CSLC: use scipy for computing coherence

CSLC/Discover/Create_Interferogram_by_Streaming_CSLC-S1.ipynb

@@ -77,7 +77,8 @@
     "import matplotlib as mpl\n",
     "import sys\n",
     "sys.path.append('../../')\n",
-    "from src.cslc_utils import get_s3path, read_cslc, cslc_info, rasterWrite, custom_merge, colorize, getbasemaps, moving_window_mean\n",
+    "from src.cslc_utils import get_s3path, read_cslc, cslc_info, rasterWrite, custom_merge, colorize, getbasemaps\n",
+    "from scipy.ndimage import uniform_filter\n",
     "\n",
     "import warnings\n",
     "warnings.filterwarnings('ignore')"
@@ -473,7 +474,7 @@
    "source": [
     "# Calculate the correlation/coherence\n",
     "merged_ifg_cpx = np.exp(1j * np.nan_to_num(merged_ifg))\n",
-    "coh = np.clip(np.abs(moving_window_mean(merged_ifg_cpx, 10)), 0, 1)\n",
+    "coh = np.clip(np.abs(uniform_filter(merged_ifg_cpx, 10)), 0, 1)\n",
     "\n",
     "# Mask nan values and zero values based on merged ifg file\n",
     "nan_mask = np.isnan(merged_ifg)\n",