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import tempfile
import os
import sys
import itertools
from operator import mul
import numpy
import time
import cf
def test(chunk_sizes=(17, 34, 300, 100000)):
start_time = time.time()
print '----------------------------------------------------------'
print 'cf.Field'
print '----------------------------------------------------------'
original_chunksize = cf.CHUNKSIZE()
filename = os.path.join(os.path.dirname(os.path.abspath(__file__)),
"test_file.nc")
for chunksize in chunk_sizes[::-1]:
cf.CHUNKSIZE(chunksize)
f = cf.read(filename)[0]
h = f.copy()
h.transpose((1, 2, 0), i=True)
h.transpose((2, 0, 1), i=True)
h.transpose(('grid_longitude', 'atmos', 'grid_latitude'), i=True)
h.transpose(('atmos', 'grid_latitude', 'grid_longitude'), i=True)
assert(cf.equals(f, h, traceback=True))
print "cf.Field.tranpose passed", "pmshape =", f.Data._pmshape
h.flip((1, 0), i=True)
h.flip((1, 0), i=True)
h.flip(0, i=True)
h.flip(1, i=True)
h.flip([0, 1], i=True)
assert(cf.equals(f, h, traceback=True))
print "cf.Field.flip passed", "pmshape =", f.Data._pmshape
# squeeze=True
#
# w = f.cm('area').copy()
# w /= 10000.
# w.transpose(i=True)
# w = w.array
# w = w.reshape(f.array.shape)
#
# w=None
# x=None
#
# filename = os.path.join(os.path.dirname(os.path.abspath(__file__)),
# "test_file.nc")
# f = cf.read(filename, squeeze=squeeze)[0]
#
# h = 'mean'
#for axis in [None] + range(f.ndim):
# b = numpy.average(f.array, axis=axis, weights=w)
# e = f.collapse('mean', axes=axis, weights=x)
# assert e.shape == b.shape, "%s, axis=%s, %s, %s" % (h, axis, e.shape, a.shape)
# assert e.allclose(b, rtol=1e-05, atol=1e-08) , "%s, axis=%s, \ne=%s, \nb=%s, \ne-b=%s" % (h, axis, e.array, b, e.array-b)rt#
# #--- End: for
# Match
f = cf.read(filename)[0]
f.long_name = 'qwerty'
# print f
all_kwargs = (
{'inverse': False},
{'inverse': False, 'match': 'eastward_wind'},
{'inverse': False, 'match': {'long_name': 'qwerty'}},
{'inverse': False, 'match': {None: 'east'}},
{'inverse': False, 'match': 'east'},
{'inverse': False, 'match': {None: 'east.*'}, 'regex': True},
{'inverse': False, 'match': 'east.*', 'regex': True},
{'inverse': False, 'match': cf.eq('east.*', regex=True)},
{'inverse': False, 'match': {None: cf.eq('east.*', regex=True)}},
{'inverse': False, 'match': {None: 'east', 'long_name': 'qwe'}},
{'inverse': False, 'match': {None: 'east', 'long_name': 'qwe'}, 'match_all': False},
{'inverse': False, 'match': {None: 'east', 'long_name': 'asd'}, 'match_all': False},
#
{'inverse': True, 'match': {None: 'east', 'long_name': 'asd'},},
)
for kwargs in all_kwargs:
# print kwargs
assert f.match(**kwargs), "f.match(**%s) failed" % kwargs
kwargs['inverse'] = not kwargs['inverse']
assert not f.match(**kwargs), "f.match(**%s) failed" % kwargs
#--- End: for
print "cf.Field.match passed", "pmshape =", f.Data._pmshape
# axes_combinations = [axes
# for n in range(1, f.ndim+1)
# for axes in itertools.permutations(range(f.ndim), n)]
#
# data_axes = f.data_axes()
#
# d = f.data.copy()
#
# for h in ('sum', 'min', 'max', 'mean', 'sd', 'var', 'mid_range', 'range'):
# for axes in axes_combinations:
# b = getattr(d, h)(axes=axes, squeeze=True)
# axes2 = [data_axes[i] for i in axes]
# e = f.collapse(h, axes=axes2).data
# assert e.allclose(b, rtol=1e-05, atol=1e-08), \
# "%s, axis=%s, unweighted, unmasked \ne=%s, \nb=%s, \ne-b=%s" % \
# (h, axes, e.array, b, e.array-b)
# #--- End: for
# print "cf.Field.collapse '%s' unweighted, unmasked passed" % \
# h, "pmshape =", f.Data._pmshape
# #--- End: for
#--- End: for
# Reset chunk size
cf.CHUNKSIZE(original_chunksize)
time_elapsed = (time.time() - start_time)/60.0
print
print '---------------------------------------------------------------------------'
print 'All cf.Field tests passed for cf version', cf.__version__
print 'Running from', os.path.abspath(cf.__file__)
print 'Time elapsed: %f minutes' % time_elapsed
print '---------------------------------------------------------------------------'
print
#--- End: def
if __name__ == "__main__":
test()
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