def cluster_labels(num_clusters=3):
from sklearn.cluster import KMeans
object_labels = get_baseline_labels()
object_key_to_array_index = {}
X = []
object_group_name = 'g3db_instances_non_test_version7'
for object_name in get_grasping_object_name_list(object_group_name):
sum_value = sum(object_labels[object_name])
object_labels[object_name] = [
x / sum_value for x in object_labels[object_name]
]
object_key_to_array_index[object_name] = len(X)
X.append(object_labels[object_name])
kmeans = KMeans(n_clusters=num_clusters, random_state=0).fit(X)
transormed_X = kmeans.transform(X)
for object_name in get_grasping_object_name_list(object_group_name):
print repr(kmeans.labels_[object_key_to_array_index[object_name]]
) + ':' + object_name + ':' + repr(
transormed_X[object_key_to_array_index[object_name]])
baseline_result_dir = 'data_low_friction_table_exp_ver6'
grasping_ros_mico_path = get_grasping_ros_mico_path()
label_file_name = grasping_ros_mico_path + "/" + baseline_result_dir + "/baseline_results/kmeans_object_labels_g3db_instances_trial.csv"
with open(label_file_name, 'w') as f:
for object_name in get_grasping_object_name_list(object_group_name):
f.write(
object_name + "," +
repr(kmeans.labels_[object_key_to_array_index[object_name]]) +
'\n')
return kmeans
def generate_cylinder_g3db_mixed_belief_ver5_commands_old(
type='1001-84_weighted'):
object_list = get_grasping_object_name_list('coffee_yogurt_cup')
object_list = object_list + ['9cm', '8cm']
belief_type = 'UNIFORM_WITH_STATE_IN'
dir_prefix = './results/despot_logs/low_friction_table/multiObjectType/'
if type in ['cylinder', 'cylinder_regression']:
config_file_name = 'Ver5MultiCylinderObject'
config_file_prefix = 'cylinder'
dir_name = './results/despot_logs/low_friction_table/multiObjectType/belief_uniform_cylinder_7_8_9_reward100_penalty10'
belief_name = 'cylinder_7_8_9'
object_list = [
'9cm', '8cm', '7cm', '75mm', '85mm', 'G3DB84_yogurtcup_final'
]
if type == 'cylinder_1001':
config_file_name = 'Ver5MultiCylinder-1001'
config_file_prefix = 'cylinderCup'
dir_name = './results/despot_logs/low_friction_table/multiObjectType/belief_uniform_cylinder_8_9_1001_reward100_penalty10'
belief_name = 'cylinder_8_9_1001'
if type in ['1001-84_weighted', '1001-84']:
config_file_name = 'Ver5Multi1001-84'
config_file_prefix = 'yoghurtCup'
dir_name = dir_prefix + 'belief_uniform_g3db_1_84_reward100_penalty10'
belief_name = '1001-84'
object_list = get_grasping_object_name_list('coffee_yogurt_cup')
if 'regression' in type:
config_file_prefix = config_file_prefix + "/use_regression"
dir_name = dir_name + "/use_regression"
if 'weighted' in type:
config_file_prefix = config_file_prefix + "/weighted_belief"
dir_name = dir_name + "/icp_score_weighted"
belief_name = belief_name + "/weighted_belief"
generate_grasping_params_file(object_list, config_file_name, dir_name,
belief_type, belief_name, config_file_prefix)
def generate_g3db_belief_despot_commands(ver="", belief='Multi'):
object_list = get_grasping_object_name_list('coffee_yogurt_cup')
for filetype in ['']:
for interface_type in [
"vrep_model", "data_model", "vrep_model_fixed_distribution",
"data_model_fixed_distribution"
]:
#generate_params_file(interface_type + "_9cm_low_friction" + filetype + ".yaml", 'despot_without_display')
if ver == 'Ver5':
interface_type = interface_type + "_ver5"
interface_type_ = "" if 'vrep' in interface_type else "Data"
dir_extenstion = "/simulator" if 'vrep' in interface_type else ""
for object_type in object_list:
ans = get_default_params()
if belief == 'Multi':
ans['output_dir'] = './results/despot_logs/low_friction_table/multiObjectType/belief_uniform_g3db_1_84_reward100_penalty10' + dir_extenstion
else:
ans['output_dir'] = './results/despot_logs/low_friction_table/multiObjectType/belief_uniform_g3db_single_reward100_penalty10' + dir_extenstion
ans['file_name_prefix'] = 'Table_scene_' + object_type
ans['config_file'] = 'config_files/' + "Vrep" + interface_type_ + "Interface" + ver + belief + "1001-84Test" + object_type + "_low_friction_table.yaml"
ans['additional_params'] = '--number=-2 -l CAP'
ans['belief_type'] = 'UNIFORM_WITH_STATE_IN'
if belief == 'Multi':
file_name = interface_type + "_multi_object_coffee_yogurt_" + object_type + "_low_friction" + filetype + ".yaml"
else:
file_name = interface_type + "_single_object_coffee_yogurt_" + object_type + "_low_friction" + filetype + ".yaml"
if 'fixed_distribution' in file_name:
ans['additional_params'] = '-l CAP --number='
ans['output_dir'] = ans[
'output_dir'] + "/fixed_distribution"
output = yaml.dump(ans, Dumper=Dumper)
f = open(file_name, 'w')
f.write(output)
def get_object_filenames(self, object_file_name):
ans = []
self.pure_shape = False
if (object_file_name == 'all_cylinders'):
self.pure_shape = True
ans = get_grasping_object_name_list(object_file_name)
else:
if (os.path.isdir(object_file_name)):
files = [
os.path.join(object_file_name, f)
for f in os.listdir(object_file_name) if '.obj' in f
]
for file in files:
ans.append(file)
elif (not os.path.exists(object_file_name)):
obj_dir_name = os.path.dirname(object_file_name)
file_prefix = os.path.basename(object_file_name)
files = [
os.path.join(obj_dir_name, f)
for f in os.listdir(obj_dir_name)
if f.startswith(file_prefix)
]
for file in files:
if '.obj' in file:
ans.append(file)
else:
ans = [object_file_name]
return ans
def get_object_list(object_group_name):
if type(object_group_name) is str:
object_list = get_grasping_object_name_list(object_group_name)
object_list = [x + '.yaml' for x in object_list]
else:
#object_list = [get_object_name(x) for x in object_group_name]
object_list = [x + '.yaml' for x in object_group_name]
return object_list
def generate_fixed_distribution_commands(type = 'G3DB'):
object_list = ['7cm', '8cm', '9cm', '75mm', '85mm']
if type == 'G3DB':
object_list = get_grasping_object_name_list()
for filetype in ['_baseline', '_combined_4']: #['', '_learning', '_combined_0', '_combined_1', '_combined_2', '_combined_0-15', '_combined_0-20', '_combined_3-50', '_combined_4']:
for interface_type in ["vrep_model_fixed_distribution", "data_model_fixed_distribution"]:
generate_params_file(interface_type + "_9cm_low_friction" + filetype + ".yaml", 'despot_without_display')
for object_type in object_list:
generate_params_file(interface_type + "_multi_object_" + object_type + "_low_friction" + filetype + ".yaml", 'despot_without_display')
def get_object_name(object_file):
object_file_parts = object_file.split('_')
for object_file_part in object_file_parts:
if 'cm' in object_file_part:
