From f7d699765d2024a8ed357733dfde11a6057b62ee Mon Sep 17 00:00:00 2001 From: Aaron Zuspan Date: Sat, 22 Feb 2025 00:17:42 -0800 Subject: [PATCH] Update demo notebook - Remove the binder configuration and link in favor of just Colab - Update the demo notebook to explicitly initialize and list config options --- .binder/environment.yml | 9 - README.md | 1 - docs/notebooks/demo.ipynb | 614 +++++++++++++++----------------------- 3 files changed, 245 insertions(+), 379 deletions(-) delete mode 100644 .binder/environment.yml diff --git a/.binder/environment.yml b/.binder/environment.yml deleted file mode 100644 index e1681ee..0000000 --- a/.binder/environment.yml +++ /dev/null @@ -1,9 +0,0 @@ -name: eerepr-demo -channels: - - conda-forge -dependencies: - - python=3.8 - - pip - - earthengine-api - - pip: - - git+https://github.com/aazuspan/eerepr.git \ No newline at end of file diff --git a/README.md b/README.md index 222afdc..63049a3 100644 --- a/README.md +++ b/README.md @@ -4,7 +4,6 @@ [![PyPI version](https://badge.fury.io/py/eerepr.svg)](https://badge.fury.io/py/eerepr) [![conda-forge link](https://img.shields.io/conda/vn/conda-forge/eerepr)](https://anaconda.org/conda-forge/eerepr) [![nbviewer](https://raw.githubusercontent.com/jupyter/design/master/logos/Badges/nbviewer_badge.svg)](https://nbviewer.org/github/aazuspan/eerepr/blob/main/docs/notebooks/demo.ipynb) -[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/aazuspan/eerepr/HEAD?labpath=docs%2Fnotebooks%2Fdemo.ipynb) [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/aazuspan/eerepr/blob/main/docs/notebooks/demo.ipynb) Add interactive Code Editor-style HTML reprs to Earth Engine objects in a Jupyter environment. diff --git a/docs/notebooks/demo.ipynb b/docs/notebooks/demo.ipynb index c1fa164..29b8c32 100644 --- a/docs/notebooks/demo.ipynb +++ b/docs/notebooks/demo.ipynb @@ -6,13 +6,13 @@ "metadata": {}, "outputs": [], "source": [ - "# Install eerepr if needed\n", - "# !pip install eerepr" + "# Install the latest eerepr if needed\n", + "# !pip install --upgrade eerepr" ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -20,21 +20,32 @@ "import eerepr\n", "\n", "ee.Authenticate()\n", - "ee.Initialize()" + "ee.Initialize(project=\"my-project\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Quick Start" + "## Quick Start\n", + "\n", + "Calling `eerepr.initialize()` registers `_repr_html_` methods for all Earth Engine objects, which will automatically be displayed instead of string reprs in a Jupyter notebook. " + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "eerepr.initialize()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Importing `eerepr` registers interactive HTML reprs to all Earth Engine objects. Just print an object to preview it. This works for simple objects, like `ee.Dictionary`..." + "This works for simple objects, like `ee.Dictionary`..." ] }, { @@ -45,16 +56,9 @@ { "data": { "text/html": [ - "
      • 0:1
      • 1:2
      • 2:3
      • 3:4
" + ".eerepr details summary {\n", + " list-style-type: none;\n", + "}\n", + "
" ], "text/plain": [ - "" + "" ] }, "execution_count": 3, @@ -175,7 +162,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "...and for much more complex objects like `ee.ImageCollection` or `ee.FeatureCollection`." + "...and for more complex objects like `ee.ImageCollection` or `ee.FeatureCollection`." ] }, { @@ -186,16 +173,9 @@ { "data": { "text/html": [ - "
    • type:ImageCollection
    • id:COPERNICUS/S2_SR
    • version:1667959494839422
          • 0:1490659200000
          • 1:1647907200000
        • description:

          Sentinel-2 is a wide-swath, high-resolution, multi-spectral\n", + "\n", + ".eerepr details summary::-webkit-details-marker {\n", + " display:none;\n", + "}\n", + "\n", + ".eerepr details summary {\n", + " list-style-type: none;\n", + "}\n", + "

          • ImageCollection COPERNICUS/S2_SR_HARMONIZED (3 elements)
            • type:ImageCollection
            • id:COPERNICUS/S2_SR_HARMONIZED
            • version:1740211306271965
            • bands: []
              • properties: Object (21 properties)
                • date_range: [1490659200000, 1647907200000]
                  • 0:1490659200000
                  • 1:1647907200000
                • description:<p>Sentinel-2 is a wide-swath, high-resolution, multi-spectral\n", "imaging mission supporting Copernicus Land Monitoring studies,\n", "including the monitoring of vegetation, soil and water cover,\n", - "as well as observation of inland waterways and coastal areas.

                  The Sentinel-2 L2 data are downloaded from scihub. They were\n", + "as well as observation of inland waterways and coastal areas.</p><p>The Sentinel-2 L2 data are downloaded from scihub. They were\n", "computed by running sen2cor. WARNING: ESA did not produce L2 data\n", - "for all L1 assets, and earlier L2 coverage is not global.

                  The assets contain\n", + "for all L1 assets, and earlier L2 coverage is not global.</p><p>The assets contain\n", "12 UINT16 spectral bands representing SR scaled by 10000 (unlike in L1 data,\n", "there is no B10). There are also several more L2-specific bands (see band\n", "list for details). See the\n", - "Sentinel-2 User Handbook\n", + "<a href="https://sentinel.esa.int/documents/247904/685211/Sentinel-2_User_Handbook">Sentinel-2 User Handbook</a>\n", "for details. In addition, three QA bands are present where one\n", "(QA60) is a bitmask band with cloud mask information. For more\n", - "details, see the full explanation of how cloud masks are computed.

                  EE asset ids for Sentinel-2 L2 assets have the following format:\n", + "details, <a href="https://sentinel.esa.int/web/sentinel/technical-guides/sentinel-2-msi/level-1c/cloud-masks">see the full explanation of how cloud masks are computed.</a></p><p>EE asset ids for Sentinel-2 L2 assets have the following format:\n", "COPERNICUS/S2_SR/20151128T002653_20151128T102149_T56MNN. Here the\n", "first numeric part represents the sensing date and time, the\n", "second numeric part represents the product generation date and\n", "time, and the final 6-character string is a unique granule identifier\n", - "indicating its UTM grid reference (see MGRS).

