Version 0.14.4, 2023-01-27
option to ignore NaN values in filter fields (PR #282)
Version 0.14.3, 2022-12-26
fixing rounding error issues in metric calculations (PR #281)
Version 0.14.2, 2022-12-14
Version 0.14.1, 2022-10-25
Version 0.14.0, 2022-05-13
fixed bugs in resample_mean (PR #262)
Integration tests with new ISMN Interface (PR #263)
Add option to Validation Framework to ignore errors in
ipynb files from docs/examples are now also used as (optional) tests (PR #263)
yapffor code formatting (see developers guide) (Fix #248, PR #263)
validation framework option to force dataset combinations that include reference dataset updated (PR #265)
Added TimestampAdapter to the validation framework to deal with datasets that have different date/time specification fields (PR #268)
Version 0.13.4, 2022-01-12
use oldest-supported-numpy in pyproject.toml to avoid errors due to incompatible numpy versions used in build-time.
Version 0.13.3, 2022-01-11
rollback to old C-files due to numpy compatibility issues
Version 0.13.2, 2021-12-17
wraparound=Trueis the new default in the climatology calculation
better error handling in validation framework
Version 0.13.1, 2021-12-16
Merge pull request #249 from pstradio/monthly_clim
Version 0.13.0, 2021-12-16
wraparound=True is the new default in the climatology calculation
better error handling in validation framework
Version 0.12.0, 2021-08-19
Version 0.11.4, 2021-07-13
fixed some bugs in the confidence interval calculation, for some metrics only bootstrapped CIs are available now
fixed bug in rolling metric calculation (now also works with float32 input data)
minor bug fixes
Version 0.11.3, 2021-06-01
ismnfrom the package dependencies
fixed a few bugs in
added Python 3.9 to CI
Version 0.11.0, 2021-05-12
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 (
kendalltau) have new versions
kendall_tauwhich 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.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_snrhave been deprecated. Use
pytesmo.metrics.tcol_metricsinstead (which is simply a renaming of
pytesmo.metrics.msehas been deprecated. There is a new, much faster implementation available (
pytesmo.metrics.mse_decomposition). Individual values of the components can be calculated with
Removed dependency on deprecated Numpy API
added mean resampling in temporal collocation
Version 0.10.0, 2021-02-15
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
Version 0.9.1, 2020-09-14
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)
Version 0.9, 2020-07-02
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
Version 0.8, 2019-11-21
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)
Version 0.7.1, 2019-09-03
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
Version 0.7.0, 2019-05-15
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
Version 0.6.11, 2019-05-15
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
Version 0.6.10, 2018-04-09
Fix bug in exponential filter when first value is a NaN value
Version 0.6.9, 2018-02-06
Add extendent collocation metric
Fix initial value for exponential filter
Version 0.6.8, 2017-08-29
Adapt validation framework examples to new ASCAT package version.
Adapt ERS reader to new ASCAT package version.
Make validation framework work with datasets that contain NaN columns.
Make validation framework work with pygeobase.object_base.TS objects and subclasses.
Add scaler classes to the validation framework making it possible to use e.g. stored CDF parameters during validation.
ensure_iterable does no longer take a single string as an iterable. We want to keep the string as one object.
Version 0.6.7, 2017-07-25
Add respect leap years option for climatology calculation.
Version 0.6.6, 2017-07-14
Compatible with Python 3.6
Version 0.6.5, 2017-07-10
Add additonal functions for working with dekads.
Version 0.6.4, 2017-06-02
Refactor resampling routine to be more modular and better usable outside of pytesmo.
Version 0.6.3, 2017-04-28
temporal matching performance improvement of approx. 50%
Add functions for handling dekadal dates. See
Version 0.6.2, 2017-01-13
Fix metadata for new version of pypi.
Version 0.6.1, 2017-01-13
Add return_clim keyword to anomaly calculation. Useful for getting both anomaly and climatology in one pandas.DataFrame. Also used in time series anomaly plot.
Fix bug in julian2date which led to negative microseconds in some edge cases.
Version 0.6.0, 2016-07-29
Moved the ASCAT readers to the ascat package. The functionality is the same, just replace
import ascatand everything should work the same as before.
The H07 reader now returns also ssm mean as a value between 0 and 100. Before it was between 0 and 1 and inconsistent with the other ssm values.
Fix small bug in julian date calculation and add tests for it.
Add hamming window to resample module
Version 0.5.2, 2016-04-26
Fix bugs when the validation framework encountered empty datasets for various reasons.
Add dataset adapters for masking and anomaly calculation.
Improve performance of moving average calculation and ISMN readers.
Version 0.5.1, 2016-04-21
Fix bug in jobs argument passing to Validation class.
Add support to use a pre initialized DataManager instance in the Validation class.