object_number = int(filter(str.isdigit, object_file_part))
if object_number < 10:
return "Cylinder" + repr(object_number) + 'cm'
elif object_number < 100:
return "Cylinder" + repr(object_number) + 'mm'
elif object_number > 1000:
g3db_objects = get_grasping_object_name_list('all_g3db')
g3dbPattern = 'G3DB' + repr(object_number - 1000) + '_'
for g3db_object in g3db_objects:
if g3dbPattern in g3db_object:
return g3db_object
def generate_sample_input_command(dir, error_files):
#object_list = ['7cm', '8cm', '9cm', '75mm', '85mm']
object_list = get_grasping_object_name_list('coffee_yogurt_cup')
command = 'data'
if 'simulator' in dir:
command = 'vrep'
command = command + '_model_fixed_distribution' + '_ver5'
if 'singleObjectType' in dir:
command = command + "_9cm"
else:
command = command + "_multi_object_" + "coffee_yogurt_" + "pattern"
command = command + '_low_friction'
ans = []
for error_file in error_files:
o = ''
for object_type in object_list:
if object_type in error_file:
o = object_type
trial_no = int(error_file.split('.')[0].split('_')[-1])
m = re.search('t([0-9]+)_', dir)
learning_version = 'None'
if m:
t = m.groups(0)[0]
else:
t = '1'
learning_version = 'empty'
m = re.search('_n([0-9]+)', dir)
if m:
n = m.groups(0)[0]
else:
n = '1'
combined_version = 'None'
m = re.search('combined_([0-9]+)', dir)
if m:
combined_version = m.groups(0)[0]
m = re.search('combined_[0-9]+-([0-9]+)', dir)
if m:
combined_version = combined_version + '-' + m.groups(0)[0]
if o:
ans.append(' '.join([
o, command, t, n, learning_version, combined_version,
repr(trial_no),
repr(trial_no + 1), '1'
]))
#print ans
return ans
def main():
base_dir = '/home/neha/WORK_FOLDER/unicorn_dir_mount/neha_github/autonomousGrasping/grasping_ros_mico/results/despot_logs/low_friction_table/vrep_scene_ver6/multiObjectType/'
dir_list = []
for i in range(0, 7):
dir_list.append('belief_uniform_baseline_' + repr(i) +
'_reward100_penalty10/simulator/fixed_distribution/')
dir_list.append(
'belief_uniform_cylinder_7_8_9_reward100_penalty10/use_discretized_data/simulator/fixed_distribution/t5_n40'
)
dir_list.append(
'belief_uniform_cylinder_7_8_9_reward100_penalty10/use_discretized_data/simulator/fixed_distribution/learning/version14'
)
patterns = get_grasping_object_name_list('cylinder_and_g3db_instances')
for pattern in patterns:
print '#############################'
print pattern
diff_values = get_diff_values(pattern)
print diff_values
for dir_name in dir_list:
correct_pick_values(os.path.join(base_dir, dir_name), pattern,
diff_values)
def parse(fileName, belief_type='', isTraining=False):
seqs = []
if fileName == 'test':
for i in range(0, 100):
#logfileName = '/home/neha/WORK_FOLDER/neha_github/apc/rosmake_ws/despot_vrep_glue/results/despot_logs/VrepData_gaussian_belief_with_state_in_belief_t5_n10_trial_' + repr(i) +'.log'
#logfileName = '/home/neha/WORK_FOLDER/ncl_dir_mount/neha_github/autonomousGrasping/grasping_ros_mico/results/despot_logs/separate_close_reward/singleObjectType/cylinder_9cm_reward100_penalty10/t1_n320_withoutLCAP/TableScene_cylinder_9cm_gaussian_belief_with_state_in_belief_t1_n320_trial_' + repr(i) +'.log'
#logfileName = '/home/neha/WORK_FOLDER/ncl_dir_mount/neha_github/autonomousGrasping/grasping_ros_mico/results/despot_logs/low_friction_table/singleObjectType/cylinder_9cm_reward100_penalty10/t5_n80/Table_scene_low_friction_9cm_cylinder_belief_gaussian_with_state_in_t5_n80_trial_' + repr(i) +'.log'
#logfileName = '/home/neha/WORK_FOLDER/unicorn_dir_mount/neha_github/autonomousGrasping/grasping_ros_mico/results/despot_logs/low_friction_table/multiObjectType/belief_cylinder_7_8_9_reward100_penalty10/t5_n20/Table_scene_low_friction_7cm_cylinder_belief_gaussian_with_state_in_t5_n20_trial_' + repr(i) +'.log'
#logfileName = '/home/neha/WORK_FOLDER/ncl_dir_mount/neha_github/autonomousGrasping/grasping_ros_mico/results/despot_logs/multiObjectType/belief_cylinder_7_8_9_reward100_penalty10/t5_n160/TableScene_cylinder_9cm_gaussian_belief_with_state_in_belief_t5_n160_trial_' + repr(i) +'.log'
#logfileName = '/home/neha/WORK_FOLDER/unicorn_dir_mount/neha_github/autonomousGrasping/grasping_ros_mico/results/despot_logs/low_friction_table/multiObjectType/belief_cylinder_7_8_9_reward100_penalty10/simulator/learning/version8/Table_scene_low_friction_7cm_cylinder_v8_trial_' + repr(i) +'.log'
#logfileName = '/home/neha/WORK_FOLDER/unicorn_dir_mount/neha_github/autonomousGrasping/grasping_ros_mico/results/despot_logs/low_friction_table/multiObjectType/belief_cylinder_7_8_9_reward100_penalty10/simulator/fixed_distribution/learning/version8/Table_scene_low_friction_7cm_cylinder_v8_trial_' + repr(i) +'.log'
t = '5'
scenario = '80'
#object = '84_yogurtcup_final-13-Nov-2015-10-32-33_instance0'
object = 'Cylinder_7'
#object='G3DB84_yogurtcup_final'
#object = 'G3DB1_Coffeecup_final-20-dec-2015'
#object = '9cm'
logfileName = '/home/neha/WORK_FOLDER/ncl_dir_mount/neha_github/autonomousGrasping/grasping_ros_mico/results/despot_logs/low_friction_table/vrep_scene_ver7/multiObjectType/'
#logfileName = logfileName + 'belief_uniform_g3db_single_reward100_penalty10/simulator/fixed_distribution/t' + t + '_n' + scenario + '/Table_scene_'+ object + '_belief_uniform_with_state_in_t' + t + '_n' + scenario + '_trial_' + repr(i) +'.log'
logfileName = logfileName + 'belief_uniform_cylinder_7_8_9_reward100_penalty10/use_discretized_data/'
#logfileName = logfileName + 'belief_uniform_g3db_instances_train1_reward100_penalty10/use_discretized_data/use_weighted_belief/fixed_distribution/horizon90/'
logfileName = logfileName + 't' + t + '_n' + scenario + '/Table_scene_' + object + '_belief_uniform_with_state_in_t' + t + '_n' + scenario + '_trial_' + repr(
i) + '.log'
#logfileName = logfileName + 'belief_uniform_g3db_1_84_reward100_penalty10/icp_score_weighted/simulator/fixed_distribution/learning/version13/'
#logfileName = logfileName + 'Table_scene_' + object + '_trial_' + repr(i) +'.log'
#object='8cm'
#logfileName = '/home/neha/WORK_FOLDER/ncl_dir_mount/neha_github/autonomousGrasping/grasping_ros_mico/results/despot_logs/low_friction_table/multiObjectType/belief_uniform_cylinder_7_8_9_reward100_penalty100/fixed_distribution/t' + t + '_n' + scenario + '/Table_scene_low_friction_'+ object + '_cylinder_belief_uniform_t' + t + '_n' + scenario + '_trial_' + repr(i) +'.log'
#print i
#seqs = seqs + parse_file(logfileName, belief_type, True, 0, 'vrep')
