def compile_data():
"""Input name of folder in saved_data and instance base"""
# folder_names = ['1015DCDKHHT-05-PT'] # ['1015DCDKHT-PK-prob', '1015DCDKHT-05-prob']
# instance_base = ['DCDKHT_05hpoint_G46Vss2_1015_'] # ['DCDKHT_100hprob_PK_G46Vss2_1015_', 'DCDKHT_05hprob_G46Vss2_1015_']
rp = RiskPlot()
folder_names = ['0106-PT-PU-345', '1111DCDKHT_MGTFC-PT-05', '1111DCDKHT_HGTFF-PT-05',
'1111DCDKHT_MGTFF-PT-05']
instance_base = ['DCDKHT_HGTdesFC_05hpoint_G46Vss2_1110_', 'DCDKHT_MGTdesFC_05hpoint_G46Vss2_1110_',
'DCDKHT_HGTdesFF_05hpoint_G46Vss2_1111_', 'DCDKHT_MGTdesFF_05hpoint_G46Vss2_1111_']
for i in range(len(folder_names)):
rp.retrieve_data(folder_names[i], instance_base[i])
def analysis_exp_1011():
# TODO fix naming! - parent
# name format 1009NCDKHT-b
rp = RiskPlot()
datename = ['1012']
config = ['DCDKHT']
probname = ['h']
pername = [100]
n_runs = 485
add = ['PK']
rp.retrieve_data(datename, config, probname, pername, n_runs, add)
return None
def plot_1000_op1():
"""250 instances per config
outcomes, times, losses in a row
"""
"""Input name of pickle file in data_compiled"""
n_runs = 1000
rp = RiskPlot(n_runs)
pickle_list = [
'0107-NC-NK-NA', '0107-PT-PK-345', '0107-PB-PK-345', '0107-PT-PU-345',
'0107-PB-PU-345', '0107-NC-DK-NA'
]
# rp.retrieve_outcomes(pickle_list)
# rp.retrieve_casualties(pickle_list)
rp.retrieve_times(pickle_list)
def plot_configs_op2():
"""250 instances per config
outcomes, times, losses in a row
"""
"""Input name of pickle file in data_compiled"""
n_runs = 250
rp = RiskPlot(n_runs)
pickle_list = [
'0106-PT-PU-345', '0106-PT-PU-335', '0106-PT-PU-333', '0106-PB-PU-345',
'0106-PB-PU-335', '0106-PB-PU-333'
]
# rp.retrieve_outcomes(pickle_list)
# rp.retrieve_casualties(pickle_list)
rp.retrieve_times(pickle_list)
def plot_graph_danger():
risk_data = RiskPlot()
ground_truth = 'gt_danger_NFF'
estimation = 'estimate_danger_fire_des_NFF_freq_05'
list_danger = [ground_truth, estimation]
risk_data.set_danger_files(list_danger)
risk_data.print_danger_data()
risk_data.plot_graph_school()
def compile_1000_op2():
"""250 instances per config
outcomes, times, losses in a row
different team makeups
"""
"""Input name of folder in data_saved and instance base"""
n_runs = 1000
rp = RiskPlot(n_runs)
folder_names = [
'0107-PT-PU-335', '0108-PT-PU-333', '0108-PB-PU-335', '0108-PB-PU-333'
]
instance_base = [
'DKDCPT_PU335_desFF_05_G46Vss2_0107_',
'DKDCPT_PU333_desFF_05_G46Vss2_0108_',
'DKDCPB_PU335_desFF_05_G46Vss2_0108_',
'DKDCPB_PU333_desFF_05_G46Vss2_0109_'
]
for i in range(len(folder_names)):
rp.retrieve_data(folder_names[i], instance_base[i])
def compile_1000_op1():
"""250 instances per config
outcomes, times, losses in a row
"""
"""Input name of folder in data_saved and instance base"""
n_runs = 1000
rp = RiskPlot(n_runs)
folder_names = [
'0107-NC-NK-NA', '0107-PT-PK-345', '0107-PB-PK-345', '0107-PT-PU-345',
'0107-PB-PU-345', '0107-NC-DK-NA'
]
instance_base = [
