nilyin
/
wrf-python
forked from 3rdparty/wrf-python
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity
Browse Source

Added the ipython notebook demo. Modified the unit tests to remove the var package

main
Bill Ladwig 9 years ago
parent
c7f5f0917f
commit
465582a6e7
2 changed files with 908 additions and 1 deletions
Whitespace
Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL
Split View
Diff Options
Show Stats Download Patch File Download Diff File
  1. 907
      wrf_open/test/ipynb/WRF_python_demo.ipynb
  2. 2
      wrf_open/test/utests.py

907
wrf_open/test/ipynb/WRF_python_demo.ipynb
Unescape View File

@ -0,0 +1,907 @@ @@ -0,0 +1,907 @@
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 1.0 Basic Variable Extraction"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"from __future__ import (absolute_import, division, print_function, unicode_literals)\n",
"\n",
"from wrf import getvar\n",
"from netCDF4 import Dataset as nc\n",
"ncfile = nc(\"/Users/ladwig/Documents/wrf_files/wrfout_d01_2016-02-25_18_00_00\")\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"p = getvar(ncfile, \"P\")\n",
"print(p)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 1.0.1 DataArray attributes: 'dims', 'coords', 'attrs'"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"print(\"dims: \", p.dims)\n",
"print(\"coords: \", p.coords) \n",
"print(\"attrs: \", p.attrs)\n",
"del p"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 1.0.2 Removing implicit 'squeeze' behavior to preserve single sized dimensions"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"p_nosqueeze = getvar(ncfile, \"P\", timeidx=0, squeeze=False)\n",
"print (p_nosqueeze)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 1.0.3 Single element metadata"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"print (p_nosqueeze[0,0,100,200])\n",
"del p_nosqueeze"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 1.0.4 Disabling/Enabling xarray"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"from wrf import disable_xarray, enable_xarray\n",
"\n",
"# Disable xarray completely\n",
"disable_xarray()\n",
"p_no_meta = getvar(ncfile, \"P\")\n",
"print(type(p_no_meta))\n",
"print (p_no_meta)\n",
"del p_no_meta\n",
"enable_xarray()\n",
"\n",
"# Disable on extraction\n",
"p_no_meta = getvar(ncfile, \"P\", meta=False)\n",
"print(\"\\n\")\n",
"print(type(p_no_meta))\n",
"print(p_no_meta)\n",
"del p_no_meta\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 2.0 Sequences of Input Files "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 2.0.1 Combining via the 'cat' method"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"wrflist = [ncfile, ncfile, ncfile]\n",
"p_cat = getvar(wrflist, \"P\", method=\"cat\")\n",
"print(p_cat)\n",
"del p_cat"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 2.0.2 Combining via the 'join' method"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"p_join = getvar(wrflist, \"P\", method=\"join\")\n",
"print(p_join)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Note how the Time dimension was replaced with the file dimension, due to the 'squeezing' of the Time dimension.\n",
"\n",
"\n",
"To maintain the Time dimension, set squeeze to False."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"p_join = getvar(wrflist, \"P\", timeidx=0, method=\"join\", squeeze=False)\n",
"print(p_join)\n",
"del p_join"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 2.0.3 Dictionary Sequences"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"wrf_dict = {\"label1\" : [ncfile, ncfile],\n",
