xskillscore.discrimination
- xskillscore.discrimination(observations, forecasts, dim=None, probability_bin_edges=array([0., 0.2, 0.4, 0.6, 0.8, 1.]))
- Returns the data required to construct the discrimination diagram for an event;
the histogram of forecasts likelihood when observations indicate an event has occurred and has not occurred.
- Parameters
observations (xarray.Dataset or xarray.DataArray) – The observations or set of observations of the event. Data should be boolean or logical (True or 1 for event occurance, False or 0 for non-occurance).
forecasts (xarray.Dataset or xarray.DataArray) – The forecast likelihoods of the event. Data should be between 0 and 1.
dim (str or list of str, optional) – Dimension(s) over which to compute the histograms Defaults to None meaning compute over all dimensions.
probability_bin_edges (array_like, optional) – Probability bin edges used to compute the histograms. Similar to np.histogram, all but the last (righthand-most) bin include the left edge and exclude the right edge. The last bin includes both edges. Defaults to 6 equally spaced edges between 0 and 1
- Returns
Array with added dimension “event” containing the histograms of forecast probabilities when the event was observed and not observed
- Return type
Examples
>>> observations = xr.DataArray(np.random.normal(size=(30, 30)), ... coords=[('x', np.arange(30)), ... ('y', np.arange(30))]) >>> forecasts = xr.DataArray(np.random.normal(size=(30, 30, 10)), ... coords=[('x', np.arange(30)), ... ('y', np.arange(30)), ... ('member', np.arange(10))]) >>> forecast_event_likelihood = (forecasts > 0).mean('member') >>> observed_event = observations > 0 >>> xs.discrimination(observed_event, forecast_event_likelihood, dim=['x','y']) <xarray.DataArray (event: 2, forecast_probability: 5)> array([[0.00437637, 0.15536105, 0.66739606, 0.12472648, 0.04814004], [0.00451467, 0.16704289, 0.66365688, 0.1241535 , 0.04063205]]) Coordinates: * forecast_probability (forecast_probability) float64 0.1 0.3 0.5 0.7 0.9 * event (event) bool True False
References