Struct easy_ml::matrices::Matrix [−][src]
pub struct Matrix<T> { /* fields omitted */ }
A general purpose matrix of some type. This type may implement
no traits, in which case the matrix will be rather useless. If the
type implements Clone
most storage and accessor methods are defined and if the type implements
Numeric
then the matrix can be used in
a mathematical way.
When doing numeric operations with Matrices you should be careful to not
consume a matrix by accidentally using it by value. All the operations are
also defined on references to matrices so you should favor &x * &y
style
notation for matrices you intend to continue using. There are also convenience
operations defined for a matrix and a scalar.
Matrix size invariants
Matrices must always be at least 1x1. You cannot construct a matrix with no rows or
no columns, and any function that resizes matrices will error if you try to use it
in a way that would construct a 0x1, 1x0, or 0x0 matrix. The maximum size of a matrix
is dependent on the platform’s std::usize::MAX
value. Matrices with dimensions NxM
such that N * M < std::usize::MAX
should not cause any errors in this library, but
attempting to expand their size further may cause panics and or errors. At the time of
writing it is no longer possible to construct or use matrices where the product of their
number of rows and columns exceed std::usize::MAX
, but some constructor methods may be used
to attempt this. Concerned readers should note that on a 64 bit computer this maximum
value is 18,446,744,073,709,551,615 so running out of memory is likely to occur first.
Matrix layout and iterator performance
See iterators submodule for Matrix layout and iterator performance
Implementations
impl<T> Matrix<T>
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impl<T> Matrix<T>
[src]Methods for matrices of any type, including non numerical types such as bool.
pub fn from_scalar(value: T) -> Matrix<T>
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pub fn from_scalar(value: T) -> Matrix<T>
[src]Creates a 1x1 matrix from some scalar
pub fn from(values: Vec<Vec<T>>) -> Matrix<T>
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pub fn from(values: Vec<Vec<T>>) -> Matrix<T>
[src]Creates a matrix from a nested array of values, each inner vector being a row, and hence the outer vector containing all rows in sequence, the same way as when writing matrices in mathematics.
Example of a 2 x 3 matrix in both notations:
[ 1, 2, 4 8, 9, 3 ]
use easy_ml::matrices::Matrix; Matrix::from(vec![ vec![ 1, 2, 4 ], vec![ 8, 9, 3 ]]);
Panics
Panics if the input is jagged or rows or column length is 0.
pub fn from_flat_row_major(size: (Row, Column), values: Vec<T>) -> Matrix<T>
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pub fn from_flat_row_major(size: (Row, Column), values: Vec<T>) -> Matrix<T>
[src]Creates a matrix with the specified size from a row major vec of data. The length of the vec must match the size of the matrix or the constructor will panic.
Example of a 2 x 3 matrix in both notations:
[ 1, 2, 4 8, 9, 3 ]
use easy_ml::matrices::Matrix; Matrix::from_flat_row_major((2, 3), vec![ 1, 2, 4, 8, 9, 3]);
This method is more efficient than Matrix::from
but requires specifying the size explicitly and manually keeping track of where rows
start and stop.
Panics
Panics if the length of the vec does not match the size of the matrix.
pub fn unit(value: T) -> Matrix<T>
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Incorrect use of terminology, a unit matrix is another term for an identity matrix, please use from_scalar
instead
pub fn size(&self) -> (Row, Column)
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pub fn size(&self) -> (Row, Column)
[src]Returns the dimensionality of this matrix in Row, Column format
pub fn get_reference(&self, row: Row, column: Column) -> &T
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pub fn get_reference(&self, row: Row, column: Column) -> &T
[src]Gets a reference to the value at this row and column. Rows and Columns are 0 indexed.
Panics
Panics if the index is out of range.
pub fn set(&mut self, row: Row, column: Column, value: T)
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pub fn set(&mut self, row: Row, column: Column, value: T)
[src]Sets a new value to this row and column. Rows and Columns are 0 indexed.
Panics
Panics if the index is out of range.
pub fn remove_row(&mut self, row: Row)
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pub fn remove_row(&mut self, row: Row)
[src]Removes a row from this Matrix, shifting all other rows to the left. Rows are 0 indexed.
Panics
This will panic if the row does not exist or the matrix only has one row.
pub fn remove_column(&mut self, column: Column)
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pub fn remove_column(&mut self, column: Column)
[src]Removes a column from this Matrix, shifting all other columns to the left. Columns are 0 indexed.
