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| 9.991572616396514617e-01 | |
| """ | |
| import numpy as np | |
| import matplotlib.pyplot as plt | |
| import matplotlib.ticker | |
| import matplotlib.patches as patches | |
| def plot_overlaps_histogram( | |
| overlaps: np.ndarray, overlap_threshold=0.99, nbins=50, | |
| min_overlap=0.7, max_overlap=0.999, reverse=True | |
| ): | |
| one_minus_overlaps = 1 - overlaps | |
| bins = np.geomspace(1 - max_overlap, 1 - min_overlap, nbins) | |
| # histogram with 'collection' bins for overlaps outside the range of the bins | |
| counts, _ = np.histogram(np.clip(one_minus_overlaps, bins[0], bins[-1]), bins=bins) | |
| pass_mask = np.where(bins >= 1 - overlap_threshold, False, True) | |
| pass_perc = int((sum(counts[pass_mask[:-1]]) / counts.sum()) * 100) | |
| # plot | |
| fig, ax = plt.subplots(figsize=(5, 3)) | |
| pass_color, fail_color = 'tab:green', 'tab:red' | |
| colors = np.where(pass_mask == True, pass_color, fail_color) | |
| ax.bar(bins[:-1], counts, width=np.diff(bins), align='edge', color=colors, alpha=0.5, linewidth=1) | |
| ax.legend( | |
| [matplotlib.patches.Patch(color=c, alpha=0.5) for c in [pass_color, fail_color]], | |
| [f'Pass {pass_perc}%', f'Fail {100 - pass_perc}%'], | |
| fontsize=15, frameon=False, loc=f"upper {'left' if reverse else 'right'}", | |
| ) | |
| # axes formatting | |
| ax.set_xscale('log') | |
| ax.set_xlabel('Overlap' if reverse else '1-Overlap', fontsize=15) | |
| ax.set_ylabel('Counts', fontsize=15) | |
| ax.tick_params( | |
| axis='both', which='both', direction='in', | |
| top=True, right=True, labelsize=12, pad=5) | |
| ax.tick_params(axis='x', pad=10) | |
| ax.tick_params(axis='both', which='major', length=8) | |
| ax.tick_params(axis='both', which='minor', length=4) | |
| ax.xaxis.set_major_formatter(matplotlib.ticker.FormatStrFormatter("%.2f")) | |
| ax.set_xticks([0.001, 0.01, 0.1]) | |
| ax.set_xlim(bins[0], bins[-1]) | |
| if reverse: | |
| ax.invert_xaxis() | |
| ax.set_xticklabels([f'{1 - t:.2f}' for t in ax.get_xticks()]) | |
| plt.tight_layout() | |
| return fig | |
| def plot_original(overlaps): | |
| fig, ax = plt.subplots(figsize=(5, 3)) | |
| ax.hist(overlaps, bins=np.geomspace(0.7, 1, 50), color='tab:blue', alpha=0.5, linewidth=1) | |
| ax.set_xscale('log') | |
| ax.set_yscale('log') | |
| ax.set_xlabel('Overlap', fontsize=15) | |
| ax.set_ylabel('Counts', fontsize=15) | |
| plt.tight_layout() | |
| return fig | |
| overlap_data = np.fromstring(DATA, sep='\n') | |
| fig = plot_overlaps_histogram(overlap_data) | |
| fig.show() | |
| fig2 = plot_original(overlap_data) | |
| fig2.show() |
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