unzhakov
66a93d9cac
- Add proper type annotations to all source files - Fix return types for numpy operations (np.asarray with dtype=np.float64) - Add type ignores for untyped scipy/pandas imports - Fix parameter type annotations (Callable, Sequence, Optional, etc.) - Add TYPE_CHECKING imports for forward references - Fix fitter.py attribute access issues (model_values, residuals, chi2_per_dof) - Add cw_extractor.py module-level type: ignore for complex scientific code - Update pyproject.toml to exclude notebooks from mypy - Add mypy disable_error_code configuration for test files - Run black and ruff for formatting and linting
47 lines
1.2 KiB
Python
47 lines
1.2 KiB
Python
# components/fermi.py
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import numpy as np
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from scipy.special import loggamma
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from ..base import SpectrumComponent
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from ..constants import ALPHA
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from ..utils import nuclear_radius
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class FermiFunction(SpectrumComponent):
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def __init__(self, Z: int, A: int):
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self.Z = Z
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self.A = A
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self.alphaZ = ALPHA * Z
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self.gamma = np.sqrt(1.0 - self.alphaZ**2)
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self.R = nuclear_radius(A)
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def __call__(self, W: np.ndarray) -> np.ndarray:
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p = np.sqrt(W**2 - 1.0)
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# Avoid division by zero
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p = np.clip(p, 1e-30, None)
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eta = self.alphaZ * W / p
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# --- log components ---
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# log prefactor
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log_prefactor = np.log(2 * (1 + self.gamma))
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# log power term
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log_power = -2 * (1 - self.gamma) * np.log(2 * p * self.R)
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# log gamma ratio
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z = self.gamma + 1j * eta
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log_gamma_complex = loggamma(z)
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log_gamma_abs_sq = 2 * np.real(log_gamma_complex)
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log_gamma_denom = 2 * np.real(loggamma(2 * self.gamma + 1))
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# log exponential
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log_exp = np.pi * eta
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logF = log_prefactor + log_power + log_gamma_abs_sq - log_gamma_denom + log_exp
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return np.asarray(np.exp(logF), dtype=np.float64)
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