def view_ruptures_per_trt(token, dstore):
tbl = []
header = ('source_model grp_id trt eff_ruptures tot_ruptures'.split())
num_trts = 0
eff_ruptures = 0
tot_ruptures = 0
csm_info = dstore['csm_info']
for i, sm in enumerate(csm_info.source_models):
for src_group in sm.src_groups:
trt = source.capitalize(src_group.trt)
er = src_group.eff_ruptures
if er:
num_trts += 1
eff_ruptures += er
tbl.append(
(sm.name, src_group.id, trt, er, src_group.tot_ruptures))
tot_ruptures += src_group.tot_ruptures
rows = [('#TRT models', num_trts), ('#eff_ruptures', eff_ruptures),
('#tot_ruptures', tot_ruptures),
('#tot_weight', csm_info.tot_weight)]
if len(tbl) > 1:
summary = '\n\n' + rst_table(rows)
else:
summary = ''
return rst_table(tbl, header=header) + summary
def view_ruptures_per_trt(token, dstore):
tbl = []
header = ('source_model grp_id trt eff_ruptures tot_ruptures'.split())
num_trts = 0
eff_ruptures = 0
tot_ruptures = 0
csm_info = dstore['csm_info']
for i, sm in enumerate(csm_info.source_models):
for src_group in sm.src_groups:
trt = source.capitalize(src_group.trt)
er = src_group.eff_ruptures
if er:
num_trts += 1
eff_ruptures += er
tbl.append(
(sm.name, src_group.id, trt, er, src_group.tot_ruptures))
tot_ruptures += src_group.tot_ruptures
rows = [('#TRT models', num_trts),
('#eff_ruptures', eff_ruptures),
('#tot_ruptures', tot_ruptures),
('#tot_weight', csm_info.tot_weight)]
if len(tbl) > 1:
summary = '\n\n' + rst_table(rows)
else:
summary = ''
return rst_table(tbl, header=header) + summary
def export_sourcegroups(ekey, dstore):
csm_info = dstore['csm_info']
data = [['grp_id', 'trt', 'eff_ruptures']]
for i, sm in enumerate(csm_info.source_models):
for src_group in sm.src_groups:
trt = source.capitalize(src_group.trt)
er = src_group.eff_ruptures
data.append((src_group.id, trt, er))
path = dstore.export_path('sourcegroups.csv')
writers.write_csv(path, data, fmt='%s')
return [path]
def export_sourcegroups(ekey, dstore):
csm_info = dstore['csm_info']
data = [['grp_id', 'trt', 'eff_ruptures']]
for i, sm in enumerate(csm_info.source_models):
for src_group in sm.src_groups:
trt = source.capitalize(src_group.trt)
er = src_group.eff_ruptures
data.append((src_group.id, trt, er))
path = dstore.export_path('sourcegroups.csv')
writers.write_csv(path, data, fmt='%s')
return [path]
def view_ruptures_per_trt(token, dstore):
tbl = []
header = ('source_model trt_id trt num_sources '
'eff_ruptures weight'.split())
num_trts = 0
tot_sources = 0
eff_ruptures = 0
tot_weight = 0
source_info = dstore['source_info'].value
csm_info = dstore['rlzs_assoc'].csm_info
w = groupby(source_info, operator.itemgetter('trt_model_id'),
lambda rows: sum(r['weight'] for r in rows))
n = groupby(source_info, operator.itemgetter('trt_model_id'),
lambda rows: sum(1 for r in rows))
for i, sm in enumerate(csm_info.source_models):
# NB: the number of effective ruptures per tectonic region model
# is stored in the array eff_ruptures as a literal string describing
# an array {trt_model_id: num_ruptures}; see the method
# CompositionInfo.get_rlzs_assoc
erdict = ast.literal_eval(csm_info.eff_ruptures[i])
for trt_model in sm.trt_models:
trt = source.capitalize(trt_model.trt)
er = erdict.get(trt, 0) # effective ruptures
if er:
num_trts += 1
num_sources = n.get(trt_model.id, 0)
tot_sources += num_sources
eff_ruptures += er
weight = w.get(trt_model.id, 0)
tot_weight += weight
tbl.append((sm.name, trt_model.id, trt,
num_sources, er, weight))
rows = [('#TRT models', num_trts),
('#sources', tot_sources),
('#eff_ruptures', eff_ruptures),
('filtered_weight', tot_weight)]
if len(tbl) > 1:
summary = '\n\n' + rst_table(rows)
else:
summary = ''
return rst_table(tbl, header=header) + summary
def view_ruptures_per_trt(token, dstore):
tbl = []
header = ('source_model grp_id trt num_sources '
'eff_ruptures tot_ruptures'.split())
num_trts = 0
tot_sources = 0
eff_ruptures = 0
tot_ruptures = 0
source_info = dstore['source_info'].value
csm_info = dstore['csm_info']
r = groupby(source_info, operator.itemgetter('grp_id'),
lambda rows: sum(r['num_ruptures'] for r in rows))
n = groupby(source_info, operator.itemgetter('grp_id'),
lambda rows: sum(1 for r in rows))
for i, sm in enumerate(csm_info.source_models):