#logfileName = '/home/neha/WORK_FOLDER/unicorn_dir_mount/neha_github/autonomousGrasping/grasping_ros_mico/results/despot_logs/low_friction_table/multiObjectType/belief_cylinder_7_8_9_reward100_penalty10/simulator/fixed_distribution/t1_n40/Table_scene_low_friction_7cm_cylinder_belief_gaussian_with_state_in_t1_n40_trial_' + repr(i) +'.log'
#print i
seqs = seqs + parse_file(logfileName, belief_type, True, 0,
'vrep/ver7')
#logfileName = '../../grasping_ros_mico/results/despot_logs/singleObjectType/cylinder_9cm_reward100_penalty10/t5_n20/TableScene_cylinder_9cm_gaussian_belief_with_state_in_belief_t5_n20_trial_' + repr(i) +'.log'
#print i
#seqs = seqs + parse_file(logfileName, belief_type, True, 0, 'vrep')
#logfileName = '../../grasping_ros_mico/results/despot_logs/singleObjectType/cylinder_9cm_reward100_penalty10/t1_n20/TableScene_cylinder_9cm_gaussian_belief_with_state_in_belief_t1_n20_trial_' + repr(i) +'.log'
#print i
#seqs = seqs + parse_file(logfileName, belief_type, True, 0, 'vrep')
elif fileName == 'toy/version1':
for i in range(0, 2000):
for t in ['5']:
for scenario in ['10', '20']:
logfileName = '../../graspingV4/results/despot_logs/t' + t + "_n" + scenario + "/Toy_train_belief_default_t" + t + "_n" + scenario + "_trial_" + repr(
i) + ".log"
seqs = seqs + parse_file(logfileName, belief_type, True, 0,
'toy')
elif fileName in ['vrep/version25']:
object_class_names = [
'g3db_instances_train3_version7_label_3_class_0',
'g3db_instances_train3_version7_label_3_class_1',
'g3db_instances_train3_version7_label_3_class_2',
'g3db_instances_train3_version7_label_3_class_3',
'g3db_instances_train3_version7_label_3_class_4'
]
object_class_samples_mapping = {}
object_class_samples_mapping[
'g3db_instances_train3_version7_label_3_class_0'] = 2000
object_class_samples_mapping[
'g3db_instances_train3_version7_label_3_class_1'] = 500
object_class_samples_mapping[
'g3db_instances_train3_version7_label_3_class_2'] = 4000
object_class_samples_mapping[
'g3db_instances_train3_version7_label_3_class_3'] = 3000
object_class_samples_mapping[
'g3db_instances_train3_version7_label_3_class_4'] = 4000
for object_class_name in object_class_names:
object_list = get_grasping_object_name_list(object_class_name)
for i in range(0, object_class_samples_mapping[object_class_name]):
for t in ['5']:
for scenario in ['160']:
for object in object_list:
logfileName = '../../grasping_ros_mico/results/despot_logs/low_friction_table/'
logfileName = logfileName + 'vrep_scene_ver7/multiObjectType/'
logfileName = logfileName + 'belief_uniform_g3db_instances_train3_reward100_penalty10/'
logfileName = logfileName + 'use_discretized_data/use_binary_touch'
logfileName = logfileName + '/use_wider_workspace/use_probabilistic_neighbour_step'
logfileName = logfileName + '/use_discrete_observation_in_update/'
logfileName = logfileName + 'use_discrete_observation_in_step/'
logfileName = logfileName + 'use_weighted_belief/'
logfileName = logfileName + 'use_classifier/kmeans-extra-data_label_3_20180419-123116/horizon90/t'
logfileName = logfileName + t + '_n' + scenario + '/Table_scene_' + object + '_belief_uniform_with_state_in_t' + t + '_n' + scenario + '_trial_' + repr(
i) + '.log'
#print i
seqs = seqs + parse_file(logfileName, belief_type,
True, 0,
'vrep/ver7/weighted_5')
elif fileName in ['vrep/version24']:
object_class_names = [
'g3db_instances_train2_version7_label_3_class_0',
'g3db_instances_train2_version7_label_3_class_1',
'g3db_instances_train2_version7_label_3_class_2',
'g3db_instances_train2_version7_label_3_class_3',
'g3db_instances_train2_version7_label_3_class_4'
]
object_class_samples_mapping = {}
object_class_samples_mapping[
'g3db_instances_train2_version7_label_3_class_0'] = 2000
object_class_samples_mapping[
'g3db_instances_train2_version7_label_3_class_1'] = 500
object_class_samples_mapping[
'g3db_instances_train2_version7_label_3_class_2'] = 4000
object_class_samples_mapping[
'g3db_instances_train2_version7_label_3_class_3'] = 3000
object_class_samples_mapping[
'g3db_instances_train2_version7_label_3_class_4'] = 4000
for object_class_name in object_class_names:
object_list = get_grasping_object_name_list(object_class_name)
for i in range(0, object_class_samples_mapping[object_class_name]):
for t in ['5']:
for scenario in ['160']:
for object in object_list:
logfileName = '../../grasping_ros_mico/results/despot_logs/low_friction_table/'
logfileName = logfileName + 'vrep_scene_ver7/multiObjectType/'
logfileName = logfileName + 'belief_uniform_g3db_instances_train2_reward100_penalty10/'
logfileName = logfileName + 'use_discretized_data/use_binary_touch'
logfileName = logfileName + '/use_wider_workspace/use_probabilistic_neighbour_step'
logfileName = logfileName + '/use_discrete_observation_in_update/'
logfileName = logfileName + 'use_discrete_observation_in_step/'
logfileName = logfileName + 'use_weighted_belief/'
logfileName = logfileName + 'use_classifier/kmeans-extra-data_label_3_20180419-123116/horizon90/t'
logfileName = logfileName + t + '_n' + scenario + '/Table_scene_' + object + '_belief_uniform_with_state_in_t' + t + '_n' + scenario + '_trial_' + repr(
i) + '.log'
#print i
seqs = seqs + parse_file(logfileName, belief_type,
True, 0,
'vrep/ver7/weighted_5')
elif fileName in ['vrep/version23']:
object_list = get_grasping_object_name_list('cylinders_train')
for i in range(0, 4000):
for t in ['5']:
for scenario in ['320']:
for object in object_list:
logfileName = '../../grasping_ros_mico/results/despot_logs/low_friction_table/'
logfileName = logfileName + 'vrep_scene_ver7/multiObjectType/'
logfileName = logfileName + 'belief_uniform_cylinder_7_8_9_reward100_penalty10/'
logfileName = logfileName + 'use_discretized_data/use_binary_touch/'
logfileName = logfileName + 'use_probabilistic_neighbour_step/'
logfileName = logfileName + 'use_discrete_observation_in_update/'
logfileName = logfileName + 'use_discrete_observation_in_step/t'
logfileName = logfileName + t + '_n' + scenario + '/Table_scene_' + object + '_belief_uniform_with_state_in_t' + t + '_n' + scenario + '_trial_' + repr(
i) + '.log'
#print i
seqs = seqs + parse_file(logfileName, belief_type,
True, 0, 'vrep/ver7')
elif fileName in ['vrep/version22']:
object_list = get_grasping_object_name_list(
'g3db_instances_train2_version7')
for i in range(0, 500):
for t in ['5']:
for scenario in ['160']:
for object in object_list:
logfileName = '../../grasping_ros_mico/results/despot_logs/low_friction_table/'
logfileName = logfileName + 'vrep_scene_ver7/multiObjectType/'
logfileName = logfileName + 'belief_uniform_g3db_instances_train2_reward100_penalty10/'
logfileName = logfileName + 'use_discretized_data/use_binary_touch'