                  Clouds can be removed by using\n", - "COPERNICUS/S2_CLOUD_PROBABILITY.\n", + "indicating its UTM grid reference (see <a href="https://en.wikipedia.org/wiki/Military_Grid_Reference_System">MGRS</a>).</p><p>Clouds can be removed by using\n", + "<a href="COPERNICUS_S2_CLOUD_PROBABILITY">COPERNICUS/S2_CLOUD_PROBABILITY</a>.\n", "See\n", - "this tutorial\n", - "explaining how to apply the cloud mask.

                  For more details on Sentinel-2 radiometric resolution, see this page.

                  Provider: European Union/ESA/Copernicus

                  Revisit Interval
                  \n", + "<a href="https://developers.google.com/earth-engine/tutorials/community/sentinel-2-s2cloudless">this tutorial</a>\n", + "explaining how to apply the cloud mask.</p><p>For more details on Sentinel-2 radiometric resolution, <a href="https://earth.esa.int/web/sentinel/user-guides/sentinel-2-msi/resolutions/radiometric">see this page</a>.</p><p><b>Provider: <a href="https://earth.esa.int/web/sentinel/user-guides/sentinel-2-msi/product-types/level-2a">European Union/ESA/Copernicus</a></b><br><p><b>Revisit Interval</b><br>\n", " 5 days\n", - "

                  Bands
                  NameDescription
                  B1

                  Aerosols

                  B2

                  Blue

                  B3

                  Green

                  B4

                  Red

                  B5

                  Red Edge 1

                  B6

                  Red Edge 2

                  B7

                  Red Edge 3

                  B8

                  NIR

                  B8A

                  Red Edge 4

                  B9

                  Water vapor

                  B11

                  SWIR 1

                  B12

                  SWIR 2

                  AOT

                  Aerosol Optical Thickness

                  WVP

                  Water Vapor Pressure. The height the water would occupy if the vapor were condensed into\n", - "liquid and spread evenly across the column.

                  SCL

                  Scene Classification Map (The "No Data" value of 0 is masked out)

                  TCI_R

                  True Color Image, Red channel

                  TCI_G

                  True Color Image, Green channel

                  TCI_B

                  True Color Image, Blue channel

                  MSK_CLDPRB

                  Cloud Probability Map (missing in some products)

                  MSK_SNWPRB

                  Snow Probability Map (missing in some products)

                  QA10

                  Always empty

                  QA20

                  Always empty

                  QA60

                  Cloud mask

                  \n", + "</p><p><b>Bands</b><table class="eecat"><tr><th scope="col">Name</th><th scope="col">Description</th></tr><tr><td>B1</td><td><p>Aerosols</p></td></tr><tr><td>B2</td><td><p>Blue</p></td></tr><tr><td>B3</td><td><p>Green</p></td></tr><tr><td>B4</td><td><p>Red</p></td></tr><tr><td>B5</td><td><p>Red Edge 1</p></td></tr><tr><td>B6</td><td><p>Red Edge 2</p></td></tr><tr><td>B7</td><td><p>Red Edge 3</p></td></tr><tr><td>B8</td><td><p>NIR</p></td></tr><tr><td>B8A</td><td><p>Red Edge 4</p></td></tr><tr><td>B9</td><td><p>Water vapor</p></td></tr><tr><td>B11</td><td><p>SWIR 1</p></td></tr><tr><td>B12</td><td><p>SWIR 2</p></td></tr><tr><td>AOT</td><td><p>Aerosol Optical Thickness</p></td></tr><tr><td>WVP</td><td><p>Water Vapor Pressure. The height the water would occupy if the vapor were condensed into\n", + "liquid and spread evenly across the column.</p></td></tr><tr><td>SCL</td><td><p>Scene Classification Map (The &quot;No Data&quot; value of 0 is masked out)</p></td></tr><tr><td>TCI_R</td><td><p>True Color Image, Red channel</p></td></tr><tr><td>TCI_G</td><td><p>True Color Image, Green channel</p></td></tr><tr><td>TCI_B</td><td><p>True Color Image, Blue channel</p></td></tr><tr><td>MSK_CLDPRB</td><td><p>Cloud Probability Map (missing in some products)</p></td></tr><tr><td>MSK_SNWPRB</td><td><p>Snow Probability Map (missing in some products)</p></td></tr><tr><td>QA10</td><td><p>Always empty</p></td></tr><tr><td>QA20</td><td><p>Always empty</p></td></tr><tr><td>QA60</td><td><p>Cloud mask</p></td></tr><tr><td colspan=100>\n", " Bitmask for QA60\n", - "
                  • \n", + "<ul><li>\n", " Bit 10: Opaque clouds\n", - "
                    • 0: No opaque clouds
                    • 1: Opaque clouds present
                  • \n", + "<ul><li>0: No opaque clouds</li><li>1: Opaque clouds present</li></ul></li><li>\n", " Bit 11: Cirrus clouds\n", - "
                    • 0: No cirrus clouds
                    • 1: Cirrus clouds present

                  Image Properties
                  NameTypeDescription
                  AOT_RETRIEVAL_ACCURACYDOUBLE

                  Accuracy of Aerosol Optical thickness model

                  CLOUDY_PIXEL_PERCENTAGEDOUBLE

                  Granule-specific cloudy pixel percentage taken from the original metadata

                  CLOUD_COVERAGE_ASSESSMENTDOUBLE

                  Cloudy pixel percentage for the whole archive that\n", - "contains this granule. Taken from the original metadata

                  CLOUDY_SHADOW_PERCENTAGEDOUBLE

                  Percentage of pixels classified as cloud shadow

                  DARK_FEATURES_PERCENTAGEDOUBLE

                  Percentage of pixels classified as dark features or shadows

                  DATASTRIP_IDSTRING

                  Unique identifier of the datastrip Product Data Item (PDI)

