Ensuring NumPy 2.0 compatibility

.pre-commit-config.yaml

@@ -11,7 +11,7 @@ repos:
     -   id: check-yaml
 
   - repo: https://github.com/PyCQA/isort
-    rev: 5.10.1
+    rev: 5.13.2
     hooks:
       - id: isort
 

pyproject.toml

@@ -30,7 +30,7 @@ dependencies = [
     "pybtex>=0.24",
     "spglib>=1.9",
     "upf-to-json>=0.9.5",
-    "ase-koopmans==0.1.4",
+    "ase-koopmans==0.1.5",
     "scikit-learn>=1.0",
     "deepdiff>=5.8.1",
 ]

src/koopmans/calculators/_koopmans_cp.py

@@ -63,7 +63,7 @@ def good_fft(nr: int) -> int:
     return nr
 
 
-def read_ham_file(filename: Path) -> np.ndarray[Any, np.dtype[np.cfloat]]:
+def read_ham_file(filename: Path) -> np.ndarray[Any, np.dtype[np.complex128]]:
     # Read a single hamiltonian XML file
     if not filename.exists():
         raise FileExistsError(f'{filename} does not exist')
@@ -77,7 +77,7 @@ def read_ham_file(filename: Path) -> np.ndarray[Any, np.dtype[np.cfloat]]:
     assert ham_xml.text is not None, f'{filename} is empty'
 
     ham_array = np.array([complex(*[float(x) for x in line.split(',')])
-                          for line in ham_xml.text.strip().split('\n')], dtype=np.cfloat) * utils.units.Hartree
+                          for line in ham_xml.text.strip().split('\n')], dtype=np.complex128) * utils.units.Hartree
 
     return ham_array.reshape((length, length))
 

src/koopmans/calculators/_ui/_calculator.py

@@ -50,13 +50,13 @@ def __init__(self, atoms: Atoms, *args, **kwargs):
         self.atoms.calc = self
 
         # Intermediate variables
-        self.centers: NDArray[np.float_] = np.array([])
+        self.centers: NDArray[np.float64] = np.array([])
         self.spreads: List[float] = []
         self.phases: List[complex] = []
-        self.hr: NDArray[np.complex_] = np.array([])
-        self.hr_coarse: NDArray[np.complex_] = np.array([])
-        self.hr_smooth: NDArray[np.complex_] = np.array([])
-        self.hk: NDArray[np.complex_] = np.array([])
+        self.hr: NDArray[np.complex128] = np.array([])
+        self.hr_coarse: NDArray[np.complex128] = np.array([])
+        self.hr_smooth: NDArray[np.complex128] = np.array([])
+        self.hk: NDArray[np.complex128] = np.array([])
         self.Rvec: NDArray[np.int_] = np.array([])
         self.Rsmooth: NDArray[np.int_] = np.array([])
         self.wRs: List[int] = []
@@ -308,7 +308,7 @@ def parse_phases(self) -> None:
             self.phases = []
         return
 
-    def print_centers(self, centers: NDArray[np.float_] = np.array([])) -> None:
+    def print_centers(self, centers: NDArray[np.float64] = np.array([])) -> None:
         """
         print_centers simply prints out the centers in the following Xcrysden-readable format:
 
@@ -649,7 +649,7 @@ def calc_dos(self) -> None:
 
         return
 
-    def correct_phase(self) -> NDArray[np.complex_]:
+    def correct_phase(self) -> NDArray[np.complex128]:
         """
         correct_phase calculate the correct phase factor to put in the Fourier transform
                       to get the interpolated k-space hamiltonian. The correction consists

src/koopmans/calculators/_ui/_utils.py

@@ -12,7 +12,7 @@
 from numpy.typing import ArrayLike, NDArray
 
 
-def crys_to_cart(vec: NDArray[np.float_], trmat: NDArray[np.float_], typ: int) -> NDArray[np.float_]:
+def crys_to_cart(vec: NDArray[np.float64], trmat: NDArray[np.float64], typ: int) -> NDArray[np.float64]:
     """
     Function to transform the numpy array vec (or a list/array of numpy arrays) from
     crystal to cartesian (in alat units), or viceversa, as it is done in QE: typ=+1
@@ -33,7 +33,8 @@ def crys_to_cart(vec: NDArray[np.float_], trmat: NDArray[np.float_], typ: int) -
     return vec_tr
 
 
-def extract_hr(hr: NDArray[np.complex_], rvect: NDArray[np.int_], nr1: int, nr2: int, nr3: int) -> NDArray[np.complex_]:
+def extract_hr(hr: NDArray[np.complex128], rvect: NDArray[np.int_],
+               nr1: int, nr2: int, nr3: int) -> NDArray[np.complex128]:
     """
     Function to select the Wannier Hamiltonian only on the primitive cell R-vectors.
     The Hamiltonian coming from a Wannier90 calculation with k-points is indeed

src/koopmans/calculators/_utils.py

@@ -311,7 +311,7 @@ class ReturnsBandStructure(ABC):
     """
 
     @abstractmethod
-    def eigenvalues_from_results(self) -> npt.NDArray[np.float_]:
+    def eigenvalues_from_results(self) -> npt.NDArray[np.float64]:
         ...
 
     @abstractmethod

src/koopmans/utils/_io.py

@@ -265,7 +265,7 @@ def read_wannier_hr_file(fname: Path) -> Tuple[np.ndarray, np.ndarray, List[int]
     return hr_np, rvect_np, weights, nrpts
 
 
-def read_wannier_u_file(fname: Path) -> Tuple[npt.NDArray[np.complex_], npt.NDArray[np.float_], int]:
+def read_wannier_u_file(fname: Path) -> Tuple[npt.NDArray[np.complex128], npt.NDArray[np.float64], int]:
 
     with open(fname, 'r') as fd:
         lines = fd.readlines()
@@ -286,7 +286,7 @@ def read_wannier_u_file(fname: Path) -> Tuple[npt.NDArray[np.complex_], npt.NDAr
     return umat, kpts, nk
 
 
-def write_wannier_u_file(fname: Path, umat: npt.NDArray[np.complex_], kpts: npt.NDArray[np.float_]):
+def write_wannier_u_file(fname: Path, umat: npt.NDArray[np.complex128], kpts: npt.NDArray[np.float64]):
 
     flines = [f' Written on {datetime.now().isoformat(timespec="seconds")}']
     flines.append(''.join([f'{x:12d}' for x in umat.shape]))