From 1c899fb641a4a3289c90a989a9e177b2e8915a46 Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Mon, 14 Dec 2020 11:47:11 -0600
Subject: [PATCH] snapshot...
---
modules/aeolus/aeolus_amv.py | 49 ++++++++++++++++++++++++++++--------
1 file changed, 38 insertions(+), 11 deletions(-)
diff --git a/modules/aeolus/aeolus_amv.py b/modules/aeolus/aeolus_amv.py
index 1ce5e6b8..8dca3893 100644
--- a/modules/aeolus/aeolus_amv.py
+++ b/modules/aeolus/aeolus_amv.py
@@ -13,6 +13,7 @@ from metpy.units import units
from util.gfs_reader import get_vert_profile_s
from amv.intercompare import get_raob_dict_cdf
from util.line_plot import do_plot
+import pickle
amv_file_duration = 60 # minutes
@@ -1061,23 +1062,49 @@ def compare_amvs_bestfit(amvs_list, bfs_list, bin_size=200):
return bin_ranges, bin_pres, bin_spd, bin_dir
-def make_plot(bin_ranges, bin_pres, bin_spd, bin_dir):
+def make_plot():
+ f = open('/Users/tomrink/amv_raob.pkl', 'rb')
+ tup_r = pickle.load(f)
+ f.close()
+
+ f = open('/Users/tomrink/amv_gfs.pkl', 'rb')
+ tup_g = pickle.load(f)
+ f.close()
+
+ bin_ranges = tup_r[0] # same for all
+ bin_pres_r = tup_r[1]
+ bin_pres_g = tup_g[1]
+
x_values = []
- num_pres = []
+ num_pres_r = []
+ num_pres_g = []
num_spd = []
num_dir = []
- pres_mad = []
- pres_bias = []
+ pres_mad_r = []
+ pres_bias_r = []
+ pres_mad_g = []
+ pres_bias_g = []
+ num_r = 0
+ num_g = 0
for i in range(len(bin_ranges)):
- x_values.append(np.average(bin_ranges[i]))
- num_pres.append(bin_pres[i].shape[0])
- num_spd.append(bin_spd[i].shape[0])
- num_dir.append(bin_dir[i].shape[0])
- pres_mad.append(np.average(np.abs(bin_pres[i])))
- pres_bias.append(np.average(bin_pres[i]))
+ num_r += bin_pres_r[i].shape[0]
+ num_g += bin_pres_g[i].shape[0]
- do_plot(x_values, [pres_mad, pres_bias], ['mad', 'bias'], ['blue', 'red'], invert=True, flip=True)
+ for i in range(len(bin_ranges)):
+ x_values.append(np.average(bin_ranges[i]))
+ num_pres_r.append((bin_pres_r[i].shape[0])/num_r)
+ num_pres_g.append((bin_pres_g[i].shape[0])/num_g)
+ #num_spd.append(bin_spd[i].shape[0])
+ #num_dir.append(bin_dir[i].shape[0])
+ pres_mad_r.append(np.average(np.abs(bin_pres_r[i])))
+ pres_bias_r.append(np.average(bin_pres_r[i]))
+ pres_mad_g.append(np.average(np.abs(bin_pres_g[i])))
+ pres_bias_g.append(np.average(bin_pres_g[i]))
+
+ #do_plot(x_values, [pres_mad_r, pres_mad_g], ['RAOB', 'GFS'], ['blue', 'red'], title='ACHA - BestFit', x_axis_label='MAD', y_axis_label='hPa', invert=True, flip=True)
+ do_plot(x_values, [pres_bias_r, pres_bias_g], ['RAOB', 'GFS'], ['blue', 'red'], title='ACHA - BestFit', x_axis_label='BIAS', y_axis_label='hPa', invert=True, flip=True)
+ #do_plot(x_values, [num_pres_r, num_pres_g], ['RAOB:'+str(num_r), 'GFS:'+str(num_g)], ['blue', 'red'], x_axis_label='Normalized Count', y_axis_label='hPa', invert=True, flip=True)
# imports the S4 NOAA output
--
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