                  DATATAKE_IDENTIFIERSTRING

                  Uniquely identifies a given Datatake. The ID contains\n", + "<ul><li>0: No cirrus clouds</li><li>1: Cirrus clouds present</li></ul></li></ul></td></tr></table><p><b>Image Properties</b><table class="eecat"><tr><th scope="col">Name</th><th scope="col">Type</th><th scope="col">Description</th></tr><tr><td>AOT_RETRIEVAL_ACCURACY</td><td>DOUBLE</td><td><p>Accuracy of Aerosol Optical thickness model</p></td></tr><tr><td>CLOUDY_PIXEL_PERCENTAGE</td><td>DOUBLE</td><td><p>Granule-specific cloudy pixel percentage taken from the original metadata</p></td></tr><tr><td>CLOUD_COVERAGE_ASSESSMENT</td><td>DOUBLE</td><td><p>Cloudy pixel percentage for the whole archive that\n", + "contains this granule. Taken from the original metadata</p></td></tr><tr><td>CLOUDY_SHADOW_PERCENTAGE</td><td>DOUBLE</td><td><p>Percentage of pixels classified as cloud shadow</p></td></tr><tr><td>DARK_FEATURES_PERCENTAGE</td><td>DOUBLE</td><td><p>Percentage of pixels classified as dark features or shadows</p></td></tr><tr><td>DATASTRIP_ID</td><td>STRING</td><td><p>Unique identifier of the datastrip Product Data Item (PDI)</p></td></tr><tr><td>DATATAKE_IDENTIFIER</td><td>STRING</td><td><p>Uniquely identifies a given Datatake. The ID contains\n", "the Sentinel-2 satellite, start date and time, absolute orbit\n", - "number, and processing baseline.

                  DATATAKE_TYPESTRING

                  MSI operation mode

                  DEGRADED_MSI_DATA_PERCENTAGEDOUBLE

                  Percentage of degraded MSI and ancillary data

                  FORMAT_CORRECTNESSSTRING

                  Synthesis of the On-Line Quality Control (OLQC) checks\n", + "number, and processing baseline.</p></td></tr><tr><td>DATATAKE_TYPE</td><td>STRING</td><td><p>MSI operation mode</p></td></tr><tr><td>DEGRADED_MSI_DATA_PERCENTAGE</td><td>DOUBLE</td><td><p>Percentage of degraded MSI and ancillary data</p></td></tr><tr><td>FORMAT_CORRECTNESS</td><td>STRING</td><td><p>Synthesis of the On-Line Quality Control (OLQC) checks\n", "performed at granule (Product_Syntax) and datastrip (Product\n", - "Syntax and DS_Consistency) levels

                  GENERAL_QUALITYSTRING

                  Synthesis of the OLQC checks performed at the datastrip level (Relative_Orbit_Number)

                  GENERATION_TIMEDOUBLE

                  Product generation time

                  GEOMETRIC_QUALITYSTRING

                  Synthesis of the OLQC checks performed at the datastrip level (Attitude_Quality_Indicator)

                  GRANULE_IDSTRING

                  Unique identifier of the granule PDI (PDI_ID)

                  HIGH_PROBA_CLOUDS_PERCENTAGEDOUBLE

                  Percentage of pixels classified as high probability clouds

                  MEAN_INCIDENCE_AZIMUTH_ANGLE_B1DOUBLE

                  Mean value containing viewing incidence azimuth angle average for band B1 and for all detectors

                  MEAN_INCIDENCE_AZIMUTH_ANGLE_B2DOUBLE

                  Mean value containing viewing incidence azimuth angle average for band B2 and for all detectors

                  MEAN_INCIDENCE_AZIMUTH_ANGLE_B3DOUBLE

                  Mean value containing viewing incidence azimuth angle average for band B3 and for all detectors

                  MEAN_INCIDENCE_AZIMUTH_ANGLE_B4DOUBLE

                  Mean value containing viewing incidence azimuth angle average for band B4 and for all detectors

                  MEAN_INCIDENCE_AZIMUTH_ANGLE_B5DOUBLE

                  Mean value containing viewing incidence azimuth angle average for band B5 and for all detectors

                  MEAN_INCIDENCE_AZIMUTH_ANGLE_B6DOUBLE

                  Mean value containing viewing incidence azimuth angle average for band B6 and for all detectors

                  MEAN_INCIDENCE_AZIMUTH_ANGLE_B7DOUBLE

                  Mean value containing viewing incidence azimuth angle average for band B7 and for all detectors

                  MEAN_INCIDENCE_AZIMUTH_ANGLE_B8DOUBLE

                  Mean value containing viewing incidence azimuth angle average for band B8 and for all detectors

                  MEAN_INCIDENCE_AZIMUTH_ANGLE_B8ADOUBLE

                  Mean value containing viewing incidence azimuth angle average for band B8a and for all detectors

                  MEAN_INCIDENCE_AZIMUTH_ANGLE_B9DOUBLE

                  Mean value containing viewing incidence azimuth angle average for band B9 and for all detectors

                  MEAN_INCIDENCE_AZIMUTH_ANGLE_B10DOUBLE

                  Mean value containing viewing incidence azimuth angle average for band B10 and for all detectors

                  MEAN_INCIDENCE_AZIMUTH_ANGLE_B11DOUBLE

                  Mean value containing viewing incidence azimuth angle average for band B11 and for all detectors

                  MEAN_INCIDENCE_AZIMUTH_ANGLE_B12DOUBLE

                  Mean value containing viewing incidence azimuth angle average for band B12 and for all detectors

                  MEAN_INCIDENCE_ZENITH_ANGLE_B1DOUBLE

                  Mean value containing viewing incidence zenith angle average for band B1 and for all detectors

                  MEAN_INCIDENCE_ZENITH_ANGLE_B2DOUBLE

                  Mean value containing viewing incidence zenith angle average for band B2 and for all detectors

                  MEAN_INCIDENCE_ZENITH_ANGLE_B3DOUBLE

                  Mean value containing viewing incidence zenith angle average for band B3 and for all detectors

                  MEAN_INCIDENCE_ZENITH_ANGLE_B4DOUBLE

                  Mean value containing viewing incidence zenith angle average for band B4 and for all detectors

                  MEAN_INCIDENCE_ZENITH_ANGLE_B5DOUBLE

                  Mean value containing viewing incidence zenith angle average for band B5 and for all detectors

                  MEAN_INCIDENCE_ZENITH_ANGLE_B6DOUBLE

                  Mean value containing viewing incidence zenith angle average for band B6 and for all detectors

