr0APAeGxkZ6d0fEBDA2WefzR9//FHgewcEBBAQoLlKRGwVObjwW+JrBVoTLLa5Eq5+FvZvs1a0/2UJ/LEC9m+1HstfsgZet7kSzrnK+lqnUeXWQ0SqhVInQY0bN6Zx48bFlouKisLj8bBq1Sq6desGwMqVK/F4PN5k5XStWrUiLCyMpUuX0qlTJwAyMjJYtmwZU6dad4h06dKFWrVqsXTpUoYOHQpAYmIiGzdu5Nlnn/WWCQgIYNu2bfTs2ROAzMxMdu7cSYsWLUpbZRGpalwuCGlnPS550Fq3bMc38MuX8OtSOHHImphx43xw+UDTi+CcfnBuf6uHSYOrRYQKnizx6quvZu/evbz++usA3HXXXbRo0YJFixZ5y7Rr144pU6Zw3XXXATB16lSmTJnCO++8wznnnMPTTz/Nd999x7Zt2wgODgZg7NixLF68mJkzZ9KwYUMeeeQRDh48yNq1a/H19QWs2+g//vhj3n77bVq0aMG//vUvFi1axNatW/ONJyqI7g4TqaZysmH3mj97ib6EfRvz7q/XFM7tZ/USteoF/kH2xCkiFaI0f79L3RNUGnPnzmXcuHHeO7kGDx7M9OnT85TZtm0bHo/H+3z8+PGcOHGCe++9l8OHD9O9e3eWLFniTYAAXnjhBfz8/Bg6dCgnTpzgiiuuYObMmd4ECOBf//oXfn5+REdHc+LECbp3784333xTogRIRKoxH19o3t16XPGkNUv1r0ushOi3ZZCyG9a8bT38Aq1E6Jx+1i349ZvbHb2IVCItm1EI9QSJ1ECZJyDh+5O9RJ7TboAIibSSoXOusi6h+Vbo/4kiUgG0dlg5UBIkUsMZA8lbTiZEu1aCyTm5P7A+nNP3z8HVV0BQQ9tCFZGSUxJUDpQEiTjM8UOw/WsrKfp1KaQdObnP5QPNup8cXB3SXoOrRaooJUHlQEmQiINlZ8Hu1Sd7iZI3593vbnbyslmrS6FWbXviFJF8lASVAyVBIuJ15I8/b79fAgn/g6y0k/v8asPZvU8OrnY3tVa+X/YMHNwOjdpYs2EXNv+RiJQrJUHlQEmQiBQo47iVCP0SayVFKXvy7nc3+3PAtYuTy4AYazZsJUIiFU5JUDlQEiQixTIG9m06mRDtWoWV+JzOZU3SOHZ5ZUco4jhVYhV5EZEaz+WCsA7Q6xG4Ywk8ugN8Crqt/s9kac3bkOYpYL+I2EFJkIhIeanTCJq0xboEdjoDi/8PnmsLn9xlzVeUk1NAORGpLEqCRETKU+/HOTkWiJNfLxwBjdtC1gnY8AG8OxBe6QT/+xd49hTyYiJSkTQmqBAaEyQiZbZ5ISybCgd/hUbnQJ/Hof0gawzRnrWwbhZs/AQyUq3yLh9ofTl0ioa2V4NfgL3xi1RjGhhdDpQEiUiFyjgGmz+F9XPg91MGTNduCBcOh04jrcHUIlIqSoLKgZIgEak0B3dYyVD8e3A06eT2iE5W71CHG6B2fdvCE6lOlASVAyVBIlLpsrNgx9ewfjZs+wJysqztfoEQOcTqHWrRE3w0nFOkMEqCyoGSIBGx1dH91gDq9bNh/9aT2xu0hI4joePN1uzUIpKHkqByoCRIRKqE3MHU62fDz/NPDqbGZa1u32kktB2gwdQif1ISVA6UBIlIlZNxzLrzbP0c+P2Hk9trN4QLhlkJUVgH++ITqQKUBJUDJUEiUqUd3AHxc63B1KmJJ7dHdLKSoQ43ajC1OJKSoHKgJEhEqoXsLNjxzSmDqTOt7X6B0H6wlRC1vFSDqcUxlASVAyVBIlLtHDtgDaZeNxv2bzm5vX4LKxnqOEKDqaXGUxJUDpQEiUi1ZQzsWWf1Dm2cD+kpf+5w/Tkz9Uhod40GU0uNpCSoHCgJEpEaIeM4bFlo9Q7lGUzd4M/B1NEaTC01ipKgcqAkSERqnIM7rIHU8e9B6t6T28M7Wr1D59+kwdRS7SkJKgdKgkSkxsrJtgZTr5tVwGDqQVbvUMtLYetiWPYMHNwOjdpA78chcrC9sYsUQ0lQOVASJCKOcOwAbPjQGj+UvPnk9qDGcPwA4ALMya9DZysRkiqtNH+/dc+kiIiT1WkMUffC2B9hzDfQ5TYIqPdnAgRWApT71QXLptoUqEj5UxIkIiLgcsFZXWDQi/DwNvDxK6CQgQO/VnZkIhVGSZCIiOTlHwRN2mJdAjuNjy8c3lnZEYlUCCVBIiKSX+/HOTkWiJNfM4/DjEusW+41pFSqOSVBIiKSX+RgaxB06HnWpIqh58E106B5FGQchYX3w7wRcDTZ7khFykx3hxVCd4eJiBQgJxt+fAW+fQqyMyCoEQx6ybq1XqQK0N1hIiJSMXx8oWcMjPkWQjvA8YPwwUhYMBbSPHZHJ1IqSoJERKT0wjpYt9T3/D9w+cBP78GrPeC3ZXZHJlJiSoJERKRs/ALgyklw2xfQoCWk7IZZgyF2AmSesDs6kWIpCRIRkQJl5xhW7DjIp/F7WLHjINk5hQwhbX4x3LPcmmgRIO5VeL037F1fecGKlIEGRhdCA6NFxMliNyYyedFmEj1p3m3h7kAmDoqkf4fwwg/8ZYl159jRfdaEi73Gw6UPg29Bky+KlD8NjBYRkTKL3ZjI2Dnr8iRAAEmeNMbOWUfsxsTCDz63H9wbB5HXQk4WfPc0vN1PM01LlaQkSEREvLJzDJMXbaagSwS52yYv2lz4pTGAoIZw00y4/j8Q6IY9a+G1S2HlG5CTUwFRi5SNkiAREfFalXAoXw/QqQyQ6EljVcKhol/I5YILboKxK+DsyyDrBHzxKMy5Djy7yzdokTJSEiQiIl7JqYUnQGUph/ssGPkJDHgO/GrDb99Zt9Jv+FDLbojtlASJiIhXSHBguZYDwMcHuo2Be763VqpP98AnY+CjUXDsYBkjFTlzSoJERMSrW6uGhLsDC1o/HrCWUQ13B9KtVcPSv3jjc+D2JXDZX6w7xzZ/CjOi4JcvzyRkkTJTEiQiIl6+Pi4mDooEyJcI5T6fOCgSX5/C0qTi3sAPeo+HO7+Cxm2tW+nfGwqLHoT0o2WOW6QslASJiEge/TuEM2NkZ8LceS95hbkDmTGyc9HzBJVURCe4exlcfJ/1fO1MeO0S+CPuzF9bpIQ0WWIhNFmiiDhddo5hVcIhklPTCAm2LoGVuQeoKAn/g//eC55dgAsueRAue8JalkOklErz91tJUCGUBImIVKI0j7XmWPxc63loB7judWuhVpFS0IzRIiJSvQS64dpXYdhcCGoM+zbCG33ghxcgJ9vu6KSGUhIkIiJVR/uB1rIbbQdATiZ8NQneGQCHfrM7MqmBKjQJOnz4MNHR0bjdbtxuN9HR0Rw5cqTIY4wxTJo0iYiICGrXrk2fPn3YtGlTnjLp6ek88MADNG7cmDp16jB48GB27847A+kvv/zCkCFDaNy4MfXq1eOSSy7h22+/Le8qiohIeavbBIa/B0P+Df7BsCsOZvSENe9ogkUpVxWaBI0YMYL4+HhiY2OJjY0lPj6e6OjoIo959tlnmTZtGtOnT2f16tWEhYXRt29fUlNTvWViYmJYsGAB8+bN44cffuDo0aMMHDiQ7OyTXabXXHMNWVlZfPPNN6xdu5aOHTsycOBAkpKSKqy+IiJSTlwu6DQSxi6HFj0h8xgsjoH3hkHqPrujk5rCVJDNmzcbwMTFxXm3rVixwgBm69atBR6Tk5NjwsLCzDPPPOPdlpaWZtxut3nttdeMMcYcOXLE1KpVy8ybN89bZs+ePcbHx8fExsYaY4zZv3+/Acz//vc/b5mUlBQDmK+++qpE8Xs8HgMYj8dT8kqLiEj5y842Zvkrxvy9iTET6xnzTEtjNi6wOyqpokrz97vCeoJWrFiB2+2me/fu3m0XX3wxbrebH3/8scBjEhISSEpKol+/ft5tAQEB9O7d23vM2rVryczMzFMmIiKCDh06eMs0atSI9u3bM2vWLI4dO0ZWVhavv/46oaGhdOnSpcD3Tk9PJyUlJc9DRESqAB8f6HG/Na9Q2AVw4pC15Mb8MXDiiN3RSTVWYUlQUlISISEh+baHhIQUekkqd3toaGie7aGhod59SUlJ+Pv706BBg0LLuFwuli5dyvr16wkODiYwMJAXXniB2NhY6tevX+B7T5kyxTt2ye1206xZs1LVV0REKlhIe7jza+j1KLh84OcPYUYP2KHxnlI2pU6CJk2ahMvlKvKxZs0awEpGTmeMKXD7qU7fX5JjTi1jjOHee+8lJCSE77//nlWrVjFkyBAGDhxIYmJigcdPmDABj8fjfezatavI9xMRKUx2jmHFjoN8Gr+HFTsOkp2jwbzlxs8fLv+rtQZZw9aQsgdmXwufj4eM43ZHJ9WMX2kPuP/++xk+fHiRZVq2bMmGDRvYty//4LX9+/fn6+nJFRYWBli9PeHhJ6dlT05O9h4TFhZGRkYGhw8fztMblJycTI8ePQD45ptvWLx4MYcPH/ZOlPTqq6+ydOlS3n33XR5//PF87x0QEEBAgGYnFZEzE7sxkcmLNpPoSfNuC3cHMnFQZPksNyGWZhdZq9IvfRJW/wdWvQ47vrEmWGxa8LAHkdOVuieocePGtGvXrshHYGAgUVFReDweVq1a5T125cqVeDweb7JyulatWhEWFsbSpUu92zIyMli2bJn3mC5dulCrVq08ZRITE9m4caO3zPHj1n8DPj55q+fj40NOTk5pqywiUiKxGxMZO2ddngQIIMmTxtg564jdWHBPtJSRfx245nkYOR+Cw+Hgr/BWX/j2acjOtDs6qQYqbExQ+/bt6d+/P2PGjCEuLo64uDjGjBnDwIEDadu2rbdcu3btWLBgAWBdBouJieHpp59mwYIFbNy4kdGjRxMUFMSIESMAcLvd3HHHHTz88MN8/fXXrF+/npEjR3L++edz5ZVXAhAVFUWDBg0YNWoUP/30E7/88guPPvooCQkJXHPNNRVVZRFxsOwcw+RFmynowlfutsmLNuvSWEVocyXcuwI63AgmG5ZNhf9cCfu32R2ZVHEVOk/Q3LlzOf/88+nXrx/9+vXjggsuYPbs2XnKbNu2DY/H430+fvx4YmJiuPfee+natSt79uxhyZIlBAcHe8u88MILXHvttQwdOpRLLrmEoKAgFi1ahK+vL2D1VsXGxnL06FEuv/xyunbtyg8//MCnn37KhRdeWJFVFhGHWpVwKF8P0KkMkOhJY1XCocoLyklqN4Ab34Ib34bA+pAYD6/3grgZoCsAUggtoFoILaAqIqXxafweHpwXX2y5l4Z3ZEjHsyo+ICdLSYSF98P2r6znTdpbPURHfodGbaD34xA52N4YpcJoAVURkUoWEhxYruXkDNQLh1s+hmumga8/7N8CB36BrHTYtxk+jIbNC+2OUqoAJUEiIuWgW6uGhLsDKWwyDxfWXWLdWjWszLCcy+WCi+6A+i1O22EAlzVuSBxPSZCISDnw9XExcVAkQL5EKPf5xEGR+PoUPeeZlDPPHwVsNHDg10oPRaoeJUEiIuWkf4dwZozsTJg77yWvMHcgM0Z21jxBdmjUhvxpKeBbC9KPVno4UrVoYHQhNDBaRMoqO8ewKuEQyalphARbl8DUA2STzQutMUC48F4Ky5204KyucMtHEKRLlDWJBkaLiNjI18dFVOtGDOl4FlGtGykBslPkYBg6G0LPA78A6+uVk61b6vesgXeuhpS9dkcpNlFPUCHUEyQiUoMlb4XZ10HqXnA3h+gF0LiN3VFJOVBPkIiISFFC2sEdX1pjhjx/wNtXwd54u6OSSqYkSEREnKl+c7gtFsIvhOMHYOZASPje7qikEikJEhER56rbBEYthhY9ISMV5twAWz+zOyqpJEqCRETE2QLrWSvRtxsI2enwQTSsn2t3VFIJlASJiIjUCoSb3oWOI611xj69F36cbndUUsGUBImIiAD4+sGQ6dDjAev5kr/AV5NBN1HXWEqCREREcrlc0O+fcOUk6/kP02DRg5CTbWtYUjGUBImIiJyu5//BoJfA5QPr3oWPRlur0EuNoiRIRESkIF1Gw00zwdcftiyEuTdBeqrdUUk5UhIkIiJSmMgh1vpi/nUhYRm8OxiOHbQ7KiknSoJERESKcnYfGLUQajeEvevgnf7g2W13VFIOlASJiIgU56wucHss1DsLDvwCb10FB361Oyo5Q0qCRERESqJJW7j9S2h0DqTs/nO9sfV2RyVnQEmQiIhISdVvZvUIRXSC4wf/XG/sf3ZHJWWkJEhERKQ06jSGUYugVS/IOGqtN7Zlkd1RSRkoCRIRESmtgGAY8dGf641lwIe3wrrZdkclpaQkSEREpCxy1xvrFA0mBxbeD8tfsjsqKQUlQSIiImXl6weDX4FLHrSeL33Semi9sWpBSZCIiMiZcLmg79+tB1i9QQsfgOwse+OSYikJEhERKQ+XPAiDp1vrja2fDR+Ngsw0u6OSIigJEhERKS+do2HoLGu9sa2LYe6NkJZid1RSCCVBIiIi5an9IBg5H/yDYef38O4gOHbA7qikAEqCREREylurXjB6EQQ1gsR4eLs/HNlld1RyGiVBIiIiFSGik7XMRr2mcPBXa5mN/dvsjkpOoSRIRESkojQ+B+74EhqfCyl7rB6hPWvtjkr+pCRIRESkIrmbwm2xENEZThyCmYPgt+/sjkpQEiQiIlLx6jSCUQuhVW/IPAZzb4LNn9odleMpCRIREakMAcFwy0fQfrC13thHo2HtTLujcjQlQSIiIpXFLwBumgmdR1nrjS16EL6fpmU2bKIkSEREpDL5+MKgl6DnQ9bzryfDkr8qEbKBkiAREZHK5nLBlROh3z+t5yumw6f3ab2xSqYkSERExC49HoAhr4LLF+Lnwoe3ar2xSqQkSERExE6dboFhs8E3ALZ9BnNu0HpjlURJkIiIiN3aXQPRn1jrjf3+A7w7EI7utzuqGk9JkIiISFXQsieMXgxBjSHxJ2uZjSN/2B1VjaYkSEREpKqI6GitN+ZuBod2wFtXQfJWu6OqsZQEiYiIVCWN21iJUJN2kLoX3ukPu9fYHVWNpCRIRESkqnGfBbd9AWd1hROH4d3BsOMbu6OqcZQEiYiIVEVBDeHWT+Hsy/5cb2wofPkXmNED/hlifd280O4oqzUlQSIiIlVVQF0Y8QGcdx3kZFqTKu7bBFnpsG8zfBitROgMKAkSERGpyvwC4Ia3oHaD03YYwAXLptoRVY1QoUnQ4cOHiY6Oxu1243a7iY6O5siRI0UeY4xh0qRJREREULt2bfr06cOmTZvylHnjjTfo06cP9erVw+VyFfiaZXlvERGRKsnHFzKOF7DDwMFfKz2cmqJCk6ARI0YQHx9PbGwssbGxxMfHEx0dXeQxzz77LNOmTWP69OmsXr2asLAw+vbtS2pqqrfM8ePH6d+/P0888US5vreIiEhVlVK3JTm48mwzQEqdlrbEUxO4jKmYZWu3bNlCZGQkcXFxdO/eHYC4uDiioqLYunUrbdu2zXeMMYaIiAhiYmJ47LHHAEhPTyc0NJSpU6dy99135yn/3Xffcdlll3H48GHq169/Ru99upSUFNxuNx6Ph3r16pW1GURERM5Y7MZE/vvea7zm/yI5xoWPy2CMtQ7r6uxzOXTTx1x1QQu7w6wSSvP3u8J6glasWIHb7fYmIQAXX3wxbrebH3/8scBjEhISSEpKol+/ft5tAQEB9O7du9Bjyuu909PTSUlJyfMQERGxW3aOYfKizcTmdOPujBi2mmakmVrsNo3JND5c5PsLwf8dTXb6MbtDrXYqLAlKSkoiJCQk3/aQkBCSkpIKPQYgNDQ0z/bQ0NBCjymv954yZYp3/JDb7aZZs2Ylfj8REZGKsirhEIkea2X5L3O6MSDjGdqlv8ulGS9zR+ajnDD+9MhZx7G3hkCax+Zoq5dSJ0GTJk3C5XIV+VizxprZ0uVy5TveGFPg9lOdvr8kxxT3GsW9zoQJE/B4PN7Hrl27SvV+IiIiFSE5Na3Qff/LuZDojMdJMUHUS14NMwfCsQOVGF315lfaA+6//36GDx9eZJmWLVuyYcMG9u3bl2/f/v378/X05AoLCwOsnpzw8HDv9uTk5EKPKex1SvveAQEBBAQElPg9REREKkNIcGCR+9eYdgzP+Cuf1nueWkkb4J2rIXoBuJtWUoTVV6l7gho3bky7du2KfAQGBhIVFYXH42HVqlXeY1euXInH46FHjx4FvnarVq0ICwtj6dKl3m0ZGRksW7as0GMKUpb3FhERqYq6tWpIuDuQwq6HuIDD9drhc0cs1GsKB36Bt/vDwR2VGWa1VGFjgtq3b0///v0ZM2YMcXFxxMXFMWbMGAYOHJjn7qx27dqxYMECwLqEFRMTw9NPP82CBQvYuHEjo0ePJigoiBEjRniPSUpKIj4+nu3btwPw888/Ex8fz6FDh0r13iIiIlWdr4+LiYMiAfIlQrnPJw6KxDfkXLg9Fhq1Ac8uKxFK+rlSY61uKnSeoLlz53L++efTr18/+vXrxwUXXMDs2bPzlNm2bRsez8mBXOPHjycmJoZ7772Xrl27smfPHpYsWUJwcLC3zGuvvUanTp0YM2YMAL169aJTp04sXHhy6vCSvLeIiEh10L9DODNGdibMnffSWJg7kBkjO9O/w59DSOo3g9tiIex8OJYMM6+BP1baEHH1UGHzBFV3JZ1nIDs7m8zMzEqMTGoqf39/fHy0ko2IFC47x7Aq4RDJqWmEBAfSrVVDfH0KuFB24gi8Nwx2xUGtIBg+F1pfXunx2qE08wQpCSpEcY1ojCEpKUlLcUi58fHxoVWrVvj7+9sdiojUBBnH4YORsONr8KkFN74FkUPsjqrCKQkqB8U1YmJiIkeOHCEkJISgoKBS38IvcqqcnBz27t1LrVq1aN68uc4nESkfWRnwyRjY/F9w+cDgV6DTSLujqlClSYJKfYu8WJfAchOgRo0a2R2O1BBNmjRh7969ZGVlUatWLbvDEZGawM8fbnwbFgXD+tnw6X2QlgJR99odWZWgAQhlkDsGKCgoyOZIpCbJvQyWnZ1tcyQiUqP4+Fo9QFH3W8+/nADfTgFdCFISdCZ0yULKk84nEakwLhf0+ydc/lfr+bJnIPZxyMmxNy6bKQkSERFxApcLej0KV//Ler7yNevyWHaWvXHZSEmQzbJzDCt2HOTT+D2s2HGQ7JzK757s06cPMTExlf6+IiJig+53wXWvg8sXfnoPPhoFWel2R2ULDYy2UezGRCYv2uxdHRgg3B3IxEGRJye+qmK+++47LrvsMg4fPkz9+vXtDkdERMriwuEQEAwfjYati+G9oTBsLgTUtTuySqWeIJvEbkxk7Jx1eRIggCRPGmPnrCN2Y6JNkYmIiCO0uwZu+Qhq1YHfvoPZ18KJw3ZHVamUBNkgO8cwedFmCrrwlbtt8qLNFXJp7NixY9x6663UrVuX8PBwnn/++Tz758yZQ9euXQkODiYsLIwRI0aQnJwMwM6dO7nssssAaNCgAS6Xi9GjRwMQGxtLz549qV+/Po0aNWLgwIHs2KHF+0REqrSz+8CohRBYH3avhneugdR9dkdVaZQE2WBVwqF8PUCnMkCiJ41VCYfK/b0fffRRvv32WxYsWMCSJUv47rvvWLt2rXd/RkYG//jHP/jpp5/473//S0JCgjfRadasGfPnzwesNd8SExN56aWXACu5euihh1i9ejVff/01Pj4+XHfddeQ4/M4DEZEqr2lXuO0LqBsGyZvgnf5w+He7o6oUGhNkg+TUwhOgspQrqaNHj/LWW28xa9Ys+vbtC8C7775L06ZNvWVuv/127/dnn302L7/8Mt26dePo0aPUrVuXhg0bAhASEpJnTNANN9yQ573eeustQkJC2Lx5Mx06dCjXeoiISDkLjYTbv4BZ18Kh36wV6G/9LzRpa3dkFUo9QTYICQ4svlApypXUjh07yMjIICoqyrutYcOGtG178iRfv349Q4YMoUWLFgQHB9OnTx8A/vjjj2Jfe8SIEZx99tnUq1ePVq1aleg4ERGpIhqeDbfHQpN2kLoX3rka9q63O6oKpSTIBt1aNSTcHUhhU+O5sO4S69aqYbm+b3HLxB07dox+/fpRt25d5syZw+rVq1mwYAFgXSYryqBBgzh48CBvvvkmK1euZOXKlSU6TkREqpB6EdalsYhOcPwgzBwEO5fbHVWFURJkA18fFxMHRQLkS4Ryn08cFImvT/nOINymTRtq1apFXFycd9vhw4f55ZdfANi6dSsHDhzgmWee4dJLL6Vdu3beQdG5Clra4eDBg2zZsoW//vWvXHHFFbRv357Dh511h4GISI0R1BBuXQgtL4WMVJhzPfyyxO6oKoSSIJv07xDOjJGdCXPnveQV5g5kxsjOFTJPUN26dbnjjjt49NFH+frrr9m4cSOjR4/Gx8c6DZo3b46/vz+vvPIKv/32GwsXLuQf//hHntdo0aIFLpeLxYsXs3//fo4ePUqDBg1o1KgRb7zxBtu3b+ebb77hoYceKvf4RUSkkgTWs26fP/dqyEqDeTfDzx/bHVW508BoG/XvEE7fyDBWJRwiOTWNkGDrElh59wCd6l//+hdHjx5l8ODBBAcH8/DDD+PxeABrFfOZM2fyxBNP8PLLL9O5c2eee+45Bg8e7D3+rLPOYvLkyTz++OPcdttt3HrrrcycOZN58+Yxbtw4OnToQNu2bXn55Ze944lERKQaqlUbhs2G/46Fnz+C+XdCeip0vc3uyMqNyxQ3UMShUlJScLvdeDwe6tWrl2dfWloaCQkJtGrVisDA8h28LM6l80pEqqScHPj8EVjzlvX8ysnQM8bWkIpS1N/v0+lymIiIiBTOxweueR56/jnM4auJ8NUkqAF9KEqCREREpGguF1w50eoFAvjhBfjsIauXqBpTEiQiIiIl0zMGBr4IuGDN27DgLsjOtDmoslMSJCIiIiXX9Ta48S3w8bMGTH8wEjJP2B1VmSgJEhERkdLpcAMMfx/8AuGXWJhzI6Sl2B1VqSkJEhERkdI7tx9EL4CAevD7DzBrMBw7aHdUpaIkSERERMqmRQ8YtQiCGlnrjL1zNaTstTuqElMSJCIiImUX0RFui4V6Z8GBbfD2VdZK9NWAkiARERE5M03OtVagb3g2HPkD3u4P+zbZHVWxlASJlMDo0aO59tpr7Q5DRKTqqt/c6hEK7QBH98E7A2D3GrujKpKSIKny+vTpQ0xMTKW8186dO3G5XMTHx+fZ/tJLLzFz5sxKiUFEpNoKDoXRi6FpN0g7Au8Oht++szuqQikJstvmhTCjB/wzxPq6eWGlvn1GRkalvl9FMcaQlZVVYa/vdrupX79+hb2+iEiNUbsB3PpfOPsyyDwGc2+CLYvtjqpASoLKizGQcax0jw0fwYfRsG8zZKVbXz+MtraX5nVKsX5Lnz59uP/++3nooYdo3Lgxffv2ZfPmzQwYMIC6desSGhpKdHQ0Bw4c8B6Tk5PD1KlTadOmDQEBATRv3pynnnrKu//nn3/m8ssvp3bt2jRq1Ii77rqLo0ePevfnXkp67rnnCA8Pp1GjRtx3331kZp6cZfTVV1/lnHPOITAwkNDQUG688UbvscuWLeOll17C5XLhcrnYuXMn3333HS6Xiy+//JKuXbsSEBDA999/X+Blq5iYmDwr2hdVn1atWgHQqVMnXC6X97jTXzc9PZ1x48YREhJCYGAgPXv2ZPXq1d79ufF9/fXXdO3alaCgIHr06MG2bdtK/FmJiFRb/nVgxAfQfhBkZ8CHt8JP87y7s3MMK3Yc5NP4PazYcZDsHHvWIfOz5V1roszj8HREGQ82eb9+cmfpDn9ir3XCldC7777L2LFjWb58OYcOHaJ3796MGTOGadOmceLECR577DGGDh3KN998A8CECRN48803eeGFF+jZsyeJiYls3boVgOPHj9O/f38uvvhiVq9eTXJyMnfeeSf3339/nstH3377LeHh4Xz77bds376dYcOG0bFjR8aMGcOaNWsYN24cs2fPpkePHhw6dIjvv/8esC5D/fLLL3To0IG///3vADRp0oSdO3cCMH78eJ577jnOPvvsEvfUFFWfVatW0a1bN7766ivOO+88/P39C3yN8ePHM3/+fN59911atGjBs88+y1VXXcX27dtp2LCht9xf/vIXnn/+eZo0acI999zD7bffzvLly0v8WYmIVFt+AXDjTFg0DuLnwoK7Ic1DbJ3BTF60mURPmrdouDuQiYMi6d8hvHJDrNR3kyqhTZs2PPvsswA8+eSTdO7cmaefftq7/+2336ZZs2b88ssvhIeH89JLLzF9+nRGjRoFQOvWrenZsycAc+fO5cSJE8yaNYs6daxEbPr06QwaNIipU6cSGhoKQIMGDZg+fTq+vr60a9eOa665hq+//poxY8bwxx9/UKdOHQYOHEhwcDAtWrSgU6dOgHUZyt/fn6CgIMLCwvLV5e9//zt9+/Ytcd1TU1OLrE+TJk0AaNSoUYHvB3Ds2DFmzJjBzJkzufrqqwF48803Wbp0KW+99RaPPvqot+xTTz1F7969AXj88ce55pprSEtLIzAwsMQxi4hUW75+MHi6NaHiyhnwxXg2Za4mMftawOUtluRJY+ycdcwY2blSEyElQeWlVpDVI1Ma/7kCkrdysicIwAUh7eHOr0r33qXQtWtX7/dr167l22+/pW7duvnK7dixgyNHjpCens4VV1xR4Gtt2bKFCy+80JsAAVxyySXk5OSwbds2bxJ03nnn4evr6y0THh7Ozz//DEDfvn1p0aIFZ599Nv3796d///5cd911BAUVX69T61ISW7ZsKbI+JbFjxw4yMzO55JJLvNtq1apFt27d2LJlS56yF1xwgff78HDrBzs5OZnmzZuX+f1FRKoVHx/oP4WcQDc+y57h4VofcYHPDpq69tPKlUSCCefFrOtZktONyYs20zcyDF8fV/GvWx6hVcq7OIHLZV2SKs2jzxNYCVDuh+2ynl/2ROlex1W6k+XUhCUnJ4dBgwYRHx+f5/Hrr7/Sq1cvateuXeRrGWNwFfL+p26vVatWvn05OTkABAcHs27dOt5//33Cw8N58sknufDCCzly5Eip6gLg4+ODOW2M1Kljj4qrT0nkvv7p9S6oLU6td+6+3HqLiDiGy8XK5ncxOTMagL6+62jn2kWgK5O2rl287v8i/XxWkehJY1XCoUoLS0mQnSIHw9DZEHqede009DwYNscaSFZJOnfuzKZNm2jZsiVt2rTJ86hTpw7nnHMOtWvX5uuvvy64CpGRxMfHc+zYMe+25cuX4+Pjw7nnnlviOPz8/Ljyyit59tln2bBhAzt37vSOSfL39yc7O7tEr9OkSRMSExPzbDv1dvfi6pM7Bqio92vTpg3+/v788MMP3m2ZmZmsWbOG9u3blyhOERGnSU5N453sq9mb0xBjTv7/7uMy5BgXD/p94i1XWZQE2S1yMIxdDn9Ntr5WYgIEcN9993Ho0CFuvvlmVq1axW+//caSJUu4/fbbyc7OJjAwkMcee4zx48cza9YsduzYQVxcHG+99RYAt9xyC4GBgYwaNYqNGzfy7bff8sADDxAdHe29FFacxYsX8/LLLxMfH8/vv//OrFmzyMnJoW3btgC0bNmSlStXsnPnTg4cOFBkT8rll1/OmjVrmDVrFr/++isTJ05k48aN3v3F1SckJITatWsTGxvLvn378Hg8+d6jTp06jB07lkcffZTY2Fg2b97MmDFjOH78OHfccUeJ215ExElCgq2xkA1dqfkuYPi4DGe7EvOUqwxKghwuIiKC5cuXk52dzVVXXUWHDh148MEHcbvd+PhYp8ff/vY3Hn74YZ588knat2/PsGHDSE5OBiAoKIgvv/ySQ4cOcdFFF3HjjTdyxRVXMH369BLHUL9+fT755BMuv/xy2rdvz2uvvcb777/PeeedB8AjjzyCr68vkZGRNGnShD/++KPQ17rqqqv429/+xvjx47noootITU3l1ltvzVOmqPr4+fnx8ssv8/rrrxMREcGQIUMKfJ9nnnmGG264gejoaDp37sz27dv58ssvadCgQYnrLSLiJN1aNSTcHUiCCSfH5M2CcoyL30w44e5AurVqWMgrlD+XOX0AhQCQkpKC2+3G4/FQr169PPvS0tJISEigVatWustHyo3OKxGp6WI3JvLf917jNf8XyTEu76UwH5fh7oz/47oRd5/x3WFF/f0+ne4OExERkUrRv0M4jLiHx//rz60Z8zibRH4z4cyqNZzrbrxd8wSJiIhIzdW/Qzh9I59gVcI9fJmaRkhwIE+1alhpt8WfSkmQiIiIVCpfHxdRrRvZHYYGRouIiIgzKQk6AxpTLuVJ55OISOVSElQGubMAHz9+3OZIpCbJyMgAyLO8iIiIVByNCSoDX19f6tevn2eunMKWjhApiZycHPbv309QUBB+fvqxFBGpDPptW0a5K4znJkIiZ8rHx4fmzZsroRYRqSRKgsrI5XIRHh5OSEhIngU6RcrK39/fO0u3iIhUvApNgg4fPsy4ceNYuHAhAIMHD+aVV16hfv36hR5jjGHy5Mm88cYbHD58mO7du/Pvf//bu4QCwBtvvMF7773HunXrSE1N5fDhw3lec+fOnfzjH//gm2++ISkpiYiICEaOHMlf/vIX7wKZ5cXX11djOERERKqhCv23c8SIEcTHxxMbG0tsbCzx8fFER0cXecyzzz7LtGnTmD59OqtXryYsLIy+ffuSmprqLXP8+HH69+/PE088UeBrbN26lZycHF5//XU2bdrECy+8wGuvvVZoeREREXGeCls7bMuWLURGRhIXF0f37t0BiIuLIyoqiq1bt3pXCD+VMYaIiAhiYmJ47LHHAEhPTyc0NJSpU6dy99135yn/3Xffcdlll+XrCSrIv/71L2bMmMFvv/1W4P709HTS09O9z1NSUmjWrFmJ1h4RERGRqqE0a4dVWE/QihUrcLvd3gQI4OKLL8btdvPjjz8WeExCQgJJSUn069fPuy0gIIDevXsXekxJeTweGjYsfGXaKVOm4Ha7vY9mzZqd0fuJiIhI1VZhY4KSkpIICQnJtz0kJISkpKRCjwEIDQ3Nsz00NJTff/+9zLHs2LGDV155heeff77QMhMmTOChhx7yPvd4PDRv3pyUlJQyv6+IiIhUrty/2yW50FXqJGjSpElMnjy5yDKrV68GKPBWX2NMsbcAn76/JMcUZu/evfTv35+bbrqJO++8s9ByAQEBBAQEeJ/nNqJ6hERERKqf1NRU3G53kWVKnQTdf//9DB8+vMgyLVu2ZMOGDezbty/fvv379+fr6cmVO/dOUlIS4eHh3u3JycmFHlOUvXv3ctlllxEVFcUbb7xRqmMjIiLYtWsXwcHBpUrAcscS7dq1q8aPJXJSXYvjlLZwSj3Lwklt46S6lpZT2qYq19MYQ2pqKhEREcWWLXUS1LhxYxo3blxsuaioKDweD6tWraJbt24ArFy5Eo/HQ48ePQo8plWrVoSFhbF06VI6deoEWEsJLFu2jKlTp5Yqzj179nDZZZfRpUsX3nnnnVLPv+Lj40PTpk1Ldcyp6tWrV+VOjIripLoWxylt4ZR6loWT2sZJdS0tp7RNVa1ncT1AuSpsYHT79u3p378/Y8aMIS4ujri4OMaMGcPAgQPz3BnWrl07FixYAFiXwWJiYnj66adZsGABGzduZPTo0QQFBTFixAjvMUlJScTHx7N9+3YAfv75Z+Lj4zl06BBg9QD16dOHZs2a8dxzz7F//36SkpIKHYskIiIizlOhkyXOnTuXcePGee/2Gjx4MNOnT89TZtu2bXg8Hu/z8ePHc+LECe69917vZIlLliwhODjYW+a1117LMy6pV69eALzzzjuMHj2aJUuWsH37drZv356vN0crdYuIiAgARspVWlqamThxoklLS7M7lArnpLoWxylt4ZR6loWT2sZJdS0tp7RNTalnhU2WKCIiIlKVabVGERERcSQlQSIiIuJISoJERETEkZQEiYiIiCMpCRIRERFHUhIk1c66detITU21OwypRPrMBXQeSPmfA0qCqrl9+/bx2WefOWISyL1799KvXz8uu+wy4uPj7Q7HVk753PWZF84p5wDoPCiKU86DijoHlARVY9OnTyciIoJBgwaxadMmu8OpUOPHj6dFixYEBQWxZcsWLr30UrtDso1TPnd95oVzyjkAOg+K4pTzoELPATtnapSyycnJMZ999pm54oorzHPPPWc6d+5sbrzxRpOdnW13aOUuIyPD3H///cblcpl58+Z5t+/bt8/GqOzhlM9dn3nhnHIOGKPzoChOOQ8q4xyo0LXDpGK4XC5CQ0OJjo7mhhtu4KKLLqJPnz58+eWXXH311XaHV26MMdSqVYtLL72Un3/+mQMHDrB161YmTJjAgQMH8PHx4ZZbbmH06NH4+/vbHW6Fc8Lnrs+8aE44B0DnQXGccB5U1jmgZTOqgZSUFDZv3kyzZs0466yzCiwzbNgwfv31V5YtW5ZnsdnqJiMjg+zsbGrXrk12dja+vr5kZWXxf//3f3z88cdkZmYycuRIzj77bDZt2sS7777L008/zdixY6ldu7bd4Zcrp3zu+swL55RzAHQeFMUp54Et50C59SlJhXj66adNvXr1TIcOHUy9evXMiy++aHbv3m2MMSYrK8vb/bljxw5Tu3Zt8/LLL9sZ7hl55plnzLnnnmtiY2O927KysowxxqxYscKMGjXKLFy4MM8x48aNMxdeeKH5+eefKzXWiuaUz12feeGccg4Yo/OgKE45D+w6B5QEVWGff/65ad++vVmwYIH57bffzFNPPWXOO+88c/vtt3vL5OTkeL//61//akJDQ82uXbuMMcYcO3bMHD16tNLjLq2DBw+ae+65x1xwwQWmXr165vrrrzf79+83xuSt34YNG7wrFuf+4CclJRmXy2VWrlxZ+YFXECd87vrMi+aEc8AYnQfFccJ5YPc5oCSoChs3bpzp1KlTnm2vvPKKadu2rXnjjTeMMSczZWOMOXr0qGnRooUZN26cmTVrlunZs6f58MMPKzXmsvjtt9/M+PHjzWeffWa+//5743K5zPvvv+890U/9QciVu+399983ISEh5qeffqrUmCuSEz53feZFc8I5YIzOg+I44Tyw+xxQElRFZWdnm7Fjx5rhw4d7s19jjNm7d6+5++67zYUXXmhSU1O9ZXNNnDjRuFwu4+/vbyZMmFDpcZdFVlaW+f33373Phw4dai644AKTkJBQYPncH4AtW7aYfv36mTFjxlRGmJXCKZ+7PvPCOeUcMEbnQVGcch7YfQ4oCaqCcj/kKVOmmGbNmuU7GRYuXGi6du3q/U/AGOs/gPvuu8+4XC5zxx13mMOHD1dixOUjt94HDx40tWrVMlOmTMnzw2+M1b07efJkM3r0aBMUFGRuueUWk5KSYke45c6Jn7vTP/PTOfEcMEbnwemceB7YdQ5oskQbJScnFzjLZ05ODgAxMTF4PB7mzp2bZ3+fPn3w8fHh4MGD3m0HDhwgODiY77//nv/85z/Ur1+/QmMvrcLqeuo2l8tFVlYWDRs25C9/+QvTpk1jy5YtecoGBQXRoEEDjh49yrJly5gzZ061uxNizZo1pKWlAXnrX9M+98Lq6cTPvCg1+Rw4nc6Dkqnp50GuKnEOnFEKJWXy22+/mUGDBpnRo0ebjRs35tmXmZmZ5/lzzz1ngoODzerVq/Ns79ixo7n33nsrPNYzVdK65l7XPvX69llnnWXuuusuc+jQIfPll1+amTNnGmNMtZ0QbMeOHWbw4MHG5XKZd999N8++mvS5l7SeTvjMT7dz504zefJkM3PmTBMXF2eMOVm3mnQOGFPyujrxPPjjjz/MwoULzYYNG7z1zu0JqUnnQUnraec5oCSokuR+8O+++65p0KCBGTp0qFm9erVJSkrKsz/3+/Hjx5vZs2cbY4zp0qWLueKKK8xnn31mjDFm7dq15sILLzRLliyp5FqUTFnqOmfOHO/JnfuD8MknnxhfX19z/vnnG5fLZf79739Xck3KR05Ojhk7dqzx8fExgwcPNvXr1zfz5883xuT9ga4Jn3tp6lmTP/OCPPbYYyYoKMhcffXVpl27dqZp06Zm06ZNxpiTPxPV/RzIVZq6Ou08ePjhh01QUJC54oorTL169czYsWPNjh07jDEmz2Dg6n4elKaedp4DSoIqUXZ2tunfv7+ZNm2ad9uxY8fylHnnnXdMw4YNTceOHc26deuMMcZs3rzZXHfddcbf39/069fPBAUFmeHDh+c7tiopbV03bNiQZ9/u3bvN+PHjjcvlMsOHD/fe8lndLFiwwNSuXdt069bN+99wVFSUufPOO40xJ/8gzJw5s1p/7mWpZ039zAsyf/5806VLF/PNN98YY4xZv369iYqKMs8884y3THU/B3KVtq5OOg/eeustExUVZb7//nuTmZlpPvjgA3PppZea3r17e8vUhPOgtPW08xxQElSBTr+17+uvvzbnnHOOyczMNMuXLzeDBw82V111lbnvvvvMihUrjDHGTJo0ybz66qv5ug49Ho9ZsmSJmT59uvnhhx8qtyIlUB51zZWenm5iYmJMw4YNzbfffltZVSg3p7bFG2+84e0NMcaY48ePm5EjR5rrr7/e+wvs6NGj5h//+IeZMWNGtfrcy6Oeuar7Z366038ebr31VtOzZ88823r37u29tTcnJ8dMmjSp2p0DxpRPXXPV1PMg9+uAAQPMyJEj85R54IEHjMvl8g5yro7nQXnUM1dlnwNKgirI8ePH841sj4uLM40aNTILFiwwXbt2NY8//riZNGmS6dWrl2nQoIFJTEy0KdozUxF1zb10Vt2c3hanXgbK/WGPiYkxF1xwgTHm5C+N6jbWoSLqWV0/89Od3jaZmZnmqaeeMs2bNzfLly/3jpNr0KCB6devn7n//vur7H/0xamIutbU8+Dw4cNmwIABZsKECXl+Dh599FHTtm1b07hx43zjgaqDiqhnZZ4DSoIqwOOPP246d+5srrzySvPSSy8Zj8djjLGm/r7iiivMRRddZO68807vCZKSkmI6dOhgbrvtNmOMyZcZV2VOqmtxTm+L3Fs3c+ue+/Wzzz4z9erVyzM3RnXilHqWxeltc+TIEWOMMZs2bTLDhg0zAwcOND4+Pubqq682X331lXn++edN69atzS233GKMqV7JsJPqWlqnt03u7eoPP/yw6dq1q5k8ebI5cOCAefTRR02TJk3Me++9Z8LDw82rr75qjCl4gsCqqCbUU0lQOUpPTzc33nijiYyMNPPmzTO33nqriYyMNFdffbUxxhoTc9111+XpEsxNAt566y1z1llneSe/quqcVNfiFNYW11xzTYHlP/30U9OqVasq16VdHKfUsyyK+3kwxvqFP3fuXDNgwIA8c5t8+umnJigoyLtUQFXnpLqWVmFtc9VVVxljjElNTTUPPvigadOmjWnYsKHp0KGDd8mHSy65JM8YyqqsJtVTSVA52rx5sznnnHPyjNj/4YcfTO3atc2UKVOMMdZaMI0aNTJ9+/bNc+zjjz9u+vTpY44dO1YlsuPiOKmuxSmqLZ599tl8l4IOHjxo/P39zeLFi/Nsr+qcUs+yKK5tcv8BmDBhgrnuuuvyHPviiy+ac889t9r0mDmprqVVkt+Lxhiza9euPIOB09LSTJMmTarNXXA1qZ5KgsrR2rVrjcvlMgcPHjTG5J310+12e28PnDRpkmnUqJH529/+Zn755RezdetW07t3b/P3v//dtthLy0l1LU5RbdGgQQPzyy+/5Cl/5MgR06tXL/Pwww9Xeqxnwin1LIuSts3//d//eW91zsrKMps3bza9evUy9913n22xl5aT6lpaxbXNtm3b8pTP3T9r1izTvXt3s3fv3soNuIxqUj2VBJWj9evXm/POO8+88sorxpiTH3xGRoZp1aqViYmJMcZYg77eeOMNU79+fdOhQwcTHBxsbrvttnyDi6syJ9W1OMW1RW4SkDsYMCsry5xzzjnmnnvuMRkZGfYEXQZOqWdZlPTnYeXKlWbIkCHeW53r1q1rbr/9dnPixAnbYi8tJ9W1tEr6M5KVlWUOHDhgPvnkE3PXXXeZOnXqmL///e8mJyenWvSO16R6KgkqR4cOHTLXXnutGTZsmDfTzf2D8Pzzz5vw8PA8lwT27Nlj4uLizK+//mpLvGfCSXUtTnFtERERkW8isFmzZuX7b6mqc0o9y6IkPw+5bbJ3716zYMECM336dLN582bbYi4rJ9W1tErzM5KcnGweeeQRc+WVV5r4+HjbYi6LmlRPrR1WQsnJyezfv5+MjAwAsrOzvfuysrIAaNCgAYMGDWLr1q18+OGHAPj5+QHgdrtp2LAhu3bt8q6XEhERQffu3WnTpk1lVqVYTqprccqjLRo0aMCuXbsA8PX1BSA6Oppzzz230upRHKfUsyzK8+cBIDw8nGuvvZb77ruP9u3bV2ZViuWkupZWef2M/PHHHwA0adKEJ598kqVLl3LhhRdWZlWK5JR65lISVIzMzEzuueceevXqxaBBgxg8eDDp6en4+vqSmZkJWB9+Wloa8+bN4/bbb6djx4588MEHfPvtt97X2b17N02aNKFFixa4XC67qlMkJ9W1OBXRFlWRU+pZFuXdNi1btrSpJsVzUl1LqyLbpiotAOuUeuZjd1dUVfbRRx+Z1q1bm969e5tvvvnGvPHGG+bss8/Ot2jdSy+9ZBo2bGiGDBlijDHmp59+Mrfccovx9/c3Y8eONXfddZcJDg42M2bMMMZUjbkRTuekuhbHKW3hlHqWhZPaxkl1LS2ntI1T6lkQJUFFuO+++8zf/va3PLNbjho1yjz00EPe56+88opp2bKlmTt3br5FIp9++mkzZswYM2DAALN8+fJKjb20nFTX4jilLZxSz7JwUts4qa6l5ZS2cUo9C+Iy5s9BG+KVk5ODj48PSUlJZGZm0qxZMwB+//13rr/+ekaMGEFUVBQ9evQgKyuL9PR06tSp4z3eGFNtLgM5qa7FcUpbOKWeZeGktnFSXUvLKW3jlHoWya7sq6p5/fXXzRtvvGG+++4777ZTu/Jefvll43K5TM+ePU3v3r1NgwYNzJNPPlktb/d0Ul2L45S2cEo9y8JJbeOkupaWU9rGKfUsKccnQe+9954JCQkxUVFRpmPHjqZJkybmn//8pzEm77pWM2fONP/73/+8J8vcuXNN7dq1zc6dO22JuyycVNfiOKUtnFLPsnBS2ziprqXllLZxSj1Ly9FJ0Ny5c82FF15oXnvtNWOMNZfNK6+8YurUqeNd76awBT63bNlifH1980wbXpU5qa7FcUpbOKWeZeGktnFSXUvLKW3jlHqWhSNvkTd/DoPKzMyke/fu3HrrrYA1l02nTp0466yz2LJlC3ByvpPT/fe//+WKK66gZ8+elRN0GTmprsVxSls4pZ5l4aS2cVJdS8spbeOUep4R+/Kvyrd27Vpz+PBh7/MjR47ky37j4+NNWFiYOXToUL7jf//9d7N9+3Zz5513moiICDNz5kxjTNW8DdBJdS2OU9rCKfUsCye1jZPqWlpOaRun1LM8OCIJ+vjjj03Tpk1N69atTfPmzc3f/vY3k5SU5N1/6u1+06ZNM5dccokxxuRZ7+iXX34xDz/8sGnatKm57LLLquxSAE6qa3Gc0hZOqWdZOKltnFTX0nJK2zilnuWpxidBq1evNu3atTMvvvii+emnn8yrr75qmjRpYsaOHetdATc7O9s7P8J1111X4CrHx48fN999912VngPBSXUtjlPawin1LAsntY2T6lpaTmkbp9SzvNXYJCi3227GjBmmadOmxuPxePdNnz7dXHzxxeYf//iHd1t2drbJyckxrVu3NosXLzbGGLNt2zYzfPhw88cff1Ru8KXkpLoWxylt4ZR6loWT2sZJdS0tp7SNU+pZUWrswOjcCZwSEhI499xzvYu7AYwePZouXbrwxRdfsGnTJgB8fHxYvXo1QUFBdO7cmZiYGC644AIOHjxISEiILXUoKSfVtThOaQun1LMsnNQ2TqpraTmlbZxSz4pSY5KgpUuXMm7cOF566SVWrVrl3X7JJZfw448/kpSUBFgr4tapU4chQ4bgcrlYsmSJt+znn3/Oxo0badu2LUuXLmX58uUsWbKEgICASq9PUZxU1+I4pS2cUs+ycFLbOKmupeWUtnFKPSuN3V1RZ2rv3r1m4MCBJiQkxNxyyy3m/PPPN26326xcudIYY8yJEydMu3btzF133WWMyTsw7NJLL82zQNw///lP06RJEzN//vzKrUQJOamuxXFKWzilnmXhpLZxUl1Lyylt45R6VrZqnQQdO3bMjBo1ygwbNsz89ttv3u0XXXSRGT16tDHGmgBq1qxZxsfHJ99Ar1tuucX06dPH+zw5OblyAi8DJ9W1OE5pC6fUsyyc1DZOqmtpOaVtnFJPO1Try2FBQUEEBAQwevRoWrVqRVZWFgADBw7MMwHU0KFDGTJkCHfeeSfLli3DGENSUhK//vorI0eO9L5ekyZNbKlHSTiprsVxSls4pZ5l4aS2cVJdS8spbeOUetrCvvyrfJw6v0HuKPmRI0eaMWPG5Nl24sQJ06dPHxMSEmL69etnIiIizMUXX1ytRsM7qa7FcUpbOKWeZeGktnFSXUvLKW3jlHpWNpcxf86rXYP06tWL22+/ndGjR2OMIScnB19fX/bt28eGDRtYvXo1LVu2ZMSIEXaHesacVNfiOKUtnFLPsnBS2ziprqXllLZxSj0rlF3ZV0XZsWOHCQ0NNWvWrPFuS09PtzGiiuOkuhbHKW3hlHqWhZPaxkl1LS2ntI1T6lnRqvWYoFOZPzu0fvjhB+rWrUuXLl0AmDx5Mg8++CDJycl2hleunFTX4jilLZxSz7JwUts4qa6l5ZS2cUo9K4tf8UWqh9wJo1atWsUNN9zA0qVLueuuuzh+/DizZ8+uUZNAOamuxXFKWzilnmXhpLZxUl1Lyylt45R6Vhr7OqHK34kTJ0ybNm2My+UyAQEB5plnnrE7pArjpLoWxylt4ZR6loWT2sZJdS0tp7SNU+pZGWrcwOi+fftyzjnnMG3aNAIDA+0Op0I5qa7FcUpbOKWeZeGktnFSXUvLKW3jlHpWtBqXBGVnZ+Pr62t3GJXCSXUtjlPawin1LAsntY2T6lpaTmkbp9SzotW4JEhERESkJGrM3WEiIiIipaEkSERERBxJSZCIiIg4kpIgERERcSQlQSIiIuJISoJERETEkZQEiYiIiCMpCRIRERFHUhIkIiIijqQkSERERBzp/wG1SnbHsRtwTgAAAABJRU5ErkJggg==\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "metadata": { + "tags": [] + }, + "outputs": [], "source": [ - "ipt,jpt = 400,300\n", + "ipt,jpt = 500,200\n", "\n", "plt.figure()\n", "plt.axhline(y=0,linestyle='--',color='k')\n", "plt.plot(ts.dates,ts.timeseries[:,ipt,jpt],'.',markersize=12,label='data')\n", - "plt.plot(ts_rec.dates,ts_rec.timeseries[:,ipt,jpt],'.-',markersize=8,label='reconstruction')\n", + "plt.plot(ts_rec.dates,ts_rec.timeseries[:,ipt,jpt],'.-',\n", + " markersize=8,label='reconstruction')\n", "plt.xticks(rotation=30)\n", "plt.legend()" ] @@ -1977,34 +544,25 @@ "id": "702a17b9-d4ad-4497-b4ef-29d20a3acfd1", "metadata": {}, "source": [ - "Additionally we can show the summertime displacement across the entire region:" + "Additionally we can show the summer time displacement across the entire region:" ] }, { "cell_type": "code", - "execution_count": 36, + "execution_count": null, "id": "2fe36477-3207-42e4-804a-029fefd29178", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "metadata": { + "tags": [] + }, + "outputs": [], "source": [ - "#The fieldsites of Happy Valley and Happy Valley East are too close\n", - "#to plot separately in this step.\n", + "#The fieldsites of Happy Valley and Happy Valley East are too close to plot separately in this step.\n", "labelpoints = [[119, 287], [277, 304], [710, 277]]\n", "labelpointnames = ['HV/HVE','IC','SM']\n", "\n", "plt.figure()\n", - "plt.imshow(ts_rec.timeseries[-1]-ts_rec.timeseries[0],vmin=-0.10,vmax=0.10,cmap='RdBu')\n", + "plt.imshow(ts_rec.timeseries[-1]-ts_rec.timeseries[0],\n", + " vmin=-0.10,vmax=0.10,cmap='RdBu')\n", "plt.colorbar()\n", "for k,name in enumerate(labelpointnames):\n", " pt = labelpoints[k]\n", @@ -2017,1259 +575,564 @@ "id": "2ca46534-2c2b-4bcd-a621-60d33fa33674", "metadata": {}, "source": [ - "\n", - "## 5.3 Re-run Mintpy with field reference points\n", + "\n", + "### 4.3 Compare InSAR and field displacement results\n", "\n", - "We run mintpy with the reference point set to one of the field sites and compare the relative displacements at other sites, which can then be compared to the relative displacments between sites from field observations. If this notebook is running in OpenScienceLab this step will take approximately 7 minutes." + "First we compare the InSAR displacement between the field sites for the given field observations dates" ] }, { "cell_type": "code", - "execution_count": 20, - "id": "66f17868-f6f5-40c8-bd3a-79eab5fd91e8", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "['HV', 'HVE', 'IC', 'SM']\n", - "\n", - "\n", - "\n", - " NOW DOING: HV\n", - "\n", - "\n", - "___________________________________________________________\n", - "\n", - " /## /## /## /## /#######\n", - " | ### /###|__/ | ## | ##__ ##\n", - " | #### /#### /## /####### /###### | ## \\ ## /## /##\n", - " | ## ##/## ##| ##| ##__ ##|_ ##_/ | #######/| ## | ##\n", - " | ## ###| ##| ##| ## \\ ## | ## | ##____/ | ## | ##\n", - " | ##\\ # | ##| ##| ## | ## | ## /##| ## | ## | ##\n", - " | ## \\/ | ##| ##| ## | ## | ####/| ## | #######\n", - " |__/ |__/|__/|__/ |__/ \\___/ |__/ \\____ ##\n", - " /## | ##\n", - " | ######/\n", - " Miami InSAR Time-series software in Python \\______/\n", - " MintPy 1.5.1, 2023-01-03\n", - "___________________________________________________________\n", - "\n", - "--RUN-at-2024-03-19 18:26:19.536265--\n", - "Current directory: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023\n", - "Run routine processing with smallbaselineApp.py on steps: ['load_data', 'modify_network', 'reference_point', 'quick_overview', 'correct_unwrap_error', 'invert_network', 'correct_LOD', 'correct_SET', 'correct_troposphere', 'deramp', 'correct_topography', 'residual_RMS', 'reference_date', 'velocity', 'geocode', 'google_earth', 'hdfeos5']\n", - "Remaining steps: ['modify_network', 'reference_point', 'quick_overview', 'correct_unwrap_error', 'invert_network', 'correct_LOD', 'correct_SET', 'correct_troposphere', 'deramp', 'correct_topography', 'residual_RMS', 'reference_date', 'velocity', 'geocode', 'google_earth', 'hdfeos5']\n", - "--------------------------------------------------\n", - "Project name: NorthSlopeEastD102_2023\n", - "Go to work directory: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023\n", - "read custom template file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/MintPy/NorthSlopeEastD102_2023.cfg\n", - "update default template based on input custom template\n", - "No new option value found, skip updating /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg\n", - "copy NorthSlopeEastD102_2023.cfg to inputs directory for backup.\n", - "copy NorthSlopeEastD102_2023.cfg to pic directory for backup.\n", - "read default template file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg\n", - "\n", - "\n", - "******************** step - load_data ********************\n", - "\n", - "load_data.py --template /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/MintPy/NorthSlopeEastD102_2023.cfg --project NorthSlopeEastD102_2023\n", - "processor : hyp3\n", - "SAR platform/sensor : unknown from project name \"NorthSlopeEastD102_2023\"\n", - "--------------------------------------------------\n", - "prepare metadata files for hyp3 products\n", - "prep_hyp3.py \"/home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/products/*/*_unw_phase_clipped.tif\"\n", - "prep_hyp3.py \"/home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/products/*/*_corr_clipped.tif\"\n", - "prep_hyp3.py \"/home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/products/*/*_dem_clipped.tif\"\n", - "prep_hyp3.py \"/home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/products/*/*_lv_theta_clipped.tif\"\n", - "prep_hyp3.py \"/home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/products/*/*_lv_phi_clipped.tif\"\n", - "prep_hyp3.py \"/home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/products/*/*_water_mask_clipped.tif\"\n", - "--------------------------------------------------\n", - "updateMode : True\n", - "compression: None\n", - "multilook x/ystep: 1/1\n", - "multilook method : nearest\n", - "input bounding box of interest in lalo: (641941.0, 7686754.0, 679925.0, 7620213.0)\n", - "box to read for datasets in y/x: (2996, 993, 3471, 1825)\n", - "--------------------------------------------------\n", - "searching geometry files info\n", - "input data files:\n", - "height : /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/products/S1AA_20230603T164401_20230615T164402_VVP012_INT80_G_ueF_C9F1/S1AA_20230603T164401_20230615T164402_VVP012_INT80_G_ueF_C9F1_dem_clipped.tif\n", - "incidenceAngle : /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/products/S1AA_20230603T164401_20230615T164402_VVP012_INT80_G_ueF_C9F1/S1AA_20230603T164401_20230615T164402_VVP012_INT80_G_ueF_C9F1_lv_theta_clipped.tif\n", - "azimuthAngle : /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/products/S1AA_20230603T164401_20230615T164402_VVP012_INT80_G_ueF_C9F1/S1AA_20230603T164401_20230615T164402_VVP012_INT80_G_ueF_C9F1_lv_phi_clipped.tif\n", - "waterMask : /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/products/S1AA_20230603T164401_20230615T164402_VVP012_INT80_G_ueF_C9F1/S1AA_20230603T164401_20230615T164402_VVP012_INT80_G_ueF_C9F1_water_mask_clipped.tif\n", - "All datasets exists in file geometryGeo.h5 with same size as required, no need to re-load.\n", - "--------------------------------------------------\n", - "searching interferogram pairs info\n", - "input data files:\n", - "unwrapPhase : /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/products/*/*_unw_phase_clipped.tif\n", - "coherence : /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/products/*/*_corr_clipped.tif\n", - "number of unwrapPhase : 17\n", - "number of coherence : 17\n", - "All date12 exists in file ifgramStack.h5 with same size as required, no need to re-load.\n", - "--------------------------------------------------\n", - "searching ionosphere pairs info\n", - "input data files:\n", - "WARNING: No data files found for the required dataset: ['unwrapPhase']! Skip loading for ionosphere stack.\n", - "--------------------------------------------------\n", - "searching offset pairs info\n", - "input data files:\n", - "WARNING: No data files found for the required dataset: ['rangeOffset', 'azimuthOffset']! Skip loading for offset stack.\n", - "time used: 00 mins 0.4 secs.\n", - "\n", - "No lookup table (longitude or rangeCoord) found in files.\n", - "Input data seems to be geocoded. Lookup file not needed.\n", - "Loaded dataset are processed by InSAR software: hyp3\n", - "Loaded dataset are in GEO coordinates\n", - "Interferogram Stack: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5\n", - "Geometry File : /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/geometryGeo.h5\n", - "Lookup Table File : None\n", - "--------------------------------------------------\n", - "updating metadata based on custom template file NorthSlopeEastD102_2023.cfg for file: ifgramStack.h5\n", - "updating metadata based on custom template file NorthSlopeEastD102_2023.cfg for file: geometryGeo.h5\n", - "\n", - "\n", - "******************** step - modify_network ********************\n", - "Input data seems to be geocoded. Lookup file not needed.\n", - "generate /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/waterMask.h5 from /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/geometryGeo.h5 for conveniency\n", - "['/home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/waterMask.h5'] exists and is newer than ['/home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/geometryGeo.h5'] --> skip.\n", - "\n", - "modify_network.py /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5 -t /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg\n", - "read options from template file: smallbaselineApp.cfg\n", - "No lookup table (longitude or rangeCoord) found in files.\n", - "No input option found to remove interferogram\n", - "Keep all interferograms by enable --reset option\n", - "--------------------------------------------------\n", - "reset dataset 'dropIfgram' to True for all interferograms for file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5\n", - "All dropIfgram are already True, no need to reset.\n", - "\n", - "plot_network.py /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5 -t /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg --nodisplay -d coherence -v 0.2 1.0\n", - "read options from template file: smallbaselineApp.cfg\n", - "read temporal/spatial baseline info from file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5\n", - "open ifgramStack file: ifgramStack.h5\n", - "calculating spatial mean of coherence in file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5 ...\n", - "read mask from file: waterMask.h5\n", - "[==================================================] 17/17 0s / 0s\n", - "write average value in space into text file: coherenceSpatialAvg.txt\n", - "number of acquisitions: 10\n", - "number of interferograms: 17\n", - "shift all perp baseline by -85.71686553955078 to zero mean for plotting\n", - "--------------------------------------------------\n", - "number of interferograms marked as drop: 0\n", - "number of interferograms marked as keep: 17\n", - "number of acquisitions marked as drop: 0\n", - "save figure to pbaseHistory.pdf\n", - "save figure to coherenceMatrix.pdf\n", - "save figure to coherenceHistory.pdf\n", - "max perpendicular baseline: 170.70 m\n", - "max temporal baseline: 24.0 days\n", - "showing coherence\n", - "data range: [0.63075197, 0.9469921]\n", - "display range: [0.2, 1.0]\n", - "save figure to network.pdf\n", - "\n", - "\n", - "******************** step - reference_point ********************\n", - "Input data seems to be geocoded. Lookup file not needed.