'NKNC_desFF_NA_G46Vss2_0107_', 'DKDCPT_PK345_desFF_NA_G46Vss2_0107_',
'DKDCPB_PK345_desFF_NA_G46Vss2_0108_',
'DKDCPT_PU345_desFF_05_G46Vss2_0106_',
'DKDCPB_PU345_desFF_05_G46Vss2_0108_', 'DKNC_desFF_NA_G46Vss2_0107_'
]
for i in range(len(folder_names)):
rp.retrieve_data(folder_names[i], instance_base[i])
def plot_for_paper():
# 3 plots mission outcome, casualties, mission times
rp = RiskPlot()
# [ND, PK, PU, NC]
# [0, 1, 2, 3, 4]
# fig 1
pickle_list = ['1111DCDKHT_HGTFC-PT-05', '1111DCDKHT_HGTFF-PT-05', '1111DCDKHT_MGTFF-PT-05', '1111DCDKHT_MGTFC-PT-05']
# ['1013NCNKHT-n-0', '1012DCDKHT-h-PK', '1015DCDKHT-PK-prob', '1012DCDKHT-h-05', '1015DCDKHHT-05-PT', '1015DCDKHT-05-prob', '1012NCDKHT-h-NA']
# FIG 2
# pickle_list = ['1012DCDKHT-h-05', ]
rp.retrieve_outcomes(pickle_list)
rp.retrieve_casualties(pickle_list)
rp.retrieve_times(pickle_list)
def compile_configs_op2():
"""250 instances per config
outcomes, times, losses in a row
different team makeups
"""
"""Input name of folder in data_saved and instance base"""
n_runs = 250
rp = RiskPlot(n_runs)
folder_names = [
'0106-PT-PU-335', '0106-PT-PU-333', '0106-PB-PU-335', '0106-PB-PU-333'
]
instance_base = [
'DCDKHT_MGTdesFF_05hpoint_G46Vss2_0106_',
'DCDKHH_MGTdesFF_05hpoint_G46Vss2_0106_',
'DKDCPB_PU335_desFF_05_G46Vss2_0106_',
'DKDCPB_PU333_desFF_05_G46Vss2_0106_'
]
for i in range(len(folder_names)):
if i == 0:
continue
rp.retrieve_data(folder_names[i], instance_base[i])
def compile_configs_op1():
"""250 instances per config
outcomes, times, losses in a row
"""
"""Input name of folder in data_saved and instance base"""
n_runs = 250
rp = RiskPlot(n_runs)
folder_names = [
'0106-NC-NK-NA', '0106-PT-PK-345', '0106-PB-PK-345', '0106-PT-PU-345',
'0106-PB-PU-345', '0106-NC-DK-NA'
]
instance_base = [
'NCNKHT_MGTdesFF_NApoint_G46Vss2_0106_',
'DCDKHT_MGTdesFF_100hpoint_PK_G46Vss2_0106_',
'DKDCPB_PK345_desFF_NA_G46Vss2_0106_',
'DCDKHT_MGTdesFF_05hpoint_G46Vss2_0105_',
'DKDCPB_PU345_desFF_05_G46Vss2_0106_',
'NCDKHT_MGTdesFF_NAhpoint_G46Vss2_0106_'
]
for i in range(len(folder_names)):
rp.retrieve_data(folder_names[i], instance_base[i])
def analysis_exp_1012():
rp = RiskPlot()
datename = ['1012', '1013']
config = ['DCDKHT', 'NCDKHT']
extra_id = ['PK', '100', '05', 'NA', 'NFOV']
pername = [5, 100]
n_runs = 1000
perception = 'point'
folders = []
"""1012DCDKHT-h-PK"""
folders.append(rp.assemble_parent_name(datename[0], config[0], extra_id[0])[0])
"""1012DCDKHT-h-100"""
folders.append(rp.assemble_parent_name(datename[0], config[0], extra_id[1])[0])
"""1012DCDKHT-h-05"""
folders.append(rp.assemble_parent_name(datename[0], config[0], extra_id[2])[0])
"""1012NCDKHT-h-NA"""
folders.append(rp.assemble_parent_name(datename[0], config[1], extra_id[3])[0])
folders.append('1013NCNKHT-n-0')
"""1013NCDKHT-h-NFOV """
folders.append(rp.assemble_parent_name(datename[1], config[0], extra_id[4])[0])
#
subtitle = ['Perfect Knowledge', '100\% images', '5\% images', 'No Constraints', 'No Danger', 'no FOV']
