doc: Remove jet from more examples.

QuLogic · QuLogic · commit 55043a0c7072 · 2016-02-17T18:26:28.000-05:00
diff --git a/examples/pie_and_polar_charts/polar_bar_demo.py b/examples/pie_and_polar_charts/polar_bar_demo.py
@@ -15,7 +15,7 @@
 
 # Use custom colors and opacity
 for r, bar in zip(radii, bars):
-    bar.set_facecolor(plt.cm.jet(r / 10.))
+    bar.set_facecolor(plt.cm.viridis(r / 10.))
     bar.set_alpha(0.5)
 
 plt.show()
diff --git a/examples/pylab_examples/figimage_demo.py b/examples/pylab_examples/figimage_demo.py
@@ -13,7 +13,7 @@
 Z.shape = 100, 100
 Z[:, 50:] = 1.
 
-im1 = plt.figimage(Z, xo=50, yo=0, cmap=cm.jet, origin='lower')
-im2 = plt.figimage(Z, xo=100, yo=100, alpha=.8, cmap=cm.jet, origin='lower')
+im1 = plt.figimage(Z, xo=50, yo=0, origin='lower')
+im2 = plt.figimage(Z, xo=100, yo=100, alpha=.8, origin='lower')
 
 plt.show()
diff --git a/examples/pylab_examples/hist_colormapped.py b/examples/pylab_examples/hist_colormapped.py
@@ -16,7 +16,7 @@
 norm = colors.Normalize(fracs.min(), fracs.max())
 
 for thisfrac, thispatch in zip(fracs, patches):
-    color = cm.jet(norm(thisfrac))
+    color = cm.viridis(norm(thisfrac))
     thispatch.set_facecolor(color)
 
 
diff --git a/examples/pylab_examples/image_origin.py b/examples/pylab_examples/image_origin.py
@@ -15,11 +15,11 @@
 lim = -2, 11, -2, 6
 plt.subplot(211, facecolor='g')
 plt.title('blue should be up')
-plt.imshow(x, origin='upper', interpolation=interp, cmap='jet')
+plt.imshow(x, origin='upper', interpolation=interp)
 #plt.axis(lim)
 
 plt.subplot(212, facecolor='y')
 plt.title('blue should be down')
-plt.imshow(x, origin='lower', interpolation=interp, cmap='jet')
+plt.imshow(x, origin='lower', interpolation=interp)
 #plt.axis(lim)
 plt.show()
diff --git a/examples/pylab_examples/layer_images.py b/examples/pylab_examples/layer_images.py
@@ -36,7 +36,7 @@ def func3(x, y):
 
 Z2 = func3(X, Y)
 
-im2 = plt.imshow(Z2, cmap=plt.cm.jet, alpha=.9, interpolation='bilinear',
+im2 = plt.imshow(Z2, cmap=plt.cm.viridis, alpha=.9, interpolation='bilinear',
                  extent=extent)
 
 plt.show()
diff --git a/examples/pylab_examples/leftventricle_bulleye.py b/examples/pylab_examples/leftventricle_bulleye.py
@@ -46,7 +46,7 @@ def bullseye_plot(ax, data, segBold=None, cmap=None, norm=None):
     data = np.array(data).ravel()
 
     if cmap is None:
-        cmap = plt.cm.jet
+        cmap = plt.cm.viridis
 
     if norm is None:
         norm = mpl.colors.Normalize(vmin=data.min(), vmax=data.max())
@@ -142,7 +142,7 @@ def bullseye_plot(ax, data, segBold=None, cmap=None, norm=None):
 
 # Set the colormap and norm to correspond to the data for which
 # the colorbar will be used.
-cmap = mpl.cm.jet
+cmap = mpl.cm.viridis
 norm = mpl.colors.Normalize(vmin=1, vmax=17)
 
 # ColorbarBase derives from ScalarMappable and puts a colorbar
diff --git a/examples/pylab_examples/quadmesh_demo.py b/examples/pylab_examples/quadmesh_demo.py
@@ -32,9 +32,9 @@
 
 ax = fig.add_subplot(122)
 #  You can control the color of the masked region:
-#cmap = cm.jet
-#cmap.set_bad('r', 1.0)
-#ax.pcolormesh(Qx,Qz,Zm, cmap=cmap)
+# cmap = cm.RdBu
+# cmap.set_bad('y', 1.0)
+# ax.pcolormesh(Qx, Qz, Zm, cmap=cmap)
 #  Or use the default, which is transparent:
 col = ax.pcolormesh(Qx, Qz, Zm, shading='gouraud')
 ax.set_title('With masked values')
diff --git a/examples/specialty_plots/advanced_hillshading.py b/examples/specialty_plots/advanced_hillshading.py
@@ -56,7 +56,7 @@ def shade_other_data():
     z2 = np.cos(x**2 + y**2)  # Data to color
 
     norm = Normalize(z2.min(), z2.max())
-    cmap = plt.cm.jet
+    cmap = plt.cm.RdBu
 
     ls = LightSource(315, 45)
     rgb = ls.shade_rgb(cmap(norm(z2)), z1)
diff --git a/examples/user_interfaces/embedding_in_wx3.py b/examples/user_interfaces/embedding_in_wx3.py
@@ -74,7 +74,7 @@ def init_plot_data(self):
         y = np.arange(100.0) * 2 * np.pi / 50.0
         self.x, self.y = np.meshgrid(x, y)
         z = np.sin(self.x) + np.cos(self.y)
-        self.im = a.imshow(z, cmap=cm.jet)  # , interpolation='nearest')
+        self.im = a.imshow(z, cmap=cm.RdBu)  # , interpolation='nearest')
 
         zmax = np.amax(z) - ERR_TOL
         ymax_i, xmax_i = np.nonzero(z >= zmax)