Panics
This will panic if the column does not exist or the matrix only has one column.
pub fn column_reference_iter(
&self,
column: Column
) -> ColumnReferenceIterator<'_, T>ⓘNotable traits for ColumnReferenceIterator<'a, T>
impl<'a, T> Iterator for ColumnReferenceIterator<'a, T> type Item = &'a T;
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pub fn column_reference_iter(
&self,
column: Column
) -> ColumnReferenceIterator<'_, T>ⓘNotable traits for ColumnReferenceIterator<'a, T>
impl<'a, T> Iterator for ColumnReferenceIterator<'a, T> type Item = &'a T;
[src]Returns an iterator over references to a column vector in this matrix. Columns are 0 indexed.
pub fn row_reference_iter(&self, row: Row) -> RowReferenceIterator<'_, T>ⓘNotable traits for RowReferenceIterator<'a, T>
impl<'a, T> Iterator for RowReferenceIterator<'a, T> type Item = &'a T;
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pub fn row_reference_iter(&self, row: Row) -> RowReferenceIterator<'_, T>ⓘNotable traits for RowReferenceIterator<'a, T>
impl<'a, T> Iterator for RowReferenceIterator<'a, T> type Item = &'a T;
[src]Returns an iterator over references to a row vector in this matrix. Rows are 0 indexed.
pub fn column_major_reference_iter(&self) -> ColumnMajorReferenceIterator<'_, T>ⓘNotable traits for ColumnMajorReferenceIterator<'a, T>
impl<'a, T> Iterator for ColumnMajorReferenceIterator<'a, T> type Item = &'a T;
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pub fn column_major_reference_iter(&self) -> ColumnMajorReferenceIterator<'_, T>ⓘNotable traits for ColumnMajorReferenceIterator<'a, T>
impl<'a, T> Iterator for ColumnMajorReferenceIterator<'a, T> type Item = &'a T;
[src]Returns a column major iterator over references to all values in this matrix, proceeding through each column in order.
pub fn row_major_reference_iter(&self) -> RowMajorReferenceIterator<'_, T>ⓘNotable traits for RowMajorReferenceIterator<'a, T>
impl<'a, T> Iterator for RowMajorReferenceIterator<'a, T> type Item = &'a T;
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pub fn row_major_reference_iter(&self) -> RowMajorReferenceIterator<'_, T>ⓘNotable traits for RowMajorReferenceIterator<'a, T>
impl<'a, T> Iterator for RowMajorReferenceIterator<'a, T> type Item = &'a T;
[src]Returns a row major iterator over references to all values in this matrix, proceeding through each row in order.
pub fn retain_mut(&mut self, slice: Slice2D)
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pub fn retain_mut(&mut self, slice: Slice2D)
[src]Shrinks this matrix down from its current MxN size down to some new size OxP where O and P are determined by the kind of slice given and 1 <= O <= M and 1 <= P <= N.
Only rows and columns specified by the slice will be retained, so for
instance if the Slice is constructed by
Slice2D::new().rows(Slice::Range(0..2)).columns(Slice::Range(0..3))
then the
modified matrix will be no bigger than 2x3 and contain up to the first two
rows and first three columns that it previously had.
See Slice for constructing slices.
Panics
This function will panic if the slice would delete all rows or all columns from this matrix, ie the resulting matrix must be at least 1x1.
pub fn try_into_scalar(self) -> Result<T, ScalarConversionError>
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pub fn try_into_scalar(self) -> Result<T, ScalarConversionError>
[src]Consumes a 1x1 matrix and converts it into a scalar without copying the data.
Example
use easy_ml::matrices::Matrix; let x = Matrix::column(vec![ 1.0, 2.0, 3.0 ]); let sum_of_squares: f64 = (x.transpose() * x).try_into_scalar()?;
impl<T: Clone> Matrix<T>
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impl<T: Clone> Matrix<T>
[src]Methods for matrices with types that can be copied, but still not neccessarily numerical.
pub fn transpose(&self) -> Matrix<T>
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pub fn transpose(&self) -> Matrix<T>
[src]Computes and returns the transpose of this matrix
use easy_ml::matrices::Matrix; let x = Matrix::from(vec![ vec![ 1, 2 ], vec![ 3, 4 ]]); let y = Matrix::from(vec![ vec![ 1, 3 ], vec![ 2, 4 ]]); assert_eq!(x.transpose(), y);
pub fn transpose_mut(&mut self)
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pub fn transpose_mut(&mut self)
[src]Transposes the matrix in place.
