Struct linregress::RegressionDataBuilder
source · [−]pub struct RegressionDataBuilder { /* private fields */ }Expand description
A builder to create a RegressionData struct for use with a FormulaRegressionBuilder.
Implementations
Create a new RegressionDataBuilder.
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>>,
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
Returns the “default value” for a type. Read more
Auto Trait Implementations
impl RefUnwindSafe for RegressionDataBuilder
impl Send for RegressionDataBuilder
impl Sync for RegressionDataBuilder
impl Unpin for RegressionDataBuilder
impl UnwindSafe for RegressionDataBuilder
Blanket Implementations
Mutably borrows from an owned value. Read more
The inverse inclusion map: attempts to construct self from the equivalent element of its
superset. Read more
Checks if self is actually part of its subset T (and can be converted to it).
Use with care! Same as self.to_subset but without any property checks. Always succeeds.
The inclusion map: converts self to the equivalent element of its superset.