import numpy as np
from sklearn.decomposition import PCA
import matplotlib.pylab as plt

def save_pic():
    fig = plt.figure(figsize=(12, 6))
    ax = fig.add_axes([0.1, 0.13, 0.85, 0.80])
    ax.plot([0, 1], [0, 1], 'k--')
    fig.savefig('./a.png')
    plt.close(fig)

def test(is_call_save_pic):
    a = np.arange(1200).reshape((30, -1))
    if is_call_save_pic:
        save_pic()
    pca = PCA(n_components=2)
    pca.fit(a)
    print('OK')

if __name__ == '__main__':
    test(False)
    try:
        test(True)
    except np.linalg.LinAlgError as e:
        print(e)