def test_read_interleaved_timestamp_data(benchmark):
""" Benchmark reading a file with interleaved timestamp data
"""
timestamps = np.tile(
np.array([
np.datetime64('2012-08-23T00:00:00.123', 'us'),
np.datetime64('2012-08-23T01:02:03.456', 'us'),
np.datetime64('2012-08-23T12:00:00.0', 'us'),
np.datetime64('2012-08-23T12:02:03.9999', 'us'),
np.datetime64('2012-08-23T12:02:03.9999', 'us'),
np.datetime64('2012-08-23T00:00:00.123', 'us'),
np.datetime64('2012-08-23T01:02:03.456', 'us'),
np.datetime64('2012-08-23T12:00:00.0', 'us'),
np.datetime64('2012-08-23T12:02:03.9999', 'us'),
np.datetime64('2012-08-23T12:02:03.9999', 'us'),
]), 100)
data = timestamp_data_chunk(timestamps)
test_file = GeneratedFile()
test_file.add_segment(
("kTocMetaData", "kTocRawData", "kTocNewObjList",
"kTocInterleavedData"),
segment_objects_metadata(
channel_metadata("/'group'/'channel1'", 0x44, 100, {}),
channel_metadata("/'group'/'channel2'", 0x44, 100, {}),
), data)
tdms_file = benchmark(read_from_start, test_file.get_bytes_io_file())
np.testing.assert_equal(tdms_file['group']['channel1'][:],
timestamps[0::2])
np.testing.assert_equal(tdms_file['group']['channel2'][:],
timestamps[1::2])
def test_stream_scaled_data_chunks(benchmark):
""" Benchmark streaming channel data when the data is scaled
"""
properties = {
"NI_Number_Of_Scales": (3, "01 00 00 00"),
"NI_Scale[0]_Scale_Type":
(0x20, hexlify_value("<I", len("Linear")) + string_hexlify("Linear")),
"NI_Scale[0]_Linear_Slope": (10, hexlify_value("<d", 2.0)),
"NI_Scale[0]_Linear_Y_Intercept": (10, hexlify_value("<d", 10.0))
}
test_file = GeneratedFile()
data_array = np.arange(0, 1000, dtype=np.dtype('int32'))
data = data_array.tobytes()
test_file.add_segment(
("kTocMetaData", "kTocRawData", "kTocNewObjList"),
segment_objects_metadata(
channel_metadata("/'group'/'channel1'", TDS_TYPE_INT32, 100,
properties), ),
data,
binary_data=True)
for _ in range(0, 9):
test_file.add_segment(("kTocRawData", ), "", data, binary_data=True)
with TdmsFile.open(test_file.get_bytes_io_file()) as tdms_file:
channel = tdms_file['group']['channel1']
channel_data = benchmark(stream_chunks, channel)
channel_data = np.concatenate(channel_data)
expected_data = np.tile(10.0 + 2.0 * data_array, 10)
np.testing.assert_equal(channel_data, expected_data)
def test_complex_metadata_reading(benchmark):
""" Benchmark reading metadata for a file with many channels and segments with alternating sets of objects
"""
test_file = GeneratedFile()
data = np.array([0] * 5, dtype=np.dtype('int32')).tobytes()
test_file.add_segment(
("kTocMetaData", "kTocRawData", "kTocNewObjList"),
segment_objects_metadata(
channel_metadata("/'group'/'channel0'", TDS_TYPE_INT32, 1),
channel_metadata("/'group'/'channel1'", TDS_TYPE_INT32, 1),
channel_metadata("/'group'/'channel2'", TDS_TYPE_INT32, 1),
channel_metadata("/'group'/'channel3'", TDS_TYPE_INT32, 1),
channel_metadata("/'group'/'channel4'", TDS_TYPE_INT32, 1),
),
data,
binary_data=True)
test_file.add_segment(
("kTocMetaData", "kTocRawData", "kTocNewObjList"),
segment_objects_metadata(
channel_metadata("/'group'/'channel5'", TDS_TYPE_INT32, 1),
channel_metadata("/'group'/'channel6'", TDS_TYPE_INT32, 1),
channel_metadata("/'group'/'channel7'", TDS_TYPE_INT32, 1),
channel_metadata("/'group'/'channel8'", TDS_TYPE_INT32, 1),
channel_metadata("/'group'/'channel9'", TDS_TYPE_INT32, 1),
),
data,
binary_data=True)
for _ in range(9):
test_file.add_segment(
("kTocMetaData", "kTocRawData", "kTocNewObjList"),
segment_objects_metadata(
channel_metadata_with_no_data("/'group'/'channel0'"),
channel_metadata_with_no_data("/'group'/'channel1'"),
channel_metadata_with_no_data("/'group'/'channel2'"),
channel_metadata_with_no_data("/'group'/'channel3'"),
channel_metadata_with_no_data("/'group'/'channel4'"),
channel_metadata_with_repeated_structure(
"/'group'/'channel5'"),
channel_metadata_with_repeated_structure(
"/'group'/'channel6'"),
channel_metadata_with_repeated_structure(
"/'group'/'channel7'"),
channel_metadata_with_repeated_structure(
"/'group'/'channel8'"),
channel_metadata_with_repeated_structure(
"/'group'/'channel9'"),
),
data,
binary_data=True)
test_file.add_segment(
("kTocMetaData", "kTocRawData", "kTocNewObjList"),
segment_objects_metadata(
channel_metadata_with_repeated_structure(
"/'group'/'channel0'"),
channel_metadata_with_repeated_structure(
"/'group'/'channel1'"),
channel_metadata_with_repeated_structure(
"/'group'/'channel2'"),
channel_metadata_with_repeated_structure(
"/'group'/'channel3'"),
channel_metadata_with_repeated_structure(
"/'group'/'channel4'"),
channel_metadata_with_no_data("/'group'/'channel5'"),
channel_metadata_with_no_data("/'group'/'channel6'"),
channel_metadata_with_no_data("/'group'/'channel7'"),
channel_metadata_with_no_data("/'group'/'channel8'"),
channel_metadata_with_no_data("/'group'/'channel9'"),
),
data,
binary_data=True)
tdms_file = benchmark(read_metadata_from_start,
test_file.get_bytes_io_file())
assert len(tdms_file) == 1
assert len(tdms_file['group']) == 10
for channel_num in range(10):
assert len(tdms_file['group']['channel{0}'.format(channel_num)]) == 10