" \"label2\" : [ncfile, ncfile]}\n",
"p_dict = getvar(wrf_dict, \"P\")\n",
"print(p_dict)\n",
"del p_dict"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 2.0.4 Generator Sequences"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"def gen_seq():\n",
" wrfseq = [ncfile, ncfile, ncfile]\n",
" for wrf in wrfseq:\n",
" yield wrf\n",
" \n",
"p_gen = getvar(gen_seq(), \"P\", method=\"join\")\n",
"print(p_gen)\n",
"del p_gen"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 2.0.5 Custom Iterable Classes"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"class FileGen(object):\n",
" def __init__(self, ncfile, count=3):\n",
" self._total = count\n",
" self._i = 0\n",
" self.ncfile = [ncfile]*count\n",
" \n",
" def __iter__(self):\n",
" return self\n",
" \n",
" def next(self):\n",
" if self._i >= self._total:\n",
" raise StopIteration\n",
" else:\n",
" val = self.ncfile[self._i]\n",
" self._i += 1\n",
" return val\n",
" \n",
" # Python 3\n",
" def __next__(self):\n",
" return self.next()\n",
"\n",
"obj_gen = FileGen(ncfile, 3)\n",
"\n",
"p_obj_gen = getvar(gen_seq(), \"P\", method=\"join\", squeeze=False)\n",
"print(p_obj_gen)\n",
"\n",
"del p_obj_gen\n",
" "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 3.0 WRF Variable Computational Routines"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"wrf_vars = [\"avo\", \"eth\", \"cape_2d\", \"cape_3d\", \"ctt\", \"dbz\", \"mdbz\", \n",
" \"geopt\", \"helicity\", \"lat\", \"lon\", \"omg\", \"p\", \"pressure\", \n",
" \"pvo\", \"pw\", \"rh2\", \"rh\", \"slp\", \"ter\", \"td2\", \"td\", \"tc\",\n",
" \"theta\", \"tk\", \"tv\", \"twb\", \"updraft_helicity\", \"ua\", \"va\", \n",
" \"wa\", \"uvmet10\", \"uvmet\", \"z\", \"ctt\"]\n",
"\n",
"vard = {varname: getvar(ncfile, varname, method=\"join\", squeeze=False) for varname in wrf_vars}\n",
"for varname in wrf_vars:\n",
" print(vard[varname])\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"(Note all of the NaNs in the above routines which produce missing values (e.g. cape_2d). xarray always converts all masked_array missing values to NaN in order to work with pandas. To get back the original missing values in a numpy masked_array, you need to use the 'npvalues' method from wrf.)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"from wrf import npvalues\n",
"masked_ndarray = npvalues(vard[\"cape_2d\"])\n",
"print(masked_ndarray)\n",
"del masked_ndarray"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"\n",
"for key in vard.keys():\n",
" del vard[key]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 3.1 Interpolation Routines"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 3.1.1 Horizontal Level Interpolation"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# 500 MB Heights\n",
"from wrf import getvar, interplevel\n",
"\n",
"z = getvar(ncfile, \"z\")\n",
"p = getvar(ncfile, \"pressure\")\n",
"ht_500mb = interplevel(z, p, 500)\n",
"\n",
"print(ht_500mb)\n",
"del ht_500mb, z, p"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 3.1.2 Vertical Cross Section Interpolation"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# Pressure using pivot and angle\n",
"from wrf import getvar, vertcross\n",
"\n",
"z = getvar(ncfile, \"z\")\n",
"p = getvar(ncfile, \"pressure\")\n",
"pivot_point = (z.shape[-2] / 2, z.shape[-1] / 2) \n",
"angle = 90.0\n",
"\n",
"p_vert = vertcross(p, z, pivot_point=pivot_point, angle=angle)\n",