\n", - "\n", - "generate_mask.py /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5 --nonzero -o /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/maskConnComp.h5 --update\n", - "input ifgramStack file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5\n", - "--------------------------------------------------\n", - "update mode: ON\n", - "1) output file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/maskConnComp.h5 already exists.\n", - "2) output file is newer than input dataset: unwrapPhase.\n", - "run or skip: skip.\n", - "\n", - "temporal_average.py /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5 --dataset coherence -o /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/avgSpatialCoh.h5 --update\n", - "--------------------------------------------------\n", - "update mode: ON\n", - "1) output file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/avgSpatialCoh.h5 already exists.\n", - "2) output file is newer than input dataset: coherence.\n", - "run or skip: skip.\n", - "Input data seems to be geocoded. Lookup file not needed.\n", - "\n", - "reference_point.py /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5 -t /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg -c /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/avgSpatialCoh.h5\n", - "--------------------------------------------------\n", - "reading reference info from template: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg\n", - "input reference point in lat/lon: (7677215.0, 664946.0)\n", - "input reference point in y/x: (119, 287)\n", - "mask: maskConnComp.h5\n", - "--------------------------------------------------\n", - "SAME reference pixel is already selected/saved in file, skip updating.\n", - "\n", - "\n", - "******************** step - quick_overview ********************\n", - "Input data seems to be geocoded. Lookup file not needed.\n", - "\n", - "temporal_average.py /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5 --dataset unwrapPhase -o /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/avgPhaseVelocity.h5 --update\n", - "--------------------------------------------------\n", - "update mode: ON\n", - "1) output file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/avgPhaseVelocity.h5 already exists.\n", - "2) output file is newer than input dataset: unwrapPhase.\n", - "run or skip: skip.\n", - "\n", - "unwrap_error_phase_closure.py /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5 --water-mask /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/waterMask.h5 --action calculate --update\n", - "update mode: ON\n", - "1) output file \"/home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/numTriNonzeroIntAmbiguity.h5\" already exists\n", - "2) output file is newer than input dataset\n", - "3) all key configurations are the same: ['REF_Y', 'REF_X']\n", - "run or skip: skip.\n", - "time used: 00 mins 0.0 secs\n", - "Done.\n", - "\n", - "\n", - "******************** step - correct_unwrap_error ********************\n", - "phase-unwrapping error correction is OFF.\n", - "\n", - "\n", - "******************** step - invert_network ********************\n", - "Input data seems to be geocoded. Lookup file not needed.\n", - "\n", - "ifgram_inversion.py /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5 -t /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg --update\n", - "read input option from template file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg\n", - "use dataset \"unwrapPhase\" by default\n", - "--------------------------------------------------\n", - "update mode: ON\n", - "1) output files already exist: ['timeseries.h5', 'temporalCoherence.h5', 'numInvIfgram.h5'].\n", - "2) output dataset is newer than input dataset: unwrapPhase.\n", - "3) all key configuration parameters are the same: ['obsDatasetName', 'numIfgram', 'weightFunc', 'maskDataset', 'maskThreshold', 'minRedundancy', 'minNormVelocity'].\n", - "run or skip: skip.\n", - "Input data seems to be geocoded. Lookup file not needed.\n", - "\n", - "generate_mask.py /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/temporalCoherence.h5 -m 0.7 -o /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/maskTempCoh.h5\n", - "update mode: ON\n", - "1) output file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/maskTempCoh.h5 already exists and newer than input file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/temporalCoherence.h5\n", - "2) all key configuration parameters are the same: ['mintpy.networkInversion.minTempCoh', 'mintpy.networkInversion.shadowMask']\n", - "run or skip: skip\n", - "number of reliable pixels: 337443\n", - "\n", - "\n", - "******************** step - correct_LOD ********************\n", - "Input data seems to be geocoded. Lookup file not needed.\n", - "No local oscillator drift correction is needed for Sen.\n", - "\n", - "\n", - "******************** step - correct_SET ********************\n", - "Input data seems to be geocoded. Lookup file not needed.\n", - "No solid Earth tides correction.\n", - "\n", - "\n", - "******************** step - correct_troposphere ********************\n", - "Input data seems to be geocoded. Lookup file not needed.\n", - "Atmospheric correction using Weather Re-analysis dataset (PyAPS, Jolivet et al., 2011)\n", - "Weather Re-analysis dataset: ERA5\n", - "['/home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseries_ERA5.h5'] exists and is newer than ['/home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseries.h5', './inputs/ERA5.h5'] --> skip.\n", - "\n", - "\n", - "******************** step - deramp ********************\n", - "No phase ramp removal.\n", - "\n", - "\n", - "******************** step - correct_topography ********************\n", - "Input data seems to be geocoded. Lookup file not needed.\n", - "\n", - "dem_error.py /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseries_ERA5.h5 -t /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg -o /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseries_ERA5_demErr.h5 --update -g /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/geometryGeo.h5\n", - "read options from template file: smallbaselineApp.cfg\n", - "--------------------------------------------------\n", - "update mode: ON\n", - "1) output file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseries_ERA5_demErr.h5 already exists.\n", - "2) output file is NOT newer than input file: ['/home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseries_ERA5.h5', '/home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/geometryGeo.h5'].\n", - "run or skip: run.\n", - "save the original settings of ['OMP_NUM_THREADS', 'OPENBLAS_NUM_THREADS', 'MKL_NUM_THREADS', 'NUMEXPR_NUM_THREADS', 'VECLIB_MAXIMUM_THREADS']\n", - "set OMP_NUM_THREADS = 1\n", - "set OPENBLAS_NUM_THREADS = 1\n", - "set MKL_NUM_THREADS = 1\n", - "set NUMEXPR_NUM_THREADS = 1\n", - "set VECLIB_MAXIMUM_THREADS = 1\n", - "open timeseries file: timeseries_ERA5.h5\n", - "--------------------------------------------------------------------------------\n", - "correct topographic phase residual (DEM error) (Fattahi & Amelung, 2013, IEEE-TGRS)\n", - "ordinal least squares (OLS) inversion with L2-norm minimization on: phase\n", - "temporal deformation model: polynomial order = 2\n", - "--------------------------------------------------------------------------------\n", - "add/update the following configuration metadata to file:\n", - "['polyOrder', 'phaseVelocity', 'stepFuncDate', 'excludeDate']\n", - "--------------------------------------------------\n", - "create HDF5 file: demErr.h5 with w mode\n", - "create dataset : dem of in size of (832, 475) with compression = None\n", - "close HDF5 file: demErr.h5\n", - "--------------------------------------------------\n", - "grab dataset structure from ref_file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseries_ERA5.h5\n", - "create HDF5 file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseries_ERA5_demErr.h5 with w mode\n", - "create dataset : bperp of float32 in size of (10,) with compression = None\n", - "create dataset : date of |S8 in size of (10,) with compression = None\n", - "create dataset : timeseries of float32 in size of (10, 832, 475) with compression = None\n", - "close HDF5 file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseries_ERA5_demErr.h5\n", - "--------------------------------------------------\n", - "grab dataset structure from ref_file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseries_ERA5.h5\n", - "create HDF5 file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseriesResidual.h5 with w mode\n", - "create dataset : bperp of float32 in size of (10,) with compression = None\n", - "create dataset : date of |S8 in size of (10,) with compression = None\n", - "create dataset : timeseries of float32 in size of (10, 832, 475) with compression = None\n", - "close HDF5 file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseriesResidual.h5\n", - "open geometry file: geometryGeo.h5\n", - "read 2D incidenceAngle, slantRangeDistance from geometry file: geometryGeo.h5\n", - "read mean bperp from timeseries file\n", - "skip pixels with ZERO in ALL acquisitions\n", - "skip pixels with NaN in ANY acquisitions\n", - "skip pixels with ZERO temporal coherence\n", - "skip pixels with ZERO / NaN value in incidenceAngle / slantRangeDistance\n", - "number of pixels to invert: 0 out of 395200 (0.0%)\n", - "--------------------------------------------------\n", - "open HDF5 file demErr.h5 in a mode\n", - "writing dataset /dem block: [0, 832, 0, 475]\n", - "close HDF5 file demErr.h5.\n", - "--------------------------------------------------\n", - "open HDF5 file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseries_ERA5_demErr.h5 in a mode\n", - "writing dataset /timeseries block: [0, 10, 0, 832, 0, 475]\n", - "close HDF5 file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseries_ERA5_demErr.h5.\n", - "--------------------------------------------------\n", - "open HDF5 file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseriesResidual.h5 in a mode\n", - "writing dataset /timeseries block: [0, 10, 0, 832, 0, 475]\n", - "close HDF5 file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseriesResidual.h5.\n", - "roll back to the original settings of ['OMP_NUM_THREADS', 'OPENBLAS_NUM_THREADS', 'MKL_NUM_THREADS', 'NUMEXPR_NUM_THREADS', 'VECLIB_MAXIMUM_THREADS']\n", - "remove env variable OMP_NUM_THREADS\n", - "remove env variable OPENBLAS_NUM_THREADS\n", - "remove env variable MKL_NUM_THREADS\n", - "remove env variable NUMEXPR_NUM_THREADS\n", - "remove env variable VECLIB_MAXIMUM_THREADS\n", - "time used: 00 mins 0.4 secs.\n", - "\n", - "\n", - "******************** step - residual_RMS ********************\n", - "\n", - "timeseries_rms.py timeseriesResidual.h5 -t /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg\n", - "read options from template file: smallbaselineApp.cfg\n", - "remove quadratic ramp from file: timeseriesResidual.h5\n", - "read mask file: maskTempCoh.h5\n", - "--------------------------------------------------\n", - "grab metadata from ref_file: timeseriesResidual.h5\n", - "grab dataset structure from ref_file: timeseriesResidual.h5\n", - "create HDF5 file: timeseriesResidual_ramp.h5 with w mode\n", - "create dataset : bperp of float32 in size of (10,) with compression = None\n", - "create dataset : date of |S8 in size of (10,) with compression = None\n", - "create dataset : timeseries of float32 in size of (10, 832, 475) with compression = None\n", - "close HDF5 file: timeseriesResidual_ramp.h5\n", - "estimating phase ramp one date at a time ...\n", - "[==================================================] 10/10 0s / 0s\n", - "finished writing to file: timeseriesResidual_ramp.h5\n", - "time used: 00 mins 0.6 secs.\n", - "\n", - "calculating residual RMS for each epoch from file: timeseriesResidual_ramp.h5\n", - "read mask from file: maskTempCoh.h5\n", - "reading timeseries data from file: timeseriesResidual_ramp.h5 ...\n", - "[==================================================] 10/10 0s / 0s\n", - "save timeseries RMS to text file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/rms_timeseriesResidual_ramp.txt\n", - "read timeseries residual RMS from file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/rms_timeseriesResidual_ramp.txt\n", - "--------------------------------------------------\n", - "date with min RMS: 20230603 - 0.0000\n", - "save date to file: reference_date.txt\n", - "--------------------------------------------------\n", - "date(s) with RMS > 3.0 * median RMS (0.0000)\n", - "None.\n", - "/home/jovyan/.local/envs/insar_analysis/lib/python3.8/site-packages/mintpy/utils/plot.py:497: UserWarning: Attempting to set identical low and high ylims makes transformation singular; automatically expanding.\n", - " ax.set_ylim([ymin, ymax])\n", - "save figure to file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/rms_timeseriesResidual_ramp.pdf\n", - "\n", - "\n", - "******************** step - reference_date ********************\n", - "\n", - "reference_date.py -t /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseries.h5 /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseries_ERA5.h5 /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseries_ERA5_demErr.h5\n", - "read reference date from file: reference_date.txt\n", - "input reference date: 20230603\n", - "--------------------------------------------------\n", - "change reference date for file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseries.h5\n", - "input refDate is the same as the existing REF_DATE.\n", - "Nothing to be done.\n", - "--------------------------------------------------\n", - "change reference date for file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseries_ERA5.h5\n", - "input refDate is the same as the existing REF_DATE.\n", - "Nothing to be done.\n", - "--------------------------------------------------\n", - "change reference date for file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseries_ERA5_demErr.h5\n", - "input refDate is the same as the existing REF_DATE.\n", - "Nothing to be done.\n", - "time used: 00 mins 3.0 secs.\n", - "\n", - "\n", - "******************** step - velocity ********************\n", - "\n", - "timeseries2velocity.py /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseries_ERA5_demErr.h5 -t /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg -o /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/velocity.h5 --update\n", - "read options from template file: smallbaselineApp.cfg\n", - "update mode: ON\n", - "1) output file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/velocity.h5 already exists.\n", - "2) output file is NOT newer than input file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseries_ERA5_demErr.h5.\n", - "run or skip: run.\n", - "open timeseries file: timeseries_ERA5_demErr.h5\n", - "exclude date: []\n", - "--------------------------------------------------\n", - "dates from input file: 10\n", - "['20230603', '20230615', '20230627', '20230709', '20230721', '20230802', '20230814', '20230826', '20230907', '20230919']\n", - "--------------------------------------------------\n", - "using all dates to calculate the time function\n", - "--------------------------------------------------\n", - "estimate deformation model with the following assumed time functions:\n", - " polynomial : 1\n", - " periodic : []\n", - " stepDate : []\n", - " exp : {}\n", - " log : {}\n", - "add/update the following configuration metadata:\n", - "['startDate', 'endDate', 'excludeDate', 'polynomial', 'periodic', 'stepDate', 'exp', 'log', 'uncertaintyQuantification', 'timeSeriesCovFile', 'bootstrapCount']\n", - "--------------------------------------------------\n", - "create HDF5 file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/velocity.h5 with w mode\n", - "create dataset : intercept of in size of (832, 475) with compression = None\n", - "create dataset : interceptStd of in size of (832, 475) with compression = None\n", - "create dataset : velocity of in size of (832, 475) with compression = None\n", - "create dataset : velocityStd of in size of (832, 475) with compression = None\n", - "create dataset : residue of in size of (832, 475) with compression = None\n", - "add /intercept attribute: UNIT = m\n", - "add /interceptStd attribute: UNIT = m\n", - "add /velocity attribute: UNIT = m/year\n", - "add /velocityStd attribute: UNIT = m/year\n", - "add /residue attribute: UNIT = m\n", - "close HDF5 file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/velocity.h5\n", - "reading data from file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/timeseries_ERA5_demErr.h5 ...\n", - "skip pixels with zero/nan value in all acquisitions\n", - "number of pixels to invert: 1 out of 395200 (0.0%)\n", - "estimating time functions via linalg.lstsq ...\n", - "estimating time functions STD from time-series fitting residual ...\n", - "--------------------------------------------------\n", - "open HDF5 file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/velocity.h5 in a mode\n", - "writing dataset /intercept block: [0, 832, 0, 475]\n", - "close HDF5 file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/velocity.h5.\n", - "--------------------------------------------------\n", - "open HDF5 file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/velocity.h5 in a mode\n", - "writing dataset /interceptStd block: [0, 832, 0, 475]\n", - "close HDF5 file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/velocity.h5.\n", - "--------------------------------------------------\n", - "open HDF5 file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/velocity.h5 in a mode\n", - "writing dataset /velocity block: [0, 832, 0, 475]\n", - "close HDF5 file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/velocity.h5.\n", - "--------------------------------------------------\n", - "open HDF5 file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/velocity.h5 in a mode\n", - "writing dataset /velocityStd block: [0, 832, 0, 475]\n", - "close HDF5 file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/velocity.h5.\n", - "--------------------------------------------------\n", - "open HDF5 file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/velocity.h5 in a mode\n", - "writing dataset /residue block: [0, 832, 0, 475]\n", - "close HDF5 file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/velocity.h5.\n", - "time used: 00 mins 0.1 secs.\n", - "\n", - "timeseries2velocity.py /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ERA5.h5 -t /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg -o /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/velocityERA5.h5 --update --ref-date 20230603 --ref-yx 119 287\n", - "read options from template file: smallbaselineApp.cfg\n", - "update mode: ON\n", - "1) output file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/velocityERA5.h5 NOT found.\n", - "run or skip: run.\n", - "open timeseries file: ERA5.h5\n", - "Traceback (most recent call last):\n", - " File \"/home/jovyan/.local/envs/insar_analysis/bin/smallbaselineApp.py\", line 10, in \n", - " sys.exit(main())\n", - " File \"/home/jovyan/.local/envs/insar_analysis/lib/python3.8/site-packages/mintpy/cli/smallbaselineApp.py\", line 208, in main\n", - " run_smallbaselineApp(inps)\n", - " File \"/home/jovyan/.local/envs/insar_analysis/lib/python3.8/site-packages/mintpy/smallbaselineApp.py\", line 1117, in run_smallbaselineApp\n", - " app.run(steps=inps.runSteps)\n", - " File \"/home/jovyan/.local/envs/insar_analysis/lib/python3.8/site-packages/mintpy/smallbaselineApp.py\", line 913, in run\n", - " self.run_timeseries2velocity(sname)\n", - " File \"/home/jovyan/.local/envs/insar_analysis/lib/python3.8/site-packages/mintpy/smallbaselineApp.py\", line 750, in run_timeseries2velocity\n", - " mintpy.cli.timeseries2velocity.main(iargs)\n", - " File \"/home/jovyan/.local/envs/insar_analysis/lib/python3.8/site-packages/mintpy/cli/timeseries2velocity.py\", line 233, in main\n", - " run_timeseries2time_func(inps)\n", - " File \"/home/jovyan/.local/envs/insar_analysis/lib/python3.8/site-packages/mintpy/timeseries2velocity.py\", line 138, in run_timeseries2time_func\n", - " inps = read_date_info(inps)\n", - " File \"/home/jovyan/.local/envs/insar_analysis/lib/python3.8/site-packages/mintpy/timeseries2velocity.py\", line 92, in read_date_info\n", - " ts_obj.open()\n", - " File \"/home/jovyan/.local/envs/insar_analysis/lib/python3.8/site-packages/mintpy/objects/stack.py\", line 174, in open\n", - " self.get_metadata()\n", - " File \"/home/jovyan/.local/envs/insar_analysis/lib/python3.8/site-packages/mintpy/objects/stack.py\", line 216, in get_metadata\n", - " self.metadata['REF_DATE'] = dateList[0]\n", - "IndexError: list index out of range\n", - "\n", - " performing spline reconstruction\n", - "119, 287\n", - "118, 290\n", - "277, 304\n", - "710, 277\n", - "\n", - "\n", - "\n", - " NOW DOING: HVE\n", - "\n", - "MintPy version 1.5.1, date 2023-01-03\n", - "--RUN-at-2024-03-19 18:26:48.546594--\n", - "Current directory: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023\n", - "Run routine processing with smallbaselineApp.py on steps: ['reference_point']\n", - "Remaining steps: ['quick_overview', 'correct_unwrap_error', 'invert_network', 'correct_LOD', 'correct_SET', 'correct_troposphere', 'deramp', 'correct_topography', 'residual_RMS', 'reference_date', 'velocity', 'geocode', 'google_earth', 'hdfeos5']\n", - "--------------------------------------------------\n", - "Project name: NorthSlopeEastD102_2023\n", - "Go to work directory: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023\n", - "read custom template file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/MintPy/NorthSlopeEastD102_2023.cfg\n", - "update default template based on input custom template\n", - " mintpy.reference.lalo: 7677215, 664946 --> 7677290, 665175\n", - "copy NorthSlopeEastD102_2023.cfg to inputs directory for backup.\n", - "copy smallbaselineApp.cfg to inputs directory for backup.\n", - "copy NorthSlopeEastD102_2023.cfg to pic directory for backup.\n", - "copy smallbaselineApp.cfg to pic directory for backup.\n", - "read default template file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg\n", - "\n", - "\n", - "******************** step - reference_point ********************\n", - "Input data seems to be geocoded. Lookup file not needed.\n", - "\n", - "generate_mask.py /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5 --nonzero -o /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/maskConnComp.h5 --update\n", - "input ifgramStack file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5\n", - "--------------------------------------------------\n", - "update mode: ON\n", - "1) output file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/maskConnComp.h5 already exists.\n", - "2) output file is newer than input dataset: unwrapPhase.\n", - "run or skip: skip.\n", - "\n", - "temporal_average.py /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5 --dataset coherence -o /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/avgSpatialCoh.h5 --update\n", - "--------------------------------------------------\n", - "update mode: ON\n", - "1) output file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/avgSpatialCoh.h5 already exists.\n", - "2) output file is newer than input dataset: coherence.\n", - "run or skip: skip.\n", - "Input data seems to be geocoded. Lookup file not needed.\n", - "\n", - "reference_point.py /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5 -t /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg -c /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/avgSpatialCoh.h5\n", - "--------------------------------------------------\n", - "reading reference info from template: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg\n", - "input reference point in lat/lon: (7677290.0, 665175.0)\n", - "input reference point in y/x: (118, 290)\n", - "mask: maskConnComp.h5\n", - "--------------------------------------------------\n", - "calculate the temporal average of unwrapPhase in file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5 ...\n", - "[==================================================] lines 832/832 0s / 0s\n", - "Add/update ref_x/y attribute to file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5\n", - "{'REF_Y': '118', 'REF_X': '290', 'REF_LAT': '7677320.0', 'REF_LON': '665160.0'}\n", - "touch avgSpatialCoh.h5\n", - "touch maskConnComp.h5\n", - "Go back to directory: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023\n", - "\n", - "################################################\n", - " Normal end of smallbaselineApp processing!\n", - "################################################\n", - "Time used: 00 mins 0.5 secs\n", - "\n", - "MintPy version 1.5.1, date 2023-01-03\n", - "--RUN-at-2024-03-19 18:26:50.961527--\n", - "Current directory: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023\n", - "Run routine processing with smallbaselineApp.py on steps: ['invert_network']\n", - "Remaining steps: ['correct_LOD', 'correct_SET', 'correct_troposphere', 'deramp', 'correct_topography', 'residual_RMS', 'reference_date', 'velocity', 'geocode', 'google_earth', 'hdfeos5']\n", - "--------------------------------------------------\n", - "Project name: NorthSlopeEastD102_2023\n", - "Go to work directory: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023\n", - "read custom template file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/MintPy/NorthSlopeEastD102_2023.cfg\n", - "update default template based on input custom template\n", - "No new option value found, skip updating /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg\n", - "read default template file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg\n", - "\n", - "\n", - "******************** step - invert_network ********************\n", - "Input data seems to be geocoded. Lookup file not needed.\n", - "\n", - "ifgram_inversion.py /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5 -t /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg --update\n", - "read input option from template file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg\n", - "use dataset \"unwrapPhase\" by default\n", - "--------------------------------------------------\n", - "update mode: ON\n", - "1) output files already exist: ['timeseries.h5', 'temporalCoherence.h5', 'numInvIfgram.h5'].\n", - "2) output dataset is newer than input dataset: unwrapPhase.\n", - "3) NOT all the metadata are the same: ['REF_Y', 'REF_X']\n", - "run or skip: run.\n", - "save the original settings of ['OMP_NUM_THREADS', 'OPENBLAS_NUM_THREADS', 'MKL_NUM_THREADS', 'NUMEXPR_NUM_THREADS', 'VECLIB_MAXIMUM_THREADS']\n", - "set OMP_NUM_THREADS = 1\n", - "set OPENBLAS_NUM_THREADS = 1\n", - "set MKL_NUM_THREADS = 1\n", - "set NUMEXPR_NUM_THREADS = 1\n", - "set VECLIB_MAXIMUM_THREADS = 1\n", - "reference pixel in y/x: (118, 290) from dataset: unwrapPhase\n", - "-------------------------------------------------------------------------------\n", - "least-squares solution with L2 min-norm on: deformation velocity\n", - "minimum redundancy: 1.0\n", - "weight function: var\n", - "calculate covariance: False \n", - "mask: no\n", - "-------------------------------------------------------------------------------\n", - "number of interferograms: 17\n", - "number of acquisitions : 10\n", - "number of lines : 832\n", - "number of columns : 475\n", - "--------------------------------------------------\n", - "create HDF5 file: timeseries.h5 with w mode\n", - "create dataset : date of |S8 in size of (10,) with compression = None\n", - "create dataset : bperp of in size of (10,) with compression = None\n", - "create dataset : timeseries of in size of (10, 832, 475) with compression = None\n", - "close HDF5 file: timeseries.h5\n", - "--------------------------------------------------\n", - "create HDF5 file: temporalCoherence.h5 with w mode\n", - "create dataset : temporalCoherence of in size of (832, 475) with compression = None\n", - "close HDF5 file: temporalCoherence.h5\n", - "--------------------------------------------------\n", - "create HDF5 file: numInvIfgram.h5 with w mode\n", - "create dataset : mask of in size of (832, 475) with compression = None\n", - "close HDF5 file: numInvIfgram.h5\n", - "calculating weight from spatial coherence ...\n", - "reading coherence in (0, 0, 475, 832) * 17 ...\n", - "convert coherence to weight in chunks of 100000 pixels: 4 chunks in total ...\n", - "convert coherence to weight using inverse of phase variance\n", - " with phase PDF for distributed scatterers from Tough et al. (1995)\n", - " number of independent looks L=41\n", - "chunk 1 / 4\n", - "chunk 2 / 4\n", - "chunk 3 / 4\n", - "chunk 4 / 4\n", - "reading unwrapPhase in (0, 0, 475, 832) * 17 ...\n", - "use input reference value\n", - "convert zero value in unwrapPhase to NaN (no-data value)\n", - "skip pixels (on the water) with zero value in file: waterMask.h5\n", - "skip pixels with unwrapPhase = NaN in all interferograms\n", - "skip pixels with zero value in file: avgSpatialCoh.h5\n", - "number of pixels to invert: 359143 out of 395200 (90.9%)\n", - "estimating time-series via WLS pixel-by-pixel ...\n", - "[==================================================] 359143/359143 pixels 85s / 1s\n", - "converting LOS phase unit from radian to meter\n", - "--------------------------------------------------\n", - "open HDF5 file timeseries.h5 in a mode\n", - "writing dataset /timeseries block: [0, 10, 0, 832, 0, 475]\n", - "close HDF5 file timeseries.h5.\n", - "--------------------------------------------------\n", - "open HDF5 file temporalCoherence.h5 in a mode\n", - "writing dataset /temporalCoherence block: [0, 832, 0, 475]\n", - "close HDF5 file temporalCoherence.h5.\n", - "--------------------------------------------------\n", - "open HDF5 file numInvIfgram.h5 in a mode\n", - "writing dataset /mask block: [0, 832, 0, 475]\n", - "close HDF5 file numInvIfgram.h5.\n", - "--------------------------------------------------\n", - "update values on the reference pixel: (118, 290)\n", - "set temporalCoherence on the reference pixel to 1.\n", - "set # of observations on the reference pixel as 17\n", - "roll back to the original settings of ['OMP_NUM_THREADS', 'OPENBLAS_NUM_THREADS', 'MKL_NUM_THREADS', 'NUMEXPR_NUM_THREADS', 'VECLIB_MAXIMUM_THREADS']\n", - "remove env variable OMP_NUM_THREADS\n", - "remove env variable OPENBLAS_NUM_THREADS\n", - "remove env variable MKL_NUM_THREADS\n", - "remove env variable NUMEXPR_NUM_THREADS\n", - "remove env variable VECLIB_MAXIMUM_THREADS\n", - "time used: 01 mins 27.7 secs.\n", - "\n", - "Input data seems to be geocoded. Lookup file not needed.\n", - "\n", - "generate_mask.py /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/temporalCoherence.h5 -m 0.7 -o /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/maskTempCoh.h5\n", - "update mode: ON\n", - "run or skip: run\n", - "input temporalCoherence file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/temporalCoherence.h5\n", - "read /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/temporalCoherence.h5\n", - "create initial mask with the same size as the input file and all = 1\n", - "all pixels with nan value = 0\n", - "exclude pixels with value < 0.7\n", - "delete exsited file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/maskTempCoh.h5\n", - "create HDF5 file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/maskTempCoh.h5 with w mode\n", - "create dataset /mask of bool in size of (832, 475) with compression=None\n", - "finished writing to /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/maskTempCoh.h5\n", - "time used: 00 mins 0.0 secs.\n", - "number of reliable pixels: 336742\n", - "Go back to directory: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023\n", - "\n", - "################################################\n", - " Normal end of smallbaselineApp processing!\n", - "################################################\n", - "Time used: 01 mins 28.8 secs\n", - "\n", - "\n", - " performing spline reconstruction\n", - "119, 287\n", - "118, 290\n", - "277, 304\n", - "710, 277\n", - "\n", - "\n", - "\n", - " NOW DOING: IC\n", - "\n", - "MintPy version 1.5.1, date 2023-01-03\n", - "--RUN-at-2024-03-19 18:28:21.914872--\n", - "Current directory: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023\n", - "Run routine processing with smallbaselineApp.py on steps: ['reference_point']\n", - "Remaining steps: ['quick_overview', 'correct_unwrap_error', 'invert_network', 'correct_LOD', 'correct_SET', 'correct_troposphere', 'deramp', 'correct_topography', 'residual_RMS', 'reference_date', 'velocity', 'geocode', 'google_earth', 'hdfeos5']\n", - "--------------------------------------------------\n", - "Project name: NorthSlopeEastD102_2023\n", - "Go to work directory: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023\n", - "read custom template file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/MintPy/NorthSlopeEastD102_2023.cfg\n", - "update default template based on input custom template\n", - " mintpy.reference.lalo: 7677290, 665175 --> 7664601, 666290\n", - "copy NorthSlopeEastD102_2023.cfg to inputs directory for backup.\n", - "copy smallbaselineApp.cfg to inputs directory for backup.\n", - "copy NorthSlopeEastD102_2023.cfg to pic directory for backup.\n", - "copy smallbaselineApp.cfg to pic directory for backup.\n", - "read default template file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg\n", - "\n", - "\n", - "******************** step - reference_point ********************\n", - "Input data seems to be geocoded. Lookup file not needed.\n", - "\n", - "generate_mask.py /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5 --nonzero -o /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/maskConnComp.h5 --update\n", - "input ifgramStack file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5\n", - "--------------------------------------------------\n", - "update mode: ON\n", - "1) output file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/maskConnComp.h5 already exists.\n", - "2) output file is newer than input dataset: unwrapPhase.\n", - "run or skip: skip.