def test_decorator():
with suppress_warnings() as sup:
sup.filter(category=DeprecationWarning)
# with unindentation of parameters
decorator = doccer.filldoc(doc_dict, True)
@decorator
def func():
""" Docstring
%(strtest3)s
"""
assert_equal(
func.__doc__, """ Docstring
Another test
with some indent
""")
# without unindentation of parameters
decorator = doccer.filldoc(doc_dict, False)
@decorator
def func():
""" Docstring
%(strtest3)s
"""
assert_equal(
func.__doc__, """ Docstring
Another test
with some indent
""")
_extra_arguments_doc = ("""extra_arguments : sequence, optional
Sequence of extra positional arguments to pass to passed function.""")
_extra_keywords_doc = ("""extra_keywords : dict, optional
dict of extra keyword arguments to pass to passed function.""")
_prefilter_doc = ("""prefilter : bool, optional
Determines if the input array is prefiltered with `spline_filter`
before interpolation. The default is True, which will create a
temporary `float64` array of filtered values if `order > 1`. If
setting this to False, the output will be slightly blurred if
`order > 1`, unless the input is prefiltered, i.e. it is the result
of calling `spline_filter` on the original input.""")
docdict = {
'input': _input_doc,
'axis': _axis_doc,
'output': _output_doc,
'size_foot': _size_foot_doc,
'mode_interp_constant': _mode_interp_constant_doc,
'mode_interp_mirror': _mode_interp_mirror_doc,
'mode_reflect': _mode_reflect_doc,
'mode_multiple': _mode_multiple_doc,
'cval': _cval_doc,
'origin': _origin_doc,
'origin_multiple': _origin_multiple_doc,
'extra_arguments': _extra_arguments_doc,
'extra_keywords': _extra_keywords_doc,
'prefilter': _prefilter_doc
}
docfiller = doccer.filldoc(docdict)
import itertools
import numpy
import warnings
from scipy._lib import doccer
from . import _nd_image
from . import _ni_support
from ._ni_docstrings import docdict
# Change the default 'reflect' to 'constant' via modifying a copy of docdict
docdict_copy = docdict.copy()
del docdict
docdict_copy['mode'] = docdict_copy['mode'].replace("Default is 'reflect'",
"Default is 'constant'")
docfiller = doccer.filldoc(docdict_copy)
__all__ = [
'spline_filter1d', 'spline_filter', 'geometric_transform',
'map_coordinates', 'affine_transform', 'shift', 'zoom', 'rotate'
]
@docfiller
def spline_filter1d(input,
order=3,
axis=-1,
output=numpy.float64,
mode='mirror'):
"""
Calculate a one-dimensional spline filter along the given axis.
import math
import numpy
import warnings
from . import _ni_support
from . import _nd_image
from ._ni_docstrings import docdict
from scipy._lib import doccer
# Change the default 'reflect' to 'constant' via modifying a copy of docdict
docdict_copy = docdict.copy()
del docdict
docdict_copy['mode'] = docdict_copy['mode'].replace("Default is 'reflect'",
"Default is 'constant'")
docfiller = doccer.filldoc(docdict_copy)
__all__ = ['spline_filter1d', 'spline_filter', 'geometric_transform',
'map_coordinates', 'affine_transform', 'shift', 'zoom', 'rotate']
@docfiller
def spline_filter1d(input, order=3, axis=-1, output=numpy.float64,
mode='mirror'):
"""
Calculate a one-dimensional spline filter along the given axis.
The lines of the array along the given axis are filtered by a
spline filter. The order of the spline must be >= 2 and <= 5.
Parameters
"""extra_arguments : sequence, optional
Sequence of extra positional arguments to pass to passed function.""")
_extra_keywords_doc = (
"""extra_keywords : dict, optional
dict of extra keyword arguments to pass to passed function.""")
_prefilter_doc = (
"""prefilter : bool, optional
Determines if the input array is prefiltered with `spline_filter`
before interpolation. The default is True, which will create a
temporary `float64` array of filtered values if `order > 1`. If
setting this to False, the output will be slightly blurred if
`order > 1`, unless the input is prefiltered, i.e. it is the result
of calling `spline_filter` on the original input.""")
docdict = {
'input': _input_doc,
'axis': _axis_doc,
'output': _output_doc,
'size_foot': _size_foot_doc,
'mode': _mode_doc,
'mode_multiple': _mode_multiple_doc,
'cval': _cval_doc,
'origin': _origin_doc,
'origin_multiple': _origin_multiple_doc,
'extra_arguments': _extra_arguments_doc,
'extra_keywords': _extra_keywords_doc,
'prefilter': _prefilter_doc
}
docfiller = doccer.filldoc(docdict)