                  MEAN_INCIDENCE_ZENITH_ANGLE_B7DOUBLE

                  Mean value containing viewing incidence zenith angle average for band B7 and for all detectors

                  MEAN_INCIDENCE_ZENITH_ANGLE_B8DOUBLE

                  Mean value containing viewing incidence zenith angle average for band B8 and for all detectors

                  MEAN_INCIDENCE_ZENITH_ANGLE_B8ADOUBLE

                  Mean value containing viewing incidence zenith angle average for band B8a and for all detectors

                  MEAN_INCIDENCE_ZENITH_ANGLE_B9DOUBLE

                  Mean value containing viewing incidence zenith angle average for band B9 and for all detectors

                  MEAN_INCIDENCE_ZENITH_ANGLE_B10DOUBLE

                  Mean value containing viewing incidence zenith angle average for band B10 and for all detectors

                  MEAN_INCIDENCE_ZENITH_ANGLE_B11DOUBLE

                  Mean value containing viewing incidence zenith angle average for band B11 and for all detectors

                  MEAN_INCIDENCE_ZENITH_ANGLE_B12DOUBLE

                  Mean value containing viewing incidence zenith angle average for band B12 and for all detectors

                  MEAN_SOLAR_AZIMUTH_ANGLEDOUBLE

                  Mean value containing sun azimuth angle average for all bands and detectors

                  MEAN_SOLAR_ZENITH_ANGLEDOUBLE

                  Mean value containing sun zenith angle average for all bands and detectors

                  MEDIUM_PROBA_CLOUDS_PERCENTAGEDOUBLE

                  Percentage of pixels classified as medium probability clouds

                  MGRS_TILESTRING

                  US-Military Grid Reference System (MGRS) tile

                  NODATA_PIXEL_PERCENTAGEDOUBLE

                  Percentage of No Data pixels

                  NOT_VEGETATED_PERCENTAGEDOUBLE

                  Percentage of pixels classified as non-vegetated

                  PROCESSING_BASELINESTRING

                  Configuration baseline used at the time of the product\n", + "Syntax and DS_Consistency) levels</p></td></tr><tr><td>GENERAL_QUALITY</td><td>STRING</td><td><p>Synthesis of the OLQC checks performed at the datastrip level (Relative_Orbit_Number)</p></td></tr><tr><td>GENERATION_TIME</td><td>DOUBLE</td><td><p>Product generation time</p></td></tr><tr><td>GEOMETRIC_QUALITY</td><td>STRING</td><td><p>Synthesis of the OLQC checks performed at the datastrip level (Attitude_Quality_Indicator)</p></td></tr><tr><td>GRANULE_ID</td><td>STRING</td><td><p>Unique identifier of the granule PDI (PDI_ID)</p></td></tr><tr><td>HIGH_PROBA_CLOUDS_PERCENTAGE</td><td>DOUBLE</td><td><p>Percentage of pixels classified as high probability clouds</p></td></tr><tr><td>MEAN_INCIDENCE_AZIMUTH_ANGLE_B1</td><td>DOUBLE</td><td><p>Mean value containing viewing incidence azimuth angle average for band B1 and for all detectors</p></td></tr><tr><td>MEAN_INCIDENCE_AZIMUTH_ANGLE_B2</td><td>DOUBLE</td><td><p>Mean value containing viewing incidence azimuth angle average for band B2 and for all detectors</p></td></tr><tr><td>MEAN_INCIDENCE_AZIMUTH_ANGLE_B3</td><td>DOUBLE</td><td><p>Mean value containing viewing incidence azimuth angle average for band B3 and for all detectors</p></td></tr><tr><td>MEAN_INCIDENCE_AZIMUTH_ANGLE_B4</td><td>DOUBLE</td><td><p>Mean value containing viewing incidence azimuth angle average for band B4 and for all detectors</p></td></tr><tr><td>MEAN_INCIDENCE_AZIMUTH_ANGLE_B5</td><td>DOUBLE</td><td><p>Mean value containing viewing incidence azimuth angle average for band B5 and for all detectors</p></td></tr><tr><td>MEAN_INCIDENCE_AZIMUTH_ANGLE_B6</td><td>DOUBLE</td><td><p>Mean value containing viewing incidence azimuth angle average for band B6 and for all detectors</p></td></tr><tr><td>MEAN_INCIDENCE_AZIMUTH_ANGLE_B7</td><td>DOUBLE</td><td><p>Mean value containing viewing incidence azimuth angle average for band B7 and for all detectors</p></td></tr><tr><td>MEAN_INCIDENCE_AZIMUTH_ANGLE_B8</td><td>DOUBLE</td><td><p>Mean value containing viewing incidence azimuth angle average for band B8 and for all detectors</p></td></tr><tr><td>MEAN_INCIDENCE_AZIMUTH_ANGLE_B8A</td><td>DOUBLE</td><td><p>Mean value containing viewing incidence azimuth angle average for band B8a and for all detectors</p></td></tr><tr><td>MEAN_INCIDENCE_AZIMUTH_ANGLE_B9</td><td>DOUBLE</td><td><p>Mean value containing viewing incidence azimuth angle average for band B9 and for all detectors</p></td></tr><tr><td>MEAN_INCIDENCE_AZIMUTH_ANGLE_B10</td><td>DOUBLE</td><td><p>Mean value containing viewing incidence azimuth angle average for band B10 and for all detectors</p></td></tr><tr><td>MEAN_INCIDENCE_AZIMUTH_ANGLE_B11</td><td>DOUBLE</td><td><p>Mean value containing viewing incidence azimuth angle average for band B11 and for all detectors</p></td></tr><tr><td>MEAN_INCIDENCE_AZIMUTH_ANGLE_B12</td><td>DOUBLE</td><td><p>Mean value containing viewing incidence azimuth angle average for band B12 and for all detectors</p></td></tr><tr><td>MEAN_INCIDENCE_ZENITH_ANGLE_B1</td><td>DOUBLE</td><td><p>Mean value containing viewing incidence zenith angle average for band B1 and for all detectors</p></td></tr><tr><td>MEAN_INCIDENCE_ZENITH_ANGLE_B2</td><td>DOUBLE</td><td><p>Mean value containing viewing incidence zenith angle average for band B2 and for all detectors</p></td></tr><tr><td>MEAN_INCIDENCE_ZENITH_ANGLE_B3</td><td>DOUBLE</td><td><p>Mean value containing viewing incidence zenith angle average for band B3 and for all detectors</p></td></tr><tr><td>MEAN_INCIDENCE_ZENITH_ANGLE_B4</td><td>DOUBLE</td><td><p>Mean value containing viewing incidence zenith angle average for band B4 and for all detectors</p></td></tr><tr><td>MEAN_INCIDENCE_ZENITH_ANGLE_B5</td><td>DOUBLE</td><td><p>Mean value containing viewing incidence zenith angle average for band B5 and for all detectors</p></td></tr><tr><td>MEAN_INCIDENCE_ZENITH_ANGLE_B6</td><td>DOUBLE</td><td><p>Mean value containing viewing incidence zenith angle average for band B6 and for all detectors</p></td></tr><tr><td>MEAN_INCIDENCE_ZENITH_ANGLE_B7</td><td>DOUBLE</td><td><p>Mean value containing viewing incidence zenith angle average for band B7 and for all detectors</p></td></tr><tr><td>MEAN_INCIDENCE_ZENITH_ANGLE_B8</td><td>DOUBLE</td><td><p>Mean value containing viewing incidence zenith angle average for band B8 and for all detectors</p></td></tr><tr><td>MEAN_INCIDENCE_ZENITH_ANGLE_B8A</td><td>DOUBLE</td><td><p>Mean value containing viewing incidence zenith angle average for band B8a and for all detectors</p></td></tr><tr><td>MEAN_INCIDENCE_ZENITH_ANGLE_B9</td><td>DOUBLE</td><td><p>Mean value containing viewing incidence zenith angle average for band B9 and for all detectors</p></td></tr><tr><td>MEAN_INCIDENCE_ZENITH_ANGLE_B10</td><td>DOUBLE</td><td><p>Mean value containing viewing incidence zenith angle average for band B10 and for all detectors</p></td></tr><tr><td>MEAN_INCIDENCE_ZENITH_ANGLE_B11</td><td>DOUBLE</td><td><p>Mean value containing viewing incidence zenith angle average for band B11 and for all detectors</p></td></tr><tr><td>MEAN_INCIDENCE_ZENITH_ANGLE_B12</td><td>DOUBLE</td><td><p>Mean value containing viewing incidence zenith angle average for band B12 and for all detectors</p></td></tr><tr><td>MEAN_SOLAR_AZIMUTH_ANGLE</td><td>DOUBLE</td><td><p>Mean value containing sun azimuth angle average for all bands and detectors</p></td></tr><tr><td>MEAN_SOLAR_ZENITH_ANGLE</td><td>DOUBLE</td><td><p>Mean value containing sun zenith angle average for all bands and detectors</p></td></tr><tr><td>MEDIUM_PROBA_CLOUDS_PERCENTAGE</td><td>DOUBLE</td><td><p>Percentage of pixels classified as medium probability clouds</p></td></tr><tr><td>MGRS_TILE</td><td>STRING</td><td><p>US-Military Grid Reference System (MGRS) tile</p></td></tr><tr><td>NODATA_PIXEL_PERCENTAGE</td><td>DOUBLE</td><td><p>Percentage of No Data pixels</p></td></tr><tr><td>NOT_VEGETATED_PERCENTAGE</td><td>DOUBLE</td><td><p>Percentage of pixels classified as non-vegetated</p></td></tr><tr><td>PROCESSING_BASELINE</td><td>STRING</td><td><p>Configuration baseline used at the time of the product\n", "generation in terms of processor software version and major Ground\n", - "Image Processing Parameters (GIPP) version

