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