def calculate_fragility(capacity_curves, gmrs, damage_model, damping_model,
damping):
no_damage_states = len(damage_model['damage_states'])
no_gmrs = len(gmrs['time'])
no_capacity_curves = len(capacity_curves['Sd'])
PDM = numpy.zeros((no_gmrs, no_damage_states + 1))
Sds = numpy.zeros((no_gmrs, no_capacity_curves))
for icc in range(no_capacity_curves):
print str((icc + 1) * 100 / no_capacity_curves) + '%'
limit_states = utils.define_limit_states(capacity_curves, icc,
damage_model)
for igmr in range(no_gmrs):
damping = optimize.fmin(
calculate_performance_point,
0.05,
args=(gmrs, igmr, capacity_curves, icc, damping_model,
damping),
xtol=0.001,
ftol=0.001,
disp=False,
)
[PDM, ds] = utils.allocate_damage(igmr, PDM, Sdi, limit_states)
Sds[igmr][icc] = Sdi
return PDM, Sds
def calculate_fragility(capacity_curves, gmrs, damage_model, damping, hysteresis_model, damping_model):
no_damage_states = len(damage_model["damage_states"])
no_gmrs = len(gmrs["time"])
no_capacity_curves = len(capacity_curves["Sd"])
PDM = numpy.zeros((no_gmrs, no_damage_states + 1))
Sds = numpy.zeros((no_gmrs, no_capacity_curves))
c1, c2, cR, cT = get_parameters(hysteresis_model, damping_model)
if c1 > 0:
for icc in range(no_capacity_curves):
print str((icc + 1) * 100 / no_capacity_curves) + "%"
Te = capacity_curves["periods"][icc]
Sdy = capacity_curves["Sdy"][icc]
for igmr in range(no_gmrs):
limit_states = utils.define_limit_states(capacity_curves, icc, damage_model)
time = gmrs["time"][igmr]
acc = gmrs["acc"][igmr]
spec_Te = utils.NigamJennings(time, acc, [Te], damping)
spec_10sec = utils.NigamJennings(time, acc, [1.0], damping)
spec_03sec = utils.NigamJennings(time, acc, [0.3], damping)
Tc = spec_10sec["Sa"] / spec_03sec["Sa"]
Sdi = optimize.fmin(
calculate_Sd,
Sdy,
args=(spec_Te["Sd"], Tc, capacity_curves, icc, c1, c2, cR, cT),
xtol=0.001,
ftol=0.001,
disp=False,
)
[PDM, ds] = utils.allocate_damage(igmr, PDM, Sdi, limit_states)
Sds[igmr][icc] = Sdi
return PDM, Sds
def calculate_fragility(capacity_curves, gmrs, damage_model, damping,
hysteresis_model, damping_model):
no_damage_states = len(damage_model['damage_states'])
no_gmrs = len(gmrs['time'])
no_capacity_curves = len(capacity_curves['Sd'])
PDM = numpy.zeros((no_gmrs, no_damage_states + 1))
Sds = numpy.zeros((no_gmrs, no_capacity_curves))
c1, c2, cR, cT = get_parameters(hysteresis_model, damping_model)
if c1 > 0:
for icc in range(no_capacity_curves):
print str((icc + 1) * 100 / no_capacity_curves) + '%'
Te = capacity_curves['periods'][icc]
Sdy = capacity_curves['Sdy'][icc]
for igmr in range(no_gmrs):
limit_states = utils.define_limit_states(
capacity_curves, icc, damage_model)
time = gmrs['time'][igmr]
acc = gmrs['acc'][igmr]
spec_Te = utils.NigamJennings(time, acc, [Te], damping)
spec_10sec = utils.NigamJennings(time, acc, [1.0], damping)
spec_03sec = utils.NigamJennings(time, acc, [0.3], damping)
Tc = spec_10sec['Sa'] / spec_03sec['Sa']
Sdi = optimize.fmin(calculate_Sd,
Sdy,
args=(spec_Te['Sd'], Tc, capacity_curves,
icc, c1, c2, cR, cT),
xtol=0.001,
ftol=0.001,
disp=False)
[PDM, ds] = utils.allocate_damage(igmr, PDM, Sdi, limit_states)
Sds[igmr][icc] = Sdi
return PDM, Sds
def calculate_fragility(capacity_curves, hysteresis, msa, gmrs, damage_model,
damping, degradation):
no_damage_states = len(damage_model['damage_states'])
no_bins = msa['n. bins']
