Merge pull request #216 from datacarpentry/redundant-code

Remove redundant code

Author: uschille

_episodes/04-drawing.md

@@ -70,7 +70,6 @@ image = skimage.io.imread(fname="data/maize-seedlings.tif")
 
 fig, ax = plt.subplots()
 plt.imshow(image)
-plt.show()
 ~~~
 {: .language-python}
 
@@ -118,7 +117,6 @@ mask[rr, cc] = False
 # Display mask image
 fig, ax = plt.subplots()
 plt.imshow(mask, cmap="gray")
-plt.show()
 ~~~
 {: .language-python}
 
@@ -219,7 +217,6 @@ The function returns the rectangle as row (`rr`) and column (`cc`) coordinate ar
 > > # Display the image
 > > fig, ax = plt.subplots()
 > > plt.imshow(image)
-> > plt.show()
 > > ~~~
 > > {: .language-python}
 > >
@@ -250,7 +247,6 @@ The function returns the rectangle as row (`rr`) and column (`cc`) coordinate ar
 > > # display the results
 > > fig, ax = plt.subplots()
 > > plt.imshow(image)
-> > plt.show()
 > > ~~~
 > > {: .language-python}
 > >
@@ -300,7 +296,6 @@ The function returns the rectangle as row (`rr`) and column (`cc`) coordinate ar
 > > # display the results
 > > fig, ax = plt.subplots()
 > > plt.imshow(image)
-> > plt.show()
 > > ~~~
 > > {: .language-python}
 > {: .solution}
@@ -362,7 +357,6 @@ Then, we display the masked image.
 ~~~
 fig, ax = plt.subplots()
 plt.imshow(image)
-plt.show()
 ~~~
 {: .language-python}
 
@@ -408,7 +402,6 @@ The resulting masked image should look like this:
 > > # Display the result
 > > fig, ax = plt.subplots()
 > > plt.imshow(image)
-> > plt.show()
 > > ~~~
 > > {: .language-python}
 > {: .solution}
@@ -425,7 +418,6 @@ The resulting masked image should look like this:
 > # Display the image
 > fig, ax = plt.subplots()
 > plt.imshow(image)
-> plt.show()
 > ~~~
 > {: .language-python}
 >
@@ -472,7 +464,6 @@ The resulting masked image should look like this:
 > > # display the result
 > > fig, ax = plt.subplots()
 > > plt.imshow(image)
-> > plt.show()
 > > ~~~
 > > {: .language-python}
 > >
@@ -541,7 +532,6 @@ The resulting masked image should look like this:
 > > # display the result
 > > fig, ax = plt.subplots()
 > > plt.imshow(image)
-> > plt.show()
 > > ~~~
 > > {: .language-python}
 > {: .solution}

_episodes/05-creating-histograms.md

@@ -57,7 +57,6 @@ image = skimage.io.imread(fname="data/plant-seedling.jpg", as_gray=True)
 # display the image
 fig, ax = plt.subplots()
 plt.imshow(image, cmap="gray")
-plt.show()
 ~~~
 {: .language-python}
 
@@ -123,7 +122,6 @@ plt.ylabel("pixel count")
 plt.xlim([0.0, 1.0])  # <- named arguments do not work here
 
 plt.plot(bin_edges[0:-1], histogram)  # <- or here
-plt.show()
 ~~~
 {: .language-python}
 
@@ -151,7 +149,6 @@ Finally, we create the histogram plot itself with
 We use the **left** bin edges as x-positions for the histogram values by
 indexing the `bin_edges` array to ignore the last value
 (the **right** edge of the last bin).
-Then we make it appear with `plt.show()`.
 When we run the program on this image of a plant seedling,
 it produces this histogram:
 
@@ -202,7 +199,6 @@ it produces this histogram:
 > > # display the image
 > > fig, ax = plt.subplots()
 > > plt.imshow(image, cmap="gray")
-> > plt.show()
 > >
 > > # create mask here, using np.zeros() and skimage.draw.rectangle()
 > > mask = np.zeros(shape=image.shape, dtype="bool")
@@ -212,7 +208,6 @@ it produces this histogram:
 > > # display the mask
 > > fig, ax = plt.subplots()
 > > plt.imshow(mask, cmap="gray")
-> > plt.show()
 > >
 > > # mask the image and create the new histogram
 > > histogram, bin_edges = np.histogram(image[mask], bins=256, range=(0.0, 1.0))
@@ -226,7 +221,6 @@ it produces this histogram:
 > > plt.xlim([0.0, 1.0])
 > > plt.plot(bin_edges[0:-1], histogram)
 > >
-> > plt.show()
 > > ~~~
 > > {: .language-python}
 > >
@@ -252,7 +246,6 @@ image = skimage.io.imread(fname="data/plant-seedling.jpg")
 # display the image
 fig, ax = plt.subplots()
 plt.imshow(image)
-plt.show()
 ~~~
 {: .language-python}
 
@@ -282,8 +275,6 @@ for channel_id, c in zip(channel_ids, colors):
 plt.title("Color Histogram")
 plt.xlabel("Color value")
 plt.ylabel("Pixel count")
-
-plt.show()
 ~~~
 {: .language-python}
 
