def generate_motion_csv(output_dir, site_tag, soil_amp):
"""Produce scenario motion CSV files.
(previously produced if save_motion=True)
Parameters:
output_dir - path to directory where the simulation data has been produced,
and where the output files will be placed
site_tag - used to identify the appropriate data as input
is_bedrock - if True use bedrock results, else use soil results
"""
# EQRM flags
eqrm_flags = create_parameter_data(os.path.join(output_dir, "eqrm_flags.py"))
# Ground motion
motion, atten_periods = load_motion(output_dir, site_tag, soil_amp, file_format="binary")
return save_motion_to_csv(soil_amp, eqrm_flags, motion)
def generate_motion_csv(output_dir,
site_tag,
soil_amp):
"""Produce scenario motion CSV files.
(previously produced if save_motion=True)
Parameters:
output_dir - path to directory where the simulation data has been produced,
and where the output files will be placed
site_tag - used to identify the appropriate data as input
is_bedrock - if True use bedrock results, else use soil results
"""
# EQRM flags
eqrm_flags = create_parameter_data(
os.path.join(output_dir, 'eqrm_flags.py'))
# Ground motion
motion, atten_periods = load_motion(output_dir,
site_tag, soil_amp,
file_format='binary')
return save_motion_to_csv(soil_amp, eqrm_flags, motion)
def events_shaking_a_site(output_dir,
site_tag,
site_lat,
site_lon,
period,
soil_amp,
file_format='binary'):
"""events_shaking_a_site
Given disaggregated output data produce a csv file showing ground motion
and event information for the given site and period.
Parameters:
output_dir - path to directory where the simulation data has been produced,
and where the output files will be placed
site_tag - used to identify the appropriate data as input
site_lat - site latitude
site_lon - site longitude (use the closest site as the cockey flies)
period - attenuation period (must be an exact match)
soil_amp - if True use soil results, else use bedrock results
Output file:
<output_dir>/
- if soil_amp:
<site_tag>_bedrock_SA_events_ap[<period>]_lat[<site_lat>]_lon[<site_lon>].csv
- else:
<site_tag>_soil_SA_events_ap[<period>]_lat[<site_lat>]_lon[<site_lon>].csv
Columns:
'ground_motion' - ground motion value
'ground_motion_model' - ground motion model used
'trace_start_lat' - rupture trace start latitude
'trace_start_lon' - rupture trace start longitude
'trace_end_lat' - rupture trace end latitude
'trace_end_lon' - rupture trace end longitude
'rupture_centroid_lat' - rupture centroid latitude
'rupture_centroid_lon' - rupture centroid longitude
'depth' - rupture depth to centroid (km)
'azimuth' - rupture azimuth (degrees from true North)
'dip' - rupture dip
'Mw' - rupture moment magnitude
'length' - rupture length
'width' - rupture width
'activity' - event activity (probability that the event will
occur this year)
'Rjb' - Joyner-Boore distance to rupture plane
'Rrup' - Closest distance to rupture plane
'site_lat' - Closest site latitude
'site_lon' - Closest site longitude
"""
# Ground motion
motion, atten_periods = load_motion(output_dir,
site_tag, soil_amp, file_format)
if period not in atten_periods:
raise Exception("Period %s not in atten_periods %s" % (period,
atten_periods))
period_ind = where(period == atten_periods)[0][0]
