From a89dd4deddb4052426fcea706bd0e75fd97218a6 Mon Sep 17 00:00:00 2001
From: Siva Prasad Varma <sivapvarma@gmail.com>
Date: Wed, 19 Mar 2014 17:18:33 +0530
Subject: [PATCH] changed f to fig

---
 doc/examples/plot_canny.py                    |  4 ++--
 doc/examples/plot_contours.py                 |  2 +-
 doc/examples/plot_corner.py                   |  2 +-
 doc/examples/plot_daisy.py                    |  2 +-
 doc/examples/plot_entropy.py                  |  4 ++--
 doc/examples/plot_equalize.py                 |  4 ++--
 doc/examples/plot_hog.py                      |  2 +-
 doc/examples/plot_holes_and_peaks.py          |  2 +-
 doc/examples/plot_ihc_color_separation.py     |  2 +-
 doc/examples/plot_line_hough_transform.py     |  4 ++--
 doc/examples/plot_local_equalize.py           |  4 ++--
 doc/examples/plot_local_otsu.py               |  6 +++---
 doc/examples/plot_medial_transform.py         |  4 ++--
 doc/examples/plot_otsu.py                     |  2 +-
 doc/examples/plot_peak_local_max.py           |  4 ++--
 doc/examples/plot_phase_unwrap.py             | 20 +++++++++----------
 doc/examples/plot_piecewise_affine.py         |  2 +-
 doc/examples/plot_pyramid.py                  |  2 +-
 doc/examples/plot_radon_transform.py          |  8 ++++----
 .../plot_random_walker_segmentation.py        |  4 ++--
 doc/examples/plot_ransac.py                   |  2 +-
 doc/examples/plot_regional_maxima.py          |  4 ++--
 doc/examples/plot_regionprops.py              |  2 +-
 doc/examples/plot_skeleton.py                 |  4 ++--
 doc/examples/plot_ssim.py                     |  2 +-
 doc/examples/plot_swirl.py                    |  2 +-
 26 files changed, 50 insertions(+), 50 deletions(-)

diff --git a/doc/examples/plot_canny.py b/doc/examples/plot_canny.py
index 25b7e6ac..f1caf264 100644
--- a/doc/examples/plot_canny.py
+++ b/doc/examples/plot_canny.py
@@ -35,7 +35,7 @@ edges1 = filter.canny(im)
 edges2 = filter.canny(im, sigma=3)
 
 # display results
-f, (ax1, ax2, ax3) = plt.subplots(nrows=1, ncols=3, figsize=(8, 3))
+fig, (ax1, ax2, ax3) = plt.subplots(nrows=1, ncols=3, figsize=(8, 3))
 
 ax1.imshow(im, cmap=plt.cm.jet)
 ax1.axis('off')
@@ -49,7 +49,7 @@ ax3.imshow(edges2, cmap=plt.cm.gray)
 ax3.axis('off')
 ax3.set_title('Canny filter, $\sigma=3$', fontsize=20)
 
-f.subplots_adjust(wspace=0.02, hspace=0.02, top=0.9,
+fig.subplots_adjust(wspace=0.02, hspace=0.02, top=0.9,
                     bottom=0.02, left=0.02, right=0.98)
 
 plt.show()
diff --git a/doc/examples/plot_contours.py b/doc/examples/plot_contours.py
index 1be586a9..e686b4ac 100644
--- a/doc/examples/plot_contours.py
+++ b/doc/examples/plot_contours.py
@@ -29,7 +29,7 @@ r = np.sin(np.exp((np.sin(x)**3 + np.cos(y)**2)))
 contours = measure.find_contours(r, 0.8)
 
 # Display the image and plot all contours found
-f, ax = plt.subplots()
+fig, ax = plt.subplots()
 ax.imshow(r, interpolation='nearest', cmap=plt.cm.gray)
 
 for n, contour in enumerate(contours):
diff --git a/doc/examples/plot_corner.py b/doc/examples/plot_corner.py
index 45cc1c75..4e962e17 100644
--- a/doc/examples/plot_corner.py
+++ b/doc/examples/plot_corner.py
@@ -29,7 +29,7 @@ image[230:280, 60:110] = 1
 coords = corner_peaks(corner_harris(image), min_distance=5)
 coords_subpix = corner_subpix(image, coords, window_size=13)
 
