[i] general improvements

FHSTP/prep.py

@@ -2,8 +2,8 @@
 # Title: Data Preparation for LINK Configs and Transmissions
 # Author: Fabian Kovac <ds191008@fhstp.ac.at>
 # Team: University of Applied Sciences St. Pölten
-# Version: 1.4
-# Last changed: 2021-06-24
+# Version: 1.5
+# Last changed: 2021-06-28
 #
 
 import sys
@@ -41,7 +41,7 @@ def parse_arguments() -> argparse.Namespace:
     # add transmissions parameter to parser
     required_args = parser.add_argument_group('required arguments')
     required_args.add_argument('-c', '--config', type = str, required = True, help = 'Path to Config-File')
-    required_args.add_argument('-t', '--transmissions', type = str, required = True, help = 'Path to Config-File')
+    required_args.add_argument('-t', '--transmissions', type = str, required = True, help = 'Path to Transmissions-File')
     required_args.add_argument('-i', '--inca', type = str, required = True, help = 'Path to Inca-Dir')
     
     # parse arguments
@@ -71,10 +71,10 @@ def _log(msg: str) -> None:
 
 def load_inca_file(file_inca: pathlib.Path) -> np.array:
     """Loads loads gzipped INCA data to a given file
-
+    
     Parameters:
        file_inca (pathlib.Path): Path to INCA file
-
+    
     Returns:
         x (np.array): Matrix with shape (401, 701)
     """
@@ -90,17 +90,17 @@ def load_inca_file(file_inca: pathlib.Path) -> np.array:
 
 def load_inca_data(dir_inca: pathlib.Path) -> np.array:
     """Loads inca files to a given inca dir
-
+    
     Parameters:
         dir_inca (pathlib.Path): Directory for INCA files
-
+    
     Returns:
         inca_Data (np.array): Tensor with shape (96, 401, 701)
     """
     
     # initialize tensor with 96 15min intervals
     inca_data = np.zeros((96, 401, 701))
-
+    
     # load inca dates from inca dir
     for i, file_inca in enumerate(sorted([file for file in dir_inca.iterdir() if file.is_file()])):        
         # load zipped ascii data
@@ -114,13 +114,13 @@ def load_inca_data(dir_inca: pathlib.Path) -> np.array:
 
 def get_midpoint(lon_a: np.array, lat_a: np.array, lon_b: np.array, lat_b: np.array) -> np.array:
     """Calculcates the midpoint between two utm coordinate pairs
-
+    
     Parameters:
         lon_a (np.array): Longitudes of point A
         lat_a (np.array): Latitudes of point A
         lon_b (np.array): Longitudes of point B
         lat_b (np.array): Latitudes of point B
-
+    
     Returns:
         lon, lat (np.array): Vectors with longitudes and latitudes of the midpoints
     """
@@ -143,56 +143,59 @@ def get_midpoint(lon_a: np.array, lat_a: np.array, lon_b: np.array, lat_b: np.ar
 
 
 def get_distance(lon_a: np.array, lat_a: np.array, lon_b: np.array, lat_b: np.array) -> np.array:
-    """Calculcates distance between two coordinates in km
-    using a rotation-ellipsoid in cartesian coordinates out of polar coordiantes
-
+    """Calculcates distance between two coordinates in km using a WGS84 rotation-ellipsoid
+    
     Parameters:
         lon_a (np.array): Longitudes of point A
         lat_a (np.array): Latitudes of point A
         lon_b (np.array): Longitudes of point B
         lat_b (np.array): Latitudes of point B
-
+    
     Returns:
-        length (np.array): Vector with distances in km (can directly be assigned a pandas column)
+        length (np.array): Vector with distances in km
     """
-
-    # constants (euqator radius and pole radius in km)
+    
+    # constants (equator radius and pole radius in km)
     # r_equator is the 'semi-major axis' and r_pole the 'semi-minor axis' on a WGS84 ellipsoid
     r_equator = 6378.137
     r_pole = 6356.7523142
-
-    # calculate rotation-ellipsoid in cartesian coordinates out of polar coordiantes
+    
+    # calculate points on rotation-ellipsoid
+    # point A
     za = np.sin(np.radians(lat_a)) * r_pole
     ra = np.cos(np.radians(lat_a)) * r_equator
     xa = np.sin(np.radians(lon_a)) * ra
     ya = np.cos(np.radians(lon_a)) * ra
-
+    
+    # point B
     zb = np.sin(np.radians(lat_b)) * r_pole
     rb = np.cos(np.radians(lat_b)) * r_equator
     xb = np.sin(np.radians(lon_b)) * rb
     yb = np.cos(np.radians(lon_b)) * rb
-
-    # calculate distances between point a and point b
+    
+    # calculate differences between A and B
     dx = xa - xb
     dy = ya - yb
     dz = za - zb
-    length = np.sqrt(np.square(dx) + np.square(dy) + np.square(dz))
-
-    return length
+    
+    # calculate distances between points using the square root of the sum of squares
+    distance = np.sqrt(np.square(dx) + np.square(dy) + np.square(dz))
+    	
+    return distance
 
 
 def utm_to_lambert(lon: np.array, lat: np.array) -> tuple:
-    """Convert WGS 84 UTM coordinates to a Lambert Conic Conformal Projection
+    """Convert UTM coordinates to a Lambert Conic Conformal Projection
     