                  PRODUCT_IDSTRING

                  The full id of the original Sentinel-2 product

                  RADIATIVE_TRANSFER_ACCURACYDOUBLE

                  Accuracy of radiative transfer model

                  RADIOMETRIC_QUALITYSTRING

                  Based on the OLQC reports contained in the Datastrips/QI_DATA with RADIOMETRIC_QUALITY checklist name

                  REFLECTANCE_CONVERSION_CORRECTIONDOUBLE

                  Earth-Sun distance correction factor

                  SATURATED_DEFECTIVE_PIXEL_PERCENTAGEDOUBLE

                  Percentage of saturated or defective pixels

                  SENSING_ORBIT_DIRECTIONSTRING

                  Imaging orbit direction

                  SENSING_ORBIT_NUMBERDOUBLE

                  Imaging orbit number

                  SENSOR_QUALITYSTRING

                  Synthesis of the OLQC checks performed at granule\n", + "Image Processing Parameters (GIPP) version</p></td></tr><tr><td>PRODUCT_ID</td><td>STRING</td><td><p>The full id of the original Sentinel-2 product</p></td></tr><tr><td>RADIATIVE_TRANSFER_ACCURACY</td><td>DOUBLE</td><td><p>Accuracy of radiative transfer model</p></td></tr><tr><td>RADIOMETRIC_QUALITY</td><td>STRING</td><td><p>Based on the OLQC reports contained in the Datastrips/QI_DATA with RADIOMETRIC_QUALITY checklist name</p></td></tr><tr><td>REFLECTANCE_CONVERSION_CORRECTION</td><td>DOUBLE</td><td><p>Earth-Sun distance correction factor</p></td></tr><tr><td>SATURATED_DEFECTIVE_PIXEL_PERCENTAGE</td><td>DOUBLE</td><td><p>Percentage of saturated or defective pixels</p></td></tr><tr><td>SENSING_ORBIT_DIRECTION</td><td>STRING</td><td><p>Imaging orbit direction</p></td></tr><tr><td>SENSING_ORBIT_NUMBER</td><td>DOUBLE</td><td><p>Imaging orbit number</p></td></tr><tr><td>SENSOR_QUALITY</td><td>STRING</td><td><p>Synthesis of the OLQC checks performed at granule\n", "(Missing_Lines, Corrupted_ISP, and Sensing_Time) and datastrip\n", - "(Degraded_SAD and Datation_Model) levels