logfileName = logfileName + '/use_wider_workspace/use_probabilistic_neighbour_step_temperature_bug'
logfileName = logfileName + '/use_discrete_observation_in_update/'
logfileName = logfileName + 'use_discrete_observation_in_step/'
logfileName = logfileName + 'use_weighted_belief/'
logfileName = logfileName + 'use_classifier/kmeans-extra-data_label_4_20180504-200455/horizon90/t'
logfileName = logfileName + t + '_n' + scenario + '/Table_scene_' + object + '_belief_uniform_with_state_in_t' + t + '_n' + scenario + '_trial_' + repr(
i) + '.log'
#print i
seqs = seqs + parse_file(logfileName, belief_type,
True, 0,
'vrep/ver7/weighted_4')
elif fileName in ['vrep/version21']:
object_list = get_grasping_object_name_list(
'g3db_instances_train2_version7')
for i in range(0, 500):
for t in ['5']:
for scenario in ['80']:
for object in object_list:
logfileName = '../../grasping_ros_mico/results/despot_logs/low_friction_table/'
logfileName = logfileName + 'vrep_scene_ver7/multiObjectType/'
logfileName = logfileName + 'belief_uniform_g3db_instances_train2_reward100_penalty10/'
logfileName = logfileName + 'use_discretized_data/use_binary_touch'
logfileName = logfileName + '/use_wider_workspace/use_probabilistic_neighbour_step_temperature_bug'
logfileName = logfileName + '/use_discrete_observation_in_update/'
logfileName = logfileName + 'use_discrete_observation_in_step/'
logfileName = logfileName + 'use_weighted_belief/'
logfileName = logfileName + 'use_classifier/kmeans-extra-data_label_3_20180419-123116/horizon90/t'
logfileName = logfileName + t + '_n' + scenario + '/Table_scene_' + object + '_belief_uniform_with_state_in_t' + t + '_n' + scenario + '_trial_' + repr(
i) + '.log'
#print i
seqs = seqs + parse_file(logfileName, belief_type,
True, 0,
'vrep/ver7/weighted_5')
elif fileName in ['vrep/version20']:
object_list = get_grasping_object_name_list(
'g3db_instances_train1_version7')
for i in range(0, 500):
for t in ['5']:
for scenario in ['160']:
for object in object_list:
logfileName = '../../grasping_ros_mico/results/despot_logs/low_friction_table/'
logfileName = logfileName + 'vrep_scene_ver7/multiObjectType/'
logfileName = logfileName + 'belief_uniform_g3db_instances_train1_reward100_penalty10/'
logfileName = logfileName + 'use_discretized_data/use_weighted_belief/'
logfileName = logfileName + 'use_classifier/kmeans_20180215-115011/horizon90/t'
logfileName = logfileName + t + '_n' + scenario + '/Table_scene_' + object + '_belief_uniform_with_state_in_t' + t + '_n' + scenario + '_trial_' + repr(
i) + '.log'
#print i
seqs = seqs + parse_file(logfileName, belief_type,
True, 0,
'vrep/ver7/weighted_3')
elif fileName in ['vrep/version19']:
object_list = get_grasping_object_name_list(
'g3db_instances_train1_version7')
for i in range(0, 243):
for t in ['5']:
for scenario in ['160']:
for object in object_list:
logfileName = '../../grasping_ros_mico/results/despot_logs/low_friction_table/'
logfileName = logfileName + 'vrep_scene_ver7/multiObjectType/'
logfileName = logfileName + 'belief_uniform_g3db_instances_train1_reward100_penalty10/'
logfileName = logfileName + 'use_discretized_data/fixed_distribution/horizon90/t'
logfileName = logfileName + t + '_n' + scenario + '/Table_scene_' + object + '_belief_uniform_with_state_in_t' + t + '_n' + scenario + '_trial_' + repr(
i) + '.log'
#print i
seqs = seqs + parse_file(logfileName, belief_type,
True, 0, 'vrep/ver7')
elif fileName in ['vrep/version18']:
object_list = get_grasping_object_name_list('cylinders_train')
for i in range(0, 4000):
for t in ['5']:
for scenario in ['80']:
for object in object_list:
logfileName = '../../grasping_ros_mico/results/despot_logs/low_friction_table/'
logfileName = logfileName + 'vrep_scene_ver7/multiObjectType/'
logfileName = logfileName + 'belief_uniform_cylinder_7_8_9_reward100_penalty10/'
logfileName = logfileName + 'use_discretized_data/t'
logfileName = logfileName + t + '_n' + scenario + '/Table_scene_' + object + '_belief_uniform_with_state_in_t' + t + '_n' + scenario + '_trial_' + repr(
i) + '.log'
#print i
seqs = seqs + parse_file(logfileName, belief_type,
True, 0, 'vrep/ver7')
elif fileName in ['vrep/version17']:
#data with number of objects = 10 bug
object_list = get_grasping_object_name_list('g3db_instances_train1')
for i in range(0, 1000):
for t in ['5']:
for scenario in ['40']:
for object in object_list:
logfileName = '../../grasping_ros_mico/results/despot_logs/low_friction_table/'
logfileName = logfileName + 'vrep_scene_ver6/multiObjectType/'
logfileName = logfileName + 'belief_uniform_g3db_instances_train1_reward100_penalty10/'
logfileName = logfileName + 'use_discretized_data/use_weighted_belief/horizon90/t'
logfileName = logfileName + t + '_n' + scenario + '/Table_scene_' + object + '_belief_uniform_with_state_in_t' + t + '_n' + scenario + '_trial_' + repr(
i) + '.log'
#print i
seqs = seqs + parse_file(logfileName, belief_type,
True, 0,
'vrep/ver5/weighted_15')
elif fileName in ['vrep/version16']:
#Had point cloud bug
object_list = get_grasping_object_name_list('g3db_instances_train1')
for i in range(0, 2000):
for t in ['5']:
for scenario in ['320']:
for object in object_list:
logfileName = '../../grasping_ros_mico/results/despot_logs/low_friction_table/'
logfileName = logfileName + 'vrep_scene_ver6/multiObjectType/'
logfileName = logfileName + 'belief_uniform_g3db_instances_train1_reward100_penalty10/'
logfileName = logfileName + 'use_discretized_data/use_weighted_belief/horizon90/t'
logfileName = logfileName + t + '_n' + scenario + '/Table_scene_' + object + '_belief_uniform_with_state_in_t' + t + '_n' + scenario + '_trial_' + repr(
i) + '.log'
#print i
seqs = seqs + parse_file(logfileName, belief_type,
True, 0,
'vrep/ver5/weighted_15')
elif fileName in ['vrep/version14', 'vrep/version15']:
#version 14 and 15 differ only in training params
object_list = get_grasping_object_name_list('cylinders_train')
for i in range(0, 4000):
for t in ['5']:
for scenario in ['40']:
for object in object_list:
logfileName = '../../grasping_ros_mico/results/despot_logs/low_friction_table/'
logfileName = logfileName + 'vrep_scene_ver6/multiObjectType/'
logfileName = logfileName + 'belief_uniform_cylinder_7_8_9_reward100_penalty10/'
logfileName = logfileName + 'use_discretized_data/t'
logfileName = logfileName + t + '_n' + scenario + '/Table_scene_' + object + '_belief_uniform_with_state_in_t' + t + '_n' + scenario + '_trial_' + repr(
i) + '.log'
#print i
seqs = seqs + parse_file(logfileName, belief_type,
True, 0, 'vrep/ver5')
elif fileName == 'vrep/version13':