for src_group in sm.src_groups:
trt = source.capitalize(src_group.trt)
er = src_group.eff_ruptures
if er:
num_trts += 1
num_sources = n.get(src_group.id, 0)
tot_sources += num_sources
eff_ruptures += er
ruptures = r.get(src_group.id, 0)
tot_ruptures += ruptures
tbl.append(
(sm.name, src_group.id, trt, num_sources, er, ruptures))
rows = [
('#TRT models', num_trts),
('#sources', tot_sources),
('#eff_ruptures', eff_ruptures),
('#tot_ruptures', tot_ruptures),
('#tot_weight', csm_info.tot_weight),
]
if len(tbl) > 1:
summary = '\n\n' + rst_table(rows)
else:
summary = ''
return rst_table(tbl, header=header) + summary
def view_ruptures_per_trt(token, dstore):
tbl = []
header = ('source_model trt_id trt num_sources '
'eff_ruptures weight'.split())
num_trts = 0
tot_sources = 0
eff_ruptures = 0
tot_weight = 0
source_info = dstore['source_info'].value
csm_info = dstore['rlzs_assoc'].csm_info
w = groupby(source_info, operator.itemgetter('trt_model_id'),
lambda rows: sum(r['weight'] for r in rows))
n = groupby(source_info, operator.itemgetter('trt_model_id'),
lambda rows: sum(1 for r in rows))
for i, sm in enumerate(csm_info.source_models):
# NB: the number of effective ruptures per tectonic region model
# is stored in the array eff_ruptures as a literal string describing
# an array {trt_model_id: num_ruptures}; see the method
# CompositionInfo.get_rlzs_assoc
erdict = ast.literal_eval(csm_info.eff_ruptures[i])
for trt_model in sm.trt_models:
trt = source.capitalize(trt_model.trt)
er = erdict.get(trt, 0) # effective ruptures
if er:
num_trts += 1
num_sources = n.get(trt_model.id, 0)
tot_sources += num_sources
eff_ruptures += er
weight = w.get(trt_model.id, 0)
tot_weight += weight
tbl.append(
(sm.name, trt_model.id, trt, num_sources, er, weight))
rows = [('#TRT models', num_trts), ('#sources', tot_sources),
('#eff_ruptures', eff_ruptures), ('filtered_weight', tot_weight)]
if len(tbl) > 1:
summary = '\n\n' + rst_table(rows)
else:
summary = ''
return rst_table(tbl, header=header) + summary
def view_ruptures_per_trt(token, dstore):
tbl = []
header = ('source_model grp_id trt num_sources '
'eff_ruptures tot_ruptures'.split())
num_trts = 0
tot_sources = 0
eff_ruptures = 0
tot_ruptures = 0
source_info = dstore['source_info'].value
csm_info = dstore['csm_info']
r = groupby(source_info, operator.itemgetter('grp_id'),
lambda rows: sum(r['num_ruptures'] for r in rows))
n = groupby(source_info, operator.itemgetter('grp_id'),
lambda rows: sum(1 for r in rows))
for i, sm in enumerate(csm_info.source_models):
for src_group in sm.src_groups:
trt = source.capitalize(src_group.trt)
er = src_group.eff_ruptures
if er:
num_trts += 1
num_sources = n.get(src_group.id, 0)
tot_sources += num_sources
eff_ruptures += er
ruptures = r.get(src_group.id, 0)
tot_ruptures += ruptures
tbl.append((sm.name, src_group.id, trt,
num_sources, er, ruptures))
rows = [('#TRT models', num_trts),
('#sources', tot_sources),
('#eff_ruptures', eff_ruptures),
('#tot_ruptures', tot_ruptures),
('#tot_weight', csm_info.tot_weight), ]
if len(tbl) > 1:
summary = '\n\n' + rst_table(rows)
else:
summary = ''
return rst_table(tbl, header=header) + summary
def view_ruptures_per_trt(token, dstore):
tbl = []
header = ('source_model trt_id trt num_sources '
'eff_ruptures weight'.split())
num_trts = 0
tot_sources = 0
eff_ruptures = 0
tot_weight = 0
source_info = dstore['source_info'].value
csm_info = dstore['csm_info']
w = groupby(source_info, operator.itemgetter('trt_model_id'),
lambda rows: sum(r['weight'] for r in rows))
n = groupby(source_info, operator.itemgetter('trt_model_id'),
lambda rows: sum(1 for r in rows))
for i, sm in enumerate(csm_info.source_models):
for trt_model in sm.trt_models:
trt = source.capitalize(trt_model.trt)
er = trt_model.eff_ruptures
if er:
num_trts += 1
num_sources = n.get(trt_model.id, 0)
tot_sources += num_sources
eff_ruptures += er
weight = w.get(trt_model.id, 0)
tot_weight += weight
tbl.append((sm.name, trt_model.id, trt,
num_sources, er, weight))
rows = [('#TRT models', num_trts),
('#sources', tot_sources),
('#eff_ruptures', eff_ruptures),
('filtered_weight', tot_weight)]
if len(tbl) > 1:
summary = '\n\n' + rst_table(rows)
else:
summary = ''
return rst_table(tbl, header=header) + summary