no_rec_bin = msa['records per bin']
no_gmrs = no_bins * no_rec_bin
no_capacity_curves = len(capacity_curves['Sd'])
PDM = numpy.zeros((no_bins, no_damage_states + 1))
Sds = numpy.zeros((no_gmrs, no_capacity_curves))
gmr_info = numpy.zeros((no_gmrs, 2))
for icc in range(no_capacity_curves):
print str((icc + 1) * 100 / no_capacity_curves) + '%'
folder_scaled_recs = msa['input folder']
target_files = os.listdir(folder_scaled_recs)
for ele in target_files:
if ele[-3:] != 'csv':
target_files.remove(ele)
counter = 0
for index, ibin in enumerate(target_files):
if index < no_bins:
print ibin
else:
break
with open(folder_scaled_recs + '/' + ibin, 'rb') as f:
reader = csv.reader(f)
newlist = [row for row in reader]
record_name = [ele[0] for ele in newlist]
record_scaling = [float(ele[1]) for ele in newlist]
for igmr in range(no_rec_bin):
limit_states = utils.define_limit_states(
capacity_curves, icc, damage_model)
target_name = record_name[igmr]
scaling_factor = record_scaling[igmr]
time, disps = run_time_history_analysis(
capacity_curves, hysteresis, icc, gmrs, target_name,
scaling_factor, damping, degradation)
Sdi = max(numpy.abs(numpy.array(disps)))
#with open('dynamicResult.csv', 'rb') as f:
#reader = csv.reader(f)
#newlist = [row[0] for row in reader]
#if newlist == ['KO']:
# ds = no_ls
[PDM, ds] = utils.allocate_damage(index, PDM, Sdi,
limit_states)
gmr_info[counter, :] = [
gmrs['name'].index(target_name), scaling_factor
]
Sds[counter][icc] = Sdi
counter = counter + 1
print "gmr n.", counter, "max disp. =", Sdi, "DS =", ds
return PDM, Sds, gmr_info
def calculate_fragility(capacity_curves, hysteresis, msa, gmrs,damage_model,damping,degradation):
no_damage_states = len(damage_model['damage_states'])
no_bins = msa['n. bins']
no_rec_bin = msa['records per bin']
no_gmrs = no_bins*no_rec_bin
no_capacity_curves = len(capacity_curves['Sd'])
PDM = numpy.zeros((no_bins,no_damage_states+1))
Sds = numpy.zeros((no_gmrs,no_capacity_curves))
gmr_info = numpy.zeros((no_gmrs,2))
for icc in range(no_capacity_curves):
print str((icc+1)*100/no_capacity_curves) + '%'
folder_scaled_recs = msa['input folder']
target_files = os.listdir(folder_scaled_recs)
for ele in target_files:
if ele[-3:] != 'csv':
target_files.remove(ele)
counter = 0
for index,ibin in enumerate(target_files):
if index < no_bins:
print ibin
else:
break
with open(folder_scaled_recs+'/'+ibin, 'rb') as f:
reader = csv.reader(f)
newlist = [row for row in reader]
record_name = [ele[0] for ele in newlist]
record_scaling = [float(ele[1]) for ele in newlist]
for igmr in range(no_rec_bin):
limit_states = utils.define_limit_states(capacity_curves, icc,damage_model)
target_name = record_name[igmr]
scaling_factor = record_scaling[igmr]
time, disps = run_time_history_analysis(capacity_curves,hysteresis,icc,gmrs,target_name,scaling_factor,damping,degradation)
Sdi = max(numpy.abs(numpy.array(disps)))
#with open('dynamicResult.csv', 'rb') as f:
#reader = csv.reader(f)
#newlist = [row[0] for row in reader]
#if newlist == ['KO']:
# ds = no_ls
[PDM, ds] = utils.allocate_damage(index,PDM,Sdi,limit_states)
gmr_info[counter,:] = [gmrs['name'].index(target_name), scaling_factor]
Sds[counter][icc] = Sdi
counter = counter+1
print "gmr n.", counter, "max disp. =", Sdi, "DS =", ds
return PDM, Sds, gmr_info
def calculate_fragility(capacity_curves,gmrs,damage_model,damping_model,damping):
