def percentile(a, q, axis=None, out=None, interpolation='linear',
keepdims=False):
"""Computes the q-th percentile of the data along the specified axis.
Args:
a (cupy.ndarray): Array for which to compute percentiles.
q (float, tuple of floats or cupy.ndarray): Percentiles to compute
in the range between 0 and 100 inclusive.
axis (int or tuple of ints): Along which axis or axes to compute the
percentiles. The flattened array is used by default.
out (cupy.ndarray): Output array.
interpolation (str): Interpolation method when a quantile lies between
two data points. ``linear`` interpolation is used by default.
Supported interpolations are``lower``, ``higher``, ``midpoint``,
``nearest`` and ``linear``.
keepdims (bool): If ``True``, the axis is remained as an axis of
size one.
Returns:
cupy.ndarray: The percentiles of ``a``, along the axis if specified.
.. seealso:: :func:`numpy.percentile`
"""
if not isinstance(q, cupy.ndarray):
q = cupy.asarray(q, dtype='d')
q = cupy.true_divide(q, 100)
if not _quantile_is_valid(q): # synchronize
raise ValueError('Percentiles must be in the range [0, 100]')
return _quantile_unchecked(a, q, axis=axis, out=out,
interpolation=interpolation, keepdims=keepdims)
def percentile(a,
q,
axis=None,
out=None,
overwrite_input=False,
method='linear',
keepdims=False,
*,
interpolation=None):
"""Computes the q-th percentile of the data along the specified axis.
Args:
a (cupy.ndarray): Array for which to compute percentiles.
q (float, tuple of floats or cupy.ndarray): Percentiles to compute
in the range between 0 and 100 inclusive.
axis (int or tuple of ints): Along which axis or axes to compute the
percentiles. The flattened array is used by default.
out (cupy.ndarray): Output array.
overwrite_input (bool): If True, then allow the input array `a`
to be modified by the intermediate calculations, to save
memory. In this case, the contents of the input `a` after this
function completes is undefined.
method (str): Interpolation method when a quantile lies between
two data points. ``linear`` interpolation is used by default.
Supported interpolations are``lower``, ``higher``, ``midpoint``,
``nearest`` and ``linear``.
keepdims (bool): If ``True``, the axis is remained as an axis of
size one.
interpolation (str): Deprecated name for the method keyword argument.
Returns:
cupy.ndarray: The percentiles of ``a``, along the axis if specified.
.. seealso:: :func:`numpy.percentile`
"""
if interpolation is not None:
method = _check_interpolation_as_method(method, interpolation,
'percentile')
if not isinstance(q, cupy.ndarray):
q = cupy.asarray(q, dtype='d')
q = cupy.true_divide(q, 100)
if not _quantile_is_valid(q): # synchronize
raise ValueError('Percentiles must be in the range [0, 100]')
return _quantile_unchecked(a,
q,
axis=axis,
out=out,
overwrite_input=overwrite_input,
method=method,
keepdims=keepdims)
def cupy_background_correction(data,
dark,
flat,
clip_min=MINIMUM_PIXEL_VALUE,
clip_max=MAXIMUM_PIXEL_VALUE):
"""
Carry out something akin to background correction in Mantid Imaging using cupy.
:param data: The fake data array.
:param dark: The fake dark array.
:param flat: The fake flat array.
:param clip_min: Minimum clipping value.
:param clip_max: Maximum clipping value.
"""
flat = cp.subtract(flat, dark)
flat[flat == 0] = MINIMUM_PIXEL_VALUE
data = cp.subtract(data, dark)
data = cp.true_divide(data, flat)
data = cp.clip(
data, clip_min,
clip_max) # For some reason using the 'out' parameter doesn't work
def __rtruediv__(self, other):
return cupy.true_divide(other, self)
def __truediv__(self, other):
return cupy.true_divide(self, other)
def _cov_pairwise(x1, x2, factor):
return cupy.nansum(x1 * x2, axis=1, keepdims=True) * cupy.true_divide(
1, factor)