"print(p_vert)\n",
"del p_vert\n",
"\n",
"# Pressure using start_point and end_point\n",
"start_point = (z.shape[-2]/2, 0)\n",
"end_point = (z.shape[-2]/2, -1)\n",
"\n",
"p_vert = vertcross(p, z, start_point=start_point, end_point=end_point)\n",
"print(p_vert)\n",
"del p_vert, p, z"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 3.1.3 Interpolate 2D Variable to a Line"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# T2 using pivot and angle\n",
"from wrf import interpline, getvar\n",
"\n",
"t2 = getvar(ncfile, \"T2\")\n",
"pivot_point = (t2.shape[-2] / 2, t2.shape[-1] / 2) \n",
"angle = 90.0\n",
"\n",
"t2_line = interpline(t2, pivot_point=pivot_point, angle=angle)\n",
"print(t2_line)\n",
"\n",
"del t2_line\n",
"\n",
"# T2 using start_point and end_point\n",
"start_point = (t2.shape[-2]/2, 0)\n",
"end_point = (t2.shape[-2]/2, -1)\n",
"\n",
"t2_line = interpline(t2, start_point=start_point, end_point=end_point)\n",
"print(t2_line)\n",
"\n",
"del t2_line, t2"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 3.1.4 Vertical Coordinate Interpolation"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"from wrf import vinterp, getvar\n",
"\n",
"# Interpolate tk to theta levels \n",
"tk = getvar(ncfile, \"tk\") \n",
"interp_levels = [200, 300, 500, 1000]\n",
"\n",
"interp_field = vinterp(ncfile, \n",
" field=tk, \n",
" vert_coord=\"theta\", \n",
" interp_levels=interp_levels, \n",
" extrapolate=True, \n",
" field_type=\"tk\", \n",
" log_p=True)\n",
"\n",
"print(interp_field)\n",
"del interp_field\n",
"\n",
"# Interpolate tk to theta-e levels \n",
" \n",
"interp_levels = [200, 300, 500, 1000]\n",
"\n",
"interp_field = vinterp(ncfile, \n",
" field=tk, \n",
" vert_coord=\"eth\", \n",
" interp_levels=interp_levels, \n",
" extrapolate=True, \n",
" field_type=\"tk\", \n",
" log_p=True)\n",
"\n",
"print(interp_field)\n",
"del interp_field\n",
"\n",
"# Interpolate tk to geopotential height (MSL) levels \n",
" \n",
"interp_levels = [30, 60, 90]\n",
"\n",
"interp_field = vinterp(ncfile, \n",
" field=tk, \n",
" vert_coord=\"ght_msl\", \n",
" interp_levels=interp_levels, \n",
" extrapolate=True, \n",
" field_type=\"tk\", \n",
" log_p=True)\n",
"\n",
"print(interp_field)\n",
"del interp_field\n",
"\n",
"# Interpolate tk to geopotential height (MSL) levels \n",
" \n",
"interp_levels = [30, 60, 90]\n",
"\n",
"interp_field = vinterp(ncfile, \n",
" field=tk, \n",
" vert_coord=\"ght_agl\", \n",
" interp_levels=interp_levels, \n",
" extrapolate=True, \n",
" field_type=\"tk\", \n",
" log_p=True)\n",
"\n",
"print(interp_field)\n",
"del interp_field\n",
"\n",
"# Interpolate tk to pressure levels\n",
"interp_levels = [850, 500]\n",
" \n",
"interp_field = vinterp(ncfile, \n",
" field=tk, \n",
" vert_coord=\"pressure\", \n",
" interp_levels=interp_levels, \n",
" extrapolate=True, \n",
" field_type=\"tk\", \n",
" log_p=True)\n",
"\n",
"print(interp_field)\n",
"del interp_field, tk\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 3.2 Lat/Lon to X/Y Routines"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"from wrf.latlon import get_ll, get_ij # These names are going to change\n",
"\n",
"a = get_ll(ncfile, [400,105], [200,205])\n",
"b = get_ij(ncfile, 45.5, -110.8)\n",
"\n",
"# Note: Lists/Dictionaries of files will add a new dimension ('domain') only if the domain is moving\n",
"c = get_ll([ncfile, ncfile, ncfile], [400,105], [200,205])\n",
"d = get_ll({\"label1\" : [ncfile, ncfile],\n",
" \"label2\" : [ncfile, ncfile]},\n",