                  SOLAR_IRRADIANCE_B1DOUBLE

                  Mean solar exoatmospheric irradiance for band B1

                  SOLAR_IRRADIANCE_B2DOUBLE

                  Mean solar exoatmospheric irradiance for band B2

                  SOLAR_IRRADIANCE_B3DOUBLE

                  Mean solar exoatmospheric irradiance for band B3

                  SOLAR_IRRADIANCE_B4DOUBLE

                  Mean solar exoatmospheric irradiance for band B4

                  SOLAR_IRRADIANCE_B5DOUBLE

                  Mean solar exoatmospheric irradiance for band B5

                  SOLAR_IRRADIANCE_B6DOUBLE

                  Mean solar exoatmospheric irradiance for band B6

                  SOLAR_IRRADIANCE_B7DOUBLE

                  Mean solar exoatmospheric irradiance for band B7

                  SOLAR_IRRADIANCE_B8DOUBLE

                  Mean solar exoatmospheric irradiance for band B8

                  SOLAR_IRRADIANCE_B8ADOUBLE

                  Mean solar exoatmospheric irradiance for band B8a

                  SOLAR_IRRADIANCE_B9DOUBLE

                  Mean solar exoatmospheric irradiance for band B9

                  SOLAR_IRRADIANCE_B10DOUBLE

                  Mean solar exoatmospheric irradiance for band B10

                  SOLAR_IRRADIANCE_B11DOUBLE

                  Mean solar exoatmospheric irradiance for band B11

                  SOLAR_IRRADIANCE_B12DOUBLE

                  Mean solar exoatmospheric irradiance for band B12

                  SNOW_ICE_PERCENTAGEDOUBLE

                  Percentage of pixels classified as snow or ice

                  SPACECRAFT_NAMESTRING

                  Sentinel-2 spacecraft name: Sentinel-2A, Sentinel-2B

                  THIN_CIRRUS_PERCENTAGEDOUBLE

                  Percentage of pixels classified as thin cirrus clouds

                  UNCLASSIFIED_PERCENTAGEDOUBLE

                  Percentage of unclassified pixels

                  VEGETATION_PERCENTAGEDOUBLE

                  Percentage of pixels classified as vegetation

                  WATER_PERCENTAGEDOUBLE

                  Percentage of pixels classified as water

                  WATER_VAPOUR_RETRIEVAL_ACCURACYDOUBLE

                  Declared accuracy of the Water Vapor model

                  Terms of Use

                  The use of Sentinel data is governed by the Copernicus\n", - "Sentinel Data Terms and Conditions.

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                    • DATASTRIP_ID:S2A_USER_MSI_L2A_DS_MPS__20170328T123128_S20170328T084228_N02.04
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      " + "</style>
    • keywords: List (7 elements)
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      • 1:esa
      • 2:eu
      • 3:msi
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    • period:0
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    • provider:European Union/ESA/Copernicus
    • provider_url:https://earth.esa.int/web/sentinel/user-guides/sentinel-2-msi/product-types/level-2a
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    • tags: List (7 elements)
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    • thumb:https://mw1.google.com/ges/dd/images/COPERNICUS_S2_SR_thumb.png
    • title:Sentinel-2 MSI: MultiSpectral Instrument, Level-2A
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          • RADIATIVE_TRANSFER_ACCURAY:0
          • RADIOMETRIC_QUALITY_FLAG:PASSED
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          • SENSING_ORBIT_DIRECTION:DESCENDING
          • SENSING_ORBIT_NUMBER:64
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          • SOLAR_IRRADIANCE_B10:367.15
          • SOLAR_IRRADIANCE_B11:245.59
          • SOLAR_IRRADIANCE_B12:85.25
          • SOLAR_IRRADIANCE_B2:1941.63
          • SOLAR_IRRADIANCE_B3:1822.61
          • SOLAR_IRRADIANCE_B4:1512.79
          • SOLAR_IRRADIANCE_B5:1425.56
          • SOLAR_IRRADIANCE_B6:1288.32
          • SOLAR_IRRADIANCE_B7:1163.19
          • SOLAR_IRRADIANCE_B8:1036.39
          • SOLAR_IRRADIANCE_B8A:955.19
          • SOLAR_IRRADIANCE_B9:813.04
          • SPACECRAFT_NAME:Sentinel-2A
          • THIN_CIRRUS_PERCENTAGE:0
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          • WATER_PERCENTAGE:0.074907
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      • 1: Image COPERNICUS/S2_SR_HARMONIZED/20170328T083601_20170328T084228_T35RNL (26 bands)
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        • properties: Object (82 properties)
          • AOT_RETRIEVAL_ACCURACY:0
          • BARE_SOILS_PERCENTAGE:95.071429
          • CLOUDY_PIXEL_PERCENTAGE:1.4639
          • CLOUD_COVERAGE_ASSESSMENT:1.4639
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          • FORMAT_CORRECTNESS_FLAG:PASSED
          • GENERAL_QUALITY_FLAG:PASSED
          • GENERATION_TIME:1490845271000
          • GEOMETRIC_QUALITY_FLAG:PASSED
          • GRANULE_ID:L2A_T35RNL_A009213_20170328T084228
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          • MEDIUM_PROBA_CLOUDS_PERCENTAGE:0.201293
          • MGRS_TILE:35RNL
          • NODATA_PIXEL_PERCENTAGE:28.142375
          • PROCESSING_BASELINE:02.04
          • PRODUCT_ID:S2A_MSIL2A_20170328T083601_N0204_R064_T35RNL_20170328T084228
          • RADIATIVE_TRANSFER_ACCURAY:0
          • RADIOMETRIC_QUALITY_FLAG:PASSED
          • REFLECTANCE_CONVERSION_CORRECTION:1.00613186852888
          • SATURATED_DEFECTIVE_PIXEL_PERCENTAGE:0
          • SENSING_ORBIT_DIRECTION:DESCENDING
          • SENSING_ORBIT_NUMBER:64
          • SENSOR_QUALITY_FLAG:PASSED
          • SNOW_ICE_PERCENTAGE:0
          • SOLAR_IRRADIANCE_B1:1913.57
          • SOLAR_IRRADIANCE_B10:367.15
          • SOLAR_IRRADIANCE_B11:245.59
          • SOLAR_IRRADIANCE_B12:85.25
          • SOLAR_IRRADIANCE_B2:1941.63
          • SOLAR_IRRADIANCE_B3:1822.61
          • SOLAR_IRRADIANCE_B4:1512.79
          • SOLAR_IRRADIANCE_B5:1425.56
          • SOLAR_IRRADIANCE_B6:1288.32
          • SOLAR_IRRADIANCE_B7:1163.19
          • SOLAR_IRRADIANCE_B8:1036.39
          • SOLAR_IRRADIANCE_B8A:955.19
          • SOLAR_IRRADIANCE_B9:813.04
          • SPACECRAFT_NAME:Sentinel-2A
          • THIN_CIRRUS_PERCENTAGE:0
          • VEGETATION_PERCENTAGE:0.413109
          • WATER_PERCENTAGE:0.107508
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      • 2: Image COPERNICUS/S2_SR_HARMONIZED/20170328T083601_20170328T084228_T35RNM (26 bands)
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      • " ], "text/plain": [ - "" + "" ] }, "execution_count": 4, @@ -360,21 +323,14 @@ } ], "source": [ - "ee.ImageCollection(\"COPERNICUS/S2_SR\").limit(10)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Performance and Error Handling" + "ee.ImageCollection(\"COPERNICUS/S2_SR_HARMONIZED\").limit(3)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Just like in the Code Editor, printing an object with `eerepr` requests data from the server, so large objects may take a while or even time out. If `eerepr` fails to retrieve data it will fall back to the string repr and warn you about the error it encountered. For example, if we try to display an invalid `ee.Projection`..." + "IPython only displays the last object evaluated in a cell. To display multiple HTML reprs, you can use `IPython.display.display`." ] }, { @@ -382,80 +338,12 @@ "execution_count": 5, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/az/eerepr/eerepr/repr.py:43: UserWarning: Getting info failed with: 'Projection: The CRS of a map projection could not be parsed.'. Falling back to string repr.\n", - " warn(f\"Getting info failed with: '{e}'. Falling back to string repr.\")\n" - ] - }, { "data": { "text/html": [ - "
      <ee.Projection object at 0x7fe8d5bc7fa0>
      " - ], - "text/plain": [ - "" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "ee.Projection(\"foo\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Caching" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "`eerepr` caches results within each Jupyter session, so a large request will run slowly the first time but should be nearly instant if you repeat it." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "fc = ee.FeatureCollection(\"WRI/GPPD/power_plants\").limit(1_000)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "First run takes a few seconds to retrieve data." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
        • type:FeatureCollection
        • id:WRI/GPPD/power_plants
        • version:1577374742750831
          • cap_year:Float
          • capacitymw:Float
          • comm_year:Float
          • country:String
          • country_lg:String
          • fuel1:String
          • fuel2:String
          • fuel3:String
          • fuel4:String
          • gppd_idnr:String
          • gwh_2013:Float
          • gwh_2014:Float
          • gwh_2015:Float
          • gwh_2016:Float
          • gwh_estimt:Float
          • latitude:Float
          • longitude:Float
          • name:String
          • owner:String
          • source:String
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          • system:index:String
          • url:String
            • 0:1528675200000
            • 1:1528675200000
          • description:

