snapshot...

modules/aeolus/aeolus_amv.py

@@ -6,6 +6,7 @@ import xarray as xr
 from netCDF4 import Dataset, Dimension, Variable
 from aeolus.geos_nav import GEOSNavigation
 from util.util import haversine_np
+from amv.intercompare import best_fit
 import math
 
 
@@ -158,7 +159,7 @@ class CarrStereo(AMVFiles):
 
 # raob_dict: time -> profiles
 # amv_files_path: directory containing AMVs, '/home/user/amvdir/'
-# return dict: aeolus time -> tuple (amv_lon, amv_lat, amv_pres, amv_spd, amv_dir)
+# return dict: raob -> tuple (amv_lon, amv_lat, amv_pres, amv_spd, amv_dir)
 def match_amvs_to_raobs(raob_dict,  raob_time, amv_files):
     nav = amv_files.get_navigation()
     amv_params = amv_files.get_parameters()
@@ -315,6 +316,33 @@ def create_file2(filename, raob_to_amv_dct, raob_dct, amv_files):
     rootgrp.close()
 
 
+def analyze2(raob_to_amv_dct, raob_dct):
+    keys = list(raob_to_amv_dct.keys())
+
+    for key in keys:
+        rlat = key[0]
+        rlon = key[1]
+
+        raob = raob_dct.get(key)
+        nlevs = raob.shape[0]
+        raob_prs = raob[:, 0]
+        raob_spd = raob[:, 3]
+        raob_dir = raob[:, 2]
+        amvs = raob_to_amv_dct.get(key)
+        num_amvs = amvs.shape[1]
+        for i in range(num_amvs):
+            amv_lon = amvs[0, i]
+            amv_lat = amvs[1, i]
+            amv_prs = amvs[4, i]
+            amv_spd = amvs[5, i]
+            amv_dir = amvs[6, i]
+
+            bf = best_fit(amv_spd, amv_dir, amv_prs, amv_lat, amv_lon, raob_spd, raob_dir, raob_prs)
+            if bf[3] == 0:
+                print(nlevs, amv_prs, bf[2])
+
+
+
 # imports the S4 NOAA output
 # filename: full path as a string, '/home/user/filename'
 # returns a dict: time -> list of profiles (a profile is a list of levels)