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Fixed database typo and removed unnecessary class identifier.

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Batuhan Berk Başoğlu 2020-10-14 10:10:37 -04:00
parent 00ad49a143
commit 45fb349a7d
5098 changed files with 952558 additions and 85 deletions
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venv/Lib/site-packages/skimage/_shared/utils.py Normal file
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import inspect
import warnings
import functools
import sys
import numpy as np
import numbers
from ..util import img_as_float
from ._warnings import all_warnings, warn
__all__ = ['deprecated', 'get_bound_method_class', 'all_warnings',
'safe_as_int', 'check_nD', 'check_shape_equality', 'warn']
class skimage_deprecation(Warning):
"""Create our own deprecation class, since Python >= 2.7
silences deprecations by default.
"""
pass
class change_default_value:
"""Decorator for changing the default value of an argument.
Parameters
----------
arg_name: str
The name of the argument to be updated.
new_value: any
The argument new value.
changed_version : str
The package version in which the change will be introduced.
warning_msg: str
Optional warning message. If None, a generic warning message
is used.
"""
def __init__(self, arg_name, *, new_value, changed_version,
warning_msg=None):
self.arg_name = arg_name
self.new_value = new_value
self.warning_msg = warning_msg
self.changed_version = changed_version
def __call__(self, func):
parameters = inspect.signature(func).parameters
arg_idx = list(parameters.keys()).index(self.arg_name)
old_value = parameters[self.arg_name].default
if self.warning_msg is None:
self.warning_msg = (
f"The new recommended value for {self.arg_name} is "
f"{self.new_value}. Until version {self.changed_version}, "
f"the default {self.arg_name} value is {old_value}. "
f"From version {self.changed_version}, the {self.arg_name} "
f"default value will be {self.new_value}. To avoid "
f"this warning, please explicitly set {self.arg_name} value.")
@functools.wraps(func)
def fixed_func(*args, **kwargs):
if len(args) < arg_idx + 1 and self.arg_name not in kwargs.keys():
# warn that arg_name default value changed:
warnings.warn(self.warning_msg, FutureWarning, stacklevel=2)
return func(*args, **kwargs)
return fixed_func
class deprecate_kwarg:
"""Decorator ensuring backward compatibility when argument names are
modified in a function definition.
Parameters
----------
arg_mapping: dict
Mapping between the function's old argument names and the new
ones.
warning_msg: str
Optional warning message. If None, a generic warning message
is used.
removed_version : str
The package version in which the deprecated argument will be
removed.
"""
def __init__(self, kwarg_mapping, warning_msg=None, removed_version=None):
self.kwarg_mapping = kwarg_mapping
if warning_msg is None:
self.warning_msg = ("'{old_arg}' is a deprecated argument name "
"for `{func_name}`. ")
if removed_version is not None:
self.warning_msg += ("It will be removed in version {}. "
.format(removed_version))
self.warning_msg += "Please use '{new_arg}' instead."
else:
self.warning_msg = warning_msg
def __call__(self, func):
@functools.wraps(func)
def fixed_func(*args, **kwargs):
for old_arg, new_arg in self.kwarg_mapping.items():
if old_arg in kwargs:
# warn that the function interface has changed:
warnings.warn(self.warning_msg.format(
old_arg=old_arg, func_name=func.__name__,
new_arg=new_arg), FutureWarning, stacklevel=2)
# Substitute new_arg to old_arg
kwargs[new_arg] = kwargs.pop(old_arg)
# Call the function with the fixed arguments
return func(*args, **kwargs)
return fixed_func
class deprecated(object):
"""Decorator to mark deprecated functions with warning.
Adapted from <http://wiki.python.org/moin/PythonDecoratorLibrary>.
Parameters
----------
alt_func : str
If given, tell user what function to use instead.
behavior : {'warn', 'raise'}
Behavior during call to deprecated function: 'warn' = warn user that
function is deprecated; 'raise' = raise error.
removed_version : str
The package version in which the deprecated function will be removed.
"""
def __init__(self, alt_func=None, behavior='warn', removed_version=None):
self.alt_func = alt_func
self.behavior = behavior
self.removed_version = removed_version
def __call__(self, func):
alt_msg = ''
if self.alt_func is not None:
alt_msg = ' Use ``%s`` instead.' % self.alt_func
rmv_msg = ''
if self.removed_version is not None:
rmv_msg = (' and will be removed in version %s' %
self.removed_version)
msg = ('Function ``%s`` is deprecated' % func.__name__ +
rmv_msg + '.' + alt_msg)
@functools.wraps(func)
def wrapped(*args, **kwargs):
if self.behavior == 'warn':
func_code = func.__code__
warnings.simplefilter('always', skimage_deprecation)
warnings.warn_explicit(msg,
category=skimage_deprecation,
filename=func_code.co_filename,
lineno=func_code.co_firstlineno + 1)
elif self.behavior == 'raise':
raise skimage_deprecation(msg)
return func(*args, **kwargs)
# modify doc string to display deprecation warning
doc = '**Deprecated function**.' + alt_msg
if wrapped.__doc__ is None:
wrapped.__doc__ = doc
else:
wrapped.__doc__ = doc + '\n\n ' + wrapped.__doc__
return wrapped
def get_bound_method_class(m):
"""Return the class for a bound method.
