Typing, linting, update dependencies

pyproject.toml

@@ -30,7 +30,7 @@ classifiers = [
 dynamic = ["version"]
 dependencies = [
     "attrs >=21.2.0",
-    "numpy >=1.21",
+    "numpy >=2.0",
     "scipy >=1.7.0",
     "matplotlib >=3.3.2",
     "iminuit >=2.7.0",
@@ -56,8 +56,8 @@ dev = [
     "pytest-xdist >=3.5.0",
     "pytest-sugar >=1.0.0",
     "uproot >=4",
-    "boost-histogram >=1.2.1",
-    "hist >=2.7.1",
+    "boost-histogram >=1.5",
+    "hist >=2.8",
 ]
 docs = [
     "sphinx>=7.0",

src/pachyderm/binned_data.py

@@ -1252,7 +1252,7 @@ def _apply_rebin(
 
     # Only use numba if available
     f = _sum_values_for_rebin_numba if _sum_values_for_rebin_numba is not None else _sum_values_for_rebin
-    return f(  # type: ignore[no-any-return]
+    return f(
         n_bins_new_axis=n_bins_new_axis,
         values=values,
         run_starts=run_starts,
@@ -1264,9 +1264,9 @@ def _apply_rebin(
 def _sum_values_for_rebin(
     n_bins_new_axis: int,
     values: npt.NDArray[np.float64],
-    run_starts: npt.NDArray[np.float64],
-    run_values: npt.NDArray[np.float64],
-    run_lengths: npt.NDArray[np.float64],
+    run_starts: npt.NDArray[np.int64],
+    run_values: npt.NDArray[np.int64],
+    run_lengths: npt.NDArray[np.int64],
 ) -> npt.NDArray[np.float64]:
     """Implementation of summing up values for the rebinning
 

src/pachyderm/fit/cost_function.py

@@ -144,7 +144,7 @@ def __init__(self, *cost_functions: T_CostFunction | SimultaneousFit):
 
     def __add__(self, other: T_CostFunction | SimultaneousFit) -> SimultaneousFit:
         """Add a new function to the simultaneous fit."""
-        return type(self)(self, other)
+        return type(self)(self, other)  # type: ignore[arg-type]
 
     def __radd__(self, other: T_CostFunction | SimultaneousFit) -> SimultaneousFit:
         """For use with ``sum(...)``."""

src/pachyderm/generic_config.py

@@ -586,8 +586,8 @@ def iterate_with_selected_objects_in_order(
         selected_analysis_objects = []
         for selected_values in itertools.product(*selected_iterators):
             for key_index, obj in analysis_objects.items():
-                selected_via_analysis_iterables = all(getattr(key_index, k) == v for k, v in values)
-                selected_via_selected_iterators = all(getattr(key_index, k) == v for k, v in selected_values)
+                selected_via_analysis_iterables = all(getattr(key_index, k) == v for k, v in values)  # type: ignore[misc,has-type]
+                selected_via_selected_iterators = all(getattr(key_index, k) == v for k, v in selected_values)  # type: ignore[misc,has-type]
                 selected_obj = selected_via_analysis_iterables and selected_via_selected_iterators
 
                 if selected_obj:

src/pachyderm/histogram.py

@@ -545,7 +545,7 @@ def _integral(
         # Provide the opportunity to scale by bin width
         widths = np.ones(len(self.y))
         if multiply_by_bin_width:
-            widths = self.bin_widths
+            widths = self.bin_widths  # type: ignore[assignment]
 
         # Integrate by summing up all of the bins and the errors.
         # Perform the integral.

tests/fit/test_function.py

@@ -18,7 +18,7 @@
 def test_gaussian() -> None:
     """Test the gaussian function."""
     # Setup
-    x = np.arange(-10, 10, 0.1)
+    x = np.arange(-10, 10, 0.1, dtype=np.float64)
     mean = 0.5
     sigma = 4.2
 

tests/test_binned_data.py

@@ -4,6 +4,7 @@
 """
 from __future__ import annotations
 
+import logging
 from typing import Any
 
 import numpy as np
@@ -12,6 +13,8 @@
 
 from pachyderm import binned_data
 
+logger = logging.getLogger(__name__)
+
 
 def test_axis_slice_copy() -> None:
     axis = binned_data.Axis(np.arange(1, 11))
@@ -65,6 +68,7 @@ def test_axis_slice(
     hist = pytest.importorskip("hist")
     hist_s = slice(s.start, s.stop, hist.rebin(s.step) if s.step else s.step)
     hist_h = hist.Hist(hist.axis.Regular(10, 1, 11))
+    logger.info(f"{hist_h.axes[0].edges}")
     hist_sliced_axis = hist_h[hist_s].axes[0]
 
     np.testing.assert_allclose(sliced_axis.bin_edges, hist_sliced_axis.edges)
@@ -103,7 +107,7 @@ def test_axis_slice_rebin(
     np.testing.assert_allclose(sliced_axis.bin_edges, expected_bin_edges)
 
 
-@pytest.fixture()
+@pytest.fixture
 def hists_for_rebinning() -> tuple[npt.NDArray[np.float64], binned_data.BinnedData]:
     _values = []
     for i in range(2, 12):

tests/test_histogram.py

@@ -23,7 +23,7 @@
 logger = logging.getLogger(__name__)
 
 
-@pytest.fixture()
+@pytest.fixture
 def retrieve_root_list(test_root_hists: Any) -> Iterator[tuple[str, Any, Any]]:
     """Create an set of lists to load for a ROOT file.
 
@@ -227,7 +227,7 @@ def test_retrieve_object(self, retrieve_root_list: Any) -> None:
         assert output == expected
 
 
-@pytest.fixture()
+@pytest.fixture
 def setup_histogram_conversion() -> tuple[str, str, histogram.Histogram1D]:
     """Setup expected values for histogram conversion tests.
 
@@ -569,7 +569,7 @@ def test_get_array_from_hist2D(self, use_bin_edges, set_zero_to_NaN, test_root_h
             assert np.isclose(hist_array[0][1], 0.0)
 
 
-@pytest.fixture()
+@pytest.fixture
 def setup_basic_hist() -> (
     tuple[histogram.Histogram1D, npt.NDArray[np.float64], npt.NDArray[np.float64], npt.NDArray[np.float64]]
 ):