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Merged
micheles merged 1 commit into from
Oct 14, 2023
Merged

Skipping useless calculations #9108

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25 changes: 14 additions & 11 deletions openquake/hazardlib/calc/gmf.py
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Original file line number Diff line number Diff line change
Expand Up @@ -267,35 +267,38 @@ def compute_all(self, max_iml=None,
rng = numpy.random.default_rng(self.seed)
data = AccumDict(accum=[])
for g, (gs, rlzs) in enumerate(self.cmaker.gsims.items()):
idxs, = numpy.where(numpy.isin(self.rlz, rlzs))
E = len(idxs)
if E == 0: # crucial for performance
continue
with cmon:
array = self.compute(gs, rlzs, mean_stds[:, g], rng) # NME
array = self.compute(gs, idxs, mean_stds[:, g], rng) # NME
with umon:
self.update(data, array, rlzs, mean_stds[:, g], max_iml)
with umon:
return self.strip_zeros(data)

def compute(self, gsim, rlzs, mean_stds, rng):
def compute(self, gsim, idxs, mean_stds, rng):
"""
:param gsim: GSIM used to compute mean_stds
:param rlzs: realizations associated to the gsim
:param idxs: affected indices
:param mean_stds: array of shape (4, M, N)
:param rng: random number generator for the rupture
:returns: a 32 bit array of shape (N, M, E)
"""
# sets self.eps
M = len(self.imts)
mask = numpy.isin(self.rlz, rlzs)
E = mask.sum()
E = len(idxs)
result = numpy.zeros(
(len(self.imts), len(self.ctx.sids), E), F32)
ccdist = self.cross_correl.distribution
# build arrays of random numbers of shape (M, N, E) and (M, E)
intra_eps = [ccdist.rvs((self.N, E), rng) for _ in range(M)]
self.eps[mask] = self.cross_correl.get_inter_eps(self.imts, E, rng).T
self.eps[idxs] = self.cross_correl.get_inter_eps(self.imts, E, rng).T
for m, imt in enumerate(self.imts):
try:
result[m] = self._compute(
mean_stds[:, m], m, imt, gsim, intra_eps[m], mask)
mean_stds[:, m], m, imt, gsim, intra_eps[m], idxs)
except Exception as exc:
raise RuntimeError(
'(%s, %s, source_id=%r) %s: %s' %
Expand All @@ -307,7 +310,7 @@ def compute(self, gsim, rlzs, mean_stds, rng):
self.ctx.ampcode, result, self.imts, self.seed)
return result.transpose(1, 0, 2)

def _compute(self, mean_stds, m, imt, gsim, intra_eps, mask):
def _compute(self, mean_stds, m, imt, gsim, intra_eps, idxs):
# sets self.sig
im = imt.string
if self.cmaker.truncation_level <= 1E-9:
Expand All @@ -329,7 +332,7 @@ def _compute(self, mean_stds, m, imt, gsim, intra_eps, mask):

mean, sig, _, _ = mean_stds
gmf = exp(mean[:, None] + sig[:, None] * intra_eps, im!='MMI')
self.sig[mask, m] = numpy.nan
self.sig[idxs, m] = numpy.nan
else:
mean, sig, tau, phi = mean_stds
# the [:, None] is used to implement multiplication by row;
Expand All @@ -344,10 +347,10 @@ def _compute(self, mean_stds, m, imt, gsim, intra_eps, mask):
if len(intra_res.shape) == 1: # a vector
intra_res = intra_res[:, None]

inter_res = tau[:, None] * self.eps[mask, m]
inter_res = tau[:, None] * self.eps[idxs, m]
# shape (N, 1) * E => (N, E)
gmf = exp(mean[:, None] + intra_res + inter_res, im!='MMI')
self.sig[mask, m] = tau.max() # from shape (N, 1) => scalar
self.sig[idxs, m] = tau.max() # from shape (N, 1) => scalar
return gmf # shapes (N, E)


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