CHANGELOG.rst

Changes - from version >= 1.x

2025-12-26

version 1.2.1

• [enhancement] Blocks can handle missing geometries (geometry as None or NaN)
• [debug] Blocks default value column is block_values, and PointSupport default value column is values (to avoiding naming collisions during the join operation)
• [debug] Blocks object default index is created when it is not provided by the user
• [enhancement] verbose parameter for PoissonKrigingInput class that controls progress bar when calculating point support distances between neighbors

2025-11-23

version 1.2.0

• [enhancement] Blocks has the new parameters values and geometries, that might be provided instead of ds parameter
• [enhancement] calculate_semivariance() function has the new parameters values and geometries, that might be provided instead of ds parameter
• [enhancement] interpolate_points() function has the new parameters known_values and known_geometries, that might be provided instead of the known_locations parameter
• [enhancement] validate_kriging() function has the new parameters known_values and known_geometries, that might be provided instead of the known_locations parameter
• [enhancement] validate_kriging() has new parameter: progress_bar that controls tqdm progress bar
• [enhancement] inverse_distance_weighting() function has the new parameters known_values and known_geometries, that might be provided instead of the known_locations parameter
• [enhancement] IndicatorKriging class has the new parameters known_values and known_geometries, that might be provided instead of the known_locations parameter
• [enhancement] ordinary_kriging() function has the new parameters known_values and known_geometries, that might be provided instead of the known_locations parameter
• [enhancement] simple_kriging() function has the new parameters known_values and known_geometries, that might be provided instead of the known_locations parameter
• [enhancement] UniversalKriging class has the new parameters known_values and known_geometries, that might be provided instead of the known_locations parameter
• [api change] inblock_semivariance() function is now private: _inblock_semivariance()
• [enhancement] DirectionalVariogram() class has the new parameters values and geometries, that might be provided instead of ds parameter
• [tests] Added basic tests for DirectionalVariogram() class
• [enhancement] ExperimentalVariogram() class has the new parameters values and geometries, that might be provided instead of ds parameter
• [tests] Added basic tests for ExperimentalVariogram() class
• [enhancement] build_experimental_variogram() function has the new parameters values and geometries, that might be provided instead of ds parameter
• [tests] Added basic tests for build_experimental_variogram() function
• [enhancement] VariogramCloud() class has the new parameters values and geometries, that might be provided instead of ds parameter
• [api change] directional_weighted_semivariance() function is now private: _directional_weighted_semivariance()
• [api change] omnidirectional_variogram() function is now private: _omnidirectional_variogram()
• [api change] omnidirectional_semivariogram_cloud() function is now private: _omnidirectional_semivariogram_cloud()
• [enhancement] calculate_covariance() function has the new parameters values and geometries, that might be provided instead of ds parameter
• [api change] directional_covariance() function is now private: _directional_covariance()
• [api change] omnidirectional_covariance() function is now private: _omnidirectional_covariance()
• [api change] directional_semivariance() function is now private: _directional_semivariance()
• [api change] directional_semivariance_cloud() function is now private: _directional_semivariance_cloud()
• [api change] omnidirectional_semivariance() function is now private: _omnidirectional_semivariance()
• [enhancement] point_cloud_semivariance() function has the new parameters values and geometries, that might be provided instead of ds parameter
• [enhancement] code_indicator() function has the new parameters values and geometries, that might be provided instead of ds parameter
• [enhancement] ExperimentalIndicatorVariogram and IndicatorVariogramData classes have the new parameters values and geometries, that might be provided instead of ds parameter
• [enhancement] PointSupport has the new parameters values and geometries, that might be provided instead of ds parameter
• [docs] updated tutorials - new parameters are used in kriging operations, and when experimental variogram is computed
• [docs] added missing badges (Python version and package version)
• [docs] CITATION.cff, citation section in readme has been moved up, bibtex citation has been added
• [docs] corrected broken links to CONTRIBUTING.md file in readme and docs
• [setup] links to documentation have been added to pyproject.toml
• [docs] docstring examples - all user-facing API endpoints have examples in docstrings, using new input types (values | geometries)
• [docs] updated docstrings (examples) in: PointSupportDistance, core.block_filter, pipelines.interpolate, pyinterpolate.distance.block.calc_block_to_block_distance, validate_kriging, metrics module functions, inverse_distance_weighting, centroid_poisson_kriging, area_to_area_pk, area_to_point_pk, area_to_point_pk, area_to_point_pk, ordinary_kriging, simple_kriging, IndicatorKriging, UniversalKriging, Deconvolution,
• [enhancement] ExperimentalVariogram has new property - lag_semivariance_array that returns numpy array with lags and semivariances
• [enhancement] TheoreticalVariogram has new property - lag_yhat_array that returns numpy array with lags and predicted semivariances
• [api change] Deviation class parameters have been renamed to clearly point what is passed as the input
• [tests] Deviation class tests and debug (method selection)
• [docs] docstring example for Deviation
• [docs] docstring example for AggregatedVariogram and regularize()
• [docs] docstring example for ExperimentalVariogram and build_experimental_variogram(), calculate_semivariance(), used parameters values and geometries
• [docs] docstring example for calculate_covariance(), used parameters values and geometries
• [docs] docstring example for DirectionalVariogram, used parameters values and geometries
• [docs] docstring example for VariogramCloud, used parameters values and geometries
• [docs] ExperimentalIndicatorVariogram and TheoreticalIndicatorVariogram - updated examples in docstrings
• [docs] TheoreticalVariogram, and build_theoretical_variogram() examples
• [docs] calculate_spatial_dependence_index() example
• [bug/feature] ExperimentalVariogram class removes lags with NaN values (in covariance and semivariance)
• [docs] Example in interpolate_raster() function

