key_part1_str = args.key_part1_str
key_part2_str = args.key_part2_str
probe_id = args.probe_id
summaries_file = args.summaries_file
list_of_headings = [key_part1_str + " ; " + key_part2_str, key_part1_str, key_part2_str, 'ping', 'dns', 'traceroute', 'num_origins', 'origins_list']
list_of_entries = listdir(data_path)
list_of_files = [join(data_path, f) for f in list_of_entries if isfile(join(data_path, f))]
results_dict = {}
# build results_dict
for this_file in list_of_files:
print("reading " + this_file)
measurement_id = Measurement_Data.get_measurement_id_from_file(this_file)
# handle empty file
if measurement_id == None:
print(this_file + " appears to be empty. Skipping.")
continue
# handle nonempty file
measurement_data = Measurement_Data(measurement_id, this_file, summaries_file)
measurement_data.add_compound_key_results(probe_id, results_dict, key_part1_str, key_part2_str)
# write results_dict to file
with open(json_dict_file, 'w') as f:
json.dump(results_dict, f)
# print(Measurement_Data.calc_results_summary(json_dict_file))
help="A file containing a dictionary of measurement_id : measurement_summary. If ommitted, summaries are obtained from internet.")
return parser.parse_args()
if __name__ == "__main__":
args = parse_args()
summaries_file = args.summaries_file
data_path = args.data_path
probe_id = args.probe_id
out_file = args.out_file
list_of_entries = listdir(data_path)
list_of_files = [join(data_path, f) for f in list_of_entries if isfile(join(data_path, f))]
for this_file in list_of_files:
print("reading "+this_file)
# Get measurement ID
measurement_id = Measurement_Data.get_measurement_id_from_file(this_file)
if measurement_id == None:
print(this_file + " appears to be empty. Skipping.")
continue # go to next file
# Get data from this file
measurement_data = Measurement_Data(measurement_id, this_file, summaries_file)
if measurement_data.type == 'ping':
ping_data = Ping_Data(measurement_id, this_file, summaries_file)
ping_data.write_data_to_csv(csv_file, probe_id)
csv_file = args.csv_file
data_path = args.data_path
probe_id = args.probe_id
summaries_file = args.summaries_file
list_of_headings = ['probe_id ; target', 'probe_id', 'target', 'ping', 'dns', 'traceroute', 'num_origins', 'origins_list']
list_of_entries = listdir(data_path)
list_of_files = [join(data_path, f) for f in list_of_entries if isfile(join(data_path, f))]
results_dict = {}
# build results_dict
for this_file in list_of_files:
print("reading "+this_file)
measurement_id = Measurement_Data.get_measurement_id_from_file(this_file)
# handle empty file
if measurement_id == None:
print(this_file + " appears to be empty. Skipping.")
continue
# handle nonempty file
measurement_data = Measurement_Data(measurement_id, this_file, summaries_file)
measurement_data.add_probe_and_target_results(results_dict)
# write results_dict to file
with open(json_dict_file, 'w') as f:
json.dump(results_dict, f)
# print(Measurement_Data.calc_results_summary(json_dict_file))
)
return parser.parse_args()
# Call the script by typing:
# $ python explore_data.py filename [limit] [summaries_file]
# where filename is the name of a file containing a ripe atlas response
if __name__ == "__main__":
args = parse_args()
summaries_file = args.summaries_file
data_path = args.data_path
probe_id = args.probe_id
csv_file = join(args.csv_path, CSV_FILE_PREFIX + str(probe_id) + ".csv")
list_of_headings = Ping_Data.get_ping_headings()
Measurement_Data.prep_csv_file(csv_file, list_of_headings)
list_of_entries = listdir(data_path)
list_of_files = [
join(data_path, f) for f in list_of_entries
if isfile(join(data_path, f))
]
for this_file in list_of_files:
print("reading " + this_file)
measurement_id = Measurement_Data.get_measurement_id_from_file(
this_file)
if measurement_id == None:
print(this_file + " appears to be empty. Skipping.")
continue
key_name = args.key_name
data_path = args.data_path
probe_id = args.probe_id
summaries_file = args.summaries_file
list_of_headings = ['probe_id', 'ping', 'dns', 'traceroute', 'num_targets', 'targets_list', 'num_origins', 'origins_list']
list_of_entries = listdir(data_path)
list_of_files = [join(data_path, f) for f in list_of_entries if isfile(join(data_path, f))]
results_dict = {}
# build results_dict
for this_file in list_of_files:
print("reading "+this_file)
measurement_id = Measurement_Data.get_measurement_id_from_file(this_file)
# handle empty file
if measurement_id == None:
print(this_file + " appears to be empty. Skipping.")
