data-visualizer/normalizers.py at master · AtLomDan/data-visualizer · GitHub

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from abc import ABC, abstractmethod
import numpy as np


class MagnitudeNormalizer(ABC):
    @abstractmethod
    def normalize(self, mag: np.ndarray) -> np.ndarray:
        pass

    def __call__(self, mag: np.ndarray) -> np.ndarray:
        return self.normalize(mag)


class RationalNormalizer(MagnitudeNormalizer):
    def __init__(self, r0: float = 1.0):
        if r0 <= 0:
            raise ValueError("r0 must be positive")
        self.r0 = r0

    def normalize(self, mag: np.ndarray) -> np.ndarray:
        return mag / (mag + self.r0)


class LinearNormalizer(MagnitudeNormalizer):
    def normalize(self, mag: np.ndarray) -> np.ndarray:
        m = np.nanmax(mag)
        return mag / m if m > 0 else mag


class LogNormalizer(MagnitudeNormalizer):
    def normalize(self, mag: np.ndarray) -> np.ndarray:
        m = np.nanmax(mag)
        return np.log1p(mag) / np.log1p(m) if m > 0 else mag