cupy.linalg
)
cupy.random
)
cupy.testing
)
cupyx.scipy.fftpack
)
cupyx.scipy.interpolate
)
cupyx.scipy.linalg
)
cupyx.scipy.ndimage
)
cupyx.scipy.signal
)
cupyx.scipy.signal.windows
)
cupyx.scipy.sparse
)
cupyx.scipy.sparse.linalg
)
cupyx.scipy.sparse.csgraph
)
cupyx.scipy.spatial
)
cupyx.scipy.spatial.distance
)
cupyx.scipy.special
)
cupyx.scipy.stats
)
Multi-dimensional maximum filter.
input ( cupy.ndarray ) – The input array.
size
(
int
or
sequence
of
int
) – One of
size
or
footprint
must be
provided. If
footprint
is given,
size
is ignored. Otherwise
footprint
=
cupy.ones(size)
with
size
automatically made to
match the number of dimensions in
input
.
footprint ( cupy.ndarray ) – a boolean array which specifies which of the elements within this shape will get passed to the filter function.
output ( cupy.ndarray , dtype or None ) – The array in which to place the output. Default is is same dtype as the input.
mode
(
str
or
sequence
of
str
) – The array borders are handled according
to the given mode (
'reflect'
,
'constant'
,
'nearest'
,
'mirror'
,
'wrap'
). Default is
'reflect'
. By passing a
sequence of modes with length equal to the number of
axes
along
which the input array is being filtered, different modes can be
specified along each axis. For more details on the supported modes,
see
scipy.ndimage.minimum_filter()
.
cval
(
scalar
) – Value to fill past edges of input if mode is
'constant'
. Default is
0.0
.
origin
(
int
or
sequence
of
int
) – The origin parameter controls the
placement of the filter, relative to the center of the current
element of the input. Default of 0 is equivalent to
(0,)*input.ndim
.
axes
(
tuple
of
int
or
None
) – If None,
input
is filtered along all
axes. Otherwise,
input
is filtered along the specified axes.
When
axes
is specified, any tuples used for
size
,
mode
and/or
origin
must match the length of
axes
. The
ith entry in any of these tuples corresponds to the ith entry in
axes
. Default is
None
.
The result of the filtering.
See also