def application(report_file):
#pdb.set_trace()
#print( "Post-processing: " + report_file )
cdj = json.loads(open("config.json").read())["parameters"]
tcer = float(cdj["Typhoid_Contact_Exposure_Rate"])
teer = float(cdj["Typhoid_Environmental_Exposure_Rate"])
start_time = cdj["Start_Time"]
timestep = start_time
num_exposures_contact = []
num_exposures_enviro = []
with open("test.txt") as logfile:
route = None
for line in logfile:
if re.search("Exposing ", line) and re.search(
"route 'environment'", line):
# collect # of exposures for route contact
num_exp_e = get_val("num_exposures=", line)
num_exposures_enviro.append(num_exp_e)
if re.search("Exposing ", line) and re.search(
"route 'contact'", line):
# collect # of exposures for route environment
num_exp_c = get_val("num_exposures=", line)
num_exposures_contact.append(num_exp_c)
success = True
with open(sft.sft_output_filename, "w") as report_file:
if len(num_exposures_enviro) == 0:
success = False
report_file.write(
"Found no individual exposed from route environment.\n")
elif not sft.test_poisson(num_exposures_enviro, teer, report_file,
'environment'):
success = False
if len(num_exposures_contact) == 0:
success = False
report_file.write(
"Found no individual exposed from route contact.\n")
elif not sft.test_poisson(num_exposures_contact, tcer, report_file,
'contact'):
success = False
if success:
report_file.write(sft.format_success_msg(success))
os.remove("test.txt")
def create_report_file(param_obj, campaign_obj, demographics_obj,
report_data_obj, report_name, debug):
with open(report_name, "w") as outfile:
success = True
total_timesteps = param_obj[KEY_TOTAL_TIMESTEPS]
start_timestep = param_obj[KEY_START_TIME]
initial_population = demographics_obj[KEY_INITIAL_POPULATION]
rates = campaign_obj[KEY_CAMPAIGN_DIP]
durations = campaign_obj[KEY_CAMPAIGN_DURATIONS]
if not report_data_obj: # todo: maybe use try
success = False
outfile.write("BAD: There is no data in the InsetChart report")
else:
new_infections = report_data_obj[KEY_NEW_INFECTIONS]
statistical_population = report_data_obj[
KEY_STATISTICAL_POPULATION]
length = len(rates)
start_duration = start_timestep
new_infections_dict = {}
calculate_new_population = initial_population
for i in range(length):
rate = rates[i]
duration = durations[i]
calculate_new_population = rate * duration + calculate_new_population
end_duration = duration + start_duration
if rate not in new_infections_dict:
new_infections_dict[rate] = []
for j in range(start_duration + 1, end_duration + 1):
if j < total_timesteps + start_timestep:
new_infections_dict[rate].append(new_infections[j])
j += 1
else:
break
if end_duration > total_timesteps + start_timestep:
calculate_new_population -= rate * (
end_duration - total_timesteps - start_timestep)
break
start_duration = end_duration
if end_duration < total_timesteps + start_timestep:
rate = 0.0
if rate not in new_infections_dict:
new_infections_dict[rate] = []
for j in range(end_duration + 1, len(new_infections)):
new_infections_dict[rate].append(new_infections[j])
with open("new_infections_parsed.json", "w") as file:
json.dump(new_infections_dict, file, indent=4)
# test statistical population channel
diff_population = math.fabs(calculate_new_population -
statistical_population[-1])
if debug:
print( "calculated population is {0}, statistical population " \
"from InsetChart is {1}.".format(calculate_new_population,
statistical_population[-1]) )
error_tolerance = math.fabs(calculate_new_population -
initial_population) * 0.1
if debug:
print("diff_population is {0}, error_tolerance is {1}".format(
diff_population, error_tolerance))
if diff_population > error_tolerance:
success = False
outfile.write(
"BAD: statistical population is {0}, expected about {1}.\n"
.format(statistical_population[-1],
calculate_new_population))
# test poisson distribution for new infections
for rate in new_infections_dict:
dist = new_infections_dict[rate]
title = "rate = " + str(rate)
result = sft.test_poisson(dist,
rate,
route=title,
report_file=outfile,
normal_approximation=False)
# print result, rate, len(dist)
if not result:
success = False
outfile.write(
"BAD: ks poisson test for {0} is {1}.\n".format(
