Function reference • prioritizr

Overview Overview of the package.
`prioritizr`	prioritizr: Systematic Conservation Prioritization in R
Create and solve problems Functions for creating new problems and solving them.
`problem()`	Conservation planning problem
`solve(<OptimizationProblem>,<Solver>)` `solve(<ConservationProblem>,<missing>)`	Solve
Data Simulated datasets distributed with the package.
`sim_pu_polygons` `sim_pu_zones_polygons` `sim_pu_points` `sim_pu_lines` `sim_pu_sf` `sim_pu_zones_sf` `sim_pu_raster` `sim_locked_in_raster` `sim_locked_out_raster` `sim_pu_zones_stack` `sim_features` `sim_features_zones` `sim_phylogeny`	Simulated conservation planning data
Objectives Functions for adding an objective to a problem.
`objectives`	Add an objective
`add_max_cover_objective()`	Add maximum coverage objective
`add_max_features_objective()`	Add maximum feature representation objective
`add_max_phylo_div_objective()`	Add maximum phylogenetic diversity objective
`add_max_phylo_end_objective()`	Add maximum phylogenetic endemism objective
`add_max_utility_objective()`	Add maximum utility objective
`add_min_largest_shortfall_objective()`	Add minimum largest shortfall objective
`add_min_set_objective()`	Add minimum set objective
`add_min_shortfall_objective()`	Add minimum shortfall objective
Targets Functions for adding targets to a problem.
`targets`	Add representation targets
`add_absolute_targets()`	Add absolute targets
`add_loglinear_targets()`	Add targets using log-linear scaling
`add_manual_targets()`	Add manual targets
`add_relative_targets()`	Add relative targets
Constraints Functions for adding constraints to a problem.
`constraints`	Conservation problem constraints
`add_contiguity_constraints(<ConservationProblem>,<ANY>,<ANY>)` `add_contiguity_constraints(<ConservationProblem>,<ANY>,<data.frame>)` `add_contiguity_constraints(<ConservationProblem>,<ANY>,<matrix>)`	Add contiguity constraints
`add_feature_contiguity_constraints(<ConservationProblem>,<ANY>,<Matrix>)` `add_feature_contiguity_constraints(<ConservationProblem>,<ANY>,<data.frame>)` `add_feature_contiguity_constraints(<ConservationProblem>,<ANY>,<matrix>)` `add_feature_contiguity_constraints(<ConservationProblem>,<ANY>,<ANY>)`	Add feature contiguity constraints
`add_linear_constraints(<ConservationProblem>,<ANY>,<ANY>,<character>)` `add_linear_constraints(<ConservationProblem>,<ANY>,<ANY>,<numeric>)` `add_linear_constraints(<ConservationProblem>,<ANY>,<ANY>,<matrix>)` `add_linear_constraints(<ConservationProblem>,<ANY>,<ANY>,<Matrix>)` `add_linear_constraints(<ConservationProblem>,<ANY>,<ANY>,<Raster>)` `add_linear_constraints(<ConservationProblem>,<ANY>,<ANY>,<dgCMatrix>)`	Add linear constraints
`add_locked_in_constraints()`	Add locked in constraints
`add_locked_out_constraints()`	Add locked out constraints
`add_mandatory_allocation_constraints(<ConservationProblem>)`	Add mandatory allocation constraints
`add_manual_bounded_constraints()`	Add manually specified bound constraints
`add_manual_locked_constraints()`	Add manually specified locked constraints
`add_neighbor_constraints(<ConservationProblem>,<ANY>,<ANY>,<ANY>)` `add_neighbor_constraints(<ConservationProblem>,<ANY>,<ANY>,<data.frame>)` `add_neighbor_constraints(<ConservationProblem>,<ANY>,<ANY>,<matrix>)` `add_neighbor_constraints(<ConservationProblem>,<ANY>,<ANY>,<array>)`	Add neighbor constraints
Penalties Functions for adding penalties to a problem.
`penalties`	Add a penalty
`add_asym_connectivity_penalties(<ConservationProblem>,<ANY>,<ANY>,<matrix>)` `add_asym_connectivity_penalties(<ConservationProblem>,<ANY>,<ANY>,<Matrix>)` `add_asym_connectivity_penalties(<ConservationProblem>,<ANY>,<ANY>,<data.frame>)` `add_asym_connectivity_penalties(<ConservationProblem>,<ANY>,<ANY>,<dgCMatrix>)` `add_asym_connectivity_penalties(<ConservationProblem>,<ANY>,<ANY>,<array>)`	Add asymmetric connectivity penalties
`add_boundary_penalties()`	Add boundary penalties
`add_connectivity_penalties(<ConservationProblem>,<ANY>,<ANY>,<matrix>)` `add_connectivity_penalties(<ConservationProblem>,<ANY>,<ANY>,<Matrix>)` `add_connectivity_penalties(<ConservationProblem>,<ANY>,<ANY>,<data.frame>)` `add_connectivity_penalties(<ConservationProblem>,<ANY>,<ANY>,<dgCMatrix>)` `add_connectivity_penalties(<ConservationProblem>,<ANY>,<ANY>,<array>)`	Add connectivity penalties
