@@ -40,7 +40,8 @@ examples, if you use the -pylab method, you can skip the "mpimg." and
4040Importing image data into Numpy arrays
4141===============================================
4242
43- Plotting image data is supported by the Python Image Library (`PIL <http://www.pythonware.com/products/pil/ >`_), . Natively, matplotlib
43+ Plotting image data is supported by the Python Image Library (`PIL
44+ <http://www.pythonware.com/products/pil/> `_). Natively, matplotlib
4445only supports PNG images. The commands shown below fall back on PIL
4546if the native read fails.
4647
@@ -121,7 +122,8 @@ reading/writing for any format other than PNG is limited to uint8
121122data. Why 8 bits? Most displays can only render 8 bits per channel
122123worth of color gradation. Why can they only render 8 bits/channel?
123124Because that's about all the human eye can see. More here (from a
124- photography standpoint): `Luminous Landscape bit depth tutorial <http://www.luminous-landscape.com/tutorials/bit-depth.shtml >`_.
125+ photography standpoint): `Luminous Landscape bit depth tutorial
126+ <http://www.luminous-landscape.com/tutorials/bit-depth.shtml> `_.
125127
126128Each inner list represents a pixel. Here, with an RGB image, there
127129are 3 values. Since it's a black and white image, R, G, and B are all
@@ -170,14 +172,15 @@ typically quite poor.
170172
171173Pseudocolor is only relevant to single-channel, grayscale, luminosity
172174images. We currently have an RGB image. Since R, G, and B are all
173- similar (see for yourself above or in your data), we can just pick on
175+ similar (see for yourself above or in your data), we can just pick one
174176channel of our data:
175177
176178.. sourcecode :: ipython
177179
178180 In [6]: lum_img = img[:,:,0]
179181
180- This is array slicing. You can read more in the `Numpy tutorial <http://www.scipy.org/Tentative_NumPy_Tutorial >`_.
182+ This is array slicing. You can read more in the `Numpy tutorial
183+ <http://www.scipy.org/Tentative_NumPy_Tutorial> `_.
181184
182185.. sourcecode :: ipython
183186
@@ -226,8 +229,10 @@ object:
226229 imgplot = plt.imshow(lum_img)
227230 imgplot.set_cmap('spectral')
228231
229- There are many other colormap schemes available. See the `list and
230- images of the colormaps
232+ There are many other colormap schemes available. See the `list of
233+ colormaps
234+ <http://matplotlib.org/api/pyplot_summary.html#matplotlib.pyplot.colormaps> `_
235+ and `images of the colormaps
231236<http://matplotlib.org/examples/pylab_examples/show_colormaps.html> `_.
232237
233238.. _`Color Bars` :
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