-f, ax = plt.subplots()
+fig, ax = plt.subplots()
 ax.imshow(image, interpolation='nearest', cmap=plt.cm.gray)
 ax.plot(coords[:, 1], coords[:, 0], '.b', markersize=3)
 ax.plot(coords_subpix[:, 1], coords_subpix[:, 0], '+r', markersize=15)
diff --git a/doc/examples/plot_daisy.py b/doc/examples/plot_daisy.py
index 35504875..128d6e67 100644
--- a/doc/examples/plot_daisy.py
+++ b/doc/examples/plot_daisy.py
@@ -20,7 +20,7 @@ img = data.camera()
 descs, descs_img = daisy(img, step=180, radius=58, rings=2, histograms=6,
                          orientations=8, visualize=True)
 
-f, ax = plt.subplots()
+fig, ax = plt.subplots()
 ax.axis('off')
 ax.imshow(descs_img)
 descs_num = descs.shape[0] * descs.shape[1]
diff --git a/doc/examples/plot_entropy.py b/doc/examples/plot_entropy.py
index 9f208c73..b92a5bf3 100644
--- a/doc/examples/plot_entropy.py
+++ b/doc/examples/plot_entropy.py
@@ -22,11 +22,11 @@ fig, (ax0, ax1) = plt.subplots(ncols=2, figsize=(10, 4))
 img0 = ax0.imshow(image, cmap=plt.cm.gray)
 ax0.set_title('Image')
 ax0.axis('off')
-plt.colorbar(img0, ax=ax0)
+fig.colorbar(img0, ax=ax0)
 
 img1 = ax1.imshow(entropy(image, disk(5)), cmap=plt.cm.jet)
 ax1.set_title('Entropy')
 ax1.axis('off')
-plt.colorbar(img1, ax=ax1)
+fig.colorbar(img1, ax=ax1)
 
 plt.show()
diff --git a/doc/examples/plot_equalize.py b/doc/examples/plot_equalize.py
index 077645a1..2d04e22a 100644
--- a/doc/examples/plot_equalize.py
+++ b/doc/examples/plot_equalize.py
@@ -70,7 +70,7 @@ img_eq = exposure.equalize_hist(img)
 img_adapteq = exposure.equalize_adapthist(img, clip_limit=0.03)
 
 # Display results
-f, axes = plt.subplots(nrows=2, ncols=4, figsize=(8, 5))
+fig, axes = plt.subplots(nrows=2, ncols=4, figsize=(8, 5))
 
 ax_img, ax_hist, ax_cdf = plot_img_and_hist(img, axes[:, 0])
 ax_img.set_title('Low contrast image')
@@ -92,5 +92,5 @@ ax_cdf.set_ylabel('Fraction of total intensity')
 ax_cdf.set_yticks(np.linspace(0, 1, 5))
 
 # prevent overlap of y-axis labels
-f.subplots_adjust(wspace=0.4)
+fig.subplots_adjust(wspace=0.4)
 plt.show()
diff --git a/doc/examples/plot_hog.py b/doc/examples/plot_hog.py
index 21700089..4899c590 100644
--- a/doc/examples/plot_hog.py
+++ b/doc/examples/plot_hog.py
@@ -90,7 +90,7 @@ image = color.rgb2gray(data.lena())
 fd, hog_image = hog(image, orientations=8, pixels_per_cell=(16, 16),
                     cells_per_block=(1, 1), visualise=True)
 
-f, (ax1, ax2) = plt.subplots(1, 2, figsize=(8, 4))
+fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(8, 4))
 
 ax1.axis('off')
 ax1.imshow(image, cmap=plt.cm.gray)
diff --git a/doc/examples/plot_holes_and_peaks.py b/doc/examples/plot_holes_and_peaks.py
index d4a53f67..791c69ee 100644
--- a/doc/examples/plot_holes_and_peaks.py
+++ b/doc/examples/plot_holes_and_peaks.py
@@ -23,7 +23,7 @@ image = rescale_intensity(image, in_range=(50, 200))
 
