xhydro.frequency_analysis package¶
Frequency analysis module.
Submodules¶
xhydro.frequency_analysis.local module¶
Local frequency analysis functions and utilities.
- xhydro.frequency_analysis.local.criteria(ds: Dataset, p: Dataset) Dataset [source]¶
Compute information criteria (AIC, BIC, AICC) from fitted distributions, using the log-likelihood.
Parameters¶
- dsxr.Dataset
Dataset containing the yearly data that was fitted.
- pxr.Dataset
Dataset containing the parameters of the fitted distributions. Must have a dimension dparams containing the parameter names and a dimension scipy_dist containing the distribution names.
Returns¶
- xr.Dataset
Dataset containing the information criteria for the distributions.
- xhydro.frequency_analysis.local.fit(ds, distributions: list[str] | None = None, min_years: int | None = None, method: str = 'ML') Dataset [source]¶
Fit multiple distributions to data.
Parameters¶
- dsxr.Dataset
Dataset containing the data to fit. All variables will be fitted.
- distributionslist of str, optional
List of distribution names as defined in scipy.stats. See https://docs.scipy.org/doc/scipy/reference/stats.html#continuous-distributions. Defaults to [« expon », « gamma », « genextreme », « genpareto », « gumbel_r », « pearson3 », « weibull_min »].
- min_yearsint, optional
Minimum number of years required for a distribution to be fitted.
- methodstr
Fitting method. Defaults to « ML » (maximum likelihood).
Returns¶
- xr.Dataset
Dataset containing the parameters of the fitted distributions, with a new dimension scipy_dist containing the distribution names.
Notes¶
In order to combine the parameters of multiple distributions, the size of the dparams dimension is set to the maximum number of unique parameters between the distributions.
- xhydro.frequency_analysis.local.parametric_quantiles(p: Dataset, t: float | list[float], mode: str = 'max') Dataset [source]¶
Compute quantiles from fitted distributions.
Parameters¶
- pxr.Dataset
Dataset containing the parameters of the fitted distributions. Must have a dimension dparams containing the parameter names and a dimension scipy_dist containing the distribution names.
- tfloat or list of float
Return period(s) in years.
- mode{“max”, “min”}
Whether the return period is the probability of exceedance (max) or non-exceedance (min).
Returns¶
- xr.Dataset
Dataset containing the quantiles of the distributions.