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| def compare_violin(x, y, bins, **kwargs): | |
| import numpy as np | |
| import seaborn as sns | |
| import matplotlib.pyplot as plt | |
| nmax = int(kwargs.pop('nmax', 1e4)) | |
| nmin = int(kwargs.pop('nmax', 1)) | |
| kwargs.setdefault('showmedians', True) | |
| bins_mid = (bins[:-1] + bins[1:]) * 0.5 | |
| ix = (np.isfinite(x) & np.isfinite(y)).nonzero() | |
| x, y = x[ix], y[ix] | |
| idx = bins.searchsorted(x) - 1 | |
| dat, pos = [], [] | |
| for i in range(len(bins) - 1): | |
| a, b = y[idx == i], bins_mid[i] | |
| if a.size > nmax: | |
| a = np.random.choice(a, int(nmax), replace=False) | |
| if a.size >= nmin: | |
| dat.append(a) | |
| pos.append(b) | |
| plt.violinplot(dataset=dat, positions=pos, **kwargs) | |
| def compare_violin2(x, y, bins=10, **kwargs): | |
| import numpy as np | |
| import seaborn as sns | |
| ix = np.isfinite(x) & np.isfinite(y) | |
| x, y = x[ix], y[ix] | |
| if np.isscalar(bins): | |
| nbin = bins | |
| xmax, xmin = x.max(), x.min() | |
| else: | |
| xmin, xmax, nbin = bins | |
| step = (xmax - xmin) / nbin | |
| x = ((x - xmin) // step + 0.5) * step + xmin | |
| sns.violinplot(x=x, y=y, **kwargs) |
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