continue
# handle nonempty file
measurement_data = Measurement_Data(measurement_id, this_file, summaries_file)
measurement_data.add_to_results_dict(key_name, results_dict)
# write results_dict to file
with open(json_dict_file, 'w') as f:
json.dump(results_dict, f)
# print(Measurement_Data.calc_results_summary(json_dict_file))
parser = argparse.ArgumentParser(
description='Given a dictionary with RIPE measurement data, builds a CDF showing the time between measurements.')
parser.add_argument('json_dict_files', type=str, nargs="+",
help="A the paths and filenames containing data in json format. e.g. timestamp_probe1.json timestamp_probe22.json ...")
return parser.parse_args()
if __name__ == "__main__":
args = parse_args()
json_dict_files = args.json_dict_files
#json_dict_files = json.loads(json_dict_files)
list_of_time_differences = []
for dict_file in json_dict_files:
Measurement_Data.write_compound_key_dict_to_list(dict_file, list_of_time_differences)
print("num measurements: " + str(len(list_of_time_differences)))
#list_of_time_differences = [1448020803, 1448020805, 1448020808, 1448020808, 1448020816, 1448020831, 1448020834, 1448020855]
plt.figure(figsize=(4.5,3.5))
linedata = ECDF(list_of_time_differences)
plt.plot(linedata.x, linedata.y, lw=3)
plt.xlabel("Time between measurements (s)")
plt.ylabel("CDF of measurements")
plt.ylim(0,1)
#plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)
#plt.savefig(os.path.join(full_path, "num_networks.pdf"), bbox_inches="tight")
#plt.close()
plt.show()
'probe_id ; target', 'probe_id', 'target', 'ping', 'dns', 'traceroute',
'num_origins', 'origins_list'
]
list_of_entries = listdir(data_path)
list_of_files = [
join(data_path, f) for f in list_of_entries
if isfile(join(data_path, f))
]
results_dict = {}
# build results_dict
for this_file in list_of_files:
print("reading " + this_file)
measurement_id = Measurement_Data.get_measurement_id_from_file(
this_file)
# handle empty file
if measurement_id == None:
print(this_file + " appears to be empty. Skipping.")
continue
# handle nonempty file
measurement_data = Measurement_Data(measurement_id, this_file,
summaries_file)
measurement_data.add_probe_and_target_results(results_dict)
# write results_dict to file
with open(json_dict_file, 'w') as f:
json.dump(results_dict, f)
help="A file containing a dictionary of measurement_id : measurement_summary. If ommitted, summaries are obtained from internet.")
return parser.parse_args()
# Call the script by typing:
# $ python explore_data.py filename [limit] [summaries_file]
# where filename is the name of a file containing a ripe atlas response
if __name__ == "__main__":
args = parse_args()
summaries_file = args.summaries_file
data_path = args.data_path
probe_id = args.probe_id
csv_file = join(args.csv_path, CSV_FILE_PREFIX+str(probe_id)+".csv")
list_of_headings = Ping_Data.get_ping_headings()
Measurement_Data.prep_csv_file(csv_file, list_of_headings)
list_of_entries = listdir(data_path)
list_of_files = [join(data_path, f) for f in list_of_entries if isfile(join(data_path, f))]
for this_file in list_of_files:
print("reading "+this_file)
measurement_id = Measurement_Data.get_measurement_id_from_file(this_file)
if measurement_id == None:
print(this_file + " appears to be empty. Skipping.")
continue
measurement_data = Measurement_Data(measurement_id, this_file, summaries_file)
if measurement_data.type == 'ping':
ping_data = Ping_Data(measurement_id, this_file, summaries_file)
'probe_id', 'ping', 'dns', 'traceroute', 'num_targets', 'targets_list',
'num_origins', 'origins_list'
]
list_of_entries = listdir(data_path)
list_of_files = [
join(data_path, f) for f in list_of_entries
if isfile(join(data_path, f))
]
results_dict = {}
# build results_dict
for this_file in list_of_files:
print("reading " + this_file)
measurement_id = Measurement_Data.get_measurement_id_from_file(
this_file)
# handle empty file
if measurement_id == None:
print(this_file + " appears to be empty. Skipping.")
continue
# handle nonempty file
measurement_data = Measurement_Data(measurement_id, this_file,
summaries_file)
measurement_data.add_to_results_dict(key_name, results_dict)
# write results_dict to file
with open(json_dict_file, 'w') as f:
json.dump(results_dict, f)