Angular analysis of B+->K*+(K+pi0)mumu
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import numpy as np
from hep_ml.reweight import BinsReweighter
def select_feature(feature: np.ndarray, limits: tuple[float, float]) -> tuple[np.ndarray, list]: selection_indices = [] for index, value in enumerate(feature): if value > limits[0] and value < limits[1]: selection_indices.append(index)
return feature[selection_indices], selection_indices
def reweight_feature(original_feature: list, target_feature: list, n_bins: int, n_neighs: int = 2): original_weights = np.ones(len(original_feature)) bin_reweighter = BinsReweighter(n_bins = n_bins, n_neighs = n_neighs) bin_reweighter.fit(original = original_feature, target = target_feature, original_weight = original_weights)
return bin_reweighter.predict_weights(original = original_feature, original_weight = original_weights)
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