Enum MultivariateGaussianError 

#[non_exhaustive]
pub enum MultivariateGaussianError<T> {
    NotCovarianceMatrix {
        mean: Tensor<T, 1>,
        covariance: Tensor<T, 2>,
    },
    MeanVectorWrongLength {
        mean: Tensor<T, 1>,
        covariance: Tensor<T, 2>,
    },
}

Variants (Non-exhaustive)

Non-exhaustive enums could have additional variants added in future. Therefore, when matching against variants of non-exhaustive enums, an extra wildcard arm must be added to account for any future variants.

NotCovarianceMatrix

Fields

mean: Tensor<T, 1>

covariance: Tensor<T, 2>

MeanVectorWrongLength

Fields

mean: Tensor<T, 1>

covariance: Tensor<T, 2>

Trait Implementations

impl<T: Clone> Clone for MultivariateGaussianError<T>

fn clone(&self) -> MultivariateGaussianError<T>

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl<T: Debug> Debug for MultivariateGaussianError<T>

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

Formats the value using the given formatter.

impl<T: Debug> Display for MultivariateGaussianError<T>

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

Formats the value using the given formatter.

impl<T: Debug> Error for MultivariateGaussianError<T>

fn source(&self) -> Option<&(dyn Error + 'static)>

Returns the lower-level source of this error, if any.

fn description(&self) -> &str

👎Deprecated since 1.42.0: use the Display impl or to_string()

fn cause(&self) -> Option<&dyn Error>

👎Deprecated since 1.33.0: replaced by Error::source, which can support downcasting

fn provide<'a>(&'a self, request: &mut Request<'a>)

🔬This is a nightly-only experimental API. (error_generic_member_access)

Provides type-based access to context intended for error reports.

impl<T: PartialEq> PartialEq for MultivariateGaussianError<T>

fn eq(&self, other: &MultivariateGaussianError<T>) -> bool

Tests for self and other values to be equal, and is used by ==.

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

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl<T> StructuralPartialEq for MultivariateGaussianError<T>