# rp.retrieve_data(folders[0], 'DCDKHT_100hpoint_PK_G46Vss2_1012_', subtitle[0])
# rp.retrieve_data(folders[1], 'DCDKHT_100hpoint_G46Vss2_1012_', subtitle[1])
# rp.retrieve_data(folders[2], 'DCDKHT_05hpoint_G46Vss2_1012_', subtitle[2])
# rp.retrieve_data(folders[3], 'NCDKHT_NAhpoint_G46Vss2_1012_', subtitle[3])
# rp.retrieve_data(folders[4], 'NCNKHT_NApoint_G46Vss2_1013_', subtitle[4])
subtitle.append('no FOV')
rp.retrieve_data(folders[5], 'DCDKHT_05hpoint_NFOV_G46Vss2_1013_', subtitle[4])
def analysis_exp_1010():
"""1009NCDKHT-b"""
# code for simulation folders
datename = ['1009', '1010']
probname = ['b', 's']
pername = [5, 100]
config = ['NCDKHT', 'DCDKHT']
n_runs = 1000
rp = RiskPlot()
parent_folders = list()
parent_folders.append(rp.assemble_parent_name(datename[0], config[0], probname[0]))
parent_folders.append(rp.assemble_parent_name(datename[1], config[1], probname[0]))
parent_folders.append(rp.assemble_parent_name(datename[1], config[0], probname[1]))
parent_folders.append(rp.assemble_parent_name(datename[1], config[1], probname[1]))
# NC-b
stats_nc_b = MyStats(parent_folders[0], n_runs, pername[1])
# MyStats(parent_folders[0], n_runs, pername[0])
# DC-b
stats_dc_b = MyStats(parent_folders[1], n_runs, pername[1])
# MyStats(parent_folders[1], n_runs, pername[0])
# rp.add_stats(stats_nc_b)
# rp.add_stats(stats_dc_b)
rp.plot_stat([stats_nc_b.cum_success_rate, stats_dc_b.cum_success_rate], 'Success Rate', ['NC', 'DC'])
# # NC-s
# stats_nc_s = MyStats(parent_folders[2], n_runs, pername[1])
# MyStats(parent_folders[2], n_runs, pername[0])
#
# # DC-s
# stats_dc_s = MyStats(parent_folders[3], n_runs, pername[1])
#
# rp.add_stats(stats_nc_s)
# rp.add_stats(stats_dc_s)
# rp.plot_stat()
return
def plot_only():
extension = '.pkl'
folder_path = MyDanger.get_folder_path('data_compiled')
low_prob = ['1010NCDKHT-s-100', '1010DCDKHT-s-100']
high_prob = ['1009NCDKHT-b-100', '1009NCDKHT-b-05', '1010DCDKHT-b-100', '1010DCDKHT-b-05']
f_names = low_prob
success_rate = []
casualty_mission_rate = []
avg_mission_time = []
casualty_mvp = []
for f_name in f_names:
f_path = folder_path + '/' + f_name + extension
stats = bf.load_pickle_file(f_path)
# ---
stats.print_name(stats.parent_name, '--\nStats for')
stats.print_final_stats()
success_rate.append(copy.deepcopy(stats.cum_success_rate))
casualty_mission_rate.append(copy.deepcopy(stats.cum_casualty_mission_rate))
avg_mission_time.append(copy.deepcopy(stats.cum_mission_time))
casualty_mvp.append(copy.deepcopy(stats.cum_casualty_mvp_rate))
print(stats.prob_kill)
del stats
rp = RiskPlot()
for success in success_rate:
rp.add_stats(success)
rp.plot_stat()
rp.clear_list()
#
for avg_time in avg_mission_time:
rp.add_stats(avg_time)
#
rp.plot_stat()
rp.clear_list()
for casual in casualty_mission_rate:
rp.add_stats(casual)
rp.plot_stat()
rp.clear_list()
for mvp in casualty_mvp:
rp.add_stats(mvp)
rp.plot_stat()
rp.clear_list()