            The Global Power Plant Database is a comprehensive, open source\n", - "database of power plants around the world. It centralizes\n", - "power plant data to make it easier to navigate, compare and draw\n", - "insights. Each power plant is geolocated and entries contain\n", - "information on plant capacity, generation, ownership, and fuel type.\n", - "As of June 2018, the database includes around 28,500 power plants\n", - "from 164 countries.\n", - "It will be continuously updated as data becomes available.

            The methodology for the dataset creation is given in the World Resources\n", - "Institute publication\n", - "\"A Global Database of Power Plants\".

            Associated code for the creation of the dataset can be found on\n", - "GitHub.\n", - "The bleeding-edge version of the database (which may contain substantial\n", - "differences from the release in Earth Engine) is available on GitHub as well.

            If you use this dataset, the provider (WRI) has requested that you\n", - "register your use and (optionally)\n", - "sign up to receive update notifications.

            Table Schema
            NameTypeDescription
            countrySTRING

            3-character country code corresponding to the ISO 3166-1 alpha-3 specs

            country_lgSTRING

            Longer form of the country designation

            nameSTRING

            Name or title of the power plant, generally in Romanized form

            gppd_idnrSTRING

            10- or 12-character identifier for the power plant

            capacitymwDOUBLE

            Electrical generating capacity in megawatts

            latitudeDOUBLE

            Geolocation in decimal degrees

            longitudeDOUBLE

            Geolocation in decimal degrees

            fuel1STRING

            Energy source used in electricity generation or export

            fuel2STRING

            Energy source used in electricity generation or export

            fuel3STRING

            Energy source used in electricity generation or export

            fuel4STRING

            Energy source used in electricity generation or export

            comm_yearSTRING

            Year of plant operation, weighted by unit-capacity when data is available

            ownerSTRING

            Majority shareholder of the power plant, generally in Romanized form

            sourceSTRING

            Entity reporting the data; could be an organization, report, or document,\n", - "generally in Romanized form

            urlSTRING

            Web document corresponding to the \"source\" field

            src_latlonSTRING

            Attribution for geolocation information

            cap_yearDOUBLE

            Year the capacity information was reported

            gwh_2013DOUBLE

            Electricity generation in gigawatt-hours reported for the year 2013

            gwh_2014DOUBLE

            Electricity generation in gigawatt-hours reported for the year 2014

            gwh_2015DOUBLE

            Electricity generation in gigawatt-hours reported for the year 2015

            gwh_2016DOUBLE

            Electricity generation in gigawatt-hours reported for the year 2016

            gwh_estimtDOUBLE

            Estimated annual electricity generation in gigawatt-hours for the year\n", - "2015

            Terms of Use

            This dataset is licensed under\n", - "CC-BY 4.0.

