[all data analysis] plots work for old and new matplotlib
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@@ -38,7 +38,7 @@ ax.annotate('sampling\ndistribution',
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connectionstyle="angle3,angleA=20,angleB=120") )
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ax.annotate('bootstrap\ndistribution',
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xy=(0.13, 3.3), xycoords='data',
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xytext=(0.25, 4), textcoords='data',
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xytext=(0.22, 4), textcoords='data',
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arrowprops=dict(arrowstyle="->", relpos=(0.0,0.5),
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connectionstyle="angle3,angleA=20,angleB=60") )
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ax.bar(bins[:-1]-0.25*db, hmusrs, 0.5*db, **fsB)
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@@ -44,19 +44,19 @@ ax.annotate('Measured\ncorrelation\nis significant!',
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connectionstyle="angle3,angleA=10,angleB=80") )
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ax.annotate('95% percentile',
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xy=(0.14, 0.9), xycoords='data',
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xytext=(0.2, 4.0), textcoords='data', ha='left',
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xytext=(0.18, 4.0), textcoords='data', ha='left',
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arrowprops=dict(arrowstyle="->", relpos=(0.1,0.0),
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connectionstyle="angle3,angleA=30,angleB=70") )
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connectionstyle="angle3,angleA=30,angleB=80") )
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ax.annotate('Distribution of\nuncorrelated\nsamples',
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xy=(-0.08, 3.6), xycoords='data',
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xytext=(-0.22, 5.0), textcoords='data', ha='left',
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arrowprops=dict(arrowstyle="->", relpos=(0.5,0.0),
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connectionstyle="angle3,angleA=150,angleB=100") )
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connectionstyle="angle3,angleA=150,angleB=110") )
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ax.bar(b[:-1], h, width=b[1]-b[0], **fsC)
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ax.bar(b[:-1][b[:-1]>=rq], h[b[:-1]>=rq], width=b[1]-b[0], **fsB)
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ax.plot( [rd, rd], [0, 1], **lsA)
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ax.set_xlim(-0.25, 0.35)
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ax.set_xlabel('Correlation coefficient')
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ax.set_ylabel('Probability density of H0')
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ax.set_ylabel('Prob. density of H0')
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plt.savefig('permutecorrelation.pdf')
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