snapshot...

modules/util/plot.py

@@ -10,6 +10,7 @@ from sklearn.metrics import roc_auc_score, roc_curve
 import tensorflow as tf
 import matplotlib
 import matplotlib.pyplot as plt
+import matplotlib.dates as mdates
 import cartopy.crs as ccrs
 import xarray as xr
 import os
@@ -241,4 +242,17 @@ def make_icing_image(clvrx_file, ice_lons, ice_lats, ice_lons_vld=None, ice_lats
         ax.scatter(ice_lons_vld, ice_lats_vld, s=20.0, marker='o', color='blue', transform=ccrs.PlateCarree())
     plt.title('GOES-16, 2019-04-30_18:26Z  >60% Probability Icing', loc='left', fontweight='bold', fontsize=15)
     ImageDirAndName = os.path.join('/Users/tomrink', filename)
-    fig.savefig(ImageDirAndName)
\ No newline at end of file
+    fig.savefig(ImageDirAndName)
+
+
+# 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)
+
+    fig, ax = plt.subplots(1, 1)
+    ax.hist(values, bins=edges, ec='black')
+    #ax.xaxis.set_major_locator(mdates.MonthLocator())
+    #ax.xaxis.set_major_formatter(mdates.DateFormatter('%y-%m-%d_%h'))
+    #fig.autofmt_xdate()
+    plt.show()