From 53deddf5e06616d10d481bb2f0e2fb7e9c22c220 Mon Sep 17 00:00:00 2001 From: Olivier Debeir Date: Thu, 18 Oct 2012 10:12:19 +0200 Subject: [PATCH] cut long lines --- skimage/filter/rank/bilateral_rank.py | 9 ++++++--- skimage/filter/rank/percentile_rank.py | 27 +++++++++++++++++--------- skimage/filter/rank/rank.py | 24 +++++++++++++++-------- 3 files changed, 40 insertions(+), 20 deletions(-) diff --git a/skimage/filter/rank/bilateral_rank.py b/skimage/filter/rank/bilateral_rank.py index 1dc7552d..5ea92ed9 100644 --- a/skimage/filter/rank/bilateral_rank.py +++ b/skimage/filter/rank/bilateral_rank.py @@ -45,7 +45,8 @@ def _apply(func8, func16, image, selem, out, mask, shift_x, shift_y, s0, s1): bitdepth = find_bitdepth(image) if bitdepth > 11: raise ValueError("only uint16 <4096 image (12bit) supported!") - return func16(image, selem, shift_x=shift_x, shift_y=shift_y, mask=mask, bitdepth=bitdepth + 1, out=out, s0=s0, s1=s1) + return func16(image, selem, shift_x=shift_x, shift_y=shift_y, mask=mask, bitdepth=bitdepth + 1, out=out, + s0=s0, s1=s1) def bilateral_mean(image, selem, out=None, mask=None, shift_x=False, shift_y=False, s0=10, s1=10): @@ -109,7 +110,8 @@ def bilateral_mean(image, selem, out=None, mask=None, shift_x=False, shift_y=Fal """ - return _apply(None, _crank16_bilateral.mean, image, selem, out=out, mask=mask, shift_x=shift_x, shift_y=shift_y, s0=s0, s1=s1) + return _apply(None, _crank16_bilateral.mean, image, selem, out=out, mask=mask, shift_x=shift_x, shift_y=shift_y, + s0=s0, s1=s1) def bilateral_pop(image, selem, out=None, mask=None, shift_x=False, shift_y=False, s0=10, s1=10): @@ -173,7 +175,8 @@ def bilateral_pop(image, selem, out=None, mask=None, shift_x=False, shift_y=Fals """ - return _apply(None, _crank16_bilateral.pop, image, selem, out=out, mask=mask, shift_x=shift_x, shift_y=shift_y, s0=s0, s1=s1) + return _apply(None, _crank16_bilateral.pop, image, selem, out=out, mask=mask, shift_x=shift_x, shift_y=shift_y, + s0=s0, s1=s1) if __name__ == "__main__": import sys diff --git a/skimage/filter/rank/percentile_rank.py b/skimage/filter/rank/percentile_rank.py index 7908f5ac..77858715 100644 --- a/skimage/filter/rank/percentile_rank.py +++ b/skimage/filter/rank/percentile_rank.py @@ -35,7 +35,8 @@ def _apply(func8, func16, image, selem, out, mask, shift_x, shift_y, p0, p1): bitdepth = find_bitdepth(image) if bitdepth > 11: raise ValueError("only uint16 <4096 image (12bit) supported!") - return func16(image, selem, shift_x=shift_x, shift_y=shift_y, mask=mask, bitdepth=bitdepth + 1, out=out, p0=p0, p1=p1) + return func16(image, selem, shift_x=shift_x, shift_y=shift_y, mask=mask, bitdepth=bitdepth + 1, out=out, + p0=p0, p1=p1) else: raise TypeError("only uint8 and uint16 image supported!") @@ -101,7 +102,8 @@ def percentile_autolevel(image, selem, out=None, mask=None, shift_x=False, shift """ - return _apply(_crank8_percentiles.autolevel, _crank16_percentiles.autolevel, image, selem, out=out, mask=mask, shift_x=shift_x, shift_y=shift_y, p0=p0, p1=p1) + return _apply(_crank8_percentiles.autolevel, _crank16_percentiles.autolevel, image, selem, out=out, mask=mask, + shift_x=shift_x, shift_y=shift_y, p0=p0, p1=p1) def percentile_gradient(image, selem, out=None, mask=None, shift_x=False, shift_y=False, p0=.0, p1=1.): @@ -165,7 +167,8 @@ def percentile_gradient(image, selem, out=None, mask=None, shift_x=False, shift_ """ - return _apply(_crank8_percentiles.gradient, _crank16_percentiles.gradient, image, selem, out=out, mask=mask, shift_x=shift_x, shift_y=shift_y, p0=p0, p1=p1) + return _apply(_crank8_percentiles.gradient, _crank16_percentiles.gradient, image, selem, out=out, mask=mask, + shift_x=shift_x, shift_y=shift_y, p0=p0, p1=p1) def percentile_mean(image, selem, out=None, mask=None, shift_x=False, shift_y=False, p0=.0, p1=1.): @@ -229,7 +232,8 @@ def percentile_mean(image, selem, out=None, mask=None, shift_x=False, shift_y=Fa """ - return _apply(_crank8_percentiles.mean, _crank16_percentiles.mean, image, selem, out=out, mask=mask, shift_x=shift_x, shift_y=shift_y, p0=p0, p1=p1) + return _apply(_crank8_percentiles.mean, _crank16_percentiles.mean, image, selem, out=out, mask=mask, + shift_x=shift_x, shift_y=shift_y, p0=p0, p1=p1) def percentile_mean_substraction(image, selem, out=None, mask=None, shift_x=False, shift_y=False, p0=.0, p1=1.): @@ -293,7 +297,8 @@ def percentile_mean_substraction(image, selem, out=None, mask=None, shift_x=Fals """ - return _apply(_crank8_percentiles.mean_substraction, _crank16_percentiles.mean_substraction, image, selem, out=out, mask=mask, shift_x=shift_x, shift_y=shift_y, p0=p0, p1=p1) + return _apply(_crank8_percentiles.mean_substraction, _crank16_percentiles.mean_substraction, image, selem, out=out, + mask=mask, shift_x=shift_x, shift_y=shift_y, p0=p0, p1=p1) def percentile_morph_contr_enh(image, selem, out=None, mask=None, shift_x=False, shift_y=False, p0=.0, p1=1.): @@ -357,7 +362,8 @@ def percentile_morph_contr_enh(image, selem, out=None, mask=None, shift_x=False, """ - return _apply(_crank8_percentiles.morph_contr_enh, _crank16_percentiles.morph_contr_enh, image, selem, out=out, mask=mask, shift_x=shift_x, shift_y=shift_y, p0=p0, p1=p1) + return _apply(_crank8_percentiles.morph_contr_enh, _crank16_percentiles.morph_contr_enh, image, selem, out=out, + mask=mask, shift_x=shift_x, shift_y=shift_y, p0=p0, p1=p1) def percentile(image, selem, out=None, mask=None, shift_x=False, shift_y=False, p0=.0, p1=1.): @@ -422,7 +428,8 @@ def percentile(image, selem, out=None, mask=None, shift_x=False, shift_y=False, """ - return _apply(_crank8_percentiles.percentile, _crank16_percentiles.percentile, image, selem, out=out, mask=mask, shift_x=shift_x, shift_y=shift_y, p0=p0, p1=p1) + return _apply(_crank8_percentiles.percentile, _crank16_percentiles.percentile, image, selem, out=out, mask=mask, + shift_x=shift_x, shift_y=shift_y, p0=p0, p1=p1) def percentile_pop(image, selem, out=None, mask=None, shift_x=False, shift_y=False, p0=.0, p1=1.): @@ -486,7 +493,8 @@ def percentile_pop(image, selem, out=None, mask=None, shift_x=False, shift_y=Fal """ - return _apply(_crank8_percentiles.pop, _crank16_percentiles.pop, image, selem, out=out, mask=mask, shift_x=shift_x, shift_y=shift_y, p0=p0, p1=p1) + return _apply(_crank8_percentiles.pop, _crank16_percentiles.pop, image, selem, out=out, mask=mask, shift_x=shift_x, + shift_y=shift_y, p0=p0, p1=p1) def percentile_threshold(image, selem, out=None, mask=None, shift_x=False, shift_y=False, p0=.0, p1=1.): @@ -551,7 +559,8 @@ def percentile_threshold(image, selem, out=None, mask=None, shift_x=False, shift """ - return _apply(_crank8_percentiles.threshold, _crank16_percentiles.threshold, image, selem, out=out, mask=mask, shift_x=shift_x, shift_y=shift_y, p0=p0, p1=p1) + return _apply(_crank8_percentiles.threshold, _crank16_percentiles.threshold, image, selem, out=out, mask=mask, + shift_x=shift_x, shift_y=shift_y, p0=p0, p1=p1) if __name__ == "__main__": diff --git a/skimage/filter/rank/rank.py b/skimage/filter/rank/rank.py index 0a9dee27..d4df3aef 100644 --- a/skimage/filter/rank/rank.py +++ b/skimage/filter/rank/rank.py @@ -18,7 +18,8 @@ from skimage.filter.rank import _crank8, _crank16 from