object_list = get_grasping_object_name_list('coffee_yogurt_cup')
for i in range(0, 4000):
for t in ['5']:
for scenario in ['80']:
for object in object_list:
logfileName = '../../grasping_ros_mico/results/despot_logs/low_friction_table/multiObjectType/belief_uniform_g3db_1_84_reward100_penalty10/icp_score_weighted/t'
logfileName = logfileName + t + '_n' + scenario + '/Table_scene_' + object + '_belief_uniform_with_state_in_t' + t + '_n' + scenario + '_trial_' + repr(
i) + '.log'
#print i
seqs = seqs + parse_file(logfileName, belief_type,
True, 0,
'vrep/ver5/weighted_2')
elif fileName == 'vrep/version12':
for i in range(0, 4000):
for t in ['5']:
for scenario in ['320']:
for object in ['7cm', '8cm', '9cm']:
logfileName = '../../grasping_ros_mico/results/despot_logs/low_friction_table/multiObjectType/belief_uniform_cylinder_7_8_9_reward100_penalty10/t'
logfileName = logfileName + t + '_n' + scenario + '/Table_scene_' + object + '_belief_uniform_with_state_in_t' + t + '_n' + scenario + '_trial_' + repr(
i) + '.log'
#print i
seqs = seqs + parse_file(logfileName, belief_type,
True, 0, 'vrep/ver5')
elif fileName == 'vrep/version11':
for i in range(0, 4000):
for t in ['5']:
for scenario in ['320']:
for object in ['7cm', '8cm', '9cm']:
logfileName = '../../grasping_ros_mico/results/despot_logs/low_friction_table/multiObjectType/belief_uniform_cylinder_7_8_9_reward100_penalty10/t'
logfileName = logfileName + t + '_n' + scenario + '/Table_scene_' + object + '_belief_uniform_with_state_in_t' + t + '_n' + scenario + '_trial_' + repr(
i) + '.log'
#print i
seqs = seqs + parse_file(logfileName, belief_type,
True, 0, 'vrep')
elif fileName in ['vrep/version9', 'vrep/version10']:
for i in range(0, 500):
for t in ['5']:
for scenario in ['40', '80', '160']:
for object in ['7cm', '8cm', '9cm']:
logfileName = '../../grasping_ros_mico/results/despot_logs/low_friction_table/multiObjectType/belief_cylinder_7_8_9_reward100_penalty100/t' + t + '_n' + scenario + '/Table_scene_low_friction_' + object + '_cylinder_belief_gaussian_with_state_in_t' + t + '_n' + scenario + '_trial_' + repr(
i) + '.log'
#print i
seqs = seqs + parse_file(logfileName, belief_type,
True, 0, 'vrep')
elif fileName == 'vrep/version8':
for i in range(0, 500):
for t in ['5']:
for scenario in ['40', '80', '160']:
for object in ['7cm', '8cm', '9cm']:
logfileName = '../../grasping_ros_mico/results/despot_logs/low_friction_table/multiObjectType/belief_cylinder_7_8_9_reward100_penalty10/t' + t + '_n' + scenario + '/Table_scene_low_friction_' + object + '_cylinder_belief_gaussian_with_state_in_t' + t + '_n' + scenario + '_trial_' + repr(
i) + '.log'
#print i
seqs = seqs + parse_file(logfileName, belief_type,
True, 0, 'vrep')
elif fileName == 'vrep/version8_pick_bug':
for i in range(0, 500):
for t in ['5']:
for scenario in ['40', '80', '160']:
for object in ['7cm', '8cm', '9cm']:
logfileName = '../../grasping_ros_mico/results/despot_logs/low_friction_table/multiObjectType/belief_cylinder_7_8_9_reward100_penalty10/t' + t + '_n' + scenario + '/Table_scene_low_friction_' + object + '_cylinder_belief_gaussian_with_state_in_t' + t + '_n' + scenario + '_trial_' + repr(
i) + '.log'
#print i
seqs = seqs + parse_file(logfileName, belief_type,
True, 0, 'vrep')
elif fileName == 'vrep/version7':
for i in range(0, 1000):
logfileName = '../../grasping_ros_mico/results/despot_logs/low_friction_table/singleObjectType/cylinder_9cm_reward100_penalty10/t5_n40/Table_scene_low_friction_9cm_cylinder_belief_gaussian_with_state_in_t5_n40_trial_' + repr(
i) + '.log'
#print i
seqs = seqs + parse_file(logfileName, belief_type, True, 0, 'vrep')
logfileName = '../../grasping_ros_mico/results/despot_logs/low_friction_table/singleObjectType/cylinder_9cm_reward100_penalty10/t5_n80/Table_scene_low_friction_9cm_cylinder_belief_gaussian_with_state_in_t5_n80_trial_' + repr(
i) + '.log'
#print i
seqs = seqs + parse_file(logfileName, belief_type, True, 0, 'vrep')
logfileName = '../../grasping_ros_mico/results/despot_logs/low_friction_table/singleObjectType/cylinder_9cm_reward100_penalty10/t5_n160/Table_scene_low_friction_9cm_cylinder_belief_gaussian_with_state_in_t5_n160_trial_' + repr(
i) + '.log'
#print i
seqs = seqs + parse_file(logfileName, belief_type, True, 0, 'vrep')
logfileName = '../../grasping_ros_mico/results/despot_logs/low_friction_table/singleObjectType/cylinder_9cm_reward100_penalty10/t5_n320/Table_scene_low_friction_9cm_cylinder_belief_gaussian_with_state_in_t5_n320_trial_' + repr(
i) + '.log'
#print i
seqs = seqs + parse_file(logfileName, belief_type, True, 0, 'vrep')
elif fileName == 'vrep/version6':
for i in range(0, 500):
#logfileName = '/home/neha/WORK_FOLDER/neha_github/apc/rosmake_ws/despot_vrep_glue/results/despot_logs/VrepData_gaussian_belief_with_state_in_belief_t5_n10_trial_' + repr(i) +'.log'
################################################### v6 begins#################################################
logfileName = '../../grasping_ros_mico/results/despot_logs/high_friction_table/multiObjectType/belief_cylinder_7_8_9_reward100_penalty10/t5_n160/TableScene_cylinder_9cm_gaussian_belief_with_state_in_belief_t5_n160_trial_' + repr(
i) + '.log'
#print i
seqs = seqs + parse_file(logfileName, belief_type, True, 0, 'vrep')
logfileName = '../../grasping_ros_mico/results/despot_logs/high_friction_table/multiObjectType/belief_cylinder_7_8_9_reward100_penalty10/t5_n160/TableScene_cylinder_8cm_gaussian_belief_with_state_in_belief_t5_n160_trial_' + repr(
i) + '.log'
#print i
seqs = seqs + parse_file(logfileName, belief_type, True, 0, 'vrep')
logfileName = '../../grasping_ros_mico/results/despot_logs/high_friction_table/multiObjectType/belief_cylinder_7_8_9_reward100_penalty10/t5_n160/TableScene_cylinder_7cm_gaussian_belief_with_state_in_belief_t5_n160_trial_' + repr(
i) + '.log'
#print i
seqs = seqs + parse_file(logfileName, belief_type, True, 0, 'vrep')
logfileName = '../../grasping_ros_mico/results/despot_logs/high_friction_table/multiObjectType/belief_cylinder_7_8_9_reward100_penalty10/t5_n320/TableScene_cylinder_9cm_gaussian_belief_with_state_in_belief_t5_n320_trial_' + repr(
i) + '.log'
#print i
seqs = seqs + parse_file(logfileName, belief_type, True, 0, 'vrep')
logfileName = '../../grasping_ros_mico/results/despot_logs/high_friction_table/multiObjectType/belief_cylinder_7_8_9_reward100_penalty10/t5_n320/TableScene_cylinder_8cm_gaussian_belief_with_state_in_belief_t5_n320_trial_' + repr(
i) + '.log'
#print i
seqs = seqs + parse_file(logfileName, belief_type, True, 0, 'vrep')
