switch to total column prediction for now - need more R&D

modules/util/plot.py

@@ -206,36 +206,27 @@ def plot_image2(image, cmap='Greys'):
     plt.close()  # Close current figure
 
 
-# Example GOES file to retrieve GEOS parameters in MetPy form (CONUS)
-exmp_file = '/Users/tomrink/data/OR_ABI-L1b-RadC-M6C14_G16_s20193140811215_e20193140813588_c20193140814070.nc'
-# Full Disk
-#exmp_file = '/Users/tomrink/data/OR_ABI-L1b-RadF-M6C16_G16_s20212521800223_e20212521809542_c20212521809596.nc'
-exmp_name = 'Rad'
-# exmp_file = '/Users/tomrink/data/H08/HS_H08_20200601_0330_B01_FLDK.nc'
-# exmp_name = 'RAD'
-
-
-def plot_image3(image, cmap='Greys'):
-    exmpl_ds = xr.open_dataset(exmp_file)
-    mdat = exmpl_ds.metpy.parse_cf(exmp_name)
-    geos = mdat.metpy.cartopy_crs
-    x = mdat.x
-    y = mdat.y
+def plot_image3(image, bt, cmap='Greys'):
+
+    geos, xlen, xmin, xmax, ylen, ymin, ymax = get_cartopy_crs('GOES16', 'CONUS')
 
     fig = plt.figure(figsize=(15, 12))
     ax = fig.add_subplot(1, 1, 1, projection=geos)
     ax.set_extent([-105, -70, 15, 50], crs=ccrs.PlateCarree())
-    ax.imshow(image, cmap=cmap, origin='upper', extent=(x.min(), x.max(), y.min(), y.max()), transform=geos)
+    #ax.imshow(bt, cmap=cmap, origin='upper', extent=(xmin, xmax, ymin, ymax), transform=geos)
+    #ax.imshow(image, cmap='YlGnBu', origin='upper', extent=(xmin, xmax, ymin, ymax), vmin=0.6, vmax=1.0, transform=geos)
+    ax.imshow(image, cmap='Blues', origin='upper', extent=(xmin, xmax, ymin, ymax), vmin=0.52, vmax=1.0, transform=geos)
     ax.coastlines(resolution='50m', color='blue', linewidth=0.25)
-    # ax.add_feature(ccrs.cartopy.feature.STATES, linewidth=0.25)
+    ax.add_feature(ccrs.cartopy.feature.STATES, linewidth=0.25)
     plt.title('GOES-16', loc='left', fontweight='bold', fontsize=15)
     fig.savefig('/Users/tomrink/image')
 
 
-def make_icing_image(h5f, ice_lons, ice_lats, clvrx_str_time, satellite, domain, ice_lons_vld=None, ice_lats_vld=None, imagename='icing', extent=[-110, -60, 10, 55]):
-    image = get_grid_values_all(h5f, 'temp_10_4um_nom')
-
+def make_icing_image(h5f, probs, ice_lons, ice_lats, clvrx_str_time, satellite, domain, ice_lons_vld=None, ice_lats_vld=None, imagename='icing', extent=[-110, -60, 10, 55]):
     geos, xlen, xmin, xmax, ylen, ymin, ymax = get_cartopy_crs(satellite, domain)
+    bg_image = None
+    if h5f is not None:
+        bg_image = get_grid_values_all(h5f, 'temp_10_4um_nom')
 
     fig = plt.figure(figsize=(48, 30))
     ax = fig.add_subplot(1, 1, 1, projection=geos)
@@ -244,15 +235,17 @@ def make_icing_image(h5f, ice_lons, ice_lats, clvrx_str_time, satellite, domain,
             ax.set_extent(extent, crs=geos)
         else:
             ax.set_extent(extent, crs=ccrs.PlateCarree())
-    ax.imshow(image, origin='upper', extent=(xmin, xmax, ymin, ymax), cmap='Greys', transform=geos)
+    if bg_image is not None:
+        ax.imshow(bg_image, origin='upper', extent=(xmin, xmax, ymin, ymax), cmap='Greys', transform=geos)
+    if probs is not None:
+        ax.imshow(probs, cmap='Blues', origin='upper', extent=(xmin, xmax, ymin, ymax), vmin=0.52, vmax=1.0, transform=geos)
     ax.coastlines(resolution='50m', color='green', linewidth=1.50)
     # ax.add_feature(ccrs.cartopy.feature.STATES, linewidth=0.25)
 
     if ice_lons is not None:
         ax.scatter(ice_lons, ice_lats, s=40.0, marker='o', color='blue', transform=ccrs.PlateCarree())
     if ice_lats_vld is not None:
-        #ax.scatter(ice_lons_vld, ice_lats_vld, s=140.0, facecolors='none', marker='o', edgecolor='red', transform=ccrs.PlateCarree())
-        ax.scatter(ice_lons_vld, ice_lats_vld, s=140.0, marker='o', color='red', transform=ccrs.PlateCarree())
+        ax.scatter(ice_lons_vld, ice_lats_vld, s=180.0, marker='o', color='red', transform=ccrs.PlateCarree())
 
     title = satellite+', '+clvrx_str_time+'  >50% Probability Icing'
     plt.title(title, loc='left', fontweight='bold', fontsize=24)