Source code for

# -*- 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
# 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 <>.
import io
import os
import logging
import numpy

from openquake.baselib import sap, config
from openquake.hazardlib import stats
from openquake.baselib import datastore
from openquake.commonlib.writers import write_csv
from openquake.commonlib.util import rmsep
from openquake.commonlib import logs
from openquake.calculators import getters
from openquake.calculators.views import view
from openquake.calculators.extract import extract

if config.dbserver.multi_user:
    def read(calc_id):
        job = logs.dbcmd('get_job', calc_id)
        if job:
            return + '.hdf5')
        # calc_id can be present in the datastore and not in the database:
        # this happens if the calculation was run with `oq run`
else:  # get the datastore of the current user
    read =

[docs]def get_hcurves_and_means(dstore): """ Extract hcurves from the datastore and compute their means. :returns: curves_by_rlz, mean_curves """ rlzs_assoc = dstore['csm_info'].get_rlzs_assoc() getter = getters.PmapGetter(dstore, rlzs_assoc) sitecol = dstore['sitecol'] pmaps = getter.get_pmaps(sitecol.sids) return dict(zip(getter.rlzs, pmaps)), dstore['hcurves/mean']
@sap.Script def show(what='contents', calc_id=-1, extra=()): """ Show the content of a datastore (by default the last one). """ datadir = datastore.get_datadir() if what == 'all': # show all if not os.path.exists(datadir): return rows = [] for calc_id in datastore.get_calc_ids(datadir): try: ds = read(calc_id) oq = ds['oqparam'] cmode, descr = oq.calculation_mode, oq.description except Exception: # invalid datastore file, or missing calculation_mode # and description attributes, perhaps due to a manual kill f = os.path.join(datadir, 'calc_%s.hdf5' % calc_id) logging.warn('Unreadable datastore %s', f) continue else: rows.append((calc_id, cmode, descr.encode('utf-8'))) for row in sorted(rows, key=lambda row: row[0]): # by calc_id print('#%d %s: %s' % row) return ds = read(calc_id) # this part is experimental if what == 'rlzs' and 'poes' in ds: min_value = 0.01 # used in rmsep getter = getters.PmapGetter(ds) sitecol = ds['sitecol'] pmaps = getter.get_pmaps(sitecol.sids) weights = [rlz.weight for rlz in getter.rlzs] mean = stats.compute_pmap_stats(pmaps, [numpy.mean], weights) dists = [] for rlz, pmap in zip(getter.rlzs, pmaps): dist = rmsep(mean.array, pmap.array, min_value) dists.append((dist, rlz)) print('Realizations in order of distance from the mean curves') for dist, rlz in sorted(dists): print('%s: rmsep=%s' % (rlz, dist)) elif view.keyfunc(what) in view: print(view(what, ds)) elif what.split('/', 1)[0] in extract: print(extract(ds, what, *extra)) elif what in ds: obj = ds[what] if hasattr(obj, 'value'): # an array print(write_csv(io.BytesIO(), obj.value).decode('utf8')) else: print(obj) else: print('%s not found' % what) ds.close() show.arg('what', 'key or view of the datastore') show.arg('calc_id', 'calculation ID', type=int) show.arg('extra', 'extra arguments', nargs='*')