logfileName = '../../grasping_ros_mico/results/despot_logs/high_friction_table/multiObjectType/belief_cylinder_7_8_9_reward100_penalty10/t5_n320/TableScene_cylinder_7cm_gaussian_belief_with_state_in_belief_t5_n320_trial_' + repr(
i) + '.log'
#print i
seqs = seqs + parse_file(logfileName, belief_type, True, 0, 'vrep')
logfileName = '../../grasping_ros_mico/results/despot_logs/high_friction_table/multiObjectType/belief_cylinder_7_8_9_reward100_penalty10/t5_n640/TableScene_cylinder_9cm_gaussian_belief_with_state_in_belief_t5_n640_trial_' + repr(
i) + '.log'
#print i
seqs = seqs + parse_file(logfileName, belief_type, True, 0, 'vrep')
logfileName = '../../grasping_ros_mico/results/despot_logs/high_friction_table/multiObjectType/belief_cylinder_7_8_9_reward100_penalty10/t5_n640/TableScene_cylinder_8cm_gaussian_belief_with_state_in_belief_t5_n640_trial_' + repr(
i) + '.log'
#print i
seqs = seqs + parse_file(logfileName, belief_type, True, 0, 'vrep')
logfileName = '../../grasping_ros_mico/results/despot_logs/high_friction_table/multiObjectType/belief_cylinder_7_8_9_reward100_penalty10/t5_n640/TableScene_cylinder_7cm_gaussian_belief_with_state_in_belief_t5_n640_trial_' + repr(
i) + '.log'
#print i
seqs = seqs + parse_file(logfileName, belief_type, True, 0, 'vrep')
##############################################################v6 ends##########################################################################
elif fileName in ['vrep/verion4', 'vrep/version5']:
for i in range(0, 1000):
#####################v4 begins####################################################################
logfileName = '../../grasping_ros_mico/results/despot_logs/high_friction_table/singleObjectType/cylinder_9cm_reward100_penalty10/t5_n80/TableScene_cylinder_9cm_gaussian_belief_with_state_in_belief_t5_n80_trial_' + repr(
i) + '.log'
#print i
seqs = seqs + parse_file(logfileName, belief_type, True, 0, 'vrep')
logfileName = '../../grasping_ros_mico/results/despot_logs/high_friction_table/singleObjectType/cylinder_9cm_reward100_penalty10/t5_n40/TableScene_cylinder_9cm_gaussian_belief_with_state_in_belief_t5_n40_trial_' + repr(
i) + '.log'
#print i
seqs = seqs + parse_file(logfileName, belief_type, True, 0, 'vrep')
logfileName = '../../grasping_ros_mico/results/despot_logs/high_friction_table/singleObjectType/cylinder_9cm_reward100_penalty10/t5_n20/TableScene_cylinder_9cm_gaussian_belief_with_state_in_belief_t5_n20_trial_' + repr(
i) + '.log'
#print i
seqs = seqs + parse_file(logfileName, belief_type, True, 0, 'vrep')
logfileName = '../../grasping_ros_mico/results/despot_logs/high_friction_table/singleObjectType/cylinder_9cm_reward100_penalty10/t1_n20/TableScene_cylinder_9cm_gaussian_belief_with_state_in_belief_t1_n20_trial_' + repr(
i) + '.log'
#print i
seqs = seqs + parse_file(logfileName, belief_type, True, 0, 'vrep')
####################v4 ends#################################################################
#for i in range(0,400):
# for round_no in range(0,4):
# logfileName = '/home/neha/WORK_FOLDER/phd2013/phdTopic/despot/despot-0.2/4_objects_obs_prob_change_particles_as_state/graspingV4_state_' + repr(i) + '_multi_runs_t10_n10_obs_prob_change_particles_as_state_4objects.log'
# seqs = seqs + parse_file(logfileName, belief_type, True, round_no, 'toy')
#logfileName = '/home/neha/WORK_FOLDER/phd2013/phdTopic/despot/despot-0.2-server-version/4_objects_obs_prob_change_particles_as_state/graspingV3_state_' + repr(i) + '_t20_obs_prob_change_particles_as_state_4objects.log'
#logfileName = '/home/neha/WORK_FOLDER/phd2013/phdTopic/despot/despot-0.2/4_objects_obs_prob_change_particles_as_state/graspingV4_state_' + repr(i) + '_t10_n10_obs_prob_change_particles_as_state_4objects.log'
#seqs = seqs + parse_file(logfileName, True, True)
#logfileName = '/home/neha/WORK_FOLDER/phd2013/phdTopic/despot/despot-0.2-server-version/4_objects_obs_prob_change_particles_as_state/deepLearning_same_objects/version6/state_' + repr(i) + '.log'
#seqs = seqs + parse_file(logfileName, False, True)
#logfileName = '/home/neha/WORK_FOLDER/phd2013/phdTopic/despot/despot-0.2-server-version/4_objects_obs_prob_change_particles_as_state/deepLearning_same_objects/version7/dagger_data/graspingV4_state_' + repr(i) + '_t10_n10_obs_prob_change_particles_as_state_4objects.log'
#seqs = seqs + parse_file(logfileName, False, True)
#logfileName = '/home/neha/WORK_FOLDER/phd2013/phdTopic/despot/despot-0.2-server-version/4_objects_obs_prob_change_particles_as_state/deepLearning_same_objects/version7/dagger_data/graspingV4_state_' + repr(i) + '_t1_n10_obs_prob_change_particles_as_state_4objects.log'
#seqs = seqs + parse_file(logfileName, False, True)
else:
# seqs = seqs + parse_file(fileName, '', isTraining, -1, 'toy')
seqs = seqs + parse_file(fileName, '', isTraining, -1, 'vrep')
#print seqs
return seqs
def make_object_dirs(dir_name, object_group):
object_list = get_grasping_object_name_list(object_group)
for object in object_list:
os.mkdir(dir_name + "/" + object)
def generate_commands_file(file_name, problem_type, work_folder_dir, starting_screen_counter = 1, tensorflow_path_input = '', separate_ros_vrep_port = False, command_list_file = None):
f = open(file_name, 'w')
global initial_ros_port
global max_ros_port
global vrep_scene_version
global generic_scene
global unicorn_eagle
global unicorn_eagle_without_gpu
global current_ros_port
global num_gpus
starting_ros_port = initial_ros_port
vrep_ros_port = current_ros_port + 1
tensorflow_path = tensorflow_path_input #Assumed location of tensorflow dir
source_tensorflow = tensorflow_path != ''
vrep_dir = work_folder_dir + '/V-REP_PRO_EDU_V3_3_2_64_Linux'
problem_dir = work_folder_dir + "/neha_github/autonomousGrasping/" + problem_type
if problem_type == 'despot_without_display':
problem_dir = work_folder_dir + "/neha_github/autonomousGrasping/" + "/grasping_ros_mico"
if problem_type.startswith('despot_bt'):
problem_dir = work_folder_dir + "/neha_github/despot_bt/build/examples/cpp_models/"
problem_dir = problem_dir + problem_type.split('_')[-1]
if problem_type == 'grasping_with_vision':
problem_dir = work_folder_dir + "/AdaCompNUS/HyP-Despot-LargeObservation-clone-neha-laptop/src/HyP_examples/grasping_ros_mico"
if 'grasping_with_vision_table' in problem_type:
problem_dir = work_folder_dir + "/AdaCompNUS/HyP-Despot-LargeObservation-WithGrasping-Table/src/HyP_examples/grasping_ros_mico"
if command_list_file is not None:
with open(command_list_file, 'r') as ff:
a = ff.readlines()
inputs = a[0].split(' ')
if command_list_file is None:
input_pattern = raw_input("Pattern type: all or file identifier?")