`add_feature_weights(<ConservationProblem>,<numeric>)` `add_feature_weights(<ConservationProblem>,<matrix>)`	Add feature weights
`add_linear_penalties(<ConservationProblem>,<ANY>,<character>)` `add_linear_penalties(<ConservationProblem>,<ANY>,<numeric>)` `add_linear_penalties(<ConservationProblem>,<ANY>,<matrix>)` `add_linear_penalties(<ConservationProblem>,<ANY>,<Matrix>)` `add_linear_penalties(<ConservationProblem>,<ANY>,<Raster>)` `add_linear_penalties(<ConservationProblem>,<ANY>,<dgCMatrix>)`	Add linear penalties
Decisions Functions for specifying the type of decisions in a problem.
`decisions`	Add decision types
`add_binary_decisions()`	Add binary decisions
`add_default_decisions()`	Add default decisions
`add_proportion_decisions()`	Add proportion decisions
`add_semicontinuous_decisions()`	Add semi-continuous decisions
Solvers Functions for specifying how a problem should be solved.
`solvers`	Problem solvers
`add_cbc_solver()`	Add a CBC solver
`add_cplex_solver()`	Add a CPLEX solver
`add_default_solver()`	Add a default solver
`add_gurobi_solver()`	Add a Gurobi solver
`add_highs_solver()`	Add a HiGHS solver
`add_lpsymphony_solver()`	Add a SYMPHONY solver with lpsymphony
`add_rsymphony_solver()`	Add a SYMPHONY solver with Rsymphony
Portfolios Functions for generating a portfolio of solutions.
`portfolios`	Solution portfolios
`add_cuts_portfolio()`	Add Bender's cuts portfolio
`add_extra_portfolio()`	Add an extra portfolio
`add_gap_portfolio()`	Add a gap portfolio
`add_shuffle_portfolio()`	Add a shuffle portfolio
`add_top_portfolio()`	Add a top portfolio
Summary statistics Functions for summarizing the performance of solutions.
`summaries`	Evaluate solutions using summary statistics
`eval_asym_connectivity_summary(<ConservationProblem>,<ANY>,<ANY>,<matrix>)` `eval_asym_connectivity_summary(<ConservationProblem>,<ANY>,<ANY>,<Matrix>)` `eval_asym_connectivity_summary(<ConservationProblem>,<ANY>,<ANY>,<data.frame>)` `eval_asym_connectivity_summary(<ConservationProblem>,<ANY>,<ANY>,<dgCMatrix>)` `eval_asym_connectivity_summary(<ConservationProblem>,<ANY>,<ANY>,<array>)`	Evaluate asymmetric connectivity of solution
`eval_boundary_summary()`	Evaluate solution boundary length
`eval_connectivity_summary(<ConservationProblem>,<ANY>,<ANY>,<matrix>)` `eval_connectivity_summary(<ConservationProblem>,<ANY>,<ANY>,<Matrix>)` `eval_connectivity_summary(<ConservationProblem>,<ANY>,<ANY>,<data.frame>)` `eval_connectivity_summary(<ConservationProblem>,<ANY>,<ANY>,<dgCMatrix>)` `eval_connectivity_summary(<ConservationProblem>,<ANY>,<ANY>,<array>)`	Evaluate connectivity of solution
`eval_cost_summary()`	Evaluate solution cost
`eval_feature_representation_summary()`	Evaluate feature representation
`eval_n_summary()`	Evaluate number of planning units selected
`eval_target_coverage_summary()`	Evaluate target coverage
Importance Functions for calculating importance scores for a solution.
`importance` `irreplaceability`	Evaluate solution importance
`eval_ferrier_importance()`	Evaluate solution importance using Ferrier scores
`eval_rare_richness_importance()`	Evaluate solution importance using rarity weighted richness scores
`eval_replacement_importance()`	Evaluate solution importance using replacement cost scores
Data simulation Functions for simulating new datasets.
`simulate_cost()`	Simulate cost data
`simulate_data()`	Simulate data
`simulate_species()`	Simulate species habitat suitability data
Geoprocessing Functions for manipulating spatial datasets.
`fast_extract()`	Fast extract
`intersecting_units()`	Find intersecting units
Marxan functions Functions for importing and converting Marxan data.
`marxan_problem()`	Marxan conservation problem
`marxan_boundary_data_to_matrix()`	Convert Marxan boundary data to matrix format
`marxan_connectivity_data_to_matrix()`	Convert Marxan connectivity data to matrix format
Matrix functions Functions for creating matrices that are used in conservation planning problems.
`adjacency_matrix()`	Adjacency matrix
`boundary_matrix()`	Boundary matrix
`branch_matrix()`	Branch matrix
`connectivity_matrix()`	Connectivity matrix
`proximity_matrix()`	Proximity matrix