            Suggested citation(s)

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      • Hello
      " ], "text/plain": [ - "" + "" ] }, - "execution_count": 7, "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "fc" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Second run pulls data from the cache. Much faster!" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ + "output_type": "display_data" + }, { "data": { "text/html": [ - "
        • type:FeatureCollection
        • id:WRI/GPPD/power_plants
        • version:1577374742750831
          • cap_year:Float
          • capacitymw:Float
          • comm_year:Float
          • country:String
          • country_lg:String
          • fuel1:String
          • fuel2:String
          • fuel3:String
          • fuel4:String
          • gppd_idnr:String
          • gwh_2013:Float
          • gwh_2014:Float
          • gwh_2015:Float
          • gwh_2016:Float
          • gwh_estimt:Float
          • latitude:Float
          • longitude:Float
          • name:String
          • owner:String
          • source:String
          • src_latlon:String
          • system:index:String
          • url:String
            • 0:1528675200000
            • 1:1528675200000
          • description:

            The Global Power Plant Database is a comprehensive, open source\n", - "database of power plants around the world. It centralizes\n", - "power plant data to make it easier to navigate, compare and draw\n", - "insights. Each power plant is geolocated and entries contain\n", - "information on plant capacity, generation, ownership, and fuel type.\n", - "As of June 2018, the database includes around 28,500 power plants\n", - "from 164 countries.\n", - "It will be continuously updated as data becomes available.

            The methodology for the dataset creation is given in the World Resources\n", - "Institute publication\n", - "\"A Global Database of Power Plants\".

            Associated code for the creation of the dataset can be found on\n", - "GitHub.\n", - "The bleeding-edge version of the database (which may contain substantial\n", - "differences from the release in Earth Engine) is available on GitHub as well.

            If you use this dataset, the provider (WRI) has requested that you\n", - "register your use and (optionally)\n", - "sign up to receive update notifications.

            Table Schema
            NameTypeDescription
            countrySTRING

            3-character country code corresponding to the ISO 3166-1 alpha-3 specs

            country_lgSTRING

            Longer form of the country designation

            nameSTRING

            Name or title of the power plant, generally in Romanized form

            gppd_idnrSTRING

            10- or 12-character identifier for the power plant

            capacitymwDOUBLE

            Electrical generating capacity in megawatts

            latitudeDOUBLE

            Geolocation in decimal degrees

            longitudeDOUBLE

            Geolocation in decimal degrees

            fuel1STRING

            Energy source used in electricity generation or export

            fuel2STRING

            Energy source used in electricity generation or export

            fuel3STRING

            Energy source used in electricity generation or export

            fuel4STRING

            Energy source used in electricity generation or export

            comm_yearSTRING

            Year of plant operation, weighted by unit-capacity when data is available

            ownerSTRING

            Majority shareholder of the power plant, generally in Romanized form

            sourceSTRING

            Entity reporting the data; could be an organization, report, or document,\n", - "generally in Romanized form

            urlSTRING

            Web document corresponding to the \"source\" field

            src_latlonSTRING

            Attribution for geolocation information

            cap_yearDOUBLE

            Year the capacity information was reported

            gwh_2013DOUBLE

            Electricity generation in gigawatt-hours reported for the year 2013

            gwh_2014DOUBLE

            Electricity generation in gigawatt-hours reported for the year 2014

            gwh_2015DOUBLE

            Electricity generation in gigawatt-hours reported for the year 2015

            gwh_2016DOUBLE

            Electricity generation in gigawatt-hours reported for the year 2016

            gwh_estimtDOUBLE

            Estimated annual electricity generation in gigawatt-hours for the year\n", - "2015

            Terms of Use

            This dataset is licensed under\n", - "CC-BY 4.0.

            Suggested citation(s)

          • period:0
            • 0:infrastructure
            • 1:energy
            • 2:climate
            • 3:power
            • 4:power_plants
          • provider:World Resources Institute
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              • name:GISSI
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              • url:http://www.a2a.eu/en/plants_networks/thermoelectric/gissi/
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      " + ".eerepr details summary {\n", + " list-style-type: none;\n", + "}\n", + "
      • World
      " ], "text/plain": [ - "" + "" ] }, - "execution_count": 8, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from IPython.display import display\n", + "\n", + "display(ee.String(\"Hello\"))\n", + "display(ee.String(\"World\"))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "If you want to go back to string reprs, `eerepr.reset()` will remove the registered methods." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "fc" + "eerepr.reset()\n", + "\n", + "ee.ImageCollection(\"COPERNICUS/S2_SR_HARMONIZED\").limit(3)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Configuration\n", + "\n", + "`eerepr.initialize` accepts configuration parameters to modify caching, error handling, and performance.\n", + "\n", + "### Caching\n", + "\n", + "By default, `eerepr` keeps an unbounded cache of all computed objects in-memory to speed up future requests. If you have limited memory or are accessing datasets that change rapidly, you can reduce the cache size or disable it completely with the `max_cache_size` parameter." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "# Default unbounded cache\n", + "eerepr.initialize(max_cache_size=None)\n", + "\n", + "# Keep a maximum of 100 objects in the cache\n", + "eerepr.initialize(max_cache_size=100)\n", + "\n", + "# Disable caching\n", + "eerepr.initialize(max_cache_size=0)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Running `eerepr.initialize()` or `eerepr.reset()` will both clear the existing cache." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Error Handling\n", + "\n", + "By default, a warning will be raised when a server-side error is encountered. To throw the error instead, you can adjust the `on_error` parameter from `\"warn\"` to `\"raise\"`." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "# Server errors will raise a warning\n", + "eerepr.initialize(on_error=\"warn\")\n", + "\n", + "# Server errors will raise an exception\n", + "eerepr.initialize(on_error=\"raise\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Large Objects\n", + "\n", + "Displaying an object requires fetching data from the server, which may be slow. Large objects with hundreds of images or features can also create huge reprs that lock up your IDE. To avoid that, `eerepr` sets a default maximum repr size of 100 megabytes and falls back to the string repr with a warning when that limit is exceeded. You can display larger objects by increasing `max_repr_mbs`, but you may run into performance issues." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "# Display reprs up to 500 MB\n", + "eerepr.initialize(max_repr_mbs=500)" ] } ], "metadata": { "kernelspec": { - "display_name": "Python 3.8.13 ('eerepr')", + "display_name": "test", "language": "python", "name": "python3" }, @@ -786,14 +667,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.13" + "version": "3.10.13" }, - "orig_nbformat": 4, - "vscode": { - "interpreter": { - "hash": "d36efdd541cf2b2978c22bb1c3426113f56ad726cfd18ca7d3e04ddebc729720" - } - } + "orig_nbformat": 4 }, "nbformat": 4, "nbformat_minor": 2