From bc302211f91b3c0418163bec86641b86dde8291c Mon Sep 17 00:00:00 2001
From: rink <rink@ssec.wisc.edu>
Date: Wed, 14 Oct 2020 09:14:59 -0500
Subject: [PATCH] snapshot..
---
modules/aeolus/aeolus_amv.py | 23 +++++++++++------------
1 file changed, 11 insertions(+), 12 deletions(-)
diff --git a/modules/aeolus/aeolus_amv.py b/modules/aeolus/aeolus_amv.py
index 99a03c0c..2f02e0f2 100644
--- a/modules/aeolus/aeolus_amv.py
+++ b/modules/aeolus/aeolus_amv.py
@@ -592,10 +592,11 @@ def create_amv_to_aeolus_match_file(aeolus_files_dir, amv_files_dir, outfile=Non
# match_file: pathname for the product file
# dt_str_0: start time (YYYY-MM-DD_HH:MM)
# dt_str_1: end time (YYYY-MM-DD_HH:MM)
+# amv_var_names: list of amv parameters (see match_file) to subset
# returns: Xarray.DataArray
# amvs[nprofs, max_num_amvs_per_prof, num_of_params], profs[nprofs, max_num_levs_per_prof, num_of_params],
# prof_locs[nprofs, (lon, lat)
-def subset_by_time(match_file, dt_str_0, dt_str_1):
+def subset_by_time(match_file, dt_str_0, dt_str_1, amv_var_names):
rootgrp = Dataset(match_file, 'r', format='NETCDF4')
all_dims = rootgrp.dimensions
t_var = rootgrp['time']
@@ -604,10 +605,10 @@ def subset_by_time(match_file, dt_str_0, dt_str_1):
n_amvs_per_prof = rootgrp['num_amvs_per_prof'][:]
n_levs_per_prof = rootgrp['num_levs_per_prof'][:]
- a_dir_v = rootgrp['amv_dir']
- a_spd_v = rootgrp['amv_spd']
- a_dst_v = rootgrp['amv_dist']
- a_prs_v = rootgrp['amv_pres']
+ a_nc_vars = []
+ for vname in amv_var_names:
+ a_nc_vars.append(rootgrp[vname])
+ nvars = len(a_nc_vars)
p_lon_v = rootgrp['prof_longitude']
p_lat_v = rootgrp['prof_latitude']
@@ -643,8 +644,8 @@ def subset_by_time(match_file, dt_str_0, dt_str_1):
mx_namvs = np.max(n_amvs_per_prof[time_idxs[0]:time_idxs[0]+n_times])
mx_nlevs = np.max(n_levs_per_prof[time_idxs[0]:time_idxs[0]+n_times])
- amvs = np.zeros((n_times, mx_namvs, 4))
- profs = np.zeros((n_times, mx_nlevs, 4))
+ amvs = np.zeros((n_times, mx_namvs, nvars))
+ profs = np.zeros((n_times, mx_nlevs, nvars))
amvs.fill(np.nan)
profs.fill(np.nan)
@@ -660,10 +661,8 @@ def subset_by_time(match_file, dt_str_0, dt_str_1):
c = accum_prf
d = accum_prf + n_levs
- amvs[idx, 0:n_amvs, 0] = a_spd_v[a:b]
- amvs[idx, 0:n_amvs, 1] = a_dir_v[a:b]
- amvs[idx, 0:n_amvs, 2] = a_prs_v[a:b]
- amvs[idx, 0:n_amvs, 3] = a_dst_v[a:b]
+ 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]
@@ -676,7 +675,7 @@ def subset_by_time(match_file, dt_str_0, dt_str_1):
coords = {'num_profs': times[time_idxs], 'num_params': ['speed', 'azimuth', 'layer_bot', 'layer_top']}
prof_da = xr.DataArray(profs, coords=coords, dims=['num_profs', 'max_num_levels', 'num_params'])
- coords = {'num_profs': times[time_idxs], 'num_params': ['speed', 'azimuth', 'pressure', 'distance']}
+ coords = {'num_profs': times[time_idxs], 'num_params': amv_var_names}
amvs_da = xr.DataArray(amvs, coords=coords, dims=['num_profs', 'max_num_amvs', 'num_params'])
prof_locs_da = xr.DataArray(np.column_stack([lons[time_idxs], lats[time_idxs]]),
--
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