Struct Hist2d 

pub struct Hist2d {
    pub x: Vec<f64>,
    pub y: Vec<f64>,
    pub opts: Vec<Opt>,
}

A histogram of two variables.

ax.hist2d({data}, **{opts})

Prelude: No

JSON data: [list[float], list[float]]

Fields

x: Vec<f64>

X data set.

y: Vec<f64>

Y data set.

opts: Vec<Opt>

Optional keyword arguments.

Implementations

impl Hist2d

pub fn new<X, XE, Y, YE>(x: X, y: Y) -> Self

where X: IntoIterator<Item = XE>, XE: Real, Y: IntoIterator<Item = YE>, YE: Real,

Create a new Hist2d with no options.

pub fn new_pairs<I, XE, YE>(data: I) -> Self

where I: IntoIterator<Item = (XE, YE)>, XE: Real, YE: Real,

Create a new Hist2d with no options from a single iterator.

Trait Implementations

impl Clone for Hist2d

fn clone(&self) -> Hist2d

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for Hist2d

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

Formats the value using the given formatter.

impl Matplotlib for Hist2d

fn is_prelude(&self) -> bool

Return true if self should be considered as a prelude item, which are executed in the order seen after imports but before plot initialization.

fn data(&self) -> Option<Value>

Optionally encode some data as JSON, to be made available at self’s call site in the matplotlib script.

fn py_cmd(&self) -> String

Write self as Python. The (default) local environment will hold the following variables:

impl MatplotlibOpts for Hist2d

fn kwarg<T: Into<PyValue>>(&mut self, key: &str, val: T) -> &mut Self

Apply a single keyword argument.

fn o<T: Into<PyValue>>(self, key: &str, val: T) -> Self

where Self: Sized,

Apply a single keyword argument with full ownership of self.

fn oo<I>(self, opts: I) -> Self

where I: IntoIterator<Item = Opt>, Self: Sized,

Apply a series of keyword arguments with full ownership of self.

impl PartialEq for Hist2d

fn eq(&self, other: &Hist2d) -> bool

Equality operator ==.

fn ne(&self, other: &Rhs) -> bool

Inequality operator !=.

impl StructuralPartialEq for Hist2d