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ss_human_action_data_gen_helper.py
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ss_human_action_data_gen_helper.py
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###########################################################################
#% FUNCTION:
#% WRITER: SOUMITRA SAMANTA DATE: 140717/170717/200717/120817/1407817/180917/050918
#% For bug and others mail me at soumitramath39@gmail.com
#%---------------------------------------------------------------------------------------------
#% INPUT:
#% OUTPUT:
#%--------------------------------------------------------------------------------------
#% EXAMPLE:
#%
##########################################################################
# Some header and necessary function import
import numpy as np
import time
import matplotlib as plt
from IPython.display import clear_output
from sklearn.preprocessing import normalize
##############################################################################################
import os
import sys
ss_lib_path = 'SS_PYLIBS/'
sys.path.insert(0, ss_lib_path)
#---------------------------------------------------------------------------------------------
from ss_computation import *
from ss_image_video import *
from ss_input_output import *
from ss_drawing import *
###########################################################################
#% FUNCTION:
#% WRITER: SOUMITRA SAMANTA DATE: 200717
#% For bug and others mail me at soumitramath39@gmail.com
#%--------------------------------------------------------------------------
#% INPUT:
#% OUTPUT:
#%---------------------------------------------------------------------------
#% EXAMPLE:
#%
##########################################################################
def ss_take_velocity_direction(int_velo, theta_thresh, velo_theta = [], num_theta_div = 10.0):
if(not(np.isscalar(velo_theta))):
velo_theta = np.mod(np.arctan2(int_velo[1, 0], int_velo[0, 0])*(180/np.pi), 360.0)
int_theta = velo_theta - theta_thresh/2.0
end_theta = velo_theta + theta_thresh/2.0
if(not(np.isscalar(num_theta_div))):
theta_div = 0.0
else:
theta_div = theta_thresh/num_theta_div
if(theta_div == 0.0):
velo_theta = np.array([int_theta, end_theta])
else:
velo_theta = np.arange(int_theta, end_theta, theta_div)
if velo_theta.size == 0:
velo_theta = np.array([int_theta, end_theta])
velo_theta = np.mod(velo_theta, 360.0)
velo_theta, idt = ss_take_sample(velo_theta, 'random', 1, 1)
Temp_pos_theta = velo_theta*(np.pi/180.0)
new_velo_dirc = np.zeros((2, 1))
new_velo_dirc[0,:] = np.cos(Temp_pos_theta)
new_velo_dirc[1,:] = np.sin(Temp_pos_theta)
return(new_velo_dirc)
def ss_take_wolf_velocity_direction(int_velo, theta_thresh, velo_theta = [], sample_flag='uniform'):
if(not(np.isscalar(velo_theta))):
velo_theta = np.mod(np.arctan2(int_velo[1, 0], int_velo[0, 0])*(180/np.pi), 360.0)
int_theta = velo_theta - theta_thresh/2.0
end_theta = velo_theta + theta_thresh/2.0
velo_theta = np.array([int_theta, end_theta])
velo_theta = np.mod(velo_theta, 360.0)
# print(velo_theta)
if sample_flag == 'random':
velo_theta, idt = ss_take_sample(velo_theta, 'random', 1, 1)
else:
velo_theta = velo_theta[0]
# print(velo_theta)
Temp_pos_theta = velo_theta*(np.pi/180.0)
new_velo_dirc = np.zeros((2, 1))
new_velo_dirc[0,:] = np.cos(Temp_pos_theta)
new_velo_dirc[1,:] = np.sin(Temp_pos_theta)
return(new_velo_dirc)
###########################################################################
#% FUNCTION:
#% WRITER: SOUMITRA SAMANTA DATE: 200717
#% For bug and others mail me at soumitramath39@gmail.com
