From 7282f561d43312174fdf6b2c82c514e8e87a93ed Mon Sep 17 00:00:00 2001 From: Ankit Agrawal Date: Mon, 6 May 2013 23:45:01 +0530 Subject: [PATCH] Added docs, tests for downsample() in skimage.transform._warps --- skimage/transform/__init__.py | 3 +- skimage/transform/_warps.py | 61 +++++++++++++++++++++++++++ skimage/transform/rescale.py | 60 -------------------------- skimage/transform/tests/test_warps.py | 29 ++++++++++++- skimage/util/shape.py | 12 ++++++ 5 files changed, 103 insertions(+), 62 deletions(-) delete mode 100644 skimage/transform/rescale.py diff --git a/skimage/transform/__init__.py b/skimage/transform/__init__.py index 859c7515..311801be 100644 --- a/skimage/transform/__init__.py +++ b/skimage/transform/__init__.py @@ -9,7 +9,7 @@ from ._geometric import (warp, warp_coords, estimate_transform, SimilarityTransform, AffineTransform, ProjectiveTransform, PolynomialTransform, PiecewiseAffineTransform) -from ._warps import swirl, resize, rotate, rescale +from ._warps import swirl, resize, rotate, rescale, downscale_local_means from .pyramids import (pyramid_reduce, pyramid_expand, pyramid_gaussian, pyramid_laplacian) @@ -39,6 +39,7 @@ __all__ = ['hough_circle', 'resize', 'rotate', 'rescale', + 'downscale_local_means', 'pyramid_reduce', 'pyramid_expand', 'pyramid_gaussian', diff --git a/skimage/transform/_warps.py b/skimage/transform/_warps.py index caf2baaf..513c8f01 100644 --- a/skimage/transform/_warps.py +++ b/skimage/transform/_warps.py @@ -1,6 +1,8 @@ import numpy as np from scipy import ndimage + from ._geometric import warp, SimilarityTransform, AffineTransform +from skimage.util.shape import view_as_blocks, _pad_asymmetric_zeros def resize(image, output_shape, order=1, mode='constant', cval=0.): @@ -283,3 +285,62 @@ def swirl(image, center=None, strength=1, radius=100, rotation=0, return warp(image, _swirl_mapping, map_args=warp_args, output_shape=output_shape, order=order, mode=mode, cval=cval) + + +def downsample(array, factors, mode='sum'): + """Performs downsampling with integer factors. + + Parameters + ---------- + array : ndarray + Input n-dimensional array. + factors: tuple + Tuple containing downsampling factor along each axis. + mode : string + Decides whether the downsampled element is the sum or mean + of its corresponding constituent elements in the input array. Default + is 'sum'. + + Returns + ------- + array : ndarray + Downsampled array with same number of dimensions as that of input + array. + + Example + ------- + >>> a = np.arange(15).reshape(3, 5) + >>> a + array([[ 0, 1, 2, 3, 4], + [ 5, 6, 7, 8, 9], + [10, 11, 12, 13, 14]]) + >>> downsample(a, (2,3)) + array([[21, 24], + [33, 27]]) + + """ + + pad_size = [] + if len(factors) != array.ndim: + raise ValueError("'factors' must have the same length " + "as 'array.shape'") + else: + for i in range(len(factors)): + if array.shape[i] % factors[i] != 0: + pad_size.append(factors[i] - (array.shape[i] % factors[i])) + else: + pad_size.append(0) + + for i in range(len(pad_size)): + array = _pad_asymmetric_zeros(array, pad_size[i], i) + + out = view_as_blocks(array, factors) + block_shape = out.shape + + if mode == 'sum': + for i in range(len(block_shape)/2): + out = out.sum(-1) + else: + for i in range(len(block_shape)/2): + out = out.mean(-1) + return out diff --git a/skimage/transform/rescale.py b/skimage/transform/rescale.py deleted file mode 100644 index 653bb222..00000000 --- a/skimage/transform/rescale.py +++ /dev/null @@ -1,60 +0,0 @@ -# TODO : Doc, Tests, PEP8 check - -import numpy as np -from skimage.util.shape import view_as_blocks - - -def _pad_asymmetric_zeros(arr, pad_amt, axis=-1): - """Pads `arr` by `pad_amt` along specified `axis`""" - if axis == -1: - axis = arr.ndim - 1 - - zeroshape = tuple([x if i != axis else pad_amt - for (i, x) in enumerate(arr.shape)]) - - return np.concatenate((arr, np.zeros(zeroshape, dtype=arr.dtype)), - axis=axis) - - -def downsample(image, factors, method='sum'): - - pad_size = [] - if len(factors) != image.ndim: - raise ValueError("'factors' must have the same length " - "as 'image.shape'") - else: - for i in range(len(factors)): - if image.shape[i] % factors[i] != 0: - pad_size.append(factors[i] - (image.shape[i] % factors[i])) - else: - pad_size.append(0) - - for i in range(len(pad_size)): - image = _pad_asymmetric_zeros(image, pad_size[i], i) - - out = view_as_blocks(image, factors) - block_shape = out.shape - - if method == 'sum': - for i in range(len(block_shape)/2): - out = out.sum(-1) - else: - for i in range(len(block_shape)/2): - out = out.mean(-1) - return out - -def upsample(image, factors, method='divide'): - - f = factors - - if (f[0] - int(f[0]) != 0) or (f[1] - int(f[1]) != 0): - raise ValueError('Use resample() for non-integer upsampling') - out = np.zeros((f[0] * image.shape[0], f[1] * image.shape[1])) - - for i in range(out.shape[0]): - for j in range(out.shape[1]): - out[i][j] = (image[i / f[0]][j / f[1]]) - if method == 'divide': - return out / float(f[0] * f[1]) - else: - return out diff --git a/skimage/transform/tests/test_warps.py b/skimage/transform/tests/test_warps.py index 93f87320..a2cd2b05 100644 --- a/skimage/transform/tests/test_warps.py +++ b/skimage/transform/tests/test_warps.py @@ -1,4 +1,4 @@ -from numpy.testing import assert_array_almost_equal, run_module_suite +from numpy.testing import assert_array_almost_equal, run_module_suite, assert_array_equal import numpy as np from scipy.ndimage import map_coordinates @@ -193,6 +193,33 @@ def test_warp_coords_example(): coords = warp_coords(tform, (30, 30, 3)) map_coordinates(image[:, :, 0], coords[:2]) +def test_downsample_sum(): + """Verifying downsampling of an array with expected result in sum mode""" + image1 = np.arange(4*6).reshape(4, 6) + out1 = tf.downsample(image1, (2, 3)) + expected1 = np.array([[ 24, 42], + [ 96, 114]]) + assert_array_equal(expected1, out1) + image2 = np.arange(5*8).reshape(5, 8) + out2 = tf.downsample(image2, (3, 3)) + expected2 = np.array([[ 81, 108, 87], + [174, 192, 138]]) + assert_array_equal(expected2, out2) + + +def test_downsample_mean(): + """Verifying downsampling of an array with expected result in mean mode""" + image1 = np.arange(4*6).reshape(4, 6) + out1 = tf.downsample(image1, (2, 3), 'mean') + expected1 = np.array([[ 4., 7.], + [ 16., 19.]]) + assert_array_equal(expected1, out1) + image2 = np.arange(5*8).reshape(5, 8) + out2 = tf.downsample(image2, (4, 5), 'mean') + expected2 = np.array([[ 14. , 10.8], + [ 8.5, 5.7]]) + assert_array_equal(expected2, out2) + if __name__ == "__main__": run_module_suite() diff --git a/skimage/util/shape.py b/skimage/util/shape.py index 0126d2e3..2763d3d4 100644 --- a/skimage/util/shape.py +++ b/skimage/util/shape.py @@ -230,3 +230,15 @@ def view_as_windows(arr_in, window_shape): arr_out = as_strided(arr_in, shape=new_shape, strides=new_strides) return arr_out + + +def _pad_asymmetric_zeros(arr, pad_amt, axis=-1): + """Pads `arr` with zeros by `pad_amt` along specified `axis`""" + if axis == -1: + axis = arr.ndim - 1 + + zeroshape = tuple([x if i != axis else pad_amt + for (i, x) in enumerate(arr.shape)]) + + return np.concatenate((arr, np.zeros(zeroshape, dtype=arr.dtype)), + axis=axis)