dcor

import numpy as np import dcor # Example data x = np.array([1, 2, 3, 4, 5]) y = np.array([1, 2, 3, 4, 5]) z = np.array([5, 4, 3, 2, 1]) w = np.array([1, 2, 3, 4, 6]) # Slightly different for energy_distance # Calculate distance correlation dc_xy = dcor.distance_correlation(x, y) dc_xz = dcor.distance_correlation(x, z) print(f"Distance correlation (x, y): {dc_xy:.4f}") print(f"Distance correlation (x, z): {dc_xz:.4f}") # Calculate energy distance ed_xw = dcor.energy_distance(x, w) print(f"Energy distance (x, w): {ed_xw:.4f}") # Perform independence test (requires bootstrapping) # Note: n_bootstraps should be sufficiently large for real analysis independence_p_value = dcor.independence_test(x, y, n_bootstraps=100).p_value print(f"P-value for independence test (x, y): {independence_p_value:.4f}")