#%--------------------------------------------------------------------------
#% INPUT:
#% OUTPUT:
#%---------------------------------------------------------------------------
#% EXAMPLE:
#%
##########################################################################
def ss_init_velocity_direction(num_points, int_theta = 0.0, end_theta = 360.0, theta_div = 1.0):
theta = np.arange(int_theta, end_theta, theta_div) # velocity direction range
velo_theta, idt = ss_take_sample(theta, 'random', num_points, 1) # random velocity direction
int_pos_velo = np.zeros((2,num_points))
Temp_pos_theta = velo_theta*(np.pi/180.0)
int_pos_velo[0,:] = np.cos(Temp_pos_theta)
int_pos_velo[1,:] = np.sin(Temp_pos_theta)
return(int_pos_velo)
###########################################################################
#% FUNCTION:
#% WRITER: SOUMITRA SAMANTA DATE: 200717
#% For bug and others mail me at soumitramath39@gmail.com
#%--------------------------------------------------------------------------
#% INPUT:
#% OUTPUT:
#%---------------------------------------------------------------------------
#% EXAMPLE:
#%
##########################################################################
def ss_boundary_constraints(pos, pos_velo, row, col, dx_row, dy_col, max_speed, max_steer_force):
steer = np.zeros((pos.shape))
des_dirc = np.zeros((pos.shape))
Temp_des_dirc = np.zeros((pos.shape[0], 4))
Temp_des_dirc1 = Temp_des_dirc.copy()
x = pos[0,0].copy()
y = pos[1,0].copy()
vx = pos_velo[0,0].copy()
vy = pos_velo[1,0].copy()
des_dirc_count = 0
if(x < dx_row):
if(vy == 0):
Temp_dirc = np.array([[max_speed], [max_speed]]).copy()
elif(abs(vy) > 1.0):
Temp_dirc = np.array([[max_speed], [vy]]).copy()
else:
Temp_dirc = np.array([[max_speed], [(max_speed)*np.sign(vy)]]).copy()
Temp_des_dirc[:,0] = np.reshape(Temp_dirc.copy(), (2,))
des_dirc_count += 1
if(x > row-dx_row-1):
if(vy == 0):
Temp_dirc = np.array([[-max_speed], [max_speed]]).copy()
elif(abs(vy) > 1.0):
Temp_dirc = np.array([[-max_speed], [vy]]).copy()
else:
Temp_dirc = np.array([[-max_speed], [(max_speed)*np.sign(vy)]]).copy()
Temp_des_dirc[:,1] = np.reshape(Temp_dirc.copy(), (2,))
des_dirc_count += 1
if(y < dy_col):
if(vx == 0):
Temp_dirc = np.array([[max_speed], [max_speed]]).copy()
elif(abs(vx) > 1.0):
Temp_dirc = np.array([[vx], [max_speed]]).copy()
else:
Temp_dirc = np.array([[(max_speed)*np.sign(vx)], [max_speed]]).copy()
Temp_des_dirc[:,2] = np.reshape(Temp_dirc.copy(), (2,))
des_dirc_count += 1
if(y > col-dy_col-1):
if(vx == 0):
Temp_dirc = np.array([[max_speed], [-max_speed]]).copy()
elif(abs(vx) > 1.0):
Temp_dirc = np.array([[vx], [-max_speed]]).copy()
else:
Temp_dirc = np.array([[(max_speed)*np.sign(vx)], [-max_speed]]).copy()
Temp_des_dirc[:,3] = np.reshape(Temp_dirc.copy(), (2,))
des_dirc_count += 1
if(des_dirc_count):
Temp_des_dirc1 = Temp_des_dirc.copy()
Temp_des_dirc = normalize(Temp_des_dirc, axis=0)
des_dirc = np.reshape(np.sum(Temp_des_dirc.copy(), axis=1), pos.shape)
des_dirc = normalize(des_dirc, axis=0)
des_dirc = max_speed*des_dirc
steer = des_dirc - pos_velo
steer = normalize(steer, axis=0)
steer = max_steer_force*steer
return(steer, des_dirc, Temp_des_dirc, Temp_des_dirc1)
###########################################################################
#% FUNCTION:
#% WRITER: SOUMITRA SAMANTA DATE: 200717
#% For bug and others mail me at soumitramath39@gmail.com
#%--------------------------------------------------------------------------
#% INPUT:
#% OUTPUT:
#%---------------------------------------------------------------------------
#% EXAMPLE:
#%
##########################################################################