\n", - "\n", - "temporal_average.py /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5 --dataset coherence -o /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/avgSpatialCoh.h5 --update\n", - "--------------------------------------------------\n", - "update mode: ON\n", - "1) output file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/avgSpatialCoh.h5 already exists.\n", - "2) output file is newer than input dataset: coherence.\n", - "run or skip: skip.\n", - "Input data seems to be geocoded. Lookup file not needed.\n", - "\n", - "reference_point.py /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5 -t /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg -c /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/avgSpatialCoh.h5\n", - "--------------------------------------------------\n", - "reading reference info from template: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg\n", - "input reference point in lat/lon: (7664601.0, 666290.0)\n", - "input reference point in y/x: (277, 304)\n", - "mask: maskConnComp.h5\n", - "--------------------------------------------------\n", - "calculate the temporal average of unwrapPhase in file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5 ...\n", - "[==================================================] lines 832/832 0s / 0s\n", - "Add/update ref_x/y attribute to file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5\n", - "{'REF_Y': '277', 'REF_X': '304', 'REF_LAT': '7664600.0', 'REF_LON': '666280.0'}\n", - "touch avgSpatialCoh.h5\n", - "touch maskConnComp.h5\n", - "Go back to directory: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023\n", - "\n", - "################################################\n", - " Normal end of smallbaselineApp processing!\n", - "################################################\n", - "Time used: 00 mins 0.5 secs\n", - "\n", - "MintPy version 1.5.1, date 2023-01-03\n", - "--RUN-at-2024-03-19 18:28:24.320374--\n", - "Current directory: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023\n", - "Run routine processing with smallbaselineApp.py on steps: ['invert_network']\n", - "Remaining steps: ['correct_LOD', 'correct_SET', 'correct_troposphere', 'deramp', 'correct_topography', 'residual_RMS', 'reference_date', 'velocity', 'geocode', 'google_earth', 'hdfeos5']\n", - "--------------------------------------------------\n", - "Project name: NorthSlopeEastD102_2023\n", - "Go to work directory: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023\n", - "read custom template file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/MintPy/NorthSlopeEastD102_2023.cfg\n", - "update default template based on input custom template\n", - "No new option value found, skip updating /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg\n", - "read default template file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg\n", - "\n", - "\n", - "******************** step - invert_network ********************\n", - "Input data seems to be geocoded. Lookup file not needed.\n", - "\n", - "ifgram_inversion.py /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5 -t /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg --update\n", - "read input option from template file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg\n", - "use dataset \"unwrapPhase\" by default\n", - "--------------------------------------------------\n", - "update mode: ON\n", - "1) output files already exist: ['timeseries.h5', 'temporalCoherence.h5', 'numInvIfgram.h5'].\n", - "2) output dataset is newer than input dataset: unwrapPhase.\n", - "3) NOT all the metadata are the same: ['REF_Y', 'REF_X']\n", - "run or skip: run.\n", - "save the original settings of ['OMP_NUM_THREADS', 'OPENBLAS_NUM_THREADS', 'MKL_NUM_THREADS', 'NUMEXPR_NUM_THREADS', 'VECLIB_MAXIMUM_THREADS']\n", - "set OMP_NUM_THREADS = 1\n", - "set OPENBLAS_NUM_THREADS = 1\n", - "set MKL_NUM_THREADS = 1\n", - "set NUMEXPR_NUM_THREADS = 1\n", - "set VECLIB_MAXIMUM_THREADS = 1\n", - "reference pixel in y/x: (277, 304) from dataset: unwrapPhase\n", - "-------------------------------------------------------------------------------\n", - "least-squares solution with L2 min-norm on: deformation velocity\n", - "minimum redundancy: 1.0\n", - "weight function: var\n", - "calculate covariance: False \n", - "mask: no\n", - "-------------------------------------------------------------------------------\n", - "number of interferograms: 17\n", - "number of acquisitions : 10\n", - "number of lines : 832\n", - "number of columns : 475\n", - "--------------------------------------------------\n", - "create HDF5 file: timeseries.h5 with w mode\n", - "create dataset : date of |S8 in size of (10,) with compression = None\n", - "create dataset : bperp of in size of (10,) with compression = None\n", - "create dataset : timeseries of in size of (10, 832, 475) with compression = None\n", - "close HDF5 file: timeseries.h5\n", - "--------------------------------------------------\n", - "create HDF5 file: temporalCoherence.h5 with w mode\n", - "create dataset : temporalCoherence of in size of (832, 475) with compression = None\n", - "close HDF5 file: temporalCoherence.h5\n", - "--------------------------------------------------\n", - "create HDF5 file: numInvIfgram.h5 with w mode\n", - "create dataset : mask of in size of (832, 475) with compression = None\n", - "close HDF5 file: numInvIfgram.h5\n", - "calculating weight from spatial coherence ...\n", - "reading coherence in (0, 0, 475, 832) * 17 ...\n", - "convert coherence to weight in chunks of 100000 pixels: 4 chunks in total ...\n", - "convert coherence to weight using inverse of phase variance\n", - " with phase PDF for distributed scatterers from Tough et al. (1995)\n", - " number of independent looks L=41\n", - "chunk 1 / 4\n", - "chunk 2 / 4\n", - "chunk 3 / 4\n", - "chunk 4 / 4\n", - "reading unwrapPhase in (0, 0, 475, 832) * 17 ...\n", - "use input reference value\n", - "convert zero value in unwrapPhase to NaN (no-data value)\n", - "skip pixels (on the water) with zero value in file: waterMask.h5\n", - "skip pixels with unwrapPhase = NaN in all interferograms\n", - "skip pixels with zero value in file: avgSpatialCoh.h5\n", - "number of pixels to invert: 359143 out of 395200 (90.9%)\n", - "estimating time-series via WLS pixel-by-pixel ...\n", - "[==================================================] 359143/359143 pixels 83s / 1s\n", - "converting LOS phase unit from radian to meter\n", - "--------------------------------------------------\n", - "open HDF5 file timeseries.h5 in a mode\n", - "writing dataset /timeseries block: [0, 10, 0, 832, 0, 475]\n", - "close HDF5 file timeseries.h5.\n", - "--------------------------------------------------\n", - "open HDF5 file temporalCoherence.h5 in a mode\n", - "writing dataset /temporalCoherence block: [0, 832, 0, 475]\n", - "close HDF5 file temporalCoherence.h5.\n", - "--------------------------------------------------\n", - "open HDF5 file numInvIfgram.h5 in a mode\n", - "writing dataset /mask block: [0, 832, 0, 475]\n", - "close HDF5 file numInvIfgram.h5.\n", - "--------------------------------------------------\n", - "update values on the reference pixel: (277, 304)\n", - "set temporalCoherence on the reference pixel to 1.\n", - "set # of observations on the reference pixel as 17\n", - "roll back to the original settings of ['OMP_NUM_THREADS', 'OPENBLAS_NUM_THREADS', 'MKL_NUM_THREADS', 'NUMEXPR_NUM_THREADS', 'VECLIB_MAXIMUM_THREADS']\n", - "remove env variable OMP_NUM_THREADS\n", - "remove env variable OPENBLAS_NUM_THREADS\n", - "remove env variable MKL_NUM_THREADS\n", - "remove env variable NUMEXPR_NUM_THREADS\n", - "remove env variable VECLIB_MAXIMUM_THREADS\n", - "time used: 01 mins 25.7 secs.\n", - "\n", - "Input data seems to be geocoded. Lookup file not needed.\n", - "\n", - "generate_mask.py /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/temporalCoherence.h5 -m 0.7 -o /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/maskTempCoh.h5\n", - "update mode: ON\n", - "run or skip: run\n", - "input temporalCoherence file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/temporalCoherence.h5\n", - "read /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/temporalCoherence.h5\n", - "create initial mask with the same size as the input file and all = 1\n", - "all pixels with nan value = 0\n", - "exclude pixels with value < 0.7\n", - "delete exsited file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/maskTempCoh.h5\n", - "create HDF5 file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/maskTempCoh.h5 with w mode\n", - "create dataset /mask of bool in size of (832, 475) with compression=None\n", - "finished writing to /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/maskTempCoh.h5\n", - "time used: 00 mins 0.0 secs.\n", - "number of reliable pixels: 339702\n", - "Go back to directory: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023\n", - "\n", - "################################################\n", - " Normal end of smallbaselineApp processing!\n", - "################################################\n", - "Time used: 01 mins 26.7 secs\n", - "\n", - "\n", - " performing spline reconstruction\n", - "119, 287\n", - "118, 290\n", - "277, 304\n", - "710, 277\n", - "\n", - "\n", - "\n", - " NOW DOING: SM\n", - "\n", - "MintPy version 1.5.1, date 2023-01-03\n", - "--RUN-at-2024-03-19 18:29:53.158970--\n", - "Current directory: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023\n", - "Run routine processing with smallbaselineApp.py on steps: ['reference_point']\n", - "Remaining steps: ['quick_overview', 'correct_unwrap_error', 'invert_network', 'correct_LOD', 'correct_SET', 'correct_troposphere', 'deramp', 'correct_topography', 'residual_RMS', 'reference_date', 'velocity', 'geocode', 'google_earth', 'hdfeos5']\n", - "--------------------------------------------------\n", - "Project name: NorthSlopeEastD102_2023\n", - "Go to work directory: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023\n", - "read custom template file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/MintPy/NorthSlopeEastD102_2023.cfg\n", - "update default template based on input custom template\n", - " mintpy.reference.lalo: 7664601, 666290 --> 7629999, 664156\n", - "copy NorthSlopeEastD102_2023.cfg to inputs directory for backup.\n", - "copy smallbaselineApp.cfg to inputs directory for backup.\n", - "copy NorthSlopeEastD102_2023.cfg to pic directory for backup.\n", - "copy smallbaselineApp.cfg to pic directory for backup.\n", - "read default template file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg\n", - "\n", - "\n", - "******************** step - reference_point ********************\n", - "Input data seems to be geocoded. Lookup file not needed.\n", - "\n", - "generate_mask.py /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5 --nonzero -o /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/maskConnComp.h5 --update\n", - "input ifgramStack file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5\n", - "--------------------------------------------------\n", - "update mode: ON\n", - "1) output file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/maskConnComp.h5 already exists.\n", - "2) output file is newer than input dataset: unwrapPhase.\n", - "run or skip: skip.\n", - "\n", - "temporal_average.py /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5 --dataset coherence -o /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/avgSpatialCoh.h5 --update\n", - "--------------------------------------------------\n", - "update mode: ON\n", - "1) output file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/avgSpatialCoh.h5 already exists.\n", - "2) output file is newer than input dataset: coherence.\n", - "run or skip: skip.\n", - "Input data seems to be geocoded. Lookup file not needed.\n", - "\n", - "reference_point.py /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5 -t /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg -c /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/avgSpatialCoh.h5\n", - "--------------------------------------------------\n", - "reading reference info from template: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg\n", - "input reference point in lat/lon: (7629999.0, 664156.0)\n", - "input reference point in y/x: (710, 277)\n", - "mask: maskConnComp.h5\n", - "--------------------------------------------------\n", - "calculate the temporal average of unwrapPhase in file /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5 ...\n", - "[==================================================] lines 832/832 0s / 0s\n", - "Add/update ref_x/y attribute to file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5\n", - "{'REF_Y': '710', 'REF_X': '277', 'REF_LAT': '7629960.0', 'REF_LON': '664120.0'}\n", - "touch avgSpatialCoh.h5\n", - "touch maskConnComp.h5\n", - "Go back to directory: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023\n", - "\n", - "################################################\n", - " Normal end of smallbaselineApp processing!\n", - "################################################\n", - "Time used: 00 mins 0.6 secs\n", - "\n", - "MintPy version 1.5.1, date 2023-01-03\n", - "--RUN-at-2024-03-19 18:29:55.737337--\n", - "Current directory: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023\n", - "Run routine processing with smallbaselineApp.py on steps: ['invert_network']\n", - "Remaining steps: ['correct_LOD', 'correct_SET', 'correct_troposphere', 'deramp', 'correct_topography', 'residual_RMS', 'reference_date', 'velocity', 'geocode', 'google_earth', 'hdfeos5']\n", - "--------------------------------------------------\n", - "Project name: NorthSlopeEastD102_2023\n", - "Go to work directory: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023\n", - "read custom template file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/MintPy/NorthSlopeEastD102_2023.cfg\n", - "update default template based on input custom template\n", - "No new option value found, skip updating /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg\n", - "read default template file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg\n", - "\n", - "\n", - "******************** step - invert_network ********************\n", - "Input data seems to be geocoded. Lookup file not needed.\n", - "\n", - "ifgram_inversion.py /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/inputs/ifgramStack.h5 -t /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg --update\n", - "read input option from template file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/smallbaselineApp.cfg\n", - "use dataset \"unwrapPhase\" by default\n", - "--------------------------------------------------\n", - "update mode: ON\n", - "1) output files already exist: ['timeseries.h5', 'temporalCoherence.h5', 'numInvIfgram.h5'].\n", - "2) output dataset is newer than input dataset: unwrapPhase.\n", - "3) NOT all the metadata are the same: ['REF_Y', 'REF_X']\n", - "run or skip: run.\n", - "save the original settings of ['OMP_NUM_THREADS', 'OPENBLAS_NUM_THREADS', 'MKL_NUM_THREADS', 'NUMEXPR_NUM_THREADS', 'VECLIB_MAXIMUM_THREADS']\n", - "set OMP_NUM_THREADS = 1\n", - "set OPENBLAS_NUM_THREADS = 1\n", - "set MKL_NUM_THREADS = 1\n", - "set NUMEXPR_NUM_THREADS = 1\n", - "set VECLIB_MAXIMUM_THREADS = 1\n", - "reference pixel in y/x: (710, 277) from dataset: unwrapPhase\n", - "-------------------------------------------------------------------------------\n", - "least-squares solution with L2 min-norm on: deformation velocity\n", - "minimum redundancy: 1.0\n", - "weight function: var\n", - "calculate covariance: False \n", - "mask: no\n", - "-------------------------------------------------------------------------------\n", - "number of interferograms: 17\n", - "number of acquisitions : 10\n", - "number of lines : 832\n", - "number of columns : 475\n", - "--------------------------------------------------\n", - "create HDF5 file: timeseries.h5 with w mode\n", - "create dataset : date of |S8 in size of (10,) with compression = None\n", - "create dataset : bperp of in size of (10,) with compression = None\n", - "create dataset : timeseries of in size of (10, 832, 475) with compression = None\n", - "close HDF5 file: timeseries.h5\n", - "--------------------------------------------------\n", - "create HDF5 file: temporalCoherence.h5 with w mode\n", - "create dataset : temporalCoherence of in size of (832, 475) with compression = None\n", - "close HDF5 file: temporalCoherence.h5\n", - "--------------------------------------------------\n", - "create HDF5 file: numInvIfgram.h5 with w mode\n", - "create dataset : mask of in size of (832, 475) with compression = None\n", - "close HDF5 file: numInvIfgram.h5\n", - "calculating weight from spatial coherence ...\n", - "reading coherence in (0, 0, 475, 832) * 17 ...\n", - "convert coherence to weight in chunks of 100000 pixels: 4 chunks in total ...\n", - "convert coherence to weight using inverse of phase variance\n", - " with phase PDF for distributed scatterers from Tough et al. (1995)\n", - " number of independent looks L=41\n", - "chunk 1 / 4\n", - "chunk 2 / 4\n", - "chunk 3 / 4\n", - "chunk 4 / 4\n", - "reading unwrapPhase in (0, 0, 475, 832) * 17 ...\n", - "use input reference value\n", - "convert zero value in unwrapPhase to NaN (no-data value)\n", - "skip pixels (on the water) with zero value in file: waterMask.h5\n", - "skip pixels with unwrapPhase = NaN in all interferograms\n", - "skip pixels with zero value in file: avgSpatialCoh.h5\n", - "number of pixels to invert: 359143 out of 395200 (90.9%)\n", - "estimating time-series via WLS pixel-by-pixel ...\n", - "[==================================================] 359143/359143 pixels 84s / 1s\n", - "converting LOS phase unit from radian to meter\n", - "--------------------------------------------------\n", - "open HDF5 file timeseries.h5 in a mode\n", - "writing dataset /timeseries block: [0, 10, 0, 832, 0, 475]\n", - "close HDF5 file timeseries.h5.\n", - "--------------------------------------------------\n", - "open HDF5 file temporalCoherence.h5 in a mode\n", - "writing dataset /temporalCoherence block: [0, 832, 0, 475]\n", - "close HDF5 file temporalCoherence.h5.\n", - "--------------------------------------------------\n", - "open HDF5 file numInvIfgram.h5 in a mode\n", - "writing dataset /mask block: [0, 832, 0, 475]\n", - "close HDF5 file numInvIfgram.h5.\n", - "--------------------------------------------------\n", - "update values on the reference pixel: (710, 277)\n", - "set temporalCoherence on the reference pixel to 1.\n", - "set # of observations on the reference pixel as 17\n", - "roll back to the original settings of ['OMP_NUM_THREADS', 'OPENBLAS_NUM_THREADS', 'MKL_NUM_THREADS', 'NUMEXPR_NUM_THREADS', 'VECLIB_MAXIMUM_THREADS']\n", - "remove env variable OMP_NUM_THREADS\n", - "remove env variable OPENBLAS_NUM_THREADS\n", - "remove env variable MKL_NUM_THREADS\n", - "remove env variable NUMEXPR_NUM_THREADS\n", - "remove env variable VECLIB_MAXIMUM_THREADS\n", - "time used: 01 mins 26.6 secs.\n", - "\n", - "Input data seems to be geocoded. Lookup file not needed.\n", - "\n", - "generate_mask.py /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/temporalCoherence.h5 -m 0.7 -o /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/maskTempCoh.h5\n", - "update mode: ON\n", - "run or skip: run\n", - "input temporalCoherence file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/temporalCoherence.h5\n", - "read /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/temporalCoherence.h5\n", - "create initial mask with the same size as the input file and all = 1\n", - "all pixels with nan value = 0\n", - "exclude pixels with value < 0.7\n", - "delete exsited file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/maskTempCoh.h5\n", - "create HDF5 file: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/maskTempCoh.h5 with w mode\n", - "create dataset /mask of bool in size of (832, 475) with compression=None\n", - "finished writing to /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/maskTempCoh.h5\n", - "time used: 00 mins 0.0 secs.\n", - "number of reliable pixels: 337844\n", - "Go back to directory: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023\n", - "\n", - "################################################\n", - " Normal end of smallbaselineApp processing!\n", - "################################################\n", - "Time used: 01 mins 27.6 secs\n", - "\n", - "\n", - " performing spline reconstruction\n", - "119, 287\n", - "118, 290\n", - "277, 304\n", - "710, 277\n", - "[[ 0. -0.00172706 -0.01118081 -0.00507933]\n", - " [ 0.00184982 0. -0.01077701 -0.00077496]\n", - " [ 0.01212128 0.00885389 0. 0.00657502]\n", - " [ 0.00669056 0.00297501 -0.00602099 0. ]]\n" - ] - }, - { - "data": { - "image/png": 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\n", 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zxxGAM/SYTG6OZLKILJPrKoF0oATovhNAN05n4oguc3NOVj5KC7Hw6cuBcXoVM6ATxMnNlPwcLMcfY+ofgM45nIjnR/v9cBp5B/LnSrPsp5Pare1pMFfrsvCVAh6RhZPV59+RLOnVkmMnfOPJPiI4wtZKONQN57KFyWGeuVsaeqEAYswUCs8WWLoFODLmaTsGECkgQByaxAx2oo6gOALL0yLNCkkl40OxRsdBVgIc4WOPgzORUAq/7IDQCTVDIb3QyKAFiApiZAFrnyw/BRHlcCMzvJd9t9MSfBEggDT28CQWuNIFmUcnJ5QIFwu081SpLpDOoZZxSDz/AFetAACX5Z2ZmvJBQAxCL/TJTxB4SGqiNAEuk8/Chzx52kn6wEysTl2NbA+i9gCEM1+NjNmcMA8Oh7qAU8sBMTI2ZuWaDjrh+JV7nntKDmq5dl25sKGPIgUwifxvNTLGWCYUHUt99oJZIWo/Z0HOEdSJDwCrHXnm0oSRaSRjtMySk2JMFE9EonkowjkxCFYjo/M+8+trjS4eOLrzwJnzudI0j+K2p8F8TFI0oCxps3GNAvL6vfxfrNjOEw52AQ9sD5ma8E4AYuaEu860wzgIIBvnmwcyXwkIRRGGXugScmLVt6oNcsKfI1lnnL5XSV63mZU5IS252VjvoxPQ80C28NRBqYzZLGm41bXlnU5yRlvuCL6T7RgAfJcsaIDU0ZnkgDqumdZQeWbad2AgJv03IBzwzMn2y5ExApg7AHFA5zswkj/ChTJZoVAuQWkSHVtV/3SbQn8lQBRKQf5WOmbmCCf7Ef3IItuLjJl3mHnCyT7iVD9i5h12xojjywEPbPWYecJVh4Q/13u+ofz9sMwOWoqjgIn6ZZJ+fkzX2yVViWjOxWKOzOhHYEX6VAo94pPFPHMkjvXk79FnQy9/ZCBwlJUhxIL3vkzUwskDGzPCagS2VxGY+fzwizy1PKR91rfLqmegPQ0B+820R82d1Ac2QkBNeVO1zvV5VstG9cif345YJq0uQ17IwMJlOwjgsE8OTpUQJoedvozLkZOkzAmv7WdZmQFaiJXFERTFQqekiwaQg4J4tqjUJFmqGLosqRypttAUxOaehJ8ueh0AyKuW2IArAGwEBewkbTQThtf/UzCU2EKuSASNBa5nVSULkCzHNHHohDrCIXAEj33ppStacjQWKwPZUmWO2VGsfgztcwAwQLX0hZYhApKeQ8YhMvoh4gtxJSs1J4E2l2zM8NgDHbyDxBbsnBCw1pZ8GhSL6oPDAlsDg2gGl5yingi69lAnqCdRnXB6PvvIZqIqVnhW77iAnVFWVxFi1c8cwQcHSoFROnEAyBSNJ5FR7jjOPhOd6MuzwlXMwQqcJ4iL1c6LmmXfMt+1PWrAXJtGWSlf3Frqg7FSFFSEZ3YYo8ja4D3m84PyAlEQJYDvwPODxUEVB5BL/HJSJ4xwwqH7LluTIwMrv4ENT8DylID52MNr8I8L4kTVTqm0EQB8qKxgZ8BZ6BOdhGjN+QsUIGVmrKKMRQZxvfoofLkG5CjlQqpuMVJAb3N3mOCT/BGKvpnSZEMJbDzM8fINMBrzOICSlaj8NJmJjcah0qL7NMlFthO1WOMEwIEkcMiLg3Nz5jP9tBwj5nCAA669ZBNXbAY8tDNiZ2TMZ4ssbxXA5bRC8RJMhYAOwKbnPAFROv/CyzmZGf0Y4VTX7QhzxwiurF4q/4sLoLEHbR/HxvwARtfBkYxnHxnHl4yNMMuql35VBt0RZYDW4CZ1dIakjQfShOFlzHt2ONmPJQr3IrV9ML+w7VED5pReopEBD+EUwQzmEgGnLTLDJTNyHgid9zjRj/AAmNW8TC8BitKAgRzB1keIBpwoc9XBUeaVFUj7xGcyA5vdJrA8lSibmC2y7SHCzwJC3CmgCplAVEWiE9FOtqyd8OIj41Qfs9NTuXKgTFZqrUZGpk+yJe6CSCSVC9bgqjhkXwF7ccqCS0RoSIoSawGuohD0nmpeN6s99Np0gtDzJkdwcCaAJX2WV0XqTLb3PA7w2o8kudSVCiONO4BTvRz30DxgNZZ7f7ATmejx5Sj3UCeQOBRKRfubonFdfh5cnkCVbrLRm3KbGJ132XcQCPCOQTsn5bihk2ujIU8YxDE7oO0EoEDNLCuRnYETXcjYmBE21ZFNg9w/Qlb9oLnnHqI31xXQfnt0tD0P5goazGWZrxahxHMkh2baFijWjOXUxwj04BQQkpb0rliKavVq6LjswxjTYj4y4CIjOI8uWWSMAqRjirYMyfJjH0T9kHJ6bA8RnV/k8yFZ4sRF7mZXFv0oEY2eBFycUX5Ya9nuy8xg5/LEFLlovQFUljO7AMxc5rGLPV0sdR0PXa7PnMSgRCROlpCjZdl3WXmSz9tGfVoAV+ezApELOSq2ilpMqpGFF233NidncCxjdfWRBY7MR3z25I4oehwhRsblm7Os7Dky95h7B0YA0QDwCjSqVTsDkxP6LV1Ldrqj/NaV4Mgy2eq9zP6bpNzh2SLLS72PeXUECIWTqSl2Gdh1wvSO4BlwxFil51kpLcSk/2eHfoiyLSX6j8qKTSJMKVN1F6uRc6Bzzcx4ATM77vW2p8FcZHdiDQICOCNQovAgVnpWXSTvn1jt9jgCtoiU5IoRLqScKPrSGstGHaga/AEAlEB9jIweAmbK2RMBQWcalTg6h5kHOhBAI0YKWI5FDz4wsD2IOkF10URiUem16nL6dEo0o9TIELlaqRCpUzT9Mw5wHOEArPwC5DrJX2MycwkOyrUGC0hAjsLMQT0c0SOkNALi4FO/hUowdQIjQCimpNPnNK7EERiTWiiBXp40mNPqIeXgsVGgyWkLiJRwI5RkVYc6l5+Tz+/s4MGtHpszj8Mh4Mhmh8csZlmOKv4PgBGAmaaH4DKRJAD3ruT10f3Uf2ADs5TuyBRVOo46NCO5RKM4ONflICAaduDJYXSdpFvglJuFioECyCrw4Mzl50MDtAY4bK/EDzQPwMJL1K8EH0l/AyJ8WtUENBPqBWz7NMuFbXsazJVHTjgMoFjnVp6crWrISyB5V8RBRgCGFGbNLKA3My+m8t4EJy9kohhGACMoUzrJJZdfuAKkJRpQIyjVMkM6tnchg7NyzoFEAbEzxNSfolbJTj4UKzyy5AJRumdISh8N57fyQTbgEUjAz3ebErgz9iAXMKQBVYmhHcsc6ANkR94sBPAoFqlG3dIwFL29Ovx8ADQgy9ImsYAKMQPjSkL8XQB7V4X4I50375/AX7Xh3hF2hhFEIhHcnDkcOxVwv3eYOdFpb85K9kAg0WFOJk92Aeg2xfE6DljNNrG9SsE+3qRBYA2aSiNjpJsgl3TdkmyMVjuAGxB0/NKYzFPUb57Qhl4mE8izM3OqRxdlTs+yips5wg5KMNUIzRKZnKYzIwbiCM8RW6NG7RKOdF2KjL54YL7fLmzb02uW/LCajG8O9UWpM5TNPo7U6SlAtZOW0/NAOUtedXxowEwKGBl24BHNslUCcyy1Q0nd0I8RsemjcuGRxcG1zDphe3ECHgzkxFWUMh2qlazKlIMzh4Mp54ZSMWqRd97l4KrslE1abA1o6pIcc+kWkn4gOXlXeUIo4fKaNGpIP+w7cIrWFHoFxd+QFD05h00KggFQ1EGGS6+kn0mnj1ichPBlAtB+slqxVHPAjiR7o65aLt+c4fLNDsEnZyjJWmojlBXU3BPcsJMDqHR1EHiQSSqNfU7du9oRkLYgnu4dDTuVc5HGVYn2Tfdfx8jmuiFmOb9ZEfpksAwiPpJEZSgKGSbJexPSpK8O0eB05SqqpEPJkmeW9ANsVj8XownNcq6JtvY0ZF3Qtqctc6tk0FtMySGpn9lsBZZLVnpGnZNq/eYwd0ACOVR1ovtxlOChuAPfbWJszwGAI5cVgqN6xjQvvUvcJZDAMh2nj5wsfcbcO6NOEeCXySVNPGYF0Y/FQeoJWHiXIwF9ivQLvkNMiaG8K5x4IFmtRLdI0bNkxrLo07Wv2n+R5RWJXHWdajlzRK5pZa6f4pCt3yz7NJZt/p0mAaU3Zi4Ibx5j1mNrrnmfrNmDM5dzuh9fjvjciSUe2OoRGbh8s8PMuxRhq2H6nPX2JUhK+k79FmYTckWVMPYI2O4jDsxCSpfgseEdqN/CfLYAQIgbR4r/IvH5IZTXj4YdkaImfl6khAw2gvvOi4UuqwcZ6w0NagLAFDBEycczMotCygGjC/AhYGDgkOoa4yAdcRcPAs5Lbhbap1l2a3sazNXCzvpkCCCqRE6bRuCt54ejBECcgaqPjLljAZAU1ALVOSfZXrYUm6aYrtRGpsnTH9bC1f8VJJ2S60hOz+TYdVkTL8dVq1w5dKBwtkOUiWkeZALRPCxizXU5B8haknxjWUp+7QCfLMIhWbyqWlE+Xkav1rErLwtIki5ScG4CpzQdQpVnJQ5Zny/98UXvnSxLRyFFhSYHbUiWMzksIxeqitOkyoxhBE4OEfedWuL4csDmzGM1Rnx+e4VVJ6H8m56xjJQKmlBOWBbMuHBYQItUYN5lxZLnQXTfQXK1a4bEkyDMwwKHSYqc6ApC74lOklKcpM/jE7tN4baZwSkzIwM5eRd5wkZKpjVAqBztp6eicde8OUPkHNWcn+Wxr1NJXKzm/TmH8/NZJtr669T2NJgrHHmC8KvG9Fa6Q4FTuW9dUjMU1DRPhk3PKg94AVmXJWs2WlEtxXahqmoZ5aqz9t2sDCxA6jXo3wKMZfuROS+d5fjyW1QbYokRMRZBLM3OUZVcTC1CvfYIYJboEH3BEcUp2vlORk+DhiBUUa98uKut9JkrCc10chU6yuUskFmzXg2SPHoDA3AdZkFWPBw6oS6AnPuEgRydChuxmCiCMdFVkmJW5sRTfcROWnUNUcZv5iSMf5ZSGmzOPDZpBVoN8LNNnOolrUMfOTlqPbruoOT9HnZyARTNyhgIoFUPQo+u20Q/yr0/MKMkgUyTm1ugI6Frgk+BX+kSaLUslvX8QF0hK6VB1vQGqgIaUVIiy0HkfslkKpOaqmn0WR9Y702U/P8+yUy3voD99uhoexrM1QEKqBxRKQvODsMIysCp1iOAHDY+y2BKmCXOQvNp6AQglqeDU71z6KpIUgAVZ65nqIzfBOgqWdS+r1nnMEFB5lhwJcpVaRalN6yMXtPeDiB0vqxclI4R1UaiZ8Y6YEhVIpqxkVKu7Y0gVA9pMJELWd+dk2gZeV2+ZtWx6+dqCSbVBpOrkqHpNtxtpgPEImVUjtx3WMZUIs8ct3Nl8DXBVuRyn11yegKQkmyOcLBzoHGZefHO+zqNrRlbWi3Fgu42MU8IyRSEu48jeOzR+Q6z5ESlGaqyfkwk+8UBIQ5wKWyfnc9FTKjfRrcIWEL6MU/qH6u4WUXGdso3sxFSzngWGmo0w2+focjiNAWQqaDgSKogXUya5TyoWc6ZpnkUtz0N5kCxztUyjCyReOLwowrIAFQWjYJh54sTTJekVWSjWuyhSxK7LmXsEzWLtpFFVaPL/dxH6/w0fdZWcfnmfFnqRoBjynJHlSoCoqIJrjh4nQkrV/7cARjNRDKmNz04UZZQqk0qGweAU5CLFys5AJW+lyy/rU5N5bHTMQYWlcfIgHMuW4gAQClQKf1TOeFotZOVKxrhqdtx+gkORX/uuxRjQOg41XiFw9jLquKvTvf4/M4Ky0Ec1gc7D+cIhzqPzhN2/AbmWIGGHpvdZgo4AgIPYnWPK7DziN2GTExKO7FUClKnLQ09xjDLNNTMFf+N+jaWoxcnZQiZ49/0AUjHYD8railDyamFr8qt4ufRoDiHcdTzFkolr5JcAPuS/fHUwNgI0r/Tq3ZdeeHaPphf2LbnwVybWqCag8Q1iJktPCoguYrIOZ/V+olmewtAOcTdS7BHtvANUFtg1+8sJWEpH0IN4jD9a8Fer0+bHCdJFankBckSyLQkV6135Vcwv0dy8N1mSVEACN2SwATkBMyIACTlgzePDDkMVKohCeiHPNYa2mNXHWT2tZGJ7AIo9iUqVK9Fc7ek7IlSug0V3x446dLRYSdRT8zA9jDi+HLAiZ0BD271OLwI2BkjNiPj2sfMU0g+ARyyssMrT+4CYidh9lpIGoYeAZJCpVGylGLNJYDI+km2hhJwtQipLq2mT07Xpc+opAqI6bMSwLYIlOMXsr5dHffK65P0d6SQ0ztLUreQtPJSJcnR1NO23/Zi29tgPvYlwAQlUtO+YPqZAmVuKXKwH23JtbKBOvUAlOX8OABB8mZoiLUFTeVVlA7RWpxWz9y+OgrseRPTd2q2s6AMlOAUoTvqSFVHQARV1r2CSqaIck6XGShNDkQSYajHZT8DDcsUfVnL6dgFnE4Jyn1kdD5Aa6+3fcmWNJD3ra5RNc/kclIr6rfBrq+Sjel9tH4NkKwmxmS16jVvrSSH+Rd2VuiHiJ0hYns14vLLDoj2e1yu1YYFZFUSo6qUZlgNjO1hlDqqKeoWHBG7jZK62AV0ZtJWH4tPudlHLhG6Wu1InhHh6DXH+Hak7MsZI+NgQEpbANHSe1skWyejKPp1SCBWH5NPBMCQFE6S/iGkDJcyhnNP2KQVLlZzzsPtBw1dsLa3wXzCE0/p8ynQtBTHkPJqW2cUgGLFkLEoNU+JAdn1fC/FGQgUC983HbEOWOV0dX91tlZUjAIcCqDrthWVA1SrAPt/zakjR4fmfa2cM6koVHkzuA34+Uax7EykYYzajzJpaMBTe92VntnUQc19GMux2USicuhyHUy7D6FU7hljslKNRXt6FfHQ9grHdwb0Q8RG57E581nSyRAHqz22jj/yvZRx2AiEmeM8GXoCtBKQ+hkUJNUv45V64ijpf3kEYsSCI+ZOJ8WUzjiNd1htYdFtok8PURccmACKETSKU5h8/cpqWUMxKlAKkph7KxZ4yf3eecKGJ9DyFOii1gB154Fm2deZ79b2Nphni7kUDc5AqEoHlM+y8Zt+O8iSlVmAXVUKkSVBkieximjohV5IDkOFJbXKlWqpwryxrnLJVqX5TMHd9quiJRpwlyASlx2zQA1iCuCMdSDXponBAGRQdyj0jPYLKLnFGZDc11SuGxCp8oojZl7S8I4MBE/5nuRoR+2/oVCywsULYMNw7kByuMZBAnhQJjPl631yfJ4eo1AgXvwK20PE8Z0BW6sRkYsVvBoZKxcz8CPGSp+uFndIqzafJlHPg/DScNgepJqPKnQoyVUDScEPTtg4ppwo2XGs6Yy18pQ6n32HmZP7uZptIkASbI1weRXlDB0FTdBmVFX2Ppe4B7MabAyAzXEbuTiszXOz3/Z029tg3kTPZT24iUAEF2eQJVPUQu0csHKMGEV9MIeAQkV7GDCyoewKaKoJ92fgH1vrWB1bLZDbbRVYFcQyKHKdc1yr4CAVarDpf/MkYI6v/VQqxvbNBiG1/1eKGxTJ38jAsGJsp73mgbAROpnQolipWjt0LQ0uIP6IlHY2F+ROqhnRlyNHyJIjeOMglIpHvspRvxwiji9XiCw1XUdmbM48Hnugw+bM48jcZ2WOc4JrAzM64hxVmuWomliMI0bqJKIWyMWUAbGOSbY0qRRKnvOZL9c0UoDzXU5zC8h9DRDDY3sUCaWWMxwjw88PVs5lSmUEtXBIjrolkY72kbE9yoQ9copsNc+C1JKVbJTE9sm7sG3fAXph294Gc20T8jZtFoz0Yba8swZlMCtYpbqP9nBxBI9FfaHabdvkxakDllR9AuxOe0jnYta3T1nt+bPGaWh5Zr1WBTirK7fXbyWKdnxsU/qHzb7a8kShx3MEx8g6eEcSLr61iiX4xpGWp4aDhNIHQ9moNE/GWpQyrDnhtQJSsl5FT14oj5FFwUFEku971O8kjcMiOByZByxTHdBrjmzg4MyBViXxlyYiUw4912dV2WUa424W8koPYZHHn7SsXXJ+qo9EUjVEbA/AzHlsOsDHJK80kbo6QXiIEgsQageQLJCnVhGRpaRhR5J+l8YBhAGeYnkuUuTqhpNCInKv0nOgfTUcP/XbwMWsAboP5he0PSrAvF5Urn9XLUO56K4V1IOTSLvZlGWdl/wrAZdkzY0NmmtGRqBw8FOWtwV3BorVnwB9REl7WmUmtG0i5F0piykVT3tVlZVmAnrsSsDunz83K5GSQVGW9lYSp/tU0a6QCXOVaA+Nrh0YGGkO3y2kmIKG9qdqPkp5KUWgE6kFTY2qBIDtFeOBLXHqLYJH8ITt1YgxMlYkx5OKPy6rYTxNFGkwjnUZNJk8PZAr/nQ6/on2YfY4vowpRz7lFLwbaXWwZI+5k6pB24NMajrxqnWttJo+o3Mv68A+MpaDOOs9Bcz8LGvtVX8PQKSdoZPrcQ4xigO0c0HUpUm1Q8tTwLAj+vn99qhoexvMp0KRjf652hQp2jC1IdaJrWbJGvdJHwxo0IVLgR2mWAFKyDiQEm0BlUyxpS5ycNHDuAZLB00B+cj10nqq2fPbiWQNsM3+CvyWN6808MZxKgFSEukqgUuUPwd0pcMpuKnIKINxYGl6V07oP2KGFQW4QKCxBnJN1do5yQyp+bi1aek/ALjywAzHlw4Pbq2wvRqxk/jhSzY8ViNjexWxWCySSqQU/3Apl3iwvHbSmduCHb4LUnVJQ+JT3EE01EgPeaZ0xWKjcuECHjOXLIdivStoy1KGgUyz+EQFbjiGnzn0owRSHV9KtKpkQFzkVctGtwnaOQG4gJByB51eRQxJiSPZP+W6iCM4zHCx2r5lfmHb3gZzXZrbz9QxBFTWo1i+xXqNkCLHQokWigAQy1MVHVnhQJwnCcuXOxS5XwvglqpoHZ9Vv41kzwNlQko0RKUE4QindAy5kv/EHNOeR//Xc7WceNvYXFuV8wbImSBljOT3zFE1KWa/AZVtRLVZh6ArleNJBipHqqZIV923HyOGWCaGx8wBn3LnCL+cMhk6RhyFYvLOoY+MyzZnuP90j63VmJJpAQfnAgbZWkWxgimNk1QFSs+Rn4FnkkOdEmgzaSrZDh4RfZIxjjH1J127RqGOqe8jHIZRkqeFQYKxyC9yAjUZl7QtJ1RPqhoPUcqUup0R2ys55+ejXB+RKHzmoZNo1ThgZJ/HPTKkVqzvEOeQ56i7eOqQ85Foi/YTbe3aHhVgvtYMh5x5ciNAtMWIh1he4n5kdCCQL4E2AugOwAiNgmQUWkVT7ALFmWjPS6afyovb2pYAsqqhUnMY+iVfU+LL8zEbEG+jXe0kp4Degri1vFWlouBtRzcCOaujMwcnovy5bp+5/rRiqeimZmliVy0aDGVprJFFYUQsXPypVcyA2eV7KADIEBpCsiTu4P7TPT6/vcJ2P8ITYTlEMAMHZlJyT7JTInPdLt33PqZ7ELfAs4U4SwEJ7kl0hlI8y0jYGeW4Gq+wCISQaJZ+FHpErWhJW0s4OJN0wzMCHBN2BqkZ6igVg0401RgZSwbmPgUBpXu0ysor+UzoF8DrA5BWABsO6LzP994WH4/dBrB98WgWOg+Jts51/0dz29NgroEZ+oIBRu6GwpVbakETEVlA70dOYfCSUGoeJIwmW7GhM6qRKC9QLPwxgBwqbc9rc4fIxrGoEmwAjeXA9ZpMUwUNgBJ2r59RKcXGqKkka5U7A5rAOrjr8ZXb1mIfaiF7KsDd6tS1OR0Po6SptoqDqI3UeZv675K8Llux6XwRgDdUjubOsXU2Zwkk+yHCE+FUP6YCIw6PPSBZCiW5FuHwIuDSDY85ieabXJeVJw4Q0F7tYB46sJMc7Fn/7ktkq4991pH3qa8zT4ir4ksYoyTrUqpF++59yZevybEAcYIijZ/eq1LaUJOpUQpkI2wPZVw6X8L4PSE7b5X3z9WEyCH4VC6OAjxFrLyJPt1ve7rtaTDPbSIrX7bIuVitFoBqTbVYV8uBQcTohiavuQXjZjVgJYA6ccgL1Zfq67ZvraU9JdUDigMufScvtcsqEqWR9JwVUHORJgLrDk07Pvq3fm4xOq1HEmiUMnTqLBSwLVx6VUxaVyP22pImm1LKV6Uvam27UQAxwOBM3eSoybSDZhb0LuRAr82Zw9Yq4pKNGe4/vcTjDs2xGhkH5yHnYwGPqfqO5KTRlMPwHTAOORCIQwfXb8sKY7WEG3o4XTVxTNHAc2yPqprxWI5WligyzTHJXjdnTvKPjz0G7rBKTs2NUAB+lWYMVVlpki7J+cJwM4cQezxm3sl5FZwT/05ECCn5Fy1Pi58nU0YpHUIKNALjIpeN2w8aupBtT4M5G5BFY5Gr5WmtUqUPvBP1wgigT+llPRHmQYJgvDNgNxFUYRUaM4OKFUBOUUBpMtDUrllaWGmGTSCN3dX8XalEzNJbQZV2s4zN+NhryZa9cW7qedSBpyHoZK7dxqZ4axnC0EnWIa3VeeIIDvOsFrHXsiblRD1ZjlwmD829Lha6UBidJywHsdYv2ZjlanTOARupYMV83sG7dPyY8vnEEVr/k1Y7wGpHVj3OS7CPRv/GIV18BMYB8+BAXYftIWLuXaZLgkvZKR2lqOJET6kenAByhK6jKt0BuZCrT2n2RuXf5yqZTZPiBjkpzRcWWEEKT9DOCamZGuaFIuq3ETeOyEoAgOu3gNBhyV7kiRep7TtAL2zb02DeWsxWntdywTMn3CSQpGwJEHQzCUwx1jVimhHcNCViu5H2L4mapAAwXB1wlHOSTEgLtb9qYWu/LFXU/s7bGslgVXTC9g0FtNsAqjxOKGBMRBiTVay88hS1YmkmHUfttweqnOZIQSrZqWj7mRy7sTmFHi9fc7I+bdSt1feX7xmLUF58gkgED3aiIhmppCGQyN8gOchBqToQcqpd129lqgWqcAlzqG676zo4cjjVxySdZASUNLqeAM2AwuSy/FAnqYFFOw5yuezh5kxqlWp6gO0h5gIkcCk6NVVbcstTONCfTiuLHquDV2JriOgigdwC3dyhZ4cOIn2k1TZoWGK+cQQnwubaPd1ve7PtbTC3zWh01TK3HLb+WMCT35xpFkcm0EctyTYyUS1oJ1kCc0Ipy3XrSkGphqaAcd7ebGOVMFbxob8rbXhqGZRNgq92IgPWNfHAutXuCSmdKlXnLuNU/m4teP1+zZkZSxQnhj5b5Eqv2NaGpbd9yP00VI6dXCT7pcjzJNmWXKFPyhBHKX+9oWpUZWKPObImu5Jj9pFxKPlM2HdwkBS9MckYZ+MOEAcEksLR6kDWY2lKXE9FF79MgU0amTlGxk5y4mrdzo6SQTEOcL7LFn4040P9Nmi1JUZCWCAuDknJv9UWDnME+wUGCmDXoRt7yfGyWubJFOSSJPLitH3L/MK2vQ3mFhATKOpL2WYYVAvVcsmqVhkNOKm2V62ucgBnwNdVFm9eIivwa+EGu3IYh5xmlZKFX9EqqOkhvQaLZ2sUBNcTlmZRbAOH7PHbpsdR0NFjqnbcAqxSHhG1gmVmxlMnUbI+gzR+HELKvlj8GNpa53HNo69PSJLqmLK+Wpviu2S11G0pOwo1UZnWgLXjmSWKaVWiWQ4HkrSxIwOjXyQ1UbpfKRKUyaEjkREq7WVXTK16xqM4S+eeUn3P1G8CnHJA5PLnet6tyNgIAV0cwN1B9IsjosQikrqiOf1AEIueCJ0Xjn5M4+8hF9xfPMoczpFc1zkd5OJNPnut7W0wNwBLHMEmF3f78luKov3cfqRgwORKDUpyufpO1oLnHdbVJ1Y+SFHS5mZL1AC6pXI0gRZQUywWsIHSVwvouo8Fcp0YrFWvE9xoPsuTnyvpfEeU5b3lqwMZpyuS09Nk6CsqDGS9PDknFnqyBFV9Y6/T7q/0UZ58zXZ+4h7qaopJ9Oc6OYt8vWwYm3PJ8ShTcLIYI+OPkC2ZS8Widsz1ep0LOcma5IbhkrzL6Xk4gTwwD2UF6AmgfgvcbeJUL2l2Oy91Q7V1DlKQOZaC3fk6OKb7yji94jweRB5gRuckDqBPQVhDFKespg04jf32aGl7H8yTdc5ApjEqcEZ5+Sx42bYcOQOZJu6fs2hx1UnpfGckH0YDrhOK8unJKnf9VtGlV1b9RDPX0HLizgAosO78bD9Dcwxr3TuqJ4oM8ohZ/qjacAVUHUPZaQAoZF5aKRkLuoGHXLtSnLwxj0N7jTY8v/UV2GMqkNr7CKRUAOaGaurYFux1taWf65jYiZJRT0Y6fhEAciRrPWGOzfirzjyyUD0bazkCkFcLngqNwjOx9g92XoJ64oAYFtgZi5IHXCYkHbewOAR2AdsD52uXa2IcmEnSLQZADPRRik1rANbMecyWJzCPO7hYjRyBztGyPtf9H81tb4O5pVmMxasvogVyYHfuONGryXEm1lO2GpvoS5vkytbPbCNPqdsEJccZkRPLNJ/UZRomgwqK9WwBDSiAowCrVmDLj1tn4dT3UxMZUFRB9tyjGb8MrCliss3IqNctVE/I0amWYtHx2e1+WNBuP0OSH45cT0aEwuFrCuOROWcuzMdhmU+UPtOJS6ik1EUUimhtVWf6ZicBe1+Aki+mS1pypaqIJN2ARrvqtY1wpZISR3Rp0luyx2oV0/Wog5dyQjDnZOXECBgooB9jLpqxM3JOE6B902paElgkdM+J5YhFOITlRVT6Wcf1uRxjv023s76Vf/RHf4Tv+q7vwlVXXQUiwr//9/+++p6Zcdttt+Gqq67CxsYGnvnMZ+KTn/xktc1yucRLXvISXH755Thw4AC++7u/G5/97GfPvvetsqRxgALrVpqj+rPlyBhGrjjOyPLgj3CIIZX1Mry8tcQpDiK367fkK6VYAMA50LAslrf+oLYyGWJlMtYnIKD+fIilr6PyqwZU7HEtRWGP0TpUdRUwmP1tdkV7HOuUbfubx1Vzm0zo6FsAta/m1P3J4w2sTSC6rXL9eaViBURKZVBx2LaNzG8FaYI8yypldVQHZLU+mn4UTltD+pUukfqfUnNUJa/Mok45tYry/LEA+8jyPKo00TvCRiAcmLnM92u+/e2BMZA444MrSbl0252BcSoVttZx69LxDnceGzOXnN67zPD7bc+1swbz06dP4+u//uvxhje8YfL7X/7lX8ZrX/tavOENb8Cf/dmf4ejRo/iO7/gOnDx5Mm9zyy234L3vfS/e9a534SMf+QhOnTqF5zznORjPsuoJW2qDXGVR2Ze7pSWsGsI31oLNSS5WTQJaciL9akE9qvNzlTXVjoA6z3g53tgCn2mtpap9HSNXdAKQnJ0p30nb7Ka+uXZHhQdux8auZuxY6TiIDLA+j6UdyoX0tfO4oZfsuXbrv47V1PdZPomab8+nnwCokjPGTWyfumm21xVWHxk7CXhXkXO/e65TIYuD1eVITu2HTr66UmCIpTxGua/bg1jJJ/uIk33MlIl2r/MOG0GUMhszh83gJB0BaZKy+lp1vxK5Szg0k4CmRXCwNT87X0rZXYxGaVVxLj+PhGZ54xvfiGuvvRaLxQLXX389PvzhD59x+w996EO4/vrrsVgs8MQnPhFvfvObq++f+cxn5lWG/fkH/+Af5G1uu+22te+PHj161n0/m3bWNMuzn/1sPPvZz578jplxxx134JWvfCW+7/u+DwDwtre9DVdeeSXe8Y534Md+7Mdw/Phx3HnnnfjN3/xNfPu3fzsA4Ld+67dw9dVX44Mf/CCe9axnrR13uVxiuSw5JE6cOAHAgFaiMqrPsA4yGsGYpXSOsBGAnREAKFU8p2TpUD4GwVizyqOrztc5AFJtnjiugQ/7meiTjYNT28DrKg7LVWufM1eqv5OzUhQopa+qmrB0QDsmSk1YC5mxPuG141c5Vo2801I5GRfIFZ68SWlgx8da/DafDaNw4eSS78LcY91PwVRWKWK1DmYOMbiaQvyp0GRN31tqhSBg149iCWuh5pStIDtPdSyUW9fGLPupeWJXVnacGZypvkyrJdftEMWC175qHyhJGPVsWmRF9o045CM2Q0gZ5BkYVwhDj+BDLjNHHEH9duVovdCN6Dxw5mdJs7z73e/GLbfcgje+8Y345m/+Zvzrf/2v8exnPxv//b//d1xzzTVr23/605/Gd37nd+JHf/RH8Vu/9Vv4z//