wassname/scikit-image
1
0
Fork 0
mirror of https://github.com/wassname/scikit-image.git synced 2026-07-04 05:53:05 +08:00
Code Issues Packages Projects Releases Wiki Activity

Move safe_as_int into utils

Browse Source
This commit is contained in:
Stefan van der Walt
2014-05-08 20:11:17 +02:00
parent a9dcdc3713
commit e9c0cde8d4
3 changed files with 84 additions and 87 deletions
Download Patch File Download Diff File Expand all files Collapse all files
skimage/_shared/_safe_as_int.py
-70
View File
@@ -1,70 +0,0 @@
import numpy as np
__all__ = ['_safe_as_int']
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], dtype=int32)
>>> _safe_as_int(53.01)
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)
skimage/_shared/tests/test_safe_as_int.py
+16 -16
View File
@@ -1,30 +1,30 @@
import numpy as np
from skimage._shared.safe_int_cast import _safe_as_int
from skimage._shared.utils import safe_as_int
def test_int_cast_not_possible():
np.testing.assert_raises(ValueError, _safe_as_int, 7.1)
np.testing.assert_raises(ValueError, _safe_as_int, [7.1, 0.9])
np.testing.assert_raises(ValueError, _safe_as_int, np.r_[7.1, 0.9])
np.testing.assert_raises(ValueError, _safe_as_int, (7.1, 0.9))
np.testing.assert_raises(ValueError, _safe_as_int, ((3, 4, 1),
np.testing.assert_raises(ValueError, safe_as_int, 7.1)
np.testing.assert_raises(ValueError, safe_as_int, [7.1, 0.9])
np.testing.assert_raises(ValueError, safe_as_int, np.r_[7.1, 0.9])
np.testing.assert_raises(ValueError, safe_as_int, (7.1, 0.9))
np.testing.assert_raises(ValueError, safe_as_int, ((3, 4, 1),
(2, 7.6, 289)))
np.testing.assert_raises(ValueError, _safe_as_int, 7.1, 0.09)
np.testing.assert_raises(ValueError, _safe_as_int, [7.1, 0.9], 0.09)
np.testing.assert_raises(ValueError, _safe_as_int, np.r_[7.1, 0.9], 0.09)
np.testing.assert_raises(ValueError, _safe_as_int, (7.1, 0.9), 0.09)
np.testing.assert_raises(ValueError, _safe_as_int, ((3, 4, 1),
np.testing.assert_raises(ValueError, safe_as_int, 7.1, 0.09)
np.testing.assert_raises(ValueError, safe_as_int, [7.1, 0.9], 0.09)
np.testing.assert_raises(ValueError, safe_as_int, np.r_[7.1, 0.9], 0.09)
np.testing.assert_raises(ValueError, safe_as_int, (7.1, 0.9), 0.09)
np.testing.assert_raises(ValueError, safe_as_int, ((3, 4, 1),
(2, 7.6, 289)), 0.25)
def test_int_cast_possible():
np.testing.assert_equal(_safe_as_int(7.1, atol=0.11), 7)
np.testing.assert_equal(_safe_as_int(-7.1, atol=0.11), -7)
np.testing.assert_equal(_safe_as_int(41.9, atol=0.11), 42)
np.testing.assert_array_equal(_safe_as_int([2, 42, 5789234.0, 87, 4]),
np.testing.assert_equal(safe_as_int(7.1, atol=0.11), 7)
np.testing.assert_equal(safe_as_int(-7.1, atol=0.11), -7)
np.testing.assert_equal(safe_as_int(41.9, atol=0.11), 42)
np.testing.assert_array_equal(safe_as_int([2, 42, 5789234.0, 87, 4]),
np.r_[2, 42, 5789234, 87, 4])
np.testing.assert_array_equal(_safe_as_int(np.r_[[[3, 4, 1.000000001],
np.testing.assert_array_equal(safe_as_int(np.r_[[[3, 4, 1.000000001],
[7, 2, -8.999999999],
[6, 9, -4234918347.]]]),
np.r_[[[3, 4, 1],
skimage/_shared/utils.py
+68 -1
View File
@@ -1,11 +1,11 @@
import warnings
import functools
import sys
import numpy as np
import six
from ._warnings import all_warnings
from ._safe_as_int import safe_as_int
__all__ = ['deprecated', 'get_bound_method_class', 'all_warnings',
'safe_as_int']
@@ -74,3 +74,70 @@ def get_bound_method_class(m):
"""
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], dtype=int32)
>>> _safe_as_int(53.01)
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)