What’s New

climpred v1.2.1 (2020-01-07)

Depreciated

• mad no longer a keyword for the median absolute error metric. Users should now use median_absolute_error, which is identical to changes in xskillscore version 0.0.10. (GH#283) Riley X. Brady
• pacc no longer a keyword for the p value associated with the Pearson product-moment correlation, since it is used by the correlation coefficient. (GH#283) Riley X. Brady
• msss no longer a keyword for the Murphy’s MSSS, since it is reserved for the standard MSSS. (GH#283) Riley X. Brady

New Features

• Metrics pearson_r_eff_p_value and spearman_r_eff_p_value account for autocorrelation in computing p values. (GH#283) Riley X. Brady

• Metric effective_sample_size computes number of independent samples between two time series being correlated. (GH#283) Riley X. Brady

• Added keywords for metrics: (GH#283) Riley X. Brady

  • 'pval' for pearson_r_p_value
  • ['n_eff', 'eff_n'] for effective_sample_size
  • ['p_pval_eff', 'pvalue_eff', 'pval_eff'] for pearson_r_eff_p_value
  • ['spvalue', 'spval'] for spearman_r_p_value
  • ['s_pval_eff', 'spvalue_eff', 'spval_eff'] for spearman_r_eff_p_value
  • 'nev' for nmse

Bug Fixes

• climpred now requires xarray version 0.14.1 so that the drop_vars() keyword used in our package does not throw an error. (GH#276) Riley X. Brady
• Update to xskillscore version 0.0.10 to fix errors in weighted metrics with pairwise NaNs. (GH#283) Riley X. Brady

Internals/Minor Fixes

• doc8 added to pre-commit to have consistent formatting on .rst files. (GH#283) Riley X. Brady
• Remove proper attribute on Metric class since it isn’t used anywhere. (GH#283) Riley X. Brady
• Add testing for effective p values. (GH#283) Riley X. Brady
• Add testing for whether metric aliases are repeated/overwrite each other. (GH#283) Riley X. Brady
• ppp changed to msess, but keywords allow for ppp and msss still. (GH#283) Riley X. Brady

Documentation

• Expansion of metrics documentation with much more detail on how metrics are computed, their keywords, references, min/max/perfect scores, etc. (GH#283) Riley X. Brady
• Update terminology page with more information on metrics terminology. (GH#283) Riley X. Brady

climpred v1.2.0 (2019-12-17)

Depreciated

• Abbreviation pval depreciated. Use p_pval for pearson_r_p_value instead. (GH#264) Aaron Spring.

New Features

• Users can now pass a custom metric or comparison to compute functions. (GH#268) Aaron Spring.

  • See user-defined-metrics and user-defined-comparisons.

• New deterministic metrics (see metrics). (GH#264) Aaron Spring.

  • Spearman ranked correlation (spearman_r)
  • Spearman ranked correlation p-value (spearman_r_p_value)
  • Mean Absolute Deviation (mad)
  • Mean Absolute Percent Error (mape)
  • Symmetric Mean Absolute Percent Error (smape)

• Users can now apply arbitrary xarray methods to HindcastEnsemble and PerfectModelEnsemble. (GH#243) Riley X. Brady.

  • See the Prediction Ensemble objects demo page.

• Add “getter” methods to HindcastEnsemble and PerfectModelEnsemble to retrieve xarray datasets from the objects. (GH#243) Riley X. Brady.

  >>> hind = climpred.tutorial.load_dataset('CESM-DP-SST')
  >>> ref = climpred.tutorial.load_dataset('ERSST')
  >>> hindcast = climpred.HindcastEnsemble(hind)
  >>> hindcast = hindcast.add_reference(ref, 'ERSST')
  >>> print(hindcast)
  <climpred.HindcastEnsemble>
  Initialized Ensemble:
      SST      (init, lead, member) float64 ...
  ERSST:
      SST      (time) float32 ...
  Uninitialized:
      None
  >>> print(hindcast.get_initialized())
  <xarray.Dataset>
  Dimensions:  (init: 64, lead: 10, member: 10)
  Coordinates:
  * lead     (lead) int32 1 2 3 4 5 6 7 8 9 10
  * member   (member) int32 1 2 3 4 5 6 7 8 9 10
  * init     (init) float32 1954.0 1955.0 1956.0 1957.0 ... 2015.0 2016.0 2017.0
  Data variables:
      SST      (init, lead, member) float64 ...
  >>> print(hindcast.get_reference('ERSST'))
  <xarray.Dataset>
  Dimensions:  (time: 61)
  Coordinates:
  * time     (time) int64 1955 1956 1957 1958 1959 ... 2011 2012 2013 2014 2015
  Data variables:
      SST      (time) float32 ...
  

