1. 24 Apr, 2025 4 commits
  2. 22 Apr, 2025 1 commit
  3. 08 Apr, 2025 1 commit
    • fbourgin's avatar
      wip · 5adc574d
      fbourgin authored
      5adc574d
  4. 27 Dec, 2023 1 commit
  5. 26 Dec, 2023 1 commit
  6. 26 Nov, 2023 1 commit
  7. 15 Jun, 2023 1 commit
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  9. 24 Mar, 2023 1 commit
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  11. 22 Feb, 2023 1 commit
  12. 17 Feb, 2023 1 commit
  13. 13 Feb, 2023 1 commit
  14. 07 Feb, 2023 1 commit
    • Thibault Hallouin's avatar
      harmonise definitions for above/below threshold events · 4410a74f
      Thibault Hallouin authored
      Low flow events were defined as the complement of high flow events,
      meaning that Brier scores were symmetric. But it is more consistent to
      include the threshold value in both the definitions of low flow and
      high flow events since we either study one or the other, and rarely
      both at the same time, especially not using the same threshold values.
      Plus, the choice of including the threshold in high flow events rather
      than low flow ones was really arbitrary.
      
      Note, only the unit tests for contingency table-based metrics are
      impacted because threshold-based metrics are using evants="high".
      4410a74f
  15. 02 Feb, 2023 1 commit
  16. 01 Feb, 2023 1 commit
  17. 30 Jan, 2023 1 commit
  18. 27 Jan, 2023 2 commits
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  21. 16 Jan, 2023 2 commits
  22. 13 Jan, 2023 2 commits
  23. 11 Jan, 2023 1 commit
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  25. 27 Dec, 2022 2 commits
  26. 21 Dec, 2022 1 commit
  27. 01 Dec, 2022 3 commits
  28. 20 Oct, 2022 1 commit
    • Thibault Hallouin's avatar
      pave the way for summary statistics on bootstrap samples · d37e69d2
      Thibault Hallouin authored
      Ultimately, the objective is for the user to be able to get the raw
      sampled metric values, or the mean and standard deviation of the sampled
      metric values, or a series of quantiles of the sampled metric values.
      There are still problems with the standard deviation on rtensor, and
      the computation of the quantiles does not work on n-dim expressions yet.
      So the second and third options are not possible yet, so only the raw
      values can be returned. Nonetheless, the machinery and the choice of
      where to introduce the summary functionality could be implemented,
      which is the purpose of this commit. A new parameter of the bootstrap
      experiment called "summary" is added: it can be given a value of 0 (to
      get the raw values). In the future, it would also take a value of 1 for
      mean+std, and 2 for quantiles.
      d37e69d2
  29. 06 Oct, 2022 1 commit
    • Thibault Hallouin's avatar
      implement bootstrapping method for metric uncertainty estimation · 16ce8f4e
      Thibault Hallouin authored
      The bootstrapping method is based on a non-overlapping block sampling
      with replacement, where the blocks are years of data. The number of
      samples and the sample length (i.e the number of year blocks) are both
      customisable.
      
      The method is accessible both for deterministic and probabilistic
      evaluation where a new axis is added. For now, the metrics for all the
      samples are returned, but in the future, some summary statistics would
      be implemented (e.g. quantiles or mean/standard deviation).
      
      /!\ For determinist evaluation, the n-dimensional functionality became
          untenable such that the number of dimensions was fixed and
          restricted to 2D tensors.
      
      New unit tests are included to test both the bootstrapping generator
      and the numerical results obtained with the bootstrapping turned on.
      16ce8f4e
  30. 30 Sep, 2022 1 commit