rename : dir -> vect (unit vectors are reperesented by the variable name 'vect' rather than 'dir')

Scripts/preprocess_daily.py

@@ -334,21 +334,21 @@ class DailyPreprocessor():
             # 교차로의 모든 (from / to) edges
             inc_edges = [edge for edge in node.getIncoming() if edge.getFunction() == ''] # incoming edges
             out_edges = [edge for edge in node.getOutgoing() if edge.getFunction() == ''] # outgoing edges
-            # 교차로의 모든 (from / to) directions
-            inc_dirs = []
+            # 교차로의 모든 (from / to) directions (unit vector)
+            inc_vects = []
             for inc_edge in inc_edges:
                 start = inc_edge.getShape()[-2]
                 end = inc_edge.getShape()[-1]
-                inc_dir = np.array(end) - np.array(start)
-                inc_dir = inc_dir / (inc_dir ** 2).sum() ** 0.5
-                inc_dirs.append(inc_dir)
-            out_dirs = []
+                inc_vect = np.array(end) - np.array(start)
+                inc_vect = inc_vect / (inc_vect ** 2).sum() ** 0.5
+                inc_vects.append(inc_vect)
+            out_vects = []
             for out_edge in out_edges:
                 start = out_edge.getShape()[0]
                 end = out_edge.getShape()[1]
-                out_dir = np.array(end) - np.array(start)
-                out_dir = out_dir / (out_dir ** 2).sum() ** 0.5
-                out_dirs.append(out_dir)
+                out_vect = np.array(end) - np.array(start)
+                out_vect = out_vect / (out_vect ** 2).sum() ** 0.5
+                out_vects.append(out_vect)
             # 진입각, 진출각 불러오기
             if not pd.isna(row.inc_angle):
                 inc_angle = int(row.inc_angle)
@@ -356,13 +356,13 @@ class DailyPreprocessor():
                 # 방위각을 일반각으로 가공, 라디안 변환, 단위벡터로 변환
                 inc_angle = (-90 - inc_angle) % 360
                 inc_angle = inc_angle * np.pi / 180.
-                inc_dir_true = np.array([np.cos(inc_angle), np.sin(inc_angle)])
+                inc_vect_true = np.array([np.cos(inc_angle), np.sin(inc_angle)])
                 out_angle = (90 - out_angle) % 360
                 out_angle = out_angle * np.pi / 180.
-                out_dir_true = np.array([np.cos(out_angle), np.sin(out_angle)])
+                out_vect_true = np.array([np.cos(out_angle), np.sin(out_angle)])
                 # 매칭 엣지 반환
-                inc_index = np.array([np.dot(inc_dir, inc_dir_true) for inc_dir in inc_dirs]).argmax()
-                out_index = np.array([np.dot(out_dir, out_dir_true) for out_dir in out_dirs]).argmax()
+                inc_index = np.array([np.dot(inc_vect, inc_vect_true) for inc_vect in inc_vects]).argmax()
+                out_index = np.array([np.dot(out_vect, out_vect_true) for out_vect in out_vects]).argmax()
                 inc_edge_id = inc_edges[inc_index].getID()
                 out_edge_id = out_edges[out_index].getID()
                 self.match5.at[index, 'inc_edge'] = inc_edge_id