@@ -381,7 +372,6 @@ Finally we label our axes and display the histogram, shown here:
 > # display the image
 > fig, ax = plt.subplots()
 > plt.imshow(image)
-> plt.show()
 > ~~~
 > {: .language-python}
 > ![Well plate image](../fig/wellplate-02.jpg)
@@ -422,7 +412,6 @@ Finally we label our axes and display the histogram, shown here:
 > > # validity of your mask
 > > fig, ax = plt.subplots()
 > > plt.imshow(masked_img)
-> > plt.show()
 > >
 > > # list to select colors of each channel line
 > > colors = ("red", "green", "blue")
@@ -444,7 +433,6 @@ Finally we label our axes and display the histogram, shown here:
 > > plt.xlabel("color value")
 > > plt.ylabel("pixel count")
 > >
-> > plt.show()
 > > ~~~
 > > {: .language-python}
 > {: .solution}

_episodes/06-blurring.md

@@ -241,7 +241,6 @@ image = skimage.io.imread(fname="data/gaussian-original.png")
 # display the image
 fig, ax = plt.subplots()
 plt.imshow(image)
-plt.show()
 ~~~
 {: .language-python}
 ![Original image](../data/gaussian-original.png)
@@ -279,7 +278,6 @@ Finally, we display the blurred image:
 # display blurred image
 fig, ax = plt.subplots()
 plt.imshow(blurred)
-plt.show()
 ~~~
 {: .language-python}
 ![Original image](../fig/gaussian-blurred.png)
@@ -325,7 +323,6 @@ plt.show()
 > > # display blurred image
 > > fig, ax = plt.subplots()
 > > plt.imshow(blurred)
-> > plt.show()
 > > ~~~
 > > {: .language-python}
 > >

_episodes/07-thresholding.md

@@ -65,7 +65,6 @@ image = skimage.io.imread("data/shapes-01.jpg")
 
 fig, ax = plt.subplots()
 plt.imshow(image)
-plt.show()
 ~~~
 {: .language-python}
 
@@ -95,7 +94,6 @@ blurred_image = skimage.filters.gaussian(gray_image, sigma=1.0)
 
 fig, ax = plt.subplots()
 plt.imshow(blurred_image, cmap="gray")
-plt.show()
 ~~~
 {: .language-python}
 
@@ -128,7 +126,6 @@ plt.title("Grayscale Histogram")
 plt.xlabel("grayscale value")
 plt.ylabel("pixels")
 plt.xlim(0, 1.0)
-plt.show()
 ~~~
 {: .language-python}
 
@@ -163,7 +160,6 @@ binary_mask = blurred_image < t
 
 fig, ax = plt.subplots()
 plt.imshow(binary_mask, cmap="gray")
-plt.show()
 ~~~
 {: .language-python}
 
@@ -208,7 +204,6 @@ selection[~binary_mask] = 0
 
 fig, ax = plt.subplots()
 plt.imshow(selection)
-plt.show()
 ~~~
 {: .language-python}
 
@@ -240,7 +235,6 @@ plt.show()
 > > plt.xlabel("gray value")
 > > plt.ylabel("pixel count")
 > > plt.xlim(0, 1.0)
-> > plt.show()
 > > ~~~
 > > {: .language-python}
 > >
@@ -269,7 +263,6 @@ plt.show()
 > >
 > > fig, ax = plt.subplots()
 > > plt.imshow(binary_mask, cmap="gray")
-> > plt.show()
 > > ~~~
 > > {: .language-python}
 > >
@@ -283,7 +276,6 @@ plt.show()
 > >
 > > fig, ax = plt.subplots()
 > > plt.imshow(selection)
-> > plt.show()
 > > ~~~
 > > {: .language-python}
 > >
@@ -318,7 +310,6 @@ image = skimage.io.imread(fname="data/maize-root-cluster.jpg")
 
 fig, ax = plt.subplots()
 plt.imshow(image)
-plt.show()
 ~~~
 {: .language-python}
 
