Fix/k stest #167
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Fix/k stest #167
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@lmizrahi the test fail, but I think this is because they are set up the wrong way. Lets discuss this in a 4eye session? |
aronsho
commented
Jul 1, 2024
seismostats/analysis/estimate_mc.py
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| @@ -44,6 +44,8 @@ def cdf_discrete_GR( | |||
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| def empirical_cdf( | |||
| sample: np.ndarray | pd.Series, | |||
| mc: float = None, | |||
| delta_m: float = 0, | |||
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0 does not make sense, put a warning that binning is in fact needed
Default small (e-16? +warning that can take long)
seismostats/analysis/estimate_mc.py
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| x, y_count = np.unique(x, return_counts=True) | ||
| # add empty bins | ||
| if delta_m > 0: |
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delta_m is always >0
seismostats/analysis/estimate_mc.py
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| idx = np.argsort(x) | ||
| x = x[idx] | ||
| y_count = y_count[idx] | ||
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| y = y[np.cumsum(y_count) - 1] |
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np.cumsum(y_count) can be zero at the beginning.
Then, we want the corresponding y to be 0
lmizrahi
approved these changes
Jul 3, 2024
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The ks test had the problem that it did not take into account bins that were empty, skewing the result.