parallel = Parallel(is_parallel=False)
# Event set objects
(event_set,
event_activity,
source_model) = load_event_set(parallel,
os.path.join(output_dir,
'%s_event_set' % site_tag))
# Site objects
sites = load_sites(
parallel,
os.path.join(
output_dir,
'%s_sites' %
site_tag))
closest_site_ind = sites.closest_site(site_lat, site_lon)
closest_site_lat = sites[closest_site_ind].latitude[0]
closest_site_lon = sites[closest_site_ind].longitude[0]
# Get the motion that corresponds to this site, collapsing spawn, rm, period
# Motion dimensions - spawn, gmm, rm, sites, events, period
motion_for_site = motion[0, :, 0, closest_site_ind,:, period_ind]
(event_set.trace_end_lat,
event_set.trace_end_lon) = xy_to_ll(event_set.rupture_centroid_x,
-event_set.rupture_centroid_y,
event_set.rupture_centroid_lat,
event_set.rupture_centroid_lon,
event_set.azimuth)
# Event activity dimensions - spawn, gmm, rm, events
# Collapse spawn and rm
event_activity = event_activity.event_activity[0, :, 0,:]
# Distances
Rjb = sites.distances_from_event_set(event_set).distance('Joyner_Boore')
Rjb_for_site = Rjb.swapaxes(0, 1)[:, closest_site_ind]
Rrup = sites.distances_from_event_set(event_set).distance('Rupture')
Rrup_for_site = Rrup.swapaxes(0, 1)[:, closest_site_ind]
if soil_amp is True:
motion_name = 'soil_SA'
elif soil_amp is False:
motion_name = 'bedrock_SA'
else:
raise IOError("soil_amp must be True or False")
# Create file and write headers
filename = '%s_%s_events_ap%s_lat%s_lon%s.csv' % (site_tag,
motion_name,
period,
closest_site_lat,
closest_site_lon)
handle = csv.writer(open(os.path.join(output_dir, filename), 'w'))
handle.writerow(['ground_motion',
'ground_motion_model',
'trace_start_lat',
'trace_start_lon',
'trace_end_lat',
'trace_end_lon',
'rupture_centroid_lat',
'rupture_centroid_lon',
'depth',
'azimuth',
'dip',
'Mw',
'length',
'width',
'activity',
'Rjb',
'Rrup',
'site_lat',
'site_lon'])
# Loop over events
for i in range(motion_for_site.shape[1]): # events
trace_start_lat = event_set.trace_start_lat[i]
trace_start_lon = event_set.trace_start_lon[i]
trace_end_lat = event_set.trace_end_lat[i]
trace_end_lon = event_set.trace_end_lon[i]
rupture_centroid_lat = event_set.rupture_centroid_lat[i]
rupture_centroid_lon = event_set.rupture_centroid_lon[i]
depth = event_set.depth[i]
azimuth = event_set.azimuth[i]
dip = event_set.dip[i]
mw = event_set.Mw[i]
length = event_set.length[i]
width = event_set.width[i]
rjb = Rjb_for_site[i]
rrup = Rrup_for_site[i]
ground_motion = motion_for_site[:, i]
activity = event_activity[:, i]
event_source = source_model[int(event_set.source[i])]
for gmm_ind, gmm in enumerate(event_source.atten_models):
handle.writerow([ground_motion[gmm_ind],
gmm,
trace_start_lat,
trace_start_lon,
trace_end_lat,
trace_end_lon,
rupture_centroid_lat,
rupture_centroid_lon,
depth,
azimuth,
dip,
mw,
length,
width,
activity[gmm_ind],
rjb,
rrup,
closest_site_lat,
closest_site_lon])
return os.path.join(output_dir, filename)
def events_shaking_a_site(output_dir, site_tag, site_lat, site_lon, period, soil_amp, file_format="binary"):
"""events_shaking_a_site
Given disaggregated output data produce a csv file showing ground motion
and event information for the given site and period.