 # convenience function for plotting images
 def imshow(image, title, **kwargs):
-    f, ax = plt.subplots(figsize=(5, 4))
+    fig, ax = plt.subplots(figsize=(5, 4))
     ax.imshow(image, **kwargs)
     ax.axis('off')
     ax.set_title(title)
diff --git a/doc/examples/plot_ihc_color_separation.py b/doc/examples/plot_ihc_color_separation.py
index f7bf689e..3e297386 100644
--- a/doc/examples/plot_ihc_color_separation.py
+++ b/doc/examples/plot_ihc_color_separation.py
@@ -61,7 +61,7 @@ h = rescale_intensity(ihc_hed[:, :, 0], out_range=(0, 1))
 d = rescale_intensity(ihc_hed[:, :, 2], out_range=(0, 1))
 zdh = np.dstack((np.zeros_like(h), d, h))
 
-f, ax = plt.subplots()
+fig, ax = plt.subplots()
 ax.imshow(zdh)
 ax.set_title("Stain separated image (rescaled)")
 ax.axis('off')
diff --git a/doc/examples/plot_line_hough_transform.py b/doc/examples/plot_line_hough_transform.py
index 271bc598..bdb05661 100644
--- a/doc/examples/plot_line_hough_transform.py
+++ b/doc/examples/plot_line_hough_transform.py
@@ -77,7 +77,7 @@ image[idx, idx] = 255
 
 h, theta, d = hough_line(image)
 
-f, ax = plt.subplots(1, 3, figsize=(8, 4))
+fig, ax = plt.subplots(1, 3, figsize=(8, 4))
 
 ax[0].imshow(image, cmap=plt.cm.gray)
 ax[0].set_title('Input image')
@@ -108,7 +108,7 @@ image = data.camera()
 edges = canny(image, 2, 1, 25)
 lines = probabilistic_hough_line(edges, threshold=10, line_length=5, line_gap=3)
 
-f2, ax = plt.subplots(1, 3, figsize=(8, 3))
+fig2, ax = plt.subplots(1, 3, figsize=(8, 3))
 
 ax[0].imshow(image, cmap=plt.cm.gray)
 ax[0].set_title('Input image')
diff --git a/doc/examples/plot_local_equalize.py b/doc/examples/plot_local_equalize.py
index 309d1e43..b3c11d55 100644
--- a/doc/examples/plot_local_equalize.py
+++ b/doc/examples/plot_local_equalize.py
@@ -72,7 +72,7 @@ img_eq = rank.equalize(img, selem=selem)
 
 
 # Display results
-f, axes = plt.subplots(2, 3, figsize=(8, 5))
+fig, axes = plt.subplots(2, 3, figsize=(8, 5))
 
 ax_img, ax_hist, ax_cdf = plot_img_and_hist(img, axes[:, 0])
 ax_img.set_title('Low contrast image')
@@ -87,5 +87,5 @@ ax_cdf.set_ylabel('Fraction of total intensity')
 
 
 # prevent overlap of y-axis labels
-plt.subplots_adjust(wspace=0.4)
+fig.subplots_adjust(wspace=0.4)
 plt.show()
diff --git a/doc/examples/plot_local_otsu.py b/doc/examples/plot_local_otsu.py
index ec3cdf48..d40af6b6 100644
--- a/doc/examples/plot_local_otsu.py
+++ b/doc/examples/plot_local_otsu.py
@@ -37,15 +37,15 @@ threshold_global_otsu = threshold_otsu(img)
 global_otsu = img >= threshold_global_otsu
 
 
-f, ax = plt.subplots(2, 2, figsize=(8, 5))
+fig, ax = plt.subplots(2, 2, figsize=(8, 5))
 ax1, ax2, ax3, ax4 = ax.ravel()
 
