def count_steps(data): print 'count_steps' plot_data(data) mag = vector_magnitude(data) plot_mag(mag) average = moving_average(data, 100) plot_mag(average) num_steps = 0 ''' This function counts the number of steps in data and returns the number of steps ''' i = 0 found = False stepArray = [] for x in average: if (x >= 4 and x <= 4.03): if found == False: num_steps = num_steps + 1 stepArray.append(i) found = True else: found = False i = i + 1 plot_steps(average, stepArray) return num_steps
def sum_sensors(self, prey_list, predator_list): vectors = [] cohesion_vector = self.cohesion_vector(prey_list) vectors.append(util.multiply_vector(cohesion_vector, self.COHESION_WEIGHT)) follow_vector = self.follow_vector(prey_list) vectors.append(util.multiply_vector(follow_vector, self.FOLLOW_WEIGHT)) separation_vector = self.separation_vector(prey_list) vectors.append(util.multiply_vector(separation_vector, self.SEPARATION_WEIGHT)) predator_vector = self.predator_vector(predator_list) vectors.append(util.multiply_vector(predator_vector, self.PREDATOR_WEIGHT)) vectors.append(self.edge_repulsion_sensor()) x_comp = 0 y_comp = 0 for x, y in vectors: x_comp += x y_comp += y vector_magnitude = util.vector_magnitude((x_comp, y_comp)) if vector_magnitude > self.MAX_SPEED: x_comp /= vector_magnitude y_comp /= vector_magnitude x_comp *= self.MAX_SPEED y_comp *= self.MAX_SPEED return (x_comp, y_comp)
def sum_sensors(self, prey_list, predator_list): vectors = [] prey_pos_vector = self.get_closest_prey_position(prey_list) vectors.append(util.multiply_vector(prey_pos_vector, self.PREY_POS_WEIGHT)) prey_vel_vector = self.get_closest_prey_velocity(prey_list) vectors.append(util.multiply_vector(prey_vel_vector, self.PREY_VEL_WEIGHT)) vectors.append(util.multiply_vector(self.edge_repulsion_sensor(), 100)) print vectors print """Prey_Pos: {} Prey_Vel: {} Repulsion: {}""".format(*vectors) x_comp = 0 y_comp = 0 for x, y in vectors: x_comp += x y_comp += y vector_magnitude = util.vector_magnitude((x_comp, y_comp)) if vector_magnitude > self.MAX_SPEED: x_comp /= vector_magnitude y_comp /= vector_magnitude x_comp *= self.MAX_SPEED y_comp *= self.MAX_SPEED return (x_comp, y_comp)
def count_steps(data): print 'count_steps' # Different Algo num_steps = 0 plot_data(data) plot_mag(vector_magnitude(data)) plot_mag(moving_average((data),230)) ''' This function counts the number of steps in data and returns the number of steps ''' return num_steps
def run(): # Get data file_name = "data.txt" # Change to your file name data = iosParser.get_data(file_name) # print data number_of_steps = count_steps(data) magnitudes = util.vector_magnitude(data) plot_mag(magnitudes) moving_avg = util.moving_average(magnitudes, 10) plot_mag(moving_avg) print "Number of steps counted are :", number_of_steps
def count_steps(data): print "Accelerometer data graph" plot_data(data) mag = vector_magnitude(data) plot_mag(mag) average = moving_average(data, 10) plot_mag(average) num_steps = 0 ''' ADD YOUR CODE HERE. This function counts the number of steps in data and returns the number of steps ''' return num_steps
def sum_sensors(self, prey_list, predator_list): vectors = [] prey_pos_vector = self.get_closest_prey_position(prey_list) vectors.append( util.multiply_vector(prey_pos_vector, self.PREY_POS_WEIGHT)) prey_vel_vector = self.get_closest_prey_velocity(prey_list) vectors.append( util.multiply_vector(prey_vel_vector, self.PREY_VEL_WEIGHT)) vectors.append(util.multiply_vector(self.edge_repulsion_sensor(), 100)) print vectors print """Prey_Pos: {} Prey_Vel: {} Repulsion: {}""".format(*vectors) x_comp = 0 y_comp = 0 for x, y in vectors: x_comp += x y_comp += y vector_magnitude = util.vector_magnitude((x_comp, y_comp)) if vector_magnitude > self.MAX_SPEED: x_comp /= vector_magnitude y_comp /= vector_magnitude x_comp *= self.MAX_SPEED y_comp *= self.MAX_SPEED return (x_comp, y_comp)