From 547f8b21a6aba6b83b546cc29effe0319cfda835 Mon Sep 17 00:00:00 2001 From: Orestis Kaparounakis Date: Thu, 24 Jul 2025 17:42:39 +0100 Subject: [PATCH] Replace np.float_ with np.float64 --- .../distributional/distributional.py | 20 +++++++++---------- 1 file changed, 10 insertions(+), 10 deletions(-) diff --git a/src/signaloid/distributional/distributional.py b/src/signaloid/distributional/distributional.py index 9b31643..6bd76b6 100644 --- a/src/signaloid/distributional/distributional.py +++ b/src/signaloid/distributional/distributional.py @@ -27,11 +27,11 @@ class DistributionalValue: def __init__(self) -> None: - self.positions: NDArray[np.float_] = np.array([], dtype=np.float_) - self.masses: NDArray[np.float_] = np.array([], dtype=np.float_) + self.positions: NDArray[np.float64] = np.array([], dtype=np.float64) + self.masses: NDArray[np.float64] = np.array([], dtype=np.float64) self.raw_masses: List[int] = [] - self.adjusted_masses: NDArray[np.float_] = np.array([], dtype=np.float_) - self.widths: NDArray[np.float_] = np.array([], dtype=np.float_) + self.adjusted_masses: NDArray[np.float64] = np.array([], dtype=np.float64) + self.widths: NDArray[np.float64] = np.array([], dtype=np.float64) self.mean: Union[None, float] = None self.particle_value: Union[None, float] = None self.variance: Union[None, float] = None @@ -186,8 +186,8 @@ def _parse_ux_string(text: str) -> Optional["DistributionalValue"]: dist_value.mean = mean_value dist_value.UR_type = representation_type dist_value.UR_order = dirac_delta_count - dist_value.positions = np.array(support_position_list, dtype=np.float_) - dist_value.masses = np.array(probability_mass_list, dtype=np.float_) + dist_value.positions = np.array(support_position_list, dtype=np.float64) + dist_value.masses = np.array(probability_mass_list, dtype=np.float64) dist_value.raw_masses = raw_probability_mass_list dist_value.particle_value = particleValue @@ -260,8 +260,8 @@ def _parse_bytes(buffer: Union[bytes, bytearray]) -> Optional["DistributionalVal dist_value.mean = mean_value dist_value.UR_type = representation_type dist_value.UR_order = dirac_delta_count - dist_value.positions = np.array(support_position_list, dtype=np.float_) - dist_value.masses = np.array(probability_mass_list, dtype=np.float_) + dist_value.positions = np.array(support_position_list, dtype=np.float64) + dist_value.masses = np.array(probability_mass_list, dtype=np.float64) dist_value.raw_masses = raw_probability_mass_list # Calculate weighted sample variance @@ -481,8 +481,8 @@ def drop_zero_mass_positions(self) -> None: *[(x, y) for x, y in zip(self.positions, self.masses) if y != 0] ) # zip() returns tuple - self.positions = np.array(list(filtered_positions), dtype=np.float_) - self.masses = np.array(list(filtered_masses), dtype=np.float_) + self.positions = np.array(list(filtered_positions), dtype=np.float64) + self.masses = np.array(list(filtered_masses), dtype=np.float64) self._has_no_zero_mass = True return