2025-10-11

version 1.1.0

• [tests] removed create_model_validation_sets() function from tests.test_kriging.point_kriging_ds.dataprep.py because it is not used anywhere
• [enhancement] new parameter - buffer - has been added to interpolate_raster when dimension is set, it is float, by default equal to 0, must be equal or greater than 1. It creates buffer of size (buffer * step_size) around the interpolated grid.
• [enhancement] from now on it is not possible to select neighbors using triangle method (in directional variogram cases)
• [docs] updated missing DOI in Indicator Variogram
• [enhancement] representative point in Blocks is sampled from the largest Polygon when MultiPolygon is passed
• [enhancement] Blocks object might be altered during CRS transformation or new object might be created (inplace parameter and copying mechanism)
• [bug] incosistent documenation - sill represents partial sill, not total sill, and documentation might be misleading

2025-07-17

version 1.0.3

• [bug] TheoreticalVariogram().__repr__() method bug when optional custom_weights are not given

2025-07-16

version 1.0.2

• [bug] neighbors selection in Deconvolution was falling when Blocks index was string, now it works with any index type

2025-07-11

version 1.0.1

• [feature] ordinary_kriging() and simple_kriging() functions allow user to pass array-like object of coordinates as the unknown_locations parameter.
• [enhancement] added __repr__() method to TheoreticalVariogram class.

Changes in transition between 0.x to 1.x

The transition to the stable version of the package brings changes that break the past API and require your attention.

The most significant changes are related to Blocks and PointSupport classes. Their scope is broader, and they serve as core data structures when you want to perform Poisson Kriging of polygons. We recommend going through API tutorials describing both objects.

New classes and functions

• CentroidPoissonKrigingInput
• ndarray_pydantic, a type-checking function
• ExperimentalVariogramModel
• RawPoints
• VariogramPoints
• PoissonKrigingInput
• SemivariogramErrorModel
• TheoreticalVariogramModel
• BlockPoissonKriging
• Deviation
• filter_blocks
• smooth_blocks is a renamed version of the old function smooth_area_to_point_pk
• interpolate_points
• validate_plot_attributes_for_experimental_variogram is a renamed version of the old function validate_plot_attributes_for_experimental_variogram_class
• validate_bins
• validate_direction_and_tolerance
• validate_semivariance_weights
• build_mask_indices
• calculate_angular_difference
• clean_mask_indices
• define_whitening_matrix
• get_triangle_edges
• triangle_mask
• select_values_in_range_from_dataframe
• regularize
• weighted_avg_point_support_semivariances
• mean_relative_difference
• symmetric_mean_relative_difference
• calculate_average_p2b_semivariance
• covariance_fn
• from_ellipse
• from_ellipse_cloud
• from_triangle
• from_triangle_cloud
• directional_weighted_semivariance
• omnidirectional_variogram_cloud
• omnidirectional_variogram
• semivariance_fn
• directional_covariance
• omnidirectional_covariance
• directional_semivariance_cloud
• omnidirectional_semivariance
• point_cloud_semivariance
• TheoreticalIndicatorVariogram is a renamed version of the old class IndicatorVariograms
• get_lags
• get_current_and_previous_lag
• TheoreticalModelFunction
• weight_experimental_semivariance
• points_to_lon_lat
• parse_point_support_distances_array
• angles_to_unknown_block
• block_to_blocks_angles
• block_base_distances
• set_blocks_dataset
• parse_kriging_input

The list of breaking changes

Please update your code accordingly:

