add more details, add visualize pickle module

libs/util.py

@@ -49,3 +49,18 @@ def convert_vector_to_mat(
             x, y = (rx_locs[i, :] + offset) / block_size
         result[int(x), int(y)] = rx_rsses[i]
     return result
+
+
+def stats(data):
+    '''
+    '''
+    data = data.reshape(-1,)
+    return {
+        "5perc": np.percentile(data, 5),
+        "25perc": np.percentile(data, 25),
+        "median": np.median(data),
+        "75perc": np.percentile(data, 75),
+        "95perc": np.percentile(data, 95),
+        "mean": np.mean(data),
+        "std": np.std(data),
+    }

localization_from_gan.py

@@ -66,7 +66,7 @@ def main(args):
         filepaths.extend(["{}/{}".format(args.folderpath, file) for file in files if '.pickle' in file])
 
     # prepare
-    if args.outputfile:
+    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\n")
 

localization_log_gamma_model.py

@@ -6,6 +6,7 @@ import pickle
 import argparse
 
 from libs.util import touch
+from libs.util import stats
 from libs.util import convert_mat_to_vector
 from libs.util import convert_vector_to_mat
 from libs.fitting import modelfit_log_gamma
@@ -34,7 +35,7 @@ def fittingSingle(filepath, args):
     rx_locs, rx_rsses = convert_mat_to_vector(data, block_size=0.1)
 
     # start fitting
-    min_pmse = float('inf')
+    min_fit_mse = float('inf')
     best_tx_loc = None
     best_tx_pwr = None
     best_env_gamma = None
@@ -51,20 +52,27 @@ def fittingSingle(filepath, args):
             monte_carlo_sampling_rate=0.8
         )
         # unpack
-        pmse, est_tx_loc, est_tx_pwr, est_env_gamma, est_rsses = result
-        if pmse < min_pmse:
-            print("|----- found better:", pmse, est_tx_loc, est_tx_pwr, est_env_gamma)
-            min_pmse = pmse
+        fit_mse, est_tx_loc, est_tx_pwr, est_env_gamma, est_rsses = result
+        if fit_mse < min_fit_mse:
+            print("|----- found better:", fit_mse, est_tx_loc, est_tx_pwr, est_env_gamma)
+            min_fit_mse = fit_mse
             best_tx_loc = est_tx_loc
             best_tx_pwr = est_tx_pwr
             best_env_gamma = est_env_gamma
             best_rsses = est_rsses
+
+    # calculate diff
+    data_best_est = convert_vector_to_mat(rx_locs, best_rsses, data.shape, block_size=0.1)
+    data_diff = data - data_best_est
+    stat = stats(data_diff)
+
     print("|- final:")
     print("|--- tx loc: {:.3f}, {:.3f}".format(best_tx_loc[0], best_tx_loc[1]))
     print("|--- tx pwr: {:.2f}".format(best_tx_pwr))
     print("|--- env gamma: {:.2f}".format(best_env_gamma))
-    print("|--- fitting mse: {:.6f}".format(min_pmse))
-    data_best_est = convert_vector_to_mat(rx_locs, best_rsses, data.shape, block_size=0.1)
+    print("|--- fitting mse: {:.6f}".format(min_fit_mse))
+    print("|--- rss diff: 5perc/95perc/median/mean: {:.4f}/{:.4f}/{:.4f}/{:.4f} m"
+          .format(stat['5perc'], stat['95perc'], stat['median'], stat['mean']))
 
     if args.outputfile:
         filename = os.path.basename(args.outputfile)
@@ -73,7 +81,8 @@ def fittingSingle(filepath, args):
                 "{},".format(filename) +
                 "{:.3f},{:.3f},".format(best_tx_loc[0], best_tx_loc[1]) +
                 "{:.2f},{:.2f}".format(best_tx_pwr, best_env_gamma) +
-                "{:.6f}".format(min_pmse) +
+                "{:.6f},".format(min_fit_mse) +
+                "{:.4f},{:.4f},{:.4f},{:.4f}".format(stat['5perc'], stat['95perc'], stat['median'], stat['mean']) +
                 "\n"
             )
 
@@ -96,9 +105,9 @@ def main(args):
         filepaths.extend(["{}/{}".format(args.folderpath, file) for file in files if '.pickle' in file])
 
     # prepare
-    if args.outputfile:
+    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\n")
+            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")
 
 
     # loop through and fit

visualize.py

@@ -0,0 +1,77 @@
+#!/usr/bin/python
+
+import os
+import pickle
+import argparse
+
+from libs.plotting import plotRSS
+
+
+def loadData(filepath):
+    try:
+        return pickle.load(open(filepath, "rb"))
+    except BaseException as e:
+        print("err: {}".format(e))
+        pass
+    return None
+
+
+def plotSingle(filepath, args):
+    '''
+    '''
+    # load data from file
+    data = loadData(filepath)
+    if data is None:
+        print("err: failed to load file {}".format(filepath))
+        return
+
+    plotRSS(data)
+
+
+def main(args):
+
+    # finding files
+    filepaths = []
+    if args.filepath:
+        filepaths.append(args.filepath)
+    if args.folderpath:
+        files = os.listdir(args.folderpath)
+        filepaths.extend(["{}/{}".format(args.folderpath, file) for file in files if '.pickle' in file])
+
+    # loop through and plot
+    for i in range(len(filepaths)):
+        print("- plotting file {}".format(filepaths[i]))
+        plotSingle(filepaths[i], args)
+
+
+if __name__ == '__main__':
+    p = argparse.ArgumentParser(description='Visualization')
+    p.add_argument(
+        '--filepath', '-f',
+        dest='filepath',
+        default=None,
+        help='input filepath for a pickle'
+    )
+    p.add_argument(
+        '--folderpath', '-fd',
+        dest='folderpath',
+        default=None,
+        help='input folderpath for many pickles'
+    )
+    try:
+        args = p.parse_args()
+    except BaseException as e:
+        print(e)
+        sys.exit()
+
+    if args.filepath is None and args.folderpath is None:
+        print("at least specify file `-f` or folder `-fd`")
+        sys.exit()
+    elif args.filepath is None and not os.path.isdir(args.folderpath):
+        print("folder {} not exit".format(args.folderpath))
+        sys.exit()
+    elif args.folderpath is None and not os.path.isfile(args.filepath):
+        print("file {} not exit".format(args.filepath))
+        sys.exit()
+
+    main(args)