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Linearly referenced data management, manipulation, and operations

Project description


The linref library builds on tabular and geospatial libraries pandas and geopandas to implement powerful features for linearly referenced data through EventsCollection and other object classes. Linear referencing operations powered by the numpy, shapely, and rangel open-source libraries allow for optimized implementations of common and advanced linearly referenced data management, manipulation, and analysis operations.

Some of the main features of this library include:

  • Event dissolves using EventsCollection.dissolve()
  • Merging and overlaying multiple tables of events with the EventsCollection.merge() method and the EventsMerge class API and its many linearly-weighted overlay aggregators
  • Linear aggregations of data such as sliding window analysis with the powerful EventsMerge.distribute() method
  • Resegmentation of linear data with EventsCollection.to_windows() and related methods
  • Creating unions of multiple EventsCollection instances with the EventsUnion object class.

Code Snippets

Create an events collection for a sample roadway events dataframe with unique
route identifier represented by the 'Route' column and data for multiple years, represented by the 'Year' column. The begin and end mile points are defined by the 'Begin' and 'End' columns. >>> ec = EventsCollection(df, keys=['Route','Year'], beg='Begin', end='End')

To select events from a specific route and a specific year, indexing for all keys can be used, producing an EventsGroup. >>> eg = ec['Route 50', 2018]

To select events on all routes but only those from a specific year, indexing for only some keys can be used. >>> ec_2018 = ec[:, 2018]

To get all events which intersect with a numeric range, the intersecting() method can be used on an EventsGroup instance. >>> df_intersecting = eg.intersecting(0.5, 1.5, closed='left_mod')

The intersecting() method can also be used for point locations by ommitting the second location attribute. >>> df_intersecting = eg.intersecting(0.75, closed='both')

The linearly weighted average of one or more attributes can be obtained using the overlay_average() method. >>> df_overlay = eg.overlay_average(0.5, 1.5, cols=['Speed_Limit','Volume'])

If the events include information on the roadway speed limit and number of lanes, they can be dissolved on these attributes. During the dissolve, other attributes can be aggregated, providing a list of associated values or performing an aggregation function over these values. >>> ec_dissolved = ec.dissolve(attr=['Speed_Limit','Lanes'], aggs=['County'])

Version Notes

0.0.9 (2023-03-02)

First update of 2023. Been a quiet start to the year.

  • Add missing .any() aggregation method to EventsMergeAttribute API. Was previously available but missed during a previous update.
  • Update documentation
  • Performance improvements
  • Various bug fixes, minor features

0.0.8.post2 (2022-12-23)

Final update of 2022 including small feature updates and bug fixes from 0.0.8. Happy Holidays!

  • Add .set_df() method for in-line modification of an EventsFrame's dataframe, inplace or not.
  • Addition of suffixes parameter and default setting to EventsUnion.union() method.
  • Performance improvements
  • Various bug fixes, minor features

0.0.8.post1 (2022-12-16)

  • Improve performance of .project() method when nearest=False by removing dependence on join_nearby() function and using native gpd features.
  • Add .size and .shape properties to EventsFrames and subclasses.
  • Various bug fixes, minor features

0.0.8 (2022-12-14)

  • Improve performance of essential .get_group() method, reducing superfluous initialization of empty dataframes and events collections and improving logging of initialized groups.
  • Improve performance of .union() method with updated RangeCollection.union() features and optimized iteration and aggregation of unified data. Performance times are significantly improved, especially for large datasets with many events groups.
  • Improve distribute method performance which was added in recent versions.
  • Drop duplicates in .project() method when using sjoin_nearest with newer versions of geopandas. Improved validation in .project() method, address edge case where projecting geometry column has a non-standard label (e.g., not 'geometry').
  • Added .sort() method to events collection. Default sorting methods remain unchanged.
  • Added warnings for missing data in target columns when initializing an EventsFrames through standard methods.
  • Remove .project_old() method from events collection due to deprecation.
  • Performance improvements
  • Various bug fixes, minor features

0.0.7 (2022-10-14)

  • Refactoring of EventsMerge system from 2D to 3D vectorized relationships for improved performance and accuracy. API and aggregation methods are largely the same.
  • Modified closed parameter use in merge relationships in accordance with rangel v0.0.6, which now performs intersections which honor the closed parameter on the left collection as well as the right collection. This provides more accurate results for events which fall on the edges of intersecting events when using left_mod or right_mod closed parameters.
  • Updates to account for rangel 0.0.6 version which is now a minimum version requirement. Added other minimum version requirements for related packages.
  • Performance improvements
  • Various bug fixes, minor features

0.0.5.post1 (2022-09-06)

  • Address deprecation of length of and iteration over multi-part geometries in shapely
  • Remove code redundancies in for get_most and get_mode

0.0.5 (2022-09-01)

  • Added sumproduct and count aggregators to EventsMergeAttribute class
  • Address deprecation of length of and iteration over multi-part geometries in shapely
  • Performance improvements
  • Various bug fixes, minor features

0.0.4 (2022-06-24)

  • Minor feature additions
  • Performance improvements
  • Addition of logos in github repo
  • Various bug fixes, minor features

0.0.3 (2022-06-07)

  • Various updates for geopandas 0.10+ dependency including improved performance of project methods
  • Automatic sorting of events dataframe prior to performing dissolve
  • Performance improvements
  • Various bug fixes, minor features

0.0.2 (2022-04-11)

  • Various bug fixes, minor features

0.0.1 (2022-03-31)

  • Original experimental release.

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