def ss_neighbour_constraints(pos, pos_velo, neighbour_pos, neighbour_pos_velo, dist_thresh, max_speed, max_steer_force):
steer = np.zeros((pos.shape))
des_dirc = np.zeros(pos.shape)
Temp_des_dirc = np.zeros(neighbour_pos.shape)
Temp_des_dirc1 = Temp_des_dirc.copy()
num_neighbour_objects = neighbour_pos.shape[1]
dist_pos_comp_pos = ss_euclidean_dist(pos, neighbour_pos, 1)
des_dirc_count = 0
for snno in range(num_neighbour_objects):
if((dist_pos_comp_pos[0,snno] > 0.0) & (dist_pos_comp_pos[0,snno] < dist_thresh)):
Temp_diff = pos - np.reshape(neighbour_pos[:,snno], pos.shape)
Temp_des_dirc1[:,snno] = np.reshape(Temp_diff.copy(), (2,))
Temp_diff = normalize(Temp_diff, axis=0)#/dist_pos_comp_pos[0,snno]
Temp_des_dirc[:,snno] = np.reshape(Temp_diff.copy(), (2,))
des_dirc_count += 1
if(des_dirc_count):
des_dirc = np.reshape(np.sum(Temp_des_dirc.copy(), axis=1), pos.shape)
des_dirc = normalize(des_dirc, axis=0)
des_dirc = max_speed*des_dirc
steer = des_dirc - pos_velo
steer = normalize(steer, axis=0)
steer = max_steer_force*steer
return(steer, des_dirc, Temp_des_dirc, Temp_des_dirc1)
###########################################################################
#% FUNCTION:
#% WRITER: SOUMITRA SAMANTA DATE: 200717
#% For bug and others mail me at soumitramath39@gmail.com
#%--------------------------------------------------------------------------
#% INPUT:
#% OUTPUT:
#%---------------------------------------------------------------------------
#% EXAMPLE:
#%
##########################################################################
def ss_border_neighbour_constraints(pos, pos_velo, row, col, dx_row, dy_col, neighbour_pos, neighbour_pos_velo, neighbour_disjoint_threshold, max_speed, combined_max_steer_force):
steer = np.zeros((pos.shape))
des_dirc = np.zeros((pos.shape))
num_neighbour_objects = neighbour_pos.shape[1]
Temp_des_dirc = np.zeros((pos.shape[0], 4+num_neighbour_objects))
Temp_des_dirc1 = Temp_des_dirc.copy()
x = pos[0,0].copy()
y = pos[1,0].copy()
vx = pos_velo[0,0].copy()
vy = pos_velo[1,0].copy()
des_dirc_count = 0
if(x < dx_row):
if(vy == 0):
Temp_dirc = np.array([[max_speed], [max_speed]]).copy()
elif(abs(vy) > 1.0):
Temp_dirc = np.array([[max_speed], [vy]]).copy()
else:
Temp_dirc = np.array([[max_speed], [(max_speed)*np.sign(vy)]]).copy()
Temp_des_dirc[:,0] = np.reshape(Temp_dirc.copy(), (2,))
Temp_des_dirc1[:,0] = np.reshape(Temp_dirc.copy(), (2,))
des_dirc_count += 1
if(x > row-dx_row-1):
if(vy == 0):
Temp_dirc = np.array([[-max_speed], [max_speed]]).copy()
elif(abs(vy) > 1.0):
Temp_dirc = np.array([[-max_speed], [vy]]).copy()
else:
Temp_dirc = np.array([[-max_speed], [(max_speed)*np.sign(vy)]]).copy()
Temp_des_dirc[:,1] = np.reshape(Temp_dirc.copy(), (2,))
Temp_des_dirc1[:,1] = np.reshape(Temp_dirc.copy(), (2,))
des_dirc_count += 1
if(y < dy_col):
if(vx == 0):
Temp_dirc = np.array([[max_speed], [max_speed]]).copy()
elif(abs(vx) > 1.0):
Temp_dirc = np.array([[vx], [max_speed]]).copy()
else:
Temp_dirc = np.array([[(max_speed)*np.sign(vx)], [max_speed]]).copy()
Temp_des_dirc[:,2] = np.reshape(Temp_dirc.copy(), (2,))
Temp_des_dirc1[:,2] = np.reshape(Temp_dirc.copy(), (2,))
des_dirc_count += 1
if(y > col-dy_col-1):
if(vx == 0):
Temp_dirc = np.array([[max_speed], [-max_speed]]).copy()
elif(abs(vx) > 1.0):
Temp_dirc = np.array([[vx], [-max_speed]]).copy()
else:
Temp_dirc = np.array([[(max_speed)*np.sign(vx)], [-max_speed]]).copy()
Temp_des_dirc[:,3] = np.reshape(Temp_dirc.copy(), (2,))
Temp_des_dirc1[:,3] = np.reshape(Temp_dirc.copy(), (2,))
des_dirc_count += 1
dist_pos_comp_pos = ss_euclidean_dist(pos, neighbour_pos, 1)
for snno in range(num_neighbour_objects):
