more parsers

opencellid_parsing/003c.convert_data_into_xy_center_at_00.py

@@ -7,10 +7,10 @@ import pickle
 import numpy as np
 
 
-def convert_gps_into_xy(latlon1, latlon2, convert2radian=False):
+def convert_gps_into_xy(latlon, reference, convert2radian=False):
     radius = 6371e3
-    lat1, lon1 = latlon1
-    lat2, lon2 = latlon2
+    lat1, lon1 = reference
+    lat2, lon2 = latlon
     if convert2radian:
         lat1 = lat1 * np.pi / 180
         lat2 = lat2 * np.pi / 180
@@ -21,8 +21,8 @@ def convert_gps_into_xy(latlon1, latlon2, convert2radian=False):
     # a = np.sin(delta_lat / 2) ** 2 + np.cos(lat1) * np.cos(lat2) * np.sin(delta_lon / 2) ** 2
     # c = 2 * np.arctan2(np.sqrt(a), np.sqrt(1 - a))
     # d1meters = radius * c    # Haversine distance
-    x = delta_lon * np.cos((lat1 + lat2) / 2)
-    y = delta_lat
+    x = radius * delta_lon * np.cos((lat1 + lat2) / 2)
+    y = radius * delta_lat
     # d2meters = radius * np.sqrt(x*x + y*y) # Pythagorean distance
     return x, y
 
@@ -71,7 +71,7 @@ for filepath in glob.glob("{}/with_groundtruth/*/*/*/*/*.csv".format(folderpath)
         lon = float(tmp[0])
         lat = float(tmp[1])
         sig = float(tmp[2])
-        x, y = convert_gps_into_xy((lat, lon), (cell_lat_rad, cell_lon_rad))
+        x, y = convert_gps_into_xy((lat * np.pi / 180, lon * np.pi / 180), (cell_lat_rad, cell_lon_rad))
         min_x = min(min_x, x)
         min_y = min(min_y, y)
         min_sig = min(min_sig, sig)

opencellid_parsing/003d_optional.generate_image.py

@@ -17,22 +17,32 @@ def blocking_display_signal_map(
     '''
     '''
     plt.scatter(data_vector[:, 3], data_vector[:, 4], s=50, c=data_vector[:, 2])
+    # plt.xlim()
+    # plt.ylim()
     plt.colorbar()
+    plt.xlabel('loc x (m)')
+    plt.ylabel('loc y (m)')
     # plt.show()
     plt.draw()
-    plt.savefig("{}.png".format(fp), dpi=50)
-    plt.pause(0.1)
-    q = input("press Enter to continue... type q to quit: ")
-    if q == 'q':
-        sys.exit()
+    plt.savefig(fp, dpi=50)
+    # plt.pause(0.1)
+    # q = input("press Enter to continue... type q to quit: ")
+    # if q == 'q':
+    #     sys.exit()
     plt.close()
 
 
 if len(sys.argv) < 3:
-    print('Usage: {} pickle_fp'.format(sys.argv[0]))
+    print('Usage: {} pickle_fp outputfolder'.format(sys.argv[0]))
     sys.exit(0)
 
 pickle_fp = sys.argv[1]
+outputfolder = sys.argv[2]
+if not os.path.isdir(outputfolder):
+    try:
+        os.makedirs(outputfolder)
+    except BaseException:
+        raise
 
 ############################
 # load
@@ -40,9 +50,10 @@ pickle_fp = sys.argv[1]
 all_data = pickle.load(open(pickle_fp, 'rb'))
 
 for data in all_data:
+    num_of_entries = len(data['measurements'])
     filename = (
-        "{}_{}_{}_{}_{}_{}.png"
-        .format(data['country_code'], data['radio'], data['mcc'], data['mnc'], data['area'], data['cell'])
+        "{}_{}_{}_{}_{}_{}_{}entries.png"
+        .format(data['country_code'], data['radio'], data['mcc'], data['mnc'], data['area'], data['cell'], num_of_entries)
     )
-    blocking_display_signal_map(data['measurements'], filename)
+    blocking_display_signal_map(data['measurements'], "{}/{}".format(outputfolder, filename))