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Releases: TUW-GEO/pytesmo

v0.13.3

11 Jan 11:10
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rollback to old C-files due to numpy compatibility issues

v0.13.2

17 Dec 09:13
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Merge pull request #257 from s-scherrer/master

Fix PyPI upload in CI

v0.13.1

16 Dec 18:52
379f160
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Merge pull request #249 from pstradio/monthly_clim

Monthly climatology

v0.13.0

16 Dec 18:48
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  • monthly climatologies
  • wraparound=True is the new default in the climatology calculation
  • better error handling in validation framework

v0.12.0

19 Aug 09:21
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  • Add option for custom reading method name to all reading adapters (PR #245)
  • MonthMetricsAdapter for new PairwiseIntercomparisonMetrics and TripleCollocationMetrics calculators (PR #246)

v0.11.4

13 Jul 16:42
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bug fixes

v0.11.3: Merge pull request #240 from s-scherrer/master

01 Jun 16:39
54090d5
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v0.11.2

19 May 15:44
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more bugs fixed

v0.11.1

19 May 07:38
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bugfix in combined temporal matcher

v0.11.0

12 May 09:27
c2d8476
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  • Analytical and bootstrapping confidence intervals for metrics (PR #206). This
    includes some changes to the existing implementations (all old
    implementations are still available, but deprecated)

    • all pairwise metric functions take two arrays as input and return a single value

    • the correlation metrics (pearsonr, spearmanr, kendalltau) have new
      versions pearson_r, spearman_r, and kendall_tau which only return the
      correlation value, but not the p-value. The old functions have been
      deprecated. For calculating correlation + p-value, it is advised to use
      scipy.stats.pearsonr, scipy.stats.spearmanr, and
      scipy.stats.kendalltau. Instead of p-values, confidence intervals for
      the correlation coefficients could be obtained with::

      r, lower, upper = with_analytical_ci(pearson_r, x, y)

    • pytesmo.metrics.tcol_error and pytesmo.metrics.tcol_snr have been
      deprecated. Use pytesmo.metrics.tcol_metrics instead (which is simply a
      renaming of tcol_snr).

    • pytesmo.metrics.mse has been deprecated. There is a new, much faster
      implementation available (pytesmo.metrics.mse_decomposition).
      Individual values of the components can be calculated with
      pytesmo.metrics.mse, pytesmo.metrics.mse_corr,
      pytesmo.metrics.mse_bias, pytesmo.metrics.mse_var.

  • Removed dependency on deprecated Numpy API

  • added mean resampling in temporal collocation

  • updated to ascat version 2.0