• ClusterDetector class has been removed due to the dependency issues, but it will be reintroduced in the next update
• calc_point_to_point_distance has been renamed to point_distance
• calculate_angular_distance has been renamed to calculate_angular_difference (because it is a difference between two angles)
• select_values_between_lags has been renamed to select_values_in_range (function covers more cases than the selection of values between the variogram lags)
• read_txt is removed, use GeoPandas or Pandas instead
• read_csv is removed, use GeoPandas or Pandas instead
• read_block is removed, use GeoPandas instead
• WeightedBlock2BlockSemivariance is removed
• WeightedBlock2PointSemivariance is removed
• weights_array is not available as a public function
• KrigingObject has been removed, but other data models have been introduced
• ExperimentalFeatureWarning is removed
• the kriging function is removed
• BlockPK has been renamed to BlockPoissonKriging
• smooth_area_to_point_pk has been renamed to smooth_blocks
• BlockToBlockKrigingComparison has been removed
• block_arr_to_dict has been removed
• block_dataframe_to_dict has been removed
• get_areal_centroids_from_agg has been removed
• get_areal_values_from_agg has been removed
• point_support_to_dict has been removed but it will be reintroduced in the upcoming updates
• transform_ps_to_dict has been removed
• transform_blocks_to_numpy has been removed
• IndexColNotUniqueError has been removed
• WrongGeometryTypeError has been removed
• SetDifferenceWarning has been removed
• check_ids has been removed
• get_aggregated_point_support_values has been removed
• get_distances_within_unknown has been removed
• get_study_max_range has been removed
• prepare_pk_known_areas has been removed
• select_poisson_kriging_data has been removed
• select_neighbors_pk_centroid_with_angle has been removed
• select_neighbors_pk_centroid has been removed
• select_centroid_poisson_kriging_data has been removed
• omnidirectional_point_cloud has been removed
• directional_point_cloud has been removed
• build_variogram_point_cloud has been removed
• omnidirectional_covariogram has been removed
• directional_covariogram has been removed
• build_experimental_variogram has been removed
• directional_semivariogram has been removed
• IndicatorVariograms renamed to TheoreticalIndicatorVariogram
• inblock_semivariance has been removed
• MetricsTypeSelectionError has been removed
• VariogramModelNotSetError has been removed
• validate_direction has been removed
• validate_points has been removed
• validate_tolerance has been removed
• validate_weights has been removed
• validate_selected_errors has been removed
• check_nuggets has been removed
• check_ranges has been removed
• check_sills has been removed
• validate_plot_attributes_for_experimental_variogram_class renamed to validate_plot_attributes_for_experimental_variogram
• validate_theoretical_variogram
• to_tiff has been removed due to the dependency problems. The functionality will be reintroduced in the future

Old changes (version < 1.x)

2025-01-04

version 0.5.4

• (python) removed Python 3.8 from the supported versions,
• (debug) fixed DivisionByZeroWarning when semivariogram range is equal to 0

2024-10-26

version 0.5.3

• (logic) debugged variance error calculations for Area-to-Point Poisson Kriging
• (bug) #428
• (enhancement) added universal kriging functionality along with multivariate regression

2024-06-26

version 0.5.2

• (dependencies) GeoPandas >= 1; numpy < 2

2024-02-19

version 0.5.1 (pre production development)

• (enhancement) interpolate_raster() function takes allow_approx_solutions parameter, and it protects from LinAlgError that might occur if interpolation points are duplicated (due to the floating point number representation).
• (refactoring) calc_point_to_point_distance function refactored to point_distance, changed input parameters' schema,
• (refactoring) new selection method for unequally spaced bins: select_values_between_lags
• (debug) np.float type casting has been changed to float

2023-09-16

version 0.5.0.post1

• (debug) hdbscan is removed from requirements, cluster detection algorithms are blocked, and those will be reimplemented in the closest future. The HDBSCAN package breaks installation of the package.

2023-08-29

version 0.5

• (feature) to_tiff() function which writes kriging output from the interpolate_raster() function to tiff and tfw files,
• (debug) safe theoretical variogram models,
• (enhancement) model_types parameter can be string only (in the future the name of this parameter will be changed),
• (dependencies) fixed dependencies (hdbscan and scikit-learn),
• (enhancement) updated tutorials, we slightly changed their structure,
• (dependencies) End of support for Python 3.7,
• (invalid) Warning when user tries to use .plot() method of the ExperimentalVariogram class,
• (invalid) Default direction and tolerance are None instead of floats,
• (invalid) Removed unnecessary warning from the .autofit() method.

