Package index

LAP Solving

Core functions for solving linear assignment problems

lap_solve()

Solve linear assignment problems

lap_solve_batch()

Solve multiple assignment problems efficiently

lap_solve_kbest()

Find k-best optimal assignments

lap_solve_line_metric()

Solve 1-D Line Assignment Problem

assignment()

Linear assignment solver

assignment_duals()

Solve assignment problem and return dual variables

bottleneck_assignment()

Solve the Bottleneck Assignment Problem

sinkhorn()

'Sinkhorn-Knopp' optimal transport solver

sinkhorn_to_assignment()

Round 'Sinkhorn' transport plan to hard assignment

Matching Functions

High-level matching for observational studies

match_couples()

Optimal matching using linear assignment

greedy_couples()

Fast approximate matching using greedy algorithm

matchmaker()

Create blocks for stratified matching

Balance Diagnostics

Assess and report match quality

balance_diagnostics()

Balance Diagnostics for Matched Pairs

balance_table()

Create Balance Table

Distance and Preprocessing

Distance computation and data preparation

compute_distances()

Compute and Cache Distance Matrix for Reuse

update_constraints()

Update Constraints on Distance Object

preprocess_matching_vars()

Preprocess matching variables with automatic checks and scaling

diagnose_distance_matrix()

Diagnose distance matrix and suggest fixes

Joined Datasets

Create analysis-ready merged datasets

join_matched()

Join Matched Pairs with Original Data

augment(<matching_result>)

Augment Matching Results with Original Data (broom-style)

augment()

Generic Augment Function

Utility Functions

Helper functions for working with results

get_total_cost()

Extract total cost from assignment result

get_method_used()

Extract method used from assignment result

as_assignment_matrix()

Convert assignment result to a binary matrix

is_lap_solve_result()

Check if object is an assignment result

is_lap_solve_batch_result()

Check if object is a batch assignment result

is_lap_solve_kbest_result()

Check if object is a k-best assignment result

is_distance_object()

Check if Object is a Distance Object

Example Data

Built-in datasets for examples and testing

hospital_staff

Hospital staff scheduling example dataset

example_costs

Example cost matrices for assignment problems

example_df

Example assignment problem data frame

Pixel Morphing

Visual demonstrations and image processing

pixel_morph()

Pixel-level image morphing (final frame only)

pixel_morph_animate()

Pixel-level image morphing (animation)

Print, Summary and Plot Methods

S3 methods for displaying and visualizing results

print(<lap_solve_result>)

Print method for assignment results

print(<lap_solve_batch_result>)

Print method for batch assignment results

print(<lap_solve_kbest_result>)

Print method for k-best assignment results

print(<matching_result>)

Print method for matching results

print(<matchmaker_result>)

Print method for matchmaker results

print(<balance_diagnostics>)

Print Method for Balance Diagnostics

print(<distance_object>)

Print Method for Distance Objects

print(<preprocessing_result>)

Print method for preprocessing result

print(<variable_health>)

Print method for variable health

summary(<lap_solve_kbest_result>)

Get summary of k-best results

summary(<distance_object>)

Summary Method for Distance Objects

summary(<matching_result>)

Summary method for matching results

summary(<balance_diagnostics>)

Summary method for balance diagnostics

plot(<matching_result>)

Plot method for matching results

plot(<balance_diagnostics>)

Plot method for balance diagnostics