if((dist_pos_comp_pos[0,snno] > 0.0) & (dist_pos_comp_pos[0,snno] < neighbour_disjoint_threshold)):
Temp_diff = pos - np.reshape(neighbour_pos[:,snno], pos.shape)
Temp_des_dirc1[:,4+snno] = np.reshape(Temp_diff.copy(), (2,))
Temp_diff = normalize(Temp_diff, axis=0)#/dist_pos_comp_pos[0,snno]
Temp_des_dirc[:,4+snno] = np.reshape(Temp_diff.copy(), (2,))
des_dirc_count += 1
if(des_dirc_count):
Temp_des_dirc = normalize(Temp_des_dirc, axis=0)
des_dirc = np.reshape(np.sum(Temp_des_dirc.copy(), axis=1), pos.shape)
des_dirc = normalize(des_dirc, axis=0)
des_dirc = max_speed*des_dirc
steer = des_dirc - pos_velo
steer = normalize(steer, axis=0)
steer = combined_max_steer_force*steer
return(steer, des_dirc, Temp_des_dirc, Temp_des_dirc1)
###########################################################################
#% FUNCTION:
#% WRITER: SOUMITRA SAMANTA DATE: 200717
#% For bug and others mail me at soumitramath39@gmail.com
#%--------------------------------------------------------------------------
#% INPUT:
#% OUTPUT:
#%---------------------------------------------------------------------------
#% EXAMPLE:
#%
##########################################################################
def ss_check_direction(pos, row, col, dx_row, dy_col, neighbour_pos, neighbour_disjoint_threshold):
num_neighbour_objects = neighbour_pos.shape[1]
x = pos[0,0].copy()
y = pos[1,0].copy()
dirc_change_flag = 0
if(x < dx_row):
dirc_change_flag += 1
if(x > row-dx_row-1):
dirc_change_flag += 1
if(y < dy_col):
dirc_change_flag += 1
if(y > col-dy_col-1):
dirc_change_flag += 1
dist_pos_comp_pos = ss_euclidean_dist(pos, neighbour_pos, 1)
for snno in range(num_neighbour_objects):
if((dist_pos_comp_pos[0,snno] > 0.0) & (dist_pos_comp_pos[0,snno] < neighbour_disjoint_threshold)):
dirc_change_flag += 1
return(dirc_change_flag)
###########################################################################
#% FUNCTION:
#% WRITER: SOUMITRA SAMANTA DATE: 200717
#% For bug and others mail me at soumitramath39@gmail.com
#%--------------------------------------------------------------------------
#% INPUT:
#% OUTPUT:
#%---------------------------------------------------------------------------
#% EXAMPLE:
#%
##########################################################################
def ss_check_bounday(pos, row, col, dx_row, dy_col):
new_pos = pos.copy()
if(pos[0,0] < dx_row):
new_pos[0,0] = dx_row
if(pos[0,0] > row-dx_row-1):
new_pos[0,0] = row-dx_row-1
if(pos[1,0] < dy_col):
new_pos[1,0] = dy_col
if(pos[1,0] > col-dy_col-1):
new_pos[1,0] = col-dy_col-1
return new_pos
def ss_chasing_random_trajectory(int_pos, int_pos_velo, max_speed, max_steer_force, row, column, dx_row, dx_column, tajectory_length, velo_theta_thresh, disjoint_threshold):
#how frequent object motion direction (AOM) will be changed. It depends on the chasing subtlety (CS)
# If CS is low then AOM will change less frequent and vise versa
dirc_change_flag = np.round(np.sqrt(2.2*np.sqrt(360.0)) - np.sqrt(np.sqrt(velo_theta_thresh[0, 1])))#6#np.round(1.3*np.sqrt(360.0) - np.sqrt(velo_theta_thresh[0, 1]))
num_points = int_pos.shape[1]
pos = np.zeros((2, num_points, tajectory_length)) #variable for object positions
pos_velo = np.zeros((2, num_points, tajectory_length)) #variable for object velocity direction
neighbour_steer_dirc = np.zeros((2, num_points, tajectory_length)) #variable for steering direction (based on neighbour objects)
boundary_steer_dirc = np.zeros((2, num_points, tajectory_length))#variable for steering direction (based on boundary condition)
pos[:,:,0] = int_pos
pos_velo[:,:,0] = int_pos_velo
