Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍
https://github.com/madlabunimib/PyCTBN
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128 lines
5.2 KiB
128 lines
5.2 KiB
"""Docstring components common to several ndimage functions."""
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from scipy._lib import doccer
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__all__ = ['docfiller']
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_input_doc = (
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"""input : array_like
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The input array.""")
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_axis_doc = (
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"""axis : int, optional
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The axis of `input` along which to calculate. Default is -1.""")
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_output_doc = (
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"""output : array or dtype, optional
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The array in which to place the output, or the dtype of the
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returned array. By default an array of the same dtype as input
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will be created.""")
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_size_foot_doc = (
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"""size : scalar or tuple, optional
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See footprint, below. Ignored if footprint is given.
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footprint : array, optional
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Either `size` or `footprint` must be defined. `size` gives
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the shape that is taken from the input array, at every element
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position, to define the input to the filter function.
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`footprint` is a boolean array that specifies (implicitly) a
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shape, but also which of the elements within this shape will get
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passed to the filter function. Thus ``size=(n,m)`` is equivalent
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to ``footprint=np.ones((n,m))``. We adjust `size` to the number
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of dimensions of the input array, so that, if the input array is
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shape (10,10,10), and `size` is 2, then the actual size used is
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(2,2,2). When `footprint` is given, `size` is ignored.""")
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_mode_doc = (
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"""mode : {'reflect', 'constant', 'nearest', 'mirror', 'wrap'}, optional
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The `mode` parameter determines how the input array is extended
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beyond its boundaries. Default is 'reflect'. Behavior for each valid
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value is as follows:
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'reflect' (`d c b a | a b c d | d c b a`)
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The input is extended by reflecting about the edge of the last
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pixel.
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'constant' (`k k k k | a b c d | k k k k`)
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The input is extended by filling all values beyond the edge with
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the same constant value, defined by the `cval` parameter.
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'nearest' (`a a a a | a b c d | d d d d`)
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The input is extended by replicating the last pixel.
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'mirror' (`d c b | a b c d | c b a`)
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The input is extended by reflecting about the center of the last
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pixel.
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'wrap' (`a b c d | a b c d | a b c d`)
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The input is extended by wrapping around to the opposite edge.""")
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_mode_multiple_doc = (
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"""mode : str or sequence, optional
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The `mode` parameter determines how the input array is extended
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when the filter overlaps a border. By passing a sequence of modes
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with length equal to the number of dimensions of the input array,
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different modes can be specified along each axis. Default value is
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'reflect'. The valid values and their behavior is as follows:
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'reflect' (`d c b a | a b c d | d c b a`)
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The input is extended by reflecting about the edge of the last
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pixel.
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'constant' (`k k k k | a b c d | k k k k`)
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The input is extended by filling all values beyond the edge with
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the same constant value, defined by the `cval` parameter.
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'nearest' (`a a a a | a b c d | d d d d`)
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The input is extended by replicating the last pixel.
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'mirror' (`d c b | a b c d | c b a`)
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The input is extended by reflecting about the center of the last
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pixel.
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'wrap' (`a b c d | a b c d | a b c d`)
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The input is extended by wrapping around to the opposite edge.""")
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_cval_doc = (
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"""cval : scalar, optional
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Value to fill past edges of input if `mode` is 'constant'. Default
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is 0.0.""")
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_origin_doc = (
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"""origin : int, optional
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Controls the placement of the filter on the input array's pixels.
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A value of 0 (the default) centers the filter over the pixel, with
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positive values shifting the filter to the left, and negative ones
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to the right.""")
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_origin_multiple_doc = (
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"""origin : int or sequence, optional
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Controls the placement of the filter on the input array's pixels.
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A value of 0 (the default) centers the filter over the pixel, with
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positive values shifting the filter to the left, and negative ones
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to the right. By passing a sequence of origins with length equal to
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the number of dimensions of the input array, different shifts can
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be specified along each axis.""")
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_extra_arguments_doc = (
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"""extra_arguments : sequence, optional
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Sequence of extra positional arguments to pass to passed function.""")
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_extra_keywords_doc = (
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"""extra_keywords : dict, optional
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dict of extra keyword arguments to pass to passed function.""")
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_prefilter_doc = (
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"""prefilter : bool, optional
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Determines if the input array is prefiltered with `spline_filter`
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before interpolation. The default is True, which will create a
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temporary `float64` array of filtered values if `order > 1`. If
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setting this to False, the output will be slightly blurred if
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`order > 1`, unless the input is prefiltered, i.e. it is the result
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of calling `spline_filter` on the original input.""")
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docdict = {
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'input': _input_doc,
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'axis': _axis_doc,
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'output': _output_doc,
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'size_foot': _size_foot_doc,
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'mode': _mode_doc,
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'mode_multiple': _mode_multiple_doc,
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'cval': _cval_doc,
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'origin': _origin_doc,
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'origin_multiple': _origin_multiple_doc,
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'extra_arguments': _extra_arguments_doc,
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'extra_keywords': _extra_keywords_doc,
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'prefilter': _prefilter_doc
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}
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docfiller = doccer.filldoc(docdict)
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