2023-05-03

version 0.4.2

• (enhancement) added support for reading feather and parquet files by Point Support and Blocks classes.

2023-04-15

version 0.4.1

• (change) The initialization of ExperimentalVariogram instance always calculates variance automatically (in the previous versions users may decide if they want to).
• (enhancement) "safe" method of variogram autofit that chooses linear, power, and spherical models,
• (enhancement) add automatic nugget selection for TheoreticalVariogram().autofit() method,
• (debug) Deconvolution().fit() and Deconvultion().fit_transform() transform nugget, range, and sill to float to avoid errors related to numpy int64 casting.

2023-04-02

version 0.4

• (feature) Cluster detection with DBSCAN,
• (feature) Cluster aggregation,
• (feature) Gridding algorithm,
• (feature) Grid aggregation,
• (feature) Removed connections to external APIs, and requests package from requirements,
• (feature) The new package with datasets has been created: https://pypi.org/project/pyinterpolate-datasets/2023.0.0/
• (feature) Theoretical Variogram calculates not Spatial Dependence Index,
• (debugging) rang key in theoretical semivariogram model renamed to range,
• (feature) Indicator Kriging.

2023-02-09

version 0.3.7

• (enhancement) added logging to Poisson Kriging ATP process,
• (test) added functional test for smooth_blocks function,
• (debug) too broad exception in download_air_quality_poland is narrowed to KeyError,
• (enhancement) log points that cannot be assigned to any area in PointSupport class,
• (enhancement) transform_ps_to_dict() function takes custom parameters for lon, lat, value and index,
• (test) check_limits() function tests,
• (test) plotting function of the VariogramCloud() class is tested and slightly changed to return True if everything has worked fine,
• (tutorials) new tutorial about ExperimentalVariogram and VariogramCloud classes,
• (test) new tests for calculate_average_semivariance() function from block module,
• (enhancement) function inblock_semivariance has been optimized,
• (docs) updated __init__.py of variogram.theoretical module,
• (enhancement) scatter plot represented as a swarm plot in VariogramCloud,
• (enhancement) added directional kriging for ATA and ATP Poisson Kriging,
• (debug) warning for directional kriging functions,
• (enhancement) initialization of KrigingObject dataclass,
• (ci/cd) added new workflow tests for MacOS and Ubuntu,
• (enhancement) added logging to Simple Kriging process.

2023-01-16

version 0.3.6

• (enhancement) Directional Centroid-based Poisson Kriging,
• (debug) Added origin (unknown point) to calculate directional Kriging and directional Centroid-based Poisson Kriging,
• (docs) Directional Ordinary Kriging tutorial,
• (engancement) logging of area to area PK function,
• (enhancement) tests package moved outside the main package,
• (feature) ordinary kriging from covariance terms,
• (feature) area-to-area PK from covariance terms,
• (debug) area-to-area PK debugged,
• (feature) area-to-point PK from covariance terms,
• (debug) area-to-point PK debugged,
• (feature) centroid-based PK from covariance terms,
• (debug) centroid-based PK debugged.

2022-11-05

version 0.3.5

• (debug) Updated directional variogram algorithm: now angle moves counterclockwise (instead of clockwise).
• (feature) Directional Ordinary Kriging,
• (feature) Directional Simple Kriging,
• (feature) Angle calculations (angle to origin, angle between vectors),
• (enhancement) direction parameter is None default, to avoid hard-to-track bugs,
• (debug) debugged interpolate_raster() function,
• (enhancement) kriging data selection - a small refactoring,
• (docs) Updated distance module docs,
• (enhancement) point kriging functions refactoring and update, better management of a singular matrices and duplicated points.

2022-10-22

version 0.3.4.post1

• (setup) added pyogrio to dependencies due to the new fiona version (1.8.22) and gdal errors.

2022-10-21

version 0.3.4

• (debug) control of data dtypes after transformations and preparation of PointSupport and Blocks,
• (debug) updated data selection methods for Poisson Kriging to avoid mixing column of numerical and non-numerical values in a single numpy array, (it makes algorithm faster),
• (update) updated tutorials,
• (feature) check area and point support indexes with smooth_area_to_point_pk(),
• (docs) updated docstrings for calculate_covariance() and calculate_semivariance() functions.

2022-10-18

version 0.3.3

• Semivariogram Deconvolution takes possible model types as a parameter,
• Semivariogram Deconvolution uses basic set of variogram models (spherical, linear, power, exponential),
• New class: DirectionalVariogram calculates experimental variograms in four directions along with isotropic variogram,
• Corrected directions (angles were described wrong 0 degrees is W-E, -90 deg is N-S direction),
• Directional variogram calculations are faster due to the change of selection method (only non-weighted case in this release),
• Numpy's sqrt() method casts ints into floats (see Issue 306),
• Users can pass a nugget for autofit() method of TheoreticalVariogram() class, the same for Deconvolution() process.

