snapshot...

modules/icing/util.py

@@ -1081,7 +1081,8 @@ def run_icing_predict_image(clvrx_dir='/Users/tomrink/data/clavrx/RadC/', output
                             l1b_andor_l2='BOTH', use_flight_altitude=True, flight_levels=[0, 1, 2, 3, 4],
                             res_fac=1, model_type='CNN', extent=[-105, -70, 15, 50], pirep_file=None, icing_dict=None,
                             data_extent=None, use_max_cth_level=False,
-                            obs_lons=None, obs_lats=None, obs_times=None, obs_alt=None, obs_intensity=None):
+                            obs_lons=None, obs_lats=None, obs_times=None, obs_alt=None, obs_intensity=None,
+                            icing_intensity_plot_min=1):
     if model_type == 'CNN':
         import deeplearning.icing_cnn as icing_cnn
         model_module = icing_cnn
@@ -1261,7 +1262,7 @@ def run_icing_predict_image(clvrx_dir='/Users/tomrink/data/clavrx/RadC/', output
         elif obs_times is not None:
             keep = np.logical_and(obs_times >= ts_0, obs_times < ts_1)
             keep = np.where(keep, np.logical_and(obs_alt >= alt_lo, obs_alt < alt_hi), False)
-            keep = np.where(keep, obs_intensity > 1, False)
+            keep = np.where(keep, obs_intensity >= icing_intensity_plot_min, False)
             keep_lons = obs_lons[keep]
             keep_lats = obs_lats[keep]
         else: