From 8609d1a34ab869a1680424307ed4030f3dcba48f Mon Sep 17 00:00:00 2001 From: Elliott Sales de Andrade Date: Mon, 24 Nov 2014 19:42:47 -0500 Subject: [PATCH] Use new colourmap in documentation examples. --- .../code_snippets/array_response_function.py | 2 +- .../beamforming_fk_analysis_1.py | 2 +- .../beamforming_fk_analysis_2.py | 3 ++- .../continuous_wavelet_transform_mlpy.py | 2 +- .../continuous_wavelet_transform_obspy.py | 2 +- .../code_snippets/hierarchical_clustering.py | 19 +++++++++++++++++-- 6 files changed, 23 insertions(+), 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 index b87012fd043..b3570ba180e 100644 --- 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 index 2712e2296fe..1af1f6b733a 100644 --- 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 index 842f965dfe3..8e19473a946 100644 --- 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 index 5b01f970f8a..a1c7b9cf53e 100644 --- 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 index 62fbd5623c6..89d37acb4b2 100644 --- 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 index d4faec75bc9..ab29e2ec991 100644 --- 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()