def test_xy_array_only_one_mask():
mask1 = numpy.array([
[0, 1, 1],
[0, 0, 1],
[0, 0, 0],
])
_y, _x = numpy.mgrid[:3, :3]
y = numpy.ma.MaskedArray(data=_y, mask=mask1)
with utils.raises(ValueError):
validate.xy_array(_x, y)
def test_xy_array_as_pairs():
_y, _x = numpy.mgrid[:3, :3]
pairs = validate.xy_array(_y, _x)
known_pairs = numpy.array([[0, 0], [0, 1], [0, 2], [1, 0], [1, 1], [1, 2],
[2, 0], [2, 1], [2, 2]])
nptest.assert_array_equal(pairs, known_pairs)
def mask_with_polygon(x, y, polyverts, inside=True):
""" Mask x-y arrays inside or outside a polygon
Parameters
----------
x, y : array-like
NxM arrays of x- and y-coordinates.
polyverts : sequence of a polygon's vertices
A sequence of x-y pairs for each vertex of the polygon.
inside : bool (default is True)
Toggles masking the inside or outside the polygon
Returns
-------
mask : bool array
The NxM mask that can be applied to ``x`` and ``y``.
"""
# validate input
polyverts = validate.polygon(polyverts)
points = validate.xy_array(x, y, as_pairs=True)
# compute the mask
mask = mpath.Path(polyverts).contains_points(points).reshape(x.shape)
if inside:
return mask
else:
return ~mask
def mask_with_polygon(x, y, polyverts, inside=True):
""" Mask x-y arrays inside or outside a polygon
Parameters
----------
x, y : array-like
NxM arrays of x- and y-coordinates.
polyverts : sequence of a polygon's vertices
A sequence of x-y pairs for each vertex of the polygon.
inside : bool (default = True)
Toggles returning a mask *inside* or *outside* the polygon.
Returns
-------
mask : bool array
The NxM mask that can be applied to ``x`` and ``y``.
"""
# validate input
polyverts = validate.polygon(polyverts)
points = validate.xy_array(x, y, as_pairs=True)
# compute the mask
mask = mpath.Path(polyverts).contains_points(points).reshape(x.shape)
# invert if we're masking things outside the polygon
if not inside:
mask = ~mask
return mask
def test_xy_array_diff_masks():
_y, _x = numpy.mgrid[:3, :3]
mask1 = numpy.array([
[0, 1, 1],
[0, 0, 1],
[0, 0, 0],
])
mask2 = numpy.array([
[0, 1, 1],
[0, 0, 1],
[1, 0, 0],
])
y = numpy.ma.MaskedArray(data=_y, mask=mask1)
x = numpy.ma.MaskedArray(data=_x, mask=mask2)
with utils.raises(ValueError):
validate.xy_array(x, y)
def write_gridout_file(xcoords, ycoords, outfile):
xcoords, ycoords = validate.xy_array(xcoords, ycoords, as_pairs=False)
ny, nx = xcoords.shape
df = pandas.DataFrame({'x': xcoords.flatten(), 'y': ycoords.flatten()})
with Path(outfile).open('w') as f:
f.write('## {:d} x {:d}\n'.format(nx, ny))
df.to_csv(f,
sep=' ',
index=False,
header=False,
na_rep='NaN',
float_format='%.3f')
return df
def test_xy_array_diff_shapes():
with utils.raises(ValueError):
validate.xy_array(numpy.zeros((3, 3)), numpy.zeros((4, 4)))
def test_xy_array_not_as_pairs():
_x, _y = numpy.mgrid[:9, :9]
x, y = validate.xy_array(_x, _y, as_pairs=False)
nptest.assert_array_equal(x, _x)
nptest.assert_array_equal(y, _y)
def test_only_one_mask(self):
y = np.ma.MaskedArray(data=self.y2, mask=self.mask1)
validate.xy_array(self.x2, y)
def test_diff_masks(self):
y = np.ma.MaskedArray(data=self.y2, mask=self.mask1)
x = np.ma.MaskedArray(data=self.x2, mask=self.mask2)
validate.xy_array(x, y)
def test_diff_shapes(self):
validate.xy_array(self.y1, self.x2)
def test_as_pairs(self):
xy = validate.xy_array(self.y2, self.x2)
nt.assert_true(np.all(xy == self.known_pairs))
def test_not_as_pairs(self):
x, y = validate.xy_array(self.y1, self.x1, as_pairs=False)
nt.assert_true(np.all(x == self.y1))
nt.assert_true(np.all(y == self.x1))
