@@ -1988,6 +1988,7 @@ both. -->
19881988.. plot::
19891989 :context: reset
19901990 :include- source: True
1991+ :output- base- name: plot- {counter}
19911992
19921993 >> > import matplotlib.pyplot as plt
19931994 >> > x = np.linspace(- 10 , 10 , 10000 ) # 10000 evenly spaced points between -10 and 10
@@ -2003,6 +2004,7 @@ this is to select them using a mask:
20032004.. plot::
20042005 :context: close- figs
20052006 :include- source: True
2007+ :output- base- name: plot- {counter}
20062008
20072009 >> > plt.scatter(x[y > 0 ], y[y > 0 ], marker = ' ,' , s = 1 )
20082010 < matplotlib.collections.PathCollection object at ... >
@@ -2193,6 +2195,7 @@ For example, say we have an image, represented in
21932195.. plot::
21942196 :context: reset
21952197 :include- source: True
2198+ :output- base- name: astronaut- {counter}
21962199
21972200 >> > def imshow(image, title):
21982201 ... import matplotlib.pyplot as plt
@@ -2214,6 +2217,7 @@ value (the second value in the last dimension, which should always be between
22142217.. plot::
22152218 :context: close- figs
22162219 :include- source: True
2220+ :output- base- name: astronaut- {counter}
22172221
22182222 >> > from skimage import color
22192223 >> > hsv_image = color.rgb2hsv(image)
@@ -2231,6 +2235,7 @@ saturation of only those pixels:
22312235.. plot::
22322236 :context: close- figs
22332237 :include- source: True
2238+ :output- base- name: astronaut- {counter}
22342239
22352240 >> > hsv_image = color.rgb2hsv(image)
22362241 >> > # Mask only those pixels whose saturation is > 0.6
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