climpred v1.1 (2019-09-23)¶
- 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
- 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.
climpredis 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
climpred v1.0.1 (2019-07-04)¶
climpred v1.0.0 (2019-07-03)¶
climpred v1.0.0 represents the first stable release of the package. It includes
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.
- Bootstrap prediction skill based on resampling with replacement consistently in
PerfectModelEnsemble. (GH#128) Aaron Spring
- Consistent bootstrap function for
bootstrap_funcwrapper. (GH#167) Aaron Spring
- many more metrics:
_crpss(GH#128) Aaron Spring
- 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.
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.
xr_rm_polycan now operate on Datasets and with multiple variables. It also interpolates across NaNs in time series. (GH#94) Andrew Huang
- Travis CI,
pytestall run for automated testing of new features. (GH#98, GH#105, GH#106) Riley X. Brady and Aaron Spring
- Clean up
check_xarraydecorators 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
- 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
check_xarraywith 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
blackcheck in CI. (GH#163) Riley X. Brady
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.