Function reference • designit

All functions
`BatchContainer`	R6 Class representing a batch container.
`BatchContainerDimension`	R6 Class representing a batch container dimension.
`L1_norm()`	Aggregation of scores: L1 norm
`L2s_norm()`	Aggregation of scores: L2 norm squared
`accept_leftmost_improvement()`	Alternative acceptance function for multi-dimensional scores in which order (left to right, e.g. first to last) denotes relevance.
`assign_from_table()`	Distributes samples based on a sample sheet.
`assign_in_order()`	Distributes samples in order.
`assign_random()`	Assignment function which distributes samples randomly.
`batch_container_from_table()`	Creates a BatchContainer from a table (data.frame/tibble::tibble) containing sample and location information.
`compile_possible_subgroup_allocation()`	Compile list of all possible ways to assign levels of the allocation variable to a given set of subgroups
`complete_random_shuffling()`	Reshuffle sample indices completely randomly
`drop_order()`	Drop highest order interactions
`first_score_only()`	Aggregation of scores: take first (primary) score only
`form_homogeneous_subgroups()`	Form groups and subgroups of 'homogeneous' samples as defined by certain variables and size constraints
`generate_terms()`	Generate `terms.object` (formula with attributes)
`get_order()`	Get highest order interaction
`invivo_study_samples`	A sample list from an in vivo experiment with multiple treatments and 2 strains
`invivo_study_treatments`	A treatment list together with additional constraints on the strain and sex of animals
`locations_table_from_dimensions()`	Create locations table from dimensions and exclude table
`longitudinal_subject_samples`	Subject sample list with group and time plus controls
`mk_exponentially_weighted_acceptance_func()`	Alternative acceptance function for multi-dimensional scores with exponentially downweighted score improvements from left to right
`mk_plate_scoring_functions()`	Create a list of scoring functions (one per plate) that quantify the spatially homogeneous distribution of conditions across the plate
`mk_simanneal_acceptance_func()`	Generate acceptance function for an optimization protocol based on simulated annealing
`mk_simanneal_temp_func()`	Create a temperature function that returns the annealing temperature at a given step (iteration)
`mk_subgroup_shuffling_function()`	Created a shuffling function that permutes samples within certain subgroups of the container locations
`mk_swapping_function()`	Create function to propose swaps of samples on each call, either with a constant number of swaps or following a user defined protocol
`multi_trt_day_samples`	Unbalanced treatment and time sample list
`optimize_design()`	Generic optimizer that can be customized by user provided functions for generating shuffles and progressing towards the minimal score
`optimize_multi_plate_design()`	Convenience wrapper to optimize a typical multi-plate design
`osat_score()`	Compute OSAT score for sample assignment.
`osat_score_generator()`	Convenience wrapper for the OSAT score
`plate_effect_example`	Example dataset with a plate effect
`plot_plate()`	Plot plate layouts
`shuffle_grouped_data()`	Generate in one go a shuffling function that produces permutations with specific constraints on multiple sample variables and group sizes fitting one specific allocation variable
`shuffle_with_constraints()`	Shuffling proposal function with constraints.
`shuffle_with_subgroup_formation()`	Compose shuffling function based on already available subgrouping and allocation information
`sum_scores()`	Aggregation of scores: sum up all individual scores
`validate_samples()`	Validates sample data.frame.
`worst_score()`	Aggregation of scores: take the maximum (i.e. worst score only)

Reference

All functions