forked from 3rdparty/wrf-python
Browse Source
Release 1.1.3
Fixed/Enhanced the cloud top temperature diagnostic.
Optical depth was not being calculated correctly when
cloud ice mixing ratio was not available.
Fixed an indexing bug that caused crashes on Windows, but should have been
crashing on all platforms.
Users can now specify if they want cloud free regions to use fill values,
rather than the default behavior of using the surface temperature.
Users can now specify the optical depth required to trigger the cloud
top temperature calculation. However, the default value of 1.0 should be
sufficient for most users.
Added 'th' alias for the theta product.
Fixed a crash issue related to updraft helicity when a dictionary is
used as the input.
Dictionary inputs now work correctly with xy_to_ll and ll_to_xy.
The cape_2d diagnostic can now work with a single column of data, just like
cape_3d.
lon0
Bill Ladwig
7 years ago
16 changed files with 431 additions and 62 deletions
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from netCDF4 import Dataset |
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import matplotlib.pyplot as plt |
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from matplotlib.cm import get_cmap |
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import cartopy.crs as crs |
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from cartopy.feature import NaturalEarthFeature |
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from wrf import to_np, getvar, smooth2d, get_cartopy, cartopy_xlim, cartopy_ylim, latlon_coords |
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# Open the NetCDF file |
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ncfile = Dataset("/Users/ladwig/Documents/wrf_files/problem_files/cfrac_bug/wrfout_d02_1987-10-01_00:00:00") |
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# Get the sea level pressure |
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ctt = getvar(ncfile, "ctt") |
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# Get the latitude and longitude points |
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lats, lons = latlon_coords(ctt) |
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# Get the cartopy mapping object |
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cart_proj = get_cartopy(ctt) |
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# Create a figure |
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fig = plt.figure(figsize=(12,9)) |
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# Set the GeoAxes to the projection used by WRF |
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ax = plt.axes(projection=cart_proj) |
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# Download and add the states and coastlines |
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states = NaturalEarthFeature(category='cultural', scale='50m', facecolor='none', |
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name='admin_1_states_provinces_shp') |
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ax.add_feature(states, linewidth=.5) |
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ax.coastlines('50m', linewidth=0.8) |
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# Make the contour outlines and filled contours for the smoothed sea level pressure. |
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plt.contour(to_np(lons), to_np(lats), to_np(ctt), 10, colors="black", |
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transform=crs.PlateCarree()) |
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plt.contourf(to_np(lons), to_np(lats), to_np(ctt), 10, transform=crs.PlateCarree(), |
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cmap=get_cmap("jet")) |
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# Add a color bar |
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plt.colorbar(ax=ax, shrink=.62) |
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# Set the map limits. Not really necessary, but used for demonstration. |
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ax.set_xlim(cartopy_xlim(ctt)) |
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ax.set_ylim(cartopy_ylim(ctt)) |
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# Add the gridlines |
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ax.gridlines(color="black", linestyle="dotted") |
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plt.title("Cloud Top Temperature") |
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plt.show() |
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@ -0,0 +1,181 @@ |
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import unittest as ut |
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import numpy.testing as nt |
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import numpy as np |
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import numpy.ma as ma |
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import os |
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import sys |
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import subprocess |
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from wrf import (getvar, interplevel, interpline, vertcross, vinterp, |
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disable_xarray, xarray_enabled, to_np, |
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xy_to_ll, ll_to_xy, xy_to_ll_proj, ll_to_xy_proj, |
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extract_global_attrs, viewitems, CoordPair, ll_points) |
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from wrf.util import is_multi_file |
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IN_DIR = "/Users/ladwig/Documents/wrf_files/wrf_vortex_multi" |
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TEST_FILES = [os.path.join(IN_DIR, "wrfout_d02_2005-08-28_00:00:00"), |
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os.path.join(IN_DIR, "wrfout_d02_2005-08-28_12:00:00"), |
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os.path.join(IN_DIR, "wrfout_d02_2005-08-29_00:00:00")] |
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def wrfin_gen(wrf_in): |
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for x in wrf_in: |
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yield x |
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class wrf_in_iter_class(object): |
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def __init__(self, wrf_in): |
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self._wrf_in = wrf_in |
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self._total = len(wrf_in) |
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self._i = 0 |
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def __iter__(self): |
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return self |
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def next(self): |
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if self._i >= self._total: |
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raise StopIteration |
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else: |
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result = self._wrf_in[self._i] |
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self._i += 1 |
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return result |
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# Python 3 |
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def __next__(self): |
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return self.next() |
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def make_test(varname, wrf_in): |
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def test(self): |
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x = getvar(wrf_in, varname, 0) |
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xa = getvar(wrf_in, varname, None) |
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return test |
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def make_interp_test(varname, wrf_in): |
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def test(self): |
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# Only testing vinterp since other interpolation just use variables |
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if (varname == "vinterp"): |
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for timeidx in (0, None): |
