# -*- coding: utf-8 -*-
# Copyright (C) Duncan Macleod (2013)
#
# This file is part of GWSumm.
#
# GWSumm is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# GWSumm 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 General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with GWSumm. If not, see <http://www.gnu.org/licenses/>.
"""Tests for `gwsumm.archive`
"""
import os
import tempfile
import pytest
import h5py
from numpy import (random, testing as nptest)
from gwpy.table import EventTable
from gwpy.timeseries import (TimeSeries, StateVector)
from gwpy.spectrogram import Spectrogram
from gwpy.segments import (Segment, SegmentList)
from .. import (archive, data, globalv, channels, triggers)
__author__ = 'Duncan Macleod <duncan.macleod@ligo.org>'
TEST_DATA = TimeSeries([1, 2, 3, 4, 5, 6, 7, 8, 9, 10], epoch=100,
unit='meter', sample_rate=1, channel='X1:TEST-CHANNEL',
name='TEST DATA')
TEST_DATA.channel = channels.get_channel(TEST_DATA.channel)
# -- utilities ----------------------------------------------------------------
[docs]
def empty_globalv():
globalv.DATA = type(globalv.DATA)()
globalv.SPECTROGRAMS = type(globalv.SPECTROGRAMS)()
globalv.SEGMENTS = type(globalv.SEGMENTS)()
globalv.TRIGGERS = type(globalv.TRIGGERS)()
[docs]
def create(data, **metadata):
SeriesClass = metadata.pop('series_class', TimeSeries)
d = SeriesClass(data, **metadata)
d.channel = channels.get_channel(d.channel)
if not d.name:
d.name = d.channel.texname
return d
# -- tests --------------------------------------------------------------------
[docs]
def test_write_archive(delete=True):
empty_globalv()
data.add_timeseries(TEST_DATA)
data.add_timeseries(create([1, 2, 3, 4, 5],
dt=60., channel='X1:TEST-TREND.mean'))
data.add_timeseries(create([1, 2, 3, 2, 1],
series_class=StateVector,
channel='X1:TEST-STATE_VECTOR'))
data.add_spectrogram(create([[1, 2, 3], [3, 2, 1], [1, 2, 3]],
series_class=Spectrogram,
channel='X1:TEST-SPECTROGRAM'))
t = EventTable(random.random((100, 5)), names=['time', 'a', 'b', 'c', 'd'])
t.meta['segments'] = SegmentList([Segment(0, 100)])
triggers.add_triggers(t, 'X1:TEST-TABLE,testing')
fname = tempfile.mktemp(suffix='.h5', prefix='gwsumm-tests-')
try:
archive.write_data_archive(fname)
archive.write_data_archive(fname) # test again to validate backups
finally:
if delete and os.path.isfile(fname):
os.remove(fname)
return fname
[docs]
def test_read_archive():
fname = test_write_archive(delete=False)
empty_globalv()
try:
archive.read_data_archive(fname)
finally:
os.remove(fname)
# check timeseries
ts = data.get_timeseries('X1:TEST-CHANNEL',
[(100, 110)], query=False).join()
nptest.assert_array_equal(ts.value, TEST_DATA.value)
for attr in ['epoch', 'unit', 'sample_rate', 'channel', 'name']:
assert getattr(ts, attr) == getattr(TEST_DATA, attr)
# check trend series
ts = data.get_timeseries('X1:TEST-TREND.mean,m-trend', [(0, 300)],
query=False).join()
assert ts.channel.type == 'm-trend'
assert ts.span == (0, 300)
# check triggers
t = triggers.get_triggers('X1:TEST-TABLE', 'testing', [(0, 100)])
assert len(t) == 100
[docs]
def test_archive_load_table():
t = EventTable(random.random((100, 5)),
names=['a', 'b', 'c', 'd', 'e'])
empty = EventTable(names=['a', 'b'])
try:
fname = tempfile.mktemp(suffix='.h5', prefix='gwsumm-tests-')
h5file = h5py.File(fname, mode='a')
# check table gets archived and read transparently
archive.archive_table(t, 'test-table', h5file)
t2 = archive.load_table(h5file['test-table'])
nptest.assert_array_equal(t.as_array(), t2.as_array())
assert t.dtype == t2.dtype
# check empty table does not get archived, with warning
with pytest.warns(UserWarning):
n = archive.archive_table(empty, 'test-empty', h5file)
assert n is None
assert 'test-empty' not in h5file
finally:
if os.path.exists(fname):
os.remove(fname)