From 45b12b310641c248dc3173588a176b4103277d06 Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Mon, 16 Nov 2020 03:25:16 -0600
Subject: [PATCH] snapshot...
---
modules/amv/intercompare.py | 111 ++++++++++++++++++++++++++++++++++++
1 file changed, 111 insertions(+)
diff --git a/modules/amv/intercompare.py b/modules/amv/intercompare.py
index 294e7b6c..1cec919c 100644
--- a/modules/amv/intercompare.py
+++ b/modules/amv/intercompare.py
@@ -13,6 +13,7 @@ import h5py
import time
from scipy.interpolate import interp1d
from util.util import minimize_quadratic
+from netCDF4 import Dataset
#-- AMV intercompare stuff ------------------------------------------
@@ -106,6 +107,116 @@ def filter_amvs(amvs, qitype=amv_cqi_idx, qival=50, lat_range=None):
else:
return amvs[keep, :]
+def get_raob_dict_cdf(filename):
+ rtgrp = Dataset(filename, 'r', format='NETCDF3')
+
+ sta_lats_var = rtgrp['staLat']
+ sta_lats_var.set_always_mask(False)
+ sta_lats_var.set_auto_mask(False)
+
+ sta_lons_var = rtgrp['staLon']
+ sta_lons_var.set_always_mask(False)
+ sta_lons_var.set_auto_mask(False)
+
+ sta_lats = sta_lats_var[:]
+ sta_lons = sta_lons_var[:]
+
+ sta_msk = np.logical_and(sta_lats > -90.0, sta_lats < 90.0)
+ # sta_msk = np.invert(sta_lats._mask)
+ num_sta = np.sum(sta_msk)
+ sta_lats = sta_lats[sta_msk]
+ sta_lons = sta_lons[sta_msk]
+
+ # mandatory levels
+ man_levs = rtgrp['prMan']
+ man_levs = man_levs[:, :]
+ num_man_levs = rtgrp['numMand']
+ num_man_levs = num_man_levs[:]._data
+ man_temp = rtgrp['tpMan']
+ man_temp = man_temp[:, :]
+ man_spd = rtgrp['wsMan']
+ man_spd = man_spd[:, :]
+ man_dir = rtgrp['wdMan']
+ man_dir = man_dir[:, :]
+
+ # significant levels
+ sig_levs = rtgrp['prSigW']
+ sig_levs = sig_levs[:, :]
+ num_sig_levs = rtgrp['numSigW']
+ num_sig_levs = num_sig_levs[:]._data
+ sig_temp = rtgrp['tpSigW']
+ sig_temp = sig_temp[:, :]
+ sig_spd = rtgrp['wsSigW']
+ sig_spd = sig_spd[:, :]
+ sig_dir = rtgrp['wdSigW']
+ sig_dir = sig_dir[:, :]
+
+ man_levs = man_levs[sta_msk,]
+ num_man_levs = num_man_levs[sta_msk]
+
+ sig_levs = sig_levs[sta_msk,]
+ num_sig_levs = num_sig_levs[sta_msk]
+
+ man_temp = man_temp[sta_msk,]
+ man_spd = man_spd[sta_msk,]
+ man_dir = man_dir[sta_msk,]
+
+ sig_temp = sig_temp[sta_msk,]
+ sig_spd = sig_spd[sta_msk,]
+ sig_dir = sig_dir[sta_msk,]
+
+ raob_dct = {}
+ for k in range(num_sta):
+ lon = sta_lons[k]
+ lat = sta_lats[k]
+
+ vld_man = np.invert(man_levs[k]._mask)
+ vld_man = np.logical_and(vld_man, np.invert(man_spd[k]._mask))
+ vld_man = np.logical_and(vld_man, np.invert(man_dir[k]._mask))
+
+ vld_sig = np.invert(sig_levs[k]._mask)
+ vld_sig = np.logical_and(vld_sig, np.invert(sig_spd[k]._mask))
+ vld_sig = np.logical_and(vld_sig, np.invert(sig_dir[k]._mask))
+
+ vld_man_levs = man_levs[k, vld_man]
+ vld_man_spd = man_spd[k, vld_man]
+ vld_man_dir = man_dir[k, vld_man]
+ vld_man_temp = man_temp[k, vld_man]
+
+ s_idxs = np.argsort(vld_man_levs)
+ s_man_levs = vld_man_levs[s_idxs]
+ s_man_spd = vld_man_spd[s_idxs]
+ s_man_dir = vld_man_dir[s_idxs]
+ s_man_temp = vld_man_temp[s_idxs]
+
+ vld_sig_levs = sig_levs[k, vld_sig]
+ vld_sig_spd = sig_spd[k, vld_sig]
+ vld_sig_dir = sig_dir[k, vld_sig]
+ vld_sig_temp = sig_temp[k, vld_sig]
+
+ all_levs = np.append(s_man_levs, vld_sig_levs)
+ all_temp = np.append(s_man_temp, vld_sig_temp)
+ all_spd = np.append(s_man_spd, vld_sig_spd)
+ all_dir = np.append(s_man_dir, vld_sig_dir)
+
+ if len(all_levs) == 0:
+ continue
+
+ s_idxs = np.argsort(all_levs)
+ all_levs = all_levs[s_idxs]
+ all_temp = all_temp[s_idxs]
+ all_spd = all_spd[s_idxs]
+
+ all_levs = all_levs[::-1]
+ all_temp = all_temp[::-1]
+ all_spd = all_spd[::-1]
+ all_dir = all_dir[::-1]
+
+ raob = np.stack([all_levs._data, all_temp._data, all_dir._data, all_spd._data], axis=1)
+
+ raob_dct[(lat, lon)] = raob
+
+ return raob_dct
def get_raob_dict(filename):
header = None
--
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