Use isort

.git-blame-ignore-revs

@@ -6,3 +6,4 @@ bb473f6ff4a23e4fd5205eacdef713db15decadf
 8d00b416689c428b2bafdaad61ed3ec660ca06c2
 d6b447cab8c40aa47dc675a0f4349ae254e8b3ce
 d8966d848af75751823e825eb76c5bbff58f5c07
+9980f7a61b32515a92a09fdcc27e21a2521a0467

advanced/advanced_numpy/examples/mandelplot.py

@@ -6,8 +6,8 @@
 
 """
 
-import numpy as np
 import mandel
+import numpy as np
 
 x = np.linspace(-1.7, 0.6, 1000)
 y = np.linspace(-1.4, 1.4, 1000)

advanced/advanced_numpy/examples/pilbuffer-answer.py

@@ -6,8 +6,8 @@
 the buffer interface.
 """
 
-import numpy as np
 import Image
+import numpy as np
 
 # Let's make a sample image, RGBA format
 

advanced/advanced_numpy/examples/pilbuffer.py

@@ -5,8 +5,8 @@
 Skeletton of the code to do an exercise using the buffer protocole.
 """
 
-import numpy as np
 import Image
+import numpy as np
 
 # Let's make a sample image, RGBA format
 

advanced/advanced_numpy/examples/plots/plot_maskedstats.py

@@ -6,8 +6,8 @@
 
 """
 
-import numpy as np
 import matplotlib.pyplot as plt
+import numpy as np
 
 data = np.loadtxt("../../../../data/populations.txt")
 populations = np.ma.masked_array(data[:, 1:])

advanced/advanced_numpy/examples/setup.py

@@ -8,8 +8,9 @@
 
 import os
 import sys
-from os.path import join
 from distutils.sysconfig import get_python_inc
+from os.path import join
+
 import numpy
 from numpy.distutils.misc_util import get_numpy_include_dirs
 

advanced/advanced_numpy/examples/setup_myobject.py

@@ -6,7 +6,7 @@
 
 """
 
-from distutils.core import setup, Extension
+from distutils.core import Extension, setup
 
 setup(
     name="myobject",

advanced/advanced_numpy/examples/wavreader.py

@@ -6,6 +6,7 @@
 """
 
 import sys
+
 import numpy as np
 
 wav_header_dtype = np.dtype(

advanced/debugging/wiener_filtering.py

@@ -1,8 +1,8 @@
 """Wiener filtering a noisy raccoon face: this module is buggy"""
 
+import matplotlib.pyplot as plt
 import numpy as np
 import scipy as sp
-import matplotlib.pyplot as plt
 
 
 def local_mean(img, size=3):

advanced/image_processing/examples/plot_GMM.py

@@ -8,9 +8,9 @@
 
 """
 
+import matplotlib.pyplot as plt
 import numpy as np
 import scipy as sp
-import matplotlib.pyplot as plt
 from sklearn.mixture import GaussianMixture
 
 rng = np.random.default_rng(27446968)

advanced/image_processing/examples/plot_block_mean.py

@@ -6,9 +6,9 @@
 blocks of an image.
 """
 
+import matplotlib.pyplot as plt
 import numpy as np
 import scipy as sp
-import matplotlib.pyplot as plt
 
 f = sp.datasets.face(gray=True)
 sx, sy = f.shape

advanced/image_processing/examples/plot_blur.py

@@ -5,8 +5,8 @@
 An example showing various processes that blur an image.
 """
 
-import scipy as sp
 import matplotlib.pyplot as plt
+import scipy as sp
 
 face = sp.datasets.face(gray=True)
 blurred_face = sp.ndimage.gaussian_filter(face, sigma=3)

advanced/image_processing/examples/plot_clean_morpho.py

@@ -7,9 +7,9 @@
 
 """
 
+import matplotlib.pyplot as plt
 import numpy as np
 import scipy as sp
-import matplotlib.pyplot as plt
 
 rng = np.random.default_rng(27446968)
 n = 10

advanced/image_processing/examples/plot_denoising.py

@@ -6,9 +6,9 @@
 one (with the median filter) and the difference between the two.
 """
 
