snapshot...

modules/util/acspo_validate.py

@@ -32,6 +32,7 @@ def acspo_validate(oper_file, cspp_file, rel_tol=0.001, outfile_nc=None):
     cspp_clear = (l2p_flags_cspp & (1 << 15)) == 0
     oper_clear = (l2p_flags_oper & (1 << 15)) == 0
 
+    # Find the overlap Track indexes relative to each ------------------------
     start_idx_oper, stop_idx_oper = -1, -1
     start_idx_cspp, stop_idx_cspp = -1, -1
 
@@ -47,6 +48,7 @@ def acspo_validate(oper_file, cspp_file, rel_tol=0.001, outfile_nc=None):
 
     print('oper start, stop ', start_idx_oper, stop_idx_oper)
     print('cspp start, stop ', start_idx_cspp, stop_idx_cspp)
+    # --------------------------------------------------------------------------
 
     lon_cspp = lon_cspp[start_idx_cspp:stop_idx_cspp, :]
     lat_cspp = lat_cspp[start_idx_cspp:stop_idx_cspp, :]
@@ -58,8 +60,8 @@ def acspo_validate(oper_file, cspp_file, rel_tol=0.001, outfile_nc=None):
     print('overlap shape, size: ', overlap_shape, np.size(lon_cspp))
 
     # check lon/lat arrays ------------------------------------
-    print(np.sum(np.isclose(lon_cspp, lon_oper, rtol=rel_tol)))
-    print(np.sum(np.isclose(lat_cspp, lat_oper, rtol=rel_tol)))
+    print('num of close overlap lons: ', np.sum(np.isclose(lon_cspp, lon_oper, rtol=rel_tol)))
+    print('num of close overlap lats: ', np.sum(np.isclose(lat_cspp, lat_oper, rtol=rel_tol)))
 
     sst_cspp_2d = sst_cspp[start_idx_cspp:stop_idx_cspp, :]
     sst_oper_2d = sst_oper[start_idx_oper:stop_idx_oper, :]
@@ -75,6 +77,7 @@ def acspo_validate(oper_file, cspp_file, rel_tol=0.001, outfile_nc=None):
     lat_cspp = lat_cspp.flatten()
     lon_oper = lon_oper.flatten()
     lat_oper = lat_oper.flatten()
+
     both_clear = oper_clear & cspp_clear
     sst_cspp = sst_cspp[both_clear]
     sst_oper = sst_oper[both_clear]
@@ -82,9 +85,10 @@ def acspo_validate(oper_file, cspp_file, rel_tol=0.001, outfile_nc=None):
     lat_cspp = lat_cspp[both_clear]
     lon_oper = lon_oper[both_clear]
     lat_oper = lat_oper[both_clear]
+    print('number of clear pixels in both: ', np.sum(both_clear))
 
     both_valid = np.invert(np.isnan(sst_cspp)) & np.invert(np.isnan(sst_oper))
-    print('number of clear and valid SSTs in both: ', np.sum(both_valid))
+    print('number of clear pixels with valid SSTs in both: ', np.sum(both_valid))
     valid_sst_cspp = sst_cspp[both_valid]
     valid_sst_oper = sst_oper[both_valid]
     valid_lon_cspp = lon_cspp[both_valid]
@@ -105,7 +109,6 @@ def acspo_validate(oper_file, cspp_file, rel_tol=0.001, outfile_nc=None):
 
     print('fraction approx equal: ',
           np.sum(np.isclose(valid_sst_cspp, valid_sst_oper, rtol=rel_tol))/np.sum(both_valid))
-    # print(np.histogram((sst_cspp[both_valid] - sst_oper[both_valid]), bins=10))
 
     h5f_oper.close()
     h5f_cspp.close()
@@ -122,11 +125,13 @@ def analyze_plot():
     h5f_e = h5py.File('/Users/tomrink/20241107171000.nc', 'r')
     h5f_f = h5py.File('/Users/tomrink/20241107202000.nc', 'r')
     h5f_g = h5py.File('/Users/tomrink/20241107203000.nc', 'r')
+
     import numpy as np
     sst_cspp_all = np.concatenate([h5f_a['sst_cspp'][0, :], h5f_b['sst_cspp'][0, :], h5f_c['sst_cspp'][0, :], h5f_d['sst_cspp'][0, :], h5f_e['sst_cspp'][0, :], h5f_f['sst_cspp'][0, :], h5f_g['sst_cspp'][0, :]])
-    sst_cspp_all.shape
+    print(sst_cspp_all.shape)
     sst_oper_all = np.concatenate([h5f_a['sst_oper'][0, :], h5f_b['sst_oper'][0, :], h5f_c['sst_oper'][0, :], h5f_d['sst_oper'][0, :], h5f_e['sst_oper'][0, :], h5f_f['sst_oper'][0, :], h5f_g['sst_oper'][0, :]])
-    sst_oper_all.shape
+    print(sst_oper_all.shape)
+
     diff = sst_cspp_all - sst_oper_all
     import matplotlib.pyplot as plt
     plt.hist(diff, bins=40)