def main():
fileName = sys.argv[1]
ncFile = NetCDFFile(fileName, 'r')
description = ET.Element('pointDataDescription')
variableKeys = ncFile.variables.keys()
variableKeys.sort()
for variableName in variableKeys:
if variableName in excludeVars:
continue
variableObject = ncFile.variables[variableName]
varElement = ET.SubElement(description, 'parameter')
varElement.set('name', variableName)
typeCode = variableObject.typecode()
numDims = len(variableObject.shape)
if numDims > 1 and typeCode is 'c':
typeCode = 's'
numDims = numDims - 1
varElement.set('type', typeMap[typeCode])
varElement.set('numDims', str(numDims))
if 'units' in variableObject._attributes:
unit = variableObject._attributes['units']
varElement.set('unit', unit)
if '_FillValue' in variableObject._attributes:
fillValue = variableObject._attributes['_FillValue']
# Disabled for now:
# if fillValue:
# varElement.set('fillValue',str(long(fillValue)))
indentElement(description)
print ET.tostring(description, 'UTF-8')
def __init__(self,
fn,
frame=0,
double=False,
store_force=False,
mode='r',
format='NETCDF4'):
self._fn = fn
self._data = None
try:
if __have_netcdf4__:
self._data = Dataset(fn, mode, format=format)
else:
if mode == 'ws':
mode = 'w'
self._data = NetCDFFile(fn, mode)
except RuntimeError as e:
raise RuntimeError('Error opening file "{0}": {1}'.format(fn, e))
if double:
self._float_str = 'f8'
else:
self._float_str = 'f4'
self._store_force = store_force
self._is_amber = False
if mode[0] == 'w':
self._data.program = 'PyCo'
self._data.programVersion = 'N/A'
self._is_defined = False
else:
if 'nx' in self._data.dimensions and 'ny' in self._data.dimensions:
try:
self._shape = (len(self._data.dimensions['nx']),
len(self._data.dimensions['ny']))
except TypeError:
self._shape = (self._data.dimensions['nx'],
self._data.dimensions['ny'])
self._shape2 = self._shape
elif 'atom' in self._data.dimensions:
n = self._data.dimensions['atom']
nx = int(sqrt(n))
assert nx * nx == n
self._shape = (nx, nx)
self._shape2 = (nx, nx)
self._is_amber = True
else:
raise RuntimeError('Unknown NetCDF convention used for file '
'%s.' % fn)
self._is_defined = True
if frame < 0:
self._cur_frame = len(self) + frame
else:
self._cur_frame = frame
"""
from pupynere import NetCDFFile
import pylab as pl
from matplotlib import rcParams
try:
import numpy
rcParams['numerix'] = 'numpy'
except:
raise ImportError('this example requires numpy')
import matplotlib.numerix.ma as MA
import matplotlib.numerix as N
from matplotlib.toolkits.basemap import Basemap
# read in data from netCDF file.
infile = 'ccsm_popgrid.nc'
fpin = NetCDFFile(infile)
tlat = fpin.variables['TLAT'][:]
tlon = fpin.variables['TLONG'][:]
temp = fpin.variables['TEMP'][:]
fillvalue = fpin.variables['TEMP'].attributes['_FillValue']
fpin.close()
# make longitudes monotonically increasing.
tlon = N.where(N.greater_equal(tlon, min(tlon[:, 0])), tlon - 360, tlon)
# create a masked array with temperature data (continents masked).
temp = MA.masked_values(temp, fillvalue)
# stack grids side-by-side (in longitiudinal direction), so
# any range of longitudes may be plotted on a world map.
tlon = N.concatenate((tlon, tlon + 360), 1)
from pupynere import NetCDFFile
from matplotlib.toolkits.basemap import Basemap, cm
import pylab, copy
from matplotlib import rcParams
# make tick labels smaller
rcParams['xtick.labelsize'] = 9
rcParams['ytick.labelsize'] = 9
# plot rainfall from NWS using special precipitation
# colormap used by the NWS, and included in basemap.
nc = NetCDFFile('nws_precip_conus_20061222.nc')
# data from http://www.srh.noaa.gov/rfcshare/precip_analysis_new.php
prcpvar = nc.variables['amountofprecip']
data = 0.01 * prcpvar[:]
data = pylab.clip(data, 0, 10000)
latcorners = nc.variables['lat'][:]
loncorners = -nc.variables['lon'][:]
plottitle = prcpvar.long_name + ' for period ending ' + prcpvar.dateofdata
print data.min(), data.max()
print latcorners
print loncorners
print plottitle
print data.shape
lon_0 = -nc.variables['true_lon'].getValue()
lat_0 = nc.variables['true_lat'].getValue()
# create polar stereographic Basemap instance.
m = Basemap(projection='stere',lon_0=lon_0,lat_0=90.,lat_ts=lat_0,\
llcrnrlat=latcorners[0],urcrnrlat=latcorners[2],\
llcrnrlon=loncorners[0],urcrnrlon=loncorners[2],\
