New release 0.1.5

.github/workflows/ci-tsdownsample.yml

@@ -87,7 +87,7 @@ jobs:
   # Perhaps smth more in line with this https://github.com/messense/crfs-rs/blob/main/.github/workflows/Python.yml
     name: build on ${{ matrix.os }} (${{ matrix.target }} - ${{ matrix.manylinux || 'auto' }})
     # only run on push to main and on release
-    if: "success() && (startsWith(github.ref, 'refs/tags/') || github.ref == 'refs/heads/main' || contains(github.event.pull_request.labels.*.name, 'Full Build'))"
+    # if: "success() && (startsWith(github.ref, 'refs/tags/') || github.ref == 'refs/heads/main' || contains(github.event.pull_request.labels.*.name, 'Full Build'))"
     strategy:
       fail-fast: false
       matrix:
@@ -166,7 +166,7 @@ jobs:
 
   Release:
     needs: [Lint_and_Check, Test, Build]
-    if: "success() && startsWith(github.ref, 'refs/tags/')"
+    # if: "success() && startsWith(github.ref, 'refs/tags/')"
     runs-on: ubuntu-latest
 
     steps:

Cargo.toml

@@ -9,10 +9,10 @@ license = "MIT"
 
 [dependencies]
 downsample_rs = { path = "downsample_rs", features = ["half"]}
-pyo3 = { version = "0.26", features = ["extension-module"] }
+pyo3 = { version = "0.26", features = ["extension-module", "generate-import-lib"] }
 numpy = { version = "0.26", features = ["half"] }
-half = { version = "2.3.1", default-features = false }
-paste = { version = "1.0.14", default-features = false }
+half = { version = "2.6", default-features = false }
+paste = { version = "1.0", default-features = false }
 
 [lib]
 name = "tsdownsample"

downsample_rs/Cargo.toml

@@ -8,16 +8,16 @@ license = "MIT"
 
 [dependencies]
 # TODO: perhaps use polars?
-argminmax = { version = "0.6.1", features = ["half"] }
-half = { version = "2.3.1", default-features = false , features=["num-traits"], optional = true}
-num-traits = { version = "0.2.17", default-features = false }
+argminmax = { version = "0.6", features = ["half"] }
+half = { version = "2.7", default-features = false , features=["num-traits"], optional = true}
+num-traits = { version = "0.2", default-features = false }
 once_cell = "1"
-rayon = { version = "1.8.0", default-features = false }
+rayon = { version = "1", default-features = false }
 
 [dev-dependencies]
-rstest = { version = "0.18.2", default-features = false }
-rstest_reuse = { version = "0.6", default-features = false }
-criterion = "0.5.1"
+rstest = { version = "0.26", default-features = false }
+rstest_reuse = { version = "0.7", default-features = false }
+criterion = "0.7"
 dev_utils = { path = "dev_utils" }
 
 [[bench]]

downsample_rs/dev_utils/Cargo.toml

@@ -6,5 +6,6 @@ edition = "2021"
 description = "Shared utilities for development (tests & benchmarks)"
 
 [dependencies]
-rand = { version = "0.7.2", default-features = false }
-rand_distr = { version = "0.2.2", default-features = false }
+num-traits = { version = "0.2", default-features = false }
+half = { version = "2.7", default-features = false, features = ["num-traits", "rand_distr"] }
+rand = { version = "0.9", default-features = false }

downsample_rs/dev_utils/src/utils.rs

@@ -1,17 +1,33 @@
 use std::ops::{Add, Sub};
 
-use rand::{thread_rng, Rng};
-use rand_distr::Uniform;
+use num_traits::{NumCast, ToPrimitive};
+use rand::distr::uniform::Error as UniformError;
+use rand::distr::Uniform;
+use rand::{rng, Rng};
 
 // random array that samples between min and max of T
 pub fn get_random_array<T>(n: usize, min_value: T, max_value: T) -> Vec<T>
 where
-    T: Copy + rand::distributions::uniform::SampleUniform,
+    T: Copy + rand::distr::uniform::SampleUniform + ToPrimitive + NumCast,
 {
-    let rng = thread_rng();
-    let uni = Uniform::new_inclusive(min_value, max_value);
-    let arr: Vec<T> = rng.sample_iter(uni).take(n).collect();
-    arr
+    let rng = rng();
+    match Uniform::new_inclusive(min_value, max_value) {
+        Ok(uni) => rng.sample_iter(uni).take(n).collect(),
+        Err(UniformError::NonFinite) => {
+            let min = min_value
+                .to_f64()
+                .expect("failed to convert lower bound to f64");
+            let max = max_value
+                .to_f64()
+                .expect("failed to convert upper bound to f64");
+            let uni = Uniform::new_inclusive(min, max).unwrap();
+            rng.sample_iter(uni)
+                .take(n)
+                .map(|v| NumCast::from(v).expect("failed to convert sample"))
+                .collect()
+        }
+        Err(err) => panic!("invalid range for random array: {err:?}"),
+    }
 }
 
 // worst case array that alternates between increasing max and decreasing min values

pyproject.toml

@@ -5,7 +5,7 @@ build-backend = "maturin"
 [project]
 name = "tsdownsample"
 description = "Time series downsampling in rust"
-version = "0.1.4.1"
+version = "0.1.5"
 requires-python = ">=3.8"
 dependencies = ["numpy"]
 authors = [{name = "Jeroen Van Der Donckt"}]

tsdownsample/__init__.py

@@ -11,7 +11,7 @@
     NaNMinMaxLTTBDownsampler,
 )
 
-__version__ = "0.1.4.1"
+__version__ = "0.1.5"
 __author__ = "Jeroen Van Der Donckt"
 
 __all__ = [