skimage.filter.rank.generic import find_bitdepth -__all__ = ['autolevel', 'bottomhat', 'equalize', 'gradient', 'maximum', 'mean', 'meansubstraction', 'median', 'minimum', 'modal', 'morph_contr_enh', 'pop', 'threshold', 'tophat'] +__all__ = ['autolevel', 'bottomhat', 'equalize', 'gradient', 'maximum', 'mean', 'meansubstraction', 'median', 'minimum', + 'modal', 'morph_contr_enh', 'pop', 'threshold', 'tophat'] def _apply(func8, func16, image, selem, out, mask, shift_x, shift_y): @@ -95,7 +96,8 @@ def autolevel(image, selem, out=None, mask=None, shift_x=False, shift_y=False): """ - return _apply(_crank8.autolevel, _crank16.autolevel, image, selem, out=out, mask=mask, shift_x=shift_x, shift_y=shift_y) + return _apply(_crank8.autolevel, _crank16.autolevel, image, selem, out=out, mask=mask, shift_x=shift_x, + shift_y=shift_y) def bottomhat(image, selem, out=None, mask=None, shift_x=False, shift_y=False): @@ -156,7 +158,8 @@ def bottomhat(image, selem, out=None, mask=None, shift_x=False, shift_y=False): [ 0, 0, 0, 0, 0]], dtype=uint16) """ - return _apply(_crank8.bottomhat, _crank16.bottomhat, image, selem, out=out, mask=mask, shift_x=shift_x, shift_y=shift_y) + return _apply(_crank8.bottomhat, _crank16.bottomhat, image, selem, out=out, mask=mask, shift_x=shift_x, + shift_y=shift_y) def equalize(image, selem, out=None, mask=None, shift_x=False, shift_y=False): @@ -217,7 +220,8 @@ def equalize(image, selem, out=None, mask=None, shift_x=False, shift_y=False): [3071, 2730, 2047, 2730, 3071]], dtype=uint16) """ - return _apply(_crank8.equalize, _crank16.equalize, image, selem, out=out, mask=mask, shift_x=shift_x, shift_y=shift_y) + return _apply(_crank8.equalize, _crank16.equalize, image, selem, out=out, mask=mask, shift_x=shift_x, + shift_y=shift_y) def gradient(image, selem, out=None, mask=None, shift_x=False, shift_y=False): @@ -279,7 +283,8 @@ def gradient(image, selem, out=None, mask=None, shift_x=False, shift_y=False): """ - return _apply(_crank8.gradient, _crank16.gradient, image, selem, out=out, mask=mask, shift_x=shift_x, shift_y=shift_y) + return _apply(_crank8.gradient, _crank16.gradient, image, selem, out=out, mask=mask, shift_x=shift_x, + shift_y=shift_y) def maximum(image, selem, out=None, mask=None, shift_x=False, shift_y=False): @@ -465,7 +470,8 @@ def meansubstraction(image, selem, out=None, mask=None, shift_x=False, shift_y=F """ - return _apply(_crank8.meansubstraction, _crank16.meansubstraction, image, selem, out=out, mask=mask, shift_x=shift_x, shift_y=shift_y) + return _apply(_crank8.meansubstraction, _crank16.meansubstraction, image, selem, out=out, mask=mask, + shift_x=shift_x, shift_y=shift_y) def median(image, selem, out=None, mask=None, shift_x=False, shift_y=False): @@ -715,7 +721,8 @@ def morph_contr_enh(image, selem, out=None, mask=None, shift_x=False, shift_y=Fa """ - return _apply(_crank8.morph_contr_enh, _crank16.morph_contr_enh, image, selem, out=out, mask=mask, shift_x=shift_x, shift_y=shift_y) + return _apply(_crank8.morph_contr_enh, _crank16.morph_contr_enh, image, selem, out=out, mask=mask, shift_x=shift_x, + shift_y=shift_y) def pop(image, selem, out=None, mask=None, shift_x=False, shift_y=False): @@ -840,7 +847,8 @@ def threshold(image, selem, out=None, mask=None, shift_x=False, shift_y=False): """ - return _apply(_crank8.threshold, _crank16.threshold, image, selem, out=out, mask=mask, shift_x=shift_x, shift_y=shift_y) + return _apply(_crank8.threshold, _crank16.threshold, image, selem, out=out, mask=mask, shift_x=shift_x, + shift_y=shift_y) def tophat(image, selem, out=None, mask=None, shift_x=False, shift_y=False):