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Replace np.float_ with np.float64 #4

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orestiskapar wants to merge 2 commits into from
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Replace np.float_ with np.float64 #4

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547f8b2
Replace np.float_ with np.float64
orestiskapar Jul 24, 2025
93c91f2
Merge branch 'main' into issue-3
orestiskapar Jul 24, 2025
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20 changes: 10 additions & 10 deletions src/signaloid/distributional/distributional.py
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Original file line number Diff line number Diff line change
Expand Up @@ -27,11 +27,11 @@

class DistributionalValue:
def __init__(self, double_precision: bool = True) -> 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
Expand Down Expand Up @@ -455,8 +455,8 @@ def _parse_bytes_dp(buffer: Union[bytes, bytearray]) -> Optional["Distributional
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
Expand Down Expand Up @@ -530,8 +530,8 @@ def _parse_bytes_sp(buffer: Union[bytes, bytearray]) -> Optional["Distributional
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
Expand Down Expand Up @@ -761,8 +761,8 @@ 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
Expand Down