• metric_kwargs can be passed to Metric. (GH#264) Aaron Spring.

  • See metric_kwargs under metrics.

Bug Fixes

• compute_metric() doesn’t drop coordinates from the initialized hindcast ensemble anymore. (GH#258) Aaron Spring.
• Metric uacc does not crash when ppp negative anymore. (GH#264) Aaron Spring.
• Update xskillscore to version 0.0.9 to fix all-NaN issue with pearson_r and pearson_r_p_value when there’s missing data. (GH#269) Riley X. Brady.

Internals/Minor Fixes

• Rewrote varweighted_mean_period() based on xrft. Changed time_dim to dim. Function no longer drops coordinates. (GH#258) Aaron Spring

• Add dim='time' in dpp(). (GH#258) Aaron Spring

• Comparisons m2m, m2e rewritten to not stack dims into supervector because this is now done in xskillscore. (GH#264) Aaron Spring

• Add tqdm progress bar to bootstrap_compute(). (GH#244) Aaron Spring

• Remove inplace behavior for HindcastEnsemble and PerfectModelEnsemble. (GH#243) Riley X. Brady

  • See demo page on prediction ensemble objects

• Added tests for chunking with dask. (GH#258) Aaron Spring

• Fix test issues with esmpy 8.0 by forcing esmpy 7.1 (GH#269). Riley X. Brady

• Rewrote metrics and comparisons as classes to accomodate custom metrics and comparisons. (GH#268) Aaron Spring

  • See user-defined-metrics and user-defined-comparisons.

Documentation

• Add examples notebook for temporal and spatial smoothing. (GH#244) Aaron Spring
• Add documentation for computing a metric over a specified dimension. (GH#244) Aaron Spring
• Update API to be more organized with individual function/class pages. (GH#243) Riley X. Brady.
• Add page describing the HindcastEnsemble and PerfectModelEnsemble objects more clearly. (GH#243) Riley X. Brady
• Add page for publications and helpful links. (GH#270) Riley X. Brady.

climpred v1.1.0 (2019-09-23)

Features

• Write information about skill computation to netcdf attributes(GH#213) Aaron Spring
• Temporal and spatial smoothing module (GH#224) Aaron Spring
• Add metrics brier_score, threshold_brier_score and crpss_es (GH#232) Aaron Spring
• Allow compute_hindcast and compute_perfect_model to specify which dimension dim to calculate metric over (GH#232) Aaron Spring

Bug Fixes

• Correct implementation of probabilistic metrics from xskillscore in compute_perfect_model, bootstrap_perfect_model, compute_hindcast and bootstrap_hindcast, now requires xskillscore>=0.05 (GH#232) Aaron Spring

Internals/Minor Fixes

• Rename .stats.DPP to dpp (GH#232) Aaron Spring
• Add matplotlib as a main dependency so that a direct pip installation works (GH#211) Riley X. Brady.
• climpred is now installable from conda-forge (GH#212) Riley X. Brady.
• Fix erroneous descriptions of sample datasets (GH#226) Riley X. Brady.
• Benchmarking time and peak memory of compute functions with asv (GH#231) Aaron Spring

Documentation

• Add scope of package to docs for clarity for users and developers. (GH#235) Riley X. Brady.

climpred v1.0.1 (2019-07-04)

Bug Fixes

• Accomodate for lead-zero within the lead dimension (GH#196) Riley X. Brady.
• Fix issue with adding uninitialized ensemble to HindcastEnsemble object (GH#199) Riley X. Brady.
• Allow max_dof keyword to be passed to compute_metric and compute_persistence for HindcastEnsemble (GH#199) Riley X. Brady.

Internals/Minor Fixes

• Force xskillscore version 0.0.4 or higher to avoid ImportError (GH#204) Riley X. Brady.
• Change max_dfs keyword to max_dof (GH#199) Riley X. Brady.
• Add testing for HindcastEnsemble and PerfectModelEnsemble (GH#199) Riley X. Brady

climpred v1.0.0 (2019-07-03)

climpred v1.0.0 represents the first stable release of the package. It includes HindcastEnsemble and PerfectModelEnsemble objects to perform analysis with. It offers a suite of deterministic and probabilistic metrics that are optimized to be run on single time series or grids of data (e.g., lat, lon, and depth). Currently, climpred only supports annual forecasts.