use easy_ml::matrices::Matrix; let mut x = Matrix::from(vec![ vec![ 1, 2 ], vec![ 3, 4 ]]); x.transpose_mut(); let y = Matrix::from(vec![ vec![ 1, 3 ], vec![ 2, 4 ]]); assert_eq!(x, y);
pub fn column_iter(&self, column: Column) -> ColumnIterator<'_, T>ⓘNotable traits for ColumnIterator<'a, T>
impl<'a, T: Clone> Iterator for ColumnIterator<'a, T> type Item = T;
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pub fn column_iter(&self, column: Column) -> ColumnIterator<'_, T>ⓘNotable traits for ColumnIterator<'a, T>
impl<'a, T: Clone> Iterator for ColumnIterator<'a, T> type Item = T;
[src]Returns an iterator over a column vector in this matrix. Columns are 0 indexed.
If you have a matrix such as:
[ 1, 2, 3 4, 5, 6 7, 8, 9 ]
then a column of 0, 1, and 2 will yield [1, 4, 7], [2, 5, 8] and [3, 6, 9]
respectively. If you do not need to copy the elements use column_reference_iter
instead.
pub fn row_iter(&self, row: Row) -> RowIterator<'_, T>ⓘNotable traits for RowIterator<'a, T>
impl<'a, T: Clone> Iterator for RowIterator<'a, T> type Item = T;
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pub fn row_iter(&self, row: Row) -> RowIterator<'_, T>ⓘNotable traits for RowIterator<'a, T>
impl<'a, T: Clone> Iterator for RowIterator<'a, T> type Item = T;
[src]Returns an iterator over a row vector in this matrix. Rows are 0 indexed.
If you have a matrix such as:
[ 1, 2, 3 4, 5, 6 7, 8, 9 ]
then a row of 0, 1, and 2 will yield [1, 2, 3], [4, 5, 6] and [7, 8, 9]
respectively. If you do not need to copy the elements use row_reference_iter
instead.
pub fn column_major_iter(&self) -> ColumnMajorIterator<'_, T>ⓘNotable traits for ColumnMajorIterator<'a, T>
impl<'a, T: Clone> Iterator for ColumnMajorIterator<'a, T> type Item = T;
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pub fn column_major_iter(&self) -> ColumnMajorIterator<'_, T>ⓘNotable traits for ColumnMajorIterator<'a, T>
impl<'a, T: Clone> Iterator for ColumnMajorIterator<'a, T> type Item = T;
[src]Returns a column major iterator over all values in this matrix, proceeding through each column in order.
If you have a matrix such as:
[ 1, 2 3, 4 ]
then the iterator will yield [1, 3, 2, 4]. If you do not need to copy the
elements use column_major_reference_iter
instead.
pub fn row_major_iter(&self) -> RowMajorIterator<'_, T>ⓘNotable traits for RowMajorIterator<'a, T>
impl<'a, T: Clone> Iterator for RowMajorIterator<'a, T> type Item = T;
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pub fn row_major_iter(&self) -> RowMajorIterator<'_, T>ⓘNotable traits for RowMajorIterator<'a, T>
impl<'a, T: Clone> Iterator for RowMajorIterator<'a, T> type Item = T;
[src]Returns a row major iterator over all values in this matrix, proceeding through each row in order.
If you have a matrix such as:
[ 1, 2 3, 4 ]
then the iterator will yield [1, 2, 3, 4]. If you do not need to copy the
elements use row_major_reference_iter
instead.
pub fn empty(value: T, size: (Row, Column)) -> Matrix<T>
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pub fn empty(value: T, size: (Row, Column)) -> Matrix<T>
[src]Creates a matrix of the provided size with all elements initialised to the provided value
pub fn get(&self, row: Row, column: Column) -> T
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pub fn get(&self, row: Row, column: Column) -> T
[src]Gets a copy of the value at this row and column. Rows and Columns are 0 indexed.
Panics
Panics if the index is out of range.
pub fn scalar(&self) -> T
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pub fn scalar(&self) -> T
[src]Similar to matrix.get(0, 0) in that this returns the element in the first row and first column, except that this method will panic if the matrix is not 1x1.
This is provided as a convenience function when you want to convert a unit matrix to a scalar, such as after taking a dot product of two vectors.
