matplotlib · tacaswell · Dec 3, 2016 · Dec 1, 2016 · Dec 1, 2016 · Dec 1, 2016
diff --git a/doc/_static/contour_frontpage.png b/doc/_static/contour_frontpage.png
diff --git a/doc/_static/histogram_frontpage.png b/doc/_static/histogram_frontpage.png
diff --git a/doc/_static/membrane_frontpage.png b/doc/_static/membrane_frontpage.png
diff --git a/doc/_static/surface3d_frontpage.png b/doc/_static/surface3d_frontpage.png
diff --git a/examples/frontpage/plot_3D.py b/examples/frontpage/plot_3D.py
@@ -0,0 +1,38 @@
+"""
+====================
+Frontpage 3D example
+====================
+
+This example reproduces the frontpage 3D example.
+
+"""
+from mpl_toolkits.mplot3d import Axes3D
+from matplotlib import cbook
+from matplotlib import cm
+from matplotlib.colors import LightSource
+import matplotlib.pyplot as plt
+import numpy as np
+
+filename = cbook.get_sample_data('jacksboro_fault_dem.npz', asfileobj=False)
+with np.load(filename) as dem:
+    z = dem['elevation']
+    nrows, ncols = z.shape
+    x = np.linspace(dem['xmin'], dem['xmax'], ncols)
+    y = np.linspace(dem['ymin'], dem['ymax'], nrows)
+    x, y = np.meshgrid(x, y)
+
+region = np.s_[5:50, 5:50]
+x, y, z = x[region], y[region], z[region]
+
+fig, ax = plt.subplots(subplot_kw=dict(projection='3d'), figsize=(1.62, 1.38))
+
+ls = LightSource(270, 45)
+# To use a custom hillshading mode, override the built-in shading and pass
+# in the rgb colors of the shaded surface calculated from "shade".
+rgb = ls.shade(z, cmap=cm.gist_earth, vert_exag=0.1, blend_mode='soft')
+surf = ax.plot_surface(x, y, z, rstride=1, cstride=1, facecolors=rgb,
+                       linewidth=0, antialiased=False, shade=False)
+ax.set_xticks([])
+ax.set_yticks([])
+ax.set_zticks([])
+fig.savefig("surface3d_frontpage.png")
diff --git a/examples/frontpage/plot_contour.py b/examples/frontpage/plot_contour.py
@@ -0,0 +1,34 @@
+"""
+=========================
+Frontpage contour example
+=========================
+
+This example reproduces the frontpage contour example.
+"""
+
+import matplotlib.pyplot as plt
+import numpy as np
+from matplotlib import mlab, cm
+
+extent = (-3, 3, -3, 3)
+
+delta = 0.5
+x = np.arange(-3.0, 4.001, delta)
+y = np.arange(-4.0, 3.001, delta)
+X, Y = np.meshgrid(x, y)
+Z1 = mlab.bivariate_normal(X, Y, 1.0, 1.0, 0.0, -0.5)
+Z2 = mlab.bivariate_normal(X, Y, 1.5, 0.5, 1, 1)
+Z = (Z1 - Z2) * 10
+
+levels = np.linspace(-2.0, 1.601, 40)
+norm = cm.colors.Normalize(vmax=abs(Z).max(), vmin=-abs(Z).max())
+
+fig, ax = plt.subplots(figsize=(1.62, 1.38))
+cset1 = ax.contourf(
+    X, Y, Z, levels,
+    norm=norm)
+ax.set_xlim(-3, 3)
+ax.set_ylim(-3, 3)
+ax.set_xticks([])
+ax.set_yticks([])
+fig.savefig("contour_frontpage.png")
diff --git a/examples/frontpage/plot_histogram.py b/examples/frontpage/plot_histogram.py
@@ -0,0 +1,22 @@
+"""
+===========================
+Frontpage histogram example
+===========================
+
+This example reproduces the frontpage histogram example.
+"""
+
+import matplotlib.pyplot as plt
+import numpy as np
+
+
+random_state = np.random.RandomState(19680801)
+X = random_state.randn(10000)
+
+fig, ax = plt.subplots(figsize=(1.62, 1.38))
+ax.hist(X, bins=25, normed=True)
+x = np.linspace(-5, 5, 1000)
+ax.plot(x, 1 / np.sqrt(2*np.pi) * np.exp(-(x**2)/2), linewidth=4)
+ax.set_xticks([])
+ax.set_yticks([])
+fig.savefig("histogram_frontpage.png")
diff --git a/examples/frontpage/plot_membrane.py b/examples/frontpage/plot_membrane.py
@@ -0,0 +1,25 @@
+"""
+======================
+Frontpage plot example
+======================
+
+
+This example reproduces the frontpage simple plot example.
+"""
+
+import matplotlib.pyplot as plt
+import matplotlib.cbook as cbook
+import numpy as np
+
+
+datafile = cbook.get_sample_data('membrane.dat', asfileobj=False)
+x = np.fromfile(datafile, np.float32)
+# 0.0005 is the sample interval
+
+fig, ax = plt.subplots(figsize=(1.62, 1.38))
+ax.plot(x, linewidth=4)
+ax.set_xlim(5000, 6000)
+ax.set_ylim(-0.6, 0.1)
+ax.set_xticks([])
+ax.set_yticks([])
+fig.savefig("membrane_frontpage.png")