def timestamp_data():
"""Test reading contiguous timestamp data
"""
times = [
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'),
]
test_file = GeneratedFile()
test_file.add_segment(
("kTocMetaData", "kTocRawData", "kTocNewObjList"),
segment_objects_metadata(
channel_metadata("/'Group'/'TimeChannel1'", 0x44, 2),
channel_metadata("/'Group'/'TimeChannel2'", 0x44, 2),
), timestamp_data_chunk(times))
expected_data = {
('Group', 'TimeChannel1'): np.array([times[0], times[1]]),
('Group', 'TimeChannel2'): np.array([times[2], times[3]]),
}
return test_file, expected_data
def complex_data():
""" Test reading a file with complex valued data
"""
complex_single_arr = np.array([1 + 2j, 3 + 4j], dtype=np.complex64)
complex_double_arr = np.array([5 + 6j, 7 + 8j], dtype=np.complex128)
data = ""
for num in complex_single_arr:
data += hexlify_value("<f", num.real)
data += hexlify_value("<f", num.imag)
for num in complex_double_arr:
data += hexlify_value("<d", num.real)
data += hexlify_value("<d", num.imag)
test_file = GeneratedFile()
test_file.add_segment(
("kTocMetaData", "kTocRawData", "kTocNewObjList"),
segment_objects_metadata(
channel_metadata("/'group'/'complex_single_channel'",
TDS_TYPE_COMPLEX64, 2),
channel_metadata("/'group'/'complex_double_channel'",
TDS_TYPE_COMPLEX128, 2),
), data)
expected_data = {
('group', 'complex_single_channel'): complex_single_arr,
('group', 'complex_double_channel'): complex_double_arr,
}
return test_file, expected_data
def float_data_with_unit():
""" Test reading a file with float valued data with units
These are the same as normal floating point data but have a 'unit_string' property
"""
single_arr = np.array([0.123, 0.234, 0.345, 0.456], dtype=np.float32)
double_arr = np.array([0.987, 0.876, 0.765, 0.654], dtype=np.double)
data = ""
for num in single_arr[0:2]:
data += hexlify_value("<f", num)
for num in