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eth = getvar(wrf_in, "eth", timeidx=timeidx) |
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interp_levels = [850,500,5] |
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field = vinterp(wrf_in, |
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field=eth, |
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vert_coord="pressure", |
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interp_levels=interp_levels, |
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extrapolate=True, |
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field_type="theta-e", |
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timeidx=timeidx, |
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log_p=True) |
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else: |
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pass |
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return test |
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def make_latlon_test(testid, wrf_in): |
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def test(self): |
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if testid == "xy_out": |
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# Lats/Lons taken from NCL script, just hard-coding for now |
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lats = [-55, -60, -65] |
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lons = [25, 30, 35] |
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xy = ll_to_xy(wrf_in, lats, lons, timeidx=0) |
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xy = ll_to_xy(wrf_in, lats, lons, timeidx=None) |
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else: |
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i_s = np.asarray([10, 100, 150], int) |
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j_s = np.asarray([10, 100, 150], int) |
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ll = xy_to_ll(wrf_in, i_s, j_s, timeidx=0) |
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ll = xy_to_ll(wrf_in, i_s, j_s, timeidx=None) |
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return test |
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class WRFVarsTest(ut.TestCase): |
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longMessage = True |
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class WRFInterpTest(ut.TestCase): |
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longMessage = True |
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class WRFLatLonTest(ut.TestCase): |
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longMessage = True |
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if __name__ == "__main__": |
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from wrf import (omp_set_num_threads, omp_set_schedule, omp_get_schedule, |
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omp_set_dynamic, omp_get_num_procs, OMP_SCHED_STATIC) |
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omp_set_num_threads(omp_get_num_procs()-1) |
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omp_set_schedule(OMP_SCHED_STATIC, 0) |
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omp_set_dynamic(False) |
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ignore_vars = [] # Not testable yet |
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wrf_vars = ["avo", "eth", "cape_2d", "cape_3d", "ctt", "dbz", "mdbz", |
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"geopt", "helicity", "lat", "lon", "omg", "p", "pressure", |
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"pvo", "pw", "rh2", "rh", "slp", "ter", "td2", "td", "tc", |
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"theta", "tk", "tv", "twb", "updraft_helicity", "ua", "va", |
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"wa", "uvmet10", "uvmet", "z", "cfrac", "zstag", "geopt_stag"] |
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interp_methods = ["interplevel", "vertcross", "interpline", "vinterp"] |
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latlon_tests = ["xy_out", "ll_out"] |
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for nc_lib in ("netcdf4", "pynio", "scipy"): |
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if nc_lib == "netcdf4": |
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try: |
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from netCDF4 import Dataset |
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except ImportError: |
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print ("netcdf4-python not installed") |
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continue |
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else: |
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test_in = [Dataset(x) for x in TEST_FILES] |
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elif nc_lib == "pynio": |
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try: |
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from Nio import open_file |
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except ImportError: |
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print ("PyNIO not installed") |
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continue |
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else: |
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test_in = [open_file(x +".nc", "r") for x in TEST_FILES] |
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elif nc_lib == "scipy": |
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try: |
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from scipy.io.netcdf import netcdf_file |
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except ImportError: |
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print ("scipy.io.netcdf not installed") |
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else: |
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test_in = [netcdf_file(x, mmap=False) for x in TEST_FILES] |
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input0 = test_in[0] |
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input1 = test_in |
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input2 = tuple(input1) |
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input3 = wrfin_gen(test_in) |
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input4 = wrf_in_iter_class(test_in) |
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input5 = {"A" : input1, |
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"B" : input2} |
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input6 = {"A" : {"AA" : input1}, |
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"B" : {"BB" : input2}} |
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for i,input in enumerate((input0, input1, input2, |
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input3, input4, input5, input6)): |
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for var in wrf_vars: |
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if var in ignore_vars: |
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continue |
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test_func1 = make_test(var, input) |
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setattr(WRFVarsTest, "test_{0}_input{1}_{2}".format(nc_lib, |
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i, var), |
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test_func1) |
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for method in interp_methods: |
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test_interp_func1 = make_interp_test(method, input) |
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setattr(WRFInterpTest, |
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"test_{0}_input{1}_{2}".format(nc_lib, |
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i, method), |
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test_interp_func1) |
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for testid in latlon_tests: |
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test_ll_func = make_latlon_test(testid, input) |
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test_name = "test_{0}_input{1}_{2}".format(nc_lib, i, testid) |
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setattr(WRFLatLonTest, test_name, test_ll_func) |
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ut.main() |
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