avegrate_max_speed = np.mean(max_speed)
avegrate_min_speed = np.mean(max_speed)/2
#################################
for snt in range(1, tajectory_length):
# print('F#-',snt)
sheep_pos = np.reshape(pos[:,0,snt-1], (pos.shape[0], 1)).copy()
wolf_pos = np.reshape(pos[:,1,snt-1], (pos.shape[0], 1)).copy()
wolf_sheep_angle = np.mod(ss_anglefrom2points(wolf_pos, sheep_pos)*(180/np.pi), 360)
for snp in range(num_points):
prev_pos_all = np.reshape(pos[:,:,snt-1], (pos.shape[0], pos.shape[1])).copy()
prev_pos = np.reshape(pos[:,snp,snt-1], (pos.shape[0], 1)).copy()
prev_pos_velo_all = np.reshape(pos_velo[:,:,snt-1], (pos_velo.shape[0], pos_velo.shape[1])).copy()
prev_pos_velo = np.reshape(pos_velo[:,snp,snt-1], (pos_velo.shape[0], 1)).copy()
boundary_max_steer_force = max_steer_force[0, snp].copy()
neighbour_max_steer_force = max_steer_force[0, snp].copy()
combined_max_steer_force = 1.2*max_steer_force[0, snp].copy()
neighbour_disjoint_threshold = disjoint_threshold[0, snp].copy()
boundary_dx_row = disjoint_threshold[0, snp].copy()#dx_row
boundary_dx_column = disjoint_threshold[0, snp].copy()#dx_column
if(snp == 0):
neighbour_disjoint_threshold = 1.*disjoint_threshold[0, snp].copy()
boundary_dx_row = 1.2*boundary_dx_row
boundary_dx_column = 1.2*boundary_dx_column
dirc_change_flag1 = ss_check_direction(prev_pos, row, column, boundary_dx_row, boundary_dx_column, prev_pos_all, neighbour_disjoint_threshold)
if(dirc_change_flag1 == 0.0):
if(np.mod(snt, dirc_change_flag+snp) == 0):#change the AOM dependns on the object number as well
if((snp == 1)):
prev_pos_velo = prev_pos_velo#max_speed[0, snp]*ss_take_velocity_direction(prev_pos_velo.copy(), velo_theta_thresh[0, snp-1].copy()) #take random velocity direction
else:
prev_pos_velo = max_speed[0, snp]*ss_take_velocity_direction(prev_pos_velo.copy(), velo_theta_thresh[0, snp].copy(), [], velo_theta_thresh[0, snp].copy()) #take random velocity direction
if(snp == 1):
prev_pos_all[:,0] = prev_pos_all[:,1].copy()# To avoid sheep destruction
if(velo_theta_thresh[0, snp] <= 180.0):#initially 180
wolf_dirc_change_flag = 1
else:
wolf_dirc_change_flag = np.round((np.sqrt(1.5*velo_theta_thresh[0, snp])))#initially 1.5
if(np.mod(snt, wolf_dirc_change_flag) == 0):
prev_pos_velo = ss_take_wolf_velocity_direction([], velo_theta_thresh[0, snp].copy(), wolf_sheep_angle)
prev_pos_velo = normalize(prev_pos_velo, axis=0)
prev_pos_velo = max_speed[0, snp]*prev_pos_velo
Temp_boundary_steer_dirc, Temp_boundary_dirc, Temp_boundary_des_dirc, Temp_boundary_des_dirc1 = ss_border_neighbour_constraints(prev_pos, prev_pos_velo, row, column, boundary_dx_row, boundary_dx_column, prev_pos_all, prev_pos_velo_all, neighbour_disjoint_threshold, max_speed[0, snp], combined_max_steer_force)
Temp_neighbour_steer_dirc = np.zeros((2,1))
new_pos_accl = Temp_neighbour_steer_dirc + Temp_boundary_steer_dirc
new_pos_velo = prev_pos_velo + new_pos_accl
new_pos_velo = normalize(new_pos_velo, axis=0)
new_max_speed = max_speed[0, snp].copy()
wolf_sheep_distance = ss_euclidean_dist(pos[:,0,snt-1], pos[:,1,snt-1], 1)
if(snp == 1):
if(wolf_sheep_distance < neighbour_disjoint_threshold):
new_max_speed -= np.exp(-np.sqrt(np.sqrt(velo_theta_thresh[0, snp]/20)))#2
new_max_speed = max(avegrate_min_speed, new_max_speed)#max(3, new_max_speed-1) #270717
max_speed[0, snp] = new_max_speed
else:
new_max_speed = min(avegrate_max_speed, new_max_speed+1)#min(5, new_max_speed+1)#270717
max_speed[0, snp] = new_max_speed
new_pos_velo = new_max_speed*new_pos_velo
new_pos = np.round(prev_pos + new_pos_velo)
new_pos = ss_check_bounday(new_pos, row, column, dx_row/2., dx_column/2.)