no_damage_states = len(damage_model['damage_states'])
no_gmrs = len(gmrs['time'])
no_capacity_curves = len(capacity_curves['Sd'])
PDM = numpy.zeros((no_gmrs,no_damage_states+1))
Sds = numpy.zeros((no_gmrs,no_capacity_curves))
for icc in range(no_capacity_curves):
print str((icc+1)*100/no_capacity_curves) + '%'
for igmr in range(no_gmrs):
limit_states = utils.define_limit_states(capacity_curves,icc,damage_model)
damping = optimize.fmin(calculate_performance_point, 0.05, args=(gmrs,igmr,capacity_curves,icc,damping_model,damping), xtol=0.001, ftol=0.001, disp = False, )
[PDM, ds] = utils.allocate_damage(igmr,PDM,Sdi,limit_states)
Sds[igmr][icc] = Sdi
return PDM, Sds
def calculate_fragility(capacity_curves, hysteresis, gmrs,damage_model,damping,degradation):
no_damage_states = len(damage_model['damage_states'])
no_gmrs = len(gmrs['time'])
no_capacity_curves = len(capacity_curves['Sd'])
PDM = numpy.zeros((no_gmrs,no_damage_states+1))
Sds = numpy.zeros((no_gmrs,no_capacity_curves))
for icc in range(no_capacity_curves):
print str((icc+1)*100/no_capacity_curves) + '%'
for igmr in range(no_gmrs):
limit_states = utils.define_limit_states(capacity_curves, icc,damage_model)
time, disps = run_time_history_analysis(capacity_curves,hysteresis,icc,gmrs,igmr,damping,degradation)
Sdi = max(numpy.abs(numpy.array(disps)))
[PDM, ds] = utils.allocate_damage(igmr,PDM,Sdi,limit_states)
Sds[igmr][icc] = Sdi
return PDM, Sds
def calculate_fragility(capacity_curves,gmrs,damage_model,damping):
#This function returns a damage probability matrix (PDM) and the corresponding spectral displacements
no_damage_states = len(damage_model['damage_states'])
no_gmrs = len(gmrs['time'])
no_capacity_curves = len(capacity_curves['Sd'])
PDM = numpy.zeros((no_gmrs,no_damage_states+1))
Sds = numpy.zeros((no_gmrs,no_capacity_curves))
for icc in range(no_capacity_curves):
print str((icc+1)*100/no_capacity_curves) + '%'
for igmr in range(no_gmrs):
limit_states = utils.define_limit_states(capacity_curves,icc,damage_model)
Sdi = calculate_target_Sd(gmrs,igmr,capacity_curves,icc,damping)
[PDM, ds] = utils.allocate_damage(igmr,PDM,Sdi,limit_states)
Sds[igmr][icc] = Sdi
return PDM, Sds
def calculate_fragility(capacity_curves, gmrs, damage_model):
#This function returns a damage probability matrix (PDM) and the corresponding spectral displacements
no_damage_states = len(damage_model['damage_states'])
no_gmrs = len(gmrs['time'])
no_capacity_curves = len(capacity_curves['Sd'])
PDM = numpy.zeros((no_gmrs, no_damage_states + 1))
Sds = numpy.zeros((no_gmrs, no_capacity_curves))
for icc in range(no_capacity_curves):
print str((icc + 1) * 100 / no_capacity_curves) + '%'
for igmr in range(no_gmrs):
limit_states = utils.define_limit_states(capacity_curves, icc,
damage_model)
Sdi = calculate_Sd(gmrs, igmr, capacity_curves, icc)
[PDM, ds] = utils.allocate_damage(igmr, PDM, Sdi, limit_states)
Sds[igmr][icc] = Sdi
return PDM, Sds
def calculate_fragility(capacity_curves, hysteresis, gmrs, damage_model,
damping, degradation):
no_damage_states = len(damage_model['damage_states'])
no_gmrs = len(gmrs['time'])
no_capacity_curves = len(capacity_curves['Sd'])
PDM = numpy.zeros((no_gmrs, no_damage_states+1))
Sds = numpy.zeros((no_gmrs, no_capacity_curves))
for icc in range(no_capacity_curves):
print str((icc+1)*100/no_capacity_curves) + '%'
