todo

README.md

@@ -23,7 +23,12 @@ rustDTW was designed for usage with timeseries data from functional brain region
 import numpy as np
 import rust_dtw
 
-rust_dtw.dtw(s=np.array([0., 1., 2.]), t=np.array([3., 4., 5.]), window=50, distance_mode="euclidean")
+rust_dtw.dtw(
+  s=np.array([0., 1., 2.]), 
+  t=np.array([3., 4., 5.]), 
+  window=50, 
+  distance_mode="euclidean"
+  )
 >>> 5.0990195
 ```
 

src/lib.rs

@@ -1,13 +1,18 @@
+use indicatif::ParallelProgressIterator;
 use ndarray::parallel::prelude::*;
 use ndarray::prelude::*;
 use std::error::Error;
-use indicatif::ParallelProgressIterator;
 
 use numpy::{
     IntoPyArray, PyArray1, PyArrayDyn, PyReadonlyArray1, PyReadonlyArray2, PyReadonlyArray3,
 };
 use pyo3::prelude::{pymodule, PyModule, PyResult, Python};
 
+//TODO:
+//1. Work out how to cargo doc to documentation
+//2. Define less neuro specific method namings
+//3. Finalize tests
+
 #[pymodule]
 fn rust_dtw(_py: Python<'_>, m: &PyModule) -> PyResult<()> {
     #[pyfn(m, "dtw")]