def _min_or_max_filter(input, size, footprint, structure, output, mode, cval,
origin, minimum):
if structure is None:
if footprint is None:
if size is None:
raise RuntimeError, "no footprint provided"
separable = True
else:
footprint = numarray.asarray(footprint, numarray.Bool)
if numarray.alltrue(numarray.ravel(footprint)):
size = footprint.shape
footprint = None
separable = True
else:
separable = False
else:
structure = numarray.asarray(structure, type=numarray.Float64)
separable = False
if footprint is None:
footprint = numarray.ones(structure.shape, numarray.Bool)
else:
footprint = numarray.asarray(footprint, numarray.Bool)
input = numarray.asarray(input)
if isinstance(input.type(), numarray.ComplexType):
raise TypeError, 'Complex type not supported'
output, return_value = _ni_support._get_output(output, input)
origins = _ni_support._normalize_sequence(origin, input.rank)
if separable:
sizes = _ni_support._normalize_sequence(size, input.rank)
axes = range(input.rank)
axes = [(axes[ii], sizes[ii], origins[ii]) for ii in range(len(axes))
if sizes[ii] > 1]
if minimum:
filter = minimum_filter1d
else:
filter = maximum_filter1d
if len(axes) > 0:
for axis, size, origin in axes:
filter(input, int(size), axis, output, mode, cval, origin)
input = output
else:
output[...] = input[...]
else:
fshape = [ii for ii in footprint.shape if ii > 0]
if len(fshape) != input.rank:
raise RuntimeError, 'footprint array has incorrect shape.'
for origin, lenf in zip(origins, fshape):
if (lenf // 2 + origin < 0) or (lenf // 2 + origin > lenf):
raise ValueError, 'invalid origin'
if not footprint.iscontiguous():
footprint = footprint.copy()
if structure is not None:
if len(structure.shape) != input.rank:
raise RuntimeError, 'structure array has incorrect shape'
if not structure.iscontiguous():
structure = structure.copy()
mode = _ni_support._extend_mode_to_code(mode)
_nd_image.min_or_max_filter(input, footprint, structure, output, mode,
cval, origins, minimum)
return return_value
def _min_or_max_filter(input, size, footprint, structure, output, mode, cval, origin, minimum):
if structure is None:
if footprint is None:
if size is None:
raise RuntimeError, "no footprint provided"
separable = True
else:
footprint = numarray.asarray(footprint, numarray.Bool)
if numarray.alltrue(numarray.ravel(footprint)):
size = footprint.shape
footprint = None
separable = True
else:
separable = False
else:
structure = numarray.asarray(structure, type=numarray.Float64)
separable = False
if footprint is None:
footprint = numarray.ones(structure.shape, numarray.Bool)
else:
footprint = numarray.asarray(footprint, numarray.Bool)
input = numarray.asarray(input)
if isinstance(input.type(), numarray.ComplexType):
raise TypeError, "Complex type not supported"
output, return_value = _ni_support._get_output(output, input)
origins = _ni_support._normalize_sequence(origin, input.rank)
if separable:
sizes = _ni_support._normalize_sequence(size, input.rank)
axes = range(input.rank)
axes = [(axes[ii], sizes[ii], origins[ii]) for ii in range(len(axes)) if sizes[ii] > 1]
if minimum:
filter = minimum_filter1d
else:
filter = maximum_filter1d
if len(axes) > 0:
for axis, size, origin in axes:
filter(input, int(size), axis, output, mode, cval, origin)
input = output
else:
output[...] = input[...]
else:
fshape = [ii for ii in footprint.shape if ii > 0]
if len(fshape) != input.rank:
raise RuntimeError, "footprint array has incorrect shape."
for origin, lenf in zip(origins, fshape):
if (lenf // 2 + origin < 0) or (lenf // 2 + origin > lenf):
raise ValueError, "invalid origin"
if not footprint.iscontiguous():
footprint = footprint.copy()
if structure is not None:
if len(structure.shape) != input.rank:
raise RuntimeError, "structure array has incorrect shape"
if not structure.iscontiguous():
structure = structure.copy()
mode = _ni_support._extend_mode_to_code(mode)
_nd_image.min_or_max_filter(input, footprint, structure, output, mode, cval, origins, minimum)
return return_value
def _min_or_max_filter(input, size, footprint, structure, output, mode,
cval, origin, minimum):
if structure is None:
if footprint is None:
if size is None:
raise RuntimeError("no footprint provided")
separable= True
else:
footprint = numpy.asarray(footprint)
footprint = footprint.astype(bool)
if numpy.alltrue(numpy.ravel(footprint),axis=0):
size = footprint.shape
footprint = None
separable = True
else:
separable = False
else:
structure = numpy.asarray(structure, dtype=numpy.float64)
separable = False
if footprint is None:
footprint = numpy.ones(structure.shape, bool)
else:
footprint = numpy.asarray(footprint)
footprint = footprint.astype(bool)
input = numpy.asarray(input)
if numpy.iscomplexobj(input):
raise TypeError('Complex type not supported')
output, return_value = _ni_support._get_output(output, input)
origins = _ni_support._normalize_sequence(origin, input.ndim)
if separable:
sizes = _ni_support._normalize_sequence(size, input.ndim)
axes = range(input.ndim)
axes = [(axes[ii], sizes[ii], origins[ii])
for ii in range(len(axes)) if sizes[ii] > 1]
if minimum:
filter_ = minimum_filter1d
else:
filter_ = maximum_filter1d
if len(axes) > 0:
for axis, size, origin in axes:
filter_(input, int(size), axis, output, mode, cval, origin)
input = output
else:
output[...] = input[...]
else:
fshape = [ii for ii in footprint.shape if ii > 0]
if len(fshape) != input.ndim:
raise RuntimeError('footprint array has incorrect shape.')
for origin, lenf in zip(origins, fshape):
if (lenf // 2 + origin < 0) or (lenf // 2 + origin > lenf):
raise ValueError('invalid origin')
if not footprint.flags.contiguous:
footprint = footprint.copy()
if structure is not None:
if len(structure.shape) != input.ndim:
raise RuntimeError('structure array has incorrect shape')
if not structure.flags.contiguous:
structure = structure.copy()
mode = _ni_support._extend_mode_to_code(mode)
_nd_image.min_or_max_filter(input, footprint, structure, output,
mode, cval, origins, minimum)
return return_value