+import matplotlib.pyplot as plt
 import numpy as np
 import scipy as sp
-import matplotlib.pyplot as plt
 
 rng = np.random.default_rng(27446968)
 

advanced/image_processing/examples/plot_display_face.py

@@ -5,8 +5,8 @@
 An example that displays a raccoon face with matplotlib.
 """
 
-import scipy as sp
 import matplotlib.pyplot as plt
+import scipy as sp
 
 f = sp.datasets.face(gray=True)
 

advanced/image_processing/examples/plot_face.py

@@ -5,8 +5,8 @@
 Small example to plot a raccoon face.
 """
 
-import scipy as sp
 import imageio.v3 as iio
+import scipy as sp
 
 f = sp.datasets.face()
 iio.imwrite("face.png", f)  # uses the Image module (PIL)

advanced/image_processing/examples/plot_face_denoise.py

@@ -5,9 +5,9 @@
 This example demoes image denoising on a Raccoon face.
 """
 
+import matplotlib.pyplot as plt
 import numpy as np
 import scipy as sp
-import matplotlib.pyplot as plt
 
 rng = np.random.default_rng(27446968)
 

advanced/image_processing/examples/plot_face_tv_denoise.py

@@ -5,10 +5,9 @@
 This example demoes Total-Variation (TV) denoising on a Raccoon face.
 """
 
+import matplotlib.pyplot as plt
 import numpy as np
 import scipy as sp
-import matplotlib.pyplot as plt
-
 from skimage.restoration import denoise_tv_chambolle
 
 rng = np.random.default_rng(27446968)

advanced/image_processing/examples/plot_find_edges.py

@@ -5,9 +5,9 @@
 The Sobel filter is one of the simplest way of finding edges.
 """
 
+import matplotlib.pyplot as plt
 import numpy as np
 import scipy as sp
-import matplotlib.pyplot as plt
 
 rng = np.random.default_rng(27446968)
 

advanced/image_processing/examples/plot_find_object.py

@@ -6,9 +6,9 @@
 
 """
 
+import matplotlib.pyplot as plt
 import numpy as np
 import scipy as sp
-import matplotlib.pyplot as plt
 
 rng = np.random.default_rng(27446968)
 n = 10

advanced/image_processing/examples/plot_geom_face.py

@@ -5,9 +5,9 @@
 This examples demos some simple geometrical transformations on a Raccoon face.
 """
 
+import matplotlib.pyplot as plt
 import numpy as np
 import scipy as sp
-import matplotlib.pyplot as plt
 
 face = sp.datasets.face(gray=True)
 lx, ly = face.shape

advanced/image_processing/examples/plot_granulo.py

@@ -5,9 +5,9 @@
 This example performs a simple granulometry analysis.
 """
 
+import matplotlib.pyplot as plt
 import numpy as np
 import scipy as sp
-import matplotlib.pyplot as plt
 
 
 def disk_structure(n):

advanced/image_processing/examples/plot_greyscale_dilation.py

@@ -5,9 +5,9 @@
 This example illustrates greyscale mathematical morphology.
 """
 
+import matplotlib.pyplot as plt
 import numpy as np
 import scipy as sp
-import matplotlib.pyplot as plt
 
 im = np.zeros((64, 64))
 rng = np.random.default_rng(27446968)

advanced/image_processing/examples/plot_histo_segmentation.py

@@ -5,9 +5,9 @@
 This example does simple histogram analysis to perform segmentation.
 """
 
+import matplotlib.pyplot as plt
 import numpy as np
 import scipy as sp
-import matplotlib.pyplot as plt
 
 rng = np.random.default_rng(27446968)
 n = 10

advanced/image_processing/examples/plot_interpolation_face.py

@@ -5,8 +5,8 @@
 The example demonstrates image interpolation on a Raccoon face.
 """
 
-import scipy as sp
 import matplotlib.pyplot as plt
+import scipy as sp
 
 f = sp.datasets.face(gray=True)
 

advanced/image_processing/examples/plot_measure_data.py

@@ -6,9 +6,9 @@
 
 """
 
+import matplotlib.pyplot as plt
 import numpy as np
 import scipy as sp
-import matplotlib.pyplot as plt
 
 rng = np.random.default_rng(27446968)
 n = 10

advanced/image_processing/examples/plot_numpy_array.py

@@ -7,9 +7,9 @@
 
 """
 
