From d5f8ca767433fb95280d5cd5e380a9be58953119 Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Wed, 28 Oct 2020 10:04:34 -0500
Subject: [PATCH] snapshot...
---
modules/aeolus/aeolus_amv.py | 31 +++++++++++++++++++++----------
1 file changed, 21 insertions(+), 10 deletions(-)
diff --git a/modules/aeolus/aeolus_amv.py b/modules/aeolus/aeolus_amv.py
index e3809f47..5914182c 100644
--- a/modules/aeolus/aeolus_amv.py
+++ b/modules/aeolus/aeolus_amv.py
@@ -579,12 +579,25 @@ def subset_by_time(match_file, dt_str_0, dt_str_1, amv_var_names):
a_nc_vars.append(rootgrp[vname])
nvars = len(a_nc_vars)
+ mf_vars = list(rootgrp.variables.keys())
+
p_lon_v = rootgrp['prof_longitude']
p_lat_v = rootgrp['prof_latitude']
- p_azm_v = rootgrp['prof_azm']
- p_spd_v = rootgrp['prof_spd']
- p_hhb_v = rootgrp['prof_hhb']
- p_hht_v = rootgrp['prof_hht']
+ p_vars = []
+ p_var_names = []
+ if 'prof_hhb' in mf_vars:
+ p_vars.append(rootgrp['prof_hhb'])
+ p_var_names.append('layer_bot')
+ if 'prof_hht' in mf_vars:
+ p_vars.append(rootgrp['prof_hht'])
+ p_var_names.append('layer_top')
+ if 'prof_spd' in mf_vars:
+ p_vars.append(rootgrp['prof_spd'])
+ p_var_names.append('speed')
+ if 'prof_azm' in mf_vars:
+ p_vars.append(rootgrp['prof_azm'])
+ p_var_names.append('azimuth')
+ npvars = len(p_vars)
dto = datetime.datetime.strptime(dt_str_0, '%Y-%m-%d_%H:%M').replace(tzinfo=timezone.utc)
dto.replace(tzinfo=timezone.utc)
@@ -614,7 +627,7 @@ def subset_by_time(match_file, dt_str_0, dt_str_1, amv_var_names):
mx_nlevs = np.max(n_levs_per_prof[time_idxs[0]:time_idxs[0]+n_times])
amvs = np.zeros((n_times, mx_namvs, nvars))
- profs = np.zeros((n_times, mx_nlevs, 4))
+ profs = np.zeros((n_times, mx_nlevs, npvars))
amvs.fill(np.nan)
profs.fill(np.nan)
@@ -633,15 +646,13 @@ def subset_by_time(match_file, dt_str_0, dt_str_1, amv_var_names):
for k in range(nvars):
amvs[idx, 0:n_amvs, k] = a_nc_vars[k][a:b]
- profs[idx, 0:n_levs, 0] = p_spd_v[c:d]
- profs[idx, 0:n_levs, 1] = p_azm_v[c:d]
- profs[idx, 0:n_levs, 2] = p_hhb_v[c:d]
- profs[idx, 0:n_levs, 3] = p_hht_v[c:d]
+ for k in range(nvars):
+ profs[idx, 0:n_levs, k] = p_vars[k][c:d]
accum_amv += n_amvs
accum_prf += n_levs
- coords = {'num_profs': times[time_idxs], 'num_params': ['speed', 'azimuth', 'layer_bot', 'layer_top']}
+ coords = {'num_profs': times[time_idxs], 'num_params': p_var_names}
prof_da = xr.DataArray(profs, coords=coords, dims=['num_profs', 'max_num_levels', 'num_params'])
coords = {'num_profs': times[time_idxs], 'num_params': amv_var_names}
--
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