fix rand crate renamed modules

Signed-off-by: Andrei Gherghescu <[email protected]>

Author: andrei-ng

docs/book/src/fundamentals/shapes.md

@@ -12,7 +12,7 @@ use plotly::layout::{
     ShapeType,
 };
 use plotly::{Bar, color::NamedColor, Plot, Scatter};
-use rand::thread_rng;
+use rand::rng;
 use rand_distr::{Distribution, Normal};
 ```
 

examples/3d_charts/src/main.rs

@@ -218,7 +218,7 @@ fn colorscale_plot(show: bool) -> Plot {
     let _color: Vec<usize> = (0..z.len()).collect();
     let _color: Vec<u8> = (0..z.len()).map(|x| x as u8).collect();
     let _color: Vec<i16> = {
-        let mut rng = rand::thread_rng();
+        let mut rng = rand::rng();
         (0..z.len()).map(|_| rng.gen_range(0..100)).collect()
     };
 

examples/basic_charts/src/main.rs

@@ -38,7 +38,7 @@ fn simple_scatter_plot(show: bool) -> Plot {
 // ANCHOR: line_and_scatter_plots
 fn line_and_scatter_plots(show: bool) -> Plot {
     let n: usize = 100;
-    let mut rng = rand::thread_rng();
+    let mut rng = rand::rng();
     let random_x: Vec<f64> = Array::linspace(0., 1., n).into_raw_vec_and_offset().0;
     let random_y0: Vec<f64> = Normal::new(5., 1.)
         .unwrap()
@@ -273,7 +273,7 @@ fn colored_and_styled_scatter_plot(show: bool) -> Plot {
 // ANCHOR: large_data_sets
 fn large_data_sets(show: bool) -> Plot {
     let n: usize = 100_000;
-    let mut rng = rand::thread_rng();
+    let mut rng = rand::rng();
     let r: Vec<f64> = Uniform::new(0., 1.).sample_iter(&mut rng).take(n).collect();
     let theta: Vec<f64> = Normal::new(0., 2. * std::f64::consts::PI)
         .unwrap()

examples/customization/src/main.rs

@@ -122,13 +122,13 @@ fn write_html(html_data: &str) -> String {
     use std::{fs::File, io::Write};
 
     use rand::{
-        distributions::{Alphanumeric, DistString},
-        thread_rng,
+        distributions::{Alphanumeric, SampleString},
+        rng,
     };
 
     // Set up the temp file with a unique filename.
     let mut temp = env::temp_dir();
-    let mut plot_name = Alphanumeric.sample_string(&mut thread_rng(), 22);
+    let mut plot_name = Alphanumeric.sample_string(&mut rng(), 22);
     plot_name.push_str(".html");
     plot_name = format!("plotly_{}", plot_name);
     temp.push(plot_name);

examples/shapes/src/main.rs

@@ -9,7 +9,7 @@ use plotly::{
     },
     Bar, Plot, Scatter,
 };
-use rand::thread_rng;
+use rand::rng;
 use rand_distr::{num_traits::Float, Distribution, Normal};
 
 // ANCHOR: filled_area_chart
@@ -433,7 +433,7 @@ fn circles_positioned_relative_to_the_axes(show: bool) -> Plot {
 
 // ANCHOR: highlighting_clusters_of_scatter_points_with_circle_shapes
 fn highlighting_clusters_of_scatter_points_with_circle_shapes(show: bool) -> Plot {
-    let mut rng = thread_rng();
+    let mut rng = rng();
     let x0 = Normal::new(2., 0.45)
         .unwrap()
         .sample_iter(&mut rng)

examples/statistical_charts/src/main.rs

@@ -170,7 +170,7 @@ fn colored_and_styled_error_bars(show: bool) -> Plot {
 // Box Plots
 // ANCHOR: basic_box_plot
 fn basic_box_plot(show: bool) -> Plot {
-    let mut rng = rand::thread_rng();
+    let mut rng = rand::rng();
     let uniform1 = Uniform::new(0.0, 1.0);
     let uniform2 = Uniform::new(1.0, 2.0);
     let n = 50;
@@ -407,7 +407,7 @@ fn grouped_horizontal_box_plot(show: bool) -> Plot {