else:
input_pattern = inputs[0]
pattern = input_pattern
#pattern_list = [pattern]
if pattern == 'all':
pattern_list = ['7cm', '8cm', '9cm', '75mm', '85mm']
elif pattern == 'grasp_objects':
pattern_list = get_grasping_object_name_list()
else:
pattern_list = get_grasping_object_name_list(pattern)
if command_list_file is None:
command_prefix = raw_input("Command prefix?")
else:
command_prefix = inputs[1]
time_steps = ['1','5']
sampled_scenarios = ['5', '10', '20', '40', '80', '160', '320', '640', '1280']
learning_versions = ['8']
combined_policy_versions = ['0', '1', '2']
begin_index = 0
end_index = 1000
if command_list_file is None:
time_steps = get_list_input(time_steps, "Planning times")
sampled_scenarios = get_list_input(sampled_scenarios, "Sampled scenarios")
learning_versions = get_list_input(learning_versions, "Learning versions")
combined_policy_versions = get_list_input(combined_policy_versions, "Combined policy versions")
begin_index_input = raw_input("Begin index (default 0):")
end_index_input = raw_input("End index (default 1000):")
else:
time_steps = inputs[2].split(',')
sampled_scenarios = inputs[3].split(',')
learning_versions = inputs[4].split(',')
combined_policy_versions = inputs[5].split(',')
begin_index_input = inputs[6]
end_index_input = inputs[7]
if begin_index_input:
begin_index = int(begin_index_input)
if end_index_input:
end_index = int(end_index_input)
index_step = end_index
if command_list_file is None:
index_step_input = raw_input("Index step (default " + repr(index_step) + " ):")
else:
index_step_input = inputs[8]
if index_step_input:
index_step = int(index_step_input)
for l in learning_versions:
for c in combined_policy_versions:
for t in time_steps:
for n in sampled_scenarios:
for p in pattern_list:
for b_index in range(begin_index, end_index, index_step):
gpu_count = (starting_screen_counter) % num_gpus
actual_command = 'cd ' + problem_dir + ';' + generate_despot_command(t, n, l, c, problem_type, p, b_index, b_index + index_step, command_prefix,gpu_count)
gpu_screen_name = ''
if problem_type == 'grasping_with_vision':
gpu_screen_name = repr(gpu_count) + '_'
despot_screen_name = repr(starting_screen_counter)+ '_' +gpu_screen_name + problem_type
if separate_ros_vrep_port and not unicorn_eagle:
starting_ros_port = vrep_ros_port
despot_screen_name = repr(starting_screen_counter)+ '_' + problem_type + '_' + repr(starting_ros_port)
roscore_screen_name = repr(starting_screen_counter)+ '_roscore_' + repr(starting_ros_port)
f.write('screen -S ' + despot_screen_name + ' -d -m \n')
script_start_command = 'script ' + despot_screen_name
f.write("screen -S " + despot_screen_name + " -X stuff '" + script_start_command + " ^M' \n")
if unicorn_eagle or unicorn_eagle_without_gpu:
ros_master_uri_command = 'export ROS_MASTER_URI=http://node_name:gpu_port_name'
f.write("screen -S " + despot_screen_name + " -X stuff '" + ros_master_uri_command + " ^M' \n")
if separate_ros_vrep_port and not unicorn_eagle and not unicorn_eagle_without_gpu:
ros_master_uri_command = 'export ROS_MASTER_URI=http://localhost:' + repr(starting_ros_port)
roscore_command = 'roscore -p ' + repr(starting_ros_port)
f.write('screen -S ' + roscore_screen_name + ' -d -m \n')
f.write("screen -S " + roscore_screen_name + " -X stuff '" + ros_master_uri_command + " ^M' \n")
f.write("screen -S " + roscore_screen_name + " -X stuff '" + roscore_command + " ^M' \n")
f.write("sleep 1 \n")
f.write("screen -S " + despot_screen_name + " -X stuff '" + ros_master_uri_command + " ^M' \n")
vrep_command = 'until rostopic list ; do sleep 1; done ; cd '
vrep_command = vrep_command + vrep_dir
vrep_command = vrep_command + '; xvfb-run --auto-servernum --server-num=1 -s "-screen 0 640x480x24" ./vrep.sh -h '
vrep_command = vrep_command + '../vrep_scenes/micoWithSensorsMutliObjectTrialWithDespotIKVer' + vrep_scene_version
if generic_scene:
vrep_command = vrep_command + 'G3DB_generic.ttt'
else:
if 'G3DB' not in p:
vrep_command = vrep_command + 'Cylinder'
vrep_command = vrep_command + p + '.ttt'
vrep_screen_name = repr(starting_screen_counter)+ '_vrep_' + repr(starting_ros_port)
f.write('screen -S ' + vrep_screen_name + ' -d -m \n')
f.write("screen -S " + vrep_screen_name + " -X stuff '" + ros_master_uri_command + " ^M' \n")
f.write("screen -S " + vrep_screen_name + " -X stuff '" + vrep_command + " ^M' \n")
f.write("sleep 1 \n")
actual_command = "until rostopic list | grep vrep ; do sleep 1; done ; " + actual_command
vrep_ros_port = vrep_ros_port + 1
if vrep_ros_port > max_ros_port:
vrep_ros_port = initial_ros_port + 1
if source_tensorflow:
tensorflow_command = 'source ' + tensorflow_path + '/bin/activate'
f.write("screen -S " + despot_screen_name + " -X stuff '" + tensorflow_command + " ^M'\n")
f.write("screen -S " + despot_screen_name + " -X stuff '" + actual_command + " ^M^D' \n")
if problem_type.startswith('despot_bt'):
f.write("sleep 1 \n") #Required because sometimes same seeds are generated
starting_screen_counter = starting_screen_counter + 1
return starting_screen_counter
def generate_params_file(file_name, problem_type):
ans = {}
ans['solver'] = 'DESPOT'
ans['planning_time'] = 1
ans['number_scenarios'] = 5
ans['horizon'] = 50
ans['begin_index'] = 0
ans['end_index'] = 1000
ans['file_name_prefix'] = ''
ans['config_file'] = 'config_files/' + file_name.replace(
'learning', 'combined_0').replace('despot', 'combined_0')
if problem_type == 'despot_without_display':
#ans['config_file'] = 'config_files/VrepDataInterface.yaml'
ans['belief_type'] = 'GAUSSIAN_WITH_STATE_IN'
ans['additional_params'] = '--number=-1 -l CAP'
if problem_type == 'graspingV4':
ans['belief_type'] = 'DEFAULT'
ans['additional_params'] = '--number='
ans['output_dir'] = './results/despot_logs'
ans['end_index'] = 400
ans['horizon'] = 90
for filetype in ['train', 'test']:
if filetype in file_name:
ans['file_name_prefix'] = 'Toy_' + filetype
if problem_type == 'pocman':
#ans['config_file'] = 'config_files/' + file_name.replace('learning', 'combined_0')
ans['belief_type'] = 'DEFAULT'
ans['additional_params'] = ''
ans['output_dir'] = './results'
ans['horizon'] = 90
ans['file_name_prefix'] = 'full_pocman_'
ans = modify_params_file_for_learning(file_name, problem_type, ans)
object_list = ['7cm', '8cm', '9cm', '75mm', '85mm']
for filetype in [
'combined_0', 'combined_1', 'combined_2', 'combined_0-15',
'combined_0-20', 'combined_3-50', 'combined_4'
]:
for interface_type in ["vrep_model", "data_model"]:
file_prefix = interface_type + "_9cm_low_friction_"
if file_name == file_prefix + filetype + ".yaml":
ans = get_default_params(file_prefix + "learning.yaml")
ans['output_dir'] = ans['output_dir'] + "/" + filetype
ans['config_file'] = (ans['config_file'].split('.')
