def test_snd_scenario():
setup_logging()
scenario = SndScenario()
scenario.run(duration=pd.Timedelta("1h30m"),
delete_existing_logs=True,
log_output_folder=params["output_folder"])
logs = load_all_logs(params["output_folder"])
for logid, lg in logs.items():
log_dataframe_sample(" - some {}".format(logid), lg)
purchases = logs["purchases"]
log_dataframe_sample(" - some failed purchases: ",
purchases[purchases["FAILED_SALE"]])
sales_of_broke = purchases[purchases["DEALER"] == "broke_dealer"]
log_dataframe_sample(" - some purchases from broke dealer: ",
sales_of_broke)
all_logs_size = np.sum(df.shape[0] for df in logs.values())
logging.info("\ntotal number of logs: {}".format(all_logs_size))
for logid, lg in logs.items():
logging.info(" {} {} logs".format(len(lg), logid))
# broke dealer should have maximum 3 successful sales
ok_sales_of_broke = sales_of_broke[~sales_of_broke["FAILED_SALE"]]
assert ok_sales_of_broke.shape[0] <= 3
def run_cdr_scenario(params):
setup_logging()
logging.info("test_cdr_scenario")
# building the circus
start_time = pd.Timestamp(datetime.now())
scenario = CdrScenario(params)
built_time = pd.Timestamp(datetime.now())
# running it
scenario.run(duration=pd.Timedelta(params["simulation_duration"]),
delete_existing_logs=True,
log_output_folder=params["output_folder"])
logs = load_all_logs(params["output_folder"])
execution_time = pd.Timestamp(datetime.now())
for logid, lg in logs.items():
logging.info(" - some {}:\n{}\n\n".format(logid,
lg.head(15).to_string()))
logging.info("MSISDNs having highest amount of calls: ")
voice_cdr = logs["voice_cdr"]
top_users = voice_cdr["MSISDN_A"].value_counts().head(10)
logging.info(top_users)
logging.info("some dropped calls: ")
dropped_calls = voice_cdr[voice_cdr["STATUS"] == "DROPPED"]
if dropped_calls.shape[0] > 15:
logging.info(dropped_calls.sample(15).sort_values("DATETIME"))
else:
logging.info(dropped_calls)
all_logs_size = np.sum(df.shape[0] for df in logs.values())
logging.info("\ntotal number of logs: {}".format(all_logs_size))
for logid, lg in logs.items():
logging.info(" {} {} logs".format(len(lg), logid))
logging.info("""\nexecution times: "
- building the circus: {}
- running the simulation: {}
""".format(built_time - start_time, execution_time - built_time))
import logging
import pandas as pd
from trumania.core import circus
import trumania.core.util_functions as util_functions
from trumania.core.operations import FieldLogger
from trumania.core.random_generators import SequencialGenerator, FakerGenerator, NumpyRandomGenerator
from trumania.core.random_generators import ConstantDependentGenerator, ConstantGenerator
util_functions.setup_logging()
logging.info("building circus")
def create_circus_with_population():
example_circus = circus.Circus(name="example",
master_seed=12345,
start=pd.Timestamp("1 Jan 2017 00:00"),
step_duration=pd.Timedelta("1h"))
person = example_circus.create_population(
name="person",
size=1000,
ids_gen=SequencialGenerator(prefix="PERSON_"))
person.create_attribute("NAME",
init_gen=FakerGenerator(
method="name",
seed=next(example_circus.seeder)))
person.create_attribute("age",
import logging
from test_cdr import run_cdr_scenario
from trumania.core.util_functions import setup_logging
# better run this outside of PyCharm for consistent measures...
#
# python tests/scenarios/long_cdr.py
if __name__ == "__main__":
setup_logging()
logging.info("starting a long CDR test ")
params = {
"time_step": 60,
"n_cells": 200,
"n_agents": 500,
"n_subscribers": 25000,
"average_degree": 20,
"n_iterations": 200
}
run_cdr_scenario(params)
"""
result on Svends's laptop:
total number of logs: 392086
execution times: "
- building the circus: 0 days 00:01:32.156013
- running the simulation: 0 days 00:14:07.355875
