Implements some manual checks for distributions

.cargo/config.toml

@@ -0,0 +1,2 @@
+[target.'cfg(all(target_os = "macos"))']
+rustflags = ["-C", "link-args=-L/usr/local/opt/openblas/lib -lopenblas"]

Cargo.toml

@@ -1,5 +1,5 @@
 [package]
-name = "rust_qcd"
+name = "rs-lattice"
 version = "0.1.0"
 edition = "2018"
 

src/bin/test_rand.rs

@@ -0,0 +1,22 @@
+use lqft::{sample_su2_theta, ColorMat, SampleHaar, IntoBytes};
+use std::fs::File;
+use std::io::Write;
+
+fn main() -> Result<(), std::io::Error> {
+  {
+    let beta = 1.0;
+    let mut file = File::create("su2_theta.dat")?;
+    for _ in 0..10000 {
+      let th: f64 = sample_su2_theta(beta);
+      file.write_all(&th.to_le_bytes())?;
+    }
+  }
+  {
+    let mut file = File::create("u2_haar.dat")?;
+    for _ in 0..10000 {
+      let u = ColorMat::<2>::sample_haar();
+      file.write_all(&u.into_bytes())?;
+    }
+  }
+  Ok(())
+}

src/lib/color_matrix.rs

@@ -1,12 +1,13 @@
 use crate::math::{c64, CMat, CVec};
 use crate::rand_dist::{SampleHaar};
+use crate::{IntoBytes};
 
 use std::ops::{Add, Index, IndexMut};
 
 // Color matrices
 #[derive(Clone)]
 pub struct ColorMat<const N: usize> {
-  data: CMat<N>
+  pub data: CMat<N>
 }
 
 impl<const N: usize> ColorMat<N> {
@@ -23,6 +24,19 @@ impl<const N: usize> ColorMat<N> {
   }
 }
 
+impl<const N: usize> IntoBytes for ColorMat<N> {
+  fn into_bytes(&self) -> Vec<u8> {
+    let mut bs: Vec<u8> = vec!();
+    for i in 0..N {
+      for j in 0..N {
+        bs.extend_from_slice(&self.data[i][j].re.to_le_bytes());
+        bs.extend_from_slice(&self.data[i][j].im.to_le_bytes());
+      }
+    }
+    bs
+  }
+}
+
 impl<const N: usize> Index<(usize, usize)> for ColorMat<N> {
   type Output = c64;
 

src/lib/lib.rs

@@ -14,6 +14,10 @@ use ndarray::Array4;
 use std::convert::TryInto;
 use std::ops::Index;
 
+pub trait IntoBytes {
+  fn into_bytes(&self) -> Vec<u8>;
+}
+
 pub trait LatticeObject<const ND: usize> {
   fn latt_shape(&self) -> [usize; ND];
   fn nd(&self) -> usize {

src/lib/rand_dist.rs

@@ -9,14 +9,13 @@ use ndarray_linalg::qr::QR;
 // on a wrapped Cauchy base distribution.
 pub fn sample_von_mises(beta: f64) -> f64 {
   let mut rng = thread_rng();
-  let u1: f64 = rng.gen();
-  let u2: f64 = rng.gen();
-  let u3: f64 = rng.gen();
-
   let tau = 1.0 + (1.0 + 4.0 * beta * beta).sqrt();
   let rho = (tau - (2.0 * tau).sqrt()) / (2.0 * beta);
 
   loop {
+    let u1: f64 = rng.gen();
+    let u2: f64 = rng.gen();
+    let u3: f64 = rng.gen();
     let r = (1.0 + rho * rho) / (2.0 * rho);
     let z = (PI * u1).cos();
     let f = (1.0 + r * z) / (r + z);
@@ -78,4 +77,4 @@ macro_rules! impl_sample_haar {
   };
 }
 impl_sample_haar!(2);
-impl_sample_haar!(3);
+impl_sample_haar!(3);