5P+PFL34xrrjiCnz/938/AOC3f/u30fclD/yDDz6Ir//6r8c/+kf/qDrW137t1+KDH/xg/t9f4Lwy55Ux+/SnP41jx47hpptuyp/N53N867d+K/74j/8YAHDPPfdgtVpV21x11VW47rrr8jZtu/3223HkyJH8c/XVVwMwgNUoJKxao1pCO8pLZn2mgiMsvMvv4ciyTHZUVA6WFpA/XM6xUumlUy5uW2whg9hUyH5qdmnvm3MJ8FK1YlgDT7Nt2yxGqVVpHYD2x7ZWtdH2ST+fXGmk2ppaYKJVsVg6Ra+7tdTVwZpXOYbXt7/1vgLIkZK2L3pfV7q6Scqnlq6ZajbvSWSurF7NoZLHwnynGna9Hh1r5nVqSZ4vqv736do3kupk4aVginLxaumPaaWgY9FHVOMk8lDJdR7nBxHDAgNczkHDPgiFeJGaOkDP9eds2mtf+1q88IUvxIte9CI8+clPxh133IGrr74ab3rTmya3f/Ob34xrrrkGd9xxB5785CfjRS96EX7kR34Er3nNa/I2l156KY4ePZp/7rrrLmxubq6BeQih2u6KK644+0E7i3ZewfzYsWMAgCuvvLL6/Morr8zfHTt2DF3X4ZJLLtl1m7a94hWvwPHjx/PPZz7zGQCFf1WuWB/wM7WKPohiqWvYNKWlq2agoyT7ojgkGWFcB2djhVIchT8fTP4RU1m+PT9Qg2HrsNSJpOi+62uxoGq30+OekcJI196CvR7PTizadCKwIGwnOwteOZmW0lJNumKdQPQ89nj6WQV85hh21ZEnbaotZoJGrhaHbXAk92bshQpKJem0OSrGgP7oZLEILteFVS16SBO+grqeT5yfVF2nZUN0JWQdpHod+r+9v2qE6Ljo8yoTTbnf+i5oPAOGXgwMSLbJnTFROElO65anQTuF/txL7cSJE9WPXblr6/se99xzT2U4AsBNN920q+F49913r23/rGc9Cx/96EexWq0m97nzzjvxAz/wAzhw4ED1+ac+9SlcddVVuPbaa/EDP/AD+N//+3+fzSWedbsgvuzWQpwKM2/bmbaZz+c4fPhw9dM2Xb6qNaegla0i/Z0ch1qcogR2lGP1o+T9QBzyS1/lGEmyu8radgGc1BLyv6u01UAN1K1lDCArZ/RlV/C0ANp5qoBbQ9KnRs6CoTpN9cde+5maXeGQ+X/qOqaaFi5GYw3rseUgct1T8QF5YkC9bTuxjYmHBlDxwC5tq+PGs0VZMaC+lvY6WgtaQRyQseuTH6H2UZhJBCVgSScbLdYhUskyGcvvAuR6jjjRL6CeaFXmGHiAjz1cvyX5ZYyKyhNlh3kMC4mhiAPc9hdwsZqm+D3XHwC4+uqrq9X67bffvna+Bx54AOM4ntG4bNuxY8cmtx+GAQ888MDa9n/6p3+KT3ziE3jRi15Uff7Upz4Vb3/72/H7v//7+PVf/3UcO3YMT3/60/Hggw+e1ZidTTuv0kQl+I8dO4bHPe5x+fP7778/D9DRo0fR9z0eeuihyjq///778fSnP/2szqcWeZ+4TE+GazXyOWc+1+RR3lEVjTcPhO2BoclmR2ahU4YemiEvW4bkEOHgkwUkAUYBFE3uFUMrALXCxlrjdqIRbrhsb8HYAouCt3Luyre352mbJhqL5v+WxRMAoQrEuTm/PRc1n+XtdAxs1siGr55q1m9gNeAZfE3mSs3lIpMfgVnUG2SSprcGQi7LZ1IvKBevk2geC6z7CIAyfo5L7nf93CM5pxmYJZ35GOVzpYGspa45yTNfTiWVssok1fCQohVlnPW+eDLjM/TFGR8HwAecGl3Wl+d+ugW6Ax349EXMZ/4IHZjtMQDgM5/5TGXUzefz3fc5S+NyavupzwGxyq+77jp80zd9U/W59Ss+5SlPwY033oiv/MqvxNve9jbceuutu577XNp5tcyvvfbazCFp6/seH/rQhzJQX3/99ZjNZtU29913Hz7xiU+cNZgD6QVMf0cITRKb7yPLdxFlGaySM71Rs8Sdt8tk4RVLdXVQHcpv60RyWICdFP0dzFJ9ymoty2/OqwiVJ64BsjpWtShvWiYHY6FPAX/73lggr5b9XEquZd22oWHaR9ge3/ofsqGdTxiq8cnRujD9tf4F1NRLvl67veHgdZx2hgTiyeLV9GkaVm/7thZrYCx9O372Gls/iz5vIyMbBEqz6NjpeQOpX4Yw9yUmVS11S7tFXTml84JjcmKq8iXi9Cpie4hVYWt91phcyvBIZeKMKqHkbNUySwWn7UjoF+ur3L3Q2pX6FJhffvnl8N6vWeHWuGzb0aNHJ7cPIeCyyy6rPt/a2sK73vWuNat8qh04cABPecpT8KlPfeqLbvtI21lb5qdOncL/+l//K///6U9/Gh//+Mdx6aWX4pprrsEtt9yCV7/61XjSk56EJz3pSXj1q1+Nzc1N/NAP/RAA4MiRI3jhC1+In/7pn8Zll12GSy+9FC972cvwlKc8JatbzqYRkPNaAGINKRiw2UaTSEXzggPymUbPBSdb56/1hVBAalK6DnAglkAZYJ3S0dZSE/qZdI6qFxpALvAAKPhICgEtgpzBr6l3mrs9cS7vklWXJjtPyFkG5QzTtIt1sGnT62snCwX+ypo/Q/QrAyCTCtg3q5lqIpjYt+0PkCbrNNpKi4g/RSgRTwAlBUdeRTXBZvZagLKCmgo6yxGiU59Hhve0tn87bnYs8z0igsv0EmcKJjvqI6doXelpeZ7SeHsB9WXYxLBaH/uRS6DaxWoXOwK06zpcf/31uOuuu/C93/u9+fO77roLz33ucyf3ufHGG/F7v/d71Wcf+MAHcMMNN2A2q+ul/tt/+2+xXC7xj//xP/6ifVkul/iLv/gLPOMZz3jY/T/bdtZg/tGPfhR/9+/+3fy/Lhl++Id/GG9961vxMz/zM9je3saLX/xiPPTQQ3jqU5+KD3zgAzh06FDe51d/9VcRQsDznvc8bG9v49u+7dvw1re+9RFJd2zE3qx5o6rla+IuhZag6sVVYJslq26MCdjUkWRBswn6AWTpvmYFU71NC4CtFWv3V3a5WkabkP8MkjatAICqEATKuARaB3jhzIGVoZzsZNdGedr+2XS19nom6R0TMKV9bIGYmslQz2fHyE5iGlOgE4c6v1Xl4RPw2WXxKnJlXZeLKWNac99mEyCnPJCxk0RjVQZDqp8prchEQK4RKtdVijxP3Xsg3TfmIlvVcbD9c8KBO0hSMIAy3cLdJjgOGFyH5RArq3yIkBqqSPz+RUTz85Foi89y/1tvvRUveMELcMMNN+DGG2/EW97yFtx77724+eabAYi44nOf+xze/va3AwBuvvlmvOENb8Ctt96KH/3RH8Xdd9+NO++8E+985zvXjn3nnXfie77ne9YsdgB42ctehu/6ru/CNddcg/vvvx+/+Iu/iBMnTuCHf/iHH8FVP7x21mD+zGc+84yOMyLCbbfdhttuu23XbRaLBV7/+tfj9a9//dmevmohLcU9AKRoOAUEVRkAxUofWSqrWL03o1j2joANR2kpy/Cdy9XbWwAHDB/PNZjp33Z10O5jH0mmGsTaSUB2LP3I+cE1dN60lju3fVe6CUCuIqSUkjpVAUNPmJe9eoWaiEw2/bSyUDbbtm3KAtb91Q+Q5YdKxUwEh+32N1BzoyoZDJ6K2qPJ5VNNWE1/mVwudAGUyRBYd0bKdZeVla2rSmlgtKt6nQrykdncU1uKsL64GVGuAuUgRogaKZQs851VFMME5RgMlMLXhFLG8FHanv/85+PBBx/Eq171Ktx333247rrr8L73vQ9PeMITAAjFe++99+btr732Wrzvfe/DS1/6Uvzar/0arrrqKrzuda/LGnNt//N//k985CMfwQc+8IHJ8372s5/FD/7gD+KBBx7AFVdcgac97Wn4kz/5k3zeC9GI92A874kTJ3DkyBH85f/9rDhByOWCzQoOTh/U9MIqSGg5NpskSZuqRk6nMOvOEzaCQ0DEiNoi123ze6zSOXO+dtkO0zf9277U7WSgn2sGw8ohiPUJoJ0IbGMUOaL2P1+3Iykfluqpali/dSC3Kwn7fZv864sFFdqx2a3v+f5NOJPtPeuT3O50ymWi+wICnJ0X2mzuSRJZ0URaBjTgbYuRmI+zQsoEcqkfwpuVjN1Hx8fuo45QQJyjuoCoLPupSTQfC1U1LLW6iaQ/WhRjZ2Rsr2J59qFGBqVnm3Dy+Bdw5eOuwvHjxydVYuej6ft63a3/L/z83IphjMstfOK1/+iC9nevtj2daCtn5kt6cKAGREtFOHKgYackxkrN6nTZ/I4sL1pkYDQyNn1hM/Vhz2MScVlFQgu+Cl7qILVA6KgGA3Vu6udKLQD1y+8bQGgtvyl8rbzzcZD840BJ/mSOMQm26VrPNImsVVqaGAvbqgmyuVeZF0//axIqTSSlAUOFXjIgtxuloGqWBuDV6Wyv3XZVQVzUUPXEZwHZOmHLdTA0La5GqerKSfdvnwUtsqGRpcRkgr+ERhnTTvoMd46AmUsFy2vwD46mSxtewLafaOvCtj0N5rmZSu/5xWzkcATkaLd2ad5GFUpAhliympFuzepqwHstLa7+nfrVWugWhK1Ujla9KBKsSsbss5v1B7ONBRCVtKkzsM3mkl9ypR6akHmdQCbBuvEfMMwkZ8fBjIdMhGUVZbnvfC2Nf0AnvTZIbDlGrEbOWu5olCxScm2XF3/KsWonZMPx65ja33lcUVM5Pn1qJxSgRKjCrIxs/hgxHOR/npJANpeh/h8AUuqOCMHJb0tqCW3IWPj1508oSrNK2W97vu1pMM/BKFycU9lZmTdKFExjYen7YfnZ8pmGTAMzv+780/OQJtNyTgJRLLAbgFelBDCxjOaoXkCJTHQFTIF1zn1keREVbPU4Cqr62cjGyZnUEW1TXpzTOHEKw7daZtsHa3la56cFL9J7YMafzd9kADOPexqDKneNpg5O/yrVpNJFe09WzUyjWm11hAqPXI/hEFlKprUW+S5jrs2ROEA9aiCPDAwk6ib1P2h/dT+dTDWWQTlsa7hbkPegLF+0nDmnB9g7QgdxambqClL5yd5tW/gkX9/Y53G+WM05nAcH6HnqzKOw7WkwV9BgkxNaWy62gKILtiBAxvrT7wAbFi3L9430TX4EFaATkOec3RbAOQK+K9YuJigKGGemHjosQMOOFHcAykrDNIIWAC6fTYXlExXFBTOq4sxAvVy1lJFayXbysbROC6T2GArkNPSwAUPZ2m7GyZsJr52Agfqa7ApK+zX3QnYMq8JHh6TMCb6OplRwRaImgqN60pmwyLVNUUw6xu33ngdxcNqVlUnw5oB8T2yzqy/9LhIb+qyJDkWSJwJZsljoGzNWDYhrXpoqq+VFavvFKS5s29tgbvTftuq9ApJdngO18sQZELW8tlq4KtHbXjE2g6EjFGhckFlCAVsljLqNtXgmNNRr1Ek6BrsgUXxR6Jas4kANGgOv0y1ts4A+BeLapA/ORFYij2MGBVZiobbYq0lOgTxvrycYatrFft+upICKvmkn29Jf6Vs/ysTriQDHGchdihfIOcSR/CMs1ZDkvpl+UH1trTJGx95GGLf9AeS5sGkZakVNHdBmzzcFUcwAk0w8bEAeEH9OcGa1lM8HMESDrqCuY+kIWQnFPlTRtBejfSmyJv51ansazHM5NhPqrU3VLa32HFi3LC0oBUSMyYEpOcMbp5zhgTPQWE5YKZ/WEjWTx5SiJB+bHDhAil6kQsEYe9Fip37l1K9ALuE2ZT2mzoHSxNTy7a3FbQNoJKikdl62zswygInuGnpQHMHOAz6sb9sCRwvwdihQA5F+ppOaKpXUmbe1igL+BJAwXxnINUlVpuXiADZAtps1DkxTLHbM9NnR3zox5j4nxyWAtcAi6H7pAHmCN7y/augFtAs9Y0P7gWSZAyCYUnMoxoyWqKNR0jYzpejQs6whsN++fNueBvP8EqkigVy29LT4slaHUVpCJHjF8UOuoUlQh+FnJ1ojk7Pce9b2wkwwU0oXo8/WVqR5Li+xg+rH7TH0/Om7MRorj4tjTbTMtMZp2zRXFtAzkDcWqtONjLyzjTjNLQEkOEr+dkNF8Zksvwk/R6adJvwN2ZnN5f4pl0wkXLFa5UTCpXdpZ+8I4AJcNJbVArn1FY7y9Tp52omv2q75zSjPjjqhVYmieYFcY10yl0nDWuDOpdS9jATQpZdRTPDsXC3yRlqjf7KxotSX/h064ALn2LbNJsp6pI33LfNd254G82opPPb1lwkAAwAtY5Z14IbLzp+pBTwOQNjMec2DM8ebiLS0S1hqFCFrgK6H0s9Ss6BbPjT0zcT5rGa5vuwiwWsBPS/JuQGhCVUOWdCeAnGdQC3vHDrk6krJMZxXF0BFP5gOl5/E51rw0T4yBOgjAyHda+aYAIJTznGR41UWKwSQZ46AmKzxUXPccHKoTd8vSufMfDuAKSipnbFFdWMnUJd3ro9AQErdmyYNAvpBYhwIQqc4Ep8Hs05MZcVh+9Am6cqOT3Nv88pRo24vYj5znAfOfFpfut+APQ7mQAGIStFCTlKAaotbgJX7JXDipHQh5dWT1TtkXrSAp0/HnWqZL7WUzwQNIRuHvJqwksU1ysVKH/Xc2XovaNUaKlZJocCt4ALUgF5ZvO3p9fh24rOt4bpLVGo9RhnIxyF/V4F6s5LJ4z3hBM3yOt/l869izKlvxdFI6W8FNypBUQCqME6OoJj66BtA1+tPFvpuWnq1xHVcW2oIqNU+ch3yjzrbmevrDE6oo9GuDG2fzN9lkk7KF0BSCYDKqioFg+Xmu+JL2pcmPmrangdzTWmqipacJyWUnNX5oWaJ5PSuWCleATU573i2QN/Lq6WAIO9THSlol7A2Zau11DMlYCYZxKEsedOx9Bi2ObuvoXeEYxXHprZWmdICiQUX6wyWk9eTRQZTM5FY69oCeE4P7EOpx7pbc/X36nzj5vxV31DTFxlQzbbi21infkdmBJKVFev9Xe2UVVjjkM4TjKXdkPabSJug/ZwC+NznrPVPXDeQojRTwJBOsCQyxJ0h5mLQsn/5vp2ANZOjyi91+8hc5H921TP20ApQYMmtc7GBfF/NcmHbngdzQKumC9c6REkclXO1MMO7riQhUiuInORjQQJhCsBMMiGOPGIYGcHXYdCE4lDSiSA7rbi1vgqgV1TJBDCoVbfWDIBa+aEu4acSYtnD1CxruY78vXWyJhCrIh3VSRhjWtu7qk/Kv2Zg3oVPnwTOVtYJ1JNB42zVa3GEbJXbYhaeKCe+coRMUzhKqWdHoVUwroyD1jz+UaWZhTaqVlooVMhuMQP6d96GSuKyKdi0E//IwCKQWWWkSzfH1hwua055FCCfuYkoS+u3seM5db8uYDsfibbOdf9Hc9vTYK4AMSYAV6tVmwZqADXnqS+Q5Y8FrNXaIwRP2UqiOEhADdQxaKy2bE266jzWarMyyKk0qlYZUQFEC4KoAV3fdDLHAMdScMJMAlMTSAbytKph850GRWnhDT0e0jlaTX998AnKovnMArkNJFpzGDd0iwRN6XZCQzAnTbaTybzzlJ3XREn7PfSSMjaOoDEWiqdV1CgNo3SR9RdwhDeTsd5jazFPWuoqEW0+V4d3G/TUArne21wTFYU+U215CZKiKsvmmo5fab71bu63Pd72NJjrA2kr0rff2eWpzW5oQdMChSPgYOewycr1irON2pe+6kj53GrWp152+zmavtg2ZfXpdU1dZ27Ny8sok51eo6YPyLltmuao0A6qoCkdG6bBGrJP7tsuy3jimKmMnLHPWulNG3l9DMaU3x0QINweIjovHLPUb7W0U6r7mRFyekJa7/M6rWSlm0BD/aBZ1ehRFHxRAF1WeyndMmtaWllNnEqmeWgu2jUrME0gFlO+Fo0IzRQPlbiB3VRIFxvQ93OzXNi2p8FcuebMI9I6iOvyGBB5orWMLR9rE1rpsdywI8oHHwpfrTtbyV5zPOuMnVoVtn1oAWAq66Bejy1w0FIqa6qUpMRYAZina+/TzBKa7I5AOb5QGcmZaa3XiYjJ1nlZD0hjZaO24rMj0xegUYvZXtvUZKgrDk8C4BoFCQDbQ8Q8CHAMkTHXEmqASCennNMtaCu1NNVU0ogC6FM0V6sqsoBumyqmtlecQXxkkVUykFcadhx0gp4lgLR9sKu0rN5qKEHbv4vVzgercxFZoT3X9jSY67NolRtAI/UznK11ArbWOsyxdF8OC9B4KgGbyRWiYGMsnuq9oKKVtmkF2uAXmN9xAqQtOE5ZfQpm5YN1hyVxxEYCJQ/5ezAHWnOsJaucZ4tyDHNsq/XmFgDbN63Vp1uJnNF52zqh9rhMTnTz9rym3wDQeYcj85QKNw2iUg5SqAKgOK4rOkwjZjAaUHe1nn3NAWzHBmXs7P2cWnEhfy9fqkMUADZnKcbBrC4k6hQVT2612hbI7bPAAKhZUZFbjyTeb4+etqfB3DYbupydlEAF5GpZtxynBX8tUqFL9o3QCfCY4zgC4AJo7Eu055TzrgV57M6tWung1HXZfdQRp9tXmQphHFtWW28saHXctpNYcdzVQKXbaqj+ro5KbZbKmKBpcjj5akcckdq3BDYqTawmODPGBKw5hB0lQzqWQhuOCIvggJ1eJjgL5qozJ5JAFEuxcEwav1p9o2PR8vh2crb+GP1fm5UoajEK/Wyeoto4cnbBEgrvXw0vIQeH6XnsKlU3b/9Xisj2dcqHc6HavgP0wrY9D+ZfVB5mtiNICa9sfZJbA/Wq6IQTFYQcqNSJ1FbJ2HZzOKFWLei5pprSPBk8zf/tMzypS28t5dRHBaKRQgrTT8dAebmroBi9HussU6qCRMOf88YoWLd0ClBxy9UCQpf984Nr+2k/1qoGpfqnSnfZ8cigDwIT5/1neqFhAR520r3xZrIZM6Dv1iqL/AxWuf7tzf2z/bTh/Y4ZI4yF7RjLoVBFmovF5ju3FrkF8pbWsauY9Yspn+t7czEN9H1p4oVtexrMW4oEqHXWtpqQgrSCoKbFBcox1CrvR+Euc85nYJ1bbRxolTSvtUyxTmdoa1+m6muuwdZagpMTg+2fAq8BZkdOAqI08VNaOdjjeU56e2+tZOQsezn3ClCu1VrnZjLL/eVY8+3VBdf7T9FllhLLx0MBWtVl+7Sy0upDnoCNoDw5TZ4vf6YOWKNmOZN0zwJ2nuws5dZYwbpPpvYScEfmHAVqHdUSFVrklUrLaF56C+R2AoGeO0tnm2swdAujJA67GG3fAXph254G87bliDqsZ0y01qd9fPUFUkAjFI2yODkdbNSg5XRzhkBywrGOg1is6fuRUThf01qryJ67AuRGPdE2C8I50m83D1E6TnBU5xvhUpxZj8MB67SR8tuEQo0YeqRdkWRaZGKlkvfJF7IOmlMOvcxJCyGcKTPlxiX4s1APi+CkmPVsAeq36vO3w0NF/TGprDH3pJrk1resJ3lzDZnqo5QPPUGwJuJSIG8nfgV2oIDZVGRv1VedzNvPzTO1D4uPrranwZxTcn9HxcIYuSSZYmaM6ZGdenAjCzUaYwq2QAL/sc+gLdZrI8HLHYigYQnuDpSgE81F7kLFZyrwVi/p2gWVVQA3L1tLJ5H9PaHLtse0E5Dy634CPCtAN5+LpzWIsodcXXqPY44uXNNtTwF6Q9/oWJ0JWLIFbCe2BFaOHLy1XB1ALCXUYgrv98Ca5Z2douRAEcDQyzbqnHUTEa2NpZ2vUa/NXnPzN5lJ04615s9qV1oVnZcsee2NPu8jqFp16nnss5AtdnNv9Lo0x/rFavuc+YVtexrMNTugpqtt5VtZWx2FF1VQsE4qW2E9MpBzcvsi6cI41BpqPT9zevlTVGFDwVjO2O7bOsVKv4t1mB9ZAyhWLVF3ZII6MP1owbdSqTTHn+qj5yjOQ8uNT/RvUoNutzfOUOuQ1nFQykev037fAtIURy/Kj1LdfojAcmRshrS6svnmbZ9dAODzZCX93Z1zzs+YPd7UdetuwK6rK4eSVRFYjzjOEZ+ogdeuJr9Y04nQXnd+by4iNu7nM7+wbZc1+d5pap1b7q+VhSno29Skur13ktQoq0bSS7jyi8Srx6JqmOLLG4XEVFM6AChWlP4QxBGZn/EWGMwx23qZu563BdyWurHHaCePNGlNOnpN36qgorRftgpVRcOxBAYZS9FObjoOrTOO9BxxEMtfj91MDATk+9cmrAKQrHPkSZfimCY0e4HmuPp76Cer8VT9NHleqn3bsTLXVDnZqaz52nu69n/iye190VgISvl+8oQ35cswE6Dw6Sh5zvfbo6LtacscEJqEuFjmUyoHa+1YEJ9qlIKEIqfCFnGivqguxVtLb9Li0z6sy9zsPm0ZO6C80GpZtTUy8/4N4HvlTNN+VbEMS9/oNhOW/dpy31rDkHEBNZRCjJmSUt65dSJmygR123XV0VyvFpbIed3TJDxzlB3XpRoQcrHnzCOrFZ6zVzZnnaKK7GTGzX2x96S9P2bVoG3KCW7HJh8XtVUu+V2KP2DqEIXLr4F7sl8N5XIxmne063v3cBvv0yy7tj0P5trsktMu3YEGKBxVL0KlxeUIDh0oDuhcAgoXpnOlO7ceTdikf11TwNjPASAXT3Ylg157Ho5rVvRaM3nUHUy/J6ihql9TfUv/7/rOZN67BjEtTpE/4rgOFOkzO8muOROtv2AKVMcB5OtkZUOKAPUOOU/JEMVS76MkI+tCB1o2Y+gCuFHZsA8VZ94W2FDe2052rew0Tx6p3wRUY3EmAcmZJjQF9MyRc1FQ6XOsn6+F8Ov4WSDHxdeZnyuYx30w37XteZrFE+WCua26wJOE8KulQxwREPPLwEBOUzoysgXLxgE4MpCLMwPCqY+9LMMTZw4gW6ZrATXWqjcgrp9b55V9r/RFa3XOa5WMWrqjbTbla3OsvH9Dy+iSXbMhZmC1/WiBwQVUpeJSIQhSqsWcw4JOnoQNPUOWWrHjFlNqBScpdxXAfNJlE5AViN6VaHxmFuCebSRrlevrtemE00RVpeu1tBGmJzpNHaHP1RollMbUxjE4OvMLSM333lE96ZuVYWXI6MrRjpv2SdMamD7vt0dH29OWuQKxjYSbWoa2lq21DoFalx7IYaAgleUmUsxmhQA55Cwb5qWhtjhD2scWbG7BVJfqbZSj9kknqYqe2GXSUNUE4NbBZMI5ly3PqQminSim6CRzfiZXUzZano9EEaRFhFsqw14TjT00L0wlF9S/ld5BcVozSlRsrmzPJQp0VMd2NEnPSdIIkHPgoa+uyU56bLZvx3q3mAF1Zp+pqUUvMkW5s5G5svIlG2Tavtl3qk8K8KSS2obiqvZpj3UR2vmgWfYt893bngbztlU87y6h7Na6WkXklKGaE4NcwCpy0i7LixaZCg+pzQJbY9kCBXyyxNGF4gxs6ZIpXlOuZH1S2o1qQeFwJzM8GlpF+5FVLSmDov0tA2opiUaS2AJFXnW4VOssfWf/tm1i8qA45HNmQB0FhAkQWktzpowCwD5RVd4R5kkVMiNBSmfKqMEFsJ+tW6Ja5i6voCIQQpGYTjS1sKcoisj1bzbb67VWKieTSVGiQ5FlltU5NdAL5jlo+W8A5EKZnG3swcTk4hFr/80FbvtgfmHbngZzW7gWmLBcLYXQADuRW6c4VDGAsmT3jiQfdvN+sQ8iYXTJCrbKhxjX3x2lIqy1a/+eiJCcem6r1KbNSdas9taa1HOOxvEJQGt1IkZQ7Ms+7fE4rgPDBAdNvlS0oTQebSGKNbVF09QKp2EpuyUgr6iidF81X/xoRkFSxJaAMAaA0BV9ufOmlJ2rVxHqGB4102KogTPdB33ephy6tuVHx9Ie5CT/TArv10CiEXUKX6C2yvM3KcdN9jFMra70mTdjnilHpbRaf9B+27NtT4O5BTu1trMBRA6klskuzSMt25PFqTlbRDUgxSkC4loWQguotFoWjbk6pJJll9PItsBoAclmFESxkic58DQJVfQDDH9q95laSUytCDgC7CpwrPKVuFCs8i+yGtHtWYGCY82jT/H09jNgzYpnP6v3bcaQTDk0lVSGtDIbXCjO1TgUBVIcQKOT++a6WoMOoFXrVYogy6WjjH9L8wETnLQdM9ZcPwE2kxaznN6h/FaqT59PROHEaVzJ8fwMoNppq5NTdd84Vlb9xbTKgX3L/EK3PQ3mLYDnZh5aa13R2EvwiwWTtJ03D7yDR89Cr6wVISZX9MfkwD695BpNmEL6tUgwjUPmi/PSN51Hj5F/t7RDvtDaEs6Arh8Borne7eU8E29qrHOtWcZEpZ/WGrZgNjVZ2HwwOpHp16oQsdffAnmzD5wrYDs1XnrOdL8DDJ+9PI0wP5AliNm+NZMeMVd8eU6FOzFOVak7Q5Noq+IUDKduLWkLoDYil4CclphMYnYFcqAxUnTMFJTjCKmlMm0A5GuxY650zEXMzRLcetGNs218ZlfEX+u2p8EcqK2i/JCbl1xAajAAY/hZIFtc6rijOCB44c37MYKZMHfF0t7Vr9VSD/rymMkgqxzsb93XApNd3p/BQm/517XjtoBprd848bcPlfOxPeeu1r29BrM6qb9r+jJ1XdqXNGZZGqiUlnF+5mvWAhd6njjAbR8HDTtwHBE3jkAdqxI0VNIZw3cFwCnlnaloo9SfuH6vIqfJI1EZDNR8Nrk1CobSxMGhA7uAVQTGsZpqqmad7/pbHepaMEVpqDIh1fc1hyXpPVXq5UvQ9i3zC9v2NJjvmmjIBMzIH7tYplpNhmN2qLELklkQycEVGT4EBEovRmzAMllGsq/P1pdKCKsgIAX0Ces2K2RcAI078vU41IDegqChKvJKRHOOJ+VIpcxQq9kUhpDKBwVE2eYXnxq3L8J1r9FIZklfXbs5Rilvlq4nlolMx49DV987XX3pMYYdsO8yWNu+rthhFhZwGtWpqzRAJoOJPoGcyE/jKFSPSiJzbEDTl3ZcmkRXZGickQI0H4vSKiMLzz9GzsDOmpQFZkJI5+OwAGEHSBGtQh9hEqjXjAJzX9j7te33295sZ7Vouf322/GN3/iNOHToEB772Mfie77ne/A//sf/qLZhZtx222246qqrsLGxgWc+85n45Cc/WW2zXC7xkpe8BJdffjkOHDiA7/7u78ZnP/vZs+89Fy1zBmRjQbKCVBwygNHQS1EEdQKOQ7GEk7NIU6qOSRFBQKJIDCVhpF+aElZDxTFKfhf7AiuYKkDZajprC9082aQ8MVZrnYHPXM8oP3kloNZ9nADdvAIZQavtSq6XwV7H0P60nLnty0S/1gB/qi/mvPl7O8678bp6fFMODuMg9xUA+xlidyCvtGYuTRia0TLf+75OFWAmABqWwkkDAuRpDFT1NEbGwMAAhwEOfUxpladWNPos+pBTCwPCcARH6FJKCYL8r6liVVeetetmnBlIk4tP1Bav3xdLEdrJWcfMdxjddPWlC9E0aOhcfvYTbe3ezgrMP/ShD+HHf/zH8Sd/8ie46667MAwDbrrpJpw+fTpv88u//Mt47Wtfize84Q34sz/7Mxw9ehTf8R3fgZMnT+ZtbrnlFrz3ve/Fu971LnzkIx/BqVOn8JznPAfjOE6ddtfGLeAA6zznLmAgVdpXBQCNRaPL2UVw6HzSsDt9oY1Vbyx/dRja5FtIE0XVj2RR6mcKVpa61DS6xCz9HPoazOPQvJyxXK+OQZpwSAHPqB/WHLC7OYnPxgJvttfzZjrLWPw5mKjNfdKczwJ5djgnRyal68nbmPQBasWznwHjILVcE03GoRNQN/2eCulnPwOHOeL8ANh38gMg8IA5VphjhcADAiICSeoHLZS9NqE1q7WAmK171cjr/vp3Ph6QI07tysbSOUxUcszb+9Gkbtb7oQaCUkMXq3ly8O4cf3blOffbWdEs73//+6v/f+M3fgOPfexjcc899+BbvuVbwMy444478MpXvhLf933fBwB429vehiuvvBLveMc78GM/9mM4fvw47rzzTvzmb/4mvv3bvx0A8Fu/9Vu4+uqr8cEPfhDPetazHnZ/1ooe2GWvpRPSZwASLwyAV5MvAPsOkYHOUUlslV5Ex8q7u+wwpDiuJW0iRrWUBadgGufE6WStQMDw/oZ3zilbiwVulSFrkaYRxcHobF/WaSFwTNeerj8pVgCsRXZW42qbBSubh8asirKfItSKlszdpkLOOchlNOCjQG8mzzX+13bHBRCMbyR05V6pryMOkq54WGZaJk+OmppBr9slmmW1A54fFCuenORFt87hxNlT8+zZfDg09CXPffrMkeRal//Xc4tnfhwTVKJOwkh0WoqMzWNhDRodRx0DzQxJ7mL6PvfbRWjnNM0dP34cAHDppZcCAD796U/j2LFjuOmmm/I28/kc3/qt34o//uM/BgDcc889WK1W1TZXXXUVrrvuurxN25bLJU6cOFH95GZ5WbUG1Vlmmy5FjUVN4ypzodpW0VYoYmwNEQPkwc8vqKEEKovcthRxqNa1WoZTgUPc/AaQglxCoQYA2HQBOUw+0T1sOV0yFdmtBa37MedlOc8Wsq9SKVPNLO3XKBQL+u11KSja+9Na31MBStU4xhrYDXWQrXWOQrEMPWiV6BGlp6zGPfWP/Qw82wSHObg7AA7z+lqcK8cJCayVxgmdfJ8oGBr7avWTr9uMt2w3VOAe2OxjxsVWzyKUFVuliknUUF7h6HNtxtE6Qtk8H5LauTYkLlY7V4rlkTpQ3/jGN+Laa6/FYrHA9ddfjw9/+MNn3P5DH/oQrr/+eiwWCzzxiU/Em9/85ur7t771rZkKsz87OzvndN5zbY8YzJkZt956K/7O3/k7uO666wAAx44dAwBceeWV1bZXXnll/u7YsWPoug6XXHLJrtu07fbbb8eRI0fyz9VXX506MbEMt5Z4AzTqoMzWWANChHp52znCRqpW47lw6xbQFRgr67zlmM05FNDJvMT28cxL6XSMCowNgGlUKbtQrL4ExtXzbvpB6jsApL/eWNNN0WVLIWUwttcxRWE111uB7TgUVVG7X+tUbkv1VauABrT0uMOy3IdEc+kEq/4Dni0QF4fBi8OIm5eA5wcRu01wtymTWqpryilaVGka8Uusqr6xS/nPxyGny1VKTa+3dcDnzJjeRNlaiioOKfahjP+U9LZ9BuL8QF5JwHxHY4mPyCtPfaZYHNLDRTTPvxRg/u53vxu33HILXvnKV+JjH/sYnvGMZ+DZz3427r333sntP/3pT+M7v/M78YxnPAMf+9jH8LM/+7P4yZ/8SbznPe+ptjt8+DDuu+++6mexWDzi856P9ojB/Cd+4ifw3/7bf8M73/nOte/aBPKa4+RM7UzbvOIVr8Dx48fzz2c+85nyZTQvTUzUSvui2L8z3dKBnZ+sNM9Iyf9J6oDSsFPKjnmTUIpjVd2dnU/H3P1as9WYeN81oISxgFO/2Qtgq6SN7WThQv7RfO1r19xY51ZHTi1gNtRMpUCZsKyrdAnNhLo2tlPl2PJxduff14BcW6zBEmNfHLp5FSXBNTSu4LaPwy1PiWWbOONVTMBnlS7qSJ3Jy5mLj2hfohkrPZ/2UQHe+lbMfllt1FZrsn+3E6idzOxqK9FEeWLIvpaymqkEAnasyKXsko9uruW1r30tXvjCF+JFL3oRnvzkJ+OOO+7A1VdfjTe96U2T27/5zW/GNddcgzvuuANPfvKT8aIXvQg/8iM/gte85jXVdkSEo0ePVj/nct7z0R4RmL/kJS/B7/7u7+IP/uAP8PjHPz5/rhfUWtj3339/ttaPHj2Kvu/x0EMP7bpN2+bzOQ4fPlz9AKhfgiqPSGMVG0440wt+VlMY5uUhlLznDIDDIr/YUAonvXRqmWclS3rRFOQngZ1cUUhMnDtvo333xvJurX5LgUw1A2qyKhhL1kCb5VH7kCaaSQdnu9KYmCxthGIGHs1/opta0De8tu1Hbkoj2GbAtAKpicmrAltyoDjC9dtwy9Nwww46l5yLoZNJ03e5fNzacfV4FljbClPaFNQnJqV29bi2WqmiUY0z1QYepfuafUMxRXtaxZVt9jnQLl5kHD+flnlLuy6Xy7Xz9X2Pe+65p6J0AeCmm27aldK9++6717Z/1rOehY9+9KNYrVb5s1OnTuEJT3gCHv/4x+M5z3kOPvaxj53Tec9HOyswZ2b8xE/8BH77t38b/+k//Sdce+211ffXXnstjh49irvuuit/1vc9PvShD+HpT386AOD666/HbDartrnvvvvwiU98Im/zsFsGzuYy4lA/zObvSXC1mQxZUuSKZAwpi5/hbFsQ9bOiJqgcaMVilrBxseh5Ni88fWu56stujl9dq92usZ7bSj2TQUTmMwUlSweQ0hUKWO2+FoS0T+146ErCWuH2XlhO11ImU9fbHn9qFaH+CDNGeSJN90RXTjZPSba0ldpIk6b0X1ZBGjLf+kUqX4jtRzs+LWibbWi1U1MxQKbfMr+erG4a+ix1LT6GlIo5JSLT7at3wQRfVZSj2WaYeDwuVJNc8+f+AwBXX311Rb3efvvta+d74IEHMI7jGWnfth07dmxy+2EY8MADDwAAvvqrvxpvfetb8bu/+7t45zvficVigW/+5m/Gpz71qUd83vPRzkrN8uM//uN4xzvegd/5nd/BoUOHcseOHDmCjY0NEBFuueUWvPrVr8aTnvQkPOlJT8KrX/1qbG5u4od+6Ifyti984Qvx0z/907jssstw6aWX4mUvexme8pSnZHXLw21kLZUU6Qkgh2nzbFF58+XLAtrQNLG6HOdk3cQhFaVolDIWcFrg3q2lRE5Vbher/LBt6oWbohvsdnY8mv+r0O/UF2ZvgyjluzEFvcQh50LR1LjV/vaaLfWStllLV2t9DABypPxu+nfbJwU9m7Z2YmJiomK55zHmQn2lQclh+uSTxr4HYgfMUCbWOIDSvdGapzK5xfq5SROEZHO0/gxMh5tzrPqUVypp7KVbofDxmirY3Ldq4kuZI3PKYYzV+OeV1VQkr5Y5TNv6qf7ugfaZz3ymrNAhq/fd2tnSvlPb28+f9rSn4WlPe1r+/pu/+Zvxt//238brX/96vO51r3vE5z3XdlZgrnzPM5/5zOrz3/iN38A//af/FADwMz/zM9je3saLX/xiPPTQQ3jqU5+KD3zgAzh06FDe/ld/9VcRQsDznvc8bG9v49u+7dvw1re+Ff5so9EiFyvGvGzsZ4UymODEATSFFIxzk2IGMvk/RWWm7WB/a0svzlQOkbaYxBRHX/0fG4qjPY9ZYgOoJpLWN2T51imJosrt7PmKxRqn120cCyDklAmpD4krLsnIhlq62U5WzVjlY2r/1eLM/D5X4J3/tmNi+2OtXluQwk7A45AtcrfaAdCDu02sItA5hzg/kHnuahUw24CCaB6/sTcUyCrfH2vZs97fLJE1AJz6bhNlASjPaqZtzMrHOXBsbnyi8Fo6K1OFZgXYXUQ0Px+VhjRoqKJbd2mXX345vPdnpH3bdvTo0cntQwi47LLLdumTwzd+4zdmy/yRnPd8tLMCc265y4lGRLjttttw22237brNYrHA61//erz+9a8/m9Of4aQTFq79exgqAABQWThAsYasRphWO+JYnAX0kbERFqDhRH0sawGFALAJPjoTLdH2V8/dft7SDA93SOw+2TI2/09RJArkiSqp+pAs1/okbvocQNGEJw22TrC70T6TwGutfjOzVFaxHWOdnDhmCzz3Mw6iLVcfhJ4rjsBqB+g2waGDW54Ghh10vkOezXSimwWwSd5FQCkpqJp1INMfapFLn8bcLwA1n564fCZK15y474js65gat0otoysh/Tsle6tonLEvq0IX8DBe5/PazkdulrPZv+s6XH/99bjrrrvwvd/7vfnzu+66C8997nMn97nxxhvxe7/3e9VnH/jAB3DDDTdgNptN7sPM+PjHP46nPOUpj/i856Pt6dwsFTBl9UD6LidJGuolrn35IzIQk30ZZl22ktiHXDBYk/9DeVRz3ir3iO7b9hGoLW8L7GQCinS/Bmx3U4lobnagdmrldU7uUwKIKbpEtzuT4oQkwIftNSRaas3yT8diJI55WGYr1Sa3ytfAXE8WrZUNVBbuFC+dk2iREyqpXcWkfO1ZDZTBdwX0W1kTT6tl2cZ3BXgjwCFk/0RkYMRM0tWODJemMMYc0XXwKVTfq6Z86PP1ZCoFAIa+PE8AqjwrX2TF0TqXARSpKpCLgZdt5e8hpSWYXUSaJaS0BefSxrPc/9Zbb8ULXvAC3HDDDbjxxhvxlre8Bffeey9uvvlmAKKU+9znPoe3v/3tAICbb74Zb3jDG3DrrbfiR3/0R3H33XfjzjvvrFR7v/ALv4CnPe1peNKTnoQTJ07gda97HT7+8Y/j137t1x72eS9E29tgDqyBT07IBEhAZZSyYAIAYw3CKSOeWpE5lWgCKg7IoKw5ssXJZB4oQ/NQ6k9VhKJtLRfeUA/qB1ir6gPU6XtbqzhPIGly0f1aq5kcJEQV9fnNdlyBbAlDb7+rfltVSgalWAAdqKx0oSwSFRGLRWmtx0x36XeYOLcCslqwLh1PFUBmfLL1OzGGBIBZreYerofot8kVjTkAP65A8wMYKYCZxbrVxR6AXrMgJtnfEBnBeTA8NhYLOI08jSZvPblMF2owkl0l5c/sxKXyR/UVKdhragpyWI6MzgfQsFNWj+neBAKCJyx3S+XwKGnPf/7z8eCDD+JVr3oV7rvvPlx33XV43/vehyc84QkARHxhtd/XXnst3ve+9+GlL30pfu3Xfg1XXXUVXve61+H7v//78zZf+MIX8M/+2T/DsWPHcOTIEXzDN3wD/uiP/gjf9E3f9LDPeyEa8cPhTr7M2okTJ3DkyBHc/38+hcOPuSSDSJXxD6jUCJkacT4DfiWNS7woyEn49iDJuESylrYf+6z40G3loAIM7HyVI2SSVvkiVInNw5InJo3m1G3Scap6mU1Gv1zIwAJAul4algaczYql7W+lAqoph/aaqjwrrUWcVxY11UXjqjie03Fz1kM9lFIi1vcwAUB2LAAkmV4oFjtH0CDPAs8Wa0FSPNuQSkTL03lyiQcuEy5950RyhKaJ1neJZy/WtD4n/chJ78+iY8/gTug8YSNQFQWcQdyqYWDAPI1bjg2wVnouzWd8Ey6AZwuMKEWe3bBTUy6afC50OPGF43jsNdfi+PHjX5SDfqRN39eX/tv/gvnmwXM61nLrFH71eU+9oP3dq21vW+bJamHMimzQAmwcygNurTgb1NEEq/BsgT4Cne9KQiygUAnOrb1oqm6AnRxMH3NrQc62lqYAcj4WVkuzufZcAKM5XqVXN8cTdUusrL61ftpjaXpcW2RCLcrGaufQVTU87blbh6WmDG4bKVDaPjX3M1M9drK0vHLuc3vd5fxg4+DWU622gTjKJJ70+Lw4BIQFuNsUMF+lSTxG4cptdO1qG3ABC+eB0GEIC/SRMUZgFSWl1SoCccXglB7Ck8Ni1iHEXqJIB7tCietjAGTJZJWzJo7ifE0BZdRvIVCKNFWFlx5Cqcc4gnfh4i9Uu9ic+V+3tqfBnMMMsdtYA7PcpiSDBpyqHBpJATBSAEfGQA5BLaGxLxazBRGONfcLpJejASB7bv09Bd7KayOkpf0o8sDQgVU219Ay+TpSibSStAtr/SqZGhVc2wGdGMcW8JOluyZ5S/0gh+K3aOgbmhoXPaalc9gAGSaOxXH9Ow30UfCKQzUxMDm5x/Z7pbUo5WJZPSgGwM4WcPBS0GqJGBaJPusAnE598ykwKuXi0BWhrirGFWa0jRDm2JhvYjkyVlEsdrXcJRsn5WNH34FCJ/rziMr5K5OGrx32SkUNW2u0EzFLBSzAqF4CBjisiDGbEULs17NW7rc93fY2mKd8zJ4NMOjLqcAYYwnHTkvTNdkWAC1U4UhetJ2RQS4gDFv5xaJxVUnNtAnXbmSVoxQ1lk7GNYdbZVHa6zHcabZimcWCojSpJOqnAnRyGJNTziZn8i1YG0tszSGs19I6i+3kdMabUVv/lTa6bclpmsennaT0umzfMrfc1wFXumKyE60rk0LlNNZ90oqncnpzBPodrD7zP2XsLtsBDlxWViKWGlltN6sGLoVJyAG+ZI2k1TY2XMC828DoOixHxsic85jntLkaYNZtgjmKqiZJHXPhkpRuAM7lTIzcbQL9Vgo2MlJcV8obckoWFtJzuIoMch1CO+YXuHk6D5b5BdRp7/W2p8E8t9ZZmAA0F/DlKGYorQN5/j8BgD4qPpXsyscEjFXoK/BgQuY8cySozSXtgKwAMcBTccVK0ZjzWcuZxgGx26wVDuSEG4UAuaYgIKIC5A2oyXFp11VLVQOz2UZpFLZ+gWbc14K0bGstf0s7WUCfoqLUR2D7ZSz6Kq+53l/rWDXjK/yyy9vTaikW+eIg/GVHER/6K/hDl2BI4JdjDCoNvKF64gBSSSqvgGEpKXW1FixHuJ0BzgXMAPBsDiYJEsr9t74CSk5ijgLUug2AOFvIdsElpVDqk+9kFbfaAnfCSyv1AyD7XwIigndCJ2kCsYvUzqfOfL+ttz0P5laS5wn1y5uXnKIP5V1kd22aWIZQFRYg5IUb04ur4F4CYsSSVivdHFzB2vKcQE2taB+8m176shRVICCDd0wOriEt4WeOEjcrfXeeqjFhF0DRBAmZICcylmXb7/yvflcFBTV5u+3+ufYq1047XZG0VEpDyeQxsqsYtUybMdT9q4lRC0gr0Ou1Kl/PUXLzGMqHwxz+0CXg0ycR54cQF4ck6dr28Rw4lFcVYy9WuJ5Xnze9NnLAagnYWISksKHlUMrMkQPSqlGzNhJHeeZ4PVMlpchmPX+paRpBWkSDCDEsgLCA3z5u6Jd03xJlKFx7nbZ1v+3dtqfBXB90BV/5pygEsqWs27fZ7DgKj9okrooQ3TbDAd1medmdN4Wg0wntJOBQQssVJClicpjHoTrnWoKtBuz0BTwVO4yRcWDmECHyNwLQR8ZqZHhH4ORsmzkF9MKf5rEZDbhBWJzdqJcclq+TQDuWMECuv0eTNyU5cNn5EkSj29qlPhc+vpVEAqiTk2meEgVrS22ZVgH5GYRbbrWNSOLI9o97AsbNS2QCZIkopimndqJHquAdckVCCpgQ/+a+ppbHROWPZAK2uk1wHEHLU9BC5DL2fVFfoawK5ULkWXZJN1/VpXXBpMDg9fiAC9z2HaAXtu1pMG+lepY/zVItawFxBIZmOauAkT7rY22VW+eiD13RHJOvg18yINmamobOqCL7akeeAmqlgefSR+Tri6mPDF5FHJw5eCJELvK3MTKcJykUzJKfvbKcW9C157CfNxLB4nxs+mXBv6liz87cG6C2ilsL3Ix3vodApTO3dEyRla4fQwajWM2quWek/CmGd6VhBeKYa4bybBM8PyBh/Dnx1aqetP0MwCaoP1X47up+6uQfaqrKWMf5/OqH0Tqyq23Q4MDdRg46y0VU8li6+pyJgiryUUpqlfQ8papLFI38NlnycXYAF6vtg/mFbXsazAHUEW75w3Vum63DSzdTFUJ6CUYFP8BY7mJl+YnzVI5Qy6daPbW12uKQwXBSUaKgFVGDZErWBQBHgsPCk8jeWKohjTGt5qk4iHb1E7VA0n5t85+kiSmH4uvY5msG6qxd5vgp2pQp1pSCWoZG4ri2ryqHTOm8EhS0iyVpC23oMRTITBK2rHxJ95fDrDwjRoOuslDaPl6A04CupFBeFItXs2vqhJPGyibXotgLTQXU0cJxyNLJGth3xCrnWKJHna8c2dlX44tTvMruOJxO12nysmjcgp+BjPGx3/Z229NgnvXUFhA0Jai1uI2kKzdfgkrUkeQt8OrLogEXKmnT/9HVuazV0WRWBpI7pPDq1pKvNM82EZXpH9N6FCgNO9hYnsaGC1gtjmCIQHSpYjwLtaKHqxy4bag8UCtw7LgaHXjJF4J8DQCyo3SNJwdyZG1eztuJIJ+7DvAq5x7yRLC2KlEnteXcq521zw6OWSJMG1VNHmuVp/pOHKAcU/KschxangatduBW25k6sYqRysomV/Kz2JXQuJKydJZOGgeQ1mtN15ylpylVcp58fAAMNVUl60o0IqG5l3ny9IWCwk4GfJv+92Eplc5T8+7cLeu9muXxYrQ9DeZrCoNquV4oFkpJ5fNnWoTAOM0qZ1vabxkJ80BSaSgVAZYTpeNGAGSkfHocbfpS2zSpCeBtqxyQ1qnWLN8BZAuLneSMQcoZ00q2tNyYneyybLA5t46NzUBYUREtJ6v7sVGFTDh316gPoDjsdkl5kGkRXxyLVm2Uj2nA3e4rfYv1uTlFvfpOLHEyjlGOmVKJ3QFZrWj2Q6VYgJKky/YpB5KF+rukuqnuoQHyNGCZjlGqh7sNRD+rZI0Yh3oFqCBtiqHktMUmXUGJeA6SwjeNvaWdpO2y0rkAbZ9mubBtb4M51w4zecHFkqEUTq3bZZBWJ1r6LGuyG+0yyGHuGDD5tLmxvABUYJI/ypnyJqgJPZZ5QbOF36QuBVBrshXQTd4RRxpNWB+/euZ1taCgGOvPpc/leqoc4WiOE0vO8/xZHrddrtcC7pTc0X5uAFuoB1cUGEBxcqplaybRDOIpPww7n0PvNa2DzYeiUaAc5rI6G0vaWqFadsq19DugbgGebYpFnPqXYxC4ZLxk3yFn4FTVSzqupnzQ/Cy5RJ2fJbomTR6r7axqWRtX5bzhKkOCjX8krwbDYn3itCkULmJuln0wv7Btb4M5gJwoy1iwa1ampUOA8jLDgp6rnH602snOLfbCVRI7YNgpL66+IH62HgDkPJQQb8PX15QwlsduLft28rCWeqIcvOH9p5zCANZTGNikW3pMywkbi61KNQtjzetyfapEWdm47rd+b+kW/d5eY4zgEKoxEkB262XddDcdv3w9s0wxsZ/VskYXUs3QAYhNH8iJc9MWoO4WOaJUrtvnCUfVOmsTk6FlqjQF5r7oBF4l3YqjrCLSvm7Ylm0HzfjY5G1pNOrVSs6l7dNnGvDEgJzD70eBPlra3gZz34nDSi05I9cCUB5q11hzShWkzUYGPJKGNzlFudvEyEbZEjpg52QJ7mhBxix1qxeqoS2US18rX2f5Zv3bcK9TVlS1nNdJqFVPnClku1k5TJXUqyx0XSU017bW1JpsefoWgFur0Fr4zeqnJB1rJsB21ZKCfKrJVnlooIT5a9IscqCdE/k+glJAzfZJ0Ew02xwW9XOk46Kf5cC0OKFe4eLkTtScROoOOTlaPo4dn5T7hcZeqCHAVBBK/pl2fC1N2I6vTToGyDW1/b3AbT9o6MK2PQ3mI6PiADkg0y0ZgtrSWRZgUULfK+BMH3mqv9OEXWTyUhcKo6Yl1NmZw+O1j9aDM2FdApDVht2s4mm1L8WxRw6Zi2Ufqxfa5s2uOOU8FsVZnB202v9US9Nq56V/Sd/tgmxvNfOp/wXwTYEIy3lXg9VYlc6JTj2FrOdjqUVu+2/pLKCoXsjVPLulKgywcXewRELqccYecB7x9AnQ4kB+S5TS0PQNWcmix61WXyW5l1roag1X123Bt5KxogZjzYzYBlzps8cR4r+pV1BsA+nGVU1NuQC4i6dmsTU8z+UY+2267Wkw9yz5KNZAzkT+rQE5kC0yQCzvkVFAIgIIAdSnnCwptSn7DoTtBOTNy6ettcJVIqaA3lqyFogsAOr/mlvGob4Ou73lVFXCZ6vMmLqSlXrHARhjpoPanCwWuKycEEDFe9sJYB1YG6Dg4uOYHDszhhmMzfcqAaRBc+2YcWxBu40UNQqRnJZgcVgKbOMw6PSDoNUW4onPA90Cbr4BHDwi2w874LCo5JrSHw8aSli/1cfnfun5lUNP9I/WGK22s9efaCCwyA4pRvAscfkpSyLsebKR4st9q84tkdBt31ofxn7bu21v30nDfbeh8JqXJYdcW025WrnkMKRMgzZcvbJcYswle9YiAdXKayiHyhrnOgq1pQ8sBVQ5JgGUGpE1MAsoJjVDW/CYJCGTFmgunP/6rebQlZWMnUiqSY8kbHy0EYcm+RRHsdC9q4HDauztOSvgqcE/3xc7sTaALZbwKgXblBB5GfdyD3O+k3QsyejoygFd0pXrduSAfonxrz4Hf8VXgDcOFgrFWs+5n2uXVlaJU/c4jRn7WQ3yDS0DoOjMqSh6OBjwH/tU0rCMiUxYXZlc7fM4roQ6shNInqAvXjkDR5Ip8lyPsd+m26MCzAGU5blatAkcNVcKDT0obsvLZKquEAXhxVdLeYkSeHNSHKxl5NPzWvAzL29rlevflVSyAXv5mbDO9G+b2c9YzjaaMYM7R6AFUu27Wba3lnt13ikQDosCANbCBoqUz5wvg13LizeRi7l/QPF5cOGalcqwY89hVgV/5ZarPtVFkbPWWrNbpkmAmKX+J0fEbgNh1sFf9jj4Q5dIbhOlSuz5tb9WxdJOJrqPuTZVyGhpuuon5VPJElZ7Lp1QNOhH/SShOFxbCovMs2oljEiTifoGeLZR8+4XuHlMZPJ8BMfYb9Ntb4M5UJb/bVEIIHO2+hLnSMYxPfDOwTuASR5yzV2iBXlVAZKlce2Dz7F2fgHpuOVFXrPKyWUuvRT5dTVVcSbr1Wwj6g1ZPnPoQP22yOxMUYK1wsw2H4ehdjLQmXNWNIlOfinhVU7Dq0Bniynr9kAtrWxbe205J3msLftscZtztc30VyWHlo7InHhSNvFsQ5zn5KTCUL8ttMliMz0LyenIhZ5q76Ol66i5xsncMjrmztURsHEQRZQ9vh2jsBA6KOqzXjs+SemYlHsl//adBCw5L4qdTK2kfDAXEcj324Vvex/MkaxMhwJOEWYJajeM5aUnB2ZfknWpikVfcB/X1SNGYpgtxlaFMGVxWktcz5cTIDUX0x7DcuK2OQf2CwnzjgPYL8DzA6bE3VAoIxfW0x60HD0npYWpQsTOXLMFVqu20dwktt8tB5yOl/OH2J9qTJRyCutVi3Rb6+C0qxd7bi2lR1RfJzmRAoZFjgAeGAgu5OyCtHEw8+OU6nXqSqCNZm0BfG0Fl6+rmdDHuJZ+wE6c1EZlcjRVjopGPCcCIw0y2pE+hnRc34kKCxDqLY4ltz/HFEw0XXH+QjTn6JzVKPtqlt3bngZzBopTLw6iN6+WqIkjTQUqMJEPG0BRJMQBI5wU6YWDT6XjdJtcKFiBw4VMd1RNgc1w9m0YfN6u3bkFiCxHMxQSSoQoz+v+jFptyFBJ1RnUondyjQBKBj6OqJLFkANg1ChKXdg0uHEofLv+n/eFOW6sgdyeY0qiSK5EgTYWvHL9lcqnpV1sOPw4AOMyB+Yo4Gu9VAHYHlUkp9JIHEF9yQtuV0y2fJ4F8pYWqn6zJoFzIJoek0ydad+mViPNvVWpIcchW+oSlCTHKz6WAYQU/Rzm03TVBWr7apYL2/Y0mJeIv8EURVCZXF2IQnZoLWexmGLSk7uhB88CtoeI4AhwhEAQZYtxjHKYS3h4SpCUj420hI1jzQ0DGWzRgFOVt8Xma9HjUCkB1hYr7qPkZHEgeBdALPUmpaJLAZ9SeciAn6WlzKRSqVO03/qbY9b1K29e9ncl5H0qVH+KcjDf5eAaHUe1NjlWk3bulgVBBa/Gys367HTPMjWUVheOkLIiphS9unFSBXFYVNJMJqqSdAE+B+2oQ32qnF6+dzbZl/L441BWgzoWJg4hp5BI37EL5dqN81SSdM0yjVSNh11R2FJ6oQNjn2p5tLQ9DebrfKR5MI2kTyNEqyCbtARlJw7QyAB5yXcSnCx0bbg2k4NLIF2BdeqH8pA5XWq75KY69Lq9jpyAK4VpAxBnlUoDXVeFZY8MLFPRX0IRfjAnjI7FUgdksioTiFi9aknbdMF5ud9OfPZ61JK1Vqgr+W7aQJ78ma5qrEokAScNGkrvi8omFyN2mSayzsYqMMj+bcdcqYgU1l9y04cyIdnnhhouvE1roHSLbQlgaYLLt1kT23ud/SxJmcIuZLC1ed+p364jWNUqz7x+Te1xmJfnBkhOf1/7QFTGehHbvprlwra9DeZqlU/w1NrEoZkolpTWFGEhS261KJG05q5LHnebZGqorPLqxTHny9zybs4yQPhKALmqDLn6hdK0rKbqD2uqgHEQrbEPqdpMwOlVBLPULPUx4TOEkg1qgWkU625jOKpCBWCHasKpgoUaUK+yBQJ1tXrrFLYUiV5re68y3eUrELItc+jWuk7HkCyJy8Lfp2PZIhH5mpanwIvD2Y8AcvD96em+Ta2qUKgyG/kr+u5F7m+V6qBZbZTnI1GAcRSJKQ31isNMcrnUXSvnmMowqWM59sU56meVPwQ6PphwJl+g5ujc1Sz7lPnubW+DedvWLHXjrOJYajJmcBV+d3QdmBkgyUDIqeBufvC0Ers6/Fonn32RyL68VOc1sXzpOIj80Tj98vEV5HMgVPlOLenRb2CMks8cAIID+lF++1RhSB98LR9XdNi11ri6noYGasPV16SCreX+xe6NXbXoamkcCtCoRd5QBWsSSk6JuDRfSpCAGKmv6eptkVY5q2241TaGzUuAOMANPWh5suQKt9di+5rvS5uCISBnvAQAHoXasQFs6Xg2OEdXBZpzvZKtmoLVIv+kkuXQKpNU5mjHRSck1bWHOTC64jRNCh4xIM5Ae12gtu8AvbBt74M5uaIvtgE4QOX4zA5DP1sLoHEEUAJyQMBwSES69x3g0nJ8WJZzNtZh1XT5DAMG2pJTNKtsWutVLUvfFStMv4+DWOVdh+PLcsxV5FRViDBEKSXn0/XEKcvc9NfWSEULgqbvPNuQbYedkt9EgT77Kcz1TAFFMw6ZBjH3MNMJyi/bykxrtJWRftqUxoZPVv+A0hZxcUgs4aEH9afhdk5CE4y1dTbyZKzHs/1CY30DtaOZY61a0T7nY7ssj83BYW3ZO/NMaIBTplg0JkLPb3X0ZhLkeaokNJaVx5ovab89KtreBvOW1wWKLpxTDmvVP1vnozaznwKeOgtXURbTM+cQlLN1ARiaArhqtSkIW2t8txcmWXlqnVeTggV2/Qzp5XcB3KWQdgL6kVM6AgYcMI4MByAIaQ5PUqgi84x24tDj2ipC9prIAbzK15YpFwUks0rJ1vpUm7iW/K86lk1qglywIeVn0WPIpOPypJ2LI6teWieGsU/pF2agYSkA2G3KYWYbBeT703DL01mNQxyK/rqdiBLYVzlfYizcfpowsk7eRvOSSS0B1CCqFIw6uHdZ8WkO9upze5zRGgS+2jffhplQQDleInS42G2fM7+wbW+DeVIiZPVC+jgvYfUlD/Ndree1hx4C6N6ty6hyaHtsuE09XgKXKprPttYiViCcOI5t6sT0CqS+wxHnMERGn77cGQrdErJ8BQj2GtqJLNM35mRmVcN+VnJxa78yF1+AtnJ8tvSLPfcUzZNT87qaivBdDmfX1AwYqZIIZo7drMrYBVlFaDm12Yah1UqZPA5zYOsheYZcSqDG5Zg573jmoMPugUEuAC4WeoxjLZ9M+6O51/Z4a1Gm+tnMPGeZcqqDjDTKOTvnicX/YQCbNJmYvhM2Gd1Fav48cObnuv+jue1pMM+Jn2whZCAvPzOIt5aM/m2WtTkdbpQK945IFC5ASlmKVBh3zHmw2agjpqiFki0x5dpoVRBKAThk0Cj7FkkhUh+02PQYCXMX0XnCzsCg1MsxSj3QzsmOIwMHZnIdTGlloaBsgWmttJoD8VAiKFVumPpcgmnmxdKcWoW0fHzrCG2aRpfKBNxlHXtV6ShvbKxye1wyBbK7A+DQwe2chNs+Dg6zPGG4nR3Q1nGR8s1TBHC3KZNVf0rSO+jYWFpCn6X0rFmLO+clT9uVzJ2hHguz2mqVKHmS0iIVicbisCg5W8aYQVtXnpJ2QPKsT40XjStZVeo5Zgvst0dX29NgDqAGC8MLZi5YuWaNwmzVJmlflScCQEiZFJkZI4R7DhpFaYGplbTp/362FvEpy+3S50opMsasVMlWG2rPva0mdKKPmWKZOaCPjK1+xDw4HOgcOu8wD4TOy/pAr80REFNQVHCh5Pkgt05xkxb8Nb4I7b5SFXEsMjg7SRheew3ADc2TNelUnHSZaiGXnaMypiWh1trxzP6aQyanZ1jtIDx0r6yWeldyk8cB4/EH4a+4KjkkEzCayj/2+ZBzRuRljC8rAR1DAOV6DKVVUW86ruMqc+HZYtbVnS1mohSOfqerC7vKiUMC9Xm6V2O6HqPQGfukglpMrv4uRtunWS5s29tgHrnizat8EwZcq0RX2tbokVSCDWIFM0qJqvz4WOtq6Ese9WytpYhAXaY3/LRtGoxiNcfKv+rSnYx157koFbaHKCQOETrvQMTYTCvqzhMes/DouMfoOvSREdL1KF0TGRgg8sXskNMxVFA9U7MAaj+bAu7dQMNa9A2Xn3lotdJdOpZVc7DJd54ANK+UXADPD4pvoT+NONsAvvCXGB+6H/6KrwCGFahbwB16TK0U6ocMtjLooVLGkA9Z3lol0iJXIjTba0/3UsvMaYHsarI3K59K1UM+USciL7Q0UTEcSr73LHFUTb/2O47FX6DU05eg7ZeNu7DtrKbnN73pTfi6r/s6HD58GIcPH8aNN96I//Af/kP+nplx22234aqrrsLGxgae+cxn4pOf/GR1jOVyiZe85CW4/PLLceDAAXz3d383PvvZzz7C3pNYsz7UYJIaxXEyp3ZFyRirkyAac0p/28em6MPnSWkSiopGj1tJ+IrDsOXn24yK+ftxSMqLaI4Tc+a+kSQI6ODMYXPmsBEcjswdDnYOj5l7HOocLpkLkOchQrHMhYbhrPcdufgZ8vI7SHk0ni3kJ8yzRlknxJzGNVmWa1SBWtEtmFMz5hxlW1Wi+K5EONp76QNstCppwIsPKYKz+EfyuGmytDgILRRH0OIAKHQSQDPrQAceU9VTLdauQ6tCyUFMdvWkSp6GJsl+mnSNmuQrT/ChM8cYiyJIJ/OQcqo4iYloC1frpFuNqaUT7Q+wbshoyoX99qhqZwXmj3/84/Ev/+W/xEc/+lF89KMfxd/7e38Pz33uczNg//Iv/zJe+9rX4g1veAP+7M/+DEePHsV3fMd34OTJk/kYt9xyC9773vfiXe96Fz7ykY/g1KlTeM5znoNxfGQVTyyXmWWHEzx5Bnb70toUqemFspGSYwqP75P0L3OlDVBlcAHq46d+tauAqpiz0RjX/R3KS54s4JRhIHP6lAD54MzhsZseR+Zi1Y0uFdSAbNtSNnptQJmwNIBmLa9KAlIF99htJL1+U4VIr6+57rV7osoQBSrzeQXUtjLQODG2hnqYzIWiDj8A8cTnQc7DbRwAugXo0KWI3YFCudh7ZPhsDouaYlKL3PQj3yft+7BTCkHbgtDVyqVZrSU/RB66oa+kmnFxpApaAlAiWoGyMtHMoJaSMsZLnB+o/R8XuSnNcq4/+226EfNUGfaH3y699FL8yq/8Cn7kR34EV111FW655Rb883/+zwGIFX7llVfil37pl/BjP/ZjOH78OK644gr85m/+Jp7//OcDAP7v//2/uPrqq/G+970Pz3rWsx7WOU+cOIEjR47g/ns/jcOHREdrNbaTDjPDMbLzyZkZs8dfKwjFsABxxAjJ3bGKsuLwjhA4vbT9FtzyZLHUMhfa1efxXyQjnXL7U4oTs3qwlXlotQOeLdBzUbNo5KcjCXSKkBVG7jeJ8xRAtsorx25Dc2RFT+yLfNKA2FQKXfVLrI35hH+iDW6pgAdIlnbMqx8almYSaEDXcNQ82xA5YpiL1b4Saao/+ZfAchtYJAAHigxRu6r67ATYxBGxK89WBeCrnfLccFGsqIqKZwsJ0QcQD16RpYDVdlV1qLGoTHTVo+NKLqU33so8e9V0MklRzQBkvKhJv5xyytBqG3HzktyXEydO4OjRozh+/DgOHz6MC9H0ff13f/YpbB48dE7H2jp1Ev/wG590Qfu7V9sj9oKM44h3vetdOH36NG688UZ8+tOfxrFjx3DTTTflbebzOb71W78Vf/zHfwwAuOeee7BaraptrrrqKlx33XV5m6m2XC5x4sSJ6kd6b/TTgFRUqYo0GJBowX00lIgucWNZvnrjNCRTwzO/dInDrarLmxdQJ5WqP/l8Jo95sm7zT5U/IxbaRSVvafIYmbERCI8JYrUfX8YsU5w5wsyJ9T1GzlGtel2avqCqf6qcbwu+TXFpIE0ubQpdYxlmWkZphZY3t/9PSPLkc1fAVSkLHZO2ZSt5rCr5VJN7N8/pX22eEyaqw9yNZU7DsgLa3M+UUkEBW849JBUQw20fl/FQqmpxONNXa2Bsc9uEOXh+UJyUlv4b+sopqqsivXYt6iF57FcFyG0ul6HPk+J+e3S2swbzP//zP8fBgwcxn89x8803473vfS++5mu+BseOHQMAXHnlldX2V155Zf7u2LFj6LoOl1xyya7bTLXbb78dR44cyT9XX311+bIFAku76HJeExjZYrrWyhyHdQqGo/DKhmMW/tOE87dcuOVvzXloXOWJRsG64srbZrlbrQOq5/Ud+uS3Pr2SfiyC8ObBSZKwEHu4nROi6234lcjAkLhy/cnAZKxkvd61LICZ964/r1ZDlq9VcNfcIIZSsTRSdfktTeCDBM64JFncLfQ+/R5mm9kCBznwqgcxY9y8NIWzj2lVNqv7zkYH3j4vRm3CGg1KpjwdxGKn5Yk1PltrzIoDNGU+VD9AbJ4ny8Eb+s+u8jSwSdVZnGivDOqWI9cJuZoIHrENd06NzgPFQvs0y67trKfpr/qqr8LHP/5xfOELX8B73vMe/PAP/zA+9KEP5e/bwWbmL3oDvtg2r3jFK3Drrbfm/0+cOFEAvQXEZsleycLskl6bWpgsxRlErRBLZkUIAAYYoPcBUGEBl/Bom7YVYw9uz6f/NxwvUw2GBCf7suH+jZPXkYMjwoYTVPYEbARXKBSW6Nf5/GDO7RFSvpYcWIUE2DmKk1OOlHKetYAmBWBtavlFkxxsgt5ao1+AdYlos1+up5n+XuO0WwtTPw9d8Q8o0G4cAoalWOazRUmNq6urROlYIM8TT0q/MHltvg4kcqttoVUU9BeHQMtTmK22RfM+W4DIYaQAj6FEFaeJneByvpZW9lopWczn7ABCqv1JKKlzxxWY9Rqk33F+YHoVdJHavprlwrazvrNd1+Fv/s2/iRtuuAG33347vv7rvx7/6l/9Kxw9ehQA1izs+++/P1vrR48eRd/3eOihh3bdZqrN5/OsoNEfAJknqKxc61DTNvYl5/XYrytcgALowzI73ERXTugcSvrcJE/LvK6eUw+TrLUM7EalsCvtwzEv99lq1KcABKKDD4RsJRKAzgk4L0fGFs1xYn5ZBkSG5GvRFo1lPuWUJWBdQ2/ANAfIWCu9LRpdURZU1DDG2qzop2Yc9dqy5ry1xNvz6AQ0DqLcMfPHeOAycSJmDnpRnytVH+KNI4gbR6bjE8w51vqcre0OtDwNnm0izg+l6NUV3M7JVFRZniHJ0GmiXdPYV8ogo8Hn0IG7jTKGQKFdDDdO46rOvZ5PYPr6JaRZHIoT/xH/PILzvvGNb8S1116LxWKB66+/Hh/+8IfPuP2HPvQhXH/99VgsFnjiE5+IN7/5zdX3v/7rv45nPOMZuOSSS3DJJZfg27/92/Gnf/qn1Ta33XYbKK0k9Ecx8kK1c56mmRnL5RLXXnstjh49irvuuit/1/c9PvShD+HpT386AOD666/HbDartrnvvvvwiU98Im9zdiefcLAZi7yy5ia4W9WlrzlMlU5JbWRjHZLoeWlYoeLb23Np/hCgWOsNDZEnIdsv/d+FImFrJwENEtFAGSA7LSOEGtpaMU6tIgaWHC4Rcq/UD5Cb72SCCt0aP54drw2Y2/S3WUo4UZ5t0gpsr6X9acfhTJZ41Seq7v/ISOqbA/l7dl7UJv1WXlFJJGvKW9Jvwy1PVxNZBbTtc2T6THHAeOixGC69RkB3toDrt+XcKdmV1mOdOeSVTy5vqM5LfSYM5ZKfRX2uDKhXjZt7oOOR+psLZv81au9+97txyy234JWvfCU+9rGP4RnPeAae/exn4957753c/tOf/jS+8zu/E894xjPwsY99DD/7sz+Ln/zJn8R73vOevM0f/uEf4gd/8AfxB3/wB7j77rtxzTXX4KabbsLnPve56lhf+7Vfi/vuuy///Pmf//kFvdazmqZ/9md/Fs9+9rNx9dVX4+TJk3jXu96FP/zDP8T73/9+EBFuueUWvPrVr8aTnvQkPOlJT8KrX/1qbG5u4od+6IcAAEeOHMELX/hC/PRP/zQuu+wyXHrppXjZy16GpzzlKfj2b//2R3wR8qL56eU8sA74JtiFYglPtw5K5UJd0nY7BWYgvaym5BaZgBU9h57ad9mqr4KCALQ5Nqr+muWxJg9rAUyu3aEfhaaaOZmd+zQMp/ooiftcsrYdwTFjJXm5MEJWHjNbCq8FYHI5nW6mG6zTt9m2SqkwQaPklK52n2abKe69sip3mSQYtqgzg50Duk3Qzsk8jiAHnnVgVaqstouUME1Ubogmte68HJ8jQFKCLT9pmXrragf8aifnot85+Dh0lCz9fksSf5kJk/SZVH8KXC76na11LUQyLAsFpJfe+l/MpFatJpqsjBebsDifZeOyCCK1+XyO+Xy+tv1rX/tavPCFL8SLXvQiAMAdd9yB3//938eb3vQm3H777Wvbv/nNb8Y111yDO+64AwDw5Cc/GR/96Efxmte8Bt///d8PAPg3/+bfVPv8+q//Ov7dv/t3+I//8T/in/yTf5I/DyFccGvctrMC87/8y7/EC17wAtx33304cuQIvu7rvg7vf//78R3f8R0AgJ/5mZ/B9vY2XvziF+Ohhx7CU5/6VHzgAx/AoUNFjvSrv/qrCCHgec97Hra3t/Ft3/ZteOtb3wrv26z7D6NZ6xbYnQ9Mlk9V+MAGmcQIeEOl5EjOAT7UQzQy4OcHwcOyst7z+a3eHKikay2fL9+bMm3ZqjdA3h5/4hqJCP0Y0Sf2aHtI5yaxyjsQIjM6CIA7IsT0TjlmjEwI5rgjr9dAAFCnM9DrUAtzbWOz+tCPrC69tRztCme3+2hVJZYaSlSE9lEplpGBQKKvdmOfsztyd0DAc1jWMkj1E9hVgPapBct2Qmucsjb5VecA2jlVZypUa7mia0yumUT1UNKkZ2c+kPlx5dGzMRPLcdvVA8URkep6sBc7cOh8hvNXIggAP//zP4/bbrut+qzve9xzzz14+ctfXn1+00037aqeu/vuuyu1HQA861nPwp133onVaoXZbN342trawmq1wqWXXlp9/qlPfQpXXXUV5vM5nvrUp+LVr341nvjEJz6s63wk7azA/M477zzj90SE2267bW1QbVssFnj961+P17/+9Wdz6t3bhHW4Vi0nSma8Et6fLGQNobYv2TgAbsih9Cs1vAhV4istDjCV7a4kAJuoCWnBSiMoq89c6VMLIOl67TE1Z8tgNh1joVK2x4jtAdicyT5TDqTIWrbZlTe86bdee86NboN7bD8ncF0BcZJWAnLAzFRRiWoynKJaFKyMHt4D0EIStNoR0PMdWGmL5clCOahiiGOu6sNdqPpsJ9tJKziNBzhKfnRyiBtHQBHgWRBqZ7UNxBHcbeTVTc4rntL9svN11LFJnEVppcFhXitetA8NUOsYaklA0d5f/LS3F6p95jOfqXTmU1b5Aw88gHEcz6iwa9uxY8cmtx+GAQ888AAe97jHre3z8pe/HF/xFV9RsQtPfepT8fa3vx1/62/9LfzlX/4lfvEXfxFPf/rT8clPfhKXXXbZWV3rw217WnRa0SrNspM1klOtrWFn3YI0lqAUn+jrZek4YKYre5QQ+BEO5GdANIDbLGu/aH7vbJUaG1gtciv7s9arvUaIxFBBlkgs8mFk7IyMzhNmrgQRbYTE/abtvdHPO0IJIMp9SROddjv9zlWLNN+Ig8we7TjYNrEiyf9Xq5R6km0LRlcceqIfCscsv7kL2X/QOeGptdQenBdaJaUCyEE8OvnaIBuOBfwsbUYmvbG12pO1HjeOCJWS+07g+UFgtoG4OLxGbeQ+pACplgvPz/jYp8pKpki1VRD5AKBRCGkK3y8Tbbl3JXX7uRwDQC2E+CLtbBV2U9tPfQ5I1Ps73/lO/OEf/iEWi5KJ8tnPfnb++ylPeQpuvPFGfOVXfiXe9ra3Vcq889m+PO7yI24Nz9vQLcWz74olphF+hmbZjSYQdUCJBo0sGQpnjuTlGdwkiK1Z6y2HabbPE48W1dDd7HF3AfIxIXlwlIF8e2B8YWeFkYEnHJljHhw8AYvgsDNExBQVSilaVIFPm6d1cNdrryw/HbecEmEXOqUZmzwGNheJzTTYbFellFXVhr5cxtLP+cfJYUw+hGxdq0WuQTMTE69YyOljXQ2MvXDhpuB15uaN1rvKXc8pl/lqJ0VdJkANHVy/VVaB5KpVR+bOGwpOjjcHYkqL2zh618rdWb+Ffu/cpHFxsTlzUaScK83y8Le9/PLL4b0/o8KubUePHp3cPoSwZlG/5jWvwatf/Wp88IMfxNd93dedsS8HDhzAU57yFHzqU596+Bdwlu0c58kvkzZh8bUvYN6OTZIiAOr0AsdSjcW+UP0WAKFb+sg5WdVaPpB2CVtxobVVmVUJtshuLJNKxbG3S+gksyQIZRKc1i0FdnIEqMPMUQbpI3Ofgp9E5+tQvxRTLwjpOHLMuV0INQCwOu5sClfoBFVUIFVaA45r3PfaxAck1UaJjtTj6jH0nEJhbAm1ERZYReSJKh/HToTq7AZSLpUUMDUUqWlOzeu7EiG6tvKjtT5p//Pzk7I+SjDRabjth+BOP2giNrt6e3P8ipLS58LP1n1EKgtt873o+eOQUiL0azTMxebML3brug7XX399pZ4DgLvuumtX9dyNN964tv0HPvAB3HDDDRVf/iu/8iv4f/6f/wfvf//7ccMNN3zRviyXS/zFX/zFJE1zvtoet8xRWyXNsne3KMv1KukQMKVYwsjNcV3Sb2sbGVlmls89ZX2bvzUXSAUC1rpqIirRALpa47NkDYdkUarF1XnCGFNgUOczQB/sXE7OtRpipSZQ69vWCFUrPIOhGU89Zv4q1+lsNNN6zZZAn+DDKydi4zie4tbBsaI4lA+Pi0NgH4rqBhrBWq8wcrESF8AmOVrJde/Wz62Tja3AlFdPJmpY/R+aTsDHLCGl6Era2TQB5sjRxgeSV5O2Jqm5B+xKABFzLBRX+wzF+pn8cihG4c6DmuVsLftbb70VL3jBC3DDDTfgxhtvxFve8hbce++9uPnmmwFIQOLnPvc5vP3tbwcA3HzzzXjDG96AW2+9FT/6oz+Ku+++G3feeSfe+c535mP+8i//Mn7u534O73jHO/A3/sbfyJb8wYMHcfDgQQDAy172MnzXd30XrrnmGtx///34xV/8RZw4cQI//MM/fE7Xf6a298HcNstftp9rLmoFbYhllpfYbUsviORLGUDk4aBWH6V9PSi66oWuQKkBdQtua6uG3Vo69khBolCV14ck/Brnh7EcpYDzZZsBp3q5PgcB8k1egkcHuA7eEYQdkBfCG3C25bhcC+TAuvWYde7NBEUTgMjRXO+spIRt1S06hgruLd9rQF+BnLuNquLRGBkhzzou55wXB6IXTnu1AwoLYLVV+XwBY5XnsU/9tsWT04TCbRpkPUZSorjlqQKiTopJu52TwC51OuX8PgUYlfQNdoJTRRZpbduwKPJFGIe7TwaLnRC+xO1LUZzi+c9/Ph588EG86lWvwn333YfrrrsO73vf+/CEJzwBgMS5WM35tddei/e973146Utfil/7tV/DVVddhde97nVZlghIEFLf9/iH//AfVueyiprPfvaz+MEf/EE88MADuOKKK/C0pz0Nf/Inf5LPeyHaOWdN/FI0zcL2V5/+/+DwwVR9vAWR1hJMpd6qbU2hAcuh591mmznD4uAXlSXrhh1Qv72uLbcgZtUqtrV8pw2Lt8mRgFy7Mc4PSOY8a7mlMPEtvwGfdOaRgePLEUNMYO5Ep6K50HPCLUcVmNsw/2qV01BU+jdNgNgazWL2zfpvja7M/opUM1UBXisXtVLFCd9EtrLNPRoSmHsuCdGIk8oEQFwcSvRMSjwV62IcOVBKre2pZGGWm65AHvk+ysphO4Nxri6kq5bZvA7K0pXCWGgrilIurvILUApa60/JZ6qH11TDyo+neyQpDOYS4Yr1djGzJn74L/5/OHjo3M5x6uQJPOPJT9jPmjjRHl2WOTANqk2rFAQwVqf+ztXiJbiIxwHeDRip2T4f0ICOXZ5zRFar2FXD1PlUImfAK6c9jQOcBTdXsuPRuMImZBlNQw8HoPMlP8mSfVKgMEaGKvYQ7HXoeJjryUWrG19AnhC1Ar3xP1iet5L0Td0XDaHX/dO1ViXT9HeTiGsqKhVIzltP1f2RiFdxVLr+NByAuHGkrHCMP0IjdVnPARS9eDOpURwl94ny1bYptZH07HDCtdq0u2zucx7XsZ7A1rbRFLj2+eNUiIMjOABAAMHEUuhm2G+P9vaoAvMqR7W1LoGi622BwTYNHkEDtvp3UnlkiyhE0MpYrFP0TtuXONQWueaBmdiW5wfF4Tn0NcfOSZM8DIjdhkSZKg+72sEhGjB0B8EQueLOwLlm6EZw6DyVIhQKTtVAGmll4nRVaZH9DUCyRhtqyV6+tdB5zGPCswXYBawi4CggxF5WGbONqoK8jQtY05qTq6mqcQBhx4CwjIfzHVYRmOsYx1RlZ7YQy9lMCrzLdQDe9IWTJHDMkcJVhC4gE6CmWvCSB0brb1bqFTvkvpP/xwHKxVMcoNp4vXaxzlNAUYpc1ehlWm0L7RKpTHg8Zuv9S932a4Be2La3wdyCJEcQT4Bns1RnoKZbONaVbBL1QoO8ULk25tBLkKDhMDkBAnFEzpB4Jm4yW+JD0XGHrliETW50dgG9W2CW9Kuu3xJqgCNcv5PD1HNGvliKIHgWf0BwBE8C5GNkxKSxjZzoYAOaU9YuONZFrJGAyNIszapjikNX1Y6msN0ZGZ2jOsOhbm+48dwHHR+lP9rkV0ACdJRgrQSYs8ayVhVLtUKauncTnylNlPn+xFUDyD6Y3IZegs8Sbz5QwBhT6gWqk4EBDi4sQNSnVYMJgtF7RA6AL5O9TuKAAe8I+HkORPpyakRlZXgux9hv021vg7lNMZt48cmycRM0SFX1BSicbjAyulFAV5b+nP9XC5/SUj2nwJ2w0Fv9dbYsXX3+yjJPVIqqM1Tf3s024WcLoV+Wp6Rv/ZZYgibgSCveLIP4E47MPbaGKLnMI4O5BF9ktUc7+bWrEvN/RTOZba3muloh2Qki/b2BFWhVKBvNgULqD033tkrJG02K3qlGjYVststFH4Dk9N7JKySlVvKEYZ6VKoFXssIVJFVyme/d0ANdoUH0fG55Wjhz01XN7Kj3t3I6K3Xj08omTYA2apV9WPPZlHzxrmTMnM3PbGDst0dN29tgDtRgbn/bv+3DPJXl0KEGYn1pDHesJcsoTRg5ajDMi3Wk55wCO3KSQClbkS1fHTPAq+49mGMsDBfMocN45HG5Ak3sNkxhgpSKlXrMHWMZCctRnIJjQo2c0kT72gL4bmPagrwFN7WaeVxPeNaMNwG5Sg8xSy4Ctbidr9IhrJ2vBSalq+w29rv02cgAKIiDlCGFnUl8DmzvW8VZ0/rxrOSvzaGTJvlMRY0DuBMnei4zlwY/549JljqZY4j+3GZuTP0JDV3Sbcgkocm37DUjTSZpovpyaPIGnCPNctFDnfZO29NgviaXU6edXXK2v32pxQgYy3QKJGy5MrXIx6GEWunKwHclX7oFrnb5zqkAhtmGyQClZsZLqhZrtdtHOF+3D4ihE9VCAnW4AJcCY6jfwrzbRM8OMwesiLKapY+MzrkiSWxBU3/rEr8Za1Xd0DhU2zO1yc+MGiRZjJEBn0qjsaU89DguFIBFAbM1GiiXfqsBl5RHJpdpNU8OfaLh+sjYAArApv3yeVoVkj1v1qIXILdFPNgFuK2HZKWRpKrqnPYm1UAbUp61/trnVJDb+jWqvug1ulB8Lzq56n1x7suGLwf2aZYL3fY0mK/V3+RGjWBBvbXGOZaMeRoopMfSFmPmI1jzc9tt0/ZMVGcT1GbpgYmlv/yrDj1T2JlNigFyYrVrM3SKDX6SwhYd3LADt/WQFEfQZT5JiTm1BjsvZAgDVQpWPV+moNI2OcxcAcuOk3PF55DGndNnVYKolAQrMhDGlFhLLfDE90txh1Pr96u9L+b+VFJOvf96PSa3ynaUq6lGXycLDdDZDfgsxaLnTFYvDb34y718L3LCOXi2wOg6+NhjpIDBe8RRUkGofNIREEEV1aJRtgz7bDQGCZuVkKWirNGAWFY2+zTLX4u2p8HcPty2YjxR4q+nXgKg/B3LPvl4QEqHWi9OsxohB7U01MQUFaFWXvPyAagTKjVgmY839RIqcI5JgeILR+v6rQyuNCwFzOOAQA4MJ6kIGFh4iRQdE/3iCXAulLzr2sd2rI1VWF2z0cnn3+RypKQCOZODjwOo3wY7D8dceGelEFwa+/ae2X5oUyu5oWM0Z4xWYUIcMHMd+pGxSrlpKkt7bAKYgCKtbO5BntR1jDQoKFnKtNrJKxMPAXs379B5kvNHzvlvNNJ2LZ2CPs/Ns1Ct0KaebyBnssxZN5uJ+UvZ3NS1PoJj7LfptrfB3PKcQNGH65JTQdRun35X2nIyumgK2doGUI6F+TqQNROFWpdr3LI5j7aqvBfHGjws6LcFBQxPnj8DiizNzdOyfgf+VI84l1zyB+cHsfIoQUNJTTGyRI+ugQfHdcvQXrdelo2YHPvJYCJKtUUjAz6tIigBOYcuXVMjGZ2yzi2XDcjE7ZCdl9XuZpKDCwgERGfCyfU+p/5THMBWAvowrVmbbZNnDtSflvMvDuVkWyMLN+4dgRLF0lZ8qkC6ncTSc0y6mtRxnwB0iQ2QcaKhL0FFD+tqLmzbp1kubNvbYA6YpXLimK1jccIaz6DRvvxtNroKeCMwLGuOliQSD6OJImyXtVOa9oZuIXK5DBgxFwdpnmQabXdKa5o5URfEOlSaoZeoQ6WabE4OXdazWqcpE1fmZq2+u50EW842HzTU+U+U6x+bceYI51zh2FVLPfSFMtLoRwPCOXZgimbhCETUNJSOf5eue+xz6P88afLl3rT334FyzpZ0vd4Ufk77kEOlPNJVRsX3pwpDOlGFAPjknAgEDExYRRm1lmLJ57MUor03QKKwYon2bJ87pd6+DPKx7LeL1/Y2mDfAK2H5sV5+m+3W6nVagFA5mHXo6Tb6k6xihLmAllZMN1aRas4rS9H0c4264AggVZFJEZA5TzVQ+Fig8PuhS3lmACJxsGVAX+3kl3hrJIwjY+4dEEWWGJnReZdVFICAyQCUakM6GcAATFarrNNBEa5KzMVArqrT1p3kkLTR1YpqApBNKD3HQSSPuwE6uUwp6SSXJ+9xAPWnxUpORUq421iTpsI6nVurvP2sHQOXcqavdnIqXi2WwUlKCqU9fJdTFzOXkNyc3Mw8I5W1rmPruzLZRADU9CWNgYbxx/DlA+j7apYL2/Y2mGuzlkl2EO5CsUztlxUAq7SMb7aJEYSJ3C5mG7WQcoTf1FK53beieFDyd6TtKI5g74wyIRRLPXTZyQildwBoSoCtgfH57QHBU8onQ5lSaRszIyJp4NMyXq1FBhCT29C58iplxygkbZQqMOy1KiUAA5ySMKwJsJqgrnSlxLMFaOyFAsF64WZAJogREu2ZE1Mlq5+GJfzJv0zKmRFxcQi0Wso4hnklL8zyTleq+4DH2r+hCzDtp0vRoaEDd5ty3/otcLeJgRMgzzYxRIZ3AeCUF0cPZ+iWNd255bxXO2A/TXXZZwko1Bx/GQE5AOA80Cz7WL572/tg3tAWYp0XnbgFjIquAIrz0BxD9eRrLUZAteAcK9DVlx+ayU7P3favBTD7k6iNbJVTmWBEQ1z3ncmBTLUcpXpoeRpMDqsot3aMUgcUYMyS+TxExsjymb4bUlVO/mv5VZf4dVs6TrfLyoszTV5pghngxAGYHZMToGTGivX61BrVMdfN1IHqO3Dqn+dUiCJRK9RvgcOipLuNQ0lBS07yq6T+5lB9Eudt/t/2K7WB5BpCWiWpbh4AeH4Q92+NCA44MFM6rVjgFrAregVljLNcVikT4zvRqGGMQ53qoKXAvszavgP0wrYv3zt/Nq3ldJ1bf7DJlajCZEnbPBk5MAhYU2XkY9rvFIAb0C5VbfrasTfRnyydBGrHm1r5fiZceopOXbvsBHi5qELal8YBR/yAxyzkeoYo2uqdQdQUkXnNwIko3LmtKqTgoqqLFtirCFJzP9oqOj1LpaOZvo0K5GZcbPUeJNVIpsZcPU5VhGkc4AmiHlntwO2cBK224XZOwm99HrRzKuV+9zkLoYJ6tRpwJimabdpHLuMsdVcZX4gdeHFY+jos4ZYnwQAes/CYeUJvyjhVeeLTuNn/dctsldsxtc9Pols4dDkbYltrlkP3ZeH03G8Xr+1py5x4HRDkiwnOk015sLQNxWF9W6BMBigvb3UurlO1atFosRATyFs1RdXp2slqHXwUAfauVrBoQEgTFFIdx0mCrZxP3c9AHLEIDl/YGbGKUgPUEWHh1fmWhgaAJ8lzvopAl6gAABnULQgpkLsGhLLypU0pm0LR+5UAebY4U17wPLZD4yzOqRQ0A2CRD1ZKICR6JMhESv1p+d8HcJhh3HhMGesUjamcM5GGxydtfHOfGHH9HqZng+KACI9+ZPzV9ogDsw0cCFGShUHGx6eKR97R2uRpJYmWZsnjDZzx2ZaVWZcnzjX67ssoWEibaujP9Rj7bbrtaTCfbMpbty+AgrD+D6Tlq+F504va0jE5PamCkFpozgOJFmllfHqeqXS51dJddejwa0CfX1zzf+ah9fjJ4Ukk2nL5bBtxcQiBgEs3Ak70kt/cO7GjF8Hh9CpC/W+RJRGXZyFeFFAEkNZBfcris5G0WTaX/u9TtFIu58aooy1Z86PLCkRlmjQ0dBm5vE11b1mDdzTFgjhZ4+IIlrOD6DBkJyQtTyewM0UwrMxPOfS04hF1jeHNhx5Iic824oAxSIm+uSdwOAjEAcuR0UfxT3hHSVu+nj/eJtrSGIDgJC998YK6tQmVgZRxUpzWWa6oEaFj7XT+cmn7WRMvbNv7YN6CdlJCrH2e83BrGHpfFQteUywANXeuwSLjAARXVCd5/xEY/v/s/XuwbVlVH45/xpxzrbX3Pi9u337cbm1oJIhg408esQV++UJKXkZCDIlowE78hepAqWCjhISQFI1RCFSJJLYaIVREkWBV/HZFqpQIVgVD8WpbUJpQxMQWaOzbj8vt89qP9Zjz98cYY8651t7n9r1977Xvac6oOnXO2Xvt9ZhrrzHH/IzP+IwkwRqd+jBiMoMhz86rF5FniS8ED1+tS3f2bPJRpxRLuqWdWLWG1pToYpEKPwDqXACWwt2tO1DQ5ChQgxkuhoAQApqAGDaqQ9eknmK9ueNfqhaV6/AIcTIJoOVIUsc3g5MoBKBr+uJk+TgCWKkVb0uhBnaAdSgMQIt5vHfa07WnbqiTKSTiNdlvz40zei5ksRfPf8NwQVbtS9SdR+sNiIJMggGNonIhoDtDXNlIj9ZUTMT77zn8jMJYGnlv+B0b0kqP7JvGHh13XaO2VfDKKlNHmDv9LNnUw4Aju8IsR9rB95spAKwxrdsP5QZWPWSrYB4y6GBgfc1RZj0F+RZ7ncG6JNQ6GFgDBGnfFsggVGtCj+MWc/sdsLtgB7lR2YhXK8ziA1CYxHLJ0BfG0IM4GSA6eY0Q1S3lUTsgziYb0zZAmBw8mUSYRfW+ZVyCLVMknI0/gamJS+ZbXhUBsYoz3qtyAkiTZqNFTMOmDkB/4s1MO08p9xza+UhvT73Pk4axoC4glGOUhh1wF1hDvjCEWRsyNcQ0Pl0+0GKFRPCzlqtyS0MATI/D30v+id7MMKmuKxQ/2lwes0fYCDj/oqELciaPTnt0OHOgl8iK/+c2iJB7ehbDRGaEUZadfRhgwzHC10q7ocM+CMsf/m1M71gWPmLgoZwAwWODWgRIdWf+IGcJR2oXTIuDwaxt4cHOFJCqT5HArSxhrRB2CQjO6NI/xKVsLIINgJWoXSPMYWRuVzxlAclxEZgxo85JK0UJQChWTGhyn+LkSgqBcRVlZJ8Ez448roRIlC0NaDGDmW3Drx2HL0Yws+04vsOOQokm6nsJRU4wt6vZOm7cV8sUPsHYmTiBEWlOIjl2m692QloNAcC8C5g1HrXh/IY1FKNzHbseA0a/88qxD56bmlyCZnD+jIvz/fyj2R49zlwfvrzbEJAiqszx9T6jDiNjKkQYYFXUDLADaOf9BKomnXT/ypYYRE9LsqpDGGbwGgUPmm33K1fJwJdr7NxcCaNViMWIW5WBH/bLxw5f3anReeDBeYexM5gUSk/k3Y0dMzNmrThWTXBml+tzKqL0Gh1CLD2TcfVBap5yvDhnkGj0nQuRDSGY/P4Nk3pdDUKZ4K68eKcYwQROSCJ4mHom26S8iCage/fMlMsa865MEFD+HVJ+ugFCYC0WYxz2Gg9LHF3rty0BORksFULvdWcIJYCFrGa8JZSyGupCkPZ/nNNwq6DBFd+fI/vmsUfHXT/IYQ6/3LnjzpemeSQutpRE1c8TUwbhRuJMR6yJYov4AyB2D8Lgh0JgaCafVCTp1tOLyR2GLVMBiOicaIWl0QYFZHqO0hIwb9mptD5g0QWQ4Nqt5wiwtBwRLjrGtDmxFlIkP/DSMcqWxOFSlAgs0xTB0WnjuXXd0piSYZ52lzntbByW+pQeVNovPVS5nV8ZGzjHDkzZPV+pYKn3u2v7pf6Z48/zLXFFp/x1SdZ2gSfITiNuAHXn4ySpCEuqAgXynuqWCJWjqGyZqKGsK6NJ6SU7U/BxiRgRXZCfI1tthzoyHzrcPOoNEIZJtgyNFMVBlD6ERnriUfr5HPP23HuTlAMePLRpb+RK51H6ANdcgoJUT0bfCj6Wl+t1hXKNZ15i9gLt3s/8ZnUoElUGV6I1JeaNx6xVbDzggb0aQIXHVBwHOpMcxX7jUVoS3Jx56ACHhEQEIxGkQSo5V5ZFbjEJKudpgZh8DcJPjxooDmkC6tpE8QwrHKnejyHUQZnolr4kqozUznm/pUsToWLzxsFXa31RsPxeqeZJ/p2QJhAgg1BMBGYRyQKJ+kMxgpPT2bAeNRhDzydFddxxxYIEQ+n7IaT/a8lZ6Ph3kpS2g+8+kQFMywqQuDTtqGjo4tqhduZ5RN7XAs94yKboizcNl6d59j/S05LTjpY5814X+XyiyPc5YHREMaaDHHx0VK7PolEsN0vkRSy/qxl6kHMOxqEjPse6Y6fAutmEwhrsLloUhmANMIJB3TEXfbM02Kl9VPZTZ8BsCY7oDRCjooh7IyVDc9aFRr55ns+S6Ki3omUuDjqAo9qV0NhB/58hH2IW+zCzbW6X5gY9MgUKW+rKM4Tf9L0sQRrkNW7iLLi9yiKPt1hOgBKE0sCxoNnA+egYWhmTDpyAbmXiZB4/5y1qH6SnKXeH6kKiisb9yX40SDEHFJgd2aPfDr8zX/FaQHpIU+Tslh1p3sAgc+T9Zr3oP9gCMfS4ycPVQTGOBUW6PUerqVx82L0ndrIPHtQ0cg5pQjD7p1Jiiww7KxH+CrZAU0zgfA3Xsqb5VjXCrPVoPWHseOl+etaiMMxsUV4zAFTUYaty2K071F3A2GmCLsSoUpOgENaLOpCYnETiPud4eidOujCUmoEAIMhqomuXx/ogZ53fh3zcgkcwZexYFJtHk4GdnkZwI/jxVro/ZPpt6zILBKg6oifTh41INNqDFxkBnpA6FRqTJGjUWIGOHUfXsak2EvYNMNTCOutpzKM8AeFABsjSy2TgRxurN74E7EgC9+La4XfmGpWvwmKhUU32njrhgQhU3JcmxFY4jhxzD/nftuRONZCm0CZti6H4lO/idnp+/Bm73AbNGF7CB8+QCgB0NSf1VGSLDPOpm2lkvpjFPqwtsW49WucYRjGEq9YKfMsGw0Gn512kLW5pAApOvNUdUEjwWnchVjMCievMv1MEHpCwXAuPDtyqzgRKVDyFnrzniUgrZwc4+cqk3vBe5bcl6+cJgCc932a9RIlhEt/F+x8n+WxCDjnVEeD2eyuOFaV6632EyTEEU0aOvUIkFgyz1F0mYQCGSzof+BDCcvEitKbFVfCcw3By6C7LYSjzJfdpAZKjaes4FpeiGRyxWS6mHW5njsFDP4QxNGFpkB5k3Va30f8lIo+WO44VicyeKQwgjptC4PZnRpbnurRfkVCNETnAGG92btQ0MQrsabcolKT7k+QbdQ0v/W3BlEkywu/maHzsTIyeC0uglrvf1I6LawrpQNR6duqVS46DSMQNBALQqDJf8htCTPpaiPysLeGsSU7cy0pFoa+DHPfw/+GqSu6ZF43yntaKQjjErB9VMwwGS7LFPG5MLyXqK2Yu5WSsaubo7MerJye5gnxCo8UUplyPDjiE0Os05AF4H+IKKcgqpqei2DGFtBBWjAF6srlqscjImOUA5BKyC5HAPEqAHmyX7p0/CwtEZ2auyG8VqorwSZ5MU4efVxoOJ4TBvnvl6kCKAKMTIZDNjtHVnPQzWAHLDC6ql5hNcgFo58yg8S1jwq5kGuLw2lWOlbRDfI115zDtmNWyvegi22LkCGPH0aME6Vi0PkIrdYeIsWt0aAbFRUCG2w7PXyceXQXljnxQkbtkB0Bo8R64qt+QWZtCAL2JIkbpi930+WHl7/B4ymax6bVVfVwpBATvYWbb6MZbIADTlnMMo2odJEVZPqQerIUhjIRXvy/loerIlR3kxblrZJ5PcUTU306vX8dl9Wge2TeBHWpnnivnxbZr8c0sgs2w8ejQ8yhulQn2Squi//z/4Dmitq4vEaDnkDkghVhilD7cV/6/RloiOBWKMbMpkGAFs9iNErHBFtFRUbNgNoctAVehMSX2mw6WWM1v2vgkttV6zNsM15Zkm5HEnAlSGW9SYctBjIIevqxRb96cYlXyN399VZXmcHJGgqaizrtOGNpHtJmlz+p5hIzlkfP/kU3Ovk1RL5n+ZwbnxH1NTZqwwBRPTfQSEPVZeLIUqITQEzoDIOwhXhFxWb8cJiQtk87zCs6Cf2sEHxPPuab9JWpHbJaLa+cFQb397W8HEeHmm2+Or4UQcMstt+Caa67BeDzG8573PHzxi1/sfW6xWOC1r30tLr/8cqytreGlL30p7r777odxBj51gM+WXxRCYpyoTrgq7vmuX/AzdKJCkYvO8SATvDw1iPA9pxSKSRI+Ejw2GJv2m0f8Wv0pXOn4flvzdTQzjjal0jSUa9IFfpSxNIRp0y56uuo6ASh3vPUBY2fYWcvhC0NYdB6nZi26EDBrAjxC5DYLG25lOfbSs5VdV6xItAOGDtCPkPPPDrfJX+9NikgTaaasCO95BQOGT3oiVCsmYm5Q4VbvG4j1ApEiOZiIOlMiVOtYdEF6qvKYmNk2RpZQhjSZOUMoLCc36y7EalxNFhOliFs55U2Gl+cKjFnXv2SrZA8uMaPz/Dmyg+1hO/Pbb78d73nPe/Bd3/Vdvdff+c534l3vehduvfVW3H777Thx4gRe8IIXYHd3N25z880347bbbsOHPvQhfOITn8De3h5e8pKXoOvOkVaVVxPmlkMo8gCqw+dEoxThDCJhnQB60M0Qi88Sn0uYrk+J1VhWLtopsXONHCs6BnVIQJK6zS1b2jN3uuaI3Jbx4Q224GIiItBiD2Z6OgpK6TmulwbjwqDpGGpxBtisDCrBR0pDOD52WC8MxgVhZI1ABEmoy4hzX1W0MmR99Ma1rSOu31utHPSz6j5q5CzjmycwzWJfuOUL2O2/gtm7H3b/FMxsG2a23Wsc0WMy6cSdr5QyWC6aH1yXXKe2ZAtgR81NsrlAqxltMQxiS1hRVbTE2wEMowDs1HOn7ATWIpk8cy2XHGIBOMp3JEqWmaTEkX1z2sNy5nt7e3jlK1+J9773vTh27Fh8PYSAd7/73Xjzm9+Ml73sZbj++uvx/ve/H9PpFB/84AcBANvb23jf+96HX/iFX8Dzn/98PO1pT8MHPvABfOELX8DHPvaxczx713sAhzSzJQxcz1Oi5JUMlmHEqHi6OvFcr9snTntMUKrT0Y/nk4A49V5Ebl2MqnvJvSGLI6RO8lrKPzxPyjrxUNew8w8eRTfH2JnoQNShbBQGpeDCzhK2KoNjI4u1wmDsCOulwchxEtUZEs76ctehVUvflT1QB3mK3vUN/88+uySboK+HwCsPzUs0U2D7Pvi/+j8Iew9mK4SmP/EPJuOYTB6OqUb6ej06McvkoFDHrA3SvSmNbe0DSyQEZrOMCyPRNY9jJfRPayQvQWksiwzSyk2LsnLnH1cDl6jsbW6GLszPka22h+XMf+InfgI/8AM/gOc///m91++66y6cPHkSL3zhC+NrVVXhuc99Lj75yU8CAO644w40TdPb5pprrsH1118ftxnaYrHAzs5O70dNoQvtcB8t4qHp/Tz6yx0/+S7S/IYFJSHDUPV17UyUTmIAAwicE5sG51WaeQJwGIWbdIx4TvE914MDcoensBKCBzWz6JSCLdGtX4HWjrjFmSzzR45/T1uO0q0B1gsT8ddNqlFRBwcfi4J6NT0BQqnrFwv1x40ho6ASvXqewyrP4d+D1VAPDtPr1klYVz++RSjGzCff34E/fR//LtfgRxs9iYV4KE0QDyd6Xb3l52MGlajGoDMlO5d6isqmyFvNEuvGTzumZipsslt3S+X7KrOgypX5veJIPGVu8si8ZytyP5ea3zsq57+4ds4J0A996EP4kz/5E9x+++1L7508eRIAcNVVV/Vev+qqq/CVr3wlblOWZS+i123080N7+9vfjre+9a3Lb3T1shMGEGzm8Ibt3oC+eNOQPSJL8IjDk0l87jyiHOLpwQOwjK9qUZEbAc00VWxm4lskEFDPF3YZ/3lFJJqSutn/+Xa5DIGwXmAc6nITFXWwxqEkoAU3jNBIu/H899gR9huPkRuhkzZz60V6gHoJUFnya6Ros0KtGPl6Dwptgq6AZd7/qnHUsQJ6CeUea4gMs3b8hO9Xu+A8gu9gNo4BvuP+qbryMY7vi+7fliwfLP/HpGoICFnz7Px7E4uDALhmGimKNrSYdjaqUhbORB0WH3gcWc+dqYYewKJVjD3EDkydlPIbGWhCprCIrHF2NkZWv0PdcgL0iNnyzWXnFJl/7Wtfw0/91E/hAx/4AEajgzt/D2dPlfk8k51pmze96U3Y3t6OP1/72teyg2VFQzZLUAnjIPb6NNmPfCaPwPLEZO7I9X0tQglDByrnkC7ExyU9rxayScCNGNccwkN5AcvKwfFYFZmuXEnIdYRyzA59736Mml105OJy3MGjCwF156N2thX4pO4EHiCSxGhgDrrBUgl/zwaYdxzzVWN0kA3HVV/W/zWnoE64rRFcBT/eimqR9sTjYK95PMzaJkgm0mCSjC1l9yeda3LkAKCCXYnlwse3hH6SUa6R2jpWzcYEKEmP0HmHvcZjv2HW0KILWLQhFgiFAMw7z86eWIqYiF+3cm8UM499V8n0mDkEHAq8/Ahmubh2TpH5HXfcgfvuuw/PeMYz4mtd1+GP/uiPcOutt+LLX/4yAI6+r7766rjNfffdF6P1EydOoK5rnD59uhed33fffXj2s5+98rhVVaGqqqXXU19OmyJwk0EgQwcy6AavTlSX4UtOU7cBUhSdOxwS6QAS2V1zgKPP4QPdVx4JKsc9eBYIg+p2p4Rpru2yFL3LPhGy5g7S5i5Ua/CjzchcUYGm9QL4xrzDvGX1xHXHdalrhcGsDajBtLzKZpLA6GO2S5FfxKBTToHPWcY5v6ZV2Hm8MSsgLCCNr96bdgFQA4SK+3t2Dbp1A7PYB46vJ00W40D13lIP2B7spswnMikaz3MbWd6iIwdrE5xkugVMO0eHKrbVm7XpvFsfUBpWQtyrfZRM0AKu0hI8cVeiWHQkUX4wXAuQj3svDwP09YUuYbsQjJQjX36wnVNk/n3f9334whe+gM9//vPx55nPfCZe+cpX4vOf/zy+7du+DSdOnMBHP/rR+Jm6rvHxj388OupnPOMZKIqit80999yDO++880BnfpD1ON15h/o8es4ixbjkzqLvXkSuNEft65knK2Vpvip6zCN55X3nhUk9zFyjfBUDyytDLUvb5pPLkM6YVBmL9H+MXGuEcpyi82oN3dpx7DU+SqcuUGC38dheMNfcGmCrsph2eXIzRIaGXvsSNA5EfNcQliesDJ4YNmIejt/SZ7PXKR/DfOxz+mXXwMx346Tox1toj30rurXLJGE5TdeRs4iG5yKTC3UNTD1lFg6ZRDENPjmTmFxtpXjNCMfcoBOBrM4D48KgNISNymKrspgUnFD2QKzOVSqiOnJNglqTCrQc8erIwffgOm16vQpSOXJ8bL/yK7+Cxz/+8RiNRnjGM56B//k//+cZt//4xz+OZzzjGRiNRvi2b/s2/Mf/+B+Xtvmd3/kdPOUpT0FVVXjKU56C22677byPe752Ts58Y2MD119/fe9nbW0Nx48fx/XXXx85529729tw22234c4778SP/diPYTKZ4BWveAUAYGtrC6961avwMz/zM/jDP/xDfO5zn8OP/uiP4qlPfepSQvWsLLIQBhF57tDzxKFEi1xdmb0ulic8h3/nyowAEqwDLCX2othTuYZQriecPKSHsU9VHMATxqVGGyvgmF6EK78phwBkf9TMpcqTC1pG7T4sEWatj9H6Xt2hCwF3bdc4PefmzwSmK65a1gZox6Kw7ER0Qhs46KFUbS9fEe/NMi0z7wilkFmES/TzOp4iURsZJ2Q4MarRdm+ySZNrr06hnXMdQr0fV2WdiGfpecYxIcOqicUInSkxCguUaFEZljwYS4XtpGCap6ooTgqDhRRqOU1Ii/M2kovgxs6J5QJkzjkmYp0EKashlksNM9eGzuf7cy7227/927j55pvx5je/GZ/73Ofwt/7W38L3f//346tf/erK7e+66y78nb/zd/C3/tbfwuc+9zn8q3/1r/C6170Ov/M7vxO3+dSnPoUf/uEfxo033og//dM/xY033oiXv/zl+MxnPvOwj3shjEKeWn8Y9rznPQ/f/d3fjXe/+90AGPt+61vfil/7tV/D6dOnccMNN+CXf/mXcf3118fPzOdz/PN//s/xwQ9+ELPZDN/3fd+HX/mVX8G11157Vsfc2dnB1tYW7v+/d2Jz61hW/Wj60qpAP+rKYQC/6vXQb9Kc85Bl2171KJD0uAHEzu5GNK/JsHMA+pF6yIpQxGkvOXSxeK75eWpCVqNTTRiKQ49j4Ko+NlyMBFYqcXreYSEcZ2sA0QfkJX8IKCxhvTBpgpBjdCIqlfcGtRL1x+ScONOeFLFEvL2IOJ9I84rcfDJQ68FjbXTu8XqH0EzgLkOh4HoCs3+qfy1AGie5v/H8dMxkDJtiAh+AkqQ1n+ZEbMmFScGjtSO4Tu61QlyuxF5n8OC8g7OEYxWnib8x6xh6EQ350lIsGCKkqBxAzGU4xeuNEwVLn74Dmhc6RyMA2zs7OHHiBLa3t7G5uXnO+zgb0+f15L33nvcxdnZ2cOKqq/C1r32tt6+DoNgbbrgBT3/60/Grv/qr8bUnP/nJ+MEf/EG8/e1vX9r+X/yLf4Hf/d3fxZe+9KX42mte8xr86Z/+KT71qU8BAH74h38YOzs7+P3f//24zYtf/GIcO3YM/+W//JeHddwLYef+DRjY//gf/yM6coAf7ltuuQX33HMP5vM5Pv7xj/ccOQCMRiP80i/9Ek6dOoXpdIoPf/jDZ+3IlyyPwMXC4HfcNCSWRZ4ES1RCWsJxYyL0AGw3RtI2QT5BHEQoqn5ELhBMLFiKiVXVjulHov2L8hGqiDRMgZl0lRErUtuam0C3C4TRJqZOxKaAGMXVwmABkiMHGGLZrKyUoQe0lDFkbAkbpMOQbH8gx3ywsulNqjnn+0xOaDAOsRrT9MeaTzzj9kuymppZL0IfYuE0+A7wBUnxTaZ7bgXi0HNpibeJHaos0xSDG0VZYhiDRbBYdAG1YCV7osWyVhisl6ZXIMTHIZTWgISiqCJcMSgxDm3IErHB96G/c7S/7shdv7/n+wMA1157Lba2tuLPKgdZ1zXuuOOOHg0aAF74whceSIP+1Kc+tbT9i170IvzxH/8xmqY54za6z4dz3Athl37W5Ew2SEZyVLxiu2GUZwxgZGmqUXXwIJ/gkaVj6N8hJUTz4yvzgcgza0V43hT33fa5ylEONsPRc6hIHlwXWpDP5GKDB4S5EQBQ55ODrzZAdgHqavhyjaGZegpjx9hrAWssCmGslOKFWZGPedCL1mN7wQ/LyHEidL0kwdwJlQU6OO44JCyL2M8SWWJOr3mgndMbzyHMYhyonbO0cObEg7FSmatytiatbPIIfpAjobYBoYlqPRQCQjnhytgcJvMtqEufDa7qU1c1AJDr6MjBwaP2BmW2kmq8MH7IoButo/FARR4zImxVFgR25ip0pjAKCT6uuu/aF1StpDQ5drkjz6CpYVckpYw+mm1VZD60Bx54AF3XraRKH0SDPnny5Mrt27bFAw88gKuvvvrAbXSfD+e4F8IOvzMXatYqRUIabNtzOFnBDmPT6vCzBr8a+SrnuMsmhczpRgekTkYPudjrOS0Cog46Qyu2f47eA+T7/PPgWVjLGMAXstQ2KQLUCcEWwqsumKpnHMx8BwgeHlyluFYQytlpFMZiPNpkfRBJeG4vWC3xiomV5sEhMSrA7IyJs7H6U52OWSHJGsc7x5Z9y6JlWcTeK4oaYr8SiSrLpEcJzZ1ZbhGfl7VGV4N8AYg+DcjwCiV4duqeJ9+Q5x26Fa3otKlG8ChlX5WrAMvwxqzVVnsGZbUe6ZuBDEobRAKXMWOVwdVh46Rz6LWJA5SmqJ2HDILAMiTXEb9TbY1Q9h/jS9aRr0pyP5x9ANjc3DxryOZcqdKrth++fjb7fDgU7fOxw+3MYXqUrJBBHT3WQQ6vDHHYVUnTGC0a9Botx8Nm3YgABFdJgpILN0JRCdyx4OU6ia5KdlwKIr5lTf88svN3BI7g1Zk5B9AoNRSmkOAAje6lkMpXawjVOupgYMQ579QdJpNjsDv3gNoFxuI8fTlGOSk5QWfY4SjX2Qmlbh8erUThqyRw4xjKhEa547UOgBTt6KZaQj/E0POJVCeqIR6e2wH/B0kkAkiKk1kkH4pRivBVokFXWNLPlScYhZgMTD2LvUCpayItcTwusb0IWC+AWRfi4tBqxC3jOCkMKhewV3tJiPLgdfESeNy1uxBPqrIvdQKDVUMoDq73eCj762a7RJjzPPdxtnb55ZfDWrsUDedU6aGdOHFi5fbOORw/fvyM2+g+H85xL4SdN2b+yJpPxT8rMObEVsiTZwO6YQ7VxI0yDFxw6BjJZ86/JyGQY+K2TEyXrk5OYggJ5I7LurgC0BJ13Ybyv5t5LyEacXmthK024CfHhFs9jeyKwhDWREc7arvIccxiH6PFdizhHzuKMIwNLexsGxt+iqKbRzGp/JHqcc9lTINcT5xsM454nhhdKp3PsfX8b4VPhtW7B+QzqGuQkqQdqJ2DFnsxYdnjmysrJNPy6X1P9DqVXQTEFZKvWMHSGWC79jGx2fgQOzxVUpHcei4Y4gmxPyPqSojZK+zoQ+AHtDCEQi9RoboLYJdsBH+BrCxLPOMZz+jRoAHgox/96IE06Gc961lL2//BH/wBnvnMZ6IoijNuo/t8OMe9EHb4I/MId2TOYtWmmvTMLUbf8n/wQMj44mAMNGHyqQ1Z3D6eCsMtmkQNZLgXaL2fosU8WWccl+VTQGCwPtHtyED60PHnJDonlXsV5+2rNU6+tfNUOBI89hqPjW4vjs3Mc2Xh2Bm0ASgAUDuHrzaSlgsAM5cCqmodrpnKlyMJjQXj+FhURZhAlfyUI83MiyyBrNK8mUMOdIboKh/vwWs96mXujB8iWqP5TmopF3zSPdfP670OXqA4yUEUmcRw8FyY5FuYhXyXJEcTjEMRAh6ctlgvLXwA1h3Sd8Y4UD3DLo2k8pYdfhcC4Jk9pBg6kBy9ES2SWEik55zp1Qzx8kvaLiDMcrb20z/907jxxhvxzGc+E8961rPwnve8B1/96lfxmte8BgBXl3/961/Hb/zGbwBg5sqtt96Kn/7pn8ZNN92ET33qU3jf+94XWSoA8FM/9VP4f/6f/wfveMc78Pf+3t/Df/tv/w0f+9jH8IlPfOKsj3sx7BB9E1ZYrvuhePMgsuvBK2QQzApnAcQinJ4NnT3QL/PPIrkAH6EF8m3EtKmZR2y1p+IomPCSOJhuq44gh4E0cesZc+9MCQTAaAMLYxFciXUDhGIz9ussAjA2AUFobmG0ia6cwMx3U6Qn0A3V+8yCUWgieE5MuhFC8GjsCPAhSuOqo1EqKIF52SDuVt/rMpRdZ8TLh0JaOj75OOUm1M/etivuZ2SpDJQqyQNoFgiuYP6/nAMFzzK9JMwXMmjJwXugMLqi8Om7YrjqmNoacIAzDldM+P4qdZAWe5gXG9iZdTBUxc5BlSXm8hNAYMcO9J14XkAELENZ+v05VKbLjfPdxznYD//wD+PUqVP42Z/9Wdxzzz24/vrr8Xu/93t43OMeB4ALFnPu9+Mf/3j83u/9Hl7/+tfjl3/5l3HNNdfgP/yH/4B/8A/+Qdzm2c9+Nj70oQ/hX//rf41/82/+DZ7whCfgt3/7t3HDDTec9XEvhp03z/yRsCHPPEIew2a2YUBFzKGOvLVajqVHuCRxd+OSvK2XnWv+ehBmiSQjAWQFQn7ZoQsjJtIMc1Gw3GFl5xebF/sW3jF+bmrurOPLcWTJ1MFg0XmsF0Yi9xRd5lE2zXejw/WjLcaD6yknUat11gNf7MGvHUcoRph2FJ1OIbK46sh7YlsAJyAVQ8+dskBW5LteJecS/DRw5j1cG+jfT/283HNqeCLy1RoocGu3YKQblC257ZxG3gI5KWdddV5COcGsCxjZ1NmHItSVdSsKHk25Dh+Y0TLvQmwXBzC8YilREytLmLWcBC0tSSVoGleVyu0VDIXB2K4QIns4tvPXyDO/7+6vXBCe+ZXf+riLer6H1Q7Z1L7C8oiraxNOO3Tkuu3AOTDzIYvuYlTsYw/IHuQCREcenVT+QIWuV4kYVwRDR5X9T+DWZ5oJI98hhIwiqTi0k8bFwp0mqrmcPM8ZiGO2psSGZbZD7L3pO9B8N7J34nnK+VG9H8vhKQRgsZeSbIEZIJNqHVPprqaFLb2oUW3gbPKIIUa4RKAhgyV35Nm1QyCQlcnQDL6KDp8IrNmjqoJ17M4UhInSS5bqdsZFTj6CR2FMhJG6ANhh4ZFlmqlT5961GNsSU6nwrCyhNJwcL0cjzLuEm1vlmcvllNbEJDSQJo94j5ByEza/7sNijwDM8s1kh+zbMLBBMjLaqiW7/q3LVO977Jfe/gBeQudRoH52UKUZyKSPtVkLM3VCxkX1vmGybonTLsdZmdDNFAi5/ByMoQ+vUTcn5oRbA1A7TRS/Yhyje7t7H0f45RqgE0VbA+WkzxKSSlIKQWh8CRpSJ52Lb1mNYHU1AqSJNe8gn1XSLtkZJr98rHqwA+R+dFkhlq7IVAVRt+9akBVaaU5HBYCuRk0lCmPYaQaeDK1qtEjPV27r14IW+xzpW4eaSgShoEwc8QRTT3l8Zew6gaickd6q2T2zhjJee7rGgIF2/Iqk76VuXPRzfs54qQHNkUU7fN+I3A6IuONr+jtjUVAzS3onwcc+lUsPx7BaMNu/loH3nLP3SXkPSNWkQOJP52Jbagq9WMdOVpNzw+uRyk5oJJ5fvzhH6jhJSm0N085hfc3VoEoD1EIlKYOHyMNS10ik3sRCI2qmWWKwXyE7bBsXo0UpR+8CBquV5MhDNiHG69f7t+pBX+XUV0XnyO6RTrjlGBAoSsWylJGi1EJORGfVn8QUxJI8V1+qNEEzF246U069FIZRu4gl/yCDEi075Kz8flFuYmFGqIMRuWHSRR+PH1JvT8rHYrhKQRpnHCCutcr+uimIR/bI2OGPzDOYZSV+mCcTI+Sh1IssilZdlVUWnfKKUvvcgeRQDcDOYciTzv7WCBtAovRB4ByFcbp2eWLK/1bH2PWdYd5JJ4p+5RNF1yIUFQKN0wqinvF7RRXxdU0e+mqNHZNnhoUJ3JA4L4IIyHjoWVQex07HY6ioSNnYrXLqw2vW11Y4u6iumE+qxiGMt4Sa2Eh1btZYWydUgWfIdzDzXbjRRir5l2ugRvqw1lOY+TaX8EMaLxuHYrGDwpUoZOVH7RzGjjBrvfQJpah/AyDq2/Su1cvELXr8cVKVTXwArxLO0i6ZWPYIZrmodvidef6jS/sMpyXLy+Je9AX08VaNGK2JsqfRSSpemzvp3AnIvoJxIOOisFYUw1rl/HPnFAZxE2VdbhQn12bIw+vOE6bW9RKlSmPMFQGprRFciRoOFZhvrjQ80irJ/HoWe1KQRDD1DH68xaX/6DsgTdL5gJS0y6PzpTE3UYxqaVXUGxvf3yZ3Bqucej7GAGixz/eEWDI4Vk92NSjIfR8wjMinfVIzT5TX4GHqGcz0dI+aqgVbI0lqFmS4aYZAVa1oqyjXnMXNQlT/Y+YL8zw14qbgUwJeIB4yDhaa4zmkduTML6o9Kpx5r78n0L/hKnlLnGhkh4/VuLTuUz9nzuAw8te8B6FlhzHYTiPA2PdzcEwKgWmNXStl+xIhynVEbrUxealgcojB96EZOVYghn2CsexYyLBOSz3DyO8iVGt8jYtdmCDsDwB+cowLbJp5rGjVKlMuWEdU9wOYqaHl/MxmMclp5r+z+xLI8CSbq0EOnfcBEEMct4Pw9sz5R1130YcPxQikdEyFfnJWyoAKSl2DYKr0um9StS2QBNOIGUNjN0Jw6zD7p2B270UoJmjHx2IClSc95pOrlILNuPq9782QxroKCtRLxiUUfZ/Jjpz5RbXD7cylupKCdPwJHgjJqUeIIncM6vDEiQJA7BSgpg9OppXSS7bKZhEeMIOHLAg325aAGXMEGCyow2pdERokbzVKFDgkXpc4QOoaBJ/JCcT9CFYcZXwZKyffRghFJxwzPQ0/OcZ88noftNhhp6TXqNF8VyMED3IjKfMXx039hBzpuWfnopRFvVc5PTP4FhSyFdMq3DxbccWX8ns5pHDG62dYBeDxJnXUxiGUYx4LEq57M0/slfwa9B5JziHAx+g+jDYxHx1DSRy9K6MldgJyVYSUXGixCJa55UJvzMdNsXJLiEyknpzt0uTPFcLepTL+Q+HIj+yi26F25tQsotMk5Rwr2yA6xKz8ehD5EZnY/Dm1Ohv0eATS5zJHvmReqH5ZpMda500ScloFDeSQSeaooiMHIkzBWtoJcgnGJnhFzxNIqwBbxkSf8q11n4FMZGEgeE6OznZBEpH6cg3wHXe3d0mRTqNyLUhSZ5TGoY10wFwfp8eTfojoKjr9s43kNMLPmoXEsWhrZuiY5Ogpy2Uo1z3Yst8wWo9tCsA3TB81AnvNd1COt9DCoPAtTNcg2Ba1HXNysxiBpJk2NXO4cp0VMIlhFoDjB5Kx1E5NvSQ7kHj0g7EI7uHrsTyiphPw+e7jyFba4XbmIbBz0i89EDFGtdgCLn/Is0QpQxHgpyv/oqgzCCmRl/N8o453Hj0Ll5k/mHXcQb/hRcT2FZv1XS/xmVes5rg4hUFXHCBFjlqZKlgrtZDkX5EqFYMITNX7oCBJza5FKNcR2gamWCD4dknX3Sx2EYxDVYzQooyOetgLVJtFLOUFgOWCqThGAn+pgx08rEtUtgza6v3OtHQI4DxJ1/QhuK4FIb8/mSxDLM/vr9CiDAAR681MjsFu3wMzPY15eQxUbaKYngKMxVq9A1+toSWHolqDthC0MnHUXgIHIlggqfGJoz6bAiCqpwjV+oGQy6Vsf91CW99sdqideYy8VVVQTKU/ImMBAELT+9wS3j7EJTXSizsVx0bJia1MxulbuWhT7FbUpe3aWrqqe4YchO6o8El0NPkk08pEkOmlAOq0k1AXjIm8Z06EpqjOLPYBN0Jo56B6xtsROzM/YmiC2nnqKxl8woaBnn45kKL0LmiJpJNqUPRXQ3mUieyhVMgFaRuVCU6yxNnYRq76wJn1Ij65dyoZoH1fm1lfCx0J3tJx61kO73jEYi24EtTOsT4B6gDYyTG+1q5lFszkGIIbsf4NeJLuYFB3XnDygLEzMdfQu77B6i/PP1BXx85JGGxzBLUc2aF25sEW7CS9B0F0NdQp5g/KAYmylUU7AD/84gRDvnQXiwnA6JCy5GQe3eXL9UDCcRbIpJxwGX3X9p26OD6CSZh+/qAPS9j1fdF1j+djMi0RV4Ia318tSMm6ml+/AtRMYfbu5+3KdWG51Og2j7FkADGPmpoabTGJY8EOilJnHAJGlnowS34vyKcJJmq05CsrvVYgFUblt2AYQeeWwxI6NtnEgWbK8FrOL2+b/ndBd72U25CVTzHhVdhiD2UxAnluIRcABOswEyhlLBx3bbU3dqmKMwCR2mlziA193n4gwywhPYVmDj+gJR4aR362sNlD7ePIVtqhduawNlH3svJ7fqDzqCusWPZTipopgy8GuB5ppHimZW1WcZhT2XIRKQqDBKsRp+ASPBPpiEBqB0ZmaUKhTAuGxyFjhkSYpY7XF+GGLPkaC5xk4mOhsRFCtcna676FkcKhMNsGgoet9xDKdfhy3GsXVxigyZ6xeKaZgFcwLjaMWLLhxJQ/9NnEGrfV5LSO9yBnoPckrV54m1COk9a83G/l0ROQeoEG308qr5r4jeNI33fwk2OsFinUz5Hl7ky7PmDiyqVIuzDc7UnL9iPEJt8ZM1DXzK+tl6w9bPYICG19M9nhduYAP2hSin7GpraCkaoPGjYb7kXBMZr2ANzqOtkVEULe2ky36b2WTyh55CiKhMr4iAlaj5igjdsCSVBMnT+ZTAfdg+CTA1fsvxM2hlZyAllTjQ6+GHFlY7UGMrbX4Sd22gGifjrQzx+UBtB+OT4I5zxL1saVTGS5rIiwsjHpNco+aDuFwWITEWX3LE++QcrplWqJetovDdfx1hzLEoYtXHztK2od67zYAjTfga3WEcoJzP4p+LXjKI3I14YWLbkkY+tbdOCmzCTCXENFxAibSFQeT9EsrxKP7MjUDrczz5fPS8lL29smNWYO/dcyi8nQ4UOjDnFw7H63d9ECGXw2dnPPoiwKDKnEqEujv2IMKBNFuq5HJ5hXA+r22XE6GAQ7grNZAtj3k33kO5i9++FHGyIhUMBXI8bRwVi5dkii/dNAWSGMj/FxnQhw+Tb+QFgVXQBcJgEMSIJ4mPDUcc7+545NGEygy5/p4de6ihpE670G0vlHFXrT+9jM5XUL6rLjkkmOVBOpOSQj163CY+jq+J1oYOAIaNauAABUpKsy4ZJ3NVpTwhqHtguxSXSsWM0m596xpehomHM4lHYEs1xUO9zOHMgc84CSpqXyGuWCe1JqRWO0Ib6q+5For9ctJz+mfibv+pNNKvlKoYdzSwJOWR9B4JToiFTx0bfQNmsEcDKPMrnYINRKidKNcZi1AR0RKluiMSUXqqj8rTEIXYtu48oIEZjZaeZkF2OuDi0moG6HnfpobelaWnJw1ixh9I7SOGg0yzi6SZNRrqMztPweoO/sV9lydycXi8N690gnQFtGWWJqphFaicjX8HOBYtTfY+EAoLbhFYMrGSbzLRdg6Vg006RuqXBYtQ4KPlITnaGYdwnZBD/U2mkD4+pWeoG6Zg5/iGGWI6Gti2uH35mrGdGqzrDHiINSVpiSW/4QkzSuUBv0Cw3InEzI5HUH+9IlOLo2Ods82syjMCA+wKTYtcqx5u+vWhkYx9clOK1i1l3gPpQhsF7IejFixYJ6yknXZh67H4ViAlrswSz2OeoWKQLlMXMlqGilb23BhUz3hEwsfjEk57/itihfOkagOpYGy3TQ/P1VMNaQlpnfv6WEqEmQio69RvDGprJ9Xanl9ybff/6aLRFcwu+pmXK7OVui7gKco1gv4N2I5X3luxhkfFyebAjZamZAaVVphA7s0CtLSVvnyI5shR3iNduyKQzRU56jQa9OaIQQUgcafWDN4CdjkcQIU3/y6tIg+tm2TNx3MtJ7MktuqhnpObnKeejvLGKL3O2B08mTcpYgQk6IOSJlmtRdiI48lBMuApLkZHDcks7sn4KZngYAeBGYivoytuRknyoHBq58jDhwNnmmBsRy7hD2Ro+quezAlxKfAzuXiCwYxrMjNCFNroMtMu4/evmDaF2d7mEGe/DAtP0ViL7vW77eds6FbF27NPHq9WtZf9Qp1x6xNkk5ACyTUHeBBbx0XB8CYhlKAjyUnev25235d/h8fo5spR1uZ77CcUMipYh7Z6/3WpX5rKlDxidXJ8sR10AfQ/7uOaPBlys6WJNw6lURfDx3oL+MF3ne3KHz630oKOUAeD+W2FGUlh164zkdOWuz1UU5YXlbqVSl4Bn3Ng403+NIXXqC+tFGT7+GfBu7FMVzkki+E454AEMuGnwGSXaqY9drjZCYya4lu7b4t3WpclNWLTpGcZzycV1VXRh8/C6Q72Lhlb5HIUD1zoeyDfHzeohOlAyrdcHOJwijDVDXoqIuKVFaTnB2MOiI/2688vHThBey/apzn4YCe41H41PT7DrqBJz5cT1XAOKvHbA4cuYX1Q43zCI3N7IUBomkoZiW/s/6JCFtOxTV0t+5A9XjAX3p3Hz/AAtIDVUOB5OBRrsalXGkJzK1RKCeRGxy+pEyFzwn7iRyDiiAroYlA8CgQgtblBzViVNoA1Du3cvRtTgzP9pg3XIAoa0ZpjIORlvJNTU7ezKgZgH74NcRRptJEkC41T5IazRZGXSStIt8fD9gpeTjLv8HA6ZvSiS91LJvgKv3cXOVcljh7HRCVB0fERSjdp5WC8PVURBmCwAYuT+2iOX5SiuN96yciHwC78/UM2AkE4hMeNaWWHiKYxTjKJkEVQ3REissLqQj0UZpMG19FOU61HYhnPGRMz/QDrUzD9nydaUTV+gEQDCMN2rBStCy+mbG3XdosJ/8S5Ml75aaWeR/S6LQhJBanIVueVt13qIHErvdxMmoj+PmCVMCEp6enV/PaRqHInhYN0InvSgJAnu0C3babsQNnaGXnSCbYAvep+uzhIIrWeJXNWHIoBO+NBH1qkIDOBpl/RbXLyAarGziiimdTH8iNehF3Stxc4WthqasocAStjnvfTjBBmMBV6V8iUJtxvE5KvTVyEQQCN6N0HigWiEhwdsuGN5xBoDAJobgdKKjrOIzeFSWcxGl5QYX05bvOVM/j+zIDrZD7cwB9EWZAHkwswIPibpJxJY0MgtErLshDi4+0KVb6dCXcN5BpKja4SwXWwsdDlwCnp+rHEdXBkEw19SDkhUWEYgj1Uz8iYYRropFBZ9K18nwRAUHM9+BDSHSHIMtgdEGaLYtvUSnCOU6L/OLEqGrozgXBc8Nnn0HX45l/Jj5ojrgtUev8EWj8pwbrRMJsCKyHC6dB//TkkPH8mpp2BREYZUerMO9RoOpYwVuj10T76UUDQ2wdP2uUD2NDBmV1TXtHBWQGEPE7JU2AM7X0gBElCvJxUpOnewAXtVUlmDIoO6CNK/gXEfnA8bF4UZD1Y60WS6uHWpnvvLGBqm2DB0i99vrkjxFyNRxP0zIQwlKNL+0n9xZr8a9c+ejLImoS67vawWjzbZXTDx3KsEDSAyKWN6vl6ZOIaM9xr8Vuonn28ZzMrW0TRO6nC/G7Jx8G6N0fZ+mDwKV0N9cyaXjvoWZb8OLo2wK1nCxYKrd2FFi02RYLyBl/pmeS5SjzcaRIZZsBhhOptExm2UGTKwElY/mE2auqAkwP1zvbT7mwcexo7bp32NdOZDhVZx0XOKxF4G0bMJTqYDOE3cDypLXxqTWegCPybz1KLSB82IPVbUOgB18aQlFYWIS9NCb91iZ1zjXfRzZSjvUzhxAv9pSnapGZ4p/hmzpewAOHgWMdFm+asmefTaKWnWK24vmtVAL47LdllHFLzYRzvaVV4iSRuqK/QaTHF3uBBVu0WhenblACJRBTeQ77rgj2irBWIRixEm8roaZbbMj8i2o9kBRAosp4FzsO6rHp64B5jtwArPkmtqWskQdEBk1HYJopGdhuYprabQNcIMOZPdkuBIKZ3AE2SSoE55+L8xiH8EVsXCIC586YL7DeQedVIG++mSPpio1AcU49nOlruHjFSOu8IQH+RlC4dCCIRUS6QJdPSqzR9kslgxKa7h4SDD9VgqwAIr00rEJsbr2yI7sIDv0zjzyl3NIRHFo4/oPqrFcHh88YFijW6PxjlxfQGsY9Q8mgsgzF0fODtZEBUOuFuTP6YOskVx0IOqERUGRI2xC77YQFzv1cOUMH6bBucYmxTrJiNJfcFXiKZPhCLM2QHc/7P4p/qyOl/NxImAn2qI99lgZ2w5eimC0u44KR1mVCQgBfoXviY5Mz0GGYinazq6l16BDnWzecUknUp/BK22dJvbILkrQSDAWqNaBxV6fnjq04WtBirl0nOQYVvj3wVhQs0DRtXDVOuCVicPfuU7L94NIL9hSktZAa0qgKrlIyBqMOq4LqD36E+FhtiNtlotqh96ZA0hRm8kenkHknaL0gJw+qM7OVuuJVZA7SO1VqYJPMdnZd+R8XEr/ixOMDtu6nrSrQgHBOJCVY2mhk15XDuegSw5EI/P8+jPHQ7mYlWGaIYDUBs44mP1TfD225EYUxoDahtkpa8e5kGi0wXh6s2DKonEIruKClsDSuMpccb7GDAVCYL67CUlBEUAsgjlwstRkce//wXZDxhEyeEZppEMHLOwi02yzroxsk/PeVbMGQFKr9EBwLk26A4EwhdSongKuRGNHKER2l9pFXLnEqNy3KEMNhD60ZqVlYGdHEaJqPFCKQFdJsup4NNiq+/5w9nFkK+1QO/Oe07aZIwf6iS115BjQFb32yZSHUqEWhWy6DM/W79BBX8jcieQTSMSFxWkL3NI7twz/jhirVHj2KIsKIwQfC6R62t+D40ctF4UGFvsw+6dYa7ur4Udb4mg6dOMtUCHiWq5CN9qAmZ5meAYyQXQ1qJ2jaBcIrsLCOXSBYQCAZW/VuXcgblQMgIjL17WjThwbdXQSnQeDqEW/xGZBumeMcXMJf0/NUCbPvJcqAKBkB5ogklq43UEmuCKW+8cEukgI5xNrVCyUc1ecPBjH1bFtLdBawasDva9aCaq/BWbS3A2MgSVg5gM6D2yUhA4OizagsiZTXV9tvYn9yL5p7Zym/FtuuYWbz2Y/J06ciO+HEHDLLbfgmmuuwXg8xvOe9zx88Ytf7O1jsVjgta99LS6//HKsra3hpS99Ke6+++6HdfLR4eoyPL6RwRhAL1LWlmpBClL85JjAMSsYKhqRZ8UrMRoH+lG4bp/97jlnWyYufMiqOtXZa7ToVf1QHvalKtUssZqzW1YkBWPlqW+5unPnPn59us2/NQnazqPKIjVzULtgDjlxu7lu40r4akMc5Uh6h45QGnbgnEMoe8wVAJGyqNBKDywI2jkpw8IHk+SBzAUyffx8yC/PVzAqCgbwdbaJXdSbCEI6h1gBOjxfmQSiBINKN8gxw2iTN7WOC7TEWRtpIdf7rmQFYQvD/VW11L/2Aa0P2F50XNG7ehTSqT3E+7k9koANZff8fH6ObLWd8/rtO7/zO3HPPffEny984QvxvXe+851417vehVtvvRW33347Tpw4gRe84AXY3U185ptvvhm33XYbPvShD+ETn/gE9vb28JKXvARd16063BktqLPVTvVdu7r0faA2qII/wY2w6AKmdszl3zn27EYJY/Y+apZHR65O9kxfrq6FqWcxucVVhoMIPvg+G0WvZThJaFJTufV6LZlUQK+y0vv+mJABNi5ncahqzF2FfAtfrkU4JZQThGodZr7LTSrAD6BZ7Eb6ZijHrP/iuUFx44HaJzxcy9UVUjHZ75U2TGpm173URu0hmAzR0epEKGMbpRP0EPlEr7IFQIzQg5MOVV02GQ9NuOdUz6IMQo8qKhOcVhp3SPIN+fdh4SboQsBcykIrR1i0AbM2wGbc/Qtlj2gEnz+X5/NzZCvtnGEW51wvGlcLIeDd73433vzmN+NlL3sZAOD9738/rrrqKnzwgx/Eq1/9amxvb+N973sffvM3fxPPf/7zAQAf+MAHcO211+JjH/sYXvSiF53byWRFQ3mPz97yWF7r/e1bhHKMaRtAxDNaG1jlzwfAGJOSdGRYe5uEWZLxuZciSW34oIdyJVeDdi1gW+GgSyu3LuHjeWWnvm/qGXw5XoJjAvnUyGAIKfVWBtn7bYomIZMY/65Y/c+WzGzZP4VQrjGdcbGPUI7hyzV25hKFUrOA61oYodCxdABgoXkLl7rN5+eY34czReT5NQwf3KXVl+ntI8Io6sRtSvgC4P+DVHN2Incrr5HAPKkptE/7UuecJ9S7hptdaFWoZ93ywrTwkhQGADvajNTMnjKi/F0ah72GI/HCEOZt+u4604dQjuCUIzuTnXNk/ud//ue45ppr8PjHPx4/8iM/gr/4i78AANx11104efIkXvjCF8Ztq6rCc5/7XHzyk58EANxxxx1omqa3zTXXXIPrr78+brPKFosFdnZ2ej/RFLpQI9PH0oEESchSGeCS67yIpfMB+43vM1pygSyFPDTy82eI2rJziTCN7jPjKFPb9AuBNHp3pSTY2hQ5DqJ0ZerETu1Sjh/3p30v20WsXgyukqIfBzPf5ve0dF/GMrgS7WWPQ7dxpTiqGfxoC37teP/SfBt1RkIIHHlmyoldQNRm6UVVw8Kn7L1hswgA6V7qWA7vbazw1XHN4CsZp2ALnphGG3z9Mo6BmOWT7nWIx2TcPSVhdQWkQmOA5CAW+1Hy1kEm4+CxkEg7atPoNemkkCV41wqD4xVhvdmBkQYqjRQLnY/zvuQ4MDks+bB/jqazg+ycIvMbbrgBv/Ebv4Fv//Zvx7333ouf+7mfw7Of/Wx88YtfxMmTJwEAV111Ve8zV111Fb7yla8AAE6ePImyLHHs2LGlbfTzq+ztb3873vrWty6/QYPT14cMKyKYfJldrqEp1+E9L2VLaWhcFWXimSNh8j1nCvSLXobLvwFuvrLjehblk/SfjPxzcLSoPPLoABXfzSYXXsoXgC9Zz8V7QJoZK289j96pS+cYSo6szWI3ygP4ogZGG4zflutwwTMn3ZYwiz1hvaT8QdRhIULtWXaXiCmK2vg6QL5k+fjk15BDW1kbt/xaIw0TODD8yFc3vZyCLWPVZpwcRdIgvx+r75FLk7kkKkM5SVWlel4tqzKiraNOy4QAato+w0rPcxBokG8xQ4FytIWy4+/ksRVCLBdCSOsRje5DlyqVz2cfR7bSzsmZf//3f3/8+6lPfSqe9axn4QlPeALe//7343u/93sB8IOdWwhh6bWhPdQ2b3rTm/DTP/3T8f+dnR1ce+21g5JrEyORGM2ps1ixZG88F7MUBpJ05G70rSnh1BFoqzQigFIRztComfP+XZbkBFbDDDrhSNFJ0l2XZX/Omx9+3hjAlCKKpfuyMbrsOQphXwTfxn6gifmT0fKkApRXBSIOBeKWb2QEbuHPzt0augBMHHEiMXhYy00w4AkBfB8LI5E50Kci5vflIPx7BSxDw7HIhdH07yDMEF2RgI8f+3oKBbV3v4BUkKXH854nDIW19NiGYRuqp/x3tRELsCDHoq7lBLJPrKBgpFGFVqEOJmOAv3Nd6zH1AaU0ougC4EK7Ohg4CzvIaT+ScW3wHuE8KzjP9/OPZjtnmCW3tbU1PPWpT8Wf//mfRxx9GGHfd999MVo/ceIE6rrG6dOnD9xmlVVVhc3Nzd6PWi4F20t0Zc57qGlCvsPIUuT05mwWdkwqWJUi26h/nsMruozXBzqHBIaJV4FYSBk1w6h+VaML+UywRbo+pSTaIqlAFqMIH1CMRqWDUbnGjB3FmCVqD4Lf+/EWV0gK/mump1HVOzCLfVC9zwyQxT6omWEUFljDIjFCxNGoamIjLIwo7IXVdMQDjQyWRLRWwWZm8Hfe3Fmta9Mk0NYSjTdMRVXZBjneUF2Tb2Y2eZDhxLEtJfJO4mDUtfFHI3dfjvmeyeQY3Ah1MKsnteDhwCX9G+K3H5i12KuHPUjPzY7AiG8+Oy9nvlgs8KUvfQlXX301Hv/4x+PEiRP46Ec/Gt+v6xof//jH8exnPxsA8IxnPANFUfS2ueeee3DnnXfGbc7JcscJDISZEmMhDLaLuiUhS9Tp54AlWiMNsb7cZJmc71+1t/OJJkIGtuTWZfVef9Uw2L86256j0QScdYlZo9dSjJg+CLCzlQnHLHZj+T465kJHOqJwr0O5zs7KjUDtHEY6Een16WRCzQI022Z+ty0lCm0jLlyIvGvrQ9+ZDCdYnVhkbOO1aF5CV0bDyFw/r5CS/JDv+gVd+aF9x5On6uAMVzt6G41NUXx+j7PvEmuVF7GhB0+qTsbIobUjXmnpKkAj9YwOyeff9r4zHUR/xbewhnD52OEx5TLmfa4Y+CWHmfvuwvwc2Uo7p6n/DW94A/7u3/27eOxjH4v77rsPP/dzP4ednR38k3/yT0BEuPnmm/G2t70NT3ziE/HEJz4Rb3vb2zCZTPCKV7wCALC1tYVXvepV+Jmf+RkcP34cl112Gd7whjfgqU99amS3nJNlzjO2WhskQ3u/Q4p2lr7o3gMuQTUroYBV2Hgs8jHRsSUmDKXP5b/VgWfnytS/ADgkFcgsslenseQYTZHGQaiUNN9lKVdiPRUz3424POutNJF+R12NEJTb7nvRbVSalCKhSOkUgS7d1hFgRekvXj8egtGi4+CbOK40vHfyeoTQhtxvoA97aR7BOBD5OBlSYEeMluIEGPt0+vRZ1dfp3essgo9ytuUaj4mqI0pRkoXn6J1MrAwFALQ1yqpE1C9Q+MZw4wrVgq+pROlr7qm64tG8EJj5I2oXwhkfOfMD7Zwi87vvvhv/6B/9IzzpSU/Cy172MpRliU9/+tN43OMeBwB44xvfiJtvvhk//uM/jmc+85n4+te/jj/4gz/AxsZG3Mcv/uIv4gd/8Afx8pe/HM95znMwmUzw4Q9/GNY+VJ3bqrOnZee9KpmVmz7wQIwiox0QDcYIOzfSyHJ1pNfbpzIhWo7YGNro89pTi7O213kmmnbC8S3L+Po2tkOLmDjAkIhAObFVmlaRClUvv55gHMJoI15PsCUXBdkCfrzFfHSl+HWsvhi7J2mTCiA2T9AiF1VJjNBXDntlk1pv5dGDnRJXPI3R6vxD3Efe7EL7mIYgsEeZKjgHqo1x9SXbL02++rqcg64ezGw7MqJaw3g6LfY4MgcSLdW4yC1XETBl/uw1HhV1mHQzlKGGqWexNuFRxWQ5BHb69GnceOON2NrawtbWFm688UY8+OCDZ/zMQxVKfuMb38BrX/taPOlJT8JkMsFjH/tYvO51r8P29nZvP9ddd91SQea//Jf/8pzOn0I4fFyfnZ0dbG1t4b67/xKba5P0MA4ZCsMoVh9iN5IIayJdz4VuJngyQwrz5YdZnQyQHOvgmDkXWROc0XKmTD1lCCRvOKz4uEnNiHv/izOgesbyrmQYK3fCX1dseL7DPGhXpWsC0zH1GoKrYJoZF0cVFTvpdi6tz1L/TKX6xZ6aAEJRCSd9Hd14C3XHic+SBtEsUiIv6sLoPru250SHUNOw0q8nuqVOvWuXlQ5XQGvBFlEVk5o5zGJ38L0YJFjz/ejqSO+NfE9IxjLYgsdfICqN3of3LC/0CkhFVjs1UxO1WTbVU7Tl+llVfl4I29nZwYkTJ7C9vd3LRV3oY2xtbeHUJ/5fbK6vnd++9vZx/P/7sotyvt///d+Pu+++G+95z3sAAP/sn/0zXHfddfjwhz984Gfe8Y534Od//ufx67/+6/j2b/92/NzP/Rz+6I/+CF/+8pexsbGBO++8E295y1vwYz/2Y3jKU56Cr3zlK3jNa16D7/qu78J//a//Ne7nuuuuw6te9SrcdNNN8bX19XWsr6+f9fkfam2WaGTQ6+jjM83voXNVk0jZeR/xT90mT5gudYTPTZ2BLv+H3dOHHHI9Dy/JMonYgi0jfAFjeemfV5pnibDo1Noa5EpedjYLoECEYsiVQLuAmW8nB6J89OBB8z0YO4Of7YPWNgWKEBy8a2Hmu/DjrRStiyPXRguxWCt4FtCS8s4WBs7wBNbJos8hRaO9a6BMlVHHJ4+2B3mQnviZwkFk0FdPT+Oj2wdptqH3R/+O0M0QNsv2E89Lz0UkDyLLSaCsYBxoviPjYkUqwqGDwcITJrprieaDLUDlBAEGWyW/ufAWBEJRrcO183S/HsIOVVHRJaxn/qUvfQkf+chH8OlPfxo33HADAOC9730vnvWsZ+HLX/4ynvSkJy195mwKJa+//nr8zu/8TvzME57wBPz8z/88fvRHfxRt28K59GxvbGysLMg8WzuvBOgjbj5kEZTt6V3ECDl/KP0gSRZZEC5ykXPrLb2BPgY/TITqZzI5gVi2HU8qYzJQVrCSR6MSYVIzB0QzpYff2hKhWlutH5I57lCMpU+lE50VScq6CmHtMvhiDGxeLqJbDcxsW2iIE5bHlfMLtpRio4oLjJo5zP4pbp3mKtjA1EoXWo4u5TwVZlnKWyA55h58NRjPng5HhF6yFnOr8hldmsR78E4QSYLFPjtbnRBj3mEA8+TjCSQGE7KEapCCrHbB+Ljct1BOGPYiAwvP7B8NLuT7pSuDeA5djUrEyrQP69laOODvR7sNiwgXi8V57e9Tn/oUtra2oiMHgO/93u/F1tbWgQWNZ1Moucp0VZE7coCj/OPHj+O7v/u78fM///Oo6/qAPay2wx2Zq+BHdOjoY83qOPNKTWngAI0ygd4kkD+0ObbK0WtYdkpqGZwxjC7jaxnsEptRuKTUqM6H2qT7ooUrPe68aoaIM4wsDMHOg7GsAAkA5ZihE02OBg8/2kQgYqdCRqAB6Sg0ExEuswCwy4nDZgZ0jp0WAD85BhJZXXXc8IPkLLE0QiAsrYz6NQEECoiTWS5N23Os3qdr0/EftHdT3JxIsfQkguVdxTK+ruIm1fUeJ4J1QlkxOVP2vdGViB7fCLzmyzVekXUtGjtC4wOKch0UAEMGplnwBOJK1F1AVa0Bow0geHRa9GZKGAIKAqhmEbhHpWP2/gIkQPl+XHvttb2X3/KWt+CWW2552Ls9efIkrrzyyqXXr7zyygMLGs+mUHJop06dwr/9t/8Wr371q3uv/9RP/RSe/vSn49ixY/jsZz+LN73pTbjrrrvwn/7TfzrrazjcznzYTusANsTwf/Itgh9zVx11ssGjg5GCIb+036XoXCLAKKqUrQLy7kFxFwKNRCwV4AlAddJVOkAhAYBZGIovS8KMgo/a4pAGy0QGIVSxvVk8Ty1HNwlvDsUoHktx9kDETi54jizFaUO0ZUy7y7rn4600Jm3NWLHCGl2CjkCp07xCGbFCM89lIE2avSh8uHoKg4nioHsuFs9J74OIYvHEpbrso4S5oz8pJwZL5uQHQUJss9cu2EER497WOsy7gAfnHUpLWC83Oer2LRof0MBh3UFoiAC6GnveYb0w2Gs8xsUkJlUPFYRyFhZ8h3Cezlw//7Wvfa2HmVdVtXL7W265ZXX1eGa33347AKwsXDybosezLZTc2dnBD/zAD+ApT3kK3vKWt/Tee/3rXx///q7v+i4cO3YM//Af/sMYrZ+NHW5nPpTiMybivz36X564hDhZXTpnutdWKu7IL5d6x1Lz7AFXsaionw30Im91CtTV7Pz4JBOGnFUsAmDHYNq+gFjwSbMcHH3zUtxGRgwt9viYxVgmq27JAVKzSNG+JjjJADatIqitmZGhDTzEYdNil8+ny6pCFa7wrVRFJhxdj2tDC2rqNIkan9rtAcsyCWGQ+MzYKXG/WfIzSPu6ON55Mrmdp3uT7VOVFX25xrmFegZtAJ46FqHfWzU7B2rbqEtOzRxhtJkqcAVOGdsS4zEAIkw7YOEJlXFYN9l+VGyt3semLeHdRqyajcNxwN+5Pdoc/tnasHjwIPvJn/xJ/MiP/MgZt7nuuuvwZ3/2Z7j33nuX3rv//vsPLGjMCyWvvvrq+PqqIsjd3V28+MUvxvr6Om677TYURXHGc9KK+v/zf/7PN4kzV9ncoZ41sBzhZU6bO9NLT8xSdEyUDrhCx3oJK9eoL/i++NMQXtFJox0wXjSizzvLa4FQUwMui2Q7G5k0IUucwqVKUFrssQyr3YcXvDt3YME4EBph3pSAUOeU8eLHW5IonnEHIjm/UFSsX752PK1oyvWo5qiwTmyHFwbSsqLWGCcHdWI6rvo7zwko9p0nngfRPIBUXTlMbpPhSSd2gmJMWp19UBZSCNJ1qe5P0owLxckzwl/6HQKAroaZ7/J7es+r9Zh4wqbR6gAAo0ZJREFUjxh68Fgj6RfbtLFSuIOBlQCAmhmvrhaEzdEmTD2FVwrlWdihwsxXrXofzj7OwS6//HJcfvnlD7nds571LGxvb+Ozn/0svud7vgcA8JnPfAbb29sHFjTmhZJPe9rTAKRCyXe84x1xu52dHbzoRS9CVVX43d/9XYxGD53c/tznPgcAvUnioexwO3OAnZvCG+oQhhAL0ItSY7eePOJVGKS3bxdbwQ2rQBX3jYyZ/DjqxAdwQmwqrZCJiHhFnnRgTJGCZbhFz7/myBuWJ4BQjPtL/mKUMH49vpFuNnJtwUkk4FvWdVEVxdFmZOEwhW8cVwuhmKSVieUiG2qmgHaoNy3QpuuMic2IVRtof0+WmE1NtXM+d4SqdJLTMVOHrpOmmjoEmzGPVk3EuvoxJkbTTNcs2IkqZ37oIKLD8T2aYi/vIZ8x09PoNor4WiCDqV2DJaAy3NRZhbioaxCKCla/f8ahWzsOs9jjIiYgceEfhXYhYZYLbU9+8pPx4he/GDfddBN+7dd+DQBTE1/ykpf0mCzf8R3fgbe//e34+3//759VoeTu7i5e+MIXYjqd4gMf+EBP9fWKK66AtRaf+tSn8OlPfxp/+2//bWxtbeH222/H61//erz0pS/FYx/72LO+hsPtzBXXVP6ziFbJP/1obvDABjIMIWQCTAB6TiYmPXOYJo94c0c+jC7zSDFPjgK9qD4A7KCDBxmHUGfFBAoZqYM0FoEcKFMuVA3xyIHWY2bRZJDzjw65nsHMtzl5N3sQwRxPcIVWRup+pBS9R/XU/ZEBuVKgiSxKlvGI73fZ/lZFVrlTl+0ijr0qD5J/LtMzp0HJRNAKVI+U2G4R5QniPrPaAW0jOEx05/i5CmcFIsCyno3X910JH7jdG3ULeDdCZzm9UxpwgpmIJ1FZObTluujB92UhHnUQyiVeAfpbv/VbeN3rXhfZKS996Utx66239rb58pe/3Cv4eeMb34jZbIYf//Efx+nTp3HDDTf0CiXvuOMOfOYznwEA/I2/8Td6+7rrrrtw3XXXoaoq/PZv/zbe+ta3YrFY4HGPexxuuukmvPGNbzyn8z/0RUMbj7msh1dTPV1qEtGLrILn5b91UukoLA9pMBA/K3S