Extract distinct cohort structures from the initial communities

Reduces the landscape's initial communities to the distinct structures they contain – a structure being the set of (species, age) cohorts in a community, irrespective of which map codes carry it. On this landscape 444k communities collapse to roughly 1.7k structures with one or two cohorts, which is what makes a structure-aware calibration tractable at all.

Usage

extract_landscape_cohort_structures(ic, max_cohorts = 2L)

Arguments

ic

A data frame of initial communities with MapCode, SpeciesCode, and Age (the landis_ic_data_list target).

max_cohorts

Integer. Largest community size to retain.

Value

A tibble with one row per cohort: structure_id, n_cohorts, species, cohort_age, n_communities.

Details

n_communities is carried so downstream work can weight or subset structures by how much of the landscape they actually represent.

See also

Other growth calibration helpers: growth_add_objective(), growth_auto_window(), growth_best_candidates(), growth_bin_observations(), growth_calibration_design(), growth_calibration_partition(), growth_calibration_work_root(), growth_climatic_distance(), growth_climatic_weight(), growth_expand_over_pseudo_species(), growth_factorial_ratio_grid(), growth_fitting_windows(), growth_identifiability(), growth_inflation_factor(), growth_mortality_onset_frac(), growth_plot_palette(), growth_pseudo_species_name(), growth_reference_curves(), growth_reference_inflection(), growth_score_fit(), growth_scoring_for(), growth_smooth_observations(), growth_structure_cell_curves(), growth_structure_cohort_table(), growth_structure_design(), growth_structure_summary(), growth_window_for(), plot_growth_calibration(), plot_growth_candidate(), plot_growth_factorial_sensitivity(), plot_growth_structures(), read_growth_scoring(), read_landscape_cohort_structures(), scale_linetype_growth_reference(), write_growth_review_bundle()