cleaned up landsat analysis using VScode

azure-landsat/landsat-hls-azure.py

@@ -1,6 +1,4 @@
 #!/usr/bin/env python3
-# need to install - pip install azure-storage-blob
-# https://nbviewer.org/github/microsoft/AIforEarthDataSets/blob/main/data/hls.ipynb
 
 # Environment setup
 import requests
@@ -75,8 +73,8 @@ def lat_lon_to_hls_tile_id(lat,lon):
 
 # Build a tile path from components, including lat/lon lookup
 # Near Bear Lake, UT
-# lat = 41.89655047211277; lon = -111.4132464403312 
-lat = 39.768402; lon = -86.158066 
+lat = 41.89655047211277; lon = -111.4132464403312 
+# lat = 39.768402; lon = -86.158066 
 
 tile_id = lat_lon_to_hls_tile_id(lat,lon)
 print('Using Tile ID {}'.format(tile_id))
@@ -120,8 +118,8 @@ def lat_lon_to_hls_tile_id(lat,lon):
 
 dpi = 100; fig = plt.figure(frameon=False,figsize=(w/dpi,h/dpi),dpi=dpi)
 ax = plt.Axes(fig,[0., 0., 1., 1.]); ax.set_axis_off(); fig.add_axes(ax)
-plt.imshow(rgb);
-plt.imsave('test.png', rgb)
+# plt.imshow(rgb);
+# plt.imsave('test.png', rgb)
 
 i_daynum = int(daynum)
 product = 'L30'
@@ -165,5 +163,6 @@ def lat_lon_to_hls_tile_id(lat,lon):
 
 dpi = 100; fig = plt.figure(frameon=False,figsize=(w/dpi,h/dpi),dpi=dpi)
 ax = plt.Axes(fig,[0., 0., 1., 1.]); ax.set_axis_off(); fig.add_axes(ax)
-plt.imshow(rgb);
-plt.show()
+# plt.imshow(rgb);
+# plt.show()
+plt.imsave('test.png', rgb)