Example
use easy_ml::matrices::Matrix; let x = Matrix::column(vec![ 1.0, 2.0, 3.0 ]); let sum_of_squares: f64 = (x.transpose() * x).scalar();
Panics
Panics if the matrix is not 1x1
pub fn map_mut(&mut self, mapping_function: impl Fn(T) -> T)
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pub fn map_mut(&mut self, mapping_function: impl Fn(T) -> T)
[src]Applies a function to all values in the matrix, modifying the matrix in place.
pub fn map_mut_with_index(
&mut self,
mapping_function: impl Fn(T, Row, Column) -> T
)
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pub fn map_mut_with_index(
&mut self,
mapping_function: impl Fn(T, Row, Column) -> T
)
[src]Applies a function to all values and each value’s index in the matrix, modifying the matrix in place.
pub fn map<U>(&self, mapping_function: impl Fn(T) -> U) -> Matrix<U> where
U: Clone,
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pub fn map<U>(&self, mapping_function: impl Fn(T) -> U) -> Matrix<U> where
U: Clone,
[src]Creates and returns a new matrix with all values from the original with the function applied to each. This can be used to change the type of the matrix such as creating a mask:
use easy_ml::matrices::Matrix; let x = Matrix::from(vec![ vec![ 0.0, 1.2 ], vec![ 5.8, 6.9 ]]); let y = x.map(|element| element > 2.0); let result = Matrix::from(vec![ vec![ false, false ], vec![ true, true ]]); assert_eq!(&y, &result);
pub fn map_with_index<U>(
&self,
mapping_function: impl Fn(T, Row, Column) -> U
) -> Matrix<U> where
U: Clone,
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pub fn map_with_index<U>(
&self,
mapping_function: impl Fn(T, Row, Column) -> U
) -> Matrix<U> where
U: Clone,
[src]Creates and returns a new matrix with all values from the original and the index of each value mapped by a function. This can be used to perform elementwise operations that are not defined on the Matrix type itself.
Exmples
Matrix elementwise division:
use easy_ml::matrices::Matrix; let x = Matrix::from(vec![ vec![ 9.0, 2.0 ], vec![ 4.0, 3.0 ]]); let y = Matrix::from(vec![ vec![ 3.0, 2.0 ], vec![ 1.0, 3.0 ]]); let z = x.map_with_index(|x, row, column| x / y.get(row, column)); let result = Matrix::from(vec![ vec![ 3.0, 1.0 ], vec![ 4.0, 1.0 ]]); assert_eq!(&z, &result);
pub fn insert_row(&mut self, row: Row, value: T)
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pub fn insert_row(&mut self, row: Row, value: T)
[src]Inserts a new row into the Matrix at the provided index, shifting other rows to the right and filling all entries with the provided value. Rows are 0 indexed.
Panics
This will panic if the row is greater than the number of rows in the matrix.
pub fn insert_row_with<I>(&mut self, row: Row, values: I) where
I: Iterator<Item = T>,
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pub fn insert_row_with<I>(&mut self, row: Row, values: I) where
I: Iterator<Item = T>,
[src]Inserts a new row into the Matrix at the provided index, shifting other rows to the right and filling all entries with the values from the iterator in sequence. Rows are 0 indexed.
Panics
This will panic if the row is greater than the number of rows in the matrix,
or if the iterator has fewer elements than self.columns()
.
Example of duplicating a row:
use easy_ml::matrices::Matrix; let x: Matrix<u8> = Matrix::row(vec![ 1, 2, 3 ]); let mut y = x.clone(); // duplicate the first row as the second row y.insert_row_with(1, x.row_iter(0)); assert_eq!((2, 3), y.size()); let mut values = y.column_major_iter(); assert_eq!(Some(1), values.next()); assert_eq!(Some(1), values.next()); assert_eq!(Some(2), values.next()); assert_eq!(Some(2), values.next()); assert_eq!(Some(3), values.next()); assert_eq!(Some(3), values.next()); assert_eq!(None, values.next());
pub fn insert_column(&mut self, column: Column, value: T)
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pub fn insert_column(&mut self, column: Column, value: T)
[src]Inserts a new column into the Matrix at the provided index, shifting other columns to the right and filling all entries with the provided value. Columns are 0 indexed.
Panics
This will panic if the column is greater than the number of columns in the matrix.
pub fn insert_column_with<I>(&mut self, column: Column, values: I) where
I: Iterator<Item = T>,
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pub fn insert_column_with<I>(&mut self, column: Column, values: I) where
I: Iterator<Item = T>,
[src]Inserts a new column into the Matrix at the provided index, shifting other columns to the right and filling all entries with the values from the iterator in sequence. Columns are 0 indexed.
Panics
This will panic if the column is greater than the number of columns in the matrix,
or if the iterator has fewer elements than self.rows()
.
