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.