-f.colorbar(ax1.imshow(img, cmap=plt.cm.gray),
+fig.colorbar(ax1.imshow(img, cmap=plt.cm.gray),
            ax=ax1, orientation='horizontal')
 ax1.set_title('Original')
 ax1.axis('off')
 
-f.colorbar(ax2.imshow(local_otsu, cmap=plt.cm.gray),
+fig.colorbar(ax2.imshow(local_otsu, cmap=plt.cm.gray),
            ax=ax2, orientation='horizontal')
 ax2.set_title('Local Otsu (radius=%d)' % radius)
 ax2.axis('off')
diff --git a/doc/examples/plot_medial_transform.py b/doc/examples/plot_medial_transform.py
index 4182fc8d..1a8469b2 100644
--- a/doc/examples/plot_medial_transform.py
+++ b/doc/examples/plot_medial_transform.py
@@ -55,12 +55,12 @@ skel, distance = medial_axis(data, return_distance=True)
 # Distance to the background for pixels of the skeleton
 dist_on_skel = distance * skel
 
-f, (ax1, ax2) = plt.subplots(1, 2, figsize=(8, 4))
+fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(8, 4))
 ax1.imshow(data, cmap=plt.cm.gray, interpolation='nearest')
 ax1.axis('off')
 ax2.imshow(dist_on_skel, cmap=plt.cm.spectral, interpolation='nearest')
 ax2.contour(data, [0.5], colors='w')
 ax2.axis('off')
 
-f.subplots_adjust(hspace=0.01, wspace=0.01, top=1, bottom=0, left=0, right=1)
+fig.subplots_adjust(hspace=0.01, wspace=0.01, top=1, bottom=0, left=0, right=1)
 plt.show()
diff --git a/doc/examples/plot_otsu.py b/doc/examples/plot_otsu.py
index a679acc5..059093ab 100644
--- a/doc/examples/plot_otsu.py
+++ b/doc/examples/plot_otsu.py
@@ -28,7 +28,7 @@ image = camera()
 thresh = threshold_otsu(image)
 binary = image > thresh
 
-f, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(8, 2.5))
+fig, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(8, 2.5))
 ax1.imshow(image, cmap=plt.cm.gray)
 ax1.set_title('Original')
 ax1.axis('off')
diff --git a/doc/examples/plot_peak_local_max.py b/doc/examples/plot_peak_local_max.py
index ce8ccf89..cebd5738 100644
--- a/doc/examples/plot_peak_local_max.py
+++ b/doc/examples/plot_peak_local_max.py
@@ -25,7 +25,7 @@ image_max = ndimage.maximum_filter(im, size=20, mode='constant')
 coordinates = peak_local_max(im, min_distance=20)
 
 # display results
-f, ax = plt.subplots(1, 3, figsize=(8, 3))
+fig, ax = plt.subplots(1, 3, figsize=(8, 3))
 ax1, ax2, ax3 = ax.ravel()
 ax1.imshow(im, cmap=plt.cm.gray)
 ax1.axis('off')
@@ -41,7 +41,7 @@ ax3.plot([p[1] for p in coordinates], [p[0] for p in coordinates], 'r.')
 ax3.axis('off')
 ax3.set_title('Peak local max')
 
-f.subplots_adjust(wspace=0.02, hspace=0.02, top=0.9,
+fig.subplots_adjust(wspace=0.02, hspace=0.02, top=0.9,
                     bottom=0.02, left=0.02, right=0.98)
 
 plt.show()
diff --git a/doc/examples/plot_phase_unwrap.py b/doc/examples/plot_phase_unwrap.py
index 09c33f90..84e5a781 100644
--- a/doc/examples/plot_phase_unwrap.py
+++ b/doc/examples/plot_phase_unwrap.py
@@ -26,19 +26,19 @@ image_wrapped = np.angle(np.exp(1j * image))
 # Perform phase unwrapping
 image_unwrapped = unwrap_phase(image_wrapped)
 