pos[:,snp,snt] = np.reshape(new_pos, (new_pos.shape[0],)).copy()
pos_velo[:,snp,snt] = np.reshape(new_pos_velo, (new_pos_velo.shape[0],)).copy()
return pos, pos_velo
def ss_pushing_id(neighbour_pos, row, col, dx_row, dy_col):
Temp_dist = ss_euclidean_dist(neighbour_pos, neighbour_pos, 1)
np.fill_diagonal(Temp_dist, np.max(Temp_dist)+2)
#Temp_dist_sort = np.sort(Temp_dist, axis = None)
#min_idx = np.where(Temp_dist == Temp_dist_sort[np.int(np.prod(Temp_dist.shape)/4)])
min_idx = np.where(Temp_dist == Temp_dist.min())
pushing_id = np.array([min_idx[0][0], min_idx[1][0]])
return(pushing_id)
def ss_pushing_random_trajectory(int_pos, int_pos_velo, pushing_subtlety,
num_pushing, pushing_contact_distance, pushing_delay,
push_interval, max_speed, max_steer_force,
row, column, dx_row, dx_column, object_radius, tajectory_length,
velo_theta_thresh, disjoint_threshold):
pusher_halt = 10
dirc_change_flag = 5
num_points = int_pos.shape[1]
pos = np.zeros((2, num_points, tajectory_length)) #variable for object positions
pos_velo = np.zeros((2, num_points, tajectory_length)) #variable for object velocity direction
neighbour_steer_dirc = np.zeros((2, num_points, tajectory_length)) #variable for steering direction (based on neighbour objects)
boundary_steer_dirc = np.zeros((2, num_points, tajectory_length))#variable for steering direction (based on boundary condition)
pos[:,:,0] = int_pos
pos_velo[:,:,0] = int_pos_velo
avegrate_max_speed = np.mean(max_speed)
avegrate_min_speed = np.mean(max_speed)/2
step_size = (tajectory_length - 2*push_interval - (push_interval+pushing_delay+pusher_halt)*num_pushing)/(num_pushing)
T = np.array(np.arange(push_interval, tajectory_length - (push_interval+pushing_delay+pusher_halt)-step_size, step_size+push_interval))
push_frame_info = np.zeros((3, num_pushing))
push_frame_info[0,:] = T.copy()
push_frame_info[1,:] = push_frame_info[0,:] + step_size + push_interval - 1
push_count = 0
pushing_start_flag = 1
pushing_halt_flag = 0
pushing_delay_count = 0
pushing_end_flag = 0
pusher_halt_count = 0
push_id = np.zeros((2, num_pushing))# np.array([[0, 1, 2], [1, 2, 3]])
push_id = push_id.astype('int')
#################################
for snt in range(1, tajectory_length):
# print('F#-',snt)
for snp in range(num_points):
prev_pos_all = np.reshape(pos[:,:,snt-1], (pos.shape[0], pos.shape[1])).copy()
prev_pos = np.reshape(pos[:,snp,snt-1], (pos.shape[0], 1)).copy()
prev_pos_velo_all = np.reshape(pos_velo[:,:,snt-1], (pos_velo.shape[0], pos_velo.shape[1])).copy()
prev_pos_velo = np.reshape(pos_velo[:,snp,snt-1], (pos_velo.shape[0], 1)).copy()
boundary_max_steer_force = max_steer_force[0, snp].copy()
neighbour_max_steer_force = max_steer_force[0, snp].copy()
combined_max_steer_force = 1.2*max_steer_force[0, snp].copy()
neighbour_disjoint_threshold = disjoint_threshold[0, snp].copy()
boundary_dx_row = disjoint_threshold[0, snp].copy()#dx_row
boundary_dx_column = disjoint_threshold[0, snp].copy()#dx_column
new_max_speed = max_speed[0, snp].copy()
##############PUISHING LOGIC####################