Parameters:
output_dir - path to directory where the simulation data has been produced,
and where the output files will be placed
site_tag - used to identify the appropriate data as input
site_lat - site latitude
site_lon - site longitude (use the closest site as the cockey flies)
period - attenuation period (must be an exact match)
soil_amp - if True use soil results, else use bedrock results
Output file:
<output_dir>/
- if soil_amp:
<site_tag>_bedrock_SA_events_ap[<period>]_lat[<site_lat>]_lon[<site_lon>].csv
- else:
<site_tag>_soil_SA_events_ap[<period>]_lat[<site_lat>]_lon[<site_lon>].csv
Columns:
'ground_motion' - ground motion value
'ground_motion_model' - ground motion model used
'trace_start_lat' - rupture trace start latitude
'trace_start_lon' - rupture trace start longitude
'trace_end_lat' - rupture trace end latitude
'trace_end_lon' - rupture trace end longitude
'rupture_centroid_lat' - rupture centroid latitude
'rupture_centroid_lon' - rupture centroid longitude
'depth' - rupture depth to centroid (km)
'azimuth' - rupture azimuth (degrees from true North)
'dip' - rupture dip
'Mw' - rupture moment magnitude
'length' - rupture length
'width' - rupture width
'activity' - event activity (probability that the event will
occur this year)
'Rjb' - Joyner-Boore distance to rupture plane
'Rrup' - Closest distance to rupture plane
'site_lat' - Closest site latitude
'site_lon' - Closest site longitude
"""
# Ground motion
motion, atten_periods = load_motion(output_dir, site_tag, soil_amp, file_format)
if period not in atten_periods:
raise Exception("Period %s not in atten_periods %s" % (period, atten_periods))
period_ind = where(period == atten_periods)[0][0]
parallel = Parallel(is_parallel=False)
# Event set objects
(event_set, event_activity, source_model) = load_event_set(
parallel, os.path.join(output_dir, "%s_event_set" % site_tag)
)
# Site objects
sites = load_sites(parallel, os.path.join(output_dir, "%s_sites" % site_tag))
closest_site_ind = sites.closest_site(site_lat, site_lon)
closest_site_lat = sites[closest_site_ind].latitude[0]
closest_site_lon = sites[closest_site_ind].longitude[0]
# Get the motion that corresponds to this site, collapsing spawn, rm, period
# Motion dimensions - spawn, gmm, rm, sites, events, period
motion_for_site = motion[0, :, 0, closest_site_ind, :, period_ind]
(event_set.trace_end_lat, event_set.trace_end_lon) = xy_to_ll(
event_set.rupture_centroid_x,
-event_set.rupture_centroid_y,
event_set.rupture_centroid_lat,
event_set.rupture_centroid_lon,
event_set.azimuth,
)
# Event activity dimensions - spawn, gmm, rm, events
# Collapse spawn and rm
event_activity = event_activity.event_activity[0, :, 0, :]
# Distances
Rjb = sites.distances_from_event_set(event_set).distance("Joyner_Boore")
Rjb_for_site = Rjb.swapaxes(0, 1)[:, closest_site_ind]
Rrup = sites.distances_from_event_set(event_set).distance("Rupture")
Rrup_for_site = Rrup.swapaxes(0, 1)[:, closest_site_ind]
if soil_amp is True:
motion_name = "soil_SA"
elif soil_amp is False:
motion_name = "bedrock_SA"
else:
raise IOError("soil_amp must be True or False")
# Create file and write headers
filename = "%s_%s_events_ap%s_lat%s_lon%s.csv" % (site_tag, motion_name, period, closest_site_lat, closest_site_lon)
handle = csv.writer(open(os.path.join(output_dir, filename), "w"))
handle.writerow(
[
"ground_motion",
"ground_motion_model",
"trace_start_lat",
"trace_start_lon",
"trace_end_lat",
"trace_end_lon",
"rupture_centroid_lat",
"rupture_centroid_lon",
"depth",
"azimuth",
"dip",
"Mw",
"length",
"width",
"activity",
"Rjb",
"Rrup",
"site_lat",
"site_lon",
]
)
# Loop over events
for i in range(motion_for_site.shape[1]): # events
trace_start_lat = event_set.trace_start_lat[i]
trace_start_lon = event_set.trace_start_lon[i]
trace_end_lat = event_set.trace_end_lat[i]
trace_end_lon = event_set.trace_end_lon[i]
rupture_centroid_lat = event_set.rupture_centroid_lat[i]
rupture_centroid_lon = event_set.rupture_centroid_lon[i]
depth = event_set.depth[i]
azimuth = event_set.azimuth[i]
dip = event_set.dip[i]
mw = event_set.Mw[i]
length = event_set.length[i]
width = event_set.width[i]
rjb = Rjb_for_site[i]
rrup = Rrup_for_site[i]
ground_motion = motion_for_site[:, i]
activity = event_activity[:, i]
event_source = source_model[int(event_set.source[i])]
for gmm_ind, gmm in enumerate(event_source.atten_models):
handle.writerow(
[
ground_motion[gmm_ind],
gmm,
trace_start_lat,
trace_start_lon,
trace_end_lat,
trace_end_lon,
rupture_centroid_lat,
rupture_centroid_lon,
depth,
azimuth,
dip,
mw,
length,
width,
activity[gmm_ind],
rjb,
rrup,
closest_site_lat,
closest_site_lon,
]
)
return os.path.join(output_dir, filename)