From 6b116eea9aca494f85db4a623ef1cabab87ba835 Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Mon, 21 Dec 2020 11:59:44 -0600
Subject: [PATCH] snapshot...
---
modules/aeolus/aeolus_amv.py | 34 +++++++++++++++++++++++++++-------
1 file changed, 27 insertions(+), 7 deletions(-)
diff --git a/modules/aeolus/aeolus_amv.py b/modules/aeolus/aeolus_amv.py
index 9a32208d..19802e36 100644
--- a/modules/aeolus/aeolus_amv.py
+++ b/modules/aeolus/aeolus_amv.py
@@ -1068,7 +1068,7 @@ def compare_amvs_bestfit_driver(all_list, bin_size=200):
amvs_list = []
bfs_list = []
rb_list = []
- gfs_list = []
+ bfs_gfs_list = []
prd_list = []
for tup in all_list:
ab_dct = tup[0]
@@ -1080,7 +1080,7 @@ def compare_amvs_bestfit_driver(all_list, bin_size=200):
amvs_list.append(tup[0])
bfs_list.append(tup[1])
rb_list.append(tup[2])
- gfs_list.append(tup[3])
+ bfs_gfs_list.append(tup[3])
keys = list(pr_dct.keys())
for key in keys:
@@ -1106,12 +1106,12 @@ def compare_amvs_bestfit_driver(all_list, bin_size=200):
amvs = np.concatenate(amvs_list)
bfs = np.concatenate(bfs_list)
rbm = np.concatenate(rb_list)
- gfs_bfs = np.concatenate(gfs_list)
+ bfs_gfs = np.concatenate(bfs_gfs_list)
prd = np.concatenate(prd_list)
thin = np.logical_and(prd[:, 2] > 0, prd[:, 2] < 1)
- thick = np.logical_and(prd[:, 2] >= 1, prd[:, 2] < 18)
- deep = np.logical_and(prd[:, 2] >= 18, prd[:, 2] <= 20)
+ thick = np.logical_and(prd[:, 2] >= 1, prd[:, 2] < 6)
+ deep = np.logical_and(prd[:, 2] >= 6, prd[:, 2] <= 20)
amvs_thin = amvs[thin, :]
amvs_thick = amvs[thick, :]
@@ -1121,11 +1121,22 @@ def compare_amvs_bestfit_driver(all_list, bin_size=200):
bfs_thick = bfs[thick, :]
bfs_deep = bfs[deep, :]
+ bfs_gfs_thin = bfs_gfs[thin, :]
+ bfs_gfs_thick = bfs_gfs[thick, :]
+ bfs_gfs_deep = bfs_gfs[deep, :]
+
+ values = []
+ bin_ranges, bin_pres, bin_spd, bin_dir = compare_amvs_bestfit(amvs_thin, bfs_thin, bin_size=bin_size)
+ values.append(bin_pres)
+ bin_ranges, bin_pres, bin_spd, bin_dir = compare_amvs_bestfit(amvs_thick, bfs_thick, bin_size=bin_size)
+ values.append(bin_pres)
bin_ranges, bin_pres, bin_spd, bin_dir = compare_amvs_bestfit(amvs, bfs, bin_size=bin_size)
- #bin_ranges, bin_pres, bin_spd, bin_dir = compare_amvs_bestfit(amvs_thin, bfs_thin, bin_size=bin_size)
+ values.append(bin_pres)
#bin_ranges, bin_pres, bin_spd, bin_dir = compare_amvs_bestfit(amvs_thick, bfs_thick, bin_size=bin_size)
#bin_ranges, bin_pres, bin_spd, bin_dir = compare_amvs_bestfit(amvs_deep, bfs_deep, bin_size=bin_size)
+ make_plot(bin_ranges, values)
+
def compare_amvs_bestfit(amvs, bfs, bin_size=200):
@@ -1246,10 +1257,14 @@ def make_plot(bin_ranges, bin_values):
bin_vals_r = bin_values[0]
bin_vals_g = bin_values[1]
+ bin_vals = bin_values[2]
x_values = []
num_vals_r = []
num_vals_g = []
+ num_vals = []
+ mad = []
+ bias = []
mad_r = []
bias_r = []
mad_g = []
@@ -1258,15 +1273,18 @@ def make_plot(bin_ranges, bin_values):
num_r = 0
num_g = 0
+ num = 0
for i in range(len(bin_ranges)):
num_r += bin_vals_r[i].shape[0]
num_g += bin_vals_g[i].shape[0]
+ num += bin_vals[i].shape[0]
for i in range(len(bin_ranges)):
x_values.append(np.average(bin_ranges[i]))
num_vals_r.append((bin_vals_r[i].shape[0])/num_r)
num_vals_g.append((bin_vals_g[i].shape[0])/num_g)
+ num_vals.append((bin_vals[i].shape[0])/num)
mad_r.append(np.average(np.abs(bin_vals_r[i])))
bias_r.append(np.average(bin_vals_r[i]))
@@ -1274,9 +1292,11 @@ def make_plot(bin_ranges, bin_values):
mad_g.append(np.average(np.abs(bin_vals_g[i])))
bias_g.append(np.average(bin_vals_g[i]))
+ mad.append(np.average(np.abs(bin_vals[i])))
+ bias.append(np.average(bin_vals[i]))
- do_plot(x_values, [mad_r, mad_g], ['GFS_linear', 'GFS_nearest'], ['blue', 'red'], title='ACHA - BestFit', x_axis_label='MAD', y_axis_label='hPa', invert=True, flip=True)
+ do_plot(x_values, [bias_r, bias_g, bias], ['THIN', 'THICK', 'ALL'], ['blue', 'red', 'black'], title='ACHA - BestFit (RAOB)', x_axis_label='BIAS', y_axis_label='hPa', invert=True, flip=True)
#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, [spd_mad_r, spd_mad_g], ['RAOB', 'GFS'], ['blue', 'red'], title='ACHA - BestFit', x_axis_label='MAE (m/s)', 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)
--
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