support groundtruth output

localization_log_gamma_model.py

@@ -4,6 +4,7 @@ import os
 import sys
 import pickle
 import argparse
+from math import sqrt
 
 from libs.util import touch
 from libs.util import stats
@@ -30,6 +31,10 @@ def fittingSingle(filepath, args):
     if data is None:
         print("err: failed to load file {}".format(filepath))
         return
+    location_gt = [float('nan'), float('nan')]
+    if len(data) is 2:
+        data, location_gt = data
+        location_gt = location_gt * 0.1
 
     # convert data matrix to vectors
     rx_locs, rx_rsses = convert_mat_to_vector(data, block_size=0.1)
@@ -69,6 +74,8 @@ def fittingSingle(filepath, args):
     print("|- final:")
     print("|--- tx loc: {:.3f}, {:.3f}".format(best_tx_loc[0], best_tx_loc[1]))
     print("|--- tx pwr: {:.2f}".format(best_tx_pwr))
+    error = sqrt((best_tx_loc[0] - location_gt[0]) ** 2 + (best_tx_loc[1] - location_gt[1]) ** 2)
+    print("|--- loc error distance: {:.2f}".format(error))
     print("|--- env gamma: {:.2f}".format(best_env_gamma))
     print("|--- fitting mse: {:.6f}".format(min_fit_mse))
     print("|--- rss diff: 5perc/95perc/median/mean: {:.4f}/{:.4f}/{:.4f}/{:.4f} m"
@@ -79,7 +86,9 @@ def fittingSingle(filepath, args):
         with open(args.outputfile, 'a') as f:
             f.write(
                 "{},".format(filename) +
+                "{:.3f},{:.3f},".format(location_gt[0], location_gt[1]) +
                 "{:.3f},{:.3f},".format(best_tx_loc[0], best_tx_loc[1]) +
+                "{:.3f},".format(error) +
                 "{:.2f},{:.2f},".format(best_tx_pwr, best_env_gamma) +
                 "{:.6f},".format(min_fit_mse) +
                 "{:.4f},{:.4f},{:.4f},{:.4f}".format(stat['5perc'], stat['95perc'], stat['median'], stat['mean']) +
@@ -107,7 +116,7 @@ def main(args):
     # prepare
     if args.outputfile and not os.path.isfile(args.outputfile):
         with open(args.outputfile, 'w') as f:
-            f.write("filename,tx_x,tx_y,tx_pwr,env_gamma,fit_mse,rss_diff_5perc,rss_diff_95perc,rss_diff_med,rss_diff_avg\n")
+            f.write("filename,true_x,true_y,est_tx_x,est_tx_y,tx_pwr,env_gamma,fit_mse,rss_diff_5perc,rss_diff_95perc,rss_diff_med,rss_diff_avg\n")
 
 
     # loop through and fit