Example of duplicating a column:
use easy_ml::matrices::Matrix; let x: Matrix<u8> = Matrix::column(vec![ 1, 2, 3 ]); let mut y = x.clone(); // duplicate the first column as the second column y.insert_column_with(1, x.column_iter(0)); assert_eq!((3, 2), y.size()); let mut values = y.column_major_iter(); assert_eq!(Some(1), values.next()); assert_eq!(Some(2), values.next()); assert_eq!(Some(3), values.next()); assert_eq!(Some(1), values.next()); assert_eq!(Some(2), values.next()); assert_eq!(Some(3), values.next()); assert_eq!(None, values.next());
pub fn retain(&self, slice: Slice2D) -> Matrix<T>
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pub fn retain(&self, slice: Slice2D) -> Matrix<T>
[src]Makes a copy of this matrix shrunk down in size according to the slice. See retain_mut.
impl<T: Numeric> Matrix<T> where
&'a T: NumericRef<T>,
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impl<T: Numeric> Matrix<T> where
&'a T: NumericRef<T>,
[src]Methods for matrices with numerical types, such as f32 or f64.
Note that unsigned integers are not Numeric because they do not implement Neg. You must first wrap unsigned integers via Wrapping.
While these methods will all be defined on signed integer types as well, such as i16 or i32, in many cases integers cannot be used sensibly in these computations. If you have a matrix of type i8 for example, you should consider mapping it into a floating type before doing heavy linear algebra maths on it.
Determinants can be computed without loss of precision using sufficiently large signed integers because the only operations performed on the elements are addition, subtraction and mulitplication. However the inverse of a matrix such as
[ 4, 7 2, 8 ]
is
[ 0.6, -0.7, -0.2, 0.4 ]
which requires a type that supports decimals to accurately represent.
Mapping matrix type example:
use easy_ml::matrices::Matrix; use std::num::Wrapping; let matrix: Matrix<u8> = Matrix::from(vec![ vec![ 2, 3 ], vec![ 6, 0 ] ]); // determinant is not defined on this matrix because u8 is not Numeric // println!("{:?}", matrix.determinant()); // won't compile // however Wrapping<u8> is numeric let matrix = matrix.map(|element| Wrapping(element)); println!("{:?}", matrix.determinant()); // -> 238 (overflow) println!("{:?}", matrix.map(|element| element.0 as i16).determinant()); // -> -18 println!("{:?}", matrix.map(|element| element.0 as f32).determinant()); // -> -18.0
pub fn determinant(&self) -> Option<T>
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pub fn determinant(&self) -> Option<T>
[src]Returns the determinant of this square matrix, or None if the matrix
does not have a determinant. See linear_algebra
pub fn inverse(&self) -> Option<Matrix<T>> where
T: Add<Output = T> + Mul<Output = T> + Sub<Output = T> + Div<Output = T>,
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pub fn inverse(&self) -> Option<Matrix<T>> where
T: Add<Output = T> + Mul<Output = T> + Sub<Output = T> + Div<Output = T>,
[src]Computes the inverse of a matrix provided that it exists. To have an inverse a
matrix must be square (same number of rows and columns) and it must also have a
non zero determinant. See linear_algebra
pub fn covariance_column_features(&self) -> Matrix<T>
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pub fn covariance_column_features(&self) -> Matrix<T>
[src]Computes the covariance matrix for this NxM feature matrix, in which
each N’th row has M features to find the covariance and variance of. See
linear_algebra
pub fn covariance_row_features(&self) -> Matrix<T>
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pub fn covariance_row_features(&self) -> Matrix<T>
[src]Computes the covariance matrix for this NxM feature matrix, in which
each M’th column has N features to find the covariance and variance of. See
linear_algebra
impl<T: Numeric + Real> Matrix<T> where
&'a T: NumericRef<T> + RealRef<T>,
[src]
impl<T: Numeric + Real> Matrix<T> where
&'a T: NumericRef<T> + RealRef<T>,
[src]Methods for matrices with numerical real valued types, such as f32 or f64.
This excludes signed and unsigned integers as they do not support decimal precision and hence can’t be used for operations like square roots.
Third party fixed precision and infinite precision decimal types should be able to implement all of the methods for Real and then utilise these functions.
pub fn euclidean_length(&self) -> T
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pub fn euclidean_length(&self) -> T
[src]Computes the L2 norm of this row or column vector, also referred to as the length or magnitude, and written as ||x||, or sometimes |x|.
||a|| = sqrt(a12 + a22 + a32…) = sqrt(aT * a)
This is a shorthand for (x.transpose() * x).scalar().sqrt()
for
column vectors and (x * x.transpose()).scalar().sqrt()
for row vectors, ie
the square root of the dot product of a vector with itself.
