import numpy as np
import pandas as pd
[docs]
def perfect(x: np.ndarray, d50: float) -> np.ndarray:
"""A perfect partition
Args:
x: The input dimension, e.g. size or density
d50: The cut-point
Returns:
"""
pn: np.ndarray = np.where(x >= d50, 1.0, 0.0)
return pn
[docs]
def napier_munn(x: np.ndarray, d50: float, ep: float) -> np.ndarray:
"""The Napier-Munn partition (1998)
REF: https://www.sciencedirect.com/science/article/pii/S1474667016453036
Args:
x: The input dimension, e.g. size or density
d50: The cut-point
ep: The Escarte Probable
Returns:
"""
pn: np.ndarray = 1 / (1 + np.exp(1.099 * (d50 - x) / ep))
return pn
# if __name__ == '__main__':
# da = np.arange(0, 10)
# PN = perfect(da, d50=6.3)
# df = pd.DataFrame([da, PN], index=['da', 'pn']).T
# print(df)
#
# da = np.arange(0, 10)
# PN = napier_munn(da, d50=6.3, ep=0.1)
# df = pd.DataFrame([da, PN], index=['da', 'pn']).T
# print(df)