-f, ax = plt.subplots(2, 2)
+fig, ax = plt.subplots(2, 2)
 ax1, ax2, ax3, ax4 = ax.ravel()
 
-f.colorbar(ax1.imshow(image, cmap='gray', vmin=0, vmax=4 * np.pi), ax=ax1)
+fig.colorbar(ax1.imshow(image, cmap='gray', vmin=0, vmax=4 * np.pi), ax=ax1)
 ax1.set_title('Original')
 
-f.colorbar(ax2.imshow(image_wrapped, cmap='gray', vmin=-np.pi, vmax=np.pi), ax=ax2)
+fig.colorbar(ax2.imshow(image_wrapped, cmap='gray', vmin=-np.pi, vmax=np.pi), ax=ax2)
 ax2.set_title('Wrapped phase')
 
-f.colorbar(ax3.imshow(image_unwrapped, cmap='gray'), ax=ax3)
+fig.colorbar(ax3.imshow(image_unwrapped, cmap='gray'), ax=ax3)
 ax3.set_title('After phase unwrapping')
 
-f.colorbar(ax4.imshow(image_unwrapped - image, cmap='gray'), ax=ax4)
+fig.colorbar(ax4.imshow(image_unwrapped - image, cmap='gray'), ax=ax4)
 ax4.set_title('Unwrapped minus original')
 
 """
@@ -64,21 +64,21 @@ image_unwrapped_no_wrap_around = unwrap_phase(image_wrapped,
 image_unwrapped_wrap_around = unwrap_phase(image_wrapped,
                                            wrap_around=(True, False))
 
-f, ax = plt.subplots(2, 2)
+fig, ax = plt.subplots(2, 2)
 ax1, ax2, ax3, ax4 = ax.ravel()
 
-f.colorbar(ax1.imshow(np.ma.array(image, mask=mask), cmap='jet'), ax=ax1)
+fig.colorbar(ax1.imshow(np.ma.array(image, mask=mask), cmap='jet'), ax=ax1)
 ax1.set_title('Original')
 
-f.colorbar(ax2.imshow(image_wrapped, cmap='jet', vmin=-np.pi, vmax=np.pi),
+fig.colorbar(ax2.imshow(image_wrapped, cmap='jet', vmin=-np.pi, vmax=np.pi),
            ax=ax2)
 ax2.set_title('Wrapped phase')
 
-f.colorbar(ax3.imshow(image_unwrapped_no_wrap_around, cmap='jet'),
+fig.colorbar(ax3.imshow(image_unwrapped_no_wrap_around, cmap='jet'),
            ax=ax3)
 ax3.set_title('Unwrapped without wrap_around')
 
-f.colorbar(ax4.imshow(image_unwrapped_wrap_around, cmap='jet'), ax=ax4)
+fig.colorbar(ax4.imshow(image_unwrapped_wrap_around, cmap='jet'), ax=ax4)
 ax4.set_title('Unwrapped with wrap_around')
 
 plt.show()
diff --git a/doc/examples/plot_piecewise_affine.py b/doc/examples/plot_piecewise_affine.py
index a0eddd20..b1fb551f 100644
--- a/doc/examples/plot_piecewise_affine.py
+++ b/doc/examples/plot_piecewise_affine.py
@@ -35,7 +35,7 @@ out_rows = image.shape[0] - 1.5 * 50
 out_cols = cols
 out = warp(image, tform, output_shape=(out_rows, out_cols))
 
-f, ax = plt.subplots()
+fig, ax = plt.subplots()
 ax.imshow(out)
 ax.plot(tform.inverse(src)[:, 0], tform.inverse(src)[:, 1], '.b')
 ax.axis((0, out_cols, out_rows, 0))
diff --git a/doc/examples/plot_pyramid.py b/doc/examples/plot_pyramid.py
index c3fb6de9..8e309edf 100644
--- a/doc/examples/plot_pyramid.py
+++ b/doc/examples/plot_pyramid.py
@@ -30,6 +30,6 @@ for p in pyramid[1:]:
     composite_image[i_row:i_row + n_rows, cols:cols + n_cols] = p
     i_row += n_rows
 
