snapshot...

modules/util/plot.py

-#!/usr/bin/env python3
-# -*- coding: utf-8 -*-
-
-
 from sklearn.metrics import roc_auc_score, roc_curve
 import tensorflow as tf
 import matplotlib
@@ -317,10 +313,38 @@ def make_icing_image(h5f, probs, ice_lons, ice_lats, clvrx_str_time, satellite,
     fig.savefig(ImageDirAndName)
 
 
+def plot_grid2d(grid_2d, x_map_2d, y_map_2d, proj, vmin=None, vmax=None, cmap='jet'):
+    import matplotlib.pyplot as plt
+    import cartopy.crs as ccrs
+
+    fig = plt.figure(figsize=(10, 10))
+    ax = fig.add_subplot(1, 1, 1, projection=proj)
+
+    # Save mappable object returned by pcolormesh
+    p = ax.pcolormesh(x_map_2d, y_map_2d, grid_2d, vmin=270.0, vmax=310.0, cmap='jet', shading='auto')
+
+    ax.coastlines(resolution='50m', color='green', linewidth=1.50)
+
+    # Add gridlines for longitudes and latitudes
+    gl = ax.gridlines(crs=ccrs.PlateCarree(), draw_labels=True,
+                      linewidth=2, color='gray', alpha=0.5, linestyle='--')
+
+    gl.xlabels_top = gl.ylabels_right = False
+    gl.ylabel_style = {'rotation': 90}
+    gl.ylabel_padding = 15
+
+    # Add color bar
+    cbar = plt.colorbar(p, orientation="horizontal", pad=0.05)
+    cbar.set_label('Value', size=15)  # Set color bar label
+
+    plt.show()
+    # plt.close()
+
+
 # values, edges in Epoch time
 def make_time_domain_hist(values, edges):
     # convert the epoch format to matplotlib date format
-    #mpl_data = mdates.epoch2num(values)
+    # mpl_data = mdates.epoch2num(values)
 
     fig, ax = plt.subplots(1, 1)
     ax.hist(values, bins=edges, ec='black')