The euclidean length can be used to compute a unit vector, that is, a vector with length of 1. This should not be confused with a unit matrix, which is another name for an identity matrix.
use easy_ml::matrices::Matrix; let a = Matrix::column(vec![ 1.0, 2.0, 3.0 ]); let length = a.euclidean_length(); // (1^2 + 2^2 + 3^2)^0.5 let unit = a / length; assert_eq!(unit.euclidean_length(), 1.0);
Panics
If the matrix is not a vector, ie if it has more than one row and more than one column.
impl<T: Numeric> Matrix<T>
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impl<T: Numeric> Matrix<T>
[src]pub fn diagonal(value: T, size: (Row, Column)) -> Matrix<T>
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pub fn diagonal(value: T, size: (Row, Column)) -> Matrix<T>
[src]Creates a diagonal matrix of the provided size with the diagonal elements set to the provided value and all other elements in the matrix set to 0. A diagonal matrix is always square.
The size is still taken as a tuple to facilitate creating a diagonal matrix from the dimensionality of an existing one. If the provided value is 1 then this will create an identity matrix.
A 3 x 3 identity matrix:
[ 1, 0, 0 0, 1, 0 0, 0, 1 ]
Panics
If the provided size is not square.
Trait Implementations
impl<T: Numeric> Add<&'_ Matrix<T>> for &Matrix<T> where
&'a T: NumericRef<T>,
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impl<T: Numeric> Add<&'_ Matrix<T>> for &Matrix<T> where
&'a T: NumericRef<T>,
[src]Elementwise addition for two referenced matrices.
impl<T: Numeric> Add<&'_ Matrix<T>> for Matrix<T> where
&'a T: NumericRef<T>,
[src]
impl<T: Numeric> Add<&'_ Matrix<T>> for Matrix<T> where
&'a T: NumericRef<T>,
[src]Elementwise addition for two matrices with one referenced.
impl<T: Numeric> Add<&'_ T> for &Matrix<T> where
&'a T: NumericRef<T>,
[src]
impl<T: Numeric> Add<&'_ T> for &Matrix<T> where
&'a T: NumericRef<T>,
[src]Operation for a matrix and scalar by reference. The scalar is applied to all elements, this is a shorthand for map().
impl<T: Numeric> Add<&'_ T> for Matrix<T> where
&'a T: NumericRef<T>,
[src]
impl<T: Numeric> Add<&'_ T> for Matrix<T> where
&'a T: NumericRef<T>,
[src]Operation for a matrix by value and scalar by reference. The scalar is applied to all elements, this is a shorthand for map().
impl<T: Numeric> Add<Matrix<T>> for Matrix<T> where
&'a T: NumericRef<T>,
[src]
impl<T: Numeric> Add<Matrix<T>> for Matrix<T> where
&'a T: NumericRef<T>,
[src]Elementwise addition for two matrices.
impl<T: Numeric> Add<Matrix<T>> for &Matrix<T> where
&'a T: NumericRef<T>,
[src]
impl<T: Numeric> Add<Matrix<T>> for &Matrix<T> where
&'a T: NumericRef<T>,
[src]Elementwise addition for two matrices with one referenced.
impl<T: Numeric> Add<T> for &Matrix<T> where
&'a T: NumericRef<T>,
[src]
impl<T: Numeric> Add<T> for &Matrix<T> where
&'a T: NumericRef<T>,
[src]Operation for a matrix by reference and scalar by value. The scalar is applied to all elements, this is a shorthand for map().
impl<T: Numeric> Add<T> for Matrix<T> where
&'a T: NumericRef<T>,
[src]
impl<T: Numeric> Add<T> for Matrix<T> where
&'a T: NumericRef<T>,
[src]Operation for a matrix and scalar by value. The scalar is applied to all elements, this is a shorthand for map().
impl<T: Display + Clone> Display for Matrix<T>
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impl<T: Display + Clone> Display for Matrix<T>
[src]Any matrix of a Displayable + Cloneable type implements Display
impl<T: Numeric> Div<&'_ T> for &Matrix<T> where
&'a T: NumericRef<T>,
[src]
impl<T: Numeric> Div<&'_ T> for &Matrix<T> where
&'a T: NumericRef<T>,
[src]Operation for a matrix and scalar by reference. The scalar is applied to all elements, this is a shorthand for map().
impl<T: Numeric> Div<&'_ T> for Matrix<T> where
&'a T: NumericRef<T>,
[src]
impl<T: Numeric> Div<&'_ T> for Matrix<T> where
&'a T: NumericRef<T>,
[src]Operation for a matrix by value and scalar by reference. The scalar is applied to all elements, this is a shorthand for map().
