Source code for openquake.commands.plot

# -*- 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 make_figure(indices, n, imtls, spec_curves, curves=(), label=''): """ :param indices: the indices of the sites under analysis :param n: the total number of sites :param imtls: ordered dictionary with the IMTs and levels :param spec_curves: a dictionary of curves IMT -> array(n_sites, n_levels) :param curves: a dictionary of dictionaries IMT -> array :param label: the label associated to `spec_curves` """ # NB: matplotlib is imported inside since it is a costly import import matplotlib.pyplot as plt fig = plt.figure() n_imts = len(imtls) n_sites = len(indices) spec_curves = spec_curves.convert(imtls, n) all_curves = [c.convert(imtls, n) for c in curves] for i, site in enumerate(indices): for j, imt in enumerate(imtls): ax = fig.add_subplot(n_sites, n_imts, i * n_imts + j + 1) ax.grid(True) ax.set_xlabel('site %d, %s' % (site, imt)) ax.set_ylim([0, 1]) if j == 0: # set Y label only on the leftmost graph ax.set_ylabel('PoE') if spec_curves is not None: ax.plot(imtls[imt], spec_curves[imt][site], '--', label=label) for r, curves in enumerate(all_curves): ax.plot(imtls[imt], curves[imt][site], label=str(r)) ax.legend() return plt
[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')