Package index • prioritizr

Overview

Overview of the package.

prioritizr prioritizr-package: prioritizr: Systematic Conservation Prioritization in R

Create and solve problems

Functions for creating new problems and solving them.

problem(): Conservation planning problem

solve(<ConservationProblem>): Solve

zones(): Management zones

Data

Simulated datasets distributed with the package.

get_sim_pu_polygons() get_sim_zones_pu_polygons() get_sim_pu_lines() get_sim_pu_points() get_sim_pu_raster() get_sim_locked_in_raster() get_sim_locked_out_raster() get_sim_zones_pu_raster() get_sim_features() get_sim_zones_features() get_sim_phylogeny() get_sim_complex_pu_raster() get_sim_complex_locked_in_raster() get_sim_complex_locked_out_raster() get_sim_complex_features() get_sim_complex_historical_features(): Get 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_penalties_objective(): Add minimum penalties 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_auto_targets(<ConservationProblem>,<character>) add_auto_targets(<ConservationProblem>,<list>) add_auto_targets(<ConservationProblem>,<TargetMethod>): Add targets automatically

add_group_targets(): Add targets based on feature groups

add_manual_targets(): Add manual targets

add_relative_targets(): Add relative targets

spec_absolute_targets(): Specify absolute targets

spec_area_targets(): Specify targets based on area units

spec_duran_targets(): Specify targets following Durán et al. (2020)

spec_interp_absolute_targets(): Specify targets based on interpolating absolute thresholds

spec_interp_area_targets(): Specify targets based on interpolating area-based thresholds

spec_jung_targets(): Specify targets following Jung et al. (2021)

spec_max_targets(): Specify targets based on maxima

spec_min_targets(): Specify targets based on minima

spec_polak_targets(): Specify targets following Polak et al. (2015)

spec_pop_size_targets(): Specify targets based on population size

spec_relative_targets(): Specify relative targets

spec_rl_ecosystem_targets(): Specify targets based on the IUCN Red List of Ecosystems

spec_rl_species_targets(): Specify targets based on the IUCN Red List of Threatened Species

spec_rodrigues_targets(): Specify targets following Rodrigues et al. (2004)

spec_rule_targets(): Specify targets following a set of rules

spec_ward_targets(): Specify targets following Ward et al. (2025)

spec_watson_targets(): Specify targets following Watson et al. (2010)

spec_wilson_targets(): Specify targets following Wilson et al. (2010)

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>,<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>,<SpatRaster>) 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(): 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>,<ANY>) add_neighbor_constraints(<ConservationProblem>,<ANY>,<ANY>,<ANY>,<data.frame>) add_neighbor_constraints(<ConservationProblem>,<ANY>,<ANY>,<ANY>,<matrix>) add_neighbor_constraints(<ConservationProblem>,<ANY>,<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(<ConservationProblem>,<ANY>,<ANY>,<ANY>,<ANY>,<data.frame>) add_boundary_penalties(<ConservationProblem>,<ANY>,<ANY>,<ANY>,<ANY>,<matrix>) add_boundary_penalties(<ConservationProblem>,<ANY>,<ANY>,<ANY>,<ANY>,<ANY>): 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>,<SpatRaster>) add_linear_penalties(<ConservationProblem>,<ANY>,<dgCMatrix>): Add linear penalties

add_neighbor_penalties(<ConservationProblem>,<ANY>,<ANY>,<matrix>) add_neighbor_penalties(<ConservationProblem>,<ANY>,<ANY>,<data.frame>) add_neighbor_penalties(<ConservationProblem>,<ANY>,<ANY>,<ANY>) add_neighbor_penalties(<ConservationProblem>,<ANY>,<ANY>,<array>): Add neighbor penalties

calibrate_cohon_penalty(): Calibrate penalties with Cohon's method

Decisions

Functions for specifying the type of decisions in a problem.

decisions: Add decision types

add_binary_decisions(): Add binary 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: Add solvers

add_cbc_solver(): Add a CBC solver

add_cplex_solver(): Add a CPLEX solver

add_default_solver(): Add 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: Add portfolios

add_cuts_portfolio(): Add Bender's cuts portfolio

add_default_portfolio(): Add a default 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 boundary length of solution

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 cost of solution

eval_feature_representation_summary(): Evaluate feature representation by solution

eval_n_summary(): Evaluate number of planning units selected by solution

eval_target_coverage_summary(): Evaluate target coverage by solution

Importance

Functions for calculating importance scores for a solution.

importance irreplaceability: Evaluate solution importance

eval_ferrier_importance(): Evaluate solution importance using Ferrier scores

eval_rank_importance(): Evaluate solution importance using incremental ranks

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

rescale_matrix(): Rescale a 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 working with problems.

compile(): Compile a problem

feature_abundances(): Feature abundances

feature_names(): Feature names

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

presolve_check(): Presolve check

run_calculations(): Run calculations

write_problem(): Write problem

zone_names(): Zone names

Class definitions and methods

Documentation for internal classes and associated functions.

new_waiver(): Waiver

optimization_problem(): Optimization problem

ConservationModifier-class ConservationModifier: Conservation problem modifier class

ConservationProblem-class ConservationProblem: Conservation problem class

Constraint-class Constraint: Constraint class

Decision-class Decision: Decision class

Objective-class Objective: Objective class

OptimizationProblem-class OptimizationProblem: Optimization problem class

Penalty-class Penalty: Penalty class

Portfolio-class Portfolio: Portfolio class

Solver-class Solver: Solver class

Target-class Target: Target class

TargetMethod-class TargetMethod: Target setting method class

Weight-class Weight: Weight class

nrow(<OptimizationProblem>) ncol(<OptimizationProblem>) ncell(<OptimizationProblem>) modelsense() vtype() obj() A() rhs() sense() lb() ub() col_ids() row_ids() compressed_formulation() set_obj() set_lb() set_ub() append_linear_constraints() remove_last_linear_constraint(): Optimization problem methods

nrow(<tbl_df>) ncol(<tbl_df>) as.list(<tbl_df>): Manipulate tibbles

Miscellaneous functions

Assorted functions distributed with the package.

show(<ConservationModifier>) show(<ConservationProblem>) show(<OptimizationProblem>) show(<Solver>): Show

linear_interpolation(): Linear interpolation

loglinear_interpolation(): Log-linear interpolation

knit_print.ConservationProblem() knit_print.OptimizationProblem(): Print an object for knitr package.

as_km2(): Standardize unit to km²

as_per_km2(): Standardize unit to density per km²

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() distribute_load() new_optimization_problem() predefined_optimization_problem() add_loglinear_targets(): Deprecation notice