 fn fully_styled_box_plot(show: bool) -> Plot {
     let rnd_sample = |num, mul| -> Vec<f64> {
         let mut v: Vec<f64> = Vec::with_capacity(num);
-        let mut rng = rand::thread_rng();
+        let mut rng = rand::rng();
         let uniform = Uniform::new(0.0, mul);
         for _ in 0..num {
             v.push(uniform.sample(&mut rng));
@@ -478,7 +478,7 @@ fn fully_styled_box_plot(show: bool) -> Plot {
 
 // Histograms
 fn sample_normal_distribution(n: usize, mean: f64, std_dev: f64) -> Vec<f64> {
-    let mut rng = rand::thread_rng();
+    let mut rng = rand::rng();
     let dist = Normal::new(mean, std_dev).unwrap();
     let mut v = Vec::<f64>::with_capacity(n);
     for _idx in 1..n {
@@ -488,7 +488,7 @@ fn sample_normal_distribution(n: usize, mean: f64, std_dev: f64) -> Vec<f64> {
 }
 
 fn sample_uniform_distribution(n: usize, lb: f64, ub: f64) -> Vec<f64> {
-    let mut rng = rand::thread_rng();
+    let mut rng = rand::rng();
     let dist = Uniform::new(lb, ub);
     let mut v = Vec::<f64>::with_capacity(n);
     for _idx in 1..n {

plotly/src/plot.rs

@@ -3,8 +3,8 @@ use std::{fs::File, io::Write, path::Path};
 use dyn_clone::DynClone;
 use erased_serde::Serialize as ErasedSerialize;
 use rand::{
-    distributions::{Alphanumeric, DistString},
-    thread_rng,
+    distr::{Alphanumeric, SampleString},
+    rng,
 };
 use rinja::Template;
 use serde::Serialize;
@@ -254,7 +254,7 @@ impl Plot {
 
         // Set up the temp file with a unique filename.
         let mut temp = env::temp_dir();
-        let mut plot_name = Alphanumeric.sample_string(&mut thread_rng(), 22);
+        let mut plot_name = Alphanumeric.sample_string(&mut rng(), 22);
         plot_name.push_str(".html");
         plot_name = format!("plotly_{}", plot_name);
         temp.push(plot_name);
@@ -296,7 +296,7 @@ impl Plot {
 
         // Set up the temp file with a unique filename.
         let mut temp = env::temp_dir();
-        let mut plot_name = Alphanumeric.sample_string(&mut thread_rng(), 22);
+        let mut plot_name = Alphanumeric.sample_string(&mut rng(), 22);
         plot_name.push_str(".html");
         plot_name = format!("plotly_{}", plot_name);
         temp.push(plot_name);
@@ -354,13 +354,13 @@ impl Plot {
     pub fn to_inline_html(&self, plot_div_id: Option<&str>) -> String {
         let plot_div_id = match plot_div_id {
             Some(id) => id.to_string(),
-            None => Alphanumeric.sample_string(&mut thread_rng(), 20),
+            None => Alphanumeric.sample_string(&mut rng(), 20),
         };
         self.render_inline(&plot_div_id)
     }
 
     fn to_jupyter_notebook_html(&self) -> String {
-        let plot_div_id = Alphanumeric.sample_string(&mut thread_rng(), 20);
+        let plot_div_id = Alphanumeric.sample_string(&mut rng(), 20);
 
         let tmpl = JupyterNotebookPlotTemplate {
             plot: self,

plotly/src/traces/histogram.rs

@@ -220,7 +220,7 @@ where
     ///
     /// fn ndarray_to_traces() {
     ///     let n: usize = 1_250;
-    ///     let mut rng = rand::thread_rng();
+    ///     let mut rng = rand::rng();
     ///     let t: Array<f64, Ix1> = Array::range(0., 10., 10. / n as f64);
     ///     let mut ys: Array<f64, Ix2> = Array::zeros((n, 4));
     ///     let mut count = 0.;