Add support for per dataset reading method names in the DataManager. This relaxes the assumption that every dataset has a
Version 0.5.0, 2016-04-20
Fix bug in temporal resampling if input was a pandas.Series
Major refactoring of validation framework. Please see updated documentation and example for detailed changes. The most important breaking changes are:
‘type’ is no longer used in the dataset dictionary.
the temporal matcher does no longer need to be specified since a reasonable default was developed that should handle most cases
metrics calculators are now given as dictionaries of functions. Please see the docs for an explanation and an example.
cell_based_jobs keyword was removed in favor of a more general definition of jobs.
New features are the possibility to use unrelated masking datasets and the possibility to temporally match any number of datasets and give them in sets of k datasets to multiple metric calculators.
Changes in the scaling module, escpecially CDF matching. The new CDF scaling module is more modular and does not make any assumptions about how unique the percentiles for the CDF matching have to be. CDF matching now returns NaN values if non unique percentiles are in the data. There are new functions that rescale based on pre-calculated percentiles so these can be used if the user wants to make sure that the percentiles are unique before matching.
Version 0.4.0, 2016-03-24
Fix bug in validation framework due to error prone string formatting in warnings.
Remove grid functionality. Use pygeogrids from now on.
Fix bug in moving average calculation when input had size 1.
Add recursive calculation of Pearson correlation coefficent.
Change H-SAF reading interface to use pygeobase consistently. This changes the interface slightly as the
read_imgmethod is now called just
H07 reader now returns more variables.
Resampling interface now respects dtype of input data.
Improvements in ISMN plotting interface make it possible to use the plot not only show it.
Version 0.3.6, 2015-12-10
make sure that climatologies are always 366 elements
add new options to climatology calculation for filling NaN values
add option to climatology calculation for wraparound before the smoothing
Version 0.3.5, 2015-11-04
fix bug in anomaly calculation that occurred when the climatology series had a name already
add option in anomaly calculation to respect leap years during matching
improve testing of scaling functions
add linear CDF scaling based on stored percentiles
add utility function for MATLAB like percentile calculation
add utility function for making sure elements in an array are unique by using iterative interpolation
Version 0.3.4, 2015-10-23
fix #63 by moving data preparation before period checks
fix bug in exponential and boxcar filter. Problem was that nan values were not ignored correctly
Version 0.3.3, 2015-08-26
add option to temporal resampling to exclude window boundaries
fix #48 by reintroducting netcdf imports
fix #60 by importing correctly from pygeogrids
fix #56 by allowing read_bulk keyword for ASCAT_SSM
fix #58 by using cKDTree keyword if available
lookup table indexing fixed, see #59
Version 0.3.2, 2015-07-09
hotfix for temporal resampling problem when time series where of unequal lenghts
Version 0.3.1, 2015-07-09
added validation framework and example on how to use it
fix bug (issue #51) in temporal matching
added test data as git submodule
Version 0.3.0, 2015-05-26
added calculation of pearson R confidence intervals based on fisher z transform
ISMN reader can now get the data coverage for stations and networks
ISMN interface can now be restricted to a list of networks
added python3 support
moved grid functionality to pygeogrids package, pytesmo grids are deprecated and will be removed in future releases
include triple collocation example and improve documentation see issue #24
Version 0.2.5, 2014-12-15
fixed ASCAT verion detection for latest H25 dataset WARP55R22
added example for Soil Water Index calculation
Version 0.2.4, 2014-12-09
moved to pyscaffold structure
added tests for modules
added grid generation routines
fix for issue #15
updated classes to work with new base classes, does not change API
added travis CI support
changed theme of documentation, and enabled read the docs
Version 0.2.3, 2014-10-03
added grouping module
Version 0.2.2, 2014-10-03
fixed bug that lead to old grids without shape information not loading
Version 0.2.1, 2014-8-14
added functionality to save grid as 2 dimensional array in grid.netcdf if grid is regular and shape information is given
Version 0.2.0, 2014-06-12
added readers, tests and examples for H-SAF image products H07, H08 and H14
added resample method that makes using pyresample a easier for the dictionary structure that pytesmo uses for image data
added colormap reader for custom colormaps
Version 0.1.3, 2014-05-26
fixed bug in grid.nearest_neighbour that caused different results on different systems. Radians are now always calculated at 64bit accuracy
ISMN routines now read the new ISMN download format
df_metrics.bias now also returns a namedtuple
Version 0.1.2, 2014-04-16
Reader for different versions of netCDF H25 HSAF product
added functionality to save grid definitions to netCDF files
Fixed Bug that masked all data if snow probabilities did not exist
Version 0.1.1, 2013-11-18
Added readers for netCDF H25 HSAF product
Added readers for netCDF ERS soil moisture product
Added general grid classes
Performance improvements for anomaly and climatology calculation through usage of cython
Introduced df_metrics module for convienent calculation of metrics for data saved in pandas.DataFrames