+qH+SwwK5DbSpl6AdrfzT9/0gysyiSVPvw58+CXIlyGWYWsU0Qz/eYsqhMlPaDI/2HRcLtQveRqRY4Uaijd4ljLlr4U5/NRa1+MkxrgL1nFwNtohMF4AZGxQCaPYgyHfwVRLvigwaFa9SU0hFYRhdfagwVvCJ4tfV6BUDZRTEyDbJNeFzYa2hM89XZDrJuyLuMxjLkIh8L8z+qd797n1flMuukxiZVBgkiomhXAPV+7ydq/g1rfgEUJMwVTou8jLzXcbsN65CAKSjEFBainotcdWHC2ur9vnXWTR0/3//z1zkdz772p/iihf9/y7q+R5WO9SReY+uF5f6oe/IB9Fqr60cBL8M6kgcooB+V3MEPIRLhhjqQZAOmaR5TSbpn+TntOJ6yNjo1HRJSU3NkECbVhFBmDCxZVxbA8UI1C5gFrvw1kXhrSCsE7PYh3clUE7QbV4t71WZ85PxdCWCZ4jFV2s8QTZTaXTRghQzl+5DwWSJx/z6JcqPLJZhbkPGLpBhPff8/uTbDB15hDt8lhD1/fug4+IKca5zdtZS1ARbstiZOmrfciNmPZaOcxbBa4Vs3H9grnmEcIpR5JMvUMAZQhlaLLzFvi+x5bhiNEyOMa5uHSwVGDW7oOmMFS5lojnfUv5LTf4WwCVdNPRosEPtzAH0Hl5NuC3BHJkzVsehf1sCQA4LOFSYAx36kb6WoQNLUrrx+CsgllRi7vpaIKGNOHJ8TSNMgVJ4t+LIjQVZy/uoZ9l+UuOImKyTqJzqfa40dCOEchw1tlksSxKpCpVopackgIOxrO8i8IoJUrVobEyEhnItOV3vI/sn5BWw6gw1oh3AI0Nd+F7S2DpE3WqbWDJLzXxN9pn8fuhrXQ0UIjimcg8hMMslnp+NTTuYppjtJ9+vrh6A5QheYBd15ORblPIda+FQkUct9zyMNnFy2uKK8QSGgJGyh7QD0gWwR9xpH2Ch6xAeRq/f4T6ObLUdfmcODGCMrNqOzNJ2ANjZ2lI41ryNIQfvRjAd9wdVHZMYVWac5bifoWCT/p2tGIK0AUvnGRjL1W1Dv0jIjNfQ7Z5OUIux/AXW/TSy74JhlDBwcMGV8ABH6NPT8BKFxpVLs+CErzA8SJtTAHFMosRAV7MGjCvi/8zgGIOahpkzMolGRx6y4h9dDQm/vieEZWRb3S5LIIIMF/5kWHUqBlud1D7otURZ3E+4vytWrpICUT/y0wSrQmP5CiFvuq2Tt/eAYyVEKyuxHc8wy9gZ0GKO/cDw2X3TFqUlXO4MBxDa2OTIjuxh2uF35vqgd22EAeA9CJlDz6N3fTjJABCIwTgucMmdvbEIbhwxzsgOGTiOCCPkpzQsU+9NBjaxPIAUoeb4dDkD2gaAMlCY4RIC68lw44MW1MiSmiiyU+C4E1HUJJcINbiKk5SeYOr9BFG1tQh6lTBSLBTcqM/L1317x6qAqlESfFQIDLZE44HSIiZco6OzLtEYhaESk5V5Yjkbszy5HMW+jONVVcY6SlosYTmaVkkH4ZanSNoDyHMcXdR391mP0Oiw1dFm9960TXrNt1y4JTkbByAUI7R2hBHxddZdwMyu4xvTFkTAVmVZ9HOx369ROAuHfmiToRewAvTIlu1QO3PquqiDEU0x1c5nuuJZhAX0sVvDWG0XgEKKYoJUVxqFNQbFMNFWYd/qhMRh5wU8zGtWuEDwXp9F8AGcfJxsAvWc4RXwgxu6Thw3Jw5D5pwosFML1TpaGDRUYTza5CrD7XuEElcjtKXg4BusVVLPEJo5PIC63ESVTTJ6LVENUAuHIuZc8PjIeVBXw5iS5W+V161Rdd44IqRGFDqGsVJz1TgCSademTmFibmL2H9zCK/p/fGDBhF5jsU6gZCS048rBQp9ymjwERtXdU4zPR1ZRH5SJVqhQGuBDCoTMO0Is9Zjr/ZwhrBVGWz4adrOVZxULc8OankoR37JOvtLnM1y2O1QO/MllklI2Cf/zw8kGdMvRPHgZXy7YEzWjbghgE8VisGW8OOk421m2334RuAcAP3eo3ouHqnKFOg7ggjTDJOm/AgyhXAfvp6niadt4H3Hjr6URKzqzGQOzMGjAaENQOFbYVxMQF0Nu38K3cZVmXIggZoZyJUw1SYnSTMpYY3IKVfxa2sQ6rQSMDY2wChcJV14PEslqEWWCgB0Uk2bsVh0CIBeS7d0PwdJZ4W/gu/ROnu5C1F5JFml5DouoVqP+/cVJzG9q1JzDJ2EPJIWjNy7lPRlrJ26Bn60wd+5eopQrcPMtuHHW5g33A5u4ggT6nC8cthtgd3aw47WsFbvcCJW9tGrVzgPuyQd+ZFddDvUzjyqGvqEOWs0BiBBMD51/YmYteidwHuYds79MMsJCEAbgLoNTBcDWK9FI7ccFsjYFDl9bVWCjw9uUsGQikEBIA/haRsWf7IFsHEFcPqvEOYMfVA5YqYLEJsph0wrhVunseLeWCUCvOeEaDND7PupHGu9JmGcWAI3tbZFakDc1exoqg1udtHOY3d6Pg+h6JXjWDrf67ATEu5NXZrYepF0bjkmreM1TDqvYippwjQQAJuSqMbFitNEcUwaM1RPgWKUuPWqizOAfKIEg3GRsRIx+YI1QYItIjU2GAuqpxipzkrw6EyJ2gf4wD1ST01blOtbDLVkgcjSVwarnfOZou9LNTI/auh8ce1QO3OENmlVZw82sugyMgxyiplEadTVwMKzil6BWOptjUNpCY4As3svQMwPDkVG48sLZXKcM3gNsOPx4ltEXH0IML6qvHZ1vK4ESLjG1gCXfQvs7EHWHZdkKACE6Q7IlbDCtNESflJdc41eHSc0/XgrRotU78OvHUewDqaeRYzYCmSgHOxGHJHdvZejXoGj4FvmscvnuRxduO3GcZGQrlz0umyCnaLlk1qWrOxF4ZpMzVcfeQ5kaHmJv0a5yoaRPEAUC8sieJ0EKZ88JG/Sa6OX4+5a8NUJzbEVCdbQIFRrmFKF3VkHa4DjIwsEYK/2sASslwalJbQ+YN5x0DC2qx/Fc3XkB33mkrAjmOWi2uF25kCM/nrJS8cOM0Z/+fJbPkNkGIYpVW+jhZ3fH4tHDLHCni7T4fvCTj1HLmyGXrVoHl2qYwCSjG4mqZqocZLI8w0CmPPsqw1uIxUCQtfBT3cA7eG59yDMYy4H2SLBP5JD4CibnSgp3tvOQc0cdvse+LXj7Niy5G5HDos2YFxOsDPvUFjC5ngrFhMx9rzgbbe+Bb5kfNzMd2Vy6uDLcXTicawlYdlTnowskH4zkPy+LlER1XKHHlcZA0aRfjd0BaavKYuFDKjeT9RT4+DHkuBtF7wqQdnrK6tBQCgnvYmYFqKJo8fuWoydQSgLdCFg0QVUlnClXcCXE/zVXouxIxQij2iJQO0c/iwbUlyyzvrIHlF7VDjz3jJVnacruHR7WG6fb0NSdVfvMdUveK4IBGLrL4AZJgB6lZuR8jZMuOWTi0acqx7SDOvPNUvipBOYssja5BOOqKc7CLN9/lzXgYoSYboHJeyFYhSLlCKUkUEeodpAGG9xkwlpkKCqgsE4tF2AM4R5F2CI0Hlg31ZY73Zgd++Nk1ewJVebhiDiW1yhiuBZUdGuVoTrTXjDcaLUMCJq3uT3a5VRJlObR+45OyRwoY5Gzj29e1tG6qmec6JsNnGVFQpJxMo4RpiFpKhKKzdFtVInsElVIkhGxcy2OfdiDDarEs4QxqS6MOZh0RIvVTjlQAsXIDIPR5H5QXb4nTmZqPPdgzSMA0zGXulaUOg/+Cp5ykk7wValmQMLWk2iQ1jirg90SCggJUWHyoB20OtSz5sMjDRdJt+xholG9qON+H9wFcJMIvK2ARkLqhgeCfN9+O1ToPEDwOP+P5KYZB3yfDIhYeYEWwKu4qTgfBt+tAVfTnrt3wDCYypOogLAjDZRXSXNKHwLs9iPlba+2kjOuJOemFqUJQU0kWGUjRf0nulYGSSIRN8bmt67PPLOE+Ayrvl3I8JqMsZ6DZrAJTIR92ZISFr4BdvbDzv4eZIsJqZ8wm7Bl2tcdTvaiKsQBC9ywlLcZSwocNenDc+KkqFaZwc/PQ2/fsVK53yEmS/v48hW26PCmatDBwZOQDnJnY8YJ7XNigQXUjTcLBjC6FqQ35MGEmUqrCGKTRt60gG5I7eOj+PbJIDV1YnimJ13j/pGnLyjdg7UM3YyHUMIfv04aL4P7D6I4AAsZvEyQ1uDwGX3oVqHqWeRVqeRa4+VAcj1dUDFE5U1DrUHuhDQ+QBLBkUzZVqjLTDFGJ0PWHcOfrTBkaZvAbsWm15EJkp2D1hnZMAy0usHUgJ5wOTIG38s2QEJwyh3q8ldMrz/dhFXLOhahqDkvRBslrxuASP5B89KlTrJkjGxcbaeUxhvRd5/t3EVNzexPk2cAEMyIuYWq3HbBcze/fAbV8GXYwRZ+Z1LCf6ZHPyl6MgBHPHML7IdbmdOw0jbx6g6RlNA0tsW7JpUxyNiocK08NKXsmtT53rrmBGiCS6y8WHVKLoXYRIzUqiZchScO6OBzgs0KpSqS0BlAzpwhyEbHRAA0NYVoN0HEeo5gu+YFmhsbOxstk8C4w0uPJKVhWpoqyMKxnFDhWIUuwPpZFPaEosOqAOw6AJMOYHdux8wFgY8kXUg1IEwcRVCxaL5BMbiQ7XOE4pqvA8cLlfDilMVHvawH0ueANWWeVHbPb/v2f57ImYmmyQH1M0op6v7GJoVjNzUMX8RJ0HvAasTPnPW/XhL2EjMJHJeagCE3aMc93j9toRZnE7fg+DjxHshHPAl68SP7K/FDrUzDxLJ5lExY8WGryxGvyFJm1qHYKoYOVMW1QP8mTDaZGcpeiX62EfYIHNSw4YW1GkTCKTE3FDvfAA59CAYmXBMM2McvFoDIEwVAPZbnoAw3eHt2waq4RIWc/jpLgwAM9tFWDvG51tPOWpWyAFMvfRUoizL5PDEYVpDaBsucHkgBFwxuRwjS9ibi1YMGRSG0JTrqNuAsePq05hwzvW/dXzysYVPSeCVDn+g46LdmLLxWmlkkG6Uj9K9+YQRqaySL4if089kME6o1mO3ot5qxpgoTUANi2PBN6DZNitUKgW2lc5OypZxFaiZM6PItwhtHSGplTmVs7BLFU450I7YLBfVDrUzp0EyhEKI3c2pReQWxwKPdgGEwFojrgA8S8OSvmYkCg8Bfu04aPZgeti7rE+lOiGVchVpVU06RqevUbUd4Lq5c/eJ/UK5Y21qTmyqVrleY9ckvHyyGYuRTDsH2hahFv3x/dMwwbPTEMw4ODCNDqytHQCQcRw9aoQOps0BgCWDU9MW48Jgr+Zzn7cBm5WR95PuTGtH/S5+itdnMMvyDTR92uHwc8FHRz6kLMb7oDmTrMKXUPcSivHeCNRlap4o1fnGphBaLaoTMnFqudf1SI+r+dZmxo4aZezApEncaMZJS8DUoCKUE5afmJ5G95hvWb1SeAg7VI4cOBLaush2qJ15hDkyXW8AUVCJODPKdDJjGZYIgQtzhGYYFI5wVaz+9LaE2T8VKWh6LGq7VHwSl/iMmxuNBAVT7akAZnBAj10zvBxhixAAmBZ+MePGsOU6n683QFPDz5nRQq4ETdbTDsoRqBKn5DuOLMnwdZZjxooBGGVxgJ0mihE7MdRwbgQCUFnCyBnUHfMxSktwhrBbd6g7dlXOgNkaxiEE9McAWVSedRxauvahE9OSfSAmtnsNmvOxzVkw8The7m/G/7euVxAUbIHYaYps77vT0zAHYKIcg03nq7AXeebpGwdfjBIcZEv4CjCL/USF1O+FEZhO/vabV/HEoRTXpW/F2duhi9SP7ILaoXfmw2V8fChzfDp7EIPLkpBtLaJREkm7iqOlXHK1rbN9Z1GBNHnoUdW0WEUTatnkwufk+02HdT+NYPC2jO3dSH7QtiBbsyMnA4w3GL9uxTm1LeCZpujVgYlTUbw3uFGvobNOKnn/zKiNHrgEPV6mkQYKBpg2Hl6KX9ZLEyNx8i2LS6myIpC45gpd5A4zn+iGnPwlWAb9FdHQcrxcX9KyfV3RdC62Bgw6uUnTjpg3EZGxWFAmUbtXGqbvAHQsHSBwTTAsreslSR6ZSEHkIEbSjELP22erO4H4aL4rbQDPTmTrTHbJO/IjPfOLaofbmWuS05h+cwJd5mZJ0B6bg4TX6xBx8Z5T0Ycu7wmaReLBigNQlUY5VtxURLOiQ+/kmMUo6+TepSSgVJ5Syw0UGAJqQUXSc2HdEtYvp2oMtA3IFSBrkxCXEYla1RCXY9De/QjVWpq0GgCuAopRKs3XRJ1xADcxAwWg8QFdCLAgnJ61WK8sfGC4RbvjkG95YtTGyEZwbmMQ8YhuOTewxCrKX89suTeo778mcMjQQjFKsE0zT98NZZuUa8l5y7n3+pTqZN01sbgoVuzqRNjVoJYnhZYcPJV8xQEgcsDkWPxumcV+FNaCJkl1wjnPqPwgu6Si9SPM/KLa4XbmS1F5k/5XNT8pG+872+xvN4pJwF6/TRHm6u1PD9Vo5WbdnxzOZNpU2LIeTIw4M4fEDkoaJGR64HmSVwWhQlsDgwa5BABOIu9iwueozrFrQVlUQx1j6b5aYyflSqZlEoPpIfAOLRFGllA5QuUMLBH4DAlNFwArsEpVIkSHlybGPEJfKX07YPek8cpWUEPnrfsdjm+mlx4LurLxjZG5b1nX3Y3SKmqFk9BVRnAVaD5nSQC9VxLV552UCIAhMGd/iaYjn3FVfEk14Dty/XzDBbRLxpEf2UW3w+3Mc2cX2uhUlWrIUZdJrBUixEhRYRhdZmfOJcqqAj2Hos4gshAUVlCHoMcgE7F6AIkWKLTH3r6J6YmxcEj0X4IrgDBKGK8Xze12wcctRwjzKchY5plrX9AQwLraewLbVMy4GETCJCsBQwZ+xI05yPHxnBE53iBRORF2Fx02K4udRYfTswZXrpfYrJz0HB1h2hGcKWHCii+VbyPNj9ksWAmp9F4bjHt8bdhDNTflrMt1974fQD/Zqo03pHI1msIouRyy8Qgl5yaCqEQiUOpA1S4AMrCOZQE6sFPvAv9YYRVBhLp612gcty0k96h3vGEQfDzcfRzZajvczjyDVWJkTqLB3dUI6tQ1sjOirmeQlsn5g5w3LQAS5RFZNG9LfiDJgMwiJbiCROuirQJASsGr+D4zGlwsJIr9QSMck0nCWpZwjY5I99/xNdJkE2QsJ0PbRqJ5A3iL4DuYaoxgERO0wY1SuTlpT9KsoTIZ1FSi7gCFLLrAkXlpCSEY1B07etUU2Z53WN+YwNRTVMUEXeaNIoddGoGEPPJcwV5Zup8KZeR4e6b3soSfDyYCnvRczAf48RaMJkxVU6VZIBSTXmUo5ffZC47tW4a/qnU+p3qPk6xA1CRnmAxAmMPJRG/13sn9jHCeTAKy+LloEMulZkcVoBfXDrczF4tNH7omOmBVzktRetuvMtSHahD5DTu8R0ebOV1qa6ayZZEfiTyuVhNGtoxMLAD6gk+qLjiAAmAznW9pcgwIrCCf4Qie5XqpniMYDy0eCoLzh64D2dS/tAfbQJb4sj/tMlQZD9gRQgjYk2Rn3QVMG4/GB5yeNZgUFoYIPgCTwmCv8XB2zNgCwMlTeeA42WiWiqpCrAjNb+IgQZrpkyeu+MDx56uNOAFzlyn4llcd1VqsJA3FiO95M02Mpmx/2i6vdy76tuQXQlEJI2Wft5dJJxamyTmAWlCeFJVzVBw+KDdfJxhzcSLzSwozP7KLaofbmZsyJfBE1VDbd/GLJmLiGhVR8EnxMHPY1GXl+fogS9QVVGK2nvHSPMfLxeJEIYyUvPpTJ5bgKqm8zBgymiSMrez0fCSpKOwLSLceFcZiJ7cGeoyDmW7H8yBjgdFarJ6Mx1GnAvQSkaZdcHK0nMDMtlFZ1hJBYVD7wGrCIQhubrBeWmxVFl0Aah9QWEInjnzsjLSO67dYy6+tZ7k3H0bbOaau+zoIXskcOYA0ceTYve+yVdEoyTpobqWrhd0kujxulLTfRbo43ktbIkgnqlgkpNG9lvzn168QXPBMD6Ks85XqxBRm9Ridp11Kjjz4gNCdb2R+KV3RpWWH25n7GghV76XIJ++yZGieBJXlOpHvyZvy/tq4PXR7k3RWIu1OojCOvhmjp+AFyqgiayQ6dHEiCs9EtglUoa+NCUIY0TtXp9+1iVZIoY/1W0ncVQKftC1QVjH5CalCpGaBYBxMM015hWwlYfZPMaY/3uolcp0hUOZwN0qHumOaojMEI0lQayjSGRlnJ1g3YhghrkryccZqvDzexAPw8qGzGyZB89eySYDHO7WESwqJDSCNSfoQTRcj5yAJy1g4pAlyW8LnMvZ6boNrCWR40RIAK/x+AheD8Xcpq5M4B2c+jLjPJgJ/pKP00Pnzd+bn+flHsx1uZy4RKg2jOOsAbzgJaBiqiAkxIxHWQQ+OPuwKueSRmz5wA9aFLrV9OY6Mh2DLtIzPeMiRIWFYBExVE/k6Ok6c6grDOBDNef/KrtF+mqIEmc65BIqUnAUZeGlOEScR6ecZS8zJwE+ORVyYK0GZf+7BUXlhCLYwGDmDCTX4+sxg1nos2oDWd9x13geYwsAiwFrljiPlBLKIWldGaNueA11phnXWkz66rpgyxzn8bMS8+19tCoG/D+W6VMMWoFokIGJSONEOY1FRhHG6xDQC5xPIlLGTEMjEhKdGj0QU2S36GYAnPH3fkoMtXcq9nKUNnfLZOOlHOqY9wswvrp3zuu7rX/86fvRHfxTHjx/HZDLBd3/3d+OOO+6I74cQcMstt+Caa67BeDzG8573PHzxi1/s7WOxWOC1r30tLr/8cqytreGlL30p7r777od1AT2KWrbcjo60S6JJAFKxzEDzWh2j6phzpeg88qiDEfVE42LpfzymLt8zbY5gbFQSjJrbw3PNEnyR50yUVhVZFM/4OaUEns9423EwTOzHSfNdlqptF1KiLhx0kfWNLBdRS7x/Qbi3G2Mh0q+tD5i1HkTAWmHgDKGmEletOayXBjuLFpU1IAIMCOtF4otHaqLKFGQ/en969yu33MHnFZ+9yP4MD7Tpf6Uj/bOreYXVziPMpg0moiqmwh/6PRFYrDdpGAcf2EG3nhtP1MGg9vx/F4Jw8/n/xgeEkH66EJLTDwGtDyw1bJbjqovEVjyyR6mdkzM/ffo0nvOc56AoCvz+7/8+/tf/+l/4hV/4BTzmMY+J27zzne/Eu971Ltx66624/fbbceLECbzgBS/A7m4SN7r55ptx22234UMf+hA+8YlPYG9vDy95yUvQnavugj7oUsIdnVtGUYM44Pi6Jtfk8wDY2alglUudg4DM+WfHjCaNfaOzFYyV28O5fkXowHFFbDZv5CCNo83+KdaFUTxVYRlJzgZXcLs2hX4keqWuBjVTYDEFTbeBnftA+6e5S9BinyNvXWlkuHlpGBffbzy+vtdge+HRdOyIpo3HTu1xatbiwXmH/cbDEuGqtQJjR1grDMYFcaTaiHqijjENHLD+rIJY8p/83mhkrg7dZI49Ezjr3V9JHMdWdsGnax9+d8RCtQY/Zm1ybnTN3wmFwCL23tWRE65rhdaH6Li7DNP1IifswVE4Ud89N/Je58PKleIjHUlfaFOY5Xx/jmy1nRPM8o53vAPXXnst/vN//s/xteuuuy7+HULAu9/9brz5zW/Gy172MgDA+9//flx11VX44Ac/iFe/+tXY3t7G+973Pvzmb/4mnv/85wMAPvCBD+Daa6/Fxz72MbzoRS9aOu5iscBisYj/7+zsAIAkLccRb6YQoA0n4jnpUt/YFOXqj0Td0UlmzY6ZF522J8WbpaAIbsSwBeaAFttoglGZDfnSOcPr+cQ8AJMie4VyrAMtWtCi5jLxYpI64jheQXBPyypOQLr8D2RAtozcaepqoDmAT63nKa8VhtBZoPXAXt2BiHtU+gAcGxksWo9JZaKzunKt4GbEAL4x70DwsNpOra17johpoeg78nxS1f+HY4Xk0FY2qzDLDrB/gSbmDHS1Q8EDC+nWNJBWCK6KE6RG5tDqYq0TAGJxUAir6k6z08ucd6crw8BOXt8PAfAPIwQ/wsyPbGjnFJn/7u/+Lp75zGfih37oh3DllVfiaU97Gt773vfG9++66y6cPHkSL3zhC+NrVVXhuc99Lj75yU8CAO644w40TdPb5pprrsH1118ftxna29/+dmxtbcWfa6+9lt/IqWnqDBSyUBhDIZBc5zrbtgevaBeZwDBNHmmHLEKG6zNVUjVgxw7SVYlNopOBb2OneD1HqmdMcWsX/CM0PF3yq/YL36lsYtG8ANhRBmPTpKUJ12oNfrSFsHYZQrXJ2tvVepzY4nlImfvYmSimBTAlsQuc7Jx3HpXj6619wAPTFl/dqbG96DBtPVofEmc6Mk/KVFSTT2JilBV/BKJUYHVQpD60AxKO8b5qZN/WrK2S1QMorz4JsHH+gppZ+qxxrGWfrbq4Y5DQUyGYOAAi/rGGYIhgDcHKawA7cP0B2Imro6cLhKUcBsz8yC6unZMz/4u/+Av86q/+Kp74xCfiv//3/47XvOY1eN3rXoff+I3fAACcPHkSAHDVVVf1PnfVVVfF906ePImyLHHs2LEDtxnam970Jmxvb8efr33tawBS1K06IMFlkXWGO/eiQYVBclohkeDbGdtEHmoVvuqJIKlmx2KPMVYrMrLqJPIu8Xp8EfXi8yzZOUTqWx9T99Uat2PL+3caK+qOWnWYZFojnKT762pmwFhOyvrRRipukXFgGVaW0qV6iokNWC8NLhuzo+9CwKQwWCtYOXHWetRdQJkVDTGswA5p7GSlI42ko3PX8QLShJqPu8JUcfWUfnKHHmjg4HNsvWtX4ugsZdskbXEZtxiJlxOuF0A2ucgkpMqKUZTM5dQVD0MQh80OXX+AzGkjOXr98Vmeg/MNwMjSOePjh9Exh66DP8+fIwncg+2cYBbvPZ75zGfibW97GwDgaU97Gr74xS/iV3/1V/GP//E/jtsNscEQwtJrQzvTNlVVoaqq5Tcyx9vT7cilWNUJZw4zsu2CTw4TiI0c4va6D3XuLUkV51gc4ig5J5ccErLJYMm8j/re0TFLJabqp4RqvU+XEwfmixJkC1ZZzLvO5xCAwkEAO/RBm7soF4BxwvV9C1rsYVxOAOPwrRsFZl1gLXPHDt0H4Iox88tHzqALIWqQrCncYRyC9cvKkPr30N/qRDx0xENMXV/GAG4Zfm64UmvnMFIbEO+JbxHsWirs0o+qKFk7BzULxs9F1jZKKrd1YskEH6mGyOAXEl5+F5Kz9kgOPh4vl0c/R1riYbUQLgCb5SDm05GdW2R+9dVX4ylPeUrvtSc/+cn46le/CgA4ceIEACxF2Pfdd1+M1k+cOIG6rnH69OkDtzlbo4z7HZ1vpjeuPSG5MUG77Fw04tOozXdZp/VRrPpTTBuujFWjvf0I9hvKMXy1nqJIOT9SRxpbkLUcMWriNcPaTb0fHXKO7feiyWKcEq5yDtq9J5TrsSkxAM4jNAuYxW6KYoM21OCIM1azBs8sCwBr9Q6+daPA2BlslBZXlB3aAFhfY+IIm2EOQ8C0CWg6Tp4GAJ0p2ZFlbBRYlyAsHTa9T0A/sZnBYblEbS9CPwN+HuGwwJW6pJru+n3QcbQFX7srY+MKauYgUTakegpTz3gSrGe99m/MJOJ9OckbKI5uKEXkBgK9oA/FWEqRPBEdTJN9CDtiuxxZbuf0LXrOc56DL3/5y73X/vf//t943OMeBwB4/OMfjxMnTuCjH/1ofL+ua3z84x/Hs5/9bADAM57xDBRF0dvmnnvuwZ133hm3OWvrusQ06VLbuOhMu3qpUnMZXxcFPUmioq0TCyX/AaQ5dA1T7zPjRBOoEvl5aeyQl/XHY0Kiv9j8gGJEHopxovMFn6CAYcIWgLZmC24U9VtCOWY4SLFdxezbeZbcE/1uk117M+/RNKmtYUMLs9iL0XppOPruDDfNoGYOMz2NUIyYoicaip1nCQCAHVqLdJxeQU1+D0xilMRtVkVuqz4PrE6A6rhn+w2DlULsJtTWkeVCOsFmkzPVe6J3b5PMQ1un85b7pU6cADjiRh42C72HUAwprm4ofu7hwCaHDWo5YrNcXDsnmOX1r389nv3sZ+Ntb3sbXv7yl+Ozn/0s3vOe9+A973kPAP6S3nzzzXjb296GJz7xiXjiE5+It73tbZhMJnjFK14BANja2sKrXvUq/MzP/AyOHz+Oyy67DG94wxvw1Kc+NbJbzskGeDOCB023EXzHSoLOieaGdJfRKFhw5XypHYpRjOaCKAiGcswNnnWJLY2dybdAPZMeneAHXvcjXGQLSBVoVl6uRT8SZUZMV66lV2wEjWAlwarXqTx6FRQrJoBw4mNXnyxC1bExzQyhZR0QP3bZOAgsVa1Htcmch98Gi7lUvKxVmyjqPQDAZmlgSZOlgPHMn1Y8uXd/1HKp2lWWiXNFlhIG93jV9nLve/x2UTPUce1Vo/q2n7CNiW8HXzEMQ4s9EHH/zkAJVw9Zc2cAXHSUq24Sj4u2pDOcLU3fDwjersf1aQJ5NNsRm+Xi2jl9g/7m3/ybuO222/CmN70JP/uzP4vHP/7xePe7341XvvKVcZs3vvGNmM1m+PEf/3GcPn0aN9xwA/7gD/4AGxsbcZtf/MVfhHMOL3/5yzGbzfB93/d9+PVf/3VYa1cd9kDLGRGRN00GMBZhvg8yli9RmCaxok/oarnFhscioB8Frhb7Ej0zlk62Sdu2c4S2EOiDy9e7wA8pOzPBrpXrrpxpOR61tSRRu8QpV+aNnqspYhQLIDkulSgQKCk6LN8y41Gjd9mGE7QmKfxlTYZ7uLQt4cclY8eLfU7uGgdLAa1nx+10LMD4+V7D2Lregrpj/vQ4S1b2RLfkPuXwQq+gKIOI9PzPaCsi9NiDNbvn8fuhv4Pne6j3x1UCCUkyeVBZHIqqn4jNJwL9X+4jwA7dh37kHTnqkm/IYbqla8g+d2RH9lB2zmDdS17yEnzhC1/AfD7Hl770Jdx0002994kIt9xyC+655x7M53N8/OMfx/XXX9/bZjQa4Zd+6Zdw6tQpTKdTfPjDH050w3MwbQFHyvbIWCpkLDc3bhN8ga6NmiQIvgdNJCdLrLgnRTZmts2wyWgDoVzjZg7VGvzkGNP9RpuxOAUQR64JTqRS7mgqoNXWoHo/OmMVCgsi1ES+FZioiU6lV/xkBhi+cQjlmkwaA7qmYuO2iMUx0bRISpKxPgC1F1imWoN3I9QdM1kA1mRB8KiDwXbt8cCsRStsF20ETcRaLTUcOpjUKEJNnC8XOqnglF8qKAorEuJLLeR6EJTvJxN7Se9sElQYxvO9UGzfrx2HrzZStyFbcj2BJj3zcdWcS14cFZPRfUlb/R50ITl3C58kFA6wR5sjD55rQM7v5+KNyunTp3HjjTdGCvSNN96IBx988MzXdBYV78973vNi0Zj+/MiP/Mh5H3tohzqFTvWcGQYAJ7IU16wmoM3joPUtkLVZWXmI2DoAfjgFPskbF6iOi2qzqFCVLyfw4y1061egGR+DrzbQTY6hlcYFKSKX3QvkELu+Z5WmAJI0a7UGP9qICdjYhk0wek1WduQi1zlizQK3BGNTGztNdALJabkRQrXOlEaBe8xiNyX8Oo7YbWhhCNhrPFo76o33emlQhlQI1fqARRui5kgXQi/yrDvf0zjPo/Fcr6UXPeerp3y1pdsBywnDYeSucBVRvxI1j6bz70S+D12RCbU1n+g13xEDAjJpspYVj167A08gFpwktZSicgygrUeb0z7IfOcvyM/Fsle84hX4/Oc/j4985CP4yEc+gs9//vO48cYbz/iZs6l4B4CbbroJ99xzT/z5tV/7tfM+9tAONVBHzUy0NVySwPUmNQ1QbnU9BxnVOJfioCZxj9G1IGNiE4FQTBD0gS0qFsSa77I2tvCobajjg2/FYQ+Xy6aHi6oOSNbzUXFwZNGldn4PgRs6qHNpa9bPamu0xYSD265myVVAys5D0v42nABm5ouqBEqDi8U+j5cbAYa7FGmFqMJJ6oTJtyitQ+s9Zq3H2LG4lAlAZQmdM9hvPDov0acPmHcsmcuwk6go6qSSO3SAaZo5jKSsI5KGFrnDFeGtnuWRuEGaDGwJuJbvM7AM6YjQmDYA4cn2/gSnNXP4teP8AQ0YMshIJz+T8feD5SSxARIOLpOGMY6bfUBYNkpHFc37i22XAmRzKWPmX/rSl/CRj3wEn/70p3HDDTcAAN773vfiWc96Fr785S/jSU960vK5nEXFu9pkMolsvwtx7FV2qCNzAL2S+fiAACmKMw5wrhc5BcOdZ/JKzhiV5wlIXUa7EtRMYRb7aKS8niVvy3gOsWhIIRw9qWyJ32uGoM5ftco12SeSBAnbn8dzN4t9+JI7+jRekqvGoTMlmmICP9pgyKeSlcKAZjlks6gzieMojrHzHGEvxKNbKXbZqz3un7ZoPBcMGSIQAQEBp2YNpo0X7RaGWjasx9iECCms5FJnWitabTmUIO5RFHVYI31RYI38fynIitG5MlwkSo9MFJU+MI4FypoZqK2ZkmgHmjpas5CLo7V1v8pX7jvpued66l2NopvDzHdh5tuswTM9HZtLn4+dDUXxkXbkF9p2dnZ6P7ncx8OxT33qU9ja2orOFAC+93u/F1tbWwdWpp9Nxbvab/3Wb+Hyyy/Hd37nd+INb3hDL3J/OMdeZYc6MkezgGlm6AQW4cg8tfrSQpFQTEDNNPXrtA5+tAFfrSVMPKO0sWJiHR/oiGEHDyf9GtG1IK10VMcbxbPKfoILEGfCzAvFynWpzZNQ1iNTu9wDgBElvyASur5FJ8qGJhAaT+i8R2nFKRqHptpEMT0VHbaya0K1CVeMYIyDnZ7m/QqjhxwQiHVuiByazgMWqOEY6wQnNtdLbh+njpxZGYStyqGyXKYeAEwbj85ZjBVbyPn5A1hkJc961WuDqDyv1O3th7gKlzp13gACRU3ymBwloYi2WUDQzBLM1i4kIZ1VgA7YL7RgZo/WESizJZdP1h6uaOdCh5xJsr1F95hvOejbfdZ2WBz1hYzMhzm2t7zlLbjlllse9n5PnjyJK6+8cun1K6+88sDK9DNVvH/lK1+J/7/yla+MtO0777wTb3rTm/Cnf/qnkZ79cI69yg61Mw+Tx8CPtkRoKnOaXYJAmCOcmB3MXiik3L3g6Ezx8q6O+DNGm2k/ZDjq1YhRl8dkYOppTEbmTAcL9CKzXkQMxMrE2NEme29YLBOdVPAwi31MjMWumUTRptYDheGYsC0msKHla2xZYMos9uDLdYZBTAmsX5EqI30L09XoyklMvoYuOW/Ay8RE2ChZv2W9MLHT0GbFbeTqLkS9kU4i9zIQas8O3ypklDM/0HfAgEAvBj26YdTaORunn0fT+bh78HeETGoZZ+qkqEgZHz0mPKURuB5CHbhw0uP5dbUwf0r4cpzwcGlTFyeIYsyJ9eABoc/issf2pSJW2IWGSB4pyOVCVoB+7Wtfw+bmZnx9ZYU4gFtuuQVvfetbz7jP22+/HQBWVqCfTfX6Q1W85ySR66+/Hk984hPxzGc+E3/yJ3+Cpz/96ed17NwOtTNXJohWRPLDFmKkzI4hVR6yCh4vqSGNCvR1ani5G4xFKCegvfuzZTlBe0vOqUJFQVgeAWVZJq62lMPHc1PsF4gYqzqmuPzvam40HFIHG2VTUAjceNlyA4xQjBGsg6ln2Ah7CNU6ph3BGn40O6nQJCn1D6MS2prMdXMEO5IknEH7mGt4qT/b5mO7CsGWqLuA2gcQ2Fn7IIqKotViidAGLo4xYIc/dsT9QOsOrWdhrtISGh+icFcbVMvkDM5XIamc1ZLTCofb6/8HfT2KKsJwRJz0Da4Emnn8vsSktI6BS9WzkWooLClNHMcktjr3VhqJF1WM+k29j+A7+ApcFBYCf1dtIUVmFuGyb31IRw5ceMd7WCL5M9nm5mbPmR9kP/mTP7nEHBnaddddhz/7sz/Dvffeu/Te/ffff2Blel7xfvXVV8fXH6qa/elPfzqKosCf//mf4+lPfzpOnDhxzsdeZYfamWtLL34oF1EUK4dFqJ3DF2OuXuyamJSixT5HoeVa6g+pLcKaOXcM6mpuZlCM4zK7QgcEwEu6YdYGTFyCECJmqpzyoXMCYrOMCPv4FqgXoGocE5is2piSgkRSzRkqgQYWoGaGav0qTNsQdbWtNtAQpoVxgGnnQNeiwBytHXESrmO6ZVeMQfU+/Ggz8sN9YLxcYZTKEUaWz2vWBVjiiJuIUBmZRIg55w/MWhGP4nOvO4/CCCULfbZPzxFHlonvOfBc7iBul+HUQ6ZL3K/y8ItxrDEgjdK1T2ekGTbL55KtGCgEToJGOqKNjUtUNbN3WcI+QvAws214wfFN1gyDKrOsx/4w7VJIbp6NPRIJ0MsvvxyXX375Q273rGc9C9vb2/jsZz+L7/me7wEAfOYzn8H29vaBlel5xfvTnvY0AKni/R3veMeBx/riF7+IpmniBPBwjr3KDnUCtNdE1xWJCRE8vHTR0bJ3repD8DGZZeoZzPR0FFhKEXzJpdzSRm1abGDqLXfhkciwmJ7CePEgJoa1y712qoknx/g4upYdr0jd8gF4kkFT9xODC4E+lI4oHXA0ocnnuQCFwEJQa8dhCGg6bo5QWY6aEXzE7BkuNlHQyhJQB5PkXK3j1nEAKjQoDWts6+qu9VKC7lvsNT4WBpXkI9WOMXRmt6wVBlYi+S4mSVcsFVc4YRo65Pz93NnmTny4T+XUCzyVC6cpTJbruwSXmoLn56DNLSKu7jsOBsj0PkNS3k/NlAMKSUTHSN44mP1TrI0D9PR5tNDsfO0wOHIAl3Q5/5Of/GS8+MUvxk033YRPf/rT+PSnP42bbroJL3nJS3psku/4ju/AbbfdBgC9ivfbbrsNd955J37sx36sV/H+f//v/8XP/uzP4o//+I/xl3/5l/i93/s9/NAP/RCe9rSn4TnPec45Hfuh7HBH5uWIl7DNIhWYhNRnk9o5uo2rkhMffl5au8XIz3JBCdVTxuLbBYKrGE6RkJIdYwk/3kqcbmhFn+klRPV8FD6IzkQiZwKEudL1NcZD1n9SluFR6LFai2JSjWeK4MgZzFuPmWGJWmprmNLF0npvSo7GwU0jQgioYVAYpuShGMV2aZaASWG4S04QnRHDhLvSslqinovzjDlbU0mDCv4swcdqWIValGetBTS9CH0VvKJjk22zBLEs3VDfc/SsXOhAxoLaHEcXiQdlN7kiHjvSDp1LVEhJolLwUU432EK+Z3xMX20k5UUJAjjhKXi8l1lRmnAHN0IYbSxfwwp7tGDml7r91m/9Fl73utdFdspLX/pS3Hrrrb1tvvzlL2N7ezv+/1AV72VZ4g//8A/x7//9v8fe3h6uvfZa/MAP/ADe8pa39Crez+bYD2UUQjh093VnZwdbW1t44M8/j43HHGdGgStZ3a7LOMEZxS0UVSzhj3i1JLp8uZZUDckwZj7fAfmOI3oymAUbVfC0GMgHoFRusx4HiC3c1EH0yvUVD29msHv3I8z2WENGuwYVUqnpRnxsZYGQQSjHDJOEFh3xuS+6EB3vSByvwhm15/PTG6w0Ou1XaSWaDgB2ao+1wkQtEdHM4usDUjLYuIR/y+szFPjGrMOs9bhi4rBWcNPnectNoScFobSm58B7TB8tWooTX1bIM4RYZJyHlNI4Rq5CEPpmABfvmPkun79CIup0BQMP2WSmzKdgS/jRBtMUgdSApGv4++NKFmib7/D7Kmcs7Cl0NSsvLnbZ2ZdrLI3QNjEx3l7+bf2WhI+A7ezs4MSJE9je3j4rDPrhHmNrawt/9lM/go3qoXMEZ7LdRY3v+vcfuqjne1jtUEfm1EiT4nIizYvnEQvt9dZUpkJbI1TrMPNdlgLQKsh6xhWYKBGsiUnBbnIMe1IQYyXqrTuONDuJOAMkqacYL5AcuZhiqnl5OgUPX23AKGfZd/D7Owj1HLS+FbfRyBBk0NqR4NPMJpk2HluVQd1xhO7B4l6153O1EgnHAiAwy4az5Bx1LyThCYAbOMv2Wy4lB+N5G4fgAGccZh3DKOvOoWu5WbGVVnONJFBHjiQqJ25mjKQSqPcl5+HHexWLhc7yi5BF5NoYA+AkbbwPgnXDlQjKDweSFovSWKVqVKWLlfsfJwt5PxiHUDmQLRh+0SIzgCcD47i603egdg4z307FQTsPMMvmym8/ywt8dNilXDT0aLBD7czNfAd2T5a42pCiGEdsk6sgW6nqZPzTj7fgJ8dA9RTkO7Rrx5mT3HLkuXATVH4H1LGq3liSetYTypIwceLAQ8BCkoAlZUm74PuJLSkKCsbGv/P2ZL5cS85gfYu1ZIC0nyjxW8PCs9YJgBItgmNefUXADBZ1x5FwF0LEvS0xfl0IwK2O3YBL9uctv+dDwKgwaDzrrCxawnq5holrYPdPsXMalejIwQaPsQH2PLDbsl5LaQ2I2KGPLEEACF7NELNZ4n1Tb64sHpIeoQc9qGfCy7Nk5VJxkTjkyPfWrkLQtnF5UVKR9iV5EJW/1Wg+CH88+BbkUwKTI/UKCCWv6JoZSGiKfnKMnbnUM4AMMFk/KxbLkR3ZudihduZBWCRmvh2rIbUgA8bwctd5xH6OjouJTM2d7UO1hilVzLYoS7hmyo6ZDEK5FlkaWxVjW0qzI7Be97zzWCukk7vg6zAp2agOWZ0CAFlq1+k1jSSD5wg/Miz6rA4AoHqKslqPTqQLNiosGvDEo02YLTGUEqR6c9FyP09L2p+SHXhhCNYADiQYO2GztMwTtwQEw3kHMlh0AQ7AwsdeSbGEnwi4fGwx6mZowwTWECoCtmuPQiYWIzNM1KwhE1c1IXiBbdJEOGSJDGmMMeEpKwflyXdCnYxl8/lKTWGvnK4KQKWDdaINrhJ9c1kpQFkqfB+XVDeN5e3KyZKKI4t3ORjRwQmjDfi140u49V8nlv1I4OYcmZ9f27ejyPxgO9zO3DiQ79Cdvg/22JUJ87alQCdbMVKjruXILC/kAXOo646ZIOrsQzFCDRepPmMTADLM5gBQWYPSAI8JU6AGP/zGsniULTkiRIb/Bs9OwXvQYjeyWthRmESN9C1Ik6OBOfOqCwLDEwzV0ziJTWzSLCGf4BOmAgJ7C4/OB1RO8GpPIMPRsyFgy7aoqYz0QQCRY15adrpxHORQWuIPSBcdWQlY4v8DXGK5+FQwpIwWxeSjk86laoE+Fh48gD6nO5rCKhkEtEABCAwWV2pafamfVwqqb6VozEXWkSbPezi28MxVV51C4IlBG4tkiesoYSxMFlIJCc+yEX5yjLtIHfR9PvCdC2+PSNGQvwBFQ+f5+UezHW5qYjODX8wQmhrd6fukAUEDmu2AmincN/6yv309Fby8YvqYfDEsAbu1j0VCi2Cx6HxSxBOMetYGrBcGVb0DqrOHUjnLkhzkBGgT25HF47fS0UijQW1WkZl2/gkiSRD341OTapKEYR1M7OjTek6CBonKDYC5KBqqfK0PTBX0AOatR2tKGAL3+JTjd563NwAKpWWLQ/ZIjpsk8m98iNWf+43Hg63DfuMx7wKmkkVVR64deXzInEmepFZoLA5GnxF0EJOFQkBbMITiwftWWmKPp25Yklf155U+Ss1MersylZW7T83isVmNsksJWZOaT+t9x+Dcg1AhY81Drg2kOZxvMgv+AlATj5z5gXaoI3O/exrY3IDZOg60DWi+h1COuLqu5K45dvc++HLMmLnjpgu+WosJMEuAs5yoW3QB1jh0GVShOtRdCJHtEUabCetVKhoZ1MGwA+za1CFHaZGe+0rGfphCcYtSqwop5BS8XoEMxe19sQHyHHnui8OctR4jazB2XHmZd/zhCk5g7BhagRQFrRU8MbRwKAxh1np8Y94y7u0Mi3mFgNpT7G3pDGEu2Py885g1AYUBKmdixF13QCdYvBHM3gARYgHQh08yi/j5qmbNq7jlMna6GggC+zjw5B2IOAKXFU/dcXLYCdwSKEuQyoqHmulqGIJMmoA1ote8DOScdSWY89WlAI26mr8bk2MHXsuRHdnDtcPtzB98AGFUgB5zFUc/830AYA4vEVCtMV3Rt0AzQ3ClJBylrJs8TDuHd1y84QFAKHsNgGnr4aQh76INqBwxDGMcSAuEjIOv1qPjy3VEWAvEgjqf4B1p7hzlUYHlB1uX6GDaZKjW4SfHmGpIHrstABphQkxHrH3gBhHBo/GE0nISclIwhl5mnMA8Edp4oDQOEIx54gwuGznMO4/T8w5jx9sW0tPSC8e8zRoEbFaSkLUUo3prEtQDsHNlVsgAYgEOjLaX3h+OkU54xHkHU09RlpNYE0DzecK4XYlgyzgJAehFxrG4KJtcAWYl5UlSFUCjrmFITSNx1XLJMHr9DpBvufirGIO0qXbw35w87wtR9HOEmR9oh9qZU1mhe+AemMUc5rFPRji2FZe11Czgi4ng51MQeQTlFAdpZiyVgnOpoGRN7oDLKi5Tn3bsyE8vGLedFC4W2QAc1TZ2FBN61hCobVlaVyLLqIAoUroAEFSzvKtj2zIS5xIVHIWXrqXotQd26070UQSLFr65F0EeogzKAMMnTKXk5GjtmYZYWQNDIRbxND6gASdHx44w7zjSrzvCuCDsNV4mCC4aYvYKO/hF57FX+wzKYThKJQAARIVFfV8pk9Gpn6EKNGLeg4pQpggWiS1UjGKRk5EagYOieUNAFwyMGyUJWykWiy343Cjh+ZpY13NyVU/TXKtMjU4EApPF4rVmKoJdrvc9+GazC9Fc4mI2pzjsdqidub3sKphuDnvlt6KbHOPy9ulpxkwrx8kmoRyireE315kHPttOWHbwGFcOnTGwocUscPu5vcZjIpHp2BmsFQZFvdcr5Q7GweUJPE2kqYVBQ+J44i42iIBMPgrZQCV8jeOovJwguApVs4eyKLHrGRKqDMMlpQFqzQGCHeysCWi8x7GRReWYEz9tfRTN2q073q712CgMJ3gBtOCio9JwZP/AtMU3ZgGTwiIUBtoMrbRAaShjzhDmnU+d54kjdFVy7FV7HmQZLEHDaF2phzqW+VsNy9QG42DBdFXV4InFYbIPnkRCbN8GMGe/V86vbdxEnoHvs2WNF3XW1kX2lK6uuGlJ0a9a1ebdKuqFDHa5QPZQrJRHgrVyZI+MHWpnjmoCNzmG7tQ9oMkx2O2vs9g/iWStPnAii2unp9npl2PYvb3E9W3mgrHuYzLaQPAOlXWwgZ3tVgFQN+fK0MWedCTK9K11SS1iTL1IUo36uug9mCX4yL5IDiQJNSlVLpQTbBZjoPVwD96N9jHfiqZcx27tcWLNoZUuP9qPc97ycn4muHqVURcJASQStbNW4Rd+7PXhnzYddusWG6WDNSVKy2yZDRsA32LmJb8gn6hFH4Y554grncouR8fR8sSmXrv+2aaJUR1zQL9CNBAhWKEjZjLIeSOQYFIhURcAL57caM9YrdzVcwi+L4esDUTU6fvkmAlCgZTiKmXXkHHMngo+6aWHFhg/5uCxOEc7G0d9KTnyIzbLxbXD7cybBQBmhpjTfwWMmc+rrcAAxIczlFyWr/rjfu04R+2uhNm5F35yTCRQGT+3AVh4C/JAqZElGSnjnkexph6XWasFgVg+Hj8nFmIkTj1MFZG9ksrmeQIAAGn07CoWZyKDbu04ELhZxmUji2nLlapErHK4XjAv3BJj51rl2QicNHIkFaA+dhKaSfm9B08KxhC2RgU2SouJbO8DsN0S1goHIz0/mT0jFbEiLaBeZNqw1rri9r0EaJ7szf8HeslErQhNJfsJow7lhFdIAGi+J3h2sbxfcE6jkS5KpSF2/rLPLkDa542SvnkuEKZYt3ZrUhqpdp3KrqWn0SL1DaRFYBcQL7+UHPXZ2FEF6MW1w+3MfYfQ1Ahdh+7USdhvWYNfv4LZKtq30XKxhlns8vKWDAIKjprIsGjW5BioXcCPtzCVUsW92mNcEEoDtGTgJHqbUYXRKMNaqY0FKUtyrUA/clc8XKEYy4m5GAlCEnPREYm2etY1ieppTIh25KKTBhjnfszIojAWO3UHA0IDj7EzGEkCc63ggiBlfQAcoaqTm3ch0jKv2ShRWoZtjk+Y8dL4gLElPl/RP1eOOXyIkgK5KayRNzUOQE8GoTde+W/5WxUyQ1nGPIWtZOIFoN19gi2iyqSyV6zh5KvukSB/R3isZRYTHKgYp0rN+D2TlZS09PN6LwF4cqipQjUagRZ7qa5A2vCpMFsn38mmXF8anwttqyL2WHR7kY99ZI+cHW5nbiyoKGFPXAd0NZfql2OOlmtmtpBEuFzCP4MX1UECYHfuhV87zlzuegoDoFy7Ao0PuGJi4QOXvFsfsG7ZMSi1LXYSAhKDAejL7AKJm9w7bwNqs+45mmTr6mX+tTg1jdiDAcxCsHtiKt689Zi1IcrOFoYijbLuGEJxhjBtfGR7zFqPeRMiOUAZKgvRXHGGo/txYVAYj1njsSDCMVuDpjMEY2FHJSddQXC6ENLImxCLk5gFQ1ExUSENq+5VI1qlew4ceqRvuioW9MTuRb4VDj5LJmhSu/E8WXXChS+tSUwez1TJNoApim0Nsg7kRsx4CmtS/Rli9WePvSKwHbcodChFrAzlBKinvckgRu3GAWEORxffoa7a/6XgxEMXELrzO5Pz/fyj2Q63My/HUbe827oGoRihNSXK2TY7Rm3JJgkrPxlxgsyx6Ba1C9idkwyxjDYBMnAEeGmkYEgcAoBTHWG/Yae8VUp0nUfVtkzVf5qkyxv6Zomyg4pg8oYJwRU9yVxldvhqXTRp7getHccCFVqPyOWetQFlZbBhGixQoDCEUVjgwbZE5ThpyUwVhmCs5Yh+GK0rzL1oQxTfWnQej6lGoPkuY8VAjNYNIUIpBNZB17+N8Ms1EWrzMDHDywOwJIVLgatvQzmGd6MoscC5h2zwtBxf4ZBAcn0M/ai6JRmDWq6nJKRJuK1hpB9qZNEIZMYJVZO47zbBZa6b9xhUESoDEtbuOGq/0Nzyw5bc9P4CsFmOMPMD7XA7cyC2+jL1PkIIKIi1pH0xZilUMB66aD2arsN6uQlLQGdGKC8bwcx34cdbPcdqiCNygDnWGw7oYLBR2lhpqUtl7iVaIpSsq76KFx0hGdFpWVnNGAWfuJIwuFEsD+conIuSui5gXE7QjjaZGik0QGtYJAsQoS1bwksVZm1LBKkEVVjEB4AooOs4Ubm36LAuGjSFJawXFoWlKGPrETB27HC1gtXs3Y/JeAuhLDFrA+atj31AK5fGUjsW6f9An5YYI3EtwsnGJhAhlGuYSam+JcG6M6pifwLgzzvjOPIPng/W8WdsaDHWE+hk3F3Jk6xW2wo2Hh27FILF+1lPGTZruJmIH23xPbJFT7eeL9iLvEMJX51/M4rcgR+xWI4st8PtzINnveia1RC12UQAAOOw13hMm46LJ6WK0zQe1nB3HmscRqPL2IfA4vSiw2UjYLTYRlduwoMTZdTNYdwIs9Zj3QFm9iAfn2axcXJU0DM29nvsVXIiYeo5nKBNoBUi0B6gmthrPEfOfP6MGxeVg/dASSZqy5SWf3cI2F506IoECwGI8rQAs06U8aKqigCPybTpcJkreIIQ6VogReDfmHcYuw1MTCcrm3sRygnWjcNktMEFTUgRuSZFc+slPw33N9WVS6TzZYU3nSmlmIskwoZMjjX6OzZpPPOXBYqJlhVrBX0CQpK/jfxynTC02hMMt3CPVYNQrQEA52MaUebUdoWq1KjwmRtdEKXEgxz00Hlfio48+IDgz+/Mzvfzj2Y73M5cH1xJYgY3QitQwWzhsd/46KgMOElXdwFNw1WKoQuYteywC8v86mnjcbKdwLQtJoXBuAyw2ydB1RpCdVwSmCp+5Vg6wNjYgYYUGtHm0fW+tH+rQGYGM0sOKMInRZUgIVF4bMmhbpMzLi3BGYNF57Gz6FALLBKVHKUwR6GShQmYNV40ZbwUCrFeS0AQR81ReLCEYuw4V1AW6LxovfiktNh4LqxyhimP3hqsrV8Bu3c/5ySqNSw8Fx250KIlJ71EfTw/fQxjY4tsootl/DApyiYDX07QxjyFTyyXIWwl34c4QQqEo3TR3tdG2w2iS/mNyELpd33ic3M8t6huDhCbVmiS08y2EZp5pCPGYzXzqOVyMe0wuDjfAd6c35nGW3dkS3aonbkfb8IXFfdnbBYItkTnCbM2YL/xaH2IiThrgFkT0Hou0bcBURa2NoSiI6yX3H1+q7IoDAtHnaoJx499K8xsG5thziqJGrWRSYUkMbKso1OBlu0D6TVSASZZwhejSDnUSHXRBXQCh5SWI+fKCt7dSIFPF+AsxU4+AYwkhMC0QmcTi6PreDwIkCIikirIgLrzqIWuWMoxFm3AZmXQeoZXakmsau6pI54ETs87XDbeAmwZm1yMDWHqLerORzEuGaA4oeh4xOhcuzBpROu5inZKFbrGY+QYHsm37xUWDaGt4Dmx2cz7jjw/ZobJh9gFykVWDDqBzLSpiSvREksflPPd1A5O2Ed+tMHt+mbbvEoEkj5LMYmdiB6OPVogk9B5BHNETbxYdqideTe5DKEkaC/HhThyjWadaHUD7PxaH7CzaNH4gI3SorBGEnVJRMsSYC1XWGpHn44IJDgxdc1ywVAeiQmPmFuSCd2wmHA5uBSeBFdEbnmwTJNslb4n0bYXmp8PQUrkmbGiDtKJFkqHwN2KoFAIX48iGzoW/KrALfDYXnSYFBazNuDBeYP10sWJb+QoNq3QKF0lC+qOMXqFUb7RWJQZhDFrvTSYRpQXAFSwLERMfWns9HfHjnxhRgiecXrrs5WQb1MRTnTsIV5f5P8PpI6BLCLP6KLx9VzHBQBaiqstzZD4AJQhUUjDaIPzJO2caw+q9Yy5IscwJvHeH6Y9Ghz5kV18O9TOfBoKbE42WNbWMH/ah8TGKE2KWIkAZ4DLJwUWXeiJPfmAmDxUJyStEhhXhmcWSTsHFqKTXXHDVuoaIKveVGcSsVuR2tUyc32wQzFmPrQ4HEecj9NuQorx5+JVrcjNThvPjZOJG2d0gaV5fSCU1mLW+iiwtVUR9mofOwgx48SgdcAD0wZN57FoPQpj4IxF6RgqmQpEM3IEHziS36u5wGjsDAwRSgvs1QzbEDSyl6GgvqhW5wOC9E/lSTNLEKvjFTXCxo5gAZSO+ewROlFHLklidJkjz6o5+X/DkFdGC+0VdcXtCCAW0aIQEKSQLOL5qnlOLAdgFrMYlaNZoBltodivWexLqnX95FiEY3LK6sV0yocheg9dQDhPmOWImniwHWpnrqp+mjy0IHD5DjOZrfTq9OhT55yh6ChDrFzkfarj7LxEkQ6AMXGggrZ5y6VPtXoz0ycPBbNR0NYpUhMn5KsNfj9LxM1E0a+yRpwxO3OlDFIQTRaR6y0MMQTS8bXd27QyeXGRUN35eP3qWLcqloodOUJhLI6PLU7PO0kGE6tCgumNtQ/wXUDdsbbKpDCYFAbThqP6tcJEvrozHM1PmxAnxbHj8W99mjjnLUMmGq6bLMkYE4a2ZGcfpMmzWMTGKZOqjRWyiJEwiaplfE2dqTpv3/a0cnJBrqjloslO1Z2XfdlQA5LMpK4G1XsoBvc9nqMtAGMjW0abYF8sOwwuznfhAmDmh+FKHxk71M6cgkcLAyd485gINRF8j2ZIKIxG5yHiygDEabMj1+hcI2EPjkArkOhvzGOxES/D6yToZAt+PXiO6gSGCcYyfc23rN1RVOzIHSs5wjiEYoRFF6J+ShcIjeDPeq7OUoQ4rOWCIM0JAKk5817jYVvCZsWTQusD77tlB79V2ZiQXB8Z7iTUBcwpYL1kZ3dsZLG96GDIRGgkNuYoDQB26I1ALzpBKpyjCefWU2xkoaaPYQ698H2QqNUaoQ/m1ERx9gZctmmSjMKQ9cKOXhQtNXpeRQH1LRc3DfBzkO3/nzWbMPUs1hHwiclkIDK55EqRlwDMbBvd+uX8XZBJyJnD4XCP7PDaoXbmHQycr0XSltXzymKEYJl9EcDFIQRZ9gdCh0S1A1hTRJtPdB2zXhrPDkeTgeOKuMrQJyYKhZAiNy0cAlLbuLaGUVgFiMp+FAJowdWpvhihBUfi2kyi7tiJt+IciQi7C6ZTjp2RJCQ76JxWyNeSdMWD4RXH8ZHFpDAYWeJiFltyp6SmQ7lzD66+6jtw3yzgspGNUbRqsLSesW9neDLZXXSwUk3aecBaHte643HSCQEy3pDxV7hFNdEJGplnrBYgOlJ1kCGLqpWNCO/5d45BRyhjUIKv+863DamVH4DU01OKk/j4ct+yVoMUuNdsjMCNEbbNGtNjvShkqqjb9l9JMdoG50aGX95vQjtKgF5cO6eszHXXXScUuP7PT/zETwDgKPKWW27BNddcg/F4jOc973n44he/2NvHYrHAa1/7Wlx++eVYW1vDS1/6Utx9990P6+Rdvc9NcqWU28y3YWbbjHMbSk48NjFmR1U5hghKy+evWt3akUet7rhEvvaALyeppFs4yeQ7/umayFygZsoNnrtGoBcpQtHO8PMdAICv1tCaEvsNUyinjcfOgrXBNRr24OYPmsS14iGnjcdIonW1qO8VAsaO4ZjR/DR2JYI3iz1Q12I0vR+m3gc1UxaoOvWXrOeydy/Gswfg6j2WwHUkeQYpArKE9dKyGmIIGDmmeZ6edai7EJOr+bnEknugp2muQ7yEOuTVk0BiAAHCv3cJWx98TvMUev/ivcoYLgAi1x/Bx/wFhZDx/LNGFODIm4KHr9aiJHHUUCfDY1nPUnJV8iEgAzPfhd0+ucyH/yY1HwIn9s/nJxxNiwfZOTnz22+/Hffcc0/8+ehHPwoA+KEf+iEAwDvf+U68613vwq233orbb78dJ06cwAte8ALs7u7Gfdx888247bbb8KEPfQif+MQnsLe3h5e85CXoHmbX7mAsC09V6+jWjkvRjhddEHbilSOMC26pNnZJX7vzCRZQXRPFqRddiLBLjCCFVhgdQCZ5qoJKsaUYkAqAJNFJrejHTI5hgQJ7tY96KcrjXgiNUCGIWcOMjsqyUy8tX4uzFIWrfEiY9qIN2Gs87tlnit+Gk5VJ18A+eDdPNM0CdP9XEB64G9RMMZqfjjreoRhh1M2iE9eJZE8mnbYLkbY5az18SFowAGJrOelOx/sQamghWH8U3AoesTdmpB0OaIbxRmeFRZoAjT+MSwdbMjwVIPopbZps2wXr9USWidxHmWwVOw+2ZEaLVuO2dWqqPVgNaOI2uIon8by6V+inLKH7zdmM4sj+eu2cYJYrrrii9/+/+3f/Dk94whPw3Oc+FyEEvPvd78ab3/xmvOxlLwMAvP/978dVV12FD37wg3j1q1+N7e1tvO9978Nv/uZv4vnPfz4A4AMf+ACuvfZafOxjH8OLXvSiczp5lbqlegqUE9RUwlRlxHoBdigGXPVoNTrsFBvXghbR3pb9GkrRpQdjwwht6k4k2i788Dt21uJojER8BuCldzmJ3XL85Bh8tR558F3g3xrRAhwB6wpivTCSCAW2F13s/HPFmKtb90RXm8AMl9ISU/mIcPU4APse7oG/wMaxb43OkOp9TuIZAypHaI9/G0I5YYx8tIG9Flh3JUaGMDWEWeO5kbMHFuJoneH8giZSE27u0XjAGuHJe3XigJMmFcx9l5HOBciGUEl0iC45cu9TNab3HH1L8jkYh3m+rFIHnXPZdfLIjxcLgwjU1rxPIHYPohZJzhZInaH0s9LlyJut1HDES2/Y4NFtXn22X+dHv3UBgc4zsj5KgB5oD5v8Wtc1PvCBD+Cf/tN/CiLCXXfdhZMnT+KFL3xh3KaqKjz3uc/FJz/5SQDAHXfcgaZpettcc801uP766+M2q2yxWGBnZ6f3AwCLYEVXQ1T1BkuwSO3zAfM2YK/2WIjErecOnayeJxx0bR0HcHS5VVmsFVmhixSikDzArH5YR4cRRZ6KEbr1K6LMLvkOwVWYu7XIg+8CFwBpdaUmEy0Bl40stiqL9cLgMSWzULTBg0JBs9ajkPZtrc9YJAXhWNiDO303F7AoF1p7UdqSee+TTZArYHfvAwDQ7EGY6WmsG2aV7MnqQB05t8WTYUCIx1ZJACLG9w2lCDyEELF/ABH64hvAzo66fgGQMlEoc7w5qwWZUNn/v713D7KsrM6Hn/eyL+f05TAXZppBEEwI3sBEjIixooZ4C0gulfKCRUhpGY3BgJcY0ShoRUBSpUk0iYkipmIMfolgmU9DAcZgLFEQZwKoIZ+/4qYBBoaevp3L3vt91/fHete79+nugbky3fPbq6prpk/vc8679+le79rPetbzqHIYG52eQs9AK2bCiGNQc0y/KWSmVNAaz6LxhwxuCa0UAPPEhZkU9Mubw0JCW/R5D5RPNTR1+Fr7fKrFy0OIbdyBfrWxeux3A/TLX/4ydu/ejd/93d8FADz00EMAgK1bt44dt3XrVtx3333xmDRNsWHDhhXHyPNXi8svvxwf+tCHVjzuCKh0Cpvb2OwsK6bk8Vg7497Ki6qgiok0qgSG1/Ik4lP8vVD4FJgDHsfIJcmIqIexkXpI2kIZNq+ITTYljbIuitJH9x0TeNpFkJztlw4PFhWOmcox6YGJRPEdh6+QeofprIcpC0Bp7B7xL3ThPKxRmEo1MqsxmWp0lINemI3sGz1aglraBQCg/jzoqGNAnU3sypSkoNn/hQlaMMoVMIuPgNJJTHV6KJ3jIdZwTVKtoIIGDL8/RWaNNI5zqyJEI/86D1SKq/k0Km2F3oMREw5mCo1V66FxqHSoypfrjCsdtVyMtrzZ+LLeYMNnpYCxSVxSqk7QKmwmY+JY9f+jcmWo2JXg9vIzpaPYm7Ob4nnpYhDVNNto48mI/U7mV111FV71qldh27ZtY4+rpjsLuFpe/tjyeKJjLr74Yrzzne+M38/Pz+O4444DwAlCaQ3jK2TGYuRqGVdA6IesuQ1wRc4a3JzIx9ggkmegIkujY5vUtQZbI5j5MnYe8HLFOivwHhgt1FVgkoXJTET9lKZRQ2IUprTFVGaRW4UHF0ukJsVkOWDDg2qE6V4CQheFF7aJgoZCL9PRyHhYeejRLGu0Lz4KtfQYqDPNFWKnBwPG9skkcFNbAV9B5wOeTn34/4COfw7KzgbeGBtTnAAzWzLLw0yJRpCirRO7CpuTXMfmp6kbOuJOuNwBopLJUhe47takTB30VU0vBCdTJTK0AsVUBW+a5TBUzqGqNrb2fm1wzmXCE97Xk7rkx0W4QhNVK9R3W2rZ70DAyQFET1jxcCVtMagISBJ0OoeQWP44sVYHiOggwCzt0NCeY7+S+X333YebbroJ1157bXxsZmYGAFffxxxT44Q7d+6M1frMzAyKosDs7OxYdb5z50688IUv3OP7ZVmGLMtWPG5CUtahcrZ+CJgchQ9CUaJHHRKoD2PuTeG1xo1/hBE06k0pM/WfRqzOwq2+IgoMjKqu0pTmF0o6tS+kSaGBqE3CODknxEQTNKlg2sDr29SxXNWG19TlAOqxe1FtehpGKsd8qMy3TnA1qwJHvvJgU+vhApt02K3Q/Vm4yaN5OrEYArt3wtgH4Lf+DBY7W9CdJOilXVCP/gR29n48ZnoA+O5B7l58SNwi7OU8jW1GqeGNxYNhquUprAzTqDrAMJF73jRxCAla5IVJ6QDBiCmyjmJc1EiyhEYiDrRFbmLmUeYhQi6NSp43BR9kFVBj6iYdH+5ZNvpPSgHZBMMoSmPoCK4iGE1ItMXiiJvCk+mhFdZ6vNhTujvcSb5N5oc29gszv/rqq7FlyxacddZZ8bETTzwRMzMzkeECMK5+8803x0R92mmnIUmSsWMefPBB3HXXXY+bzPcUOY2QuwH0aJHhhOECDHxMQArNwZTAqpCEomWSkitNwX9To2ANU/MmEx2U+gK+K8MqIZqaG6occqVXFTBLu6CqUawEHRjT5UagH09sgd0xkWgclRnMTFhs6RrWHE87cNNb4TpHAaMBzPxDSDX7dhaOMD9yUchKOObwFVSxyJXnj7/PG0rwPwUAleZwux6EWXwEU/2HYBYe5gp069PguhtxVMp3JILtK1VfH6DWhRFYJwtqk6qR2I2uv5JwTcXtKPpuxovI/5eNQTTIa0pi2ECrot40TYrK5AyVBN/O2JgGAKV5Q1fcQI14eIOqKPBO3IB1DZc1IRpeXOPYtAtvcyxUwKMDF5UpR6EnI3LE+vAU5Y8bhzsNtpj5oY19rsy997j66qtx/vnnw9r66UopXHTRRbjssstw0kkn4aSTTsJll12GbreLc889FwDQ6/Xwpje9Ce9617uwadMmbNy4Ee9+97txyimnRHbLvoQaLULlSY2NVgVjzIbtzCrFwlXUwMIl0ROkUlHxVl+Bk6s09yxV8ZYcjWqcjB6js0kDVpHnhDJCDbvYnJkmfN8OB82DSuAqt/RB3VDViVBVrJ+uqgJVOgmdTaLadjSUK5Eph5+Z8KhMjn4QQkmVx4DCAFFIUro/C2yagc+mYB/+H1BnGqP//h7SX/gVqK0nwWkLs/sBAEC18QT4HIC2KEjDg5OYJCW5s7HhulAD1hlUYuqsIisnSiEgVNqaq/FEAyBESEKohhRwZaMQ9FaCFkuS1seGTVT5CkQeRqiBroF5a25MRphEojnmb6TCDpsbxo+LIdCJnANVcIqvrfN8vomuf69KT1HiQGQm9if2pnqO/fj9fpc2jsTY52R+00034f7778cb3/jGFT97z3veg8FggLe97W2YnZ3F6aefjhtuuAFTU1PxmI9//OOw1uI1r3kNBoMBzjzzTHzuc5+DMft+W6pcwbiqhLHQ/Vkk2RRskqNQwgBBTBBlgGAENweYsZEEpgUnlAKqZFegldrWquYTx4U0R8AtW9mFSm4QaJBOBT9RxQM9Ao0YxbuIJPKkWIwVJiU5jC+YkUIe3k5AlUPYB38Etel4TCcdkJ0EKY3K88i+HszCTR8DtfMeKJvw5GlvK/RgDnbr8SCbwedT6FOCyd6x3KQTFk7ITIlWY7dsma1ZK8Jrd0Sh+ubGstGIm6LR48NDq35u4lQfzlWSmFINYwlfsekzuJKWRG0RjK1tCjQYKOL7aRRvcMoVY6YSyz8rFaZNVZgNIG3hVJAWCHd21g1hNOvLLxY+uibxWnkqt1969DKDVB84c25vnr5ekzjRQTCnaIeG9hiK1uHVmZ+fR6/Xw647v4XpozbGhEs2jfTASB8DGsyJpP7eWJYACEp6MUkD400zmyH6PwaMNzrFi6VbgF+WzASLYVXMQqG0i7lKx6Qm1VtXOxSwWCh4etITs0B4OEjBFovR8q5feR78KYegJIdefITxYKWgRwtQ5QhucjOGyRQcAdNz9wG+Yuz8f38EP7cL5B30xDTgHfTmY+E7PbjJo5lXbVPo/ixvFukEymw6ml+kASrpWY9K2WjXVoR9a1D5YGChot45ESd/rWq1yjxsVBaNBCuJvEkDDHzwOBwUmp0Cg1Rhi7EKka3DEgk+2gMCQKoRG8fymVGwEawnQavIVRfnIG/zuNkXjmA1MGk8HisUCj/u2sSKlKx1Y7XC5Nz9gLFwvWPXbLJdreqfn5/HzMwM5ubmMD09fUjeV/5e/9+ffx4mzH5zLgAAS67C2Tu+d0jXu15jXWuzUNYNt9D10Edz6GRMbMlVUDYNQkwOPslBqebmmGDi4goTxJp4cKXDQyKuXyedYGbQbI6xaiNXhAAaTAr+nu/uA7asLUgMlRUP4fDtfBCTFbxWp4HeR4zBJzkojJQPvEIXAE0ezSbWCuz6A0CVfZj5AkhzqCwHLeyGX5jlhB4olPax+6EG80DCbAw3eTSqbBrDyiMxjHVnhmVfQZy0vdIgHxQVCWOKiM2oISvEDSFCAyq0SqUi91XN625a6knlrhgjF42dlWqKXFkbmwLK1p+PfAbNDb2JgYPvfByY1igsliR8Tkulx1RqAGLzjtxo9DK+O9k9dMitQj6aQ5pNYMFpuN4xLC2xShzOxmPzvdfqJtPGwYn9HhpaC+FThm9kACRqXJcjqKpknLsq4lg3mgM+5bBuZobbbQnVgB7UcAF6uFB/H7Q92OotjYlhgIRpko5xewomB4lmCEKBk3aiuUkpOLkNzcXEcMJLh3OxGWfLPiaKeX7/oFsyr7vYNQrmE9qi0imSYhF6OM/85uEc/PxjfCJJCr3pGNinngzztOdAzfwMUxKloQeAki58p4eyuymaWKehWSlwAmkbx/eHjhqKjTWkogPbxQdLOh7br5uehhr8ca3jwFDsSQAxSUeHnlC5E3gdBmHDlRF7mRIN05qGqvoY2WS1qZ2c5LzJw8uGDcSqXhhGRIQtZgRb8ga+ITOBsQOkqLCxY1iyQBvo0RK6Vtfj+6v8nh5WBslhfO/lQY5YbOuAvg7dGc3OzuK8885Dr9dDr9fDeeedh927dz/+OT2BHtW99967qp6VUgr//M//HI9bTffqve997z6tf11X5vwHJI73FMWvgDrBqyrg3ooCVTA0L4uarqZ8xdW40vH2HWAGhWCp0EldiZsU3ubwxDh4x1oULhg/VFXNT4Y0CglpqHJNgCpU+FkVqthE8wfodWd84lHwbJsxZlywScTs0OHobs6TOqqLjUsPQFUjVEc9Baq7ERjMgtJJUNqBz3tQroTPJrDoNDpWIyEPFbxL1XABic2RpEcxzFP2USZd5q+jAqCDNC6rN8rwFSs0BvaGZkXEytfcc5Yu5x1BIJ2mLnk8N8PX3qfdiGNHjDt8b1FTQuPnRr4WsZKNWWCvpnNQc3Rfad5wteWqPNx5VCGhO89qk6pg0xGfdvluKlj3qaJAtvQgUpvCT7AnrEzjZnl72/94QY6NTA70NQ5VnHvuufjJT36C66+/HgDwe7/3ezjvvPPwr//6r3t8juhRfe5zn8PP/dzP4U//9E/xspe9DHfffTempqZw3HHH4cEHHxx7zt/93d/hyiuvxKte9aqxxz/84Q/jzW9+c/x+cnJyn9a/vpO5r4A0BUShsOEsI7frZJO6CaZN3TANOGktaRpuvbVlPLUqYsUH8C15nVg5kRehOk2pQKUTbmbKwEp4T/bxZH55rBq1hjEpNw7DKLzRirHgoh5X5zcWqh4BrsAGA0xN5UGrhd9/i1qKG5Eq+izJWlWgyQ5fi2oEn02ggMWUX4R59KF66CWb4LsY8pgs5+H1BFQ1QgIwpQ82bkxZUEq0GkiVbmiXAwh/pkZzb4DPV2zsNFJTT05GITLJy1UBEkGwRnMyfk5KR/gsCmIJk8r7sQRP2kJpD/FfjbRDNX4TqiqeSWDTCA0lzdsg/1vmPSQDvmtIdbAXFBvAjDdJ2RgmkjwOhbWxPuNHP/oRrr/+enznO9/B6aefDgD49Kc/jTPOOAN33303Tj755BXP2Rs9KmNMnMGRuO666/Da1752RbKemppacey+xLqGWRQRfDYFn08BzUTuClaxq0a1lgdCIgjQi/KOk5jSgOURfHaHqfU3IrfYZtxsC/zmwnMi1wCmA+7eCU0/cXBnvncfyldIledEHSAYVAVU0UeGsuZgi2GxXuUjMSnfaQTZVUMVNiYOG3KDDbmBz6e5+bbhqYBhNo2fOhoiC0smgaoK1jEvliKNDwDgKvi0A0o68PkUnLJ4zPSwoPJYQ1Xgkf2OJuQNPn7HcpITuz6BVeRnmdFIAi1xTEjL+9qRKcjORo2WuPHaGksnX5uBAAxxyeBP0+tTpAGSPHyWDV45GE6h0BgnbeNwUOn5554YwxdaI5kEZvdPoRcexlQ/yE3IewUabGX2nMiX9xPWGvX8yV6Pd3RQvgCs0GoajUYHtLZbbrkFvV4vJnIAeMELXoBer7dH3ai90aNaHrfffjt27NiBN73pTSt+9tGPfhSbNm3Cz//8z+MjH/kIimLfpJPXdWUexZLSCRB56H4/Jl3BvVU1qpuRUuF5AORYBMlmUMUSlLHRlEC5utqjfAqVyVG5WnIg0YChgBWPFqFDglThFp+be7UmR1P0KVaWYAZMYoKmizgPGVszcpZrhigdoR94D2vYsUgP5+CmtsJBs22etqCkA720K553FJHKJkHCKBEHpJQr+Aoalip0kzrReRLWSjAD0TIVCxSeq3XhlQusEtURwcnRhH9VOarNILwDadQ6KsJMQVVDYTI/ECC0+nqOAKGM6vC5KcV65qE+MXInFa6bMOJigxUAXAEbNjZh6EBZGCD6vpJNoQdzUKMlGOyCz6ZCz2UAs/QYjE1i34GW1UbLAYG1hF8DT/56yPuxz3F/XwNAlPOQuOSSS3DppZfu9+s+9NBD2LJly4rHt2zZskfdqL3Ro1oeV111FZ7xjGesGJK88MIL8dznPhcbNmzArbfeiosvvhj33HMPPvOZz+z1OazvZB50UCjJ4Zp/vD5QCk2taR3NfIMJMNkEarTIx2vLDutFH0rggFiV89CPUQoGhEwT1HARWjQ+vOMkVA64sZZNQgEI4oywClGTi9ec1w1YV4bEUoGySU6WbghdLMHblKV1h/PsTkRUGwR7dsPBaJEr8bzHG0bSRZn3mE3iClDnKFCSQfdnsbx4VOUgjv3DsUSvtTkKstE/VCMMNgWdFtF4P0oXKA1fF/EANbp2FfJo/GJJUnbVmOmy/FFHbBvgDQ3MNZcNKxpHJDlQ9Gu7N1Lx9euTqjFwcSuSBioQYK6AlyMwZih8/mm4e2DXKYZeHAFKp0BwDCIT8PjBXD3EVPB1pLRTs6DaOOTxwAMPjFETV5P7AIBLL710VZG+Ztx2220AsKo+1N5oS+2tHtVgMMAXvvAFfOADH1jxs3e84x3x/6eeeio2bNiA3/7t347V+t7Euk7msZIN