def test_probability(self):
self.assertEqual(valid.probability('1'), 1.0)
self.assertEqual(valid.probability('.5'), 0.5)
self.assertEqual(valid.probability('0'), 0.0)
with self.assertRaises(ValueError):
valid.probability('1.1')
with self.assertRaises(ValueError):
valid.probability('-0.1')
def test_probability(self):
self.assertEqual(valid.probability('1'), 1.0)
self.assertEqual(valid.probability('.5'), 0.5)
self.assertEqual(valid.probability('0'), 0.0)
with self.assertRaises(ValueError):
valid.probability('1.1')
with self.assertRaises(ValueError):
valid.probability('-0.1')
def view_hmap(token, dstore):
"""
Display the highest 20 points of the mean hazard map. Called as
$ oq show hmap:0.1 # 10% PoE
"""
try:
poe = valid.probability(token.split(':')[1])
except IndexError:
poe = 0.1
mean = dict(extract(dstore, 'hcurves?kind=mean'))['mean']
oq = dstore['oqparam']
hmap = calc.make_hmap_array(mean, oq.imtls, [poe], len(mean))
dt = numpy.dtype([('sid', U32)] + [(imt, F32) for imt in oq.imtls])
array = numpy.zeros(len(hmap), dt)
for i, vals in enumerate(hmap):
array[i] = (i, ) + tuple(vals)
array.sort(order=list(oq.imtls)[0])
return rst_table(array[:20])
def view_hmap(token, dstore):
"""
Display the highest 20 points of the mean hazard map. Called as
$ oq show hmap:0.1 # 10% PoE
"""
try:
poe = valid.probability(token.split(':')[1])
except IndexError:
poe = 0.1
mean = dict(extract(dstore, 'hcurves?kind=mean'))['mean']
oq = dstore['oqparam']
hmap = calc.make_hmap_array(mean, oq.imtls, [poe], len(mean))
dt = numpy.dtype([('sid', U32)] + [(imt, F32) for imt in oq.imtls])
array = numpy.zeros(len(hmap), dt)
for i, vals in enumerate(hmap):
array[i] = (i, ) + tuple(vals)
array.sort(order=list(oq.imtls)[0])
return rst_table(array[:20])
def view_hmap(token, dstore):
"""
Display the highest 20 points of the mean hazard map. Called as
$ oq show hmap:0.1 # 10% PoE
"""
try:
poe = valid.probability(token.split(':')[1])
except IndexError:
poe = 0.1
try:
mean = dstore['hcurves/mean']
except KeyError: # there is a single realization
mean = dstore['hcurves/rlz-000']
oq = dstore['oqparam']
hmap = calc.make_hmap(mean, oq.imtls, [poe])
items = sorted([(hmap[sid].array.sum(), sid) for sid in hmap])[-20:]
dt = numpy.dtype([('sid', U32)] + [(imt, F32) for imt in oq.imtls])
array = numpy.zeros(len(items), dt)
for i, (maxvalue, sid) in enumerate(reversed(items)):
array[i] = (sid, ) + tuple(hmap[sid].array[:, 0])
return rst_table(array)