if(push_count < num_pushing):
if((snt >= push_frame_info[0, push_count]) and (snt < push_frame_info[1, push_count])):
if(snt == push_frame_info[0, push_count]):
Temp_push_id = ss_pushing_id(prev_pos_all.copy(), row, column, boundary_dx_row, boundary_dx_column)
push_id[:, push_count] = Temp_push_id.copy()
pusher_pos = np.reshape(prev_pos_all[:,push_id[0, push_count]], (prev_pos_all.shape[0], 1)).copy()
pushee_pos = np.reshape(prev_pos_all[:,push_id[1, push_count]], (prev_pos_all.shape[0], 1)).copy()
Temp_dist = np.linalg.norm(pusher_pos - pushee_pos)
pusher_pushee_dist_count = Temp_dist//ss_denominator_check(max_speed[0, push_id[0, push_count]]) + 1
pusher_speed_during_pushing = Temp_dist/pusher_pushee_dist_count
#FOR PUSHER MOTION
if(snp == push_id[0, push_count]):
if(pushing_start_flag):#start pushing
pusher_pos = np.reshape(pos[:,push_id[0, push_count],snt-1], (pos.shape[0], 1)).copy()
pushee_pos = np.reshape(pos[:,push_id[1, push_count],snt-1], (pos.shape[0], 1)).copy()
Temp_dist = np.linalg.norm(pusher_pos - pushee_pos)
#if(Temp_dist >= 2*object_radius + 2*max_speed[0, push_id[0, push_count]] + pushing_contact_distance):
if(Temp_dist > 2*object_radius+2 + pushing_contact_distance):
pusher_pushee_angle = np.mod(ss_anglefrom2points(pusher_pos, pushee_pos, 1), 360)
#prev_pos_velo = ss_take_velocity_direction([], velo_theta_thresh[0, push_id[0, push_count]].copy(), pusher_pushee_angle)
prev_pos_velo = ss_take_velocity_direction([], 0.0, pusher_pushee_angle)
prev_pos_velo = normalize(prev_pos_velo, axis=0)
prev_pos_velo = max_speed[0, snp]*prev_pos_velo
max_speed[0, push_id[1, push_count]] = 0
if((Temp_dist-2*object_radius-pushing_contact_distance) < pusher_speed_during_pushing):
new_max_speed = Temp_dist-2*object_radius-pushing_contact_distance
else:
new_max_speed = pusher_speed_during_pushing
else:#end pusher movement
pushing_start_flag = 0
pushing_halt_flag = 1
pushing_delay_count = 0
new_max_speed = 0.0
elif(pushing_halt_flag):#pushing halt
if(pushing_delay_count < pushing_delay):
max_speed[0, push_id[0, push_count]] = 0
max_speed[0, push_id[1, push_count]] = 0
pushing_delay_count += 1
else:#start pushee movement
pusher_halt_count = 0
pushing_start_flag = 0
pushing_halt_flag = 0
new_max_speed = 0.0#1
max_speed[0, push_id[0, push_count]] = new_max_speed
push_frame_info[2, push_count] = snt
pushing_end_flag = 1
pusher_pos = np.reshape(pos[:,push_id[0, push_count],snt-1], (pos.shape[0], 1)).copy()
pushee_pos = np.reshape(pos[:,push_id[1, push_count],snt-1], (pos.shape[0], 1)).copy()
pusher_pushee_angle = np.mod(ss_anglefrom2points(pusher_pos, pushee_pos, 1), 360)
pushee_velo = avegrate_max_speed*ss_take_velocity_direction([], pushing_subtlety, pusher_pushee_angle, [])
pos_velo[:,push_id[1, push_count],snt-1] = np.reshape(pushee_velo.copy(),(pos_velo.shape[0],))#pos_velo[:,push_id[0, push_count],snt-1].copy()
#print('TTTT-2:{}\n' .format(pos_velo[:,push_id[1, push_count],snt-1]))
max_speed[0, push_id[1, push_count]] = avegrate_max_speed - new_max_speed
else:
new_max_speed = max_speed[0, push_id[0, push_count]].copy()
new_max_speed = min(new_max_speed+0.5, avegrate_max_speed)
max_speed[0, push_id[0, push_count]] = new_max_speed.copy()
if(snt < push_frame_info[2, push_count] + pusher_halt):
prev_pos_velo = np.reshape(pos_velo[:,push_id[1, push_count],snt-1], (pos_velo.shape[0], 1)).copy()
if((pusher_halt_count < pusher_halt)):
max_speed[0, push_id[0, push_count]] = 0
pusher_halt_count += 1
#FOR PUSHEE MOTION
elif(snp == push_id[1, push_count]):
if(pushing_end_flag):
new_max_speed = max_speed[0, push_id[1, push_count]]
max_speed[0, push_id[1, push_count]] = min(new_max_speed+1, avegrate_max_speed)
prev_pos_velo = np.reshape(pos_velo[:,push_id[1, push_count],snt-1], (pos_velo.shape[0], 1)).copy()
prev_pos_velo_all = np.reshape(pos_velo[:,:,snt-1], (pos_velo.shape[0], pos_velo.shape[1])).copy()
else:
if((pushing_halt_flag>0) and (pushing_delay < 1)):
new_max_speed = max_speed[0, push_id[1, push_count]]
max_speed[0, push_id[1, push_count]] = min(new_max_speed+1, avegrate_max_speed)
prev_pos_velo = np.reshape(pos_velo[:,push_id[1, push_count],snt-1], (pos_velo.shape[0], 1)).copy()
prev_pos_velo_all = np.reshape(pos_velo[:,:,snt-1], (pos_velo.shape[0], pos_velo.shape[1])).copy()
else:
new_max_speed = 0
else:
if((pushing_start_flag>0) or (pushing_halt_flag>0)):
new_max_speed = 0
elif((pushing_start_flag==0) and (pushing_halt_flag==0) and (pushing_end_flag>0.0) and (snt<push_frame_info[2, push_count]+pusher_halt)):
new_max_speed = 0
else:
new_max_speed = avegrate_max_speed
if(snt == push_frame_info[2, push_count]+pusher_halt):
prev_pos_velo = np.reshape(int_pos_velo[:,snp], (pos_velo.shape[0], 1)).copy()
if(snt == push_frame_info[1, push_count]):
pushing_end_flag = 0
pushing_start_flag = 1
push_count += 1
if((pushing_end_flag>0.0) and (snp == push_id[1, push_count]) ):
Temp_boundary_steer_dirc, Temp_boundary_dirc, Temp_boundary_des_dirc, Temp_boundary_des_dirc1 = ss_border_neighbour_constraints(prev_pos, prev_pos_velo, row, column, boundary_dx_row, boundary_dx_column, prev_pos_all, prev_pos_velo_all, 0.0, max_speed[0, snp], combined_max_steer_force)#neighbour_disjoint_threshold=0.0
else:
Temp_boundary_steer_dirc, Temp_boundary_dirc, Temp_boundary_des_dirc, Temp_boundary_des_dirc1 = ss_border_neighbour_constraints(prev_pos, prev_pos_velo, row, column, boundary_dx_row, boundary_dx_column, prev_pos_all, prev_pos_velo_all, neighbour_disjoint_threshold, max_speed[0, snp], combined_max_steer_force)
Temp_neighbour_steer_dirc = np.zeros((2,1))
new_pos_accl = Temp_neighbour_steer_dirc + Temp_boundary_steer_dirc
new_pos_velo = prev_pos_velo + new_pos_accl
new_pos_velo = normalize(new_pos_velo, axis=0)
new_pos_velo = new_max_speed*new_pos_velo
new_pos = np.round(prev_pos + new_pos_velo)
new_pos = ss_check_bounday(new_pos, row, column, dx_row/2., dx_column/2.)
pos[:,snp,snt] = np.reshape(new_pos, (new_pos.shape[0],)).copy()
pos_velo[:,snp,snt] = np.reshape(new_pos_velo, (new_pos_velo.shape[0],)).copy()
return pos, pos_velo, push_frame_info, push_id