Update maplotlib to matlotlib

Author: cgilon

README.html

@@ -749,7 +749,7 @@ <h2>Regular Plots</h2>
 care of filled areas:</p>
 <pre class="literal-block">
 import numpy as np
-import maplotlib.pyplot as plt
+import matplotlib.pyplot as plt
 
 n = 256
 X = np.linspace(-np.pi,np.pi,n,endpoint=True)
@@ -772,7 +772,7 @@ <h2>Scatter Plots</h2>
 care of marker size, color and transparency.</p>
 <pre class="literal-block">
 import numpy as np
-import maplotlib.pyplot as plt
+import matplotlib.pyplot as plt
 
 n = 1024
 X = np.random.normal(0,1,n)
@@ -794,7 +794,7 @@ <h2>Bar Plots</h2>
 adding labels for red bars.</p>
 <pre class="literal-block">
 import numpy as np
-import maplotlib.pyplot as plt
+import matplotlib.pyplot as plt
 
 n = 12
 X = np.arange(n)
@@ -824,7 +824,7 @@ <h2>Contour Plots</h2>
 care of the colormap (see <a class="reference internal" href="#colormaps">Colormaps</a> below).</p>
 <pre class="literal-block">
 import numpy as np
-import maplotlib.pyplot as plt
+import matplotlib.pyplot as plt
 
 def f(x,y): return (1-x/2+x**5+y**3)*np.exp(-x**2-y**2)
 
@@ -851,7 +851,7 @@ <h2>Imshow</h2>
 care of colormap, image interpolation and origin.</p>
 <pre class="literal-block">
 import numpy as np
-import maplotlib.pyplot as plt
+import matplotlib.pyplot as plt
 
 def f(x,y): return (1-x/2+x**5+y**3)*np.exp(-x**2-y**2)
 
@@ -875,7 +875,7 @@ <h2>Pie Charts</h2>
 care of colors and slices size.</p>
 <pre class="literal-block">
 import numpy as np
-import maplotlib.pyplot as plt
+import matplotlib.pyplot as plt
 
 n = 20
 Z = np.random.uniform(0,1,n)
@@ -895,7 +895,7 @@ <h2>Quiver Plots</h2>
 care of colors and orientations.</p>
 <pre class="literal-block">
 import numpy as np
-import maplotlib.pyplot as plt
+import matplotlib.pyplot as plt
 
 n = 8
 X,Y = np.mgrid[0:n,0:n]
@@ -911,7 +911,7 @@ <h2>Grids</h2>
 care of line styles.</p>
 <pre class="literal-block">
 import numpy as np
-import maplotlib.pyplot as plt
+import matplotlib.pyplot as plt
 
 axes = gca()
 axes.set_xlim(0,4)
@@ -933,7 +933,7 @@ <h2>Multi Plots</h2>
 <p>Starting from the code below, try to reproduce the graphic on the right.</p>
 <pre class="literal-block">
 import numpy as np
-import maplotlib.pyplot as plt
+import matplotlib.pyplot as plt
 
 plt.subplot(2,2,1)
 plt.subplot(2,2,3)
@@ -953,7 +953,7 @@ <h2>Polar Axis</h2>
 <p>Starting from the code below, try to reproduce the graphic on the right.</p>
 <pre class="literal-block">
 import numpy as np
-import maplotlib.pyplot as plt
+import matplotlib.pyplot as plt
 
 plt.axes([0,0,1,1])
 
@@ -981,7 +981,7 @@ <h2>3D Plots</h2>
 <p>Starting from the code below, try to reproduce the graphic on the right.</p>
 <pre class="literal-block">
 import numpy as np
-import maplotlib.pyplot as plt
+import matplotlib.pyplot as plt
 from mpl_toolkits.mplot3d import Axes3D
 
 fig = plt.figure()

README.rst

@@ -841,7 +841,7 @@ Starting from the code below, try to reproduce the graphic on the right taking
 care of filled areas::
 
    import numpy as np
-   import maplotlib.pyplot as plt
+   import matplotlib.pyplot as plt
 
    n = 256
    X = np.linspace(-np.pi,np.pi,n,endpoint=True)
@@ -873,7 +873,7 @@ care of marker size, color and transparency.
 ::
 
    import numpy as np
-   import maplotlib.pyplot as plt
+   import matplotlib.pyplot as plt
 
    n = 1024
    X = np.random.normal(0,1,n)
@@ -905,7 +905,7 @@ adding labels for red bars.
 ::
 
    import numpy as np
-   import maplotlib.pyplot as plt
+   import matplotlib.pyplot as plt
 
    n = 12
    X = np.arange(n)
@@ -943,7 +943,7 @@ care of the colormap (see `Colormaps`_ below).
 ::
 
    import numpy as np
-   import maplotlib.pyplot as plt
+   import matplotlib.pyplot as plt
 
    def f(x,y): return (1-x/2+x**5+y**3)*np.exp(-x**2-y**2)
 
@@ -980,7 +980,7 @@ care of colormap, image interpolation and origin.
 ::
 
    import numpy as np
-   import maplotlib.pyplot as plt
+   import matplotlib.pyplot as plt
 
    def f(x,y): return (1-x/2+x**5+y**3)*np.exp(-x**2-y**2)
 
@@ -1011,7 +1011,7 @@ care of colors and slices size.
 ::
 
    import numpy as np
-   import maplotlib.pyplot as plt
+   import matplotlib.pyplot as plt
 
    n = 20
    Z = np.random.uniform(0,1,n)
@@ -1039,7 +1039,7 @@ care of colors and orientations.
 ::
 
    import numpy as np
-   import maplotlib.pyplot as plt
+   import matplotlib.pyplot as plt
 
    n = 8
    X,Y = np.mgrid[0:n,0:n]
@@ -1064,7 +1064,7 @@ care of line styles.
 ::
 
    import numpy as np
-   import maplotlib.pyplot as plt
+   import matplotlib.pyplot as plt
 
    axes = gca()
    axes.set_xlim(0,4)
@@ -1094,7 +1094,7 @@ Starting from the code below, try to reproduce the graphic on the right.
 ::
 
    import numpy as np
-   import maplotlib.pyplot as plt
+   import matplotlib.pyplot as plt
 
    plt.subplot(2,2,1)
    plt.subplot(2,2,3)
@@ -1122,7 +1122,7 @@ Starting from the code below, try to reproduce the graphic on the right.
 ::
 
    import numpy as np
-   import maplotlib.pyplot as plt
+   import matplotlib.pyplot as plt
 
    plt.axes([0,0,1,1])
 
@@ -1159,7 +1159,7 @@ Starting from the code below, try to reproduce the graphic on the right.
 ::
 
    import numpy as np
-   import maplotlib.pyplot as plt
+   import matplotlib.pyplot as plt
    from mpl_toolkits.mplot3d import Axes3D
 
    fig = plt.figure()