8q7C8dXDeZ6AxDjWjXIEKMNVnLbQVQk1XAgGAjaobzVswYI3pZgtKKVQQSGRalmobiZlznnKTUOrAOuLkLQb2LuvGkqAGqQzeJuzq1CgxbFsai9ayylXQrmCLci0rTcBWbOreEpUAcnSLlA2gZHOkbkKemkXO8WTh5n730BB3Byd5CnJGK9OOqzlUvRR6Q4nZQKsUczIMZysh5VHJ9EoNWP23NhVUf/datZ0SUJ1Lvz7MS45UGPmkuDj9U7rzVf6BIF6ClGiBPc+pCKP+i66ngSOETB0YaqIDrrygcIaFBWbSV9olTIhbBRAioeJ5DVVNsHrAG9ArjtTm0gfQBxOCuOTEd6xufqBvgYATE9P7xXP/IILLsDrXve6xz3mhBNOwB133IGHH354xc8eeeSRFZW3xN7oUTXjX/7lX9Dv9/E7v/M7T7juF7zgBQCAH//4x/93JHNVDKAoj7fXIic7mU0C/dng+pPGP0yfTUQMlptuCVQxAM/+FzU+G4x41WA3DHl0uhtQ+MADJyBpNE7FkYaSvMGGqH9hydhYcUa+O4XKWmmYYgCjdI3xxoYfJ2rf3VCbBges3+dTnIwD192O5sMF0dDzDyObPBp29n72oiwW4Xc/CuRdwPsgYqVC0su4+gfgdAqjNCb8CFXCePmg8kiNxmSiY8NXvFMHESjmhqFALI6YDTJmlRYGfyImLhvm8iQv10zuosIxUtHztQ7XSeAZWYVQT4V9JNd7tSAPuOZzGdopVcrqkKZ2owJ5eHCit0Gnh7QF5VPBzCKpP6/lv58YT85PlKyf7ET+ZGPm5A8Cm2UfJ0g3b96MzZs3P+FxZ5xxBubm5nDrrbfi+c9/PgDgu9/9Lubm5vaoG9XUo/qFX/gFALUe1Uc/+tEVx1911VU455xzVpj8rBbbt28HgLFN4olifSdz8WkkH00RiICRBzrZZGSuxGGihp6HVIe+u4H/GIMJsyS3OOJts2j4zH/oGnAM7XB1P+QE7QoYk6KCwsgrZAHP5vcf1bBNGDjyOXPkxb0oQi8BS44Va8CakYRJ1NGQkVkZWgquR9z0S6F9xVzzTo/Nhn/83Rpf9o5FuEYDqCSFFxOFDkMzFSwSVEiGcwAA0+nxdCUxfNHRBCgV9FbqZqdRtUG2DELFxqNMeUa5Aw1Aj0vZSrgqbnJRRmHsA9fjDCR53QZsA+8ZtlqWXAtHMNrCWvBwjzCTAJBlf9bMD5EBGFEeDb0HHtCK5R+WHJDoBKUjdKwF2ST2D1aLFjNfFs6D6AC3EL+HDfoA4xnPeAZe+cpX4s1vfjP+9m//FgBTE88+++wxJsvTn/50XH755fjN3/zNvdKjkvjxj3+Mb37zm/ja17624r1vueUWfOc738FLX/pS9Ho93HbbbXjHO96Bc845B8cff/xen8O6TuaAH6MQiluPhcews4n1OcIAiRLNa2GMhCpZS1NuzNm9vlWntIvKMYujVIp5176CNDgj8yUkD6sVjC+YYijNO6neZAoxPL9SFjabROHD7Xw6yfAMQsJBLRvA6/KgpFNXrQ32B0ITVQ/mQNkEQwc2BY59OtSuB+AXdgPgDVDnE9z4rYZQZRIer6CUhbc5dEiqOmDytulr6j0WkfN11rUaIoBa3rbRcxC2SZNqSDYFArUwimWJxVuswGseupxfTOTkG9c1VPGBTx6rf2sjdm5MCgdO6DAWiUlqw21Xsh660hEmI08ofZ102AxcoWcdnLIYVD5aDlq9NhUS29j3+Md//Ef84R/+YWSnnHPOOfjkJz85dszdd9+Nubm5+P3e6FEBwGc/+1kce+yxY8wXiSzL8MUvfhEf+tCHMBqN8NSnPhVvfvOb8Z73vGef1r+utVl23n8PpjZsQKFSLBYOWtW0OQDRKDk1Ch1NXPkG0wgx41WjJR4CSjuArfF15YognzqBke2ysJRSyIp5QGmU6SRrelfDyGUWd3jri7Hp0shht2l8nIyF03xbb8XqTO4aFCsxqmKRmRjpxEqMuFntguEe5UqYXfcB3sFPbwGFuxNVDEC7fgI/+whUdwpmwxYgzfl1AbijjkUBZrBIocnsGh0t5wDwHUU2gccKnlgVjryoKCqEoShgLBlH/86GuUSTdiiMlshaUbpujDYYKRGSWc5Xl7uosLGqaojKcHWtwxBYpWzUZ+8a4mZ3NYrnRdrAZ5OsTx70ZgS2498pjXzpYVCnB29zKFdgwVukuv59O9A4HJj5k6nN8v9seya6q91x7UP0vcNr/veHrTbLKrG+K3OtGBN3FKVWa6syivKko4pQaSA1HeQdzVj7YK6+RU8y+MmjQUpDF/3xIZS0C+co+EvyY6NkEv3Co5fVvGXR/iYinq4MDJqxBBTuCsikUTQKCH/ATS68bwhEKc1JznOzUAl84IpaQjbpxvX6o47hTchm0KOFAKOkwPGbYDYF+zht4XozzL7wFUZk4EHIqkHEo5V33GMwSW3nRh4FLAiORbQ0ARSw8rAprZCWXYaJRx3xkORp2c+ZtTPOUInXT/4VVUlJ8LJZBgqiCVz8Cpavl7a8h4SFOWgYm0ZpBnkfGS4U28FEK/RLj9xqZMU8KOkAVQEzYipqlvWClsvBiXVXVe1jkKMDVj08UNXFIznWdzJ3fGuulA5DOyrK3RrDgy5JGDMXDZHS5Fg0KTZMGZjFR0EmgU8neNBIpgmJFRaFDlh5wmSiuVo1FqkGCl0nLBnN9wRAKZDXgEkiZzwaKgecHUrzePpoEYm8hsAMYFhFKQ0SuEJ+DsRESDaDGhXMcU47UOUQPptA1dkQmTSjbBpJybg9pd0ah7ZsNqyKPqqki2HFWivO5JhCwSP+rmBHnbQLsXEDgFGQLRBs3OhaDx5ALYgluHlDhpbx7HCOSXACEhqiqyLbkIed1Nj5joVvCHVJI9Q05GuVhh4twaadyEiSkM0eJgUlHqqoNwmrAB9kflnNktBNuF9QZtOhQGADbR9MZpPVhrzaaOMwxLpO5so7qKKP1KZITdBYcYybViaILynAap5EVOBkM5VqkM+5+Smsi8YQjc+nApVxCBW8RSPm6z3UaBFTxgICrY8WAZuy+l6s9sOQjiu4upUGa2C9mGWOO2SSmJRIBWzYV5xYpQkKwHd6UeebhBIp8IKvGOIJE5NpscRyudpADedZeTGdiCwYSruwo0VMppOR8YNRwc5ELq152KrhxlMxEcSYGi9eAa8ANcTSqKhjozeIhkXoZXlDs/k6TaohEKtwFXBuGQITuWPnCSbMCuhiwLx7yObCcFYcUrL52IQwiBt0zQrdhH/FV7byhK5h31cWH6MDMqP4vyk8hU3wAF+jjdVjXSdzABH3pEAnhOVRbavYik3uygYVoasdkv4s/9EmHfhOb3w6M/Cao5SpK6DKAfIwLCLj/lCBGheaclJVUyOBkUn5+a7C0HSQTeRc2Ssd76cpn4Yq+vBptz4fgFk40jxNOgz/0CzUaImFwEzKQ04hKapywBBAY9NRruT/D+dBwtiRx10JNZyPA0cAuIKXiVBt+Vx9BR2mYjnpFphKcgyCfK8YVXCxq+sNodG4FMlbALVeThjYYeimvvMgVW9u8U4EiHBVrMYbZhKMpYtcbgO6kh5CaCgbIMjhhk0/sIqi1VxYK0CB9898eatr9s6g8siMxsADznvsHjpsmUiwv3Gk88qXh6Pal/dAXqON1WN9J3OqQNkEsyFkIi/wxSnhP1pjUhSeOdOl1tigLdRoEZROoCANk3S5+SiyqfK1TPsagl0T0xKVFIySlJxBUy0xVqXkoZRCQQppkMUtPAWKFsHaLhKgluCNY+0F1GA3O+kELRHkUyxhC0CMpPXSLtjF/4XrboSb3jqmLEiGG66qWIJozERGj1A3fQUbdGxUNWT8XXjhACg0LaUyd7RS0KcJswCIz43XQCQUvAdUw0d1eSING1j8DAQTD1+ySXqT1ptG4zO3qR1fiK/YyDp8hr4T7npMWmu6yAYQ/jVacY9EKJjgXgmBXYVEx90o1mk/ECZLm5baOJixzpO5j6p5kZ+cdiIkAa2DJRzQywwGVSPRuhKpLQDomMhJm1oXBWC4Qb4X6lvYOKSRJ56UUTcFCNOkzKAwFkjJo+8UoFOkYOed+YKNp8UMomNTduIph2yRlnaBwRzM0i6QzXlcXMbQi37cbCibBC08Al0sgYoBV7EN3e44fdp4TM6V0gl2LyoGQGDvAEBlcjbGBurNKSRUjRonb3qpepmyBMYSbfyowjUBwAqJVG8QYxuZr6CgxxJtbd9nQ4ldj9zH44it5KxNQYo1zhUR38GUfcB7aPI8Sat0bCTHjScED0ApEHEb1jV2KmHDiHFz4QhbumhjL0OkEg70NdpYPdZ1MifDBhGqqOl6pC2QIOCwQbtaaSRFH2k1qqu5sg9NDQ0X0TuJyTuP5hN6MAeqCihVmzfX7BQ7Xt2FJFV4ZrYMPMXJSHgEAwcOR0yddAQMK4fUKEyLpnfRB2WT8FrDTR8TdVsE+tGDOU5MJoHbfCI3WAM0EqtO8qGqN0EZMkBS2oxDFg1ZAtfpoXIEYxr1d8O9yYOTn3DKCYhQVkzgDccgMrWeeDRmbljB1YydZdi4cNSblER5D8WSwrKRUIDW+HwK7o3oFCoJWizCYy/60L4CJR1U2XQwvBg/B6m0h6E6H7LhadTnsY3CYDLRLcd8H6KFWQ5trOtkLo48/AdfK+tFGVpto2GxIhqzKCOTjiUTpDnTFcFVow+DPo4A5FNBztbFBB4dhwJ9EUBNJwy2cKVngarUSPOV2RCFo1pmNVS3VnMVKAyczKZsKBEwbeave3aszyaA4D4Ek8BnE6zsVw4C3z1gzAFH50YfN2Kjj6nAUsJdD81UafjGjWAZ5EGBrdLs+UWsvNHArPFsPUZtHDNWbmrbANDFgDce3+DTo7H5NJK6AmLzWhErTxaOkAUGjZXKP+nwHIEYl/gKqhzAaosy6a5I4p5YUKxfEhwFu7zwnj6wd4wCNuYHxpeWc2hTUxsHK9Z3MgfqatBx5SzJmt3bwzHS0EOXE4DWMXnJdGjkepNI0i4xLY/A4/nZJDBarG/JBVrxDl74zUHHvPQN4wpTD9YoMOcd4Opc6H0e7NADhIpXIwhuhaTrKxTegkwHeclc8GrTCSCw05F3gMk2YYoYA4e28AIDlUMocJNXNh1VDZmSQr42XNCGE630C3RN82uaZMtADVAnIrFbqwhQ4qkpxwfmTnNwKDYqA0yF0WJjAjRw85cZSsRhKzHtBqIRM9mcdeON5QsbNnHB0n2axvNRRT9uYKvDQho+VJBlwMbTsAzng3Y7xvsEe0rKB0uL5WAk/bWwcbQwy6GNdU2SpbRT/xGGSlwMmqWSGyFBBaYKFnmvThCuiPRBaFvj3VJdBhNhgKuxisD61kk2ppsC8qzPAqAgjUqnoDAtKlpOzjd8McPbV55gNNBJmLPNcAt/FY6YXqksFhQ3QLVih/jouDOchx7OYyrwoAtHGJpO3bANVL0IpxQDVpIUmqOwd0zKvYFwDVQTq5brLPgyGE+2VEXFQUU+VuouQEayocofrzBY+Jqx96cS7nrDBYp7FnUDlDXKhRdu48bCJs41XEPh89dBE76CZo9PY+shJbBee5VOsm5NPs1mFHKOYY3ymVvNBhvTmUZuNCrHn42G4iG0xvDKnvLLwco7B+N11kIOlE3yQL5aauKeY11X5vFjDY3P2KAsh6C0i4I0Cu9hCLDas+qd0sEX1Aac2dZUN6qNnVXZh0k7GCGJPGNrVN08C9Q5n0+xaw04cUmTrAwTqPK9UgRrdZSJ9R4oXV3limDVZGqwWDj8f7sdCMAxk1xldo3FXAkMdYacRnXSG85jMu1ioA0WS48y8OsnABRk4Miga9WKZqNy5bjSn9YgzRXsyBEAXptt8OEFK6/t3muMHABUkInlPFebJKsG3zyab0RNGQ0gTJ3KOUWMvTbyiFx0D4zp6DQ25+Y6ZchJvD7Zxo5dhbTWcbhJ7kJKz2vVSmz+CMPKowzYeWZ1Q5NFI2u55fscDgehMj8oKzkyY10nc6bOWShdD51USTfePheBveKJIkbrs4mopqhHS3DdDdGZSHBf0WXRxQBlEIQyWmHgCB1p6EllWg6ZYmfSqNw4DL+xUcU1PJ5oQJMKFSwjzUlIICIx2w/SssdM8vt2rIYa8Xv0TJDBLQfMkQ93E3q4gLy7AYVjDZHCecbYw9DLwBGIEhgPZIb5+JRPcWIPr+FtDkUeRYASTFiUNTUkwtcS0NJsBMbwdBPwf/l7TTSiBg4vtCGEFTHxxuv7WjFRKOek1HhjGmANHYmk7pFQmK2XwSCxnnOe11R6Ctee75IcAYY8VDWEMXnE/pMw959bHZ8j+jOVI3QShfwg6bG00cbBinWdzAGprnykvlWOQI2JPSkknWC5DX4xaYPS84j6lGmwJpRmNkuSQUNhbuTRTVguYOSIsdl8GghiVAjsFUcMpDpJAEAcrrGBzicWa7nRUArIjIaPeG3AzUMiSUbzUBU3dlUx4IlVbZmOKOuk2t2oYzUoSBAUjqLan/OESYvQSxjwW5GPg0+UdtkdCWzSrBW7DCmlUHhAKyZaDyvPVWojkWmhZyod+wQafL48S2THtGeY6VLVGixOfFuDv6coRFIZNtYysmPQEC+jMNnKbkQ+QjuizdLkpqdaY+TGoRFPzDYi4ZzH8+E7iVSBqa1EcOAGtdEalaZDpgO+FnDtQxmOCO4Az7Bls+w51n0yB8B/jGEgR7wnmyHwgBr14wBNHBJRnHALWCCZZDZEwXrXemkXJrIplHYShSMkhqUBIpaedqGrIQZk+BYddbJOTBh715ywiQh9RzHpcuOTE8pkIvgyJ5wysFryZIobqOThlcYjfQelAK2YxpgZi7nCgchFLH4yVKezQ4fNHYNUi5mGDFPlsUEsdzLO8/UpQ7KTXC3/RlQFiOJlsl5u4loQIW4Aoo8TLJXqD6IJt2gTmp4uQh1RAiDMDNTiYxWbb4dq3svnFyZwI/WR2HwjsmAAtqBr/B4Atfa6hwpmzAyTWYUxyd7UpKiUAoEwrHhgTCnG0g9FHOlpytGBwyRtA3TPsa6Teaz4ZJgGiCJPJkjhChaqyHMTzeaslxKhAabiLZYsIEVpt4EBM1ulIIY/ju5ajJyPAzITiQ54uYpVX2p4gpDZLbwegT1GFd+i1zCECvRFZkgUjm/ntWLVvkLkccFyBJlVEY93HijgmUmC+rFh5TCdaRgNPDZ0yIzCZGpQUcKJjoDMBGZLY7DHh2Qs1DtuhNY6JQq8KYlK4PJJUIVlG2mDejjGFpEhr+akp/xcKnFXMJQicgVVWX/mSQZKJ+CDiUjz/aUfEDXmwTRDFc4j0QqZJoAqFuUKVFEK0rtjg0hgCC1NuvCksFjw556v67+YNo7kWNe/mp6A5pRjRWESUfTEbYq0MY4P76HK/tjAilM8ok4EpFoxtTCb5uSUTTKFrawHHmTyr2N1dK8BccVqlAqVtwIqxup14JUPnUduapaIUipsCira0UlijpUjEQpP6GjeJApH4XZflAr5DsAw5oJ+yebKi4VH6QkLI4eNHQtT+YgRCxuAdd51HFX3JBP3DBXZkGi1tghzM2Hwial6bNxcJ0I5LxHeirFsElQ+C4LnSc9VfgaTgpSCjhK/bNZLijnjMDZOnxqFOIzUlNdlGQUNoLayS5WHWXiYz8ukMMFX1RPDZyLha4UhYzRs4JZ3rMbQMe+cP/+1gZmvJ2imrcwPbazrZF55HgSqTB4qY/Zv1INBEFqqG2Fy+y5uNFLVm8BwMRroVx6ZsUipQt8bWK2RuQobU43CcyPNhmraaE7IFh4FAv864BIuNMuAYHAQKG2OCGUFWM3ORcJ+AerNwAXpVa6QuRInpdk8p5F4TcDhDXHVDoS7Ai6oQQ0YBGC8W6iFCYA8QD1VWEMzrXpC5GqXYZJVNL4L56GVDkNDHk4SX+O50khsVrkI17sZkeffnKpVwQ/VWIa7VD0tSibhjdukfJch1Eal60Te9P8Mn2sm2jthWEwVfShVQY+WQl8E0DaHJ9bw6VgLgypKNSRao5soGK2b1qEHPfYnMa+n3NZi5oc21nUyz4zCSOcAAfOFR8c2mnMRm61HvX02AaUUIC42hql6xuboWh0qdEKhLAAW0q+CENdEojEoGeoQDvkIHpVSyAwncIFgEq3QDZXbgBhyUUqYElJ18zKlMh+UnGyXu9YwvTEcqxnOCUSYaF2mFILGNidmtnLj136kX6KbGBjN760AmMBNH1SMz+dGMRQRXk9rMPVSMTOGAHQ1H6MV4sallI6bgJyPVE6JxjhmLqwXoSICNT1RMG7RlQkGGSuSOBD58yxrMARlkxh4BSLDCd4JpRLhTgS1t6tnYbI4GFb2gYrtBJXSGHgbjawnE8t0yWoRNu1CKxOu6V7+cj5BrJa4DzRNracqvY2DH+s6mcNXSDRiApVESUkGVY5AWqNS7DJDRMirIY+8Kw0xOabgnZkO5+DzXmDFNAaGmJKBKV3BpAkGlcfciG8We5mBVuwXyTAGheqV0LXMBJFJQYYgQuUeHpRKMNFsw1aGNxXnHoDPS5qiSXgOUCd2FV5PKvLpTLNMa+VBZNCv2BFdQ2Eq1ZhIuLcg7JuoFdMw8DBB+IS0xagIfHry0bhZICJHvImIZZxcM6FamgbkIRF9OoGY2JvMHAmR/1VE7MOqbMDeGz0Qy45No4r7HYOKuf0JAV5z09kRUOkOBkMHozSOmt4KM/8woo4PEPj3FYxJIgup8ECmNVRZQg0X0O1uwMgh9jaEQx/Xi31LpIci6a71RO4PAszi1/pJHsZY38k84LmVpzjEUXggDaYDZGw96BK9Jced29nnk8f39eIjoM5RcJ3am1NkUMmk6PoKjxT827Q4csiNQq+h0TEMcMdkyuwRQhJxcIEpPBEoNEyLQGE0IfklwSSZqDZEaEIxXpIvUT1dGo5F0OEWnnSaAEQGHo7VGR1hUBFSA6RUwOiUWTaa4ut4ClV92MAELipDn6AeqKkTuazFhsbpir+1huhWXYGPY+UqmkWj/nmS8b+hii5dPVqvRouRiVOGja5wNVwljebSUeSXi+NUoVLk2WQ02ZahMbIpOlQCSRpF0ihU7CAPPZhDnmQgm8c7nGYcrhyznqrxFmY5tLG+k7krUHjCwsjDaoEoCFppmGySp/3Q+IUnX/tlAqympyuu+iY2ARObUJBGglq7msBj+v3Co/QKpffQCjh6IkFqFIZhtDs1KiRNrrTTNIULFRyhHnXPLSdsoxVUGM4xWoHCyL+wYqzoZYMFnkaOUIQ7ENbRViGRspiXDCYRgLlwPVygPRaeoBx/P6g80jQFAqYuabW5iQBSQXNT2GoeYe8mGimqWLXzZCtbTwg/W2Klt6eM6NcccMhnEvn9jecHXXegrsaIKDgvOVDCjWsX2ECDykOFvkRqFDJrYLSKQ1iyIWrFtMgI+YjI12iJ5QPC8JdS4e7EZhDTDlUMgKpAojQom2RGz2Hug7aprQ2JdZ3MnU5Rlb5mWRg0KstwTKiwPYFx0+F8UFB0oDChaC1L4JK2PJFZDaFdhaGdQBESJTcTubHYyw1KT5hMdYBDFCrPVmo+1GyLpY84tsi1MjdcI1UeI0EaGni3AkUOs1FcTXtwNVwL5zIMoxRQOYTRe3DiIc6HiVbYPXRwBHQTHdk3RgH9khkZG3IzVmEy1BFw/mBgLc3eRKvgsQpEWWEANphVxDaF0qsyWZrCWsvhlMgvF665HAfEZC1Hp0YBIza2ZjNqXvdS6bE4cpjM+C5JA1gYOdiw2RrNj5UeKFKCyaeDQ9OQm+Sy1qQT724MhQaoUDhFNRPg3x1XQJvaXKONJ46WzXJoY5+mH6qqwp/8yZ/gxBNPRKfTwdOe9jR8+MMfhveNiooIl156KbZt24ZOp4OXvOQl+MEPfjD2OqPRCG9/+9uxefNmTExM4JxzzsFPfvKTfV68JEgX2CVpQ4ObULMwjAIyP4TuzzJmLtQ178ZGyxUFx3ib83FgfDQP8IckzvmRh/PA3MhBKx6hl2GaVKuxhqSEMFAYEfFxjfIzoMbULerhGo1aL8SEylsokjJqXg/yMB/+0UGF1OgwEQrkRvPdglHoJjpU9fy+/cqjX/kxuAeotWKkDyGTpA46ytsaqpCiGpOPlTuRptIiv8CyRmiTXx4keEdeBT0d3qSGlQ+bhUJHUxQ0g00j5q8AjCqPofPolw6LI4fHhhU8gEFJcRCrXxHmhhXmC8cMnaYQmbGgtIPK5CzJ0N/FGvaqMWyVdpkiGRqyTqdjn+/aICqu7RB664F9He6zWLuxT8n8ox/9KD71qU/hk5/8JH70ox/hyiuvxJ/92Z/hE5/4RDzmyiuvxMc+9jF88pOfxG233YaZmRm87GUvw8LCQjzmoosuwnXXXYdrrrkG3/rWt7C4uIizzz4bzu37vk0AOkldzdrAFQfqARgCu+dQ2uFEIqJMklAat/7i8O4nj8ag4knMh5b49XqZwcaO4UqbCJUjLBYeg5AMlWpg3Z43AknqDAVwgmL2RP3nTySNRaYQFqRZ4S/gwTJYNKo4iQu0w3ohcu7M5LGadUOGjkWhlEKEoFKjkRpmumgFpIo9LTtWR511CtANMw+rCAkVjrnrBKyooGVjiIkcYYBnOcdcrnkzoYeNdBQw/ZHz8bwJQtkMz40Kizy8VQTd8dRobOokSLRGcLnDw4sF+qVDv3QYlB79wmHoPEYVnyMAUD4Np1OUJsdI5yg8ofRBPM1mwfIuuC+JEqNmeMZQNQaxtDnmiUNUNA/0q43VY59glltuuQW//uu/jrPOOgsAcMIJJ+Cf/umf8L3vfQ8AJ7g///M/x/vf/3781m/9FgDg7//+77F161Z84QtfwFve8hbMzc3hqquuwj/8wz/gV3/1VwEAn//853Hcccfhpptuwite8YoV7zsajTAajeL38/PzAOrbe6l6R0GPZOA1kvAHa8NBlSc4nSNLqro6B+K/gn8SwrSlUWGwhp/fLzl5jBxhKtUheREK5+GhMJFolgVwhMQo9EtXqwaqBlQTdEKK0LQTvXMb2CmVBxJNEfKoRPMFdePTgyK3XKpu6QsYDTjPAl5AoEkGRxxh1HRQQlWcHFNjQaHKlA3GaOafm4CLC1tIpAUgtm5BkVCuXbzzaGidxBH+5ZCLXPuwgZaOcX45T2HNCCPFqGDoHJ6TaoVHBy42qicSHT6LmgueaOC/H+0DALRW2NxNUHrC0PGX6LDzugVSAmvvGL4+Lsjfyu/BCsx/lVhPTck2jpzYp8r8RS96Eb7+9a/jf/7nfwAA//Vf/4Vvfetb+LVf+zUAwD333IOHHnoIL3/5y+NzsizDi1/8Ynz7298GANx+++0oy3LsmG3btuHZz352PGZ5XH755ej1evHruOOOiz9T4LF6UbhTikWqlFJxjFt281SDG242YxceAKocQJXDyNAwISnZso/UKEymeiyhzw1LLBRcPU4kmpuCWmGahiE5UKQYOgqyuQHPTvW42p6P7BNu3EnSLzxhbuTgfA2pDCqPyjO3fNSozDPL04kySq+hQgMviF0FyEciQjhVAVXxBilMFaFdyvspYtngRCMyewDUwz3gtbpQzcvnoZrJHIha4cubomRSVIold5MwZdmx/FkKO0b+RYDAmklUK2Bjh++W5K4o0byRDiuP/zM7QL90eLRfYFR5TKYmbriyMeuQyGVD6GoXrebIWC4CqIafCsVzC9G3dJVoE/nqceAQy4Hbzh3JsU+V+R//8R9jbm4OT3/602GMgXMOH/nIR/D6178eAPDQQw8BALZu3Tr2vK1bt+K+++6Lx6Rpig0bNqw4Rp6/PC6++GK8853vjN/Pz8/HhC5j6sPANTaKx/nJpLH5KBQ7NVqsRZwUu9WzK/0IyqZQiqmOebUEsimmjQ6TjDwin1kFoxNk4X2WSvaBTIxCX3dglIq2b1zlcsK1WsUqfHnw40CiVBziAUISJ75DcKEid6A4QCTsk1FFGMDH95FNQQaLjKrxb10NOalqC6U9QKwaqHy9KSaaoSWtgIHWPFAEfp3CA6RraMV5RJlfL6e2LJGP0RKbGDrqzUx03z3qwSbZWAkigOUjVZGhDwqfg8JSyRtf5TlBl44t3xKtMZlZ9HKmNi4WDr2ME/RUqmud+rBhaAWQCtPCAHPPkxRl5eFIwYBfU/kqYu7A6pV4W52vDEKzjb//r9HG6rFPyfyLX/wiPv/5z+MLX/gCnvWsZ2HHjh246KKLsG3bNpx//vnxuCYeDCAKGj1ePN4xWZYhy7IVj5ceSIGIr1aeq8vcplCNTz0aJAQ2Qq2vnfBgSjWCqgoYG35mLPRwAWV3EwhAVi5ic2cCS6XCrgErF2ahuZgYTvQLhQ9YOmASro67AXohYkqi0P4ANqag0N3nyljFRqZg6MOKzyvRIklbXysfzovNL7jRKxWy0bVVHcDVOFwFuAo6TL9SkgPksRTgI6MFKmKevGD0skkQCXbPVaysA6ilCPiblVzy5Tzz+BlE5UqFCvx+A/IR3xf8PQpfNWiMcgfGapUKiWVK5sKoQm414IBuYqA1yw0nRmEqM9iQGwwrrrZTpZAG6pP8uiiR2w0bh4WPGvFJEmzuRNZXTmXFb+bBTzrt5tDGE8U+JfM/+qM/wnvf+1687nWvAwCccsopuO+++3D55Zfj/PPPx8zMDACuvo855pj4vJ07d8ZqfWZmBkVRYHZ2dqw637lzJ174whfu0+IpQBCCm1aekGkdqYlye8x/BBq204OqhmybVg0DcyVjJks1ilK6fLiNr6u8Q6YJS2ARrdLXbBVX8BqcJ5QhuQk8A3DTVEIahUXAxoEap5cmZ4REPNMBI/QTJl0FE2/aCUtfgCV3VbwWpZTnglsrDcDxCLwjwE6gCDICROM0wMxoOF1ru5QBbmBtFhWkeAUGUfE8ANRDWaKLA4yzWcL1lRkAAw8dnHy8ayTW8LMVnzv4zkX0ZqSy39UvMaw8EqNiI3RjJ+HNMGw4g5JfnSdkeeNSqCUKIrYvvwe+Qqo0koTdiDJfsa562t1jcj0UifdISOTt0NChjX3CzPv9PrQef4oxJlITTzzxRMzMzODGG2+MPy+KAjfffHNM1KeddhqSJBk75sEHH8Rdd921z8lcsFYJGdwRapvgnXJE4YGRZtMJMTvWxRKzW3wVBZ/UaAmq7COnEQxV8MGSrvCEo3KDTsKwyVLJlW3pCaOK+e6buhadgPnyUFGoKsENOa1kHJzgEcbwER6TqU7BoQPWPnL1hKN4iQL1wEq17OcA69ZMJJppk1XBAy+ez2XgWAumHxI5T3AiwhwdwwqDHU1IlY+JWnBxmbiUuwutEDfQqEi5/Auoq/HAT5exeF63GHnUn6dWGKvmxVFINk9pOkv/oJcnOGYqQzcxmEwNNnYtJhKWMMgCT57hnPpaCwsnhkmZww6MTQorXyFVQdPFlXi8aNPN6tGyWQ5t7FNl/upXvxof+chHcPzxx+NZz3oWtm/fjo997GN44xvfCIBvfS+66CJcdtllOOmkk3DSSSfhsssuQ7fbxbnnngsA6PV6eNOb3oR3vetd2LRpEzZu3Ih3v/vdOOWUUyK7ZV/CE8XkOfY4EIwiMDampxVQmhy2a9ngWDBYbYOBsAZsxuYN3mPOa3SshQ4YcVMoSyugXzps6iTIjUK/IgxKwkSgkhjFyXzkWFdcYJZhVW9CHgxdsFltvVRhy0jSKRyhlwnPfPwaGK2gwnNVwMi1QmygRs9MbVHpFP2gLSOJX+maPWKEjaI0uzOFMtOGir9whCJUtUZ6FI2qvNksBDQMGrK4kph9Fa3nCDxhWwROuUThGJ8W+qIiDzLML/dBuiBBDT0BQDfcNRFkSIqv69AxdCPXVJNCblVkGFHoqYj2/VjDNVw3Ma2olIXt9Mauf4uZt7EWYp+S+Sc+8Ql84AMfwNve9jbs3LkT27Ztw1ve8hZ88IMfjMe85z3vwWAwwNve9jbMzs7i9NNPxw033ICpqal4zMc//nFYa/Ga17wGg8EAZ555Jj73uc/BGLPa2+4xRo2//nw0BzIJyqQbG2gy8l44URJUEYd1ykLlU7FihSugVO3E46eOxhIyjAoP53k4qJcxS2Yi0XDeY1ARju4mgWOuoBXfDYjpr9MUqYUiPSvY9DBk6dywyfNiSTXVEoAmgoZGJ1WROdNM7pL0JYELdszsF4FmmD1DyNFXGZwnpCExA/XAlVZ6jIYZG8QEPDJwUYUxtzzxmhteSxrUFstwjpWvYRmrVVzj2DbbYKUopWO1bzRDR3IXHZO0QETeR5hH9MUFs5fX4DsLoPQqwiasAc9QEDQn8tSowK1HFC/zFGYHCCCtYEw6hp3LdVktSbeY+d5FC7Mc2lBE6+/qzM/Po9fr4b/v/SmO3ngUHBGmLN/iyx+v4NAAYlMwD9WZJHSjwObODZqe7/Qi97nwPNY+XzCEslj4AF1wphmUHkNHER//6XzBjbbUYmOHNyahwRnN+LlRCoPKR8xWxu2nUx2hh6VAWZEkqpWKmHnR2MCIuErlc+RkZI2qpW61wnSq47QoT6vy3ULla7ldMayQuwXWSeeE+9Cgxqw7VkfsOTUsm7AY1ir6MKmp6ZfC/1+had7gqBPqRMpN3XoTMIqHj6TxWagUC4WLjeWR40nc0vPkq/QUmsweo7j3kBgVbfy6tubdiykFUBcHshEJdMQ+qPWmtKqg2BPE3iTjg52w9+b15ufnMTMzg7m5OUxPTx/Edx9/j16vhwvMU9mW8QBiRB6fdPcd0vWu1ziwK3uYIwkDN4OS8NiIjSqaFaEwSURSdilixBTH6klbbnoGRUU9mGORp/B8q/mWPNUKmzs1Hu48IjuicoTp1ODkTTlMGD4ZBKw8MllE96TyYxZzMmzTZPJMphp5g2UhEIxQDGX7NbqGSnRg2DR7CFohDsgANUVSK4UswAySyE2AWUSzXDRTcsNDOJJkFcIAlCcMXC2bK4k81YoZIQjKirSM2eIr1kPxVWOQic9fpAviDQJQV+U6xaDyGFaM9wOI+u3SiJXrLYJilec7MuGtK8VcfwMfJ1SNVmNDXDxV6nkS1wP9qubRjwI3fX8S7t48p22atnEgsa6Ftpg77HF010AXfXjdhQFi01MSgweAkNSNAnwYJrLRwMICSScmMOUKKJ0i0VyVG8UQQ9cq7B4xjxyWK9me9XiEArYMhSRIxHIF7aHByb1j2chhVNXj+UnKvHQNhcXCoROgFBVu+znZ8rk6T1g+piIa5mkjgUulG5ujDRijeT2a0l0UjtMagdceEqy2mEwRJzMdsWG0oSroxFO0UUtCIjcKQBgEWkE1beqYB/lioK7M43lRo6rUFmQtBoH7nhoWNds1EJ9WvivQiiEWNh8Jd14a0VAiNfWGCl+ysUXaRUkMxSFU9cOK4S6WcWfaJoE3i4WRw1G5QavEsn/RwiyHNtZ1Mp/KDDppsIFLu1gMHpgatU8mIJV4kIwldo8vHDH/WvDhJAfZNFaO1lXom040j/BEWCqBhcJhMjHoZTx00ncGR+ecee+ZKzE3LJFojcxqOKuRW9HTJhSNHNCcHxIoReiORDVmLL+8OlTGDvXPPAiTIdPWcIV8xymn8nX1Ov66PGgVFRg967GkRgU6oI663hIh5wHkx6Y+he/tCNGcWqrs+sl1Q5EazU+BMkah+cjSAeH8CNCaKYFifm0UUDTeO7Oa2ZfEb5oZ3lCFgpgGvRonzU+AP/NwN2agkFjVmLIl9MOAVxVgmTJcm6nMYCJZ1zezhzU8Hbhqom9z+R5jXf9mmlCVUhBqSkMiFyYLhSZd3mh2yR9mZtSYi3uk1AGAZtOCJAycyLi7QB+DymN25LBUengi9B0zWYQKmYWRdGFQiBmzqPgRMfQh8rI8ps8CWtLQlByqoSDCskulj+PzlefzTYM2C09kslmEVKHyuswh5/+PqlqwC0Dkix+VmSjaRarWW/HgjSTRCkdlGpYaUrXLQgSyeMCpdktSAES3vEn3M4phGKDG74lqtUnrhtDVEClYBXEUqIwaCpnV6OUGaegRCLe/k2h0rcZROY/551ZHaG1h5DFf8KZSmhyPjfg6LpUei4WPCf3RfonFgpUYB6VHFd538gAS+d7U8ge73l9r9w9rfZx/dnYW5513XpQNOe+887B79+7Hfc61116LV7ziFdi8eTOUUtixY8eKY/ZGJXZ/3nt5rOtkPgiTfI446SyVvh4JV2ya4IirPzFZcJ6wUHoMGtzspn42acvTkuDnCabcsZxSN+Y2biKSvAVrlao3MSpUdpy4ByVFWpwNa8sDD1ywXFEylOBNiBufDWVfpht6GTIKeDoQNUaAmtYIID7fU63AWDZ47M7XphgiatWEqDqa0DU8Oi9VOSkdk3y0wiMREqspmKJaGUf8lw8OoR4MsvBMjWxg2pL8xQiDPweFo3LDmjmBGTSVMo881WLfh2hdV3oeLloqWcirYxVmXYrHBg5zI5YLfmzg8NBSgUf6JXYulbh39wBLheOJ1Irx9IkgVrY/sbeNzRYzP7xx7rnnYseOHbj++utx/fXXY8eOHTjvvPMe9zlLS0v4pV/6JVxxxRV7PGZvVGL3572Xx7qEWeTW/+HH5hoj5YE3POD/N6dCreYhGCiNuZGPCTqzGh1ba4FoJQ23CsotoUw68ARMKI/5kWp4TXr0KWiXg6tLMT4+Sin0FwcYqVpTBagbdLE5qxUwqvH1Zp5IjYIPiWlUMWPDB9pcv/SYH1aYzi1GiYIbaGjNFmlSCWtV89YdCKlSsaHLtnWI55xohVFDSMtqhqEUeahiAOUdfD5Zj9H7CiMyEYsXbrpSNXtEClipyJfrtfAPdRyLV01eOxq8cptHo4zMKJYcLj0yqyNdU6va8Lp0HonREUaT6yxuRI6APoDHhlWcwBX+vys9BhX/cU3DY9fuEvcXFTZ1Ehw9maBUFo8/KrT+QgFRmvrJILUNMD5LsD9RhE6PKKdK7EnyY2/jRz/6Ea6//np85zvfwemnnw4A+PSnP40zzjgDd999N04++eRVnycJ9957713153ujEru/770iaB3GAw88QODCo/1qv9qvg/D1wAMPHLK/18FgQDMzMwdtrZOTkyseu+SSSw5ojVdddRX1er0Vj/d6PfrsZz/7hM+/5557CABt37597PGvf/3rBIAee+yxscdPPfVU+uAHP3hQ3ltiXVbm27Ztww9/+EM885nPxAMPPLAu+Kai9Niu99DFelvzWlgvEWFhYQHbtm07ZO+R5znuueceFMWeZYP3JYhWMqUOpCoHWE9qy5YtKx7fsmXLHtVc9/Z1n0gl9mC997pM5lprHHvssQCA6enpdfGHK9Gu99DHelvz4V5vr9c75O+R5znyPD/k77M8Lr30UnzoQx963GNuu+02ACvVXoHVN46DEctf92C897pM5m200UYbexMXXHBBVHndU5xwwgm444478PDDD6/42SOPPLLCn2FfYm9UYmdmZg7Ke7fJvI022jhiY/Pmzdi8efMTHnfGGWdgbm4Ot956K57//OcDAL773e9ibm5un9Vcm9FUiX3Na14DoFaJvfLKKw/ue+81ur7GYjgc0iWXXELD4fBwL2Wvol3voY/1tub1tt4jPV75ylfSqaeeSrfccgvdcsstdMopp9DZZ589dszJJ59M1157bfx+165dtH37dvrqV79KAOiaa66h7du304MPPhiPeetb30pPecpT6KabbqLvf//79Cu/8iv0nOc8h6qq2qf3fqJYt8m8jTbaaONgxq5du+gNb3gDTU1N0dTUFL3hDW+g2dnZsWMA0NVXXx2/v/rqq1dl3DTZNYPBgC644ALauHEjdTodOvvss+n+++/f5/d+oliXqolttNFGG22Mx7qeAG2jjTbaaIOjTeZttNFGG0dAtMm8jTbaaOMIiDaZt9FGG20cAbEuk/lf//Vf48QTT0Se5zjttNPwn//5n4dlHd/85jfx6le/Gtu2bYNSCl/+8pfHfk5EuPTSS7Ft2zZ0Oh285CUvwQ9+8IOxY/ZGHvNgxeWXX45f/MVfxNTUFLZs2YLf+I3fwN13372m1/w3f/M3OPXUU+OU5BlnnIF/+7d/W7PrXR6XX355NDpfL2tuY53GPnFf1kBcc801lCQJffrTn6Yf/vCHdOGFF9LExATdd999T/pavva1r9H73/9++tKXvkQA6Lrrrhv7+RVXXEFTU1P0pS99ie6880567WtfS8cccwzNz8/HY9761rfSscceSzfeeCN9//vfp5e+9KUrOKgHK17xilfQ1VdfTXfddRft2LGDzjrrLDr++ONpcXFxza75K1/5Cn31q1+lu+++m+6++2563/veR0mS0F133bUm19uMW2+9lU444QQ69dRT6cILL4yPr+U1t7F+Y90l8+c///n01re+deyxpz/96fTe9773MK2IY3ky997TzMwMXXHFFfGx4XBIvV6PPvWpTxER0e7duylJErrmmmviMT/96U9Ja03XX3/9IV/zzp07CQDdfPPN62bNREQbNmygz3zmM2t6vQsLC3TSSSfRjTfeSC9+8YtjMl/La25jfce6glmKosDtt9+Ol7/85WOPv/zlL8e3v/3tw7Sq1eOee+7BQw89NLbWLMvw4he/OK719ttvR1mWY8ds27YNz372s5+U85mbmwMAbNy4cV2s2TmHa665BktLSzjjjDPW9Hr/4A/+AGeddVbUsJZYy2tuY33HutJmefTRR+GcWyE+05STXCsh61ltrffdd1885onkMQ9VEBHe+c534kUvehGe/exnr+k133nnnTjjjDMwHA4xOTmJ6667Ds985jNjYltr673mmmvw/e9/P6rxNWOtXuM21n+sq2QusVwWkg6RTOXBiP1Z65NxPhdccAHuuOMOfOtb31rxs7W25pNPPhk7duzA7t278aUvfQnnn38+br755jW53gceeAAXXnghbrjhhseVfF1La27jyIh1BbNs3rwZxpgV1cnOnTsPSKbyUMTMzAwAPO5am/KYezrmUMTb3/52fOUrX8E3vvENPOUpT1nza07TFD/7sz+L5z3vebj88svxnOc8B3/xF3+xJtd7++23Y+fOnTjttNNgrYW1FjfffDP+8i//Etba+J5rac1tHBmxrpJ5mqY47bTTcOONN449fuONNx6QTOWhiBNPPBEzMzNjay2KAjfffHNca1MeU0LkMQ/F+RARLrjgAlx77bX493//d5x44olrfs17Oo/RaLQm13vmmWfizjvvxI4dO+LX8573PLzhDW/Ajh078LSnPW3NrbmNIyQOT991/0OoiVdddRX98Ic/pIsuuogmJibo3nvvfdLXsrCwQNu3b6ft27cTAPrYxz5G27dvjzTJK664gnq9Hl177bV055130utf//pVKWhPJI95sOL3f//3qdfr0X/8x3/Qgw8+GL/6/X48Zq2t+eKLL6ZvfvObdM8999Add9xB73vf+0hrTTfccMOaXO9q0WSzrJc1t7H+Yt0lcyKiv/qrv6KnPvWplKYpPfe5z43Uuic7vvGNb6wqf3n++ecTEdPQLrnkEpqZmaEsy+iXf/mX6c477xx7jb2RxzxYsdpasUzSc62t+Y1vfGP8rI8++mg688wzYyJfi+tdLZYn8/Ww5jbWX7QSuG200UYbR0CsK8y8jTbaaKON1aNN5m200UYbR0C0ybyNNtpo4wiINpm30UYbbRwB0SbzNtpoo40jINpk3kYbbbRxBESbzNtoo402joBok3kbbbTRxhEQbTJvo4022jgCok3mbbTRRhtHQLTJvI022mjjCIj/H/s0yv7CYDOWAAAAAElFTkSuQmCC\n", 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\n", 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\n", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "id": "2a892c1c-ebb9-4569-833c-fd3613482386", + "metadata": { + "tags": [] + }, + "outputs": [], "source": [ - "\n", - "loclen = len(pointnames)\n", - "print(pointnames)\n", - "dispdiff = np.zeros((loclen,loclen)) #displacement difference\n", - "subsetstr = '[7620213:7686754, 641941:679925]'\n", - "\n", - "for k in range(loclen):\n", - " print(f'\\n\\n\\n NOW DOING: {pointnames[k]}\\n')\n", - " \n", - " #redo ref point, rerun mintpy\n", - " refptstr = f'{pointlocsxy[k][1]}, {pointlocsxy[k][0]}'\n", - " writenumpyconfig(config_file,hyp3_dir,reflalo = refptstr, subset = subsetstr)\n", - " if k==0:\n", - " !smallbaselineApp.py --dir {work_dir} {config_file}\n", - " else:\n", - " !smallbaselineApp.py --dir {work_dir} {config_file} --dostep reference_point\n", - " !smallbaselineApp.py --dir {work_dir} {config_file} --dostep invert_network\n", - "\n", - " #redo spline reconstruction\n", - " print('\\n performing spline reconstruction')\n", - " ts = pu.Timeseries.from_file(fn = work_dir/timeseries_filename)\n", - " sm = pu.SplineModel(dates_o=ts.dates)\n", + "#Retrieve InSAR displacment differences between points\n", + "locdisp = []\n", + "for k,name in enumerate(pointnames):\n", " ts_rec = sm.reconstruct(timeseries=ts,dates_r=fielddates[k])\n", - " \n", - " for l in range(loclen):\n", - " ipt,jpt = pointsubsetlocs[l]\n", - " print(f'{ipt}, {jpt}')\n", - " dispdiff[k,l] = ts_rec.timeseries[1,ipt,jpt] - ts_rec.timeseries[0,ipt,jpt]\n", - " # dispdiff[k,l]=refdisp - (ts_rec.timeseries[1,ipt,jpt]-ts_rec.timeseries[0,ipt,jpt])\n", - " \n", - " plt.figure()\n", - " plt.imshow(ts_rec.timeseries[1]-ts_rec.timeseries[0],cmap='RdBu',vmin=-0.1,vmax=0.1)\n", - " plt.colorbar()\n", - " \n", - "print(dispdiff)" + " ipt,jpt = pointsubsetlocs[k]\n", + " locdisp.append(ts_rec.timeseries[-1,ipt,jpt])" ] }, { "cell_type": "markdown", - "id": "31911dc9-dd68-4b83-95d8-345889454f40", - "metadata": {}, + "id": "a587409a-d070-4339-b4f6-2872d1d8ef9a", + "metadata": { + "tags": [] + }, "source": [ - " \n", - "## 5.4 Evaluate displacements to NISAR permafrost requirement\n", - "\n", - "Step 1: identify distances between field sites." + "Next we compare the double difference of displacement between each subsite pair from InSAR and field data" ] }, { "cell_type": "code", - "execution_count": 40, - "id": "161a8c76-3ee6-4ee7-8de3-688d2f408b45", - "metadata": {}, + "execution_count": null, + "id": "8dc827d0-4ab8-4375-a4fa-d84facc56daa", + "metadata": { + "tags": [] + }, "outputs": [], "source": [ - "#Identify distances\n", - "__,atrib = readfile.read(work_dir/timeseries_filename) #note data could be large, and will soon be replaced with data\n", + "__,atrib = readfile.read(Path(mintpy_dir)/timeseries_filename) \n", "xst = float(atrib['X_STEP'])\n", "yst = float(atrib['Y_STEP'])\n", "\n", - "loclen = len(pointnames)\n", - "dist = np.zeros((loclen,loclen)) #distance, will be in km\n", + "dispdiff = []\n", + "obsdiff = []\n", + "obserr = []\n", + "ddf = []\n", + "dist = []\n", + "\n", + "locvec = locdisp\n", + "loclen = len(locdisp)\n", + "\n", "for k in range(loclen):\n", - " iref,jref = pointlocs[k]\n", - " for l in range(loclen):\n", - " ipt,jpt = pointlocs[l]\n", - " dist[k,l] = np.sqrt(((iref-ipt)*yst)**2+((jref-jpt)*xst)**2)/1e3\n" + " iref,jref = pointsubsetlocs[k]\n", + " for l in range(k+1,loclen): \n", + " ipt,jpt = pointsubsetlocs[l]\n", + " dispdiff.append(locvec[k]-locvec[l]) #insar displacement difference\n", + " obsdiff.append(obsdisp[k]-obsdisp[l]) #field data displacement difference\n", + " obserr.append(np.sqrt(obsstd[k]**2+obsstd[l]**2))\n", + " ddf.append(np.abs(np.abs(dispdiff[-1])-np.abs(obsdiff[-1])))\n", + " dist.append(np.sqrt(((iref-ipt)*yst)**2+((jref-jpt)*xst)**2)/1e3)" ] }, { "cell_type": "markdown", - "id": "c09a91a8-acab-450f-9d0b-cb3ba7d617ca", + "id": "31911dc9-dd68-4b83-95d8-345889454f40", "metadata": {}, "source": [ - "Step 2: compare the relative displacements to the requirement." + " \n", + "## 4.4 Evaluate displacements to NISAR permafrost requirement\n", + "\n", + "### 4.4.1 Compute requirement validation evaluation" ] }, { "cell_type": "code", "execution_count": null, - "id": "45b175e0-3934-4b76-9369-82496092294e", - "metadata": {}, + "id": "d02fcd3c-cc61-438a-bcb9-5636502cc495", + "metadata": { + "tags": [] + }, "outputs": [], "source": [ - "insvec = dispdiff.flatten()*100 #make sure in cm\n", - "obsvec = obsdiff.flatten()*100 #make sure in cm\n", - "ddfvec = np.abs(insvec-obsvec) #absolute difference in cm\n", - "stdvec = obsdiffstd.flatten()*100 #standard deviation of observations in cm\n", - "distvec = dist.flatten() #make sure in km\n", - "reqvec = 4*(1+np.sqrt(distvec))/10 #requirement in cm\n", - "\n", - "locvec = []\n", - "for i in range(4):\n", - " cpoint = pointnames[i]\n", - " for j in range(4):\n", - " locvec.append(f'{cpoint}_{pointnames[j]}')\n", - "locvec = np.array(locvec)\n", - "\n", - "succvec = np.array(ddfvec <= reqvec)\n", - "maskvec = np.zeros_like(succvec)\n", - "maskvec[np.isnan(ddfvec)]=True\n", - "maskvec[ddfvec==0]=True\n", - "\n", - "abs_ddiff_disp = ddfvec\n", - "abs_ddiff_disp[maskvec]=np.nan\n", - "\n", - "req_met_rate = np.sum(succvec[~maskvec])/np.sum(~maskvec)\n", - "req_within_error = np.array(ddfvec-stdvec <= reqvec)\n", - "req_within_error_rate = np.sum(req_within_error[~maskvec])/np.sum(~maskvec)" + "ddf_cm = np.array(ddf)*100 #double difference in cm\n", + "obserr_cm = np.array(obserr)*100 #observation error in cm\n", + "dist = np.array(dist) #distance (in km)\n", + "reqvec = 4*(1+np.sqrt(dist))/10 #requirement in cm\n", + "\n", + "#remove HVE in 2023, and SM in 2024\n", + "sitemask = np.array([1,1,1,1,1,1],dtype='bool')\n", + "if year == 2023:\n", + " sitemask = np.array([0, 1, 1, 0, 0, 1],dtype='bool')\n", + "if year == 2024:\n", + " sitemask = np.array([1, 1, 0, 1, 0, 0],dtype='bool')\n", + "ddf_cm = ddf_cm[sitemask]\n", + "obserr_cm = obserr_cm[sitemask]\n", + "dist = dist[sitemask]\n", + "reqvec = reqvec[sitemask]\n", + "\n", + "succvec = np.array(ddf_cm <= reqvec)\n", + "succerr = np.array(ddf_cm-obserr_cm <= reqvec)\n", + "req_met_rate = np.sum(succvec)/len(succvec)\n", + "req_within_MOE = np.sum(succerr)/len(succerr)" ] }, { "cell_type": "markdown", - "id": "13d977bc-9ed5-411b-8d42-c8785908568b", - "metadata": {}, + "id": "4bc17fb4-eda7-43b5-9780-4fc99841b2f0", + "metadata": { + "scrolled": true, + "tags": [] + }, "source": [ - "Finally we plot this." + "## 4.4.2 Visualize validation results" ] }, { "cell_type": "code", "execution_count": null, - "id": "edcb3a1f-431b-4beb-a538-592c82ce204c", - "metadata": {}, + "id": "1696528b-dae4-45e1-8271-063e16cd1b09", + "metadata": { + "tags": [] + }, "outputs": [], "source": [ - "print(f\"Percent of double differences which meet the requirement: {req_met_rate*100:.1f}%\")\n", - "print(f\"Percent of double differences within margin of error of requirement: {req_within_error_rate*100:.1f}%\")\n", + "import matplotlib.patches as patches\n", + "\n", + "req_thresh = 0.8\n", + "val, val_MOE = False,False\n", + "val_str, val_MOE_str = 'FAILED','FAILED'\n", + "if req_met_rate>=req_thresh:\n", + " val = True\n", + " val_str = 'PASSED'\n", + "if req_within_MOE >= req_thresh:\n", + " val_MOE = True\n", + " val_MOE_str='PASSED'\n", + "\n", + "\n", + "print(f\"Percent of double differences which meet the requirement: \\\n", + "{req_met_rate*100:.1f}%, validation: {val_str}\")\n", + "print(f\"Percent of double differences within margin of error of requirement: \\\n", + "{req_within_MOE*100:.1f}%, validation: {val_MOE_str}\")\n", "\n", "dist_th = np.linspace(0.1,50,100) # distances for evaluation\n", "acpt_error = 4*(1+np.sqrt(dist_th)) # permafrost threshold in mm\n", "acpt_error_cm = acpt_error/10.\n", - "# abs_ddiff_disp = [abs(i) for i in diff_res_list1]\n", - "start_date = fielddates[0][0]\n", - "end_date = fielddates[0][1]\n", - "# print(len(dist))\n", + "start_date = np.min(fielddates)\n", + "end_date = np.max(fielddates)\n", "\n", "fig, ax = plt.subplots(figsize=(11,7))\n", - "plt.scatter(dist,abs_ddiff_disp,label='|$D_{obs} - D_{InSAR}|$ for pair')\n", + "plt.scatter(dist,ddf_cm,label='|$D_{obs} - D_{InSAR}|$ for pair')\n", "plt.plot(dist_th, acpt_error_cm, 'r',label='Permafrost requirement')\n", - "plt.ylim(0,10)\n", + "# ax.set_xscale('log')\n", + "plt.ylim(0,7)\n", "plt.xlim(0,50)\n", "plt.legend(loc='upper left')\n", - "plt.title(f\"Double-Difference Residuals \\n Date range {start_date.strftime('%Y-%m-%d')} to {end_date.strftime('%Y-%m-%d')} \\n InSAR and surveying/GNSS simple subtraction displacement\")\n", + "plt.title(f\"Double-Difference Residuals \\n Date range \\\n", + "{start_date.strftime('%Y-%m-%d')} to {end_date.strftime('%Y-%m-%d')} \\n InSAR\\\n", + "and surveying/GNSS simple subtraction displacement\")\n", "plt.xlabel(\"Distance (km)\")\n", "plt.ylabel(\"Amplitude of Double-Differenced Displacement Residual (cm)\")\n", - "plt.errorbar(distvec,abs_ddiff_disp,yerr=stdvec,ls='none',capsize=5)\n", - "plt.show()" + "plt.errorbar(dist,ddf_cm,yerr=obserr_cm,ls='none',capsize=5)\n", + "\n", + "\n", + "# Add legend with validation info \n", + "textstr = f'Permafrost requirement\\n'\n", + "textstr += f'Site: NorthSlopeEast\\n'\n", + "# if validation.loc['Total']['success_fail']:\n", + "if val:\n", + " validation_color = '#239d23'\n", + "else:\n", + " validation_color = '#bc2e2e'\n", + "\n", + "\n", + "props = {**{'facecolor':'none', 'edgecolor':'none'}}\n", + "ax.text(37, 6.15, textstr, fontsize=12)#, bbox=props)\n", + "ax.text(39, 6.05, val_str, fontsize=16, weight='bold')\n", + "\n", + "rect = patches.Rectangle((36.5, 5.95), 12.5, 0.9,\n", + " linewidth=1, edgecolor='black',\n", + " facecolor=validation_color)\n", + "ax.add_patch(rect)\n", + "\n", + "plt.show()\n" + ] + }, + { + "cell_type": "markdown", + "id": "b91ebd91-44e5-45a6-9194-cf61d247d8a1", + "metadata": { + "tags": [] + }, + "source": [ + "### 4.4.3 Prepare validation table" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f72df4f3-75f6-4cce-91ce-5ebc7140510b", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# validation\n", + "req_thresh = 0.8\n", + "\n", + "count = np.array([np.size(i) for i in ddf_cm])\n", + "passed = np.array([np.sum(i) for i in succvec])\n", + "passed_within_MOE = np.array([np.sum(i) for i in succerr])\n", + "success = passed/count >= req_thresh\n", + "success_within_MOE = passed_within_MOE/count >= req_thresh\n", + "\n", + "columns = ['distance[km]', 'count', 'passed',\n", + " 'within_MOE', 'success', 'success_within_MOE']\n", + "\n", + "validation = pd.DataFrame(np.vstack([dist,\n", + " count,\n", + " passed,\n", + " passed_within_MOE,\n", + " success,\n", + " success_within_MOE],dtype=object).T,\n", + " columns = columns)\n", + "\n", + "sumrow = ['Total',\n", + " np.sum(count),\n", + " np.sum(passed),\n", + " np.sum(passed_within_MOE),\n", + " np.sum(passed)/np.sum(count) >= req_thresh,\n", + " np.sum(passed_within_MOE)/np.sum(count) >= req_thresh]\n", + "validation = pd.concat([validation, pd.DataFrame([sumrow],columns = columns)],ignore_index=True)\n", + "if validation.loc[validation.index[-1]]['success']:\n", + " print(\"This displacement dataset passes the requirement.\")\n", + "else:\n", + " print(\"This displacement dataset does not pass the requirement.\")\n", + "if validation.loc[validation.index[-1]]['success_within_MOE']:\n", + " print(\"This displacement dataset passes the requirement within the field measurement margin of error.\")\n", + "validation" + ] + }, + { + "cell_type": "markdown", + "id": "70523831-9dc7-46de-86c1-6863bc76eb67", + "metadata": { + "tags": [] + }, + "source": [ + "
\n", + "Validation Method 1: success for a baseline distance bin occurs when the percentage of residuals within the requirement success threshold is >0.8\n", + "
