Update to ndarray 1.15

Author: xd009642

Cargo.toml

@@ -11,16 +11,16 @@ categories = ["science", "science::robotics", "multimedia", "multimedia::images"
 edition = "2018"
 
 [dependencies]
-ndarray = { version = "0.13", default-features = false }
-ndarray-stats = { version = "0.3", default-features = false }
-ndarray-linalg = { version = "0.12", default-features = false }
-noisy_float = { version = "0.1", default-features = false }
+ndarray = { version = "0.15", default-features = false }
+ndarray-stats = { version = "0.5", default-features = false }
+ndarray-linalg = { version = "0.13", default-features = false }
+noisy_float = { version = "0.2", default-features = false }
 num-traits = { version = "0.2", default-features = false }
 
 [dev-dependencies]
-ndarray-rand = "0.11.0"
+ndarray-rand = "0.14.0"
 rand = "0.7"
 assert_approx_eq = "1.1.0"
-noisy_float = "0.1.11"
+noisy_float = "0.2"
 png = "0.16"
-ndarray-linalg = { version = "0.12", features = ["intel-mkl"] }
+ndarray-linalg = { version = "0.13", features = ["intel-mkl"] }

src/core/colour_models.rs

@@ -199,7 +199,7 @@ where
         let mut res = Array3::<_>::zeros((image.rows(), image.cols(), HSV::channels()));
         let window = image.data.windows((1, 1, image.channels()));
 
-        Zip::indexed(window).apply(|(i, j, _), pix| {
+        Zip::indexed(window).for_each(|(i, j, _), pix| {
             let red = pix[[0, 0, 0]];
             let green = pix[[0, 0, 1]];
             let blue = pix[[0, 0, 2]];
@@ -228,7 +228,7 @@ where
         let mut res = Array3::<T>::zeros((image.rows(), image.cols(), RGB::channels()));
         let window = image.data.windows((1, 1, image.channels()));
 
-        Zip::indexed(window).apply(|(i, j, _), pix| {
+        Zip::indexed(window).for_each(|(i, j, _), pix| {
             let h = pix[[0, 0, 0]];
             let s = pix[[0, 0, 1]];
             let v = pix[[0, 0, 2]];
@@ -257,7 +257,7 @@ where
         let mut res = Array3::<T>::zeros((image.rows(), image.cols(), Gray::channels()));
         let window = image.data.windows((1, 1, image.channels()));
 
-        Zip::indexed(window).apply(|(i, j, _), pix| {
+        Zip::indexed(window).for_each(|(i, j, _), pix| {
             let r = normalise_pixel_value(pix[[0, 0, 0]]);
             let g = normalise_pixel_value(pix[[0, 0, 1]]);
             let b = normalise_pixel_value(pix[[0, 0, 2]]);
@@ -288,7 +288,7 @@ where
         let mut res = Array3::<T>::zeros((image.rows(), image.cols(), RGB::channels()));
         let window = image.data.windows((1, 1, image.channels()));
 
-        Zip::indexed(window).apply(|(i, j, _), pix| {
+        Zip::indexed(window).for_each(|(i, j, _), pix| {
             let gray = pix[[0, 0, 0]];
 
             res.slice_mut(s![i, j, ..])
@@ -321,7 +321,7 @@ where
             [0.0139322, 0.0971045, 0.7141733],
         ]);
 
-        Zip::indexed(window).apply(|(i, j, _), pix| {
+        Zip::indexed(window).for_each(|(i, j, _), pix| {
             let pixel = pix
                 .index_axis(Axis(0), 0)
                 .index_axis(Axis(0), 0)
@@ -360,7 +360,7 @@ where
             [0.0719453, -0.2289914, 1.4052427],
         ]);
 
-        Zip::indexed(window).apply(|(i, j, _), pix| {
+        Zip::indexed(window).for_each(|(i, j, _), pix| {
             let pixel = pix
                 .index_axis(Axis(0), 0)
                 .index_axis(Axis(0), 0)

src/morphology/mod.rs

@@ -32,7 +32,7 @@ where
         let (ro, co) = kernel_centre(sh[0], sh[1]);
         let mut result = Self::Output::from_elem(self.dim(), false);
         if self.shape()[0] >= sh[0] && self.shape()[1] >= sh[1] {
-            Zip::indexed(self.slice(s![.., .., 0]).windows(kernel.dim())).apply(
+            Zip::indexed(self.slice(s![.., .., 0]).windows(kernel.dim())).for_each(
                 |(i, j), window| {
                     result[[i + ro, j + co, 0]] = (&kernel & &window) == kernel;
                 },
@@ -50,7 +50,7 @@ where
         let (ro, co) = kernel_centre(sh[0], sh[1]);
         let mut result = Self::Output::from_elem(self.dim(), false);
         if self.shape()[0] >= sh[0] && self.shape()[1] >= sh[1] {
-            Zip::indexed(self.slice(s![.., .., 0]).windows(kernel.dim())).apply(
+            Zip::indexed(self.slice(s![.., .., 0]).windows(kernel.dim())).for_each(
                 |(i, j), window| {
                     result[[i + ro, j + co, 0]] = (&kernel & &window).iter().any(|x| *x);
                 },

src/processing/conv.rs

@@ -120,7 +120,7 @@ where
             if shape.0 > 0 && shape.1 > 0 {
                 let mut result = unsafe { Self::Output::uninitialized(shape) };
 
-                Zip::indexed(self.windows(kernel.dim())).apply(|(i, j, _), window| {
+                Zip::indexed(self.windows(kernel.dim())).for_each(|(i, j, _), window| {
                     let mut temp;
                     for channel in 0..k_s[2] {
                         temp = T::zero();

src/processing/filter.rs

@@ -35,7 +35,7 @@ where
         let c_offset = shape[1] / 2;
         let region = (shape[0], shape[1], 1);
         let mut result = Array3::<T>::zeros(self.dim());
-        Zip::indexed(self.windows(region)).apply(|(i, j, k), window| {
+        Zip::indexed(self.windows(region)).for_each(|(i, j, k), window| {
             let mut flat_window = Array::from_iter(window.iter()).mapv(|x| *x);
             if let Ok(v) = flat_window.quantile_mut(n64(0.5f64), &Linear {}) {
                 result

src/transform/mod.rs

@@ -1,7 +1,7 @@
 use crate::core::{ColourModel, Image, ImageBase};
 use crate::transform::affine::translation;
 use ndarray::{array, prelude::*, s, Data};
-use ndarray_linalg::solve::Inverse;
+use ndarray_linalg::*;
 use num_traits::{Num, NumAssignOps};
 use std::cmp::{max, min};