Source code for

# -*- coding: utf-8 -*-
# vim: tabstop=4 shiftwidth=4 softtabstop=4
# Copyright (C) 2015-2022 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 os
import json
import logging
import numpy

from openquake.baselib import hdf5
from openquake.commonlib import datastore
from openquake.calculators.views import view, text_table
from openquake.calculators.extract import extract

[docs]def str_or_int(calc_id): try: return int(calc_id) except ValueError: return calc_id
[docs]def main(what='contents', calc_id: str_or_int = -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 = 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.warning('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 = # this part is experimental if 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.getitem(what) if '__pdcolumns__' in obj.attrs: df = ds.read_df(what) print(df.sort_values(df.columns[0])) elif hasattr(obj, 'items'): # is a group of datasets print(obj) else: # is a single dataset obj.refresh() # for SWMR mode print_(hdf5.ArrayWrapper.from_(obj)) else: print('%s not found' % what) ds.close()
main.what = 'key or view of the datastore' main.calc_id = 'calculation ID or datastore path' main.extra = dict(help='extra arguments', nargs='*')