for igmr in range(no_gmrs):
limit_states = utils.define_limit_states(capacity_curves, icc,
damage_model)
time, disps = run_time_history_analysis(capacity_curves,
hysteresis, icc, gmrs,
igmr, damping, degradation)
Sdi = max(numpy.abs(numpy.array(disps)))
[PDM, ds] = utils.allocate_damage(igmr, PDM, Sdi, limit_states)
Sds[igmr][icc] = Sdi
return PDM, Sds
def calculate_fragility(capacity_curves,gmrs,damage_model,damping):
#This function returns a damage probability matrix (PDM) and the corresponding spectral displacements
#after an iterative process to find the minimum Sd value for each case
no_damage_states = len(damage_model['damage_states'])
no_gmrs = len(gmrs['time'])
no_capacity_curves = len(capacity_curves['Sd'])
PDM = numpy.zeros((no_gmrs,no_damage_states+1))
Sds = numpy.zeros((no_gmrs,no_capacity_curves))
for icc in range(no_capacity_curves):
print str((icc+1)*100/no_capacity_curves) + '%'
Te = capacity_curves['periods'][icc]
Sdy = capacity_curves['Sdy'][icc]
for igmr in range(no_gmrs):
limit_states = utils.define_limit_states(capacity_curves,icc,damage_model)
time = gmrs['time'][igmr]
acc = gmrs['acc'][igmr]
spec_Te = utils.NigamJennings(time,acc,[Te],damping)
Sdi = optimize.fmin(calculate_Sd, Sdy, args=(spec_Te['Sd'],capacity_curves,icc), xtol=0.001, ftol=0.001, disp = False, )
[PDM, ds] = utils.allocate_damage(igmr,PDM,Sdi,limit_states)
Sds[igmr][icc] = Sdi
return PDM, Sds
def run_NLTHA(icc, capacity_curves, hysteresis, gmrs, gmr_characteristics,
damage_model, damping, degradation, number_models_in_DS, msa):
# This function runs a set of NLTHA and writes for each
# Damage States a file with the list of records causing the structure to
# fall in the given DS. The analyses stop when the number_models_in_DS is
# reached for each DS.
no_damage_states = len(damage_model['damage_states'])
no_gmrs = len(gmrs['time'])
no_rec_bin = msa['records per bin']
# remove files containing results of previous analyses if they exist
for iDS in range(0, no_damage_states + 1):
try:
os.remove('initial_DS%d.csv' % iDS)
except OSError:
pass
counter = 0
# we are running all the gmrs and counter is the variable that records
# the count of gmrs already run
PDM1 = numpy.zeros((no_gmrs, no_damage_states + 1))
store_DS = []
for iDS in range(0, no_damage_states):
# in this loop are excluded DS=0 and DS=collapse because they are
# not of interest for fragility of damaged buildings
for igmr in range(counter, no_gmrs):
limit_states = utils.define_limit_states(capacity_curves, icc,
damage_model)
counter = igmr + 1
target_name = gmrs['name'][igmr]
available_aftershocks = filter_M_T(target_name,
gmr_characteristics)
if available_aftershocks >= no_rec_bin:
time, disps = run_time_history_analysis(
capacity_curves, hysteresis, icc, gmrs, target_name, 1,
damping, degradation)
Sdi = max(numpy.abs(numpy.array(disps)))
PDM1, ds = utils.allocate_damage(igmr, PDM1, Sdi, limit_states)
store_DS.append([gmrs['name'][igmr], ds, 1])
# if maximum number of models in DS is achieved stop
if sum(PDM1[:, iDS]) >= number_models_in_DS:
break
# This section works in case not enough records per DS are found
if sum(PDM1[:, iDS]) < number_models_in_DS and iDS != 0:
print "WARNING: there are not enough strong ground motions in DS ", str(
iDS), ", scaling is required"
for previous_DS in numpy.arange(iDS, 0, -1):
