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Reorder eps and weight keyword args to tv_denoise

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Tony S Yu
2011-06-23 11:15:31 -04:00
parent 680a89e5ce
commit 8c0d798896
1 changed files with 17 additions and 17 deletions
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scikits/image/filter/tv_denoise.py
+17 -17
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@@ -1,6 +1,6 @@
import numpy as np
def _tv_denoise_3d(im, eps=2.e-4, weight=100, keep_type=False, n_iter_max=200):
def _tv_denoise_3d(im, weight=100, eps=2.e-4, keep_type=False, n_iter_max=200):
"""
Perform total-variation denoising on 3-D arrays
@@ -9,15 +9,15 @@ def _tv_denoise_3d(im, eps=2.e-4, weight=100, keep_type=False, n_iter_max=200):
im: ndarray
3-D input data to be denoised
weight: float, optional
denoising weight. The greater ``weight``, the more denoising (at
the expense of fidelity to ``input``)
eps: float, optional
relative difference of the value of the cost function that determines
the stop criterion. The algorithm stops when
(E_(n-1) - E_n) < eps * E_0
weight: float, optional
denoising weight. The greater ``weight``, the more denoising (at
the expense of fidelity to ``input``)
keep_type: bool, optional (False)
whether the output has the same dtype as the input array.
keep_type is False by default, and the dtype of the output
@@ -92,7 +92,7 @@ def _tv_denoise_3d(im, eps=2.e-4, weight=100, keep_type=False, n_iter_max=200):
else:
return out
def _tv_denoise_2d(im, eps=2.e-4, weight=50, keep_type=False, n_iter_max=200):
def _tv_denoise_2d(im, weight=50, eps=2.e-4, keep_type=False, n_iter_max=200):
"""
Perform total-variation denoising
@@ -101,15 +101,15 @@ def _tv_denoise_2d(im, eps=2.e-4, weight=50, keep_type=False, n_iter_max=200):
im: ndarray
input data to be denoised
weight: float, optional
denoising weight. The greater ``weight``, the more denoising (at
the expense of fidelity to ``input``)
eps: float, optional
relative difference of the value of the cost function that determines
the stop criterion. The algorithm stops when
(E_(n-1) - E_n) < eps * E_0
weight: float, optional
denoising weight. The greater ``weight``, the more denoising (at
the expense of fidelity to ``input``)
keep_type: bool, optional (False)
whether the output has the same dtype as the input array.
keep_type is False by default, and the dtype of the output
@@ -188,7 +188,7 @@ def _tv_denoise_2d(im, eps=2.e-4, weight=50, keep_type=False, n_iter_max=200):
else:
return out
def tv_denoise(im, eps=2.e-4, weight=50, keep_type=False, n_iter_max=200):
def tv_denoise(im, weight=50, eps=2.e-4, keep_type=False, n_iter_max=200):
"""
Perform total-variation denoising on 2-d and 3-d images
@@ -199,15 +199,15 @@ def tv_denoise(im, eps=2.e-4, weight=50, keep_type=False, n_iter_max=200):
but it is cast into an ndarray of floats for the computation
of the denoised image.
weight: float, optional
denoising weight. The greater ``weight``, the more denoising (at
the expense of fidelity to ``input``)
eps: float, optional
relative difference of the value of the cost function that
determines the stop criterion. The algorithm stops when
(E_(n-1) - E_n) < eps * E_0
weight: float, optional
denoising weight. The greater ``weight``, the more denoising (at
the expense of fidelity to ``input``)
keep_type: bool, optional (False)
whether the output has the same dtype as the input array.
keep_type is False by default, and the dtype of the output
@@ -261,9 +261,9 @@ def tv_denoise(im, eps=2.e-4, weight=50, keep_type=False, n_iter_max=200):
"""
if im.ndim == 2:
return _tv_denoise_2d(im, eps, weight, keep_type, n_iter_max)
return _tv_denoise_2d(im, weight, eps, keep_type, n_iter_max)
elif im.ndim == 3:
return _tv_denoise_3d(im, eps, weight, keep_type, n_iter_max)
return _tv_denoise_3d(im, weight, eps, keep_type, n_iter_max)
else:
raise ValueError('only 2-d and 3-d images may be denoised with this function')