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Merge branch 'development' into ridge

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This commit is contained in:
VolodymyrOrlov
2020-11-11 16:12:34 -08:00
committed by GitHub
parent cc26555bfd b86c553bb1
commit 8f72716fe9
59 changed files with 793 additions and 499 deletions
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src/linalg/naive/dense_matrix.rs
+44 -46
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@@ -1,4 +1,3 @@
extern crate num;
use std::fmt;
use std::fmt::Debug;
use std::marker::PhantomData;
@@ -31,8 +30,7 @@ impl<T: RealNumber> BaseVector<T> for Vec<T> {
}
fn to_vec(&self) -> Vec<T> {
let v = self.clone();
v
self.clone()
}
fn zeros(len: usize) -> Self {
@@ -54,7 +52,7 @@ impl<T: RealNumber> BaseVector<T> for Vec<T> {
let mut result = T::zero();
for i in 0..self.len() {
result = result + self[i] * other[i];
result += self[i] * other[i];
}
result
@@ -64,7 +62,7 @@ impl<T: RealNumber> BaseVector<T> for Vec<T> {
let mut norm = T::zero();
for xi in self.iter() {
norm = norm + *xi * *xi;
norm += *xi * *xi;
}
norm.sqrt()
@@ -83,7 +81,7 @@ impl<T: RealNumber> BaseVector<T> for Vec<T> {
let mut norm = T::zero();
for xi in self.iter() {
norm = norm + xi.abs().powf(p);
norm += xi.abs().powf(p);
}
norm.powf(T::one() / p)
@@ -91,19 +89,19 @@ impl<T: RealNumber> BaseVector<T> for Vec<T> {
}
fn div_element_mut(&mut self, pos: usize, x: T) {
self[pos] = self[pos] / x;
self[pos] /= x;
}
fn mul_element_mut(&mut self, pos: usize, x: T) {
self[pos] = self[pos] * x;
self[pos] *= x;
}
fn add_element_mut(&mut self, pos: usize, x: T) {
self[pos] = self[pos] + x
self[pos] += x
}
fn sub_element_mut(&mut self, pos: usize, x: T) {
self[pos] = self[pos] - x;
self[pos] -= x;
}
fn add_mut(&mut self, other: &Self) -> &Self {
@@ -166,7 +164,7 @@ impl<T: RealNumber> BaseVector<T> for Vec<T> {
fn sum(&self) -> T {
let mut sum = T::zero();
for i in 0..self.len() {
sum = sum + self[i];
sum += self[i];
}
sum
}
@@ -198,7 +196,7 @@ pub struct DenseMatrixIterator<'a, T: RealNumber> {
}
impl<T: RealNumber> fmt::Display for DenseMatrix<T> {
fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
let mut rows: Vec<Vec<f64>> = Vec::new();
for r in 0..self.nrows {
rows.push(
@@ -217,15 +215,15 @@ impl<T: RealNumber> DenseMatrix<T> {
/// `values` should be in column-major order.
pub fn new(nrows: usize, ncols: usize, values: Vec<T>) -> Self {
DenseMatrix {
ncols: ncols,
nrows: nrows,
values: values,
ncols,
nrows,
values,
}
}
/// New instance of `DenseMatrix` from 2d array.
pub fn from_2d_array(values: &[&[T]]) -> Self {
DenseMatrix::from_2d_vec(&values.into_iter().map(|row| Vec::from(*row)).collect())
DenseMatrix::from_2d_vec(&values.iter().map(|row| Vec::from(*row)).collect())
}
/// New instance of `DenseMatrix` from 2d vector.
@@ -236,8 +234,8 @@ impl<T: RealNumber> DenseMatrix<T> {
.unwrap_or_else(|| panic!("Cannot create 2d matrix from an empty vector"))
.len();
let mut m = DenseMatrix {
ncols: ncols,
nrows: nrows,
ncols,
nrows,
values: vec![T::zero(); ncols * nrows],
};
for row in 0..nrows {
@@ -262,8 +260,8 @@ impl<T: RealNumber> DenseMatrix<T> {
/// * `values` - values to initialize the matrix.
pub fn from_vec(nrows: usize, ncols: usize, values: &Vec<T>) -> DenseMatrix<T> {
let mut m = DenseMatrix {
ncols: ncols,
nrows: nrows,
ncols,
nrows,
values: vec![T::zero(); ncols * nrows],
};
for row in 0..nrows {
@@ -286,7 +284,7 @@ impl<T: RealNumber> DenseMatrix<T> {
DenseMatrix {
ncols: values.len(),
nrows: 1,
values: values,
values,
}
}
@@ -302,13 +300,13 @@ impl<T: RealNumber> DenseMatrix<T> {
DenseMatrix {
ncols: 1,
nrows: values.len(),
values: values,
values,
}
}
/// Creates new column vector (_1xN_ matrix) from a vector.
