def test_make_bivariate_histogram(self):
x, y = np.ones((100, 100)), np.ones((100, 100))
make_bivariate_histogram(
x_position=x,
y_position=y,
histogram_range=None,
masked=None,
bins=200,
spatial_std=3,
)
def test_single_negative_x(self):
size = 100
x, y = -np.ones(size), np.zeros(size)
s = make_bivariate_histogram(x, y)
hist_iX = s.axes_manager[0].value2index(-1)
hist_iY = s.axes_manager[1].value2index(0)
assert s.data[hist_iY, hist_iX] == size
s.data[hist_iY, hist_iX] = 0
assert not s.data.any()
def get_bivariate_histogram(self,
histogram_range=None,
masked=None,
bins=200,
spatial_std=3):
"""
Useful for finding the distribution of magnetic vectors(?).
Parameters
----------
histogram_range : tuple, optional
Set the minimum and maximum of the histogram range.
Default is setting it automatically.
masked : 2-D NumPy bool array, optional
Mask parts of the data. The array must be the same
size as the signal. The True values are masked.
Default is not masking anything.
bins : integer, default 200
Number of bins in the histogram
spatial_std : number, optional
If histogram_range is not given, this value will be
used to set the automatic histogram range.
Default value is 3.
Returns
-------
s_hist : HyperSpy Signal2D
Examples
--------
>>> s = ps.dummy_data.get_stripe_pattern_dpc_signal()
>>> s_hist = s.get_bivariate_histogram()
>>> s_hist.plot()
"""
x_position = self.inav[0].data
y_position = self.inav[1].data
s_hist = make_bivariate_histogram(
x_position,
y_position,
histogram_range=histogram_range,
masked=masked,
bins=bins,
spatial_std=spatial_std,
)
s_hist.metadata.General.title = "Bivariate histogram of {0}".format(
self.metadata.General.title)
return s_hist
def get_bivariate_histogram(self,
histogram_range=None,
masked=None,
bins=200,
spatial_std=3):
"""
Useful for finding the distribution of magnetic vectors(?).
Parameters
----------
histogram_range : tuple, optional
Set the minimum and maximum of the histogram range.
Default is setting it automatically.
masked : 1-D NumPy bool array, optional
Mask parts of the data. The array must be the same
size as the signal. The True values are masked.
Default is not masking anything.
bins : integer, default 200
Number of bins in the histogram
spatial_std : number, optional
If histogram_range is not given, this value will be
used to set the automatic histogram range.
Default value is 3.
Returns
-------
s_hist : Signal2D
"""
x_position = self.inav[0].data
y_position = self.inav[1].data
s_hist = make_bivariate_histogram(
x_position,
y_position,
histogram_range=histogram_range,
masked=masked,
bins=bins,
spatial_std=spatial_std,
)
return s_hist