plot_depth_error.py
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00001 #!/usr/bin/env python
00002 
00003 import rospy
00004 import numpy as np
00005 import csv
00006 import sys
00007 import matplotlib.pyplot as plt
00008 from sklearn import linear_model, datasets
00009 
00010 if __name__ == "__main__":
00011     csv_files = sys.argv[1:]
00012     xs = []
00013     ys = []
00014     es = []
00015     for csv_file in csv_files:
00016         with open(csv_file) as f:
00017             reader = csv.reader(f)
00018             (true_depths, observed_depths) = zip(*[(float(row[0]), float(row[1])) for row in reader])
00019             errs = [a - b for (a, b) in zip(true_depths, observed_depths)]
00020             true_mean = np.mean(true_depths)
00021             observed_mean = np.mean(observed_depths)
00022             err_mean = np.mean(errs, axis=0)
00023             err_stddev = np.std(errs, axis=0)
00024             xs.append(true_mean)
00025             ys.append(observed_mean)
00026             #es.append(err_mean)
00027             es.append(err_stddev)
00028     #plt.errorbar(xs, ys, es, linestyle='None', marker='^')
00029     plt.scatter(xs, es)
00030     model_ransac = linear_model.RANSACRegressor(linear_model.LinearRegression(), min_samples=2,
00031                                                 residual_threshold=0.1)
00032     X = np.array(xs).reshape((len(xs), 1))
00033     Y = np.array(es)
00034     model_ransac.fit(X, Y)
00035     line_y_ransac = model_ransac.predict(X)
00036     plt.plot(X, line_y_ransac, "r--",
00037              label="{0} x + {1}".format(model_ransac.estimator_.coef_[0][0],
00038                                         model_ransac.estimator_.intercept_[0]))
00039     print "{0} x + {1}".format(model_ransac.estimator_.coef_[0][0],
00040                                model_ransac.estimator_.intercept_[0])
00041     plt.grid()
00042     plt.xlabel("Distance [m]")
00043     plt.ylabel("Standard Deviation [m]")
00044     # plt.legend(prop={'size': '8'})
00045     plt.show()


jsk_pcl_ros
Author(s): Yohei Kakiuchi
autogenerated on Tue Jul 2 2019 19:41:44