title, result))
numpy_distro = np.random.poisson(rate, len(dist))
sft.plot_data(
dist,
numpy_distro,
title="new infections for {}".format(title),
label1="new infection from model, {}".format(title),
label2="Poisson distro from numpy",
xlabel="data points",
ylabel="new infection",
category="plot_data_{0}".format(title),
show=True)
sft.plot_probability(
dist,
numpy_distro,
title="probability mass function for {}".format(title),
label1="new infection probability from model",
label2="new infection probability from numpy distro",
category="plot_probability_{0}".format(title),
show=True)
outfile.write(sft.format_success_msg(success))
if debug:
print("SUMMARY: Success={0}\n".format(success))
return success
def create_report_file(param_obj, campaign_obj, demographics_obj, report_data_obj, report_name, debug):
with open(report_name, "w") as outfile:
success = True
total_timesteps = param_obj[KEY_TOTAL_TIMESTEPS]
start_timestep = param_obj[KEY_START_TIME]
initial_population = demographics_obj[KEY_INITIAL_POPULATION]
rates = campaign_obj[KEY_CAMPAIGN_DIP]
durations = campaign_obj[KEY_CAMPAIGN_DURATIONS]
if not report_data_obj: # todo: maybe use try
success = False
outfile.write("BAD: There is no data in the InsetChart report")
else:
new_infections = report_data_obj[KEY_NEW_INFECTIONS]
statistical_population = report_data_obj[KEY_STATISTICAL_POPULATION]
length = len(rates)
start_duration = start_timestep
new_infections_dict = {}
calculate_new_population = initial_population
for i in range(length):
rate = rates[i]
duration = durations[i]
calculate_new_population = rate * duration + calculate_new_population
end_duration = duration + start_duration
if rate not in new_infections_dict:
new_infections_dict[rate] = []
for j in range(start_duration + 1, end_duration + 1):
if j < total_timesteps + start_timestep:
new_infections_dict[rate].append(new_infections[j])
j += 1
else:
break
if end_duration > total_timesteps + start_timestep:
calculate_new_population -= rate * (end_duration - total_timesteps - start_timestep)
break
start_duration = end_duration
if end_duration < total_timesteps + start_timestep:
rate = 0.0
if rate not in new_infections_dict:
new_infections_dict[rate] = []
for j in range(end_duration + 1, len(new_infections)):
new_infections_dict[rate].append(new_infections[j])
with open("new_infections_parsed.json","w") as file:
json.dump(new_infections_dict, file, indent = 4)
# test statistical population channel
diff_population = math.fabs(calculate_new_population - statistical_population[-1])
if debug:
print "calculated population is {0}, statistical population " \
"from InsetChart is {1}.".format(calculate_new_population,
statistical_population[-1])
error_tolerance = math.fabs(calculate_new_population - initial_population)* 0.1
if debug:
print "diff_population is {0}, error_tolerance is {1}".format(diff_population, error_tolerance)
if diff_population > error_tolerance:
success = False
outfile.write("BAD: statistical population is {0}, expected about {1}.\n".format(statistical_population[-1], calculate_new_population))
# test poisson distribution for new infections
for rate in new_infections_dict:
dist = new_infections_dict[rate]
title = "rate = " + str(rate)
result = sft.test_poisson(dist, rate, route = title, report_file = outfile, normal_approximation = False)
# print result, rate, len(dist)
if not result:
success = False
outfile.write("BAD: ks poisson test for {0} is {1}.\n".format(title, result))
numpy_distro = np.random.poisson(rate, len(dist))
sft.plot_data(dist, sorted(numpy_distro),
title="new infections for {}".format(title),
label1="new infection from model, {}".format(title),
label2="Poisson distro from numpy",
xlabel="data points", ylabel="new infection",
category="plot_data_{0}".format(title), show=True)
sft.plot_probability(dist, numpy_distro,
title="probability mass function for {}".format(title),
label1="new infection probability from model",
label2="new infection probability from numpy distro",
category="plot_probability_{0}".format(title), show=True)
outfile.write(sft.format_success_msg(success))
if debug:
print "SUMMARY: Success={0}\n".format(success)
return success