`rij_matrix()`	Feature by planning unit matrix
Processing multi-zone data Functions for manipulating data that pertain to multiple zones.
`category_layer()`	Category layer
`category_vector()`	Category vector
`binary_stack()`	Binary stack
Problem manipulation functions Functions for extracting information from problems.
`number_of_features()`	Number of features
`number_of_planning_units()`	Number of planning units
`number_of_total_units()`	Number of total units
`number_of_zones()`	Number of zones
`feature_names()`	Feature names
`feature_abundances()`	Feature abundances
`zone_names()`	Zone names
Miscellaneous functions Assorted functions distributed with the package.
`print(<ConservationProblem>)` `print(<ConservationModifier>)` `print(<Id>)` `print(<Id>)` `print(<OptimizationProblem>)` `print(<ScalarParameter>)` `print(<ArrayParameter>)` `print(<Solver>)` `print(<Zones>)` `print(<tbl_df>)`	Print
`show(<ConservationModifier>)` `show(<ConservationProblem>)` `show(<Id>)` `show(<OptimizationProblem>)` `show(<Parameter>)` `show(<Solver>)`	Show
`%>%` `pipe`	Pipe operator
`%T>%` `tee`	Tee operator
`is.Id()` `is.Waiver()`	Is it?
`as.Id()` `as.list(<Parameters>)` `as.list(<Zones>)`	Coerce object to another object
`compile()`	Compile a problem
`presolve_check()`	Presolve check
`loglinear_interpolation()`	Log-linear interpolation
`run_calculations()`	Run calculations
`distribute_load()`	Distribute load
`write_problem()`	Write problem
Class definitions and methods Documentation for internal data structures and associated functions.
`new_id()`	Identifier
`new_waiver()`	Waiver
`pproto()`	Create a new `pproto` object
`new_optimization_problem()`	Optimization problem
`predefined_optimization_problem()`	Predefined optimization problem
`as.list(<OptimizationProblem>)`	Convert `OptimizationProblem` to list
`ArrayParameter-class` `ArrayParameter`	Array parameter prototype
`Collection-class` `Collection`	Collection prototype
`ConservationModifier-class` `ConservationModifier`	Conservation problem modifier prototype
`ConservationProblem-class` `ConservationProblem`	Conservation problem class
`Constraint-class` `Constraint`	Constraint prototype
`Decision-class` `Decision`	Decision prototype
`MiscParameter-class` `MiscParameter`	Miscellaneous parameter prototype
`Objective-class` `Objective`	Objective prototype
`OptimizationProblem-class` `OptimizationProblem`	Optimization problem class
`Parameter-class` `Parameter`	Parameter class
`Parameters-class` `Parameters`	Parameters class
`Penalty-class` `Penalty`	Penalty prototype
`Portfolio-class` `Portfolio`	Portfolio prototype
`ScalarParameter-class` `ScalarParameter`	Scalar parameter prototype
`Solver-class` `Solver`	Solver prototype
`Target-class` `Target`	Target prototype
`zones()`	Management zones
`nrow()` `ncol()` `ncell()` `modelsense()` `vtype()` `obj()` `A()` `rhs()` `sense()` `lb()` `ub()` `col_ids()` `row_ids()` `compressed_formulation()`	Optimization problem methods
`nrow(<tbl_df>)` `ncol(<tbl_df>)` `as.list(<tbl_df>)`	Manipulate tibbles
Parameter definitions Documentation for internal structures that describe input parameters.
`proportion_parameter_array()` `binary_parameter_array()` `integer_parameter_array()` `numeric_parameter_array()`	Array parameters
`numeric_matrix_parameter()` `binary_matrix_parameter()`	Matrix parameters
`misc_parameter()`	Miscellaneous parameter
`proportion_parameter()` `binary_parameter()` `integer_parameter()` `numeric_parameter()`	Scalar parameters
`parameters()`	Parameters
Deprecated functions Documentation for functions that are no longer available.
`add_connected_constraints()` `add_corridor_constraints()` `set_number_of_threads()` `get_number_of_threads()` `is.parallel()` `add_pool_portfolio()` `connected_matrix()` `feature_representation()` `replacement_cost()` `rarity_weighted_richness()` `ferrier_score()`	Deprecation notice

Reference

Overview

Create and solve problems

Data

Objectives

Targets

Constraints

Penalties

Decisions

Solvers

Portfolios

Summary statistics

Importance

Data simulation

Geoprocessing

Marxan functions

Matrix functions

Processing multi-zone data

Problem manipulation functions

Miscellaneous functions

Class definitions and methods

Parameter definitions

Deprecated functions