+import matplotlib.pyplot as plt
 import numpy as np
 import scipy as sp
-import matplotlib.pyplot as plt
 
 face = sp.datasets.face(gray=True)
 face[10:13, 20:23]

advanced/image_processing/examples/plot_propagation.py

@@ -5,9 +5,9 @@
 This example shows simple operations of mathematical morphology.
 """
 
+import matplotlib.pyplot as plt
 import numpy as np
 import scipy as sp
-import matplotlib.pyplot as plt
 
 square = np.zeros((32, 32))
 square[10:-10, 10:-10] = 1

advanced/image_processing/examples/plot_radial_mean.py

@@ -5,9 +5,9 @@
 This example shows how to do a radial mean with scikit-image.
 """
 
+import matplotlib.pyplot as plt
 import numpy as np
 import scipy as sp
-import matplotlib.pyplot as plt
 
 f = sp.datasets.face(gray=True)
 sx, sy = f.shape

advanced/image_processing/examples/plot_sharpen.py

@@ -6,8 +6,8 @@
 applying the filter inverse to the blur.
 """
 
-import scipy as sp
 import matplotlib.pyplot as plt
+import scipy as sp
 
 f = sp.datasets.face(gray=True).astype(float)
 blurred_f = sp.ndimage.gaussian_filter(f, 3)

advanced/image_processing/examples/plot_spectral_clustering.py

@@ -5,11 +5,10 @@
 This example uses spectral clustering to do segmentation.
 """
 
-import numpy as np
 import matplotlib.pyplot as plt
-
-from sklearn.feature_extraction import image
+import numpy as np
 from sklearn.cluster import spectral_clustering
+from sklearn.feature_extraction import image
 
 ################################################################################
 l = 100

advanced/image_processing/examples/plot_synthetic_data.py

@@ -5,9 +5,9 @@
 The example generates and displays simple synthetic data.
 """
 
+import matplotlib.pyplot as plt
 import numpy as np
 import scipy as sp
-import matplotlib.pyplot as plt
 
 rng = np.random.default_rng(27446968)
 n = 10

advanced/image_processing/examples/plot_watershed_segmentation.py

@@ -5,11 +5,11 @@
 This example shows how to do segmentation with watershed.
 """
 
-import numpy as np
-from skimage.segmentation import watershed
-from skimage.feature import peak_local_max
 import matplotlib.pyplot as plt
+import numpy as np
 import scipy as sp
+from skimage.feature import peak_local_max
+from skimage.segmentation import watershed
 
 # Generate an initial image with two overlapping circles
 x, y = np.indices((80, 80))

advanced/interfacing_with_c/ctypes/cos_module.py

@@ -3,7 +3,6 @@
 import ctypes
 
 # find and load the library
-
 # OSX or linux
 from ctypes.util import find_library
 

advanced/interfacing_with_c/ctypes_numpy/cos_doubles.py

@@ -1,9 +1,10 @@
 """Example of wrapping a C library function that accepts a C double array as
 input using the numpy.ctypeslib."""
 
+from ctypes import c_int
+
 import numpy as np
 import numpy.ctypeslib as npct
-from ctypes import c_int
 
 # input type for the cos_doubles function
 # must be a double array, with single dimension that is contiguous

advanced/interfacing_with_c/cython/setup.py

@@ -1,4 +1,5 @@
-from distutils.core import setup, Extension
+from distutils.core import Extension, setup
+
 from Cython.Distutils import build_ext
 
 setup(

advanced/interfacing_with_c/cython_numpy/setup.py

@@ -1,4 +1,5 @@
-from distutils.core import setup, Extension
+from distutils.core import Extension, setup
+
 import numpy
 from Cython.Distutils import build_ext
 

advanced/interfacing_with_c/cython_simple/setup.py

@@ -1,4 +1,5 @@
-from distutils.core import setup, Extension
+from distutils.core import Extension, setup
+
 from Cython.Distutils import build_ext
 
 setup(

advanced/interfacing_with_c/numpy_c_api/setup.py

@@ -1,4 +1,5 @@
-from distutils.core import setup, Extension
+from distutils.core import Extension, setup
+
 import numpy
 
 # define the extension module