# finding gmrs leading to iDS-1 and applying scaling factor to them
temp = numpy.array(store_DS)
list_of_models = temp[scipy.logical_and(
temp[:, 1] == str(iDS - 1), temp[:, 2] == str(
1))] # names of the ground motion for the previous iDS
for scaling_factor in numpy.linspace(1.2, 3, 7):
for ele in list_of_models:
limit_states = utils.define_limit_states(
capacity_curves, icc, damage_model)
gmr_name = ele[0]
igmr = gmrs['name'].index(gmr_name)
# mainshock Mw and Tg are compared to all aftershock Mw and Tg
available_aftershocks = filter_M_T(
gmr_name, gmr_characteristics)
if available_aftershocks < no_rec_bin:
index = numpy.where(list_of_models[:, 0] == ele[0])
list_of_models = numpy.delete(list_of_models,
(index),
axis=0)
else:
time, disps = run_time_history_analysis(
capacity_curves, hysteresis, icc, gmrs,
gmr_name, scaling_factor, damping, degradation)
Sdi = max(numpy.abs(numpy.array(disps)))
PDM1, ds = utils.allocate_damage(
igmr, PDM1, Sdi, limit_states)
store_DS.append([gmr_name, ds, scaling_factor])
if ds >= iDS:
index = numpy.where(
list_of_models[:, 0] == ele[0])
list_of_models = numpy.delete(list_of_models,
(index),
axis=0)
if sum(PDM1[:, iDS]) >= number_models_in_DS: break
if sum(PDM1[:, iDS]) >= number_models_in_DS: break
if sum(PDM1[:, iDS]) >= number_models_in_DS: break
if sum(PDM1[:, iDS]) < number_models_in_DS:
print "WARNING: not enough models in DS%d" % iDS
# Store names of records and corresponding DS achieved so far
save_DS_list(iDS, store_DS, limit_states)
def run_2MSA(icc, capacity_curves, hysteresis, msa, damage_model, gmrs,
damping, degradation, PDMs, Sds, gmr_info, gmr_characteristics):
no_damage_states = len(damage_model['damage_states'])
no_bins = msa['n. bins']
no_rec_bin = msa['records per bin']
no_gmrs = no_bins * no_rec_bin
filter_aftershock = msa['filter']
Mw_multiplier = gmr_characteristics[-1]
counter = 0
for iDS in range(1, no_damage_states):
PDM = PDMs['iDS' + str(iDS)]
# Open files with records name bringing the system to DS = iDS
with open('initial_DS%d.csv' % iDS, 'rU') as f:
gmr_list = [row for row in csv.reader(f)]
for index_gmr1, gmr_name in enumerate(gmr_list):
print "Initial DS=", iDS
igmr1 = gmrs['name'].index(
gmr_name[0]) # index for 1st gmr within gmrs list
scl1 = float(gmr_name[1]) #scaling factor for first ground motion
[M_m, Tg_m, Mw, Tg] = find_M_T(gmr_name[0], gmr_characteristics)
# Read files with records name and corresponding scaling factor for each target IM
folder_scaled_recs = msa['input folder']
target_files = os.listdir(folder_scaled_recs)
for ele in target_files:
# Remove files that are not csv
if ele[-3:] != 'csv':
target_files.remove(ele)
for index, ibin in enumerate(target_files):
if index >= no_bins: break
print ibin
with open(folder_scaled_recs + '/' + ibin, 'rb') as f:
reader = csv.reader(f)
newlist = [row for row in reader]
record_name = [ele[0] for ele in newlist]
record_scaling = [float(ele[1]) for ele in newlist]
# Run NLTHA with 1st gmr to bring the system to iDS and 2nd gmr corresponding to target IM
for igmr in range(len(record_name)):
limit_states = utils.define_limit_states(
capacity_curves, icc, damage_model)
target_name = record_name[igmr]
scl2 = record_scaling[igmr]
[M_a, Tg_a, Mw, Tg] = find_M_T(target_name,
gmr_characteristics)
if scipy.logical_and(
M_a < M_m * Mw_multiplier,