Features

• Bootstrap prediction skill based on resampling with replacement consistently in ReferenceEnsemble and PerfectModelEnsemble. (GH#128) Aaron Spring
• Consistent bootstrap function for climpred.stats functions via bootstrap_func wrapper. (GH#167) Aaron Spring
• many more metrics: _msss_murphy, _less and probabilistic _crps, _crpss (GH#128) Aaron Spring

Bug Fixes

• compute_uninitialized now trims input data to the same time window. (GH#193) Riley X. Brady
• rm_poly now properly interpolates/fills NaNs. (GH#192) Riley X. Brady

Internals/Minor Fixes

• The climpred version can be printed. (GH#195) Riley X. Brady
• Constants are made elegant and pushed to a separate module. (GH#184) Andrew Huang
• Checks are consolidated to their own module. (GH#173) Andrew Huang

Documentation

• Documentation built extensively in multiple PRs.

climpred v0.3 (2019-04-27)

climpred v0.3 really represents the entire development phase leading up to the version 1 release. This was done in collaboration between Riley X. Brady, Aaron Spring, and Andrew Huang. Future releases will have less additions.

Features

• Introduces object-oriented system to climpred, with classes ReferenceEnsemble and PerfectModelEnsemble. (GH#86) Riley X. Brady

• Expands bootstrapping module for perfect-module configurations. (GH#78, GH#87) Aaron Spring

• Adds functions for computing Relative Entropy (GH#73) Aaron Spring

• Sets more intelligible dimension expectations for climpred (GH#98, GH#105) Riley X. Brady and Aaron Spring:

  • init: initialization dates for the prediction ensemble
  • lead: retrospective forecasts from prediction ensemble; returned dimension for prediction calculations
  • time: time dimension for control runs, references, etc.
  • member: ensemble member dimension.

• Updates open_dataset to display available dataset names when no argument is passed. (GH#123) Riley X. Brady

• Change ReferenceEnsemble to HindcastEnsemble. (GH#124) Riley X. Brady

• Add probabilistic metrics to climpred. (GH#128) Aaron Spring

• Consolidate separate perfect-model and hindcast functions into singular functions (GH#128) Aaron Spring

• Add option to pass proxy through to open_dataset for firewalled networks. (GH#138) Riley X. Brady

Bug Fixes

• xr_rm_poly can now operate on Datasets and with multiple variables. It also interpolates across NaNs in time series. (GH#94) Andrew Huang
• Travis CI, treon, and pytest all run for automated testing of new features. (GH#98, GH#105, GH#106) Riley X. Brady and Aaron Spring
• Clean up check_xarray decorators and make sure that they work. (GH#142) Andrew Huang
• Ensures that help() returns proper docstring even with decorators. (GH#149) Andrew Huang
• Fixes bootstrap so p values are correct. (GH#170) Aaron Spring

Internals/Minor Fixes

• Adds unit testing for all perfect-model comparisons. (GH#107) Aaron Spring
• Updates CESM-LE uninitialized ensemble sample data to have 34 members. (GH#113) Riley X. Brady
• Adds MPI-ESM hindcast, historical, and assimilation sample data. (GH#119) Aaron Spring
• Replaces check_xarray with a decorator for checking that input arguments are xarray objects. (GH#120) Andrew Huang
• Add custom exceptions for clearer error reporting. (GH#139) Riley X. Brady
• Remove “xr” prefix from stats module. (GH#144) Riley X. Brady
• Add codecoverage for testing. (GH#152) Riley X. Brady
• Update exception messages for more pretty error reporting. (GH#156) Andrew Huang
• Add pre-commit and flake8/black check in CI. (GH#163) Riley X. Brady
• Change loadutils module to tutorial and open_dataset to load_dataset. (GH#164) Riley X. Brady
• Remove predictability horizon function to revisit for v2. (GH#165) Riley X. Brady
• Increase code coverage through more testing. (GH#167) Aaron Spring
• Consolidates checks and constants into modules. (GH#173) Andrew Huang

climpred v0.2 (2019-01-11)

Name changed to climpred, developed enough for basic decadal prediction tasks on a perfect-model ensemble and reference-based ensemble.

climpred v0.1 (2018-12-20)

Collaboration between Riley Brady and Aaron Spring begins.