2022-10-08

version 0.3.2

• new test dataset with regular blocks,
• more tests for Deconvolution, area_to_point_pk(), area_to_area_pk(), and centroid_based_pk(),
• if there are no values for a given lag in experimental variogram RunetimeError() is raised,
• average_block_to_block_semivariances() appends 0 to the lags with 0 points,
• calculate_block_to_block_semivariance() - valid calculation of number of point pairs.

2022-09-29

version 0.3.1

• experimental variogram, covariogram, and variogram cloud function and classes check if there are NaN's in the input data and raise ValueError,
• the length of major and minor axes of a directional variogram ellipsis are calculated differently from the tolerance parameter, (now we have a less of chaos),
• tutorial for directional variograms (Basic),
• updated download_air_quality_poland() function, now it can store downloaded data,
• updated documentation.

2022-09-04

version 0.3.0

• module io_ops renamed to io,
• the refactored function read_point_data (old) into read_txt, new functions to read csv and blocks data,
• the new objects to store block data and its point-support: Blocks and PointSupport,
• Kriging is now supported by functions, not by classes, to speed up some calculations. In the future, classes will be introduced again,
• user has much more control over the variograms development. ExperimentalVariogram class calculates variance, covariance, and semivariance, has own plotting function. TheoreticalVariogram has more models to fit, and gives more control to search for the best fit - the algorithm searches over ranges and sills. Nugget is still fixed,
• module pipelines has the function for the block data smoothing (area-to-point Poisson Kriging), the class for block data filtering (area-to-area Poisson Kriging), the kriging comparison class, and method to download sample air pollution data,
• there are many small changes and API transformations... The package is faster and more stable,
• it works with Python 3.7, 3.8, 3.9, and 3.10,
• Ordinary and Simple Kriging of large datasets may be performed in parallel,
• the package has a few warnings and raises custom errors,
• setup.py is removed, now package installs from setup.cfg,
• data structures are more complex, but they allow user to be more flexible with an input.

2021-12-31

version 0.2.5

• neighbors selection (lags counting) has been changed,
• TheoreticalSemivariogram searches for optimal sill in a grid search algorithm,
• corrected error in Krige class; now calculation of error variance is correct.

2021-12-11

version 0.2.4

• self.points_values chenged to self.points_array in TheoreticalSemivariogram class,
• NaN values are tested and checked in calc_semivariance_from_pt_cloud() function,
• new semivariogram models included in the package: cubic, circular, power,
• corrected calculation of the closest neighbors for kriging interpolation,
• changed prepare_kriging_data() function,
• the new optional parameter check_coordinates (bool) of calc_point_to_point_distance() function to control the coordinates uniqueness tests. This test is very resource-consuming and should be avoided in a normal work and it should be performed before data injection into the modeling pipeline.
• the new dev/profiling/ directory to test and profile parts of a code.

2021-08-23

version 0.2.3.post1

• the outliers removal function: you can choose side for outlier detection and remove. Default is top, available are: both, top, down,
• the outliers removal function: changed algorithm,
• new tutorial about outliers and their influence on the final model.

2021-05-13

version 0.2.3

• more parameters to store (and access) in TheoreticalSemivariogram class,
• error weighting against the linear regression model (ax + b),
• global mean for Simple Kriging as a required parameter,
• tqdm progress bar to RegularizedSemivariogram.transform() and interpolate_raster() functions,
• refactored Semivariogram Regularization: ranges are controlled by algorithm, not an user,
• added pull request template,
• added issues templates,
• bug in spherical semivariogram model,
• experimental variogram as points (not a solid line),
• inverse distance weighting function: algorithm, tests, documentation and new tutorial,
• changed output names of regularized data (ArealKriging.regularize_data) from estimated value to reg.est and from estimated prediction error to reg.err,
• error related to the id column as a string removed,
• TheoreticalSemivariogram params attribute changed to nugget, sill and range attributes.

2021-03-10

version 0.2.2.post2

• directional semivariograms methods, docs and tests added,
• check if points are within elliptical area around point of interest method, docs and tests added,
• broken dependency in README.md corrected.

2021-03-02

version 0.2.2.post1

• variogram point cloud methods, tutorials, docs and tests added,
• updated tutorials and baseline datasets to show examples with spatial correlation,
• updated README.md: contribution, example, sample image,
• data is tested against duplicates (points with the same coordinates),
• removed bug in interpolate_raster() method.