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data_loader_2d.py
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import torch
import torch.utils.data as data
import os
import pickle
import numpy as np
#import nltk
#from PIL import Image
import os.path
import random
from torch.autograd import Variable
import torch.nn as nn
import math
import gc
#N=number of environments; NP=Number of Paths
def load_dataset(N=100,NP=4000,folder='../data/simple/',s=0):
# load data as [path]
# for each path, it is
# [[input],[target],[env_id]]
obs = []
# add start s
for i in range(0,N):
#load obstacle point cloud
temp=np.fromfile(folder+'obs_cloud/obc'+str(i+s)+'.dat')
obs.append(temp)
obs = np.array(obs)
## calculating length of the longest trajectory
max_length=0
path_lengths=np.zeros((N,NP),dtype=np.int8)
for i in range(0,N):
for j in range(0,NP):
fname=folder+'env/'+'e'+str(i+s)+'/path'+str(j)+'.dat'
if os.path.isfile(fname):
path=np.fromfile(fname)
path=path.reshape(len(path)//2,2)
path_lengths[i][j]=len(path)
if len(path)> max_length:
max_length=len(path)
paths=np.zeros((N,NP,max_length,2), dtype=np.float32) ## padded paths
for i in range(0,N):
for j in range(0,NP):
fname=folder+'env/'+'e'+str(i+s)+'/path'+str(j)+'.dat'
if os.path.isfile(fname):
path=np.fromfile(fname)
path=path.reshape(len(path)//2,2)
for k in range(0,len(path)):
paths[i][j][k]=path[k]
path_data = []
for i in range(0,N):
for j in range(0,NP):
dataset=[]
targets=[]
env_indices=[]
if path_lengths[i][j]>0:
for m in range(0, path_lengths[i][j]-1):
data = np.concatenate( (paths[i][j][m], paths[i][j][path_lengths[i][j]-1]) ).astype(np.float32)
targets.append(paths[i][j][m+1])
dataset.append(data)
env_indices.append(i)
path_data.append([dataset, targets, env_indices])
# only return raw data (in order), follow below to randomly shuffle
return obs, path_data
# data=list(zip(dataset,targets))
# random.shuffle(data)
# dataset,targets=list(zip(*data))
# dataset and targets are both list
# here the first item of data is index in obs
# return obs, list(zip(*data))
def load_raw_dataset(N=100,NP=4000,s=0,sp=0,folder='../data/simple/'):
obc=np.zeros((N,7,2),dtype=np.float32)
temp=np.fromfile(folder+'obs.dat')
obs=temp.reshape(len(temp)//2,2)
temp=np.fromfile(folder+'obs_perm2.dat',np.int32)
perm=temp.reshape(77520,7)
## loading obstacles
for i in range(0,N):
for j in range(0,7):
for k in range(0,2):
obc[i][j][k]=obs[perm[i+s][j]][k]
obs = []
k=0
for i in range(s,s+N):
temp=np.fromfile(folder+'obs_cloud/obc'+str(i)+'.dat')
obs.append(temp)
obs = np.array(obs).astype(np.float32)
## calculating length of the longest trajectory
max_length=0
path_lengths=np.zeros((N,NP),dtype=np.int8)
for i in range(0,N):
for j in range(0,NP):
fname=folder+'env/'+'e'+str(i+s)+'/path'+str(j+sp)+'.dat'
if os.path.isfile(fname):
path=np.fromfile(fname)
path=path.reshape(len(path)//2,2)
path_lengths[i][j]=len(path)
if len(path)> max_length:
max_length=len(path)
paths=np.zeros((N,NP,max_length,2), dtype=np.float32) ## padded paths
for i in range(0,N):
for j in range(0,NP):
fname=folder+'env/'+'e'+str(i+s)+'/path'+str(j+sp)+'.dat'
if os.path.isfile(fname):
path=np.fromfile(fname)
path=path.reshape(len(path)//2,2)
for k in range(0,len(path)):
paths[i][j][k]=path[k]
return obc,obs,paths,path_lengths
#N=number of environments; NP=Number of Paths; s=starting environment no.; sp=starting_path_no
#Unseen_environments==> N=10, NP=2000,s=100, sp=0
#seen_environments==> N=100, NP=200,s=0, sp=4000
def load_test_dataset(N=100,NP=200, s=0,sp=4000, folder='../data/simple/'):
obc=np.zeros((N,7,2),dtype=np.float32)
temp=np.fromfile(folder+'obs.dat')
obs=temp.reshape(len(temp)//2,2)
temp=np.fromfile(folder+'obs_perm2.dat',np.int32)
perm=temp.reshape(77520,7)
## loading obstacles
for i in range(0,N):
for j in range(0,7):
for k in range(0,2):
obc[i][j][k]=obs[perm[i+s][j]][k]
obs = []
k=0
for i in range(s,s+N):
temp=np.fromfile(folder+'obs_cloud/obc'+str(i)+'.dat')
obs.append(temp)
obs = np.array(obs).astype(np.float32)
## calculating length of the longest trajectory
max_length=0
path_lengths=np.zeros((N,NP),dtype=np.int8)
for i in range(0,N):
for j in range(0,NP):
fname=folder+'env/'+'e'+str(i+s)+'/path'+str(j+sp)+'.dat'
if os.path.isfile(fname):
path=np.fromfile(fname)
path=path.reshape(len(path)//2,2)
path_lengths[i][j]=len(path)
if len(path)> max_length:
max_length=len(path)
paths=np.zeros((N,NP,max_length,2), dtype=np.float32) ## padded paths
for i in range(0,N):
for j in range(0,NP):
fname=folder+'env/'+'e'+str(i+s)+'/path'+str(j+sp)+'.dat'
if os.path.isfile(fname):
path=np.fromfile(fname)
path=path.reshape(len(path)//2,2)
for k in range(0,len(path)):
paths[i][j][k]=path[k]
return obc,obs,paths,path_lengths