@@ -342,7 +333,6 @@ plt.title("Graylevel histogram")
 plt.xlabel("gray value")
 plt.ylabel("pixel count")
 plt.xlim(0, 1.0)
-plt.show()
 ~~~
 {: .language-python}
 
@@ -386,7 +376,6 @@ binary_mask = blurred_image > t
 
 fig, ax = plt.subplots()
 plt.imshow(binary_mask, cmap="gray")
-plt.show()
 ~~~
 {: .language-python}
 
@@ -401,7 +390,6 @@ selection[~binary_mask] = 0
 
 fig, ax = plt.subplots()
 plt.imshow(selection)
-plt.show()
 ~~~
 {: .language-python}
 
@@ -703,7 +691,6 @@ data/trial-293.jpg,0.13607895611702128
 > > plt.xlabel("gray value")
 > > plt.ylabel("pixel count")
 > > plt.xlim(0, 1.0)
-> > plt.show()
 > > ~~~
 > > {: .language-python}
 > >
@@ -724,7 +711,6 @@ data/trial-293.jpg,0.13607895611702128
 > >
 > > fig, ax = plt.subplots()
 > > plt.imshow(binary_mask, cmap="gray")
-> > plt.show()
 > > ~~~
 > > {: .language-python}
 > >

_episodes/08-connected-components.md

@@ -297,8 +297,7 @@ labeled_image, count = connected_components(filename="data/shapes-01.jpg", sigma
 
 fig, ax = plt.subplots()
 plt.imshow(labeled_image)
-plt.axis("off")
-plt.show()
+plt.axis("off");
 ~~~
 {: .language-python}
 
@@ -361,8 +360,7 @@ colored_label_image = skimage.color.label2rgb(labeled_image, bg_label=0)
 
 fig, ax = plt.subplots()
 plt.imshow(colored_label_image)
-plt.axis("off")
-plt.show()
+plt.axis("off");
 ~~~
 {: .language-python}
 
@@ -503,8 +501,7 @@ This will produce the output
 > > fig, ax = plt.subplots()
 > > plt.hist(object_areas)
 > > plt.xlabel("Area (pixels)")
-> > plt.ylabel("Number of objects")
-> > plt.show()
+> > plt.ylabel("Number of objects");
 > > ~~~
 > > {: .language-python}
 > >
@@ -694,8 +691,7 @@ This will produce the output
 > >
 > > fig, ax = plt.subplots()
 > > plt.imshow(colored_label_image)
-> > plt.axis("off")
-> > plt.show()
+> > plt.axis("off");
 > >
 > > print("Found", count, "objects in the image.")
 > > ~~~
@@ -740,8 +736,7 @@ This will produce the output
 > > im = plt.imshow(colored_area_image)
 > > cbar = fig.colorbar(im, ax=ax, shrink=0.85)
 > > cbar.ax.set_title("Area")
-> > plt.axis("off")
-> > plt.show()
+> > plt.axis("off");
 > > ~~~
 > > {: .language-python}
 > >

_episodes/09-challenges.md

@@ -68,7 +68,6 @@ and `data/colonies-03.tif`.
 > > # display the image
 > > fig, ax = plt.subplots()
 > > plt.imshow(bacteria_image)
-> > plt.show()
 > > ~~~
 > > {: .language-python}
 > >
@@ -84,7 +83,6 @@ and `data/colonies-03.tif`.
 > > # display the gray image
 > > fig, ax = plt.subplots()
 > > plt.imshow(gray_bacteria, cmap="gray")
-> > plt.show()
 > > ~~~
 > > {: .language-python}
 > >
@@ -101,7 +99,6 @@ and `data/colonies-03.tif`.
 > > plt.xlabel("gray value")
 > > plt.ylabel("pixel count")
 > > plt.xlim(0, 1.0)
-> > plt.show()
 > > ~~~
 > > {: .language-python}
 > >
@@ -117,7 +114,6 @@ and `data/colonies-03.tif`.
 > > mask = blurred_image < 0.2
 > > fig, ax = plt.subplots()
 > > plt.imshow(mask, cmap="gray")
-> > plt.show()
 > > ~~~
 > > {: .language-python}
 > >
@@ -146,7 +142,6 @@ and `data/colonies-03.tif`.
 > > # plot overlay
 > > fig, ax = plt.subplots()
 > > plt.imshow(summary_image)
-> > plt.show()
 > > ~~~
 > > {: .language-python}
 > >