impl<T: Numeric> Div<T> for &Matrix<T> where
&'a T: NumericRef<T>,
[src]
impl<T: Numeric> Div<T> for &Matrix<T> where
&'a T: NumericRef<T>,
[src]Operation for a matrix by reference and scalar by value. The scalar is applied to all elements, this is a shorthand for map().
impl<T: Numeric> Div<T> for Matrix<T> where
&'a T: NumericRef<T>,
[src]
impl<T: Numeric> Div<T> for Matrix<T> where
&'a T: NumericRef<T>,
[src]Operation for a matrix and scalar by value. The scalar is applied to all elements, this is a shorthand for map().
impl<T: Numeric> Mul<&'_ Matrix<T>> for &Matrix<T> where
&'a T: NumericRef<T>,
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impl<T: Numeric> Mul<&'_ Matrix<T>> for &Matrix<T> where
&'a T: NumericRef<T>,
[src]Matrix multiplication for two referenced matrices.
This is matrix multiplication such that a matrix of dimensionality (LxM) multiplied with a matrix of dimensionality (MxN) yields a new matrix of dimensionality (LxN) with each element corresponding to the sum of products of the ith row in the first matrix and the jth column in the second matrix.
Matrices of the wrong sizes will result in a panic. No broadcasting is performed, ie you cannot multiply a (NxM) matrix by a (Nx1) column vector, you must transpose one of the arguments so that the operation is valid.
impl<T: Numeric> Mul<&'_ Matrix<T>> for Matrix<T> where
&'a T: NumericRef<T>,
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impl<T: Numeric> Mul<&'_ Matrix<T>> for Matrix<T> where
&'a T: NumericRef<T>,
[src]Matrix multiplication for two matrices with one referenced.
impl<T: Numeric> Mul<&'_ T> for &Matrix<T> where
&'a T: NumericRef<T>,
[src]
impl<T: Numeric> Mul<&'_ T> for &Matrix<T> where
&'a T: NumericRef<T>,
[src]Operation for a matrix and scalar by reference. The scalar is applied to all elements, this is a shorthand for map().
impl<T: Numeric> Mul<&'_ T> for Matrix<T> where
&'a T: NumericRef<T>,
[src]
impl<T: Numeric> Mul<&'_ T> for Matrix<T> where
&'a T: NumericRef<T>,
[src]Operation for a matrix by value and scalar by reference. The scalar is applied to all elements, this is a shorthand for map().
impl<T: Numeric> Mul<Matrix<T>> for Matrix<T> where
&'a T: NumericRef<T>,
[src]
impl<T: Numeric> Mul<Matrix<T>> for Matrix<T> where
&'a T: NumericRef<T>,
[src]Matrix multiplication for two matrices.
impl<T: Numeric> Mul<Matrix<T>> for &Matrix<T> where
&'a T: NumericRef<T>,
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impl<T: Numeric> Mul<Matrix<T>> for &Matrix<T> where
&'a T: NumericRef<T>,
[src]Matrix multiplication for two matrices with one referenced.
impl<T: Numeric> Mul<T> for &Matrix<T> where
&'a T: NumericRef<T>,
[src]
impl<T: Numeric> Mul<T> for &Matrix<T> where
&'a T: NumericRef<T>,
[src]Operation for a matrix by reference and scalar by value. The scalar is applied to all elements, this is a shorthand for map().
impl<T: Numeric> Mul<T> for Matrix<T> where
&'a T: NumericRef<T>,
[src]
impl<T: Numeric> Mul<T> for Matrix<T> where
&'a T: NumericRef<T>,
[src]Operation for a matrix and scalar by value. The scalar is applied to all elements, this is a shorthand for map().
impl<T: Numeric> Neg for &Matrix<T> where
&'a T: NumericRef<T>,
[src]
impl<T: Numeric> Neg for &Matrix<T> where
&'a T: NumericRef<T>,
[src]Elementwise negation for a referenced matrix.
impl<T: Numeric> Neg for Matrix<T> where
&'a T: NumericRef<T>,
[src]
impl<T: Numeric> Neg for Matrix<T> where
&'a T: NumericRef<T>,
[src]Elementwise negation for a matrix.
impl<T: PartialEq> PartialEq<Matrix<T>> for Matrix<T>
[src]
impl<T: PartialEq> PartialEq<Matrix<T>> for Matrix<T>
[src]PartialEq is implemented as two matrices are equal if and only if all their elements are equal and they have the same size.
