Use new colourmap in documentation examples.

obspy · Apr 25, 2015 · 8609d1a · 8609d1a
1 parent 6263df6
commit 8609d1a
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Showing 6 changed files with 23 additions and 7 deletions.
diff --git a/misc/docs/source/tutorial/code_snippets/array_response_function.py b/misc/docs/source/tutorial/code_snippets/array_response_function.py
@@ -25,7 +25,7 @@
 # plot
 plt.pcolor(np.arange(kxmin, kxmax + kstep * 1.1, kstep) - kstep / 2.,
            np.arange(kymin, kymax + kstep * 1.1, kstep) - kstep / 2.,
-           transff.T)
+           transff.T, cmap='YlGnBu_r')
 
 plt.colorbar()
 plt.clim(vmin=0., vmax=1.)

diff --git a/misc/docs/source/tutorial/code_snippets/beamforming_fk_analysis_1.py b/misc/docs/source/tutorial/code_snippets/beamforming_fk_analysis_1.py
@@ -90,7 +90,7 @@
 for i, lab in enumerate(labels):
     ax = fig.add_subplot(4, 1, i + 1)
     ax.scatter(out[:, 0], out[:, i + 1], c=out[:, 1], alpha=0.6,
-               edgecolors='none')
+               edgecolors='none', cmap='YlGnBu_r')
     ax.set_ylabel(lab)
     ax.set_xlim(out[0, 0], out[-1, 0])
     ax.set_ylim(out[:, i + 1].min(), out[:, i + 1].max())

diff --git a/misc/docs/source/tutorial/code_snippets/beamforming_fk_analysis_2.py b/misc/docs/source/tutorial/code_snippets/beamforming_fk_analysis_2.py
@@ -86,7 +86,7 @@
 
 # Plot
 
-cmap = cm.hot_r
+cmap = cm.YlGnBu_r
 
 # make output human readable, adjust backazimuth to values between 0 and 360
 t, rel_power, abs_power, baz, slow = out.T
@@ -127,6 +127,7 @@
 
 # set slowness limits
 ax.set_ylim(0, 3)
+[i.set_color('grey') for i in ax.get_yticklabels()]
 ColorbarBase(cax, cmap=cmap,
              norm=Normalize(vmin=hist.min(), vmax=hist.max()))
 

diff --git a/misc/docs/source/tutorial/code_snippets/continuous_wavelet_transform_mlpy.py b/misc/docs/source/tutorial/code_snippets/continuous_wavelet_transform_mlpy.py
@@ -25,7 +25,7 @@
 ax1.plot(t, tr.data, 'k')
 
 img = ax2.imshow(np.abs(spec), extent=[t[0], t[-1], freq[-1], freq[0]],
-                 aspect='auto', interpolation="nearest")
+                 aspect='auto', interpolation='nearest', cmap='YlGnBu_r')
 # Hackish way to overlay a logarithmic scale over a linearly scaled image.
 twin_ax = ax2.twinx()
 twin_ax.set_yscale('log')

diff --git a/misc/docs/source/tutorial/code_snippets/continuous_wavelet_transform_obspy.py b/misc/docs/source/tutorial/code_snippets/continuous_wavelet_transform_obspy.py
@@ -22,7 +22,7 @@
     t,
     np.logspace(np.log10(f_min), np.log10(f_max), scalogram.shape[0]))
 
-ax.pcolormesh(x, y, np.abs(scalogram))
+ax.pcolormesh(x, y, np.abs(scalogram), cmap='YlGnBu_r')
 ax.set_xlabel("Time after %s [s]" % tr.stats.starttime)
 ax.set_ylabel("Frequency [Hz]")
 ax.set_yscale('log')

diff --git a/misc/docs/source/tutorial/code_snippets/hierarchical_clustering.py b/misc/docs/source/tutorial/code_snippets/hierarchical_clustering.py
@@ -13,15 +13,30 @@
         dissimilarity = data['dissimilarity']
 
 plt.subplot(121)
-plt.imshow(1 - dissimilarity, interpolation="nearest")
+plt.imshow(1 - dissimilarity, interpolation='nearest', cmap='YlGnBu_r')
 
 dissimilarity = distance.squareform(dissimilarity)
 threshold = 0.3
 linkage = hierarchy.linkage(dissimilarity, method="single")
 clusters = hierarchy.fcluster(linkage, threshold, criterion="distance")
 
+# A little nicer set of colors.
+cmap = plt.get_cmap('Paired', lut=6)
+colors = ['#%02x%02x%02x' % tuple(col * 255 for col in cmap(i)[:3])
+          for i in range(6)]
+try:
+    hierarchy.set_link_color_palette(colors[1:])
+except AttributeError:
+    # Old version of SciPy
+    pass
+
 plt.subplot(122)
-hierarchy.dendrogram(linkage, color_threshold=0.3)
+try:
+    hierarchy.dendrogram(linkage, color_threshold=0.3,
+                         above_threshold_color=cmap(0))
+except TypeError:
+    # Old version of SciPy
+    hierarchy.dendrogram(linkage, color_threshold=0.3)
 plt.xlabel("Event number")
 plt.ylabel("Dissimilarity")
 plt.show()