From 4f6b39dcd3fe85ee2453f3ba35fa84ad9ee68550 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Johannes=20Sch=C3=B6nberger?= Date: Fri, 5 Jul 2013 14:19:10 +0200 Subject: [PATCH] Rename block_* functions to local_* --- skimage/measure/__init__.py | 12 +++---- skimage/measure/{blocks.py => local.py} | 22 ++++++------ .../tests/{test_blocks.py => test_local.py} | 36 +++++++++---------- skimage/transform/_warps.py | 4 +-- 4 files changed, 37 insertions(+), 37 deletions(-) rename skimage/measure/{blocks.py => local.py} (90%) rename skimage/measure/tests/{test_blocks.py => test_local.py} (73%) diff --git a/skimage/measure/__init__.py b/skimage/measure/__init__.py index 021a6edf..26eb179c 100755 --- a/skimage/measure/__init__.py +++ b/skimage/measure/__init__.py @@ -3,7 +3,7 @@ from ._regionprops import regionprops, perimeter from ._structural_similarity import structural_similarity from ._polygon import approximate_polygon, subdivide_polygon from .fit import LineModel, CircleModel, EllipseModel, ransac -from .blocks import block_sum, block_median, block_mean, block_min, block_max +from .local import local_sum, local_mean, local_median, local_min, local_max __all__ = ['find_contours', @@ -16,8 +16,8 @@ __all__ = ['find_contours', 'CircleModel', 'EllipseModel', 'ransac', - 'block_sum', - 'block_mean', - 'block_median', - 'block_min', - 'block_max'] + 'local_sum', + 'local_mean', + 'local_median', + 'local_min', + 'local_max'] diff --git a/skimage/measure/blocks.py b/skimage/measure/local.py similarity index 90% rename from skimage/measure/blocks.py rename to skimage/measure/local.py index abeef10f..3f628a53 100644 --- a/skimage/measure/blocks.py +++ b/skimage/measure/local.py @@ -2,7 +2,7 @@ import numpy as np from ..util.shape import view_as_blocks, _pad_asymmetric_zeros -def _block_func(image, factors, func): +def _local_func(image, factors, func): """Down-sample image by applying function to local blocks. Parameters @@ -45,7 +45,7 @@ def _block_func(image, factors, func): return out -def block_sum(image, block_size): +def local_sum(image, block_size): """Sum elements in local blocks. The image is padded with zeros if it is not perfectly divisible by integer @@ -75,10 +75,10 @@ def block_sum(image, block_size): [33, 27]]) """ - return _block_func(image, block_size, np.sum) + return _local_func(image, block_size, np.sum) -def block_mean(image, block_size): +def local_mean(image, block_size): """Average elements in local blocks. The image is padded with zeros if it is not perfectly divisible by integer @@ -108,10 +108,10 @@ def block_mean(image, block_size): [ 5.5, 4.5]]) """ - return _block_func(image, block_size, np.mean) + return _local_func(image, block_size, np.mean) -def block_median(image, block_size): +def local_median(image, block_size): """Median element in local blocks. The image is padded with zeros if it is not perfectly divisible by integer @@ -139,10 +139,10 @@ def block_median(image, block_size): array([[ 5.]]) """ - return _block_func(image, block_size, np.median) + return _local_func(image, block_size, np.median) -def block_min(image, block_size): +def local_min(image, block_size): """Minimum element in local blocks. The image is padded with zeros if it is not perfectly divisible by integer @@ -172,10 +172,10 @@ def block_min(image, block_size): [0, 0, 0]]) """ - return _block_func(image, block_size, np.min) + return _local_func(image, block_size, np.min) -def block_max(image, block_size): +def local_max(image, block_size): """Maximum element in local blocks. The image is padded with zeros if it is not perfectly divisible by integer @@ -205,4 +205,4 @@ def block_max(image, block_size): [12, 14]]) """ - return _block_func(image, block_size, np.max) + return _local_func(image, block_size, np.max) diff --git a/skimage/measure/tests/test_blocks.py b/skimage/measure/tests/test_local.py similarity index 73% rename from skimage/measure/tests/test_blocks.py rename to skimage/measure/tests/test_local.py index 11894585..fc01b7b9 100644 --- a/skimage/measure/tests/test_blocks.py +++ b/skimage/measure/tests/test_local.py @@ -1,78 +1,78 @@ import numpy as np from numpy.testing import assert_array_equal -from skimage.measure import (block_sum, block_mean, block_median, block_min, - block_max) +from skimage.measure import (local_sum, local_mean, local_median, local_min, + local_max) -def test_block_sum(): +def test_local_sum(): image1 = np.arange(4 * 6).reshape(4, 6) - out1 = block_sum(image1, (2, 3)) + out1 = local_sum(image1, (2, 3)) expected1 = np.array([[ 24, 42], [ 96, 114]]) assert_array_equal(expected1, out1) image2 = np.arange(5 * 8).reshape(5, 8) - out2 = block_sum(image2, (3, 3)) + out2 = local_sum(image2, (3, 3)) expected2 = np.array([[ 81, 108, 87], [174, 192, 138]]) assert_array_equal(expected2, out2) -def test_block_mean(): +def test_local_mean(): image1 = np.arange(4 * 6).reshape(4, 6) - out1 = block_mean(image1, (2, 3)) + out1 = local_mean(image1, (2, 3)) expected1 = np.array([[ 4., 7.], [ 16., 19.]]) assert_array_equal(expected1, out1) image2 = np.arange(5 * 8).reshape(5, 8) - out2 = block_mean(image2, (4, 5)) + out2 = local_mean(image2, (4, 5)) expected2 = np.array([[14. , 10.8], [ 8.5, 5.7]]) assert_array_equal(expected2, out2) -def test_block_median(): +def test_local_median(): image1 = np.arange(4 * 6).reshape(4, 6) - out1 = block_median(image1, (2, 3)) + out1 = local_median(image1, (2, 3)) expected1 = np.array([[ 4., 7.], [ 16., 19.]]) assert_array_equal(expected1, out1) image2 = np.arange(5 * 8).reshape(5, 8) - out2 = block_median(image2, (4, 5)) + out2 = local_median(image2, (4, 5)) expected2 = np.array([[ 14., 17.], [ 0., 0.]]) assert_array_equal(expected2, out2) image3 = np.array([[1, 5, 5, 5], [5, 5, 5, 1000]]) - out3 = block_median(image3, (2, 4)) + out3 = local_median(image3, (2, 4)) assert_array_equal(5, out3) -def test_block_min(): +def test_local_min(): image1 = np.arange(4 * 6).reshape(4, 6) - out1 = block_min(image1, (2, 3)) + out1 = local_min(image1, (2, 3)) expected1 = np.array([[ 0, 3], [12, 15]]) assert_array_equal(expected1, out1) image2 = np.arange(5 * 8).reshape(5, 8) - out2 = block_min(image2, (4, 5)) + out2 = local_min(image2, (4, 5)) expected2 = np.array([[0, 0], [0, 0]]) assert_array_equal(expected2, out2) -def test_block_max(): +def test_local_max(): image1 = np.arange(4 * 6).reshape(4, 6) - out1 = block_max(image1, (2, 3)) + out1 = local_max(image1, (2, 3)) expected1 = np.array([[ 8, 11], [20, 23]]) assert_array_equal(expected1, out1) image2 = np.arange(5 * 8).reshape(5, 8) - out2 = block_max(image2, (4, 5)) + out2 = local_max(image2, (4, 5)) expected2 = np.array([[28, 31], [36, 39]]) assert_array_equal(expected2, out2) diff --git a/skimage/transform/_warps.py b/skimage/transform/_warps.py index c3d918ee..6511182b 100644 --- a/skimage/transform/_warps.py +++ b/skimage/transform/_warps.py @@ -2,7 +2,7 @@ import numpy as np from scipy import ndimage from ._geometric import warp, SimilarityTransform, AffineTransform -from ..measure.blocks import _block_func +from ..measure.local import _local_func def resize(image, output_shape, order=1, mode='constant', cval=0.): @@ -260,7 +260,7 @@ def downscale_local_mean(image, factors): [5.5, 4.5]]) """ - return _block_func(image, factors, np.mean) + return _local_func(image, factors, np.mean) def _swirl_mapping(xy, center, rotation, strength, radius):