Module array

Expand description

Array manipulation and data utilities

This module provides functions for manipulating and summarizing data arrays, inspired by d3-array. It includes statistics, search, binning, transformations, and set operations.

§Example

use d3rs::array::{mean, min_by, max_by, bisect_right_f64};

let data = vec![3.0, 1.0, 4.0, 1.0, 5.0, 9.0, 2.0, 6.0];
assert_eq!(mean(&data), Some(3.875));
assert_eq!(min_by(&data, |a, b| a.partial_cmp(b).unwrap()), Some(&1.0));
assert_eq!(max_by(&data, |a, b| a.partial_cmp(b).unwrap()), Some(&9.0));

let sorted = vec![1.0, 2.0, 3.0, 5.0, 8.0, 13.0];
assert_eq!(bisect_right_f64(&sorted, 4.0), 3);

Structs§

Bin: A bin containing values within a range.
BinGenerator: Configuration for generating bins/histograms.
Bisector: A bisector that uses a custom accessor function.

Enums§

ThresholdStrategy: Strategy for determining bin thresholds.

Functions§

bin: Convenience function to create bins from f64 data with default settings.
binary_search: Returns the index of the value in a sorted slice that equals x, or None if not found.
bisect: Returns the insertion point for x in a sorted slice to maintain sorted order.
bisect_left: Returns the leftmost insertion point for x in a sorted slice.
bisect_left_f64: Binary search for f64 values (handles NaN correctly).
bisect_right: Returns the rightmost insertion point for x in a sorted slice.
bisect_right_f64: Binary search for f64 values (handles NaN correctly).
count: Returns the count of values in the slice that satisfy the predicate.
cross: Returns cross product of two slices.
cumsum: Returns the cumulative sum of values in the slice.
deviation: Returns the sample standard deviation of values in the slice.
difference: Returns elements that are in a but not in b.
extent: Returns the minimum and maximum values in the slice.
extent_by: Returns the minimum and maximum values using a custom comparator.
filter: Filters elements by a predicate.
group: Groups elements by a key function.
index: Creates an index from key to element.
intersection: Returns elements that are in both a and b.
is_disjoint: Returns true if a and b have no elements in common.
is_subset: Returns true if a is a subset of b (all elements of a are in b).
is_superset: Returns true if a is a superset of b (all elements of b are in a).
least_index: Finds the value in a sorted slice that is closest to x.
log_ticks: Generate nice logarithmic ticks for a given domain.
map: Maps elements using a function.
max: Returns the maximum value in the slice.
max_by: Returns the maximum value in the slice using a custom comparator.
max_index: Returns the index of the maximum value in the slice.
mean: Returns the arithmetic mean of values in the slice.
mean_by: Returns the arithmetic mean using an accessor function.
median: Returns the median of values in a mutable slice.
merge_sorted: Merges multiple sorted slices into a single sorted Vec.
min: Returns the minimum value in the slice.
min_by: Returns the minimum value in the slice using a custom comparator.
min_index: Returns the index of the minimum value in the slice.
nice: Extend the domain to nice round values.
nice_bin_edges: Computes nice bin edges that span the given extent.
nice_number: Find a “nice” number approximately equal to the range.
pairs: Returns pairs of consecutive elements.
quantile: Returns the p-quantile of values in a mutable slice.
quantile_sorted: Returns the p-quantile of values in a sorted slice.
reduce: Reduces elements to a single value.
reverse: Reverses the order of elements in a slice.
rollup: Groups elements and applies a reducer to each group.
shuffle: Randomly shuffles a slice using the Fisher-Yates algorithm.
shuffle_seeded: Randomly shuffles a slice using a seeded random number generator.
sort_by: Sorts a slice in place using a key accessor.
sort_by_desc: Sorts a slice in place in descending order using a key accessor.
sum: Returns the sum of values in the slice.
symmetric_difference: Returns the symmetric difference: elements in a or b but not both.
threshold_sturges: Computes the recommended number of bins using Sturges’ formula.
tick_increment: Increment a nice step size to the next larger nice value.
tick_step: Compute the step size for generating approximately count ticks.
ticks: Generate nice linear ticks for a given domain.
ticks_interval: Generate ticks at specific intervals (e.g., every 5, 10, etc.).
time_ticks: Generate date/time ticks (placeholder for future implementation).
union: Returns elements that are in either a or b (or both).
unique: Returns a new Vec containing only unique elements (first occurrence).
variance: Returns the sample variance of values in the slice.

Module array

Module array Copy item path

§Example

Structs§

Enums§

Functions§

Module array