def to_csv_array(ruptures):
"""
:param ruptures: a list of ruptures
:returns: an array of ruptures suitable for serialization in CSV
"""
if not code2cls:
code2cls.update(BaseRupture.init())
arr = numpy.zeros(len(ruptures), rupture_dt)
for rec, rup in zip(arr, ruptures):
arrays = surface_to_arrays(rup.surface) # shape (3, s1, s2)
rec['serial'] = rup.rup_id
rec['mag'] = rup.mag
rec['rake'] = rup.rake
rec['lon'] = rup.hypocenter.x
rec['lat'] = rup.hypocenter.y
rec['dep'] = rup.hypocenter.z
rec['multiplicity'] = rup.multiplicity
rec['trt'] = rup.tectonic_region_type
rec['kind'] = ' '.join(cls.__name__ for cls in code2cls[rup.code])
rec['mesh'] = json.dumps([[[[float5(z) for z in y] for y in x]
for x in array] for array in arrays])
extra = {}
if hasattr(rup, 'probs_occur'):
extra['probs_occur'] = rup.probs_occur
else:
extra['occurrence_rate'] = rup.occurrence_rate
if hasattr(rup, 'weight'):
extra['weight'] = rup.weight
_fixfloat32(extra)
rec['extra'] = json.dumps(extra)
return arr
def get_rup_array(ebruptures, srcfilter=nofilter):
"""
Convert a list of EBRuptures into a numpy composite array, by filtering
out the ruptures far away from every site
"""
if not BaseRupture._code:
BaseRupture.init() # initialize rupture codes
rups = []
geoms = []
for ebrupture in ebruptures:
rup = ebrupture.rupture
arrays = surface_to_arrays(rup.surface) # one array per surface
points = []
shapes = []
for array in arrays:
s0, s1, s2 = array.shape
assert s0 == 3, s0
assert s1 < TWO16, 'Too many lines'
assert s2 < TWO16, 'The rupture mesh spacing is too small'
shapes.append(s1)
shapes.append(s2)
points.extend(array.flat)
# example of points: [25.0, 25.1, 25.1, 25.0,
# -24.0, -24.0, -24.1, -24.1,
# 5.0, 5.0, 5.0, 5.0]
points = F32(points)
shapes = U32(shapes)
hypo = rup.hypocenter.x, rup.hypocenter.y, rup.hypocenter.z
rec = numpy.zeros(1, rupture_dt)[0]
rec['seed'] = rup.rup_id
n = len(points) // 3
lons = points[0:n]
lats = points[n:2 * n]
rec['minlon'] = minlon = lons.min()
rec['minlat'] = minlat = lats.min()
rec['maxlon'] = maxlon = lons.max()
rec['maxlat'] = maxlat = lats.max()
rec['mag'] = rup.mag
rec['hypo'] = hypo
if srcfilter.integration_distance and len(
srcfilter.close_sids(rec, rup.tectonic_region_type)) == 0:
continue
rate = getattr(rup, 'occurrence_rate', numpy.nan)
tup = (0, ebrupture.rup_id, ebrupture.source_id, ebrupture.trt_smrlz,
rup.code, ebrupture.n_occ, rup.mag, rup.rake, rate, minlon,
minlat, maxlon, maxlat, hypo, 0, 0)
rups.append(tup)
# we are storing the geometries as arrays of 32 bit floating points;
# the first element is the number of surfaces, then there are
# 2 * num_surfaces integers describing the first and second
# dimension of each surface, and then the lons, lats and deps of
# the underlying meshes of points.
geom = numpy.concatenate([[len(shapes) // 2], shapes, points])
geoms.append(geom)
if not rups:
return ()
dic = dict(geom=numpy.array(geoms, object))
# NB: PMFs for nonparametric ruptures are not saved since they
# are useless for the GMF computation
return hdf5.ArrayWrapper(numpy.array(rups, rupture_dt), dic)
def surface_to_array(surface):
return surface_to_arrays(surface)[0]