def test_discrepancy_with_arange_catch_failure(self):
ar = numpy.arange(self.start, self.end + self.dh / 2, self.dh)
cr = cleaner_range(self.start, self.end, self.dh)
self.assertRaises(AssertionError, numpy.testing.assert_array_equal, ar, cr)
self.assertRaises(AssertionError, numpy.testing.assert_array_equal, ar, self.truth)
def _build_bitmask_vec(self):
"""
same as build mask but using vectorized calls to bin1d
"""
# build bounding box of set of polygons based on origins
nd_origins = numpy.array([poly.origin for poly in self.polygons])
bbox = [(numpy.min(nd_origins[:, 0]), numpy.min(nd_origins[:, 1])),
(numpy.max(nd_origins[:, 0]), numpy.max(nd_origins[:, 1]))]
# get midpoints for hashing
midpoints = numpy.array([poly.centroid() for poly in self.polygons])
# set up grid over bounding box
xs = cleaner_range(bbox[0][0], bbox[1][0], self.dh)
ys = cleaner_range(bbox[0][1], bbox[1][1], self.dh)
# set up mask array, 1 is index 0 is mask
a = numpy.ones([len(ys), len(xs), 2])
# set all indices to nan
a[:, :, 1] = numpy.nan
# bin1d returns the index of polygon within the cartesian grid
idx = bin1d_vec(midpoints[:, 0], xs)
idy = bin1d_vec(midpoints[:, 1], ys)
for i in range(len(self.polygons)):
a[idy[i], idx[i], 1] = int(i)
# build mask in dim=0; here masked values are 1. see note below.
if idx[i] >= 0 and idy[i] >= 0:
if self.poly_mask is not None:
# note: csep1 gridded forecast file format convention states that a "1" indicates a valid cell, which is the opposite
# of the masking criterion
if self.poly_mask[i] == 1:
a[idy[i], idx[i], 0] = 0
else:
a[idy[i], idx[i], 0] = 0
return a, xs, ys
def global_region(dh=0.1, name="global", magnitudes=None):
""" Creates a global region used for evaluating gridded forecasts on the global scale.
The gridded region corresponds to the
Args:
dh:
Returns:
csep.utils.CartesianGrid2D:
"""
# generate latitudes
lons = cleaner_range(-180.0, 179.9, dh)
lats = cleaner_range(-90, 89.9, dh)
coords = itertools.product(lons, lats)
region = CartesianGrid2D(
[Polygon(bbox) for bbox in compute_vertices(coords, dh)],
dh,
name=name)
if magnitudes is not None:
region.magnitudes = magnitudes
return region
def test_discrepancy_with_direct_input(self):
cr = cleaner_range(self.start, self.end, self.dh)
numpy.testing.assert_array_equal(self.truth, cr)