Changes between version 0.x and 1.x#

The new release of pyinterpolate has introduced API changes that can break old pipelines. This document covers those changes. The most profound decision was to remove I/O adapters. Pyinterpolate doesn’t handle file reading, and user should use other packages to read spatial data (for example GeoPandas or Pandas). Not all of those functions, classes, and models are listed in the official user-facing API documentation!

(This document is not completed, and some changes will be updated in the closest future)

Functions#

Functions#

version 0.x

version 1.x

calc_point_to_point_distance()

changed to point_distance()

calculate_angular_distance()

changed to calculate_angular_difference()

select_values_between_lags()

changed to select_values_in_range()

weights_array()

now private _weights_array()

smooth_area_to_point_pk()

changed to smooth_blocks()

validate_plot_attributes_for_experimental_variogram_class()

changed to validate_plot_attributes_for_experimental_variogram()

Classes#

Classes#

version 0.x

version 1.x

BlockPK()

changed to BlockPoissonKriging()

Blocks()

heavily refactored and optimized

PointSupport()

heavily refactored and optimized

IndicatorVariograms()

changed to TheoreticalIndicatorVariogram()

Temporarily not available functions and classes#

  • ClusterDetector() (due to the dependency issues)

  • point_support_to_dict()

New functions and classes#

  • CentroidPoissonKrigingInput() - class model for centroid-based Poisson Kriging operation

  • ndarray_pydantic - annotation model

  • ExperimentalVariogramModel - data model of Experimental Variogram

  • RawPoints - data model of raw points

  • VariogramPoints - data model of variogram points

  • SemivariogramErrorModel - data model of semivariogram error types

  • TheoreticalVariogramModel - data model of theoretical variogram

  • filter_blocks() - filters block aggregates using Poisson Kriging

  • smooth_blocks() - transforms aggregated data into point support model

  • BlockPoissonKriging() - Area-to-Area, Area-to-Point, or Centroid-based Poisson Kriging regularization

  • interpolate_points() - ordinary kriging of multiple points

  • interpolate_points_dask() - same a/a but using dask, for large datasets

  • validate_plot_attributes_for_experimental_variogram()

  • 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() - semivariogram regularization / deconvolution

  • weighted_avg_point_support_semivariances()

  • mean_relative_difference()

  • symmetric_mean_relative_difference()

  • Deviation() - class handles deviation monitoring during semivariogram regularization

  • calculate_average_p2b_semivariance()

  • covariance_fn() - calculate covariance

  • from_ellipse() - directional variogram method

  • from_ellipse_cloud() - a/a but for variogram cloud

  • from_triangle() - directional variogram method

  • from_triangle_cloud() - a/a but for variogram cloud

  • directional_weighted_semivariance()

  • omnidirectional_variogram_cloud()

  • omnidirectional_variogram()

  • semivariance_fn()

  • directional_covariance()

  • omnidirectional_covariance()

  • directional_semivariance_cloud()

  • omnidirectional_semivariance()

  • point_cloud_semivariance()

  • TheoreticalIndicatorVariogram() - Indicator Variogram

  • get_lags()

  • get_current_and_previous_lag()

  • TheoreticalModelFunction() - theoretical functions for variogram modeling

  • 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()

Functions and classes that are no longer supported#

  • to_tiff()

  • read_txt()

  • read_csv()

  • read_block()

  • WeightedBlock2BlockSemivariance()

  • WeightedBlock2PointSemivariance()

  • KrigingObject()

  • ExperimentalFeatureWarning()

  • kriging() - instead use ordinary_kriging() or simple_kriging()

  • BlockToBlockKrigingComparison()

  • block_arr_to_dict()

  • block_dataframe_to_dict()

  • get_areal_centroids_from_agg()

  • get_areal_values_from_agg()

  • transform_ps_to_dict()

  • transform_blocks_to_numpy()

  • IndexColNotUniqueError()

  • WrongGeometryTypeError()

  • SetDifferenceWarning

  • check_ids()

  • get_aggregated_point_support_values()

  • get_distances_within_unknown()

  • get_study_max_range()

  • prepare_pk_known_areas()

  • select_poisson_kriging_data()

  • select_neighbors_pk_centroid_with_angle()

  • select_neighbors_pk_centroid()

  • select_centroid_poisson_kriging_data()

  • omnidirectional_point_cloud()

  • directional_point_cloud()

  • build_variogram_point_cloud()

  • omnidirectional_covariogram()

  • directional_covariogram()

  • directional_semivariogram()

  • inblock_semivariance()

  • MetricsTypeSelectionError()

  • VariogramModelNotSetError()

  • validate_direction()

  • validate_points()

  • validate_tolerance()

  • validate_weights()

  • validate_selected_errors()

  • check_nuggets()

  • check_ranges()

  • check_sills()

  • validate_theoretical_variogram()

  • to_tiff() - might be returned, but for now it is removed due to the dependency issues