From a8a39ebf35130f865e3a9829708cdf73e19643e2 Mon Sep 17 00:00:00 2001 From: emmanuelle Date: Sat, 9 May 2015 12:08:21 +0200 Subject: [PATCH] Used new function to generate binary blobs in existing gallery example --- .../plot_random_walker_segmentation.py | 25 +++---------------- 1 file changed, 3 insertions(+), 22 deletions(-) diff --git a/doc/examples/plot_random_walker_segmentation.py b/doc/examples/plot_random_walker_segmentation.py index fa70e503..0c494de5 100644 --- a/doc/examples/plot_random_walker_segmentation.py +++ b/doc/examples/plot_random_walker_segmentation.py @@ -25,30 +25,11 @@ from scipy import ndimage import matplotlib.pyplot as plt from skimage.segmentation import random_walker - - -def microstructure(l=256): - """ - Synthetic binary data: binary microstructure with blobs. - - Parameters - ---------- - - l: int, optional - linear size of the returned image - """ - n = 5 - x, y = np.ogrid[0:l, 0:l] - mask = np.zeros((l, l)) - generator = np.random.RandomState(1) - points = l * generator.rand(2, n ** 2) - mask[(points[0]).astype(np.int), (points[1]).astype(np.int)] = 1 - mask = ndimage.gaussian_filter(mask, sigma=l / (4. * n)) - return (mask > mask.mean()).astype(np.float) - +from skimage.data import binary_blobs +import skimage # Generate noisy synthetic data -data = microstructure(l=128) +data = skimage.img_as_float(binary_blobs(length=128, seed=1)) data += 0.35 * np.random.randn(*data.shape) markers = np.zeros(data.shape, dtype=np.uint) markers[data < -0.3] = 1