Struct CountMatrix

pub struct CountMatrix<A: Alphabet> { /* private fields */ }

A matrix storing symbol occurrences at each position.

Implementations

impl<A: Alphabet> CountMatrix<A>

pub fn new(data: DenseMatrix<u32, A::K>) -> Result<Self, InvalidData>

Create a new count matrix from the given data.

The matrix must contain count data, for sequences of the same length, i.e. rows should all sum to the same value.

pub fn from_sequences<I>(sequences: I) -> Result<Self, InvalidData>

where I: IntoIterator, <I as IntoIterator>::Item: AsRef<EncodedSequence<A>>,

Create a new count matrix from the given sequences.

Errors

This function returns Err(InvalidData) when the sequences do not all have the same length:

let result = CountMatrix::<Dna>::from_sequences([
    EncodedSequence::new(vec![T, T, A, T]),
    EncodedSequence::new(vec![T, C, A]),
]);
assert!(result.is_err());

pub fn to_freq<P>(&self, pseudo: P) -> FrequencyMatrix<A>

where P: Into<Pseudocounts<A>>,

Build a probability matrix from this count matrix using pseudo-counts.

pub fn sequence_count(&self) -> usize

Get the number of sequences used to build the matrix.

pub fn entropy(&self) -> Vec<f32>

Compute the Shannon entropy of each row of the matrix.

The entropy of a row, sometimes refered to as “uncertainty”, is computed by treating each motif position as a random variable taking values in alphabet A.

pub fn consensus(&self) -> String

Build the consensus sequence for the matrix.

For each row of the matrix, the symbol with the highest occurence is extracted. Symbols as position with entropy higher than 1.0 are shown in lowercase.

impl<A: ComplementableAlphabet> CountMatrix<A>

pub fn reverse_complement(&self) -> Self

Get the reverse-complement of this count matrix.

impl<A: Alphabet> CountMatrix<A>

pub fn matrix(&self) -> &DenseMatrix<u32, A::K>

The raw data storage for the matrix.

pub fn len(&self) -> usize

Get the length of the motif encoded in this matrix.

pub fn is_empty(&self) -> bool

Check whether the matrix is empty.

Trait Implementations

impl<A: Alphabet> AsRef<CountMatrix<A>> for CountMatrix<A>

fn as_ref(&self) -> &Self

Converts this type into a shared reference of the (usually inferred) input type.

impl<A: Alphabet> AsRef<DenseMatrix<u32, <A as Alphabet>::K>> for CountMatrix<A>

fn as_ref(&self) -> &DenseMatrix<u32, A::K>

Converts this type into a shared reference of the (usually inferred) input type.

impl<A: Clone + Alphabet> Clone for CountMatrix<A>

where A::K: Clone,

fn clone(&self) -> CountMatrix<A>

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<A: Alphabet> Correlation for CountMatrix<A>

fn num_rows(&self) -> usize

The number of rows in the matrix.

fn dot(&self, other: &Self, i: usize, j: usize) -> f32

Compute the dot product between row i of self and row j of other.

fn norm(&self, i: usize) -> f32

Compute the Euclidean norm of row i.

fn auto_correlation(&self, delay: usize) -> f32

Compute the auto-correlation with the given delay.

fn cross_correlation(&self, other: &Self) -> f32

Compute the cross-correlation between two matrices.

impl<A: Debug + Alphabet> Debug for CountMatrix<A>

where A::K: Debug,

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

Formats the value using the given formatter.

impl<A: Alphabet> Index<usize> for CountMatrix<A>

type Output = <DenseMatrix<u32, <A as Alphabet>::K> as Index<usize>>::Output

The returned type after indexing.

fn index(&self, index: usize) -> &Self::Output

Performs the indexing (container[index]) operation.

impl<A: PartialEq + Alphabet> PartialEq for CountMatrix<A>

where A::K: PartialEq,

fn eq(&self, other: &CountMatrix<A>) -> 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<A: Eq + Alphabet> Eq for CountMatrix<A>

where A::K: Eq,

impl<A: Alphabet> StructuralPartialEq for CountMatrix<A>