tibble could lead to an error.decay_logistic().detailed_results to spatial_availability(), used to specify whether results should be aggregated by origin-destination pair or by origin. When aggregation by origin-destination pair, the output also includes the demand, impedance and combined balancing factors used to calculate spatial availability.concentration_index() and theil_t().palma_ratio() and gini_index()) and poverty (fgt_poverty()).spatial_availability() and balancing_cost().cost_to_closest() parameter n now accepts a numeric vector, instead of being restricted to a single number.cumulative_cutoff() parameters cutoff and travel_cost now accepts a numeric and a character vector, respectively, instead of being restricted to a single number/string.cumulative_interval() parameter interval now accepts a list of numeric vectors, instead of being restricted to a single vector.decay_stepped(), both steps and weights can take a list of numeric vectors as input, instead of being restricted to a single numeric vector each).cost_to_closest() would return NA values when filling missing ids (which should be filled with Inf, since they cannot reach any opportunities). This was also responsible for the warning reported in #27, which was also fixed.The package has been to tremendous changes. Basically, there’s not a single part of it that remained untouched: documentation, vignettes, function names, parameter names, extra functionality, performance improvements, etc. While it is impossible to highlight everything that has been done, we’ll try to summary some of the key points in the following topics.
data. Now they require two input datasets: travel_matrix and land_use_data.time_to_closest() -> cost_to_closest()cumulative_time_cutoff() -> cumulative_cutoff()cumulative_time_interval() -> cumulative_interval()gravity_access() -> gravity()opportunity_col -> opportunitytravel_cost_col -> travel_costby_col -> activecost_to_closest(): n_opportunities -> ncumulative_interval(): stat -> summary_functionfloating_catchment_area(): population_col -> demandfloating_catchment_area(): fca_metric -> methodactive now takes a logical, instead of a string (which by_col previously took).cumulative_interval(): summary_function now takes a function, instead of a string (which stat previously took).decay_stepped().interval_increment to cumulative_interval(), used to specify how many travel cost units separate the cutoffs used to calculate the accessibility estimates which will be used to calculate the summary estimate within the specified interval.group_by parameter, that allows accessibility estimates to be grouped by one or more columns present in travel_matrix.cumulative_interval()) gained a fill_missing_ids parameter, that includes in the results origins whose accessibility would be 0 but, due to some commonly overlooked implementation details, are usually left out from the output. cumulative_interval() doesn’t have this parameter because its result will always include all origins, otherwise the summary measure wouldn’t be calculated properly.