" + ] + }, + { + "cell_type": "markdown", + "id": "d9ac4b93-056e-4ea1-bf9a-e2abcdb25ca2", + "metadata": { + "tags": [] + }, + "source": [ + "### 4.4.4 Save Validation results" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "37baa020-0c74-4163-af01-5bfe3cb0b103", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Save Method 1 results to file\n", + "run_date = dt.now().strftime('%Y%m%dT%H%M%S')\n", + "save_fldr = f\"{run_date}-Permafrost-Method1\"\n", + "# save_dir = os.path.join(mintpy_dir, save_fldr)\n", + "save_dir = str(Path.home()/'stash') #set your own location\n", + "\n", + "validation_fig_method1 = fig\n", + "validation_table_method1 = validation\n", + "\n", + "save_params = {\n", + " 'save_dir': save_dir,\n", + " 'run_date': run_date,\n", + " 'requirement': \"Permafrost\",\n", + " 'site': site,\n", + " 'method': \"1\",\n", + " 'sitedata': site_info,\n", + " 'gnss_insar_figs': [],\n", + " 'validation_figs': [validation_fig_method1],\n", + " 'validation_table': validation_table_method1,\n", + " 'ts_functions': None,\n", + "}\n", + "save_results(**save_params)" + ] + }, + { + "cell_type": "markdown", + "id": "40b8c61d-4935-49ee-a661-6fe588f8f8f6", + "metadata": {}, + "source": [ + "\n", + "# 5. Validation Method 2: InSAR-only structure fucntions\n", + "\n", + "The NISAR permafrost validation requirement states that at least 80% of the time, the difference in surface displacement for two given points over 90 days should be no greater than $4(1+\\sqrt{\\text{L}})$ mm for points of L km apart, with $\\text{L} \\leq 50$ km.\n", + "\n", + "The surface deformation across tundra permafrost will vary spatially due to multiple mechanisms, including soil type, excess surface ice, and local topography and climate. Variability occurs at spatial scales from centimeters to tens of kilometers. Nonetheless, we will evaluate the differences in surface displacement relative to the validation requirement using the InSAR signal alone over this terrain." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "481d32f3-656e-4133-b2e8-374ed70defe0", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "#Permafrost requirements:\n", + "dist_th = np.linspace(0.1,50,100) # distances for evaluation (km)\n", + "acpt_error = 4*(1+np.sqrt(dist_th)) # permafrost threshold in mm, for dist in km\n", + "acpt_error_cm = acpt_error/10. #cm" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9a624d4f-df59-46d6-8969-f14e2d4a60e9", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "#show displacements at end of the timeseries\n", + "if 'timeseries_filename' not in locals():\n", + " timeseries_filename = 'timeseries.h5'\n", + "\n", + "with h5py.File(Path(mintpy_dir)/timeseries_filename, 'r') as f:\n", + " dispmap = np.array(f['timeseries'][-1])*100\n", + "\n", + "vmax = np.nanmax(np.abs(dispmap))\n", + "plt.figure()\n", + "plt.imshow(dispmap,vmin=-vmax,vmax=vmax,cmap='RdBu')\n", + "plt.colorbar(label='96 day displacement (cm)')" + ] + }, + { + "cell_type": "markdown", + "id": "4a6c472a-ab64-47d4-96ec-27eaa7a1dfef", + "metadata": {}, + "source": [ + "\n", + "## 5.1 Use structure functions to identify pixel pairs\n", + "\n", + "We sample a large set of pixel pairs to compare relative displacements with. We use a water mask from the Hyp3 processing to mask out locations to not use. Information about how that water mask is developed can [be found here](https://storymaps.arcgis.com/stories/485916be1b1d46889aa436794b5633cb)." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e42a677f-901e-49c1-a027-855795c4a0a1", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "__,atrib = readfile.read(Path(mintpy_dir)/timeseries_filename)\n", + "\n", + "X0,Y0 = load_geo_utm(atrib)\n", + "X0_2d,Y0_2d = np.meshgrid(X0,Y0)\n", + "\n", + "M2dist = []; rel_measure = []\n", + "\n", + "tsmap = dispmap\n", + "tsmap[tsmap==0]=np.nan\n", + "\n", + "# wmask = pu.get_watermask(Path(gunw_dir))\n", + "with h5py.File(Path(mintpy_dir)/'waterMask.h5') as data:\n", + " wmask = data['waterMask'][:]\n", + "tsmap[wmask==0]=np.nan\n", + "\n", + "#deramping will remove linear spatial trends in the displacement data.\n", + "#Currently disabled\n", + "dist_i, rel_measure_i = samp_pair(X0_2d,Y0_2d,tsmap,num_samples=1000000,deramp=False)\n", + "\n", + "M2dist.append(dist_i) #distance of pair, in m\n", + "rel_measure.append(rel_measure_i) #relative displacement of pair, in cm \n", + " \n", + "M2dist,rel_measure = np.array(M2dist),np.array(rel_measure)\n", + "\n", + "#use only pixel pairs within 50 km\n", + "rel_measure = rel_measure[M2dist<=50e3]\n", + "M2dist=M2dist[M2dist<=50e3]\n", + "\n", + "M2km = [i/1e3 for i in M2dist] #convert distance to km\n", + "rmcm = [i for i in rel_measure] #relative measure in cm\n", + "\n", + "fig, ax = plt.subplots(figsize=[9, 5.5])\n", + "img1 = ax.hist(M2km, bins=100)\n", + "ax.set_title(f\"Histogram of distance\")\n", + "ax.set_xlabel(r'Distance ($km$)')\n", + "ax.set_ylabel('Frequency')\n", + "\n", + "fig, ax = plt.subplots(figsize=[9, 5.5])\n", + "img1 = ax.hist(rmcm, bins=100)\n", + "ax.set_title(f\"Histogram of Relative Measurement\")\n", + "ax.set_xlabel(r'Relative Measurement ($cm$)')\n", + "ax.set_ylabel('Frequency')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cefe2464-e4f4-4dcd-bcaf-5a8b2732039b", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "start_date = dt.strptime(atrib['START_DATE'], '%Y%m%d')\n", + "end_date = dt.strptime(atrib['END_DATE'], '%Y%m%d')\n", + "start_str = start_date.strftime('%Y-%m-%d')\n", + "end_str = end_date.strftime('%Y-%m-%d')\n", + "\n", + "# Define requirement\n", + "permafrost_threshold_rqmt = 4 # mm/yr\n", + "permafrost_distance_rqmt = [0.1, 50.0] # km\n", + "\n", + "# Validation parameters\n", + "n_bins = 10\n", + "# threshold = 0.683 \n", + "threshold = 0.8\n", + "\n", + "pair_distance = np.array([i/1e3 for i in dist_i])\n", + "pair_difference = np.array([i*10 for i in rel_measure_i])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "fe837b49-80d2-40b7-80cc-a19e3fb6fd3a", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "validation_table,fig = display_permafrost_validation(pair_distance, # binned distance for point\n", + " pair_difference, # binned relative velocities mm/yr\n", + " site,\n", + " start_str,\n", + " end_str,\n", + " requirement=permafrost_threshold_rqmt,\n", + " req_dist_fcn=True,\n", + " distance_rqmt = permafrost_distance_rqmt, # [0.1, 50] km\n", + " n_bins=n_bins, # number of bins, to collect statistics \n", + " threshold=threshold, \n", + " sensor='Sentinel-1', # sensor that is validated, Sentinel-1 or NISAR\n", + " validation_type='permafrost',\n", + " validation_data='Field meas') " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8e8d7949-39fd-4204-a8de-e2092d52fcd7", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "req_dist_fcn = True\n", + "reqval = 4\n", + "pair_req_met = np.array(pair_difference < reqval*(1+float(req_dist_fcn)*\n", + " np.sqrt(pair_distance)))\n", + "pair_req_met[np.isnan(pair_difference)]=np.nan\n", + "df = pd.DataFrame(np.vstack([pair_distance,\n", + " pair_difference,\n", + " pair_req_met]).T,\n", + " columns=['distance', 'double_diff','req_met'])\n", + "\n", + "# remove nans\n", + "df_nonan = df.dropna(subset=['double_diff'])\n", + "bins = np.linspace(*permafrost_distance_rqmt, num=n_bins+1)\n", + "bin_centers = (bins[:-1] + bins[1:]) / 2\n", + "binned_df = df_nonan.groupby(pd.cut(df_nonan['distance'], bins),\n", + " observed=False)[['req_met']]\n", + "\n", + "# get binned validation table \n", + "bin_req = reqval*(1+float(req_dist_fcn)*np.sqrt(bin_centers))\n", + "validation = pd.DataFrame([])\n", + "validation['total_count[#]'] = binned_df.apply(lambda x: np.ma.masked_invalid(x)\n", + " .count())\n", + "validation['passed_req.[#]'] = binned_df.apply(lambda x: np.count_nonzero(x))\n", + "\n", + "# Add total at the end\n", + "validation = pd.concat([validation, pd.DataFrame(validation.sum(axis=0)).T])\n", + "validation['passed_pc'] = validation['passed_req.[#]'] / validation['total_count[#]']\n", + "validation['success_fail'] = validation['passed_pc'] > threshold\n", + "validation.index.name = 'distance[km]'\n", + "# Rename last row\n", + "validation.rename({validation.iloc[-1].name:'Total'}, inplace=True)\n", + "if validation.loc[validation.index[-1]]['success_fail']:\n", + " print(\"This displacement dataset passes the requirement.\")\n", + "else:\n", + " print(\"This displacement dataset does not pass the requirement.\")\n", + "validation" + ] + }, + { + "cell_type": "markdown", + "id": "3a806207-7f08-4d8e-ba6c-aefcf60acfd5", + "metadata": { + "tags": [] + }, + "source": [ + "
\n", + "Validation Method 1: success for a baseline distance bin occurs when the percentage of residuals within the requirement success threshold is >0.8\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "70d7dc97-53a6-4d09-91ac-eae6f65dacf8", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Save Method 2 results to file\n", + "run_date = dt.now().strftime('%Y%m%dT%H%M%S')\n", + "save_fldr = f\"{run_date}-Permafrost-Method2\"\n", + "save_dir = str(Path.home()/'stash') #set your own location\n", + "\n", + "validation_fig_method2 = fig\n", + "validation_table_method2 = validation\n", + "\n", + "save_params = {\n", + " 'save_dir': save_dir,\n", + " 'run_date': run_date,\n", + " 'requirement': \"Permafrost\",\n", + " 'site': site,\n", + " 'method': \"2\",\n", + " 'sitedata': site_info,\n", + " 'gnss_insar_figs': [],\n", + " 'validation_figs': [validation_fig_method2],\n", + " 'validation_table': validation_table_method2,\n", + " 'ts_functions': None,\n", + "}\n", + "save_results(**save_params)" ] }, { "cell_type": "markdown", - "id": "953508b0-c2b3-41ec-aa56-d936db9e62fc", + "id": "3361fd78-30ad-4070-af0b-2604c71b6a3b", "metadata": {}, "source": [ "\n", @@ -3281,9 +1144,9 @@ ], "metadata": { "kernelspec": { - "display_name": "insar_analysis [conda env:.local-insar_analysis]", + "display_name": "solid_earth_atbd", "language": "python", - "name": "conda-env-.local-insar_analysis-py" + "name": "solid_earth_atbd" }, "language_info": { "codemirror_mode": { @@ -3295,7 +1158,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.16" + "version": "3.12.5" } }, "nbformat": 4, diff --git a/methods/permafrost/Permafrost_fielddata.ipynb b/methods/permafrost/Permafrost_fielddata.ipynb index 07f14cd..292c3a0 100644 --- a/methods/permafrost/Permafrost_fielddata.ipynb +++ b/methods/permafrost/Permafrost_fielddata.ipynb @@ -21,7 +21,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 1, "id": "f0d15576-f694-44e1-9f30-9fc2217afa9c", "metadata": {}, "outputs": [], @@ -31,34 +31,24 @@ "import numpy as np\n", "import pandas as pd\n", "import os\n", + "from solid_utils import permafrost_utils as pu\n", "from matplotlib import pyplot as plt\n", "from datetime import datetime\n" ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "id": "41c6eb75-5e00-4066-8c5c-57e02255bb17", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Field directory: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/fielddata\n" - ] - } - ], + "outputs": [], "source": [ "site='NorthSlopeEastD102'\n", - "year=2023\n", + "year=2025\n", "\n", - "if 'base_dir' not in locals():\n", - " base_dir = Path.cwd()\n", - "if 'work_dir' not in locals():\n", - " work_dir = base_dir/'work'/'permafrost_ouputs'/site/str(year)\n", - "if 'field_dir' not in locals():\n", - " field_dir = work_dir/'fielddata'\n", + "base_dir = Path.cwd()\n", + "work_dir = base_dir/'work'/'permafrost_ouputs'/site/str(year)\n", + "field_dir = base_dir/'fielddata'\n", "\n", "print(\"Field directory:\", field_dir)\n", "work_dir.mkdir(parents=True, exist_ok=True)\n", @@ -67,54 +57,17 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 4, "id": "73b56408-d2b7-4b0d-a179-357f94a14dd3", "metadata": {}, "outputs": [], "source": [ "fieldsites = ['HV','HVE','IC','SM']\n", "fieldsitenames = ['Happy Valley','Happy Valley East','Ice Cut','Slope Mountain']\n", - "fieldsitelocs = [[69.15478,-148.84382],[69.15531,-148.83792],[69.04113,-148.83162],[68.43289,-148.94216]]" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "e3debfc4-9896-4a5d-8a87-51d131a20b12", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Archive: /home/jovyan/NISAR_cal/field_data_2023.zip\n", - " inflating: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/fielddata/SM_displacement_level.csv \n", - " inflating: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/fielddata/SM_displacement_gnss.csv \n", - " inflating: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/fielddata/IC_displacement_level.csv \n", - " inflating: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/fielddata/IC_displacement_gnss.csv \n", - " inflating: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/fielddata/HVE_displacement_level.csv \n", - " inflating: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/fielddata/HVE_displacement_gnss.csv \n", - " inflating: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/fielddata/HV_displacement_level.csv \n", - " inflating: /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/fielddata/HV_displacement_gnss.csv \n" - ] - }, - { - "data": { - "text/plain": [ - "0" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# option to unzip field data directly [True/False]\n", - "# Set to False if importing field data from Cal/Val data base instead (not implemented yet).\n", - "Unzip_field_data = True\n", - "\n", - "os.system(f'unzip {str(base_dir)}/field_data_2023.zip -d {field_dir}/')" + "fieldsitelocs = [[69.15478,-148.84382],\n", + " [69.15531,-148.83792],\n", + " [69.04113,-148.83162],\n", + " [68.43289,-148.94216]]" ] }, { @@ -139,49 +92,57 @@ }, { "cell_type": "code", - "execution_count": 15, - "id": "c950d44a-6c21-42f5-85b4-d7b25ea5f5f9", - "metadata": {}, - "outputs": [], - "source": [ - "def open_fielddata(site,field_dir):\n", - " \"\"\"Opens the leveling and GNSS data for the given site.\"\"\"\n", - " ldata = pd.read_csv(field_dir/f'{site}_displacement_level.csv')\n", - " ldata['transect'] = [i[0:3] for i in ldata['point_name']]\n", - " ldata['trans_dist'] = [int(i[3:])*2 for i in ldata['point_name']]\n", - " ldata['mask'] = ldata['flag'][:]==0\n", - " \n", - " gdata = pd.read_csv(field_dir/f'{site}_displacement_gnss.csv')\n", - " gdata['transect'] = [i[0:3] for i in gdata['point_name'][:]]\n", - " gdata['trans_dist'] = [int(i[3:])*2 for i in gdata['point_name']]\n", - " gdata['mask'] = gdata['flag'][:]==0\n", - " return ldata,gdata\n" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "f78a69c1-3df4-44c7-b66b-57bc3fa46696", + "execution_count": 14, + "id": "3767844a-89ce-47db-af9d-75de180ba5b2", "metadata": {}, "outputs": [], "source": [ - "#get dates from data\n", - "date1list,date2list = [],[]\n", "\n", - "for site in fieldsites:\n", - " ldata,gdata = open_fielddata(site,field_dir)\n", - " #get dates using leveling date (if possible)\n", - " date1,date2 = ldata['date1'][0],ldata['date2'][0]\n", - " if np.isnan(date1):\n", - " date1 = gdata['date1'][0]\n", - " if np.isnan(date1):\n", - " date1 = f'{year}0525'\n", - " if np.isnan(date2):\n", - " date2 = gdata['date2'][0]\n", - " if np.isnan(date2):\n", - " date2 = f'{year}0820'\n", - " date1list.append(str(date1))\n", - " date2list.append(str(date2))" + "def getRelElv(subsite: str, year:int, measMethod: str, \n", + " dataInput:str = 'DB',removeFlags=[2,3]):\n", + " \"\"\"Gets relative elevation measurement from permafrost calval DB.\n", + " subsite: Abbvr of subsite (HV, HVE, IC, SM)\n", + " measMethod: 'gnss' or 'level'\n", + " dataInputs: 'DB' or 'from_csv' if using a set of csv files that emulate\n", + " the DB\n", + " removeFlags: list of data flags for which the corresponding results will be\n", + " removed. Flags are 0 - good data, 1 - data 15 cm out of mean,\n", + " 2 - data very far from mean and probably erroneous,\n", + " 3 - data missing. Default: [2,3]\n", + " \"\"\"\n", + " middate = datetime(year,7,15)\n", + " pts = pu.pointnames(subsite)\n", + "\n", + " if dataInput == 'from_csv':\n", + " data = pd.read_csv('fielddata/measured_displacement.csv')\n", + " data['measurement_date'] = [datetime.strptime(i,'%Y-%m-%d') \n", + " for i in data['measurement_date']]\n", + "\n", + " m1,m2 = [],[] #early/late summer measurement\n", + " date1,date2 = np.nan,np.nan\n", + " \n", + " for pt in pts:\n", + " querystr = f'point_id_keystr == \"{pt}\" and measurement_type == \"{measMethod}\"'\n", + " ptdata = data.query(querystr)\n", + " d1,d2 = pu.sortyeardate(ptdata,year,middate)\n", + " meas1, meas2 = np.nan,np.nan\n", + " if len(d1)>=1:\n", + " meas1 = d1.iloc[0]['relative_elevation_m']\n", + " date1 = pd.Timestamp(d1.iloc[0]['measurement_date']).to_pydatetime()\n", + " mflag = d1.iloc[0]['measurement_flag']\n", + " if mflag in removeFlags:\n", + " meas = np.nan\n", + " m1.append(meas1)\n", + " \n", + " if len(d2)>=1:\n", + " meas2 = d2.iloc[0]['relative_elevation_m']\n", + " date2 = pd.Timestamp(d2.iloc[0]['measurement_date']).to_pydatetime()\n", + " mflag = d2.iloc[0]['measurement_flag']\n", + " if mflag in removeFlags:\n", + " meas2 = np.nan\n", + " m2.append(meas2)\n", + " \n", + " return np.array(m1),np.array(m2),date1,date2,pts\n" ] }, { @@ -189,85 +150,43 @@ "id": "23f7eb0c-9d57-4350-99d8-06b81066f685", "metadata": {}, "source": [ - "Regarding 2023, the transects for the site Happy Valley East were created in August 2023, and therefore subsidence measurements do not exist for that summer. At Slope Mountain, the GNSS measurements were not collected in June 2023, and therefore summer displacements only come from the surveying.\n", + "Regarding 2023, the transects for the site Happy Valley East were created in August 2023, and therefore subsidence measurements do not exist for that summer. At Slope Mountain, the GNSS measurements were not collected in June 2023, and therefore summer displacements only come from the surveying. In June 2024 neither level nor GNSS measurements were able to be taken at Slope Mountain.\n", "\n", "Now we can plot the field measurements." ] }, { "cell_type": "code", - "execution_count": 18, - "id": "d11a94b3-092d-4d0c-a94c-8881eae817ab", + "execution_count": null, + "id": "bb3f18ff-8613-48e2-a0c9-963d75e518c6", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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\n", 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\n", 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ - "#plot the field data displacement results\n", - "for k,site in enumerate(fieldsites):\n", - "\n", - " ldata,gdata = open_fielddata(site,field_dir)\n", - " translist = np.unique(ldata['transect'][:])\n", + "trdist = np.linspace(0,100,51)\n", + "tnames = ['TA','TB','TC']\n", + "for k,subsite in enumerate(fieldsites):\n", + " lv1,lv2,lvd1,lvd2,pts = getRelElv(subsite,year,'level',dataInput = 'from_csv')\n", + " gn1,gn2,gnd1,gnd2,__ = getRelElv(subsite,year,'gnss',dataInput = 'from_csv')\n", + " lvd,gnd = lv2-lv1,gn2-gn1\n", + " if pd.isnull(lvd1):\n", + " lvd1 = datetime(year,6,1)\n", + " if pd.isnull(lvd2):\n", + " lvd2 = datetime(year,9,1)\n", " \n", - " clist = ['C00','C01','C02']\n", - "\n", " fig = plt.figure(figsize=(10,4.5))\n", " ax = fig.add_subplot(1,2,2)\n", - " d1str = datetime.strptime(date1list[k],'%Y%m%d').strftime('%Y-%m-%d')\n", - " d2str = datetime.strptime(date2list[k],'%Y%m%d').strftime('%Y-%m-%d')\n", + " d1str = lvd1.strftime('%Y-%m-%d')\n", + " d2str = lvd2.strftime('%Y-%m-%d')\n", " fig.suptitle(f'{fieldsitenames[k]}\\n{d1str} to {d2str}')\n", - " for i,t in enumerate(translist):\n", - " lt = ldata.iloc[np.array(ldata['transect'][:])==t]\n", - " gt = gdata.iloc[np.array(gdata['transect'][:])==t]\n", - " \n", - " axt = fig.add_subplot(3,2,1+i*2) \n", - " axt.plot(lt.iloc[np.array(lt['mask'])]['trans_dist'],\n", - " lt.iloc[np.array(lt['mask'])]['height_diff']*100,'.-',color='black',label='level')\n", - " axt.plot(gt.iloc[np.array(gt['mask'])]['trans_dist'],\n", - " gt.iloc[np.array(gt['mask'])]['height_diff']*100,'x-',color='gray',label='GNSS')\n", + " for i in range(3):\n", + " axt = fig.add_subplot(3,2,1+i*2) \n", + " plt.plot(trdist,lvd[i*51:(i+1)*51]*100,'.-',color='black',label='level')\n", + " plt.plot(trdist,gnd[i*51:(i+1)*51]*100,'x-',color='gray',label='GNSS')\n", "\n", - " axt.set_ylim(-30,5)\n", + " axt.set_ylim(-18,5)\n", " axt.set_xlim(-1,101)\n", " axt.axhline(0,linestyle='--',color='k')\n", + " t=tnames[i]\n", " axt.text(91,-28,t,fontsize=12)\n", " \n", " if i<2:\n", @@ -280,26 +199,16 @@ " if k==0:\n", " if i==0:\n", " axt.legend(loc=3)\n", - " \n", - " # ax2.plot(np.arange(np.sum(gt['mask']))*2,gt.iloc[np.array(gt['mask'])]['height_diff'],'.-')\n", - " \n", - " tmask = lt['mask'] & gt['mask']\n", - " ltvec,gtvec = lt[tmask]['height_diff'][:],gt[tmask]['height_diff'][:]\n", - " ax.plot(gtvec*100,ltvec*100,'.',label=t)\n", + "\n", + " ax.plot(gnd*100,lvd*100,'.')\n", "\n", " ax.axhline(0,linestyle='--',color='k')\n", " ax.axvline(0,linestyle='--',color='k')\n", - " ax.legend()\n", + " # ax.legend()\n", " ax.set_xlim([-25,5])\n", " ax.set_ylim([-25,5])\n", " ax.set_xlabel('GNSS displacement (cm)')\n", - " ax.set_ylabel('Level displacement (cm)')\n", - "\n", - " lmask,gmask = ldata['flag'][:]==0,gdata['flag'][:]==0\n", - " mask = (lmask) & (gmask)\n", - " ldatavec,gdatavec = ldata['height_diff'][:],gdata['height_diff'][:]\n", - " lmean,lstd = np.mean(ldatavec[lmask]),np.std(ldatavec[lmask])\n", - " gmean,gstd = np.mean(gdatavec[gmask]),np.std(gdatavec[gmask])" + " ax.set_ylabel('Level displacement (cm)')\n" ] }, { @@ -314,64 +223,26 @@ }, { "cell_type": "code", - "execution_count": 19, - "id": "357db7a3-cc18-4722-bd78-0f5ea0558356", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "HV\n", - "Mean from leveling: -16.2 +/- 3.5 cm\n", - "Mean from GNSS: -11.0 +/- 3.6 cm\n", - "Overall mean: -13.6 +/- 2.5 cm\n", - "\n", - "HVE\n", - "Mean from leveling: nan +/- nan cm\n", - "Mean from GNSS: nan +/- nan cm\n", - "Overall mean: nan +/- nan cm\n", - "\n", - "IC\n", - "Mean from leveling: -6.7 +/- 3.4 cm\n", - "Mean from GNSS: -6.0 +/- 2.9 cm\n", - "Overall mean: -6.3 +/- 2.3 cm\n", - "\n", - "SM\n", - "Mean from leveling: -9.6 +/- 4.4 cm\n", - "Mean from GNSS: nan +/- nan cm\n", - "Overall mean: -9.6 +/- 4.4 cm\n", - "\n", - "Displaying dataframe:\n", - " name date1 date2 latitude longitude rel_change stdev\n", - "0 HV 20230530 20230813 69.15478 -148.84382 -0.136049 0.025139\n", - "1 HVE 20230525 20230820 69.15531 -148.83792 NaN NaN\n", - "2 IC 20230527 20230815 69.04113 -148.83162 -0.063390 0.022596\n", - "3 SM 20230529 20230816 68.43289 -148.94216 -0.096067 0.043627\n", - "\n", - " Saving data to /home/jovyan/NISAR_cal/work/permafrost_ouputs/NorthSlopeEastD102/2023/fielddata/field_results.csv\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_312/2437221705.py:11: RuntimeWarning: Mean of empty slice\n", - " tdisp = np.nanmean([ldisp,gdisp])\n" - ] - } - ], + "execution_count": null, + "id": "b04f8fc4-f20c-48df-9091-0635feb0802b", + "metadata": { + "scrolled": true + }, + "outputs": [], "source": [ - "#initialize dataframe\n", - "fielddisp = pd.DataFrame(columns = ['name','date1','date2','latitude','longitude','rel_change','stdev'])\n", - "for i,site in enumerate(fieldsites):\n", - " # print(site)\n", - " lat,lon = fieldsitelocs[i]\n", - " ldata,gdata = open_fielddata(site,field_dir)\n", + "fielddisp = pd.DataFrame(columns = ['name','date1','date2','rel_change','stdev'])\n", + "for k,subsite in enumerate(fieldsites):\n", + " lat,lon = fieldsitelocs[k]\n", + " lv1,lv2,lvd1,lvd2,pts = getRelElv(subsite,year,'level',dataInput = 'from_csv')\n", + " gn1,gn2,gnd1,gnd2,__ = getRelElv(subsite,year,'gnss',dataInput = 'from_csv')\n", + " lvd,gnd = lv2-lv1,gn2-gn1\n", + " if pd.isnull(lvd1):\n", + " lvd1 = datetime(year,6,1)\n", + " if pd.isnull(lvd2):\n", + " lvd2 = datetime(year,9,1)\n", "\n", - " lmask,gmask = ldata['flag'][:]==0,gdata['flag'][:]==0\n", - " ldisp,lstd = np.mean(ldata[lmask]['height_diff']),np.std(ldata[lmask]['height_diff'])\n", - " gdisp,gstd = np.mean(gdata[gmask]['height_diff']),np.std(gdata[gmask]['height_diff'])\n", + " ldisp,lstd = np.nanmean(lvd),np.nanstd(lvd)/np.sqrt(np.sum(~np.isnan(lvd)))\n", + " gdisp,gstd = np.nanmean(gnd),np.nanstd(gnd)/np.sqrt(np.sum(~np.isnan(gnd)))\n", " tdisp = np.nanmean([ldisp,gdisp])\n", "\n", " #get standard deviation between measurement types, propogate errors\n", @@ -383,14 +254,14 @@ " else:\n", " tstd = np.nan\n", "\n", - " print(f'{site}')\n", + " print(f'{subsite}')\n", " print(f'Mean from leveling: {ldisp*100:.1f} +/- {lstd*100:.1f} cm')\n", " print(f'Mean from GNSS: {gdisp*100:.1f} +/- {gstd*100:.1f} cm')\n", " print(f'Overall mean: {tdisp*100:.1f} +/- {tstd*100:.1f} cm\\n')\n", "\n", " \n", - " sitedata = [site,date1list[i],date2list[i],lat,lon,tdisp,tstd]\n", - " fielddisp.loc[i]=sitedata\n", + " sitedata = [subsite,lvd1,lvd2,tdisp,tstd]\n", + " fielddisp.loc[k]=sitedata\n", "print('Displaying dataframe:')\n", "print(fielddisp)\n", "\n", @@ -402,9 +273,9 @@ ], "metadata": { "kernelspec": { - "display_name": "insar_analysis [conda env:.local-insar_analysis]", + "display_name": "solid_earth_atbd", "language": "python", - "name": "conda-env-.local-insar_analysis-py" + "name": "solid_earth_atbd" }, "language_info": { "codemirror_mode": { @@ -416,7 +287,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.16" + "version": "3.12.5" } }, "nbformat": 4, diff --git a/methods/permafrost/field_data_2023.zip b/methods/permafrost/field_data_2023.zip deleted file mode 100644 index 69877ae..0000000 Binary files a/methods/permafrost/field_data_2023.zip and /dev/null differ diff --git a/methods/secular/Secular_Requirement_Validation.ipynb b/methods/secular/Secular_Requirement_Validation.ipynb index fd82084..3730928 100644 --- a/methods/secular/Secular_Requirement_Validation.ipynb +++ b/methods/secular/Secular_Requirement_Validation.ipynb @@ -1984,7 +1984,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.3" + "version": "3.13.5" }, "toc": { "base_numbering": 1, diff --git a/my_sites.txt b/my_sites.txt index 2b64ad9..b372056 100644 --- a/my_sites.txt +++ b/my_sites.txt @@ -611,6 +611,22 @@ "SET_source" : "mintpy", "do_iono" : "True", "do_tropo" : "True", - "tropo_model" : "ERA5"} + "tropo_model" : "ERA5"}, + + "Info" : "######## PERMAFROST #########", + + "NorthSlopeEastD102" : { + "calval_location" : "NorthSlopeEastD102", + "region_identifier" : "POINT(-149.37 69.09)", + "subset_region" : "[7620213:7686754, 641941:679925]", + "download_start_date" : "20230525", + "download_end_date" : "20230910", + "mintpy_ref_loc" : "7651392, 666923", + "tempBaseMax" : "36", + "ifgExcludeList" : "auto", + "maskWater" : "True", + "sentinel_direction" : "DESCENDING", + "sentinel_path" : "102", + "sentinel_frame" : "362"} } } diff --git a/prep/ARIA_prep.ipynb b/prep/ARIA_prep.ipynb index a085736..8122e6c 100644 --- a/prep/ARIA_prep.ipynb +++ b/prep/ARIA_prep.ipynb @@ -671,7 +671,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.3" + "version": "3.13.5" } }, "nbformat": 4, diff --git a/prep/NISAR_prep.ipynb b/prep/NISAR_prep.ipynb index 12c7bcd..21c1a38 100644 --- a/prep/NISAR_prep.ipynb +++ b/prep/NISAR_prep.ipynb @@ -305,9 +305,9 @@ ], "metadata": { "kernelspec": { - "display_name": "mintpy_dev", + "display_name": "Python (solid_earth_atbd_dev)", "language": "python", - "name": "mintpy_dev" + "name": "solid_earth_atbd_dev" }, "language_info": { "codemirror_mode": { @@ -319,7 +319,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.8" + "version": "3.13.5" } }, "nbformat": 4, diff --git a/solid_utils/plotting.py b/solid_utils/plotting.py index edac857..f9ff9bb 100644 --- a/solid_utils/plotting.py +++ b/solid_utils/plotting.py @@ -15,7 +15,7 @@ def display_validation(pair_distance: NDArray, pair_difference: NDArray, requirement: float = 2, distance_rqmt: list = [0.1, 50], n_bins: int = 10, threshold: float = 0.683, sensor:str ='Sentinel-1', validation_type:str='secular', - validation_data:str='GNSS'): + validation_data:str='Field_meas'): """Display double-difference validation results. Bin the double differences as a function of point separation, compute the stastics for each bin, and @@ -514,5 +514,151 @@ def style_specific_cells(val): # plt.savefig(f'transient_validation_{index[i]}.png', bbox_inches='tight', transparent=True) plt.close() - return styled_df, fig + return styled_df, fig + +def display_permafrost_validation(pair_distance: NDArray, pair_difference: NDArray, + site_name: str, start_date: str, end_date: str, + requirement: float = 2, req_dist_fcn: bool = False, + distance_rqmt: list = [0.1, 50], n_bins: int = 10, threshold: float = 0.8, + sensor:str ='Sentinel-1', validation_type:str='permafrost', + validation_data:str='field'): + ''' + Parameters: + pair_distance : array - 1d array of pair distances used in validation + pair_difference : array - 1d array 0f pair double differenced velocity residuals + site_name : str - name of the cal/val site + start_date : str - data record start date, eg. 20190101 + end_date : str - data record end date, eg. 20200101 + requirement : float - value required for test to pass + e.g, 2 mm/yr for 3 years of data over distance requiremeent + req_dist_fcn: bool - flag to scale requirement with distance. If True, requirement = value * (1+sqrt(L)) + distance_rqmt : list - distance over requirement is tested, eg. length scales of 0.1-50 km + n_bins : int - number of bins + threshold : float - threshold represents percentile of Gaussian normal distribution + within residuals are expected to be to pass the test + e.g. 0.8 for 80% + sensor : str - sensor used in validation, e.g Sentinel-1 or NISAR + validation_type : str - type of validation: permafrost + validation_data : str - data used to validate against; field or INSAR + + Return + validation_table + validation_figure + ''' + # init dataframe + pair_req_met = np.array(pair_difference < requirement*(1+float(req_dist_fcn)*np.sqrt(pair_distance))) + pair_req_met[np.isnan(pair_difference)]=np.nan + df = pd.DataFrame(np.vstack([pair_distance, + pair_difference, + pair_req_met]).T, + columns=['distance', 'double_diff','req_met']) + + # remove nans + df_nonan = df.dropna(subset=['double_diff']) + bins = np.linspace(*distance_rqmt, num=n_bins+1) + bin_centers = (bins[:-1] + bins[1:]) / 2 + binned_df = df_nonan.groupby(pd.cut(df_nonan['distance'], bins), + observed=False)[['req_met']] + binned_df_diff = df_nonan.groupby(pd.cut(df_nonan['distance'], bins), + observed=False)[['double_diff']] + + # get binned validation table + bin_req = requirement*(1+float(req_dist_fcn)*np.sqrt(bin_centers)) + validation = pd.DataFrame([]) + validation['total_count[#]'] = binned_df.apply(lambda x: np.ma.masked_invalid(x).count()) + validation['passed_req.[#]'] = binned_df.apply(lambda x: np.count_nonzero(x)) + + # Add total at the end + validation = pd.concat([validation, pd.DataFrame(validation.sum(axis=0)).T]) + validation['passed_pc'] = validation['passed_req.[#]'] / validation['total_count[#]'] + validation['success_fail'] = validation['passed_pc'] > threshold + validation.index.name = 'distance[km]' + # Rename last row + validation.rename({validation.iloc[-1].name:'Total'}, inplace=True) + + # Figure + fig, ax = plt.subplots(1, figsize=(9, 3), layout="none", dpi=200) + ymax = 20 + if validation_type=='permafrost': + ymax=50 + + + # Plot residuals + ms = 8 if pair_difference.shape[0] < 1e4 else 0.3 + alpha = 0.6 if pair_difference.shape[0] < 1e4 else 0.2 + ax.scatter(df_nonan.distance, df_nonan.double_diff, + color='black', s=ms, zorder=1, alpha=alpha, edgecolor='None') + + for i,r in enumerate(bin_req): + ibin = [bins[i],bins[i+1]] + ax.fill_between(ibin, 0, r, color='#e6ffe6', zorder=0, alpha=0.6) + ax.fill_between(ibin, r, 51, color='#ffe6e6', zorder=0, alpha=0.6) + ax.vlines(bins, 0, ymax+1, linewidth=0.3, color='gray', zorder=1) + + req_line_x = np.linspace(*distance_rqmt, num=200) + req_line_y = requirement*(1+req_dist_fcn*np.sqrt(req_line_x)) + ax.plot(req_line_x,req_line_y, color='k', linestyle='--', zorder=3) + + # Bar plot for each bin + quantile_th = binned_df_diff.quantile(q=threshold)['double_diff'].values + for bin_center, quantile, flag in zip(bin_centers, + quantile_th, + validation['success_fail']): + if flag: + color = '#227522' + else: + color = '#7c1b1b' + ax.bar(bin_center, quantile, align='center', width=np.diff(bins)[0], + color='None', edgecolor=color, linewidth=2, zorder=3) + + # Add legend with data info + legend_kwargs = dict(transform=ax.transAxes, verticalalignment='top') + props = dict(boxstyle='square', facecolor='white', alpha=1, linewidth=0.4) + textstr = f'Sensor: {sensor} \n{validation_data}-InSAR point pairs\n' + textstr += f'Record: {start_date}-{end_date}' + + # place a text box in upper left in axes coords + ax.text(0.02, 0.95, textstr, fontsize=8, bbox=props, **legend_kwargs) + + # Add legend with validation info + textstr = f'{validation_type.capitalize()} requirement\n' + textstr += f'Site: {site_name}\n' + if validation.loc['Total']['success_fail']: + validation_flag = 'PASSED' + validation_color = '#239d23' + else: + validation_flag ='FAILED' + validation_color = '#bc2e2e' + + props = {**props, **{'facecolor':'none', 'edgecolor':'none'}} + ax.text(0.818, 0.93, textstr, fontsize=8, bbox=props, **legend_kwargs) + ax.text(0.852, 0.82, f"{validation_flag}", + fontsize=10, weight='bold', + bbox=props, **legend_kwargs) + + rect = patches.Rectangle((0.8, 0.75), 0.19, 0.2, + linewidth=1, edgecolor='black', + facecolor=validation_color, + transform=ax.transAxes) + ax.add_patch(rect) + + # Title & labels + fig.suptitle(f"{validation_type.capitalize()} requirement: {site_name}", fontsize=10) + ax.set_xlabel("Distance (km)", fontsize=8) + if validation_data == 'GNSS': + txt = "Double-Differenced \nVelocity Residual (mm/yr)" + else: + txt = "Relative displacement measurement (mm)" + ax.set_ylabel(txt, fontsize=8) + ax.minorticks_on() + ax.tick_params(axis='x', which='minor', length=4, direction='in', top=False, width=1.5) + ax.tick_params(axis='both', labelsize=8) + ax.set_xticks(bin_centers, minor=True) + ax.set_xticks(np.arange(0,55,5)) + ax.set_ylim(0,ymax) + ax.set_xlim(*distance_rqmt) + + validation = validation.rename(columns={'success_fail': f'passed_req [>{threshold*100:.1f}%]'}) + + return validation, fig diff --git a/solid_utils/saving.py b/solid_utils/saving.py index 7f005f2..674a88d 100644 --- a/solid_utils/saving.py +++ b/solid_utils/saving.py @@ -127,3 +127,129 @@ def save_results(save_dir:str, run_date:str, requirement:str, site:str, method:s # Save to zip file shutil.make_archive(save_dir, 'zip', save_dir) + +def save_results_permafrost(save_dir:str, run_date:str, requirement:str, site:str, method:str, + sitedata:dict, gnss_insar_figs, validation_figs:list, validation_table:pd.DataFrame, + ts_functions:dict=None, summary:str=""): + """Save the input parameters and results to an output folder. + The results folder will include image files, and an HTML file + recording the inputs, essential figures, and validation table. + """ + # Create new directory for outputs + if os.path.exists(save_dir): + print(f"Directory {save_dir} exists") + else: + print(f"Creating {os.path.basename(save_dir)}") + os.makedirs(save_dir) + + # Begin HTML string + html_str = """ + + + + {requirement:s} Method {method} + + +

{requirement:s} requirement validation +{site:s} site, Method {method}

+ +""".format(requirement=requirement.title(), + site=site, + method=method) + + # Run date time + html_str += """ +

Run time:

+ {run_date:s} + +""".format(run_date=run_date) + + # Site parameters + html_str += "" + html_str += """

Setup parameters:

+
    +""" + for key, value in sitedata.items(): + html_str += "
  • {}: {}
    • ".format(key, value) + html_str += """
+""" + + # Timeseries basis functions + if ts_functions is not None: + html_str += "" + html_str += """

Timeseries basis functions

+
    + """ + for key, value in ts_functions.items(): + html_str += "
  • {}: {}
    • ".format(key, value) + html_str += """
+""" + + # Processing results + html_str += """ +

InSAR and GNSS LOS Velocities

+Visual comparison of GNSS and InSAR LOS velocities +
+ +""".format(method=method) + + # Save GNSS InSAR figures + for i, gnss_insar_fig in enumerate(gnss_insar_figs): + fig_name = f"{requirement:s}_Method{method}_gnss_insar_figure{i + 1:d}.png" + fig_path = os.path.join(save_dir, fig_name) + print(f"Saving GNSS-InSAR figure to: {fig_name}") + gnss_insar_fig.savefig(fig_path, bbox_inches='tight', transparent=True, + dpi=300) + + # Embed GNSS-InSAR figures + html_str += """ +Method {method} GNSS InSAR Image + +""".format(fig_name=fig_name, + method=method) + + # Validation results + html_str += """ +

Method {method} Results

+ +""".format(method=method) + + # Save validation figures + for i, validation_fig in enumerate(validation_figs): + fig_name = f"{requirement:s}_Method{method}_validation_figure{i + 1:d}.png" + fig_path = os.path.join(save_dir, fig_name) + print(f"Saving validation figure to: {fig_name}") + validation_fig.savefig(fig_path, bbox_inches='tight', transparent=True, + dpi=300) + + # Embed validation figure + html_str += """ + Method {method} Validation Image + + """.format(fig_name=fig_name, + method=method) + + # Validation table + html_str += """ +{} +""".format(validation_table.to_html()) + + # Save summary + html_str += """ +

Summary

+{:s} +""".format(summary) + + # Write to HTML file + html_name = f"{requirement:s}_Method{method}_validation_report.html" + html_path = os.path.join(save_dir, html_name) + with open(html_path, 'w') as html_file: + html_file.write(html_str) + + # pdf_file = html_path.split(".")[0]+".pdf" + # HTML(html_path).write_pdf(pdf_file) + # print(f"Saved PDF version of report to: {pdf_file}") + print(f"Saved parameters and results to: {save_dir:s}") + + # Save to zip file + shutil.make_archive(save_dir, 'zip', save_dir) \ No newline at end of file