-f, ax = plt.subplots()
+fig, ax = plt.subplots()
 ax.imshow(composite_image)
 plt.show()
diff --git a/doc/examples/plot_radon_transform.py b/doc/examples/plot_radon_transform.py
index 45e31ed5..04cf7bab 100644
--- a/doc/examples/plot_radon_transform.py
+++ b/doc/examples/plot_radon_transform.py
@@ -60,7 +60,7 @@ from skimage.transform import radon, rescale
 image = imread(data_dir + "/phantom.png", as_grey=True)
 image = rescale(image, scale=0.4)
 
-f, (ax1, ax2) = plt.subplots(1, 2, figsize=(8, 4.5))
+fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(8, 4.5))
 
 ax1.set_title("Original")
 ax1.imshow(image, cmap=plt.cm.Greys_r)
@@ -73,7 +73,7 @@ ax2.set_ylabel("Projection position (pixels)")
 ax2.imshow(sinogram, cmap=plt.cm.Greys_r,
            extent=(0, 180, 0, sinogram.shape[0]), aspect='auto')
 
-f.subplots_adjust(hspace=0.4, wspace=0.5)
+fig.subplots_adjust(hspace=0.4, wspace=0.5)
 plt.show()
 
 """
@@ -101,7 +101,7 @@ error = reconstruction_fbp - image
 print('FBP rms reconstruction error: %.3g' % np.sqrt(np.mean(error**2)))
 
 imkwargs = dict(vmin=-0.2, vmax=0.2)
-f, (ax1, ax2) = plt.subplots(1, 2, figsize=(8, 4.5))
+fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(8, 4.5))
 ax1.set_title("Reconstruction\nFiltered back projection")
 ax1.imshow(reconstruction_fbp, cmap=plt.cm.Greys_r)
 ax2.set_title("Reconstruction error\nFiltered back projection")
@@ -152,7 +152,7 @@ error = reconstruction_sart - image
 print('SART (1 iteration) rms reconstruction error: %.3g'
       % np.sqrt(np.mean(error**2)))
 
-f, ax = plt.subplots(2, 2, figsize=(8, 8.5))
+fig, ax = plt.subplots(2, 2, figsize=(8, 8.5))
 ax1, ax2, ax3, ax4 = ax.ravel()
 ax1.set_title("Reconstruction\nSART")
 ax1.imshow(reconstruction_sart, cmap=plt.cm.Greys_r)
diff --git a/doc/examples/plot_random_walker_segmentation.py b/doc/examples/plot_random_walker_segmentation.py
index 2f7d08b8..fa70e503 100644
--- a/doc/examples/plot_random_walker_segmentation.py
+++ b/doc/examples/plot_random_walker_segmentation.py
@@ -58,7 +58,7 @@ markers[data > 1.3] = 2
 labels = random_walker(data, markers, beta=10, mode='bf')
 
 # Plot results
-f, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(8, 3.2))
+fig, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(8, 3.2))
 ax1.imshow(data, cmap='gray', interpolation='nearest')
 ax1.axis('off')
 ax1.set_title('Noisy data')
@@ -69,6 +69,6 @@ ax3.imshow(labels, cmap='gray', interpolation='nearest')
 ax3.axis('off')
 ax3.set_title('Segmentation')
 
-f.subplots_adjust(hspace=0.01, wspace=0.01, top=1, bottom=0, left=0,
+fig.subplots_adjust(hspace=0.01, wspace=0.01, top=1, bottom=0, left=0,
                     right=1)
 plt.show()
diff --git a/doc/examples/plot_ransac.py b/doc/examples/plot_ransac.py
index 1fce1b3d..770e8cd1 100644
--- a/doc/examples/plot_ransac.py
+++ b/doc/examples/plot_ransac.py
@@ -45,7 +45,7 @@ line_x = np.arange(-250, 250)
 line_y = model.predict_y(line_x)
 line_y_robust = model_robust.predict_y(line_x)
 
