Binomsplit in 2 and 3 dimensions

.gitignore

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+/target
+Cargo.lock

Cargo.toml

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+[package]
+name = "rustfrc"
+version = "0.1.0"
+edition = "2018"
+
+[lib]
+name = "rustfrc"
+crate-type = ["cdylib"]
+
+[dependencies]
+numpy = "0.14"
+ndarray = { version = "0.15", features = ["rayon"] }
+ndarray-rand = "0.14"
+rand = "0.8"
+
+[dependencies.pyo3]
+version = "0.14"
+features = ["extension-module"]

pyproject.toml

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+[tool.poetry]
+name = "rustfrc"
+version = "0.1.0"
+description = "Package with some basic optimized Rust functions for use with FRC resolution determination for microscopy. TU Delft BEP 2021-2022."
+authors = ["Tip ten Brink <[email protected]>"]
+
+[tool.poetry.dependencies]
+python = "^3.7"
+numpy = "^1.18"
+
+[tool.poetry.dev-dependencies]
+maturin = "^0.11.3"
+diplib = "3.0.0"
+
+[build-system]
+requires = ["poetry-core>=1.0.0"]
+build-backend ="maturin"

src/lib.rs

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+use ndarray_rand::rand_distr::Binomial;
+use ndarray_rand::rand::prelude::Distribution;
+use ndarray_rand::rand::thread_rng;
+use numpy::{IntoPyArray, PyArray3, PyReadonlyArray3, PyReadonlyArray2, PyArray2};
+use pyo3::prelude::{pymodule, PyModule, PyResult, Python};
+
+#[pymodule]
+fn rustfrc(_py: Python<'_>, m: &PyModule) -> PyResult<()> {
+    #[pyfn(m)]
+    fn binom_split_3d<'py>(py: Python<'py>, x: PyReadonlyArray3<'py, i32>) -> PyResult<&'py PyArray3<i32>> {
+        let mut x = x.as_array().to_owned();
+        x.par_mapv_inplace(|i| {
+            let mut rng = thread_rng();
+            Binomial::new(i as u64, 0.5).unwrap().sample(&mut rng) as i32
+        });
+        Ok(x.into_pyarray(py))
+    }
+
+    #[pyfn(m)]
+    fn binom_split_2d<'py>(py: Python<'py>, x: PyReadonlyArray2<'py, i32>) -> PyResult<&'py PyArray2<i32>> {
+        let mut x = x.as_array().to_owned();
+        x.par_mapv_inplace(|i| {
+            let mut rng = thread_rng();
+            Binomial::new(i as u64, 0.5).unwrap().sample(&mut rng) as i32
+        });
+        Ok(x.into_pyarray(py))
+    }
+    Ok(())
+}
+
+

test.py

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+import rustfrc as r
+import diplib as dip
+import numpy as np
+import time
+
+rng = np.random.default_rng()
+img = dip.ImageRead('Benton')(0)[:388, :388]
+x = np.array(img)
+#x3d = np.repeat(x[:, :, np.newaxis], 1000, axis=2)
+half_x = np.rint(x/2).astype(int)
+# half_x = np.rint(x/2).astype(int)
+# print(half_x)
+start = time.time_ns()
+#a = rng.binomial(half_x, 0.5)
+a = r.binom_split_2d(half_x)
+b = half_x - a
+# for i in range(100):
+#     a = rng.binomial(half_x, 0.5)
+#     b = half_x - a
+end_time = time.time_ns()
+print(str(float(end_time - start)/1e9) + " s")
+
+#
+