A collection of diagnostic and interpolation routines for use with output from the Weather Research and Forecasting (WRF-ARW) Model.
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from __future__ import print_function, division
import os
import argparse
import numpy as np
from netCDF4 import Dataset
from wrf import (getvar, interplevel, interpline, vertcross, vinterp, py2round,
CoordPair, ll_to_xy, xy_to_ll, to_np)
VARS_TO_KEEP = ("Times", "XLAT", "XLONG", "XLAT_U", "XLAT_V", "XLONG_U",
"XLONG_V", "U", "V", "W", "PH", "PHB", "T", "P", "PB", "Q2",
"T2", "PSFC", "U10", "V10", "XTIME", "QVAPOR", "QCLOUD",
"QGRAUP", "QRAIN", "QSNOW", "QICE", "MAPFAC_M", "MAPFAC_U",
"MAPFAC_V", "F", "HGT", "RAINC", "RAINSH", "RAINNC")
DIMS_TO_TRIM = ("west_east", "south_north", "bottom_top", "bottom_top_stag",
"west_east_stag", "south_north_stag")
WRF_DIAGS = ["avo", "eth", "cape_2d", "cape_3d", "ctt", "dbz", "mdbz",
"geopt", "helicity", "lat", "lon", "omg", "p", "pressure",
"pvo", "pw", "rh2", "rh", "slp", "ter", "td2", "td", "tc",
"theta", "tk", "tv", "twb", "updraft_helicity", "ua", "va",
"wa", "uvmet10", "uvmet", "z", "cfrac", "zstag"]
INTERP_METHS = ["interplevel", "vertcross", "interpline", "vinterp"]
LATLON_METHS = ["xy", "ll"]
def copy_and_reduce(opts):
infilename = opts.filename
outfilename = os.path.expanduser(
os.path.join(opts.outdir, "ci_test_file.nc"))
with Dataset(infilename) as infile, Dataset(outfilename, "w") as outfile:
# Copy the global attributes
outfile.setncatts(infile.__dict__)
# Copy Dimensions
for name, dimension in infile.dimensions.iteritems():
if name in DIMS_TO_TRIM:
if name.find("_stag") > 0:
dimsize = (len(dimension) / 2
if len(dimension) % 2 == 0
else (len(dimension) + 1) / 2)
else:
dimsize = (len(dimension) / 2
if len(dimension) % 2 == 0
else (len(dimension) - 1) / 2)
else:
dimsize = len(dimension)
outfile.createDimension(name, dimsize)
# Copy Variables
for name, variable in infile.variables.iteritems():
if name not in VARS_TO_KEEP:
continue
outvar = outfile.createVariable(name, variable.datatype,
variable.dimensions, zlib=True)
in_slices = tuple(slice(0, dimsize) for dimsize in outvar.shape)
outvar[:] = variable[in_slices]
outvar.setncatts(infile.variables[name].__dict__)
def add_to_ncfile(outfile, var, varname):
dim_d = dict(zip(var.dims, var.shape))
for dimname, dimsize in dim_d.items():
if dimname not in outfile.dimensions:
outfile.createDimension(dimname, dimsize)
fill_value = None
if "_FillValue" in var.attrs:
fill_value = var.attrs["_FillValue"]
ncvar = outfile.createVariable(varname, var.dtype, var.dims,
zlib=True, fill_value=fill_value)
var_vals = to_np(var)
ncvar[:] = var_vals[:]
def make_result_file(opts):
infilename = os.path.expanduser(
os.path.join(opts.outdir, "ci_test_file.nc"))
outfilename = os.path.expanduser(
os.path.join(opts.outdir, "ci_result_file.nc"))
with Dataset(infilename) as infile, Dataset(outfilename, "w") as outfile:
for varname in WRF_DIAGS:
var = getvar(infile, varname)
add_to_ncfile(outfile, var, varname)
for interptype in INTERP_METHS:
if interptype == "interpline":
hts = getvar(infile, "z")
p = getvar(infile, "pressure")
hts_850 = interplevel(hts, p, 850.)
add_to_ncfile(outfile, hts_850, "interplevel")
if interptype == "vertcross":
hts = getvar(infile, "z")
p = getvar(infile, "pressure")
pivot_point = CoordPair(hts.shape[-1] // 2, hts.shape[-2] // 2)
ht_cross = vertcross(hts, p, pivot_point=pivot_point,
angle=90.)
add_to_ncfile(outfile, ht_cross, "vertcross")
if interptype == "interpline":
t2 = getvar(infile, "T2")
pivot_point = CoordPair(t2.shape[-1] // 2, t2.shape[-2] // 2)
t2_line = interpline(t2, pivot_point=pivot_point, angle=90.0)
add_to_ncfile(outfile, t2_line, "interpline")
if interptype == "vinterp":
tk = getvar(infile, "temp", units="k")
interp_levels = [200, 300, 500, 1000]
field = vinterp(infile,
field=tk,
vert_coord="theta",
interp_levels=interp_levels,
extrapolate=True,
field_type="tk",
log_p=True)
add_to_ncfile(outfile, field, "vinterp")
for latlonmeth in LATLON_METHS:
if latlonmeth == "xy":
# Hardcoded values from other unit tests
lats = [22.0, 25.0, 27.0]
lons = [-90.0, -87.5, -83.75]
xy = ll_to_xy(infile, lats[0], lons[0])
add_to_ncfile(outfile, xy, "xy")
else:
# Hardcoded from other unit tests
x_s = np.asarray([10, 50, 90], int)
y_s = np.asarray([10, 50, 90], int)
ll = xy_to_ll(infile, x_s[0], y_s[0])
add_to_ncfile(outfile, ll, "ll")
def main(opts):
copy_and_reduce(opts)
make_result_file(opts)
if __name__ == "__main__":
DEFAULT_FILE = ("/Users/ladwig/Documents/wrf_files/"
"wrf_vortex_multi/moving_nest/"
"wrfout_d02_2005-08-28_12:00:00")
parser = argparse.ArgumentParser(description="Generate conda test files "
"for unit testing.")
parser.add_argument("-f", "--filename", required=False,
default=DEFAULT_FILE,
help="the WRF test file")
parser.add_argument("-o", "--outdir", required=False, default="./",
help="the location for the output files")
opts = parser.parse_args()
main(opts)