)[0] + '_' + filetype + ".yaml"
for object_type in object_list:
file_prefix = interface_type + "_multi_object_" + object_type + "_low_friction_"
if file_name == file_prefix + filetype + '.yaml':
ans = get_default_params(file_prefix + 'learning.yaml')
ans['output_dir'] = ans['output_dir'] + "/" + filetype
ans['config_file'] = (ans['config_file'].split('.')
)[0] + '_' + filetype + ".yaml"
if 'uniform_belief' in file_name:
new_file_name = file_name
if 'G3DB' in file_name:
object_list = get_grasping_object_name_list()
for object_type in object_list:
if object_type in file_name:
G3DB_object_type = object_type
new_file_name = file_name.replace(G3DB_object_type, '75mm')
ans = get_default_params(new_file_name.replace('_uniform_belief', ''))
ans['belief_type'] = 'UNIFORM'
ans['output_dir'] = ans['output_dir'].replace(
'belief_cylinder', 'belief_uniform_cylinder')
if 'G3DB' in file_name:
ans['config_file'] = ans['config_file'].replace(
'75mm', G3DB_object_type)
ans['file_name_prefix'] = ans['file_name_prefix'].replace(
'75mm', G3DB_object_type)
elif 'penalty_100' in file_name:
new_file_name = file_name
if 'G3DB' in file_name:
object_list = get_grasping_object_name_list()
for object_type in object_list:
if object_type in file_name:
G3DB_object_type = object_type
new_file_name = file_name.replace(G3DB_object_type, '75mm')
if 'v8' in file_name:
ans = get_default_params(
new_file_name.replace('_penalty_100_v8', ''))
ans['output_dir'] = ans['output_dir'].replace(
"penalty10", "penalty100")
#ans['output_dir'] = ans['output_dir'].replace("version8","version9")
ans['config_file'] = ans['config_file'].replace(
'Vrep', 'VrepPenalty100V8')
elif 'v10' in file_name:
ans = get_default_params(
new_file_name.replace('_penalty_100_v10', ''))
ans['output_dir'] = ans['output_dir'].replace(
"penalty10", "penalty100")
ans['output_dir'] = ans['output_dir'].replace(
"version8", "version10")
ans['config_file'] = ans['config_file'].replace(
'Vrep', 'VrepPenalty100V10')
else:
ans = get_default_params(new_file_name.replace('_penalty_100', ''))
ans['output_dir'] = ans['output_dir'].replace(
"penalty10", "penalty100")
ans['output_dir'] = ans['output_dir'].replace(
"version8", "version9")
ans['config_file'] = ans['config_file'].replace(
'Vrep', 'VrepPenalty100')
if 'G3DB' in file_name:
ans['config_file'] = ans['config_file'].replace(
'75mm', G3DB_object_type)
ans['file_name_prefix'] = ans['file_name_prefix'].replace(
'75mm', G3DB_object_type)
elif 'fixed_distribution' in file_name:
new_file_name = file_name
if 'G3DB' in file_name:
object_list = get_grasping_object_name_list()
for object_type in object_list:
if object_type in file_name:
G3DB_object_type = object_type
new_file_name = file_name.replace(G3DB_object_type, '75mm')
ans = get_default_params(
new_file_name.replace('_fixed_distribution', ''))
ans['additional_params'] = '-l CAP --number='
if ('simulator' in ans['output_dir']):
ans['output_dir'] = ans['output_dir'].replace(
"simulator", "simulator/fixed_distribution")
else:
if 'penalty100' in ans['output_dir']:
ans['output_dir'] = ans['output_dir'].replace(
"penalty100", "penalty100/fixed_distribution")
else:
ans['output_dir'] = ans['output_dir'].replace(
"penalty10", "penalty10/fixed_distribution")
ans['end_index'] = 245
if 'G3DB' in file_name:
ans['config_file'] = ans['config_file'].replace(
'75mm', G3DB_object_type)
ans['file_name_prefix'] = ans['file_name_prefix'].replace(
'75mm', G3DB_object_type)
if 'combined' in file_name:
ans['solver'] = 'LEARNINGPLANNING'
if 'combined_4' in file_name:
ans['solver'] = 'DESPOTWITHLEARNEDPOLICY'
#m = re.search('combined_[0-9]+', file_name)
#switching_version = int(m.group().split('_')[-1])
#if switching_version > 2:
# ans['additional_params'] = '--max-policy-simlen=10 ' + ans['additional_params']
if 'learning' in file_name:
ans['solver'] = 'DEEPLEARNING'
if 'baseline' in file_name:
ans = get_default_params(file_name.replace('_baseline', ''))
ans['output_dir'] = ans['output_dir'] + "/baseline"
ans['solver'] = 'USERDEFINED'
if file_name == 'data_model_9cm_combined_automatic.yaml':
ans['config_file'] = 'config_files/VrepDataInterface_v4_automatic.yaml'
ans['file_name_prefix'] = 'Table_scene_9cm_cylinder_v4_automatic'
ans['output_dir'] = './results/despot_logs/high_friction_table/singleObjectType/cylinder_9cm_reward100_penalty10/learning/version4/combined_1'
if file_name == 'data_model_9cm_low_friction.yaml':
ans['config_file'] = 'config_files/VrepDataInterface_low_friction.yaml'
ans['file_name_prefix'] = 'Table_scene_9cm_cylinder'
ans['output_dir'] = './results/despot_logs/low_friction_table/singleObjectType/cylinder_9cm_reward100_penalty10'
output = yaml.dump(ans, Dumper=Dumper)
f = open(file_name, 'w')
f.write(output)
def get_grasping_object_name_list(type='used'):
return grasping_object_list.get_grasping_object_name_list(type)
