Numpy v2 compatibility

.pre-commit-config.yaml

@@ -5,7 +5,7 @@ ci:
 
 repos:
 - repo: https://github.com/pre-commit/pre-commit-hooks
-  rev: "v4.5.0"
+  rev: "v4.6.0"
   hooks:
   - id: check-added-large-files
   - id: check-case-conflict
@@ -34,18 +34,18 @@ repos:
   - id: isort
 
 - repo: https://github.com/asottile/pyupgrade
-  rev: "v3.15.2"
+  rev: "v3.16.0"
   hooks:
   - id: pyupgrade
     args: ["--py38-plus"]
 
 - repo: https://github.com/psf/black
-  rev: "24.3.0"
+  rev: "24.4.2"
   hooks:
   - id: black-jupyter
 
 - repo: https://github.com/pre-commit/mirrors-mypy
-  rev: "v1.9.0"
+  rev: "v1.10.1"
   hooks:
     - id: mypy
       files: src
@@ -58,7 +58,7 @@ repos:
     args: ["--all"]
 
 - repo: https://github.com/PyCQA/flake8
-  rev: "7.0.0"
+  rev: "7.1.0"
   hooks:
   - id: flake8
     additional_dependencies: [
@@ -81,7 +81,7 @@ repos:
     stages: [manual]
 
 - repo: https://github.com/codespell-project/codespell
-  rev: "v2.2.6"
+  rev: "v2.3.0"
   hooks:
   - id: codespell
     args: ["-L", "nd,unparseable,compiletime"]

setup.cfg

@@ -39,7 +39,7 @@ install_requires =
     matplotlib
     numba!=0.53.*,!=0.54.*
     parse
-    pint
+    pint!=0.24
     pyarrow
     scipy
     tqdm>=4.27

src/dspeed/processors/gaussian_filter1d.py

@@ -30,7 +30,7 @@
 
 # All this code belongs to the team that coded Scipy, found at this link:
 #     https://github.com/scipy/scipy/blob/v1.6.0/scipy/ndimage/filters.py#L210-L260
-# The only thing changed was the calculation of the convulution, which
+# The only thing changed was the calculation of the convolution, which
 # originally called a function from a C library.  In this code, the convolution is
 # performed with NumPy's built in convolution function.
 from __future__ import annotations

src/dspeed/processors/get_multi_local_extrema.py

@@ -102,10 +102,10 @@ def get_multi_local_extrema(
     n_min_right_counter = 0
 
     # initialize temporary arrays
-    left_vt_max = np.zeros(len(vt_max_out), dtype=np.float_)
-    left_vt_min = np.zeros(len(vt_min_out), dtype=np.float_)
-    right_vt_max = np.zeros(len(vt_max_out), dtype=np.float_)
-    right_vt_min = np.zeros(len(vt_min_out), dtype=np.float_)
+    left_vt_max = np.zeros(len(vt_max_out), dtype=float)
+    left_vt_min = np.zeros(len(vt_min_out), dtype=float)
+    right_vt_max = np.zeros(len(vt_max_out), dtype=float)
+    right_vt_min = np.zeros(len(vt_min_out), dtype=float)
 
     left_vt_max[:] = np.nan
     left_vt_min[:] = np.nan