impl<T: Numeric> Sub<&'_ Matrix<T>> for &Matrix<T> where
&'a T: NumericRef<T>,
[src]
impl<T: Numeric> Sub<&'_ Matrix<T>> for &Matrix<T> where
&'a T: NumericRef<T>,
[src]Elementwise subtraction for two referenced matrices.
impl<T: Numeric> Sub<&'_ Matrix<T>> for Matrix<T> where
&'a T: NumericRef<T>,
[src]
impl<T: Numeric> Sub<&'_ Matrix<T>> for Matrix<T> where
&'a T: NumericRef<T>,
[src]Elementwise subtraction for two matrices with one referenced.
impl<T: Numeric> Sub<&'_ T> for &Matrix<T> where
&'a T: NumericRef<T>,
[src]
impl<T: Numeric> Sub<&'_ T> for &Matrix<T> where
&'a T: NumericRef<T>,
[src]Operation for a matrix and scalar by reference. The scalar is applied to all elements, this is a shorthand for map().
impl<T: Numeric> Sub<&'_ T> for Matrix<T> where
&'a T: NumericRef<T>,
[src]
impl<T: Numeric> Sub<&'_ T> for Matrix<T> where
&'a T: NumericRef<T>,
[src]Operation for a matrix by value and scalar by reference. The scalar is applied to all elements, this is a shorthand for map().
impl<T: Numeric> Sub<Matrix<T>> for Matrix<T> where
&'a T: NumericRef<T>,
[src]
impl<T: Numeric> Sub<Matrix<T>> for Matrix<T> where
&'a T: NumericRef<T>,
[src]Elementwise subtraction for two matrices.
impl<T: Numeric> Sub<Matrix<T>> for &Matrix<T> where
&'a T: NumericRef<T>,
[src]
impl<T: Numeric> Sub<Matrix<T>> for &Matrix<T> where
&'a T: NumericRef<T>,
[src]Elementwise subtraction for two matrices with one referenced.
impl<T: Numeric> Sub<T> for &Matrix<T> where
&'a T: NumericRef<T>,
[src]
impl<T: Numeric> Sub<T> for &Matrix<T> where
&'a T: NumericRef<T>,
[src]Operation for a matrix by reference and scalar by value. The scalar is applied to all elements, this is a shorthand for map().
Auto Trait Implementations
impl<T> RefUnwindSafe for Matrix<T> where
T: RefUnwindSafe,
T: RefUnwindSafe,
impl<T> Send for Matrix<T> where
T: Send,
T: Send,
impl<T> Sync for Matrix<T> where
T: Sync,
T: Sync,
impl<T> Unpin for Matrix<T> where
T: Unpin,
T: Unpin,
impl<T> UnwindSafe for Matrix<T> where
T: UnwindSafe,
T: UnwindSafe,
Blanket Implementations
impl<T> BorrowMut<T> for T where
T: ?Sized,
[src]
impl<T> BorrowMut<T> for T where
T: ?Sized,
[src]pub fn borrow_mut(&mut self) -> &mut T
[src]
pub fn borrow_mut(&mut self) -> &mut T
[src]Mutably borrows from an owned value. Read more
impl<T> ToOwned for T where
T: Clone,
[src]
impl<T> ToOwned for T where
T: Clone,
[src]type Owned = T
type Owned = T
The resulting type after obtaining ownership.
pub fn to_owned(&self) -> T
[src]
pub fn to_owned(&self) -> T
[src]Creates owned data from borrowed data, usually by cloning. Read more
pub fn clone_into(&self, target: &mut T)
[src]
pub fn clone_into(&self, target: &mut T)
[src]🔬 This is a nightly-only experimental API. (toowned_clone_into
)
recently added
Uses borrowed data to replace owned data, usually by cloning. Read more
impl<T, Rhs, Output> NumericByValue<Rhs, Output> for T where
T: Add<Rhs, Output = Output> + Sub<Rhs, Output = Output> + Mul<Rhs, Output = Output> + Div<Rhs, Output = Output> + Neg<Output = Output>,
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T: Add<Rhs, Output = Output> + Sub<Rhs, Output = Output> + Mul<Rhs, Output = Output> + Div<Rhs, Output = Output> + Neg<Output = Output>,
impl<RefT, T> NumericRef<T> for RefT where
RefT: NumericByValue<T, T> + for<'a> NumericByValue<&'a T, T>,
[src]
RefT: NumericByValue<T, T> + for<'a> NumericByValue<&'a T, T>,