/// * `values` - values to initialize the matrix.
pub fn iter<'a>(&'a self) -> DenseMatrixIterator<'a, T> {
pub fn iter(&self) -> DenseMatrixIterator<'_, T> {
DenseMatrixIterator {
cur_c: 0,
cur_r: 0,
@@ -357,7 +355,7 @@ impl<'de, T: RealNumber + fmt::Debug + Deserialize<'de>> Deserialize<'de> for De
impl<'a, T: RealNumber + fmt::Debug + Deserialize<'a>> Visitor<'a> for DenseMatrixVisitor<T> {
type Value = DenseMatrix<T>;
fn expecting(&self, formatter: &mut fmt::Formatter) -> fmt::Result {
fn expecting(&self, formatter: &mut fmt::Formatter<'_>) -> fmt::Result {
formatter.write_str("struct DenseMatrix")
}
@@ -413,7 +411,7 @@ impl<'de, T: RealNumber + fmt::Debug + Deserialize<'de>> Deserialize<'de> for De
}
}
const FIELDS: &'static [&'static str] = &["nrows", "ncols", "values"];
const FIELDS: &[&str] = &["nrows", "ncols", "values"];
deserializer.deserialize_struct(
"DenseMatrix",
FIELDS,
@@ -565,7 +563,7 @@ impl<T: RealNumber> BaseMatrix<T> for DenseMatrix<T> {
matrix.set(i, i, T::one());
}
return matrix;
matrix
}
fn shape(&self) -> (usize, usize) {
@@ -617,7 +615,7 @@ impl<T: RealNumber> BaseMatrix<T> for DenseMatrix<T> {
for c in 0..other.ncols {
let mut s = T::zero();
for i in 0..inner_d {
s = s + self.get(r, i) * other.get(i, c);
s += self.get(r, i) * other.get(i, c);
}
result.set(r, c, s);
}
@@ -636,7 +634,7 @@ impl<T: RealNumber> BaseMatrix<T> for DenseMatrix<T> {
let mut result = T::zero();
for i in 0..(self.nrows * self.ncols) {
result = result + self.values[i] * other.values[i];
result += self.values[i] * other.values[i];
}
result
@@ -730,19 +728,19 @@ impl<T: RealNumber> BaseMatrix<T> for DenseMatrix<T> {
}
fn div_element_mut(&mut self, row: usize, col: usize, x: T) {
self.values[col * self.nrows + row] = self.values[col * self.nrows + row] / x;
self.values[col * self.nrows + row] /= x;
}
fn mul_element_mut(&mut self, row: usize, col: usize, x: T) {
self.values[col * self.nrows + row] = self.values[col * self.nrows + row] * x;
self.values[col * self.nrows + row] *= x;
}
fn add_element_mut(&mut self, row: usize, col: usize, x: T) {
self.values[col * self.nrows + row] = self.values[col * self.nrows + row] + x
self.values[col * self.nrows + row] += x
}
fn sub_element_mut(&mut self, row: usize, col: usize, x: T) {
self.values[col * self.nrows + row] = self.values[col * self.nrows + row] - x;
self.values[col * self.nrows + row] -= x;
}
fn transpose(&self) -> Self {
@@ -762,9 +760,9 @@ impl<T: RealNumber> BaseMatrix<T> for DenseMatrix<T> {
fn rand(nrows: usize, ncols: usize) -> Self {
let values: Vec<T> = (0..nrows * ncols).map(|_| T::rand()).collect();
DenseMatrix {
ncols: ncols,
nrows: nrows,
values: values,
ncols,
nrows,
values,
}
}
@@ -772,7 +770,7 @@ impl<T: RealNumber> BaseMatrix<T> for DenseMatrix<T> {
let mut norm = T::zero();
for xi in self.values.iter() {
norm = norm + *xi * *xi;
norm += *xi * *xi;
}
norm.sqrt()
@@ -793,7 +791,7 @@ impl<T: RealNumber> BaseMatrix<T> for DenseMatrix<T> {
let mut norm = T::zero();
for xi in self.values.iter() {
norm = norm + xi.abs().powf(p);
norm += xi.abs().powf(p);
}
norm.powf(T::one() / p)
@@ -805,12 +803,12 @@ impl<T: RealNumber> BaseMatrix<T> for DenseMatrix<T> {
for r in 0..self.nrows {
for c in 0..self.ncols {
mean[c] = mean[c] + self.get(r, c);
mean[c] += self.get(r, c);
}
}
for i in 0..mean.len() {
mean[i] = mean[i] / T::from(self.nrows).unwrap();
mean[i] /= T::from(self.nrows).unwrap();
}
mean
@@ -818,28 +816,28 @@ impl<T: RealNumber> BaseMatrix<T> for DenseMatrix<T> {
fn add_scalar_mut(&mut self, scalar: T) -> &Self {
for i in 0..self.values.len() {
self.values[i] = self.values[i] + scalar;
self.values[i] += scalar;
}
self
}
fn sub_scalar_mut(&mut self, scalar: T) -> &Self {
for i in 0..self.values.len() {
self.values[i] = self.values[i] - scalar;
self.values[i] -= scalar;
}
self
}
fn mul_scalar_mut(&mut self, scalar: T) -> &Self {
for i in 0..self.values.len() {
self.values[i] = self.values[i] * scalar;
self.values[i] *= scalar;
}
self
}
fn div_scalar_mut(&mut self, scalar: T) -> &Self {
for i in 0..self.values.len() {
self.values[i] = self.values[i] / scalar;
self.values[i] /= scalar;
}
self
}
@@ -905,7 +903,7 @@ impl<T: RealNumber> BaseMatrix<T> for DenseMatrix<T> {
fn sum(&self) -> T {
let mut sum = T::zero();
for i in 0..self.values.len() {
sum = sum + self.values[i];
sum += self.values[i];
}
sum
}
@@ -937,7 +935,7 @@ impl<T: RealNumber> BaseMatrix<T> for DenseMatrix<T> {
for c in 0..self.ncols {
let p = (self.get(r, c) - max).exp();
self.set(r, c, p);
z = z + p;
z += p;
}
}
for r in 0..self.nrows {
@@ -1061,7 +1059,7 @@ mod tests {
DenseMatrix::new(1, 3, vec![1., 2., 3.])
);
assert_eq!(
DenseMatrix::from_row_vector(vec.clone()).to_row_vector(),
DenseMatrix::from_row_vector(vec).to_row_vector(),
vec![1., 2., 3.]
);
}