dead code

CoLo-AT/simulation_process/data_generation.py

-#!/usr/bin/env python3
-# -*- coding: utf-8 -*-
-"""
-Created on Tue Feb 13 16:11:36 2018
-
-@author: william
-"""
-
-class DataGenerator():
-    def init_(self):
-        pass
-    
-    	def within_map(self, loc): 
-		'''
-		For runtime self_generated data, 
-		Parameters:
-			loc: array, shape = (2,1) 
-				robot's location for [x, y]
-		Return: Boolean 
-			True if within the map, False if not 
-		'''
-		center_point = [0,0]
-		if sqrt(pow(loc[0]-center_point[0], 2)+pow(loc[1]-center_point[1], 2)) > d_max:
-			return False
-		else:
-			return True
-	def generate_propgation_data(self, current_loc, current_orientation):
-
-		'''
-		To generate propagtion data randomly so that it will run within predefined map *assuming orientation is perfect
-		Parameters:
-			current_loc: array, shape = (2,1) 
-				robot's current location for [x, y]
-			current_orientation: float
-				robot's current orientation in radian
-		Return array, shape = (2,1) 
-		'''
-		[meas_v, meas_a_v] = [random.uniform(-max_v,max_v), random.uniform(-max_a_v, max_a_v)]
-		actual_v  = meas_v + random.normal(0, sqrt(var_u_v))
-		pre_update_position = [current_loc[0] + cos(current_orientation)*actual_v*delta_t, current_loc[1] + sin(current_orientation)*actual_v*delta_t]
-
-		while(not within_map(pre_update_position)):
-			[meas_v, meas_a_v] = [random.uniform(-max_v,max_v), random.uniform(-max_a_v, max_a_v)]
-			actual_v  = meas_v + random.normal(0, sqrt(var_u_v))
-			pre_update_position = [current_loc[0] + cos(current_orientation)*actual_v*delta_t, current_loc[1] + sin(current_orientation)*actual_v*delta_t]
-		
-		orientation = current_orientation + meas_a_v*delta_t
-		actual_loc = pre_update_position
-		return [actual_v, meas_v, orientation, actual_loc]
-
-    def generate_measurement_data(self, observer_loc, observee_loc, observer_orientation):
-        	delta_x = observer_loc[0] - observee_loc[0]
-        	delta_y = observer_loc[1] - observee_loc[1]
-        	dis = sqrt(delta_y*delta_y + delta_x*delta_x) + random.normal(0, sqrt(var_dis))
-        	bearing = atan2(delta_y, delta_x) + random.normal(0, sqrt(var_angle)) - observer_orientation
-        	return [dis, bearing]