deeplearning/modulus/modulus-core-v021/_modules/modulus/metrics/climate/efi.html

Core v0.2.1

Source code for modulus.metrics.climate.efi

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#     http://www.apache.org/licenses/LICENSE-2.0
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# TODO(Dallas) Introduce Distributed Class for computation.

import torch
from modulus.metrics.general.histogram import normal_pdf, normal_cdf, histogram
from modulus.metrics.general.entropy import _entropy_from_counts

Tensor = torch.Tensor


[docs]def efi( pred_cdf: Tensor, bin_edges: Tensor, climatology_mean: Tensor, climatology_std: Tensor, ) -> Tensor: """Calculates the Extreme Forecast Index (EFI) for an ensemble forecast against a climatological distribution. Parameters ---------- pred_cdf : Tensor Cumulative distribution function of predictions of shape [N, ...] where N is the number of bins. This cdf must be defined over the passed bin_edges. bin_edges : Tensor Tensor of bin edges with shape [N+1, ...] where N is the number of bins. climatology_mean : Tensor Tensor of climatological mean with shape [...] climatology_std : Tensor Tensor of climatological std with shape [...] Returns ------- Tensor EFI values of each of the batched dimensions. Note ---- Reference: https://www.atmos.albany.edu/daes/atmclasses/atm401/spring_2016/ppts_pdfs/ECMWF_EFI.pdf """ clim_cdf = normal_cdf(climatology_mean, climatology_std, bin_edges, grid="right") return torch.trapz( (clim_cdf - pred_cdf) / torch.sqrt(1e-8 + clim_cdf * (1.0 - clim_cdf)), clim_cdf, dim=0, )
[docs]def normalized_entropy( pred_pdf: Tensor, bin_edges: Tensor, climatology_mean: Tensor, climatology_std: Tensor, ) -> Tensor: """Calculates the relative entropy, or surprise, of using the prediction distribution as opposed to the climatology distribution. Parameters ---------- pred_cdf : Tensor Cumulative distribution function of predictions of shape [N, ...] where N is the number of bins. This cdf must be defined over the passed bin_edges. bin_edges : Tensor Tensor of bin edges with shape [N+1, ...] where N is the number of bins. climatology_mean : Tensor Tensor of climatological mean with shape [...] climatology_std : Tensor Tensor of climatological std with shape [...] Returns ------- Tensor Relative Entropy values of each of the batched dimensions. Note ---- Reference: https://www.atmos.albany.edu/daes/atmclasses/atm401/spring_2016/ppts_pdfs/ECMWF_EFI.pdf """ clim_pdf = normal_pdf(climatology_mean, climatology_std, bin_edges, grid="right") return 1.0 - _entropy_from_counts(pred_pdf, bin_edges) / _entropy_from_counts( clim_pdf, bin_edges )
© Copyright 2023, NVIDIA Modulus Team. Last updated on Sep 21, 2023.