-f, ax = plt.subplots()
+fig, ax = plt.subplots()
 ax.plot(data[inliers, 0], data[inliers, 1], '.b', alpha=0.6,
         label='Inlier data')
 ax.plot(data[outliers, 0], data[outliers, 1], '.r', alpha=0.6,
diff --git a/doc/examples/plot_regional_maxima.py b/doc/examples/plot_regional_maxima.py
index f7b125f1..dd676014 100644
--- a/doc/examples/plot_regional_maxima.py
+++ b/doc/examples/plot_regional_maxima.py
@@ -50,7 +50,7 @@ ax3.imshow(image - dilated)
 ax3.set_title('image - dilated')
 ax3.axis('off')
 
-plt.tight_layout()
+fig.tight_layout()
 
 """
 
@@ -98,7 +98,7 @@ ax3.axhline(yslice, color='r', alpha=0.4)
 ax3.set_title('image - dilated')
 ax3.axis('off')
 
-plt.tight_layout()
+fig.tight_layout()
 plt.show()
 
 """
diff --git a/doc/examples/plot_regionprops.py b/doc/examples/plot_regionprops.py
index e989c709..065bae55 100644
--- a/doc/examples/plot_regionprops.py
+++ b/doc/examples/plot_regionprops.py
@@ -26,7 +26,7 @@ image = rotate(image, angle=15, order=0)
 label_img = label(image)
 regions = regionprops(label_img)
 
-f, ax = plt.subplots()
+fig, ax = plt.subplots()
 ax.imshow(image, cmap=plt.cm.gray)
 
 for props in regions:
diff --git a/doc/examples/plot_skeleton.py b/doc/examples/plot_skeleton.py
index 3346490f..a4a3a60c 100644
--- a/doc/examples/plot_skeleton.py
+++ b/doc/examples/plot_skeleton.py
@@ -47,7 +47,7 @@ image[circle2] = 0
 skeleton = skeletonize(image)
 
 # display results
-f, (ax1, ax2) = plt.subplots(1, 2, figsize=(8, 4.5))
+fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(8, 4.5))
 
 ax1.imshow(image, cmap=plt.cm.gray)
 ax1.axis('off')
@@ -57,7 +57,7 @@ ax2.imshow(skeleton, cmap=plt.cm.gray)
 ax2.axis('off')
 ax2.set_title('skeleton', fontsize=20)
 
-f.subplots_adjust(wspace=0.02, hspace=0.02, top=0.98,
+fig.subplots_adjust(wspace=0.02, hspace=0.02, top=0.98,
                     bottom=0.02, left=0.02, right=0.98)
 
 plt.show()
diff --git a/doc/examples/plot_ssim.py b/doc/examples/plot_ssim.py
index 4e657150..319c72fe 100644
--- a/doc/examples/plot_ssim.py
+++ b/doc/examples/plot_ssim.py
@@ -45,7 +45,7 @@ def mse(x, y):
 img_noise = img + noise
 img_const = img + abs(noise)
 
-f, (ax0, ax1, ax2) = plt.subplots(nrows=1, ncols=3, figsize=(8, 4))
+fig, (ax0, ax1, ax2) = plt.subplots(nrows=1, ncols=3, figsize=(8, 4))
 
 mse_none = mse(img, img)
 ssim_none = ssim(img, img, dynamic_range=img.max() - img.min())
diff --git a/doc/examples/plot_swirl.py b/doc/examples/plot_swirl.py
index 98226a20..8f79db94 100644
--- a/doc/examples/plot_swirl.py
+++ b/doc/examples/plot_swirl.py
@@ -74,7 +74,7 @@ from skimage.transform import swirl
 image = data.checkerboard()
 swirled = swirl(image, rotation=0, strength=10, radius=120, order=2)
 
-f, (ax0, ax1) = plt.subplots(1, 2, figsize=(8, 3))
+fig, (ax0, ax1) = plt.subplots(1, 2, figsize=(8, 3))
 
 ax0.imshow(image, cmap=plt.cm.gray, interpolation='none')
 ax0.axis('off')