Created
September 12, 2024 21:01
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Plot moving means and standard deviations
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| def sliding_mean_and_stddev_interval( | |
| axis, xs, ys, n_neighbors=30, linewidth=1, color="k", ci_alpha=0.25 | |
| ): | |
| """Plot moving means and standard deviations""" | |
| _1 = np.ones(2 * n_neighbors + 1) | |
| _ys = np.nan_to_num(ys) | |
| sliding_sum = correlate1d(_ys, _1, mode="constant") | |
| sliding_N = correlate1d(np.isfinite(ys).astype(float), _1, mode="constant") | |
| sliding_mean = sliding_sum / sliding_N | |
| sliding_sumsq = correlate1d(_ys**2, _1, mode="constant") | |
| sliding_std = np.sqrt(sliding_sumsq / sliding_N - sliding_mean**2) | |
| if ci_alpha: | |
| ci = axis.fill_between( | |
| xs, | |
| sliding_mean - sliding_std, | |
| sliding_mean + sliding_std, | |
| color=color, | |
| alpha=ci_alpha, | |
| edgecolor=None, | |
| ) | |
| line = axis.plot(xs, sliding_mean, color=color, linewidth=linewidth) | |
| return line, ci, sliding_mean, sliding_std, sliding_N |
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