v0.11.1

bugfix in combined temporal matcher

v0.11.0

• 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

v0.10.0

• Drop Travis CI and Appveyor CI, replaced by Github Actions ci.yml workflow
• New implementation of temporal collocation based on pd.reindex (PR #204)
• CDF matching function updated
• min_obs keyword added to MetricsCalculators

v0.9.1

• Include more combinations in validation framework, raise error if n < n_datasets
• n_wise_apply now can handle (drop) nans in a passed data frame correctly.
• TC metrics calculator has now option to calculate metrics for reference
• Fix deprecation warnings in anomaly adapter (Issue #198)
• Change combinations created by val framework, catch cases where scaling ref not in combinations (Issue #187)

v0.9

• Update pyscaffold v3.2.3
• Rolling Prearson's R and RMSD metrics calculator
• New results manager to handle rolling metrics
• Add deprecation warning for colormaps module
• Move timedate module to cadati, import from there
• Filter warnings in places where they are safe to ignore and not caused by pytesmo
• Update Docs and ipython notebooks

v0.8

• Update Triple Collocation metrics and metrics caluclator
• Update metrics apply function, use dictionaries instead of dataframe for results
• Remove io module and grids.grid.py and grids.netcdf.py modules
• Move resampling module to repurpose package (https://github.com/TUW-GEO/repurpose)
• Documentation updates

v0.7.1

• Change naming convention for Intercomparison metrics calculator results
• Use kdtree from pykdtree instead of scipy (faster)
• Add MetadataMetrics to metrics calculator
• Remove pybufr-ecmwf, use generic test data for testing spatial resampling

v0.7.0

• Add option for filling no data values to moving average
• Add option for minimum observations to moving average
• Default behavior of climatology calculation will now fill no_data values
  Nothing is changing if there are no no_data values in the time series

v0.6.11

• Add more metrics calculators
• Remove pytesmo.io.ismn module and move it to the ismn package
• Update tests for ascat v1.0 package
• Rename arguments for metrics functions to be more general
• Split linreg scaling function to determine and apply corrections separately
• Compatible with Python 3.7 on Windows

v0.6.10

• Update readme
• Fix bug in exponential filter when first value is a NaN value