Struct linregress::RegressionDataBuilder

pub struct RegressionDataBuilder { /* private fields */ }

A builder to create a RegressionData struct for use with a FormulaRegressionBuilder.

Implementations

impl RegressionDataBuilder

pub fn new() -> Self

Create a new RegressionDataBuilder.

pub fn invalid_value_handling(self, setting: InvalidValueHandling) -> Self

Configure how to handle non real f64 values (NaN or infinity or negative infinity) using a variant of the InvalidValueHandling enum.

The default value is ReturnError.

Example

use linregress::{InvalidValueHandling, RegressionDataBuilder};

let builder = RegressionDataBuilder::new();
let builder = builder.invalid_value_handling(InvalidValueHandling::DropInvalid);

pub fn build_from<'a, I, S>(self, data: I) -> Result<RegressionData<'a>, Error>where
    I: IntoIterator<Item = (S, Vec<f64>)>,
    S: Into<Cow<'a, str>>,

Build a RegressionData struct from the given data.

Any type that implements the IntoIterator trait can be used for the data. This could for example be a Hashmap or a Vec.

The iterator must consist of tupels of the form (S, Vec<f64>) where S is a type that implements Into<Cow<str>>, such as String or str.

You can think of this format as the representation of a table of data where each tuple (S, Vec<f64>) represents a column. The S is the header or label of the column and the Vec<f64> contains the data of the column.

Because ~ and + are used as separators in the formula they may not be used in the name of a data column.

Example

use std::collections::HashMap;
use linregress::RegressionDataBuilder;

let mut data1 = HashMap::new();
data1.insert("Y", vec![1., 2., 3., 4.]);
data1.insert("X", vec![4., 3., 2., 1.]);
let regression_data1 = RegressionDataBuilder::new().build_from(data1)?;

let y = vec![1., 2., 3., 4.];
let x = vec![4., 3., 2., 1.];
let data2 = vec![("X", x), ("Y", y)];
let regression_data2 = RegressionDataBuilder::new().build_from(data2)?;

Trait Implementations

impl Clone for RegressionDataBuilder

fn clone(&self) -> RegressionDataBuilder

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for RegressionDataBuilder

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for RegressionDataBuilder

fn default() -> RegressionDataBuilder

Returns the “default value” for a type.

impl Copy for RegressionDataBuilder