"""
return m.im_class if sys.version < '3' else m.__self__.__class__
def safe_as_int(val, atol=1e-3):
"""
Attempt to safely cast values to integer format.
Parameters
----------
val : scalar or iterable of scalars
Number or container of numbers which are intended to be interpreted as
integers, e.g., for indexing purposes, but which may not carry integer
type.
atol : float
Absolute tolerance away from nearest integer to consider values in
``val`` functionally integers.
Returns
-------
val_int : NumPy scalar or ndarray of dtype `np.int64`
Returns the input value(s) coerced to dtype `np.int64` assuming all
were within ``atol`` of the nearest integer.
Notes
-----
This operation calculates ``val`` modulo 1, which returns the mantissa of
all values. Then all mantissas greater than 0.5 are subtracted from one.
Finally, the absolute tolerance from zero is calculated. If it is less
than ``atol`` for all value(s) in ``val``, they are rounded and returned
in an integer array. Or, if ``val`` was a scalar, a NumPy scalar type is
returned.
If any value(s) are outside the specified tolerance, an informative error
is raised.
Examples
--------
>>> safe_as_int(7.0)
7
>>> safe_as_int([9, 4, 2.9999999999])
array([9, 4, 3])
>>> safe_as_int(53.1)
Traceback (most recent call last):
...
ValueError: Integer argument required but received 53.1, check inputs.
>>> safe_as_int(53.01, atol=0.01)
53
"""
mod = np.asarray(val) % 1 # Extract mantissa
# Check for and subtract any mod values > 0.5 from 1
if mod.ndim == 0: # Scalar input, cannot be indexed
if mod > 0.5:
mod = 1 - mod
else: # Iterable input, now ndarray
mod[mod > 0.5] = 1 - mod[mod > 0.5] # Test on each side of nearest int
try:
np.testing.assert_allclose(mod, 0, atol=atol)
except AssertionError:
raise ValueError("Integer argument required but received "
"{0}, check inputs.".format(val))
return np.round(val).astype(np.int64)
def check_shape_equality(im1, im2):
"""Raise an error if the shape do not match."""
if not im1.shape == im2.shape:
raise ValueError('Input images must have the same dimensions.')
return
def check_nD(array, ndim, arg_name='image'):
"""
Verify an array meets the desired ndims and array isn't empty.
Parameters
----------
array : array-like
Input array to be validated
ndim : int or iterable of ints
Allowable ndim or ndims for the array.
arg_name : str, optional
The name of the array in the original function.
"""
array = np.asanyarray(array)
msg_incorrect_dim = "The parameter `%s` must be a %s-dimensional array"
msg_empty_array = "The parameter `%s` cannot be an empty array"
if isinstance(ndim, int):
ndim = [ndim]
if array.size == 0:
raise ValueError(msg_empty_array % (arg_name))
if not array.ndim in ndim:
raise ValueError(msg_incorrect_dim % (arg_name, '-or-'.join([str(n) for n in ndim])))
def check_random_state(seed):
"""Turn seed into a `np.random.RandomState` instance.
Parameters
----------
seed : None, int or np.random.RandomState
If `seed` is None, return the RandomState singleton used by `np.random`.
If `seed` is an int, return a new RandomState instance seeded with `seed`.
If `seed` is already a RandomState instance, return it.
Raises
------
ValueError
If `seed` is of the wrong type.
"""
# Function originally from scikit-learn's module sklearn.utils.validation
if seed is None or seed is np.random:
return np.random.mtrand._rand
if isinstance(seed, (numbers.Integral, np.integer)):
return np.random.RandomState(seed)
if isinstance(seed, np.random.RandomState):
return seed
raise ValueError('%r cannot be used to seed a numpy.random.RandomState'
' instance' % seed)
def convert_to_float(image, preserve_range):
"""Convert input image to float image with the appropriate range.
Parameters
----------
image : ndarray
Input image.
preserve_range : bool
Determines if the range of the image should be kept or transformed
using img_as_float. Also see
https://scikit-image.org/docs/dev/user_guide/data_types.html
Notes:
------
* Input images with `float32` data type are not upcast.
Returns
-------
image : ndarray
Transformed version of the input.
"""
if preserve_range:
# Convert image to double only if it is not single or double
# precision float
if image.dtype.char not in 'df':
image = image.astype(float)
else:
image = img_as_float(image)
return image
def _validate_interpolation_order(image_dtype, order):
"""Validate and return spline interpolation's order.
Parameters
----------
image_dtype : dtype
Image dtype.
order : int, optional
The order of the spline interpolation. The order has to be in
the range 0-5. See `skimage.transform.warp` for detail.
Returns
-------
order : int
if input order is None, returns 0 if image_dtype is bool and 1
otherwise. Otherwise, image_dtype is checked and input order
is validated accordingly (order > 0 is not supported for bool
image dtype)
"""
if order is None:
return 0 if image_dtype == bool else 1
if order < 0 or order > 5:
raise ValueError("Spline interpolation order has to be in the "
"range 0-5.")
if image_dtype == bool and order != 0:
warn("Input image dtype is bool. Interpolation is not defined "
"with bool data type. Please set order to 0 or explicitely "
"cast input image to another data type. Starting from version "
"0.19 a ValueError will be raised instead of this warning.",
FutureWarning, stacklevel=2)
return order