abs_errors_retrofitted = []
# calculate retrofitted time.
refugees_in_camps_sim = 0
for c in camps:
refugees_in_camps_sim += c.numAgents
# t_retrofitted = d.retrofit_time_to_refugee_count(refugees_in_camps_sim, camp_names)
# calculate errors
for i in range(0, len(camp_locations)):
camp_number = camp_locations[i]
errors += [
a.rel_error(locations[camp_number].numAgents, loc_data[i])
]
abs_errors += [
a.abs_error(locations[camp_number].numAgents, loc_data[i])
]
# errors when using retrofitted time stepping.
# TODO: T_RETROFITTED IS USED HERE BUT IS STILL INITIALIZED ON 0......
# camp_pops_retrofitted += [d.get_field(camp_names[i], t_retrofitted, FullInterpolation=True)]
camp_pops_retrofitted += [
d.get_field(camp_names[i], t, FullInterpolation=True)
]
errors_retrofitted += [
a.rel_error(camps[i].numAgents, camp_pops_retrofitted[-1])
]
abs_errors_retrofitted += [
a.abs_error(camps[i].numAgents, camp_pops_retrofitted[-1])
]
for i in camp_locations:
camps += [locations[i]]
camp_names = ["Mahama", "Nduta", "Nyarugusu", "Nakivale", "Lusenda"]
refugees_in_camps_sim = 0
for c in camps:
refugees_in_camps_sim += c.numAgents
# calculate errors
for i in range(0, len(camp_locations)):
camp_number = camp_locations[i]
errors += [
a.rel_error(locations[camp_number].numAgents, loc_data[i])
]
abs_errors += [
a.abs_error(locations[camp_number].numAgents, loc_data[i])
]
output = "%s" % t
for i in range(0, len(errors)):
camp_number = camp_locations[i]
output += ",%s,%s,%s" % (locations[camp_number].numAgents,
loc_data[i], errors[i])
if refugees_raw > 0:
#output_string += ",%s,%s,%s,%s" % (float(np.sum(abs_errors))/float(refugees_raw), int(sum(loc_data)), e.numAgents(), refugees_raw)
output += ",%s,%s,%s,%s,%s,%s" % (
float(np.sum(abs_errors)) / float(refugees_raw),
int(sum(loc_data)), e.numAgents(), refugees_raw,
refugees_in_camps_sim, refugee_debt)
camp_pops_retrofitted = []
errors_retrofitted = []
abs_errors_retrofitted = []
# calculate retrofitted time.
refugees_in_camps_sim = 0
for c in camps:
refugees_in_camps_sim += c.numAgents
t_retrofitted = d.retrofit_time_to_refugee_count(refugees_in_camps_sim, camp_locations)
# calculate errors
j=0
for i in camp_locations:
errors += [a.rel_error(lm[i].numAgents, loc_data[j])]
abs_errors += [a.abs_error(lm[i].numAgents, loc_data[j])]
# errors when using retrofitted time stepping.
camp_pops_retrofitted += [d.get_field(i, t_retrofitted, FullInterpolation=True)]
errors_retrofitted += [a.rel_error(lm[i].numAgents, camp_pops_retrofitted[-1])]
abs_errors_retrofitted += [a.abs_error(lm[i].numAgents, camp_pops_retrofitted[-1])]
j += 1
output = "%s" % t
for i in range(0,len(errors)):
output += ",%s,%s,%s" % (lm[camp_locations[i]].numAgents, loc_data[i], errors[i])
if refugees_raw>0:
camps = []
for i in camp_locations:
camps += [lm[i]]
loc_data += [d.get_field(i, t)]
# calculate retrofitted time.
refugees_in_camps_sim = 0
for c in camps:
refugees_in_camps_sim += c.numAgents
# calculate errors
j = 0
for i in camp_locations:
errors += [a.rel_error(lm[i].numAgents, loc_data[j])]
abs_errors += [a.abs_error(lm[i].numAgents, loc_data[j])]
j += 1
output = "%s" % t
for i in range(0, len(errors)):
output += ",%s,%s,%s" % (lm[camp_locations[i]].numAgents,
loc_data[i], errors[i])
if refugees_raw > 0:
#output_string += ",%s,%s,%s,%s" % (float(np.sum(abs_errors))/float(refugees_raw), int(sum(loc_data)), e.numAgents(), refugees_raw)
output += ",%s,%s,%s,%s,%s,%s" % (
float(np.sum(abs_errors)) / float(refugees_raw),
int(sum(loc_data)), e.numAgents(), refugees_raw,
refugees_in_camps_sim, refugee_debt)
refugees_in_camps_sim, camp_names)
# calculate error terms.
camp_pops = []
errors = []
abs_errors = []
camp_pops_retrofitted = []
errors_retrofitted = []
abs_errors_retrofitted = []
for i in range(0, len(camp_names)):
# normal 1 step = 1 day errors.
camp_pops += [
d.get_field(camp_names[i], t, FullInterpolation=True)
]
errors += [a.rel_error(camps[i].numAgents, camp_pops[-1])]
abs_errors += [a.abs_error(camps[i].numAgents, camp_pops[-1])]
# errors when using retrofitted time stepping.
camp_pops_retrofitted += [
d.get_field(camp_names[i],
t_retrofitted,
FullInterpolation=True)
]
errors_retrofitted += [
a.rel_error(camps[i].numAgents, camp_pops_retrofitted[-1])
]
abs_errors_retrofitted += [
a.abs_error(camps[i].numAgents, camp_pops_retrofitted[-1])
]
# Total error is calculated using float(np.sum(abs_errors))/float(refugees_raw))
