# -*- coding: utf-8 -*-
# vim: tabstop=4 shiftwidth=4 softtabstop=4
#
# Copyright (C) 2015-2018 GEM Foundation
#
# OpenQuake is free software: you can redistribute it and/or modify it
# under the terms of the GNU Affero General Public License as published
# by the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# OpenQuake is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Affero General Public License for more details.
#
# You should have received a copy of the GNU Affero General Public License
# along with OpenQuake. If not, see <http://www.gnu.org/licenses/>.
import numpy
from openquake.baselib import sap, datastore
from openquake.hazardlib.stats import mean_curve, compute_pmap_stats
from openquake.calculators import getters
[docs]def get_pmaps(dstore, indices):
rlzs_assoc = dstore['csm_info'].get_rlzs_assoc()
getter = getters.PmapGetter(dstore, rlzs_assoc)
getter.init()
pmaps = getter.get_pmaps(indices)
weights = dstore['csm_info'].rlzs['weight']
mean = compute_pmap_stats(pmaps, [mean_curve], weights)
return mean, pmaps
@sap.Script
def plot(calc_id, other_id=None, sites='0'):
"""
Hazard curves plotter.
"""
# read the hazard data
haz = datastore.read(calc_id)
other = datastore.read(other_id) if other_id else None
oq = haz['oqparam']
indices = numpy.array(list(map(int, sites.split(','))))
n_sites = len(haz['sitecol'])
if not set(indices) <= set(range(n_sites)):
invalid = sorted(set(indices) - set(range(n_sites)))
print('The indices %s are invalid: no graph for them' % invalid)
valid = sorted(set(range(n_sites)) & set(indices))
print('Found %d site(s); plotting %d of them' % (n_sites, len(valid)))
if other is None:
mean_curves, pmaps = get_pmaps(haz, indices)
single_curve = len(pmaps) == 1
plt = make_figure(valid, n_sites, oq.imtls, mean_curves,
[] if single_curve else pmaps, 'mean')
else:
mean1, _ = get_pmaps(haz, indices)
mean2, _ = get_pmaps(other, indices)
plt = make_figure(valid, n_sites, oq.imtls, mean1,
[mean2], 'reference')
plt.show()
plot.arg('calc_id', 'a computation id', type=int)
plot.arg('other_id', 'optional id of another computation', type=int)
plot.opt('sites', 'comma-separated string with the site indices')