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import numpy as np 
import json
import numpy as np

from matplotlib import pyplot as plt


def hps(X):

    X_mean = np.mean(X, axis=0)
    X_centered = X -  X_mean
    X_cov = np.cov(X_centered.T)

    # * 3.1. Get Eigen Values and Vectors
    eigen_values, eigen_vectors = np.linalg.eig(X_cov)
    # * 3.2. Get the top M eigen values indices
    top_M_idx = np.argsort(eigen_values)[::-1][-1]

    # return np.dot(X_mean, top_M_idx)
    return eigen_values[top_M_idx]
    

if __name__ == '__main__':
    results = json.load(open("video-to-pose3D/outputs/alpha_pose_d05/alphapose-results.json"))
    hpss = []
    frames = []
    for i in range(0, 135):
        keypoints = np.array(results[i]["keypoints"]).reshape(17,3)[:,:2]
        hps_val = hps(keypoints)
        hpss.append(hps_val)
        frames.append(i)
    
    fig = plt.figure()
    ax = plt.subplot(111)

    der = np.gradient(hpss,frames)

    ax.plot(frames, der)
    plt.xticks(np.arange(min(frames), max(frames) + 1, 10))
    plt.grid()
    fig.savefig('hps_d06_dif.png')