def test_mp_indexer_4(self):
# that a list with two types is properly filtered when it's given as a Stream
# --> test lengths
# --> two events at each offset
actual = indexer.stream_indexer(0, [self.in_stream], verbatim, [base.ElementWrapper])[1]
self.assertSequenceEqual(list(self.in_series.index), list(actual.index))
self.assertSequenceEqual(list(self.in_series.values), list(actual.values))
def test_multi_event_2(self):
# Test this:
# offset: 0.0 | 0.5 | 1.0 | 1.5 | 2.0
# part 1: [1] | [2][6] | [3] | [4][7] | [5][8]
# part 2: [1] | [2][6] | [3][7] | [4] | [5][8]
part_1 = stream.Stream()
for i in xrange(5):
obj = base.ElementWrapper(i)
obj.offset = 0.5 * i
obj.duration = duration.Duration(0.5)
part_1.append(obj)
part_2 = stream.Stream()
for i in xrange(5):
obj = base.ElementWrapper(i)
obj.offset = 0.5 * i
obj.duration = duration.Duration(0.5)
part_2.append(obj)
add_these = [(part_1, 0.5, 6), (part_1, 1.5, 7), (part_1, 2.0, 8),
(part_2, 0.5, 6), (part_2, 1.0, 7), (part_2, 2.0, 8)]
for part, offset, number in add_these:
zed = base.ElementWrapper(number)
zed.duration = duration.Duration(0.5)
part.insert(offset, zed)
expected = pandas.Series({0.0: u'(0, 0)', 0.5: u'(1, 1)', 1.0: u'(2, 2)',
1.5: u'(3, 3)', 2.0: u'(4, 4)'})
actual = indexer.stream_indexer(0, [part_1, part_2], verbatim_variable)[1]
self.assertSequenceEqual(list(expected.index), list(actual.index))
self.assertSequenceEqual(list(expected), list(actual))
def test_stream_indexer(self):
result = indexer.stream_indexer(0, [self.in_stream], verbatim, [base.ElementWrapper])[1]
# that we get a Series back when a Stream is given
self.assertIs(type(result), pandas.Series)
# the verbatim function is designed to produce exactly what is given
self.assertEqual(len(result), len(self.in_stream))
self.assertSequenceEqual(list(result), [elt.obj for elt in self.in_stream])
def test_mp_indexer_5(self):
# test _4, but we want both ElementWrapper and Rest objects (we should only get
# the "first" events)
actual = indexer.stream_indexer(0,
[self.shared_mixed_list],
verbatim_rests,
[base.ElementWrapper, note.Rest])[1]
self.assertSequenceEqual(list(self.shared_mixed_rests_series.index), list(actual.index))
self.assertSequenceEqual(list(self.shared_mixed_rests_series.values), list(actual.values))
def test_mp_indexer_3(self):
# same as test _2, but the Strame is pickled
# ** inputted Streams are pickled
# --> test values
# --> one event at each offset
input_stream = converter.freeze(stream.Stream(self.mixed_list), u'pickle')
actual = indexer.stream_indexer(0, [input_stream], verbatim, [base.ElementWrapper])[1]
self.assertSequenceEqual(list(self.mixed_series_notes.index), list(actual.index))
self.assertSequenceEqual(list(self.mixed_series_notes.values), list(actual.values))
def test_indexer_init_10(self):
# when no "types" is specified, make sure it returns everything in the Stream
# setup the input stream
the_stream = stream.Stream()
the_stream.append(note.Note(u'D#2', quarterLength=0.5))
the_stream.append(note.Rest(quarterLength=0.5))
the_stream.append(clef.TrebleClef())
# setup the expected Series
expected = pandas.Series({0.0: note.Note(u'D#2', quarterLength=0.5),
0.5: note.Rest(quarterLength=0.5),
1.0: clef.TrebleClef()})
# run the test; verify results
actual = indexer.stream_indexer(12, [the_stream], verbatim_ser)
# check the multiprocessing token is returned, then get rid of it
self.assertEqual(2, len(actual))
self.assertEqual(12, actual[0])
actual = actual[1]
# check both the index and values are equal
self.assertSequenceEqual(list(expected.index), list(actual.index))
self.assertSequenceEqual(list(expected.values), list(actual.values))
def test_multi_event_1(self):
# Test this:
# offset: 0.0 | 0.5 | 1.0 | 1.5 | 2.0
# part 1: [0] | [1] | [2] | [3] | [4]
# part 2: [0] | [1] | [2] | [3] | [4]
part_1 = stream.Stream()
for i in xrange(5):
obj = base.ElementWrapper(i)
obj.offset = 0.5 * i
obj.duration = duration.Duration(0.5)
part_1.append(obj)
part_2 = stream.Stream()
for i in xrange(5):
obj = base.ElementWrapper(i)
obj.offset = 0.5 * i
obj.duration = duration.Duration(0.5)
part_2.append(obj)
expected = pandas.Series({0.0: u'(0, 0)', 0.5: u'(1, 1)', 1.0: u'(2, 2)',
1.5: u'(3, 3)', 2.0: u'(4, 4)'})
actual = indexer.stream_indexer(0, [part_1, part_2], verbatim_variable)[1]
self.assertSequenceEqual(list(expected.index), list(actual.index))
self.assertSequenceEqual(list(expected), list(actual))