     Parameters:
         lon (np.array): Vector containing longitudes
         lat (np.array): Vector containing latitudes
     
     Returns:
-        x, y (tuple(np.array, np.array)): tuple of two vectors with coordinates
+        x, y (np.array): tuple of two vectors with coordinates
 	"""
     
-    # convert utm coordinates (angles of degree) to radians
+    # convert utm coordinates to radians
     lon = np.radians(lon)
     lat = np.radians(lat)
     
@@ -208,7 +211,7 @@ def utm_to_lambert(lon: np.array, lat: np.array) -> tuple:
     lat0 = np.radians(47.5)
     
     # INCA grid: 701x401 km
-    # compensate for point of reference is in the middle of the grid
+    # compensate for point of reference (middle of the grid)
     # false easting: half of 701km = 350500m
     # false northing: half of 401km = 200500m
     x0 = 350500
@@ -224,7 +227,7 @@ def utm_to_lambert(lon: np.array, lat: np.array) -> tuple:
     p = R * F * (1 / np.tan(np.pi/4 + lat/2))**n
     p0 = R * F * (1 / np.tan(np.pi/4 + lat0/2))**n
 
-    # calculate lambert conic conformal x and y
+    # calculate x and y
     x = p * np.sin(n * (lon - lon0)) + x0
     y = p0 - p * np.cos(n * (lon - lon0)) + y0
 
@@ -233,17 +236,24 @@ def utm_to_lambert(lon: np.array, lat: np.array) -> tuple:
 
 def lambert_to_inca_idx(x: np.array, y: np.array) -> tuple:
     """Convert x and y of Lambert Conic Conformal Projection to INCA index
-    (rounded lambert coordinates)
     
     Parameters:
-        x (np.array): Vector containing x values in meter of Lambert Conic Conformal Projection
-        y (np.array): Vector containing y values in meter of in Lambert Conic Conformal Projection
+        x (np.array): Vector containing x values in meter of Lambert Conformal Conic Projection
+        y (np.array): Vector containing y values in meter of in Lambert Conformal Conic Projection
     
     Returns:
-        ix, iy (tuple(np.array, np.array)): tuple of indices for INCA data
+        ix, iy (np.array): indices for INCA data
 	"""
     
-    return np.round(x/1000, decimals = 0).astype(int), np.round(y/1000, decimals = 0).astype(int)
+    # convert from m to km
+    x /= 1000
+    y /= 1000
+    
+    # convert coordinates to INCA index (coordinates as int)
+    ix = x.astype(int)
+    iy = y.astype(int)
+    
+    return ix, iy
 
 
 def get_inca_data(datetimes: np.array, lon_a: np.array, lat_a: np.array, lon_b: np.array, lat_b: np.array, lengths: np.array) -> np.array:
@@ -269,8 +279,9 @@ def get_inca_data(datetimes: np.array, lon_a: np.array, lat_a: np.array, lon_b:
     window = 15
     inca_times = sorted([str(i * datetime.timedelta(seconds = window))[2:] for i in range(24*60//window)])
     
-    # generate times of LINK data
-    link_times = datetimes.map(lambda x: f'{x[-4:-2]}:{x[-2:]}')
+    # generate times of LINK data (last 4 chars of datetime vector)
+    time_func = np.vectorize(lambda x: f'{x[-4:-2]}:{x[-2:]}')
+    link_times = time_func(datetimes)
     
     # get INCA indices of LINK times
     idx_times = np.searchsorted(inca_times, link_times)
@@ -311,13 +322,7 @@ def get_inca_data(datetimes: np.array, lon_a: np.array, lat_a: np.array, lon_b:
 
 
 def prep() -> None:
-    """Data preparation for LINK config and transmissions
-    
-    Parameters:
-        file_config (pathlib.Path): Config File
-        file_trans (pathlib.Path): Transmissions File
-        dir_inca (pathlib.Path): INCA Directory
-	"""
+    """Data preparation for LINK config and transmissions"""
     
     _log('\n******************************** READ FILES ********************************')