" [400,105], [200,205])\n",
"\n",
"print(a)\n",
"print(\"\\n\")\n",
"print(b)\n",
"print(\"\\n\")\n",
"print(c)\n",
"print(\"\\n\")\n",
"print(d)"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": true
},
"source": [
"# 4.0 Plotting with Cartopy"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"%matplotlib inline"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# SLP\n",
"import matplotlib.pyplot as plt\n",
"from matplotlib.cm import get_cmap\n",
"import cartopy.crs as crs\n",
"from cartopy.feature import NaturalEarthFeature\n",
"\n",
"from wrf import npvalues, getvar\n",
"\n",
"slp = getvar(ncfile, \"slp\")\n",
"lons = slp.coords[\"XLONG\"]\n",
"lats = slp.coords[\"XLAT\"]\n",
"\n",
"wrf_proj = slp.attrs[\"projection\"]\n",
"cart_proj = wrf_proj.cartopy()\n",
"\n",
"fig = plt.figure(figsize=(20,20))\n",
"ax = plt.axes([0.1,0.1,0.8,0.8], projection=cart_proj)\n",
"\n",
"states = NaturalEarthFeature(category='cultural', scale='50m', facecolor='none',\n",
" name='admin_1_states_provinces_shp')\n",
"ax.add_feature(states, linewidth=.5)\n",
"ax.coastlines('50m', linewidth=0.8)\n",
"\n",
"# Can only get this to work if I manually transform the lat/lon points to projected space.\n",
"xform_coords = cart_proj.transform_points(crs.PlateCarree(), npvalues(lons), npvalues(lats))\n",
"x = xform_coords[:,:,0]\n",
"y = xform_coords[:,:,1]\n",
"\n",
"plt.contour(x, y, npvalues(slp), 20, cmap=get_cmap(\"gist_ncar\"))\n",
"plt.colorbar(ax=ax, shrink=.7)\n",
"\n",
"ax.set_xlim(wrf_proj.cartopy_xlim())\n",
"ax.set_ylim(wrf_proj.cartopy_ylim())\n",
"ax.gridlines()\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# 500 MB Heights and Winds\n",
"\n",
"import matplotlib.pyplot as plt\n",
"from matplotlib.cm import get_cmap\n",
"import cartopy.crs as crs\n",
"from cartopy.feature import NaturalEarthFeature\n",
"\n",
"from wrf import getvar, interplevel, npvalues\n",
"\n",
"\n",
"p = getvar(ncfile, \"pressure\")\n",
"z = getvar(ncfile, \"z\", units=\"dm\")\n",
"ua = getvar(ncfile, \"ua\", units=\"kts\")\n",
"va = getvar(ncfile, \"va\", units=\"kts\")\n",
"\n",
"ht_500 = interplevel(z, p, 500)\n",
"u_500 = interplevel(ua, p, 500)\n",
"v_500 = interplevel(va, p, 500)\n",
"\n",
"lons = ht_500.coords[\"XLONG\"]\n",
"lats = ht_500.coords[\"XLAT\"]\n",
"\n",
"wrf_proj = slp.attrs[\"projection\"]\n",
"cart_proj = wrf_proj.cartopy()\n",
"\n",
"fig = plt.figure(figsize=(20,20))\n",
"ax = plt.axes([0.1,0.1,0.8,0.8], projection=cart_proj)\n",
"\n",
"states = NaturalEarthFeature(category='cultural', scale='50m', facecolor='none',\n",
" name='admin_1_states_provinces_shp')\n",
"ax.add_feature(states, linewidth=0.5)\n",
"ax.coastlines('50m', linewidth=0.8)\n",
"\n",
"# Can only get this to work if I manually transform the lat/lon points to projected space.\n",
"xform_coords = cart_proj.transform_points(crs.PlateCarree(), npvalues(lons), npvalues(lats))\n",
"x = xform_coords[:,:,0]\n",
"y = xform_coords[:,:,1]\n",
"\n",
"plt.contour(x, y, npvalues(ht_500), 20, cmap=get_cmap(\"plasma\"))\n",
"plt.barbs(x[::50,::50], y[::50,::50], npvalues(u_500[::50, ::50]), npvalues(v_500[::50, ::50]))\n",
"plt.colorbar(ax=ax, shrink=.7)\n",
"\n",
"ax.set_xlim(wrf_proj.cartopy_xlim())\n",
"ax.set_ylim(wrf_proj.cartopy_ylim())\n",
"ax.gridlines()\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# Cross-section of pressure using xarray's builtin plotting\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"from matplotlib.cm import get_cmap\n",
"\n",
"from wrf import getvar, vertcross, npvalues\n",
"\n",
"p = getvar(ncfile, \"pressure\")\n",
"z = getvar(ncfile, \"z\", units=\"dm\")\n",
"\n",
"pivot_point = (z.shape[-2] / 2, z.shape[-1] / 2) \n",
"angle = 90.0\n",
"\n",
"p_vert = vertcross(p, z, pivot_point=pivot_point, angle=angle)\n",
"\n",
"fig = plt.figure(figsize=(20,8))\n",
"ax = plt.axes([0.1,0.1,0.8,0.8])\n",
"\n",
"p_vert.plot.contour(ax=ax, levels=[0 + 50*n for n in xrange(20)], cmap=get_cmap(\"viridis\"))\n",
"\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": false
},
"source": [
"# Multi-time Moving Domain Files"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"import os\n",
"from wrf import getvar\n",
"from netCDF4 import Dataset as nc\n",
"\n",
"dir = \"/Users/ladwig/Documents/wrf_files/wrf_vortex_multi\"\n",
"ncfilenames = [os.path.join(dir, x) for x in os.listdir(dir) if x.find(\"_d02_\") > 0]\n",
"ncfiles = [nc(x) for x in ncfilenames]\n",
"#print (ncfiles[0].variables[\"XLONG\"][0,0,-1], ncfiles[0].variables[\"XLONG\"][-1,0,-1])\n",
"#print (ncfiles[1].variables[\"XLONG\"][0,0,-1], ncfiles[1].variables[\"XLONG\"][-1,0,-1])\n",
"#print (ncfiles[-1].variables[\"XLONG\"][0,0,-1], ncfiles[-1].variables[\"XLONG\"][-1,0,-1])\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"p = getvar(ncfiles, \"P\", timeidx=3, method=\"join\", meta=True, squeeze=True)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"print (p)\n",
"#print (p.attrs[\"projection\"].shape)\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"print (p.attrs[\"projection\"])\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"ncfiles[2].variables[\"XTIME\"][:]\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"p = getvar(ncfiles, \"P\", timeidx=None, method=\"cat\", meta=True, squeeze=True)\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"print (p)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"print (type(p.coords[\"Time\"]))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"import datetime\n",
"import pandas\n",
"print (type(p.coords[\"Time\"].values.astype(datetime.datetime)))\n",
"print (repr(datetime.datetime.utcfromtimestamp(p.coords[\"Time\"][0].values.astype(int) * 1E-9)))\n",
"print (pandas.to_datetime(p.coords[\"Time\"].values))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"wrf_vars = [\"avo\", \"eth\", \"cape_2d\", \"cape_3d\", \"ctt\", \"dbz\", \"mdbz\", \n",
" \"geopt\", \"helicity\", \"lat\", \"lon\", \"omg\", \"p\", \"pressure\", \n",
" \"pvo\", \"pw\", \"rh2\", \"rh\", \"slp\", \"ter\", \"td2\", \"td\", \"tc\",\n",
" \"theta\", \"tk\", \"tv\", \"twb\", \"updraft_helicity\", \"ua\", \"va\", \n",
" \"wa\", \"uvmet10\", \"uvmet\", \"z\", \"ctt\"]\n",
"\n",
"vard = {varname: getvar(ncfiles, varname, method=\"join\", squeeze=False) for varname in wrf_vars}\n",
"for varname in wrf_vars:\n",
" print(vard[varname])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 2",
"language": "python",
"name": "python2"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.11"
}
},
"nbformat": 4,
"nbformat_minor": 0
}

2
wrf_open/test/utests.py
Unescape View File

@ -5,7 +5,7 @@ import numpy.ma as ma @@ -5,7 +5,7 @@ import numpy.ma as ma
import os, sys
import subprocess
from wrf.var import (getvar, interplevel, interpline, vertcross, vinterp,
from wrf import (getvar, interplevel, interpline, vertcross, vinterp,
disable_xarray, xarray_enabled, npvalues)
NCL_EXE = "/Users/ladwig/nclbuild/6.3.0/bin/ncl"

Write Preview
Loading…
Cancel
Save