#!/usr/bin/env python3 import sys import numpy as np import pandas as pd import matplotlib.pyplot as plt def plot(filename: str, filename_2: str, num_data_points: int): df_1 = pd.read_csv(filename, delimiter = ',', names=['x', 'y', 'z']) df_2 = pd.read_csv(filename_2, delimiter = ',', names=['x', 'y', 'z']) n = num_data_points y = df_1['x'].to_list() x = np.linspace(0, n, n) plt.plot(x, y[:n], label='x raw: var ' + str(np.var(y)), color='black') var_1 = np.var(y) y = df_2['x'].to_list() x = np.linspace(0, n, n) plt.plot(x, y[:n], label='x calib: var ' + str(np.var(y)), color='red') var_2 = np.var(y) plt.ylim([-0.1, 0.1]) plt.legend() plt.show() if var_1 < var_2: print("Variance of {} is smaller: {}".format(filename, var_1)) else: print("Variance of {} is smaller: {}".format(filename_2, var_2)) y = df_1['y'].to_list() x = np.linspace(0, n, n) plt.plot(x, y[:n], label='y raw: var ' + str(np.var(y)), color='black') var_1 = np.var(y) y = df_2['y'].to_list() x = np.linspace(0, n, n) plt.plot(x, y[:n], label='y calib: var ' + str(np.var(y)), color='red') var_2 = np.var(y) plt.ylim([-0.1, 0.1]) plt.legend() plt.show() if var_1 < var_2: print("Variance of {} is smaller: {}".format(filename, var_1)) else: print("Variance of {} is smaller: {}".format(filename_2, var_2)) y = df_1['z'].to_list() x = np.linspace(0, n, n) plt.plot(x, y[:n], label='z raw: var ' + str(np.var(y)), color='black') var_1 = np.var(y) y = df_2['z'].to_list() x = np.linspace(0, n, n) plt.plot(x, y[:n], label='z calib: var ' + str(np.var(y)), color='red') var_2 = np.var(y) plt.ylim([-0.1, 0.1]) plt.legend() plt.show() if var_1 < var_2: print("Variance of {} is smaller: {}".format(filename, var_1)) else: print("Variance of {} is smaller: {}".format(filename_2, var_2)) file_1 = sys.argv[1] file_1 = sys.argv[1] file_1 = sys.argv[1] file_2 = sys.argv[2] n = int(sys.argv[3]) plot(file_1, file_2, n)