Tg_a < Tg_m) or filter_aftershock == 'FALSE':
igmr2 = gmrs['name'].index(
target_name
) # index of 2nd gmr within the gmrs list
time, disps = run_2time_history_analyses(
capacity_curves, hysteresis, icc, gmrs, igmr1,
igmr2, scl1, scl2, damping, degradation)
Sdi = max(numpy.abs(numpy.array(disps)))
# In PDM the number of models in each final damage state corresponding
# to the same IM bin (defined by the variable index) are summed up
PDM, ds = utils.allocate_damage(
index, PDM, Sdi, limit_states)
gmr_info['iDS' + str(iDS)].append([igmr2, scl2])
Sds['iDS' + str(iDS)].append(Sdi)
counter = counter + 1
print "gmr n.", counter, "max disp. =", Sdi, "DS =", ds
if sum(PDM[index, :]) >= no_rec_bin * (index_gmr1 +
1) * (icc + 1):
break
PDMs['iDS' + str(iDS)] = PDM
return PDMs, Sds, gmr_info
def run_NLTHA(icc,capacity_curves,hysteresis,gmrs,gmr_characteristics,damage_model,damping,degradation,number_models_in_DS,msa):
# This function runs a set of NLTHA and writes for each
# Damage States a file with the list of records causing the structure to
# fall in the given DS. The analyses stop when the number_models_in_DS is
# reached for each DS.
no_damage_states = len(damage_model['damage_states'])
no_gmrs = len(gmrs['time'])
no_rec_bin = msa['records per bin']
# remove files containing results of previous analyses if they exist
for iDS in range(0,no_damage_states+1):
try:
os.remove('initial_DS%d.csv' %iDS)
except OSError:
pass
counter = 0
# we are running all the gmrs and counter is the variable that records
# the count of gmrs already run
PDM1 = numpy.zeros((no_gmrs,no_damage_states+1))
store_DS = []
for iDS in range(0,no_damage_states):
# in this loop are excluded DS=0 and DS=collapse because they are
# not of interest for fragility of damaged buildings
for igmr in range(counter,no_gmrs):
limit_states = utils.define_limit_states(capacity_curves,icc,damage_model)
counter = igmr+1
target_name = gmrs['name'][igmr]
available_aftershocks = filter_M_T(target_name,gmr_characteristics)
if available_aftershocks >= no_rec_bin:
time, disps = run_time_history_analysis(capacity_curves, hysteresis, icc,gmrs,target_name,1,damping,degradation)
Sdi = max(numpy.abs(numpy.array(disps)))
PDM1, ds = utils.allocate_damage(igmr,PDM1,Sdi,limit_states)
store_DS.append([gmrs['name'][igmr], ds, 1])
# if maximum number of models in DS is achieved stop
if sum(PDM1[:,iDS]) >= number_models_in_DS:
break
# This section works in case not enough records per DS are found
if sum(PDM1[:,iDS]) < number_models_in_DS and iDS != 0:
print "WARNING: there are not enough strong ground motions in DS ", str(iDS),", scaling is required"
for previous_DS in numpy.arange(iDS,0,-1):
# finding gmrs leading to iDS-1 and applying scaling factor to them
temp = numpy.array(store_DS)
list_of_models = temp[scipy.logical_and(temp[:,1] == str(iDS-1),temp[:,2] == str(1))] # names of the ground motion for the previous iDS
for scaling_factor in numpy.linspace(1.2,3,7):
for ele in list_of_models:
limit_states = utils.define_limit_states(capacity_curves,icc,damage_model)
gmr_name = ele[0]
igmr = gmrs['name'].index(gmr_name)
# mainshock Mw and Tg are compared to all aftershock Mw and Tg
available_aftershocks = filter_M_T(gmr_name,gmr_characteristics)
if available_aftershocks < no_rec_bin:
index = numpy.where(list_of_models[:,0] == ele[0])
list_of_models = numpy.delete(list_of_models, (index), axis=0)
else:
time, disps = run_time_history_analysis(capacity_curves, hysteresis, icc,gmrs,gmr_name,scaling_factor,damping,degradation)
Sdi = max(numpy.abs(numpy.array(disps)))
PDM1, ds = utils.allocate_damage(igmr,PDM1,Sdi,limit_states)
store_DS.append([gmr_name, ds, scaling_factor])
if ds >= iDS:
index = numpy.where(list_of_models[:,0] == ele[0])
list_of_models = numpy.delete(list_of_models, (index), axis=0)
if sum(PDM1[:,iDS]) >= number_models_in_DS: break
if sum(PDM1[:,iDS]) >= number_models_in_DS: break
if sum(PDM1[:,iDS]) >= number_models_in_DS: break
if sum(PDM1[:,iDS]) < number_models_in_DS:
print "WARNING: not enough models in DS%d" %iDS
# Store names of records and corresponding DS achieved so far
save_DS_list(iDS,store_DS, limit_states)
def run_2MSA(icc,capacity_curves,hysteresis,msa,damage_model,gmrs,damping,degradation,PDMs, Sds, gmr_info, gmr_characteristics):
no_damage_states = len(damage_model['damage_states'])
no_bins = msa['n. bins']
no_rec_bin = msa['records per bin']
no_gmrs = no_bins*no_rec_bin
filter_aftershock = msa['filter']
Mw_multiplier = gmr_characteristics[-1]
counter = 0
for iDS in range(1,no_damage_states):
PDM = PDMs['iDS'+str(iDS)]
# Open files with records name bringing the system to DS = iDS
with open('initial_DS%d.csv' %iDS, 'rU') as f:
gmr_list = [row for row in csv.reader(f)]
for index_gmr1, gmr_name in enumerate(gmr_list):
print "Initial DS=", iDS
igmr1 = gmrs['name'].index(gmr_name[0]) # index for 1st gmr within gmrs list
scl1 = float(gmr_name[1]) #scaling factor for first ground motion
[M_m, Tg_m, Mw, Tg] = find_M_T(gmr_name[0], gmr_characteristics)
# Read files with records name and corresponding scaling factor for each target IM
folder_scaled_recs = msa['input folder']
target_files = os.listdir(folder_scaled_recs)
for ele in target_files:
# Remove files that are not csv
if ele[-3:] != 'csv':
target_files.remove(ele)
for index,ibin in enumerate(target_files):
if index>=no_bins: break
print ibin
with open(folder_scaled_recs+'/'+ibin, 'rb') as f:
reader = csv.reader(f)
newlist = [row for row in reader]
record_name = [ele[0] for ele in newlist]
record_scaling = [float(ele[1]) for ele in newlist]
# Run NLTHA with 1st gmr to bring the system to iDS and 2nd gmr corresponding to target IM
for igmr in range(len(record_name)):
limit_states = utils.define_limit_states(capacity_curves,icc,damage_model)
target_name = record_name[igmr]
scl2 = record_scaling[igmr]
[M_a, Tg_a, Mw, Tg] = find_M_T(target_name, gmr_characteristics)
if scipy.logical_and(M_a<M_m*Mw_multiplier, Tg_a<Tg_m) or filter_aftershock=='FALSE':
igmr2 = gmrs['name'].index(target_name) # index of 2nd gmr within the gmrs list
time, disps = run_2time_history_analyses(capacity_curves,hysteresis,icc,gmrs,igmr1,igmr2,scl1,scl2,damping,degradation)
Sdi = max(numpy.abs(numpy.array(disps)))
# In PDM the number of models in each final damage state corresponding
# to the same IM bin (defined by the variable index) are summed up
PDM, ds = utils.allocate_damage(index,PDM,Sdi,limit_states)
gmr_info['iDS' + str(iDS)].append([igmr2, scl2])
Sds['iDS' + str(iDS)].append(Sdi)
counter = counter+1
print "gmr n.", counter, "max disp. =", Sdi, "DS =", ds
if sum(PDM[index,:]) >= no_rec_bin*(index_gmr1+1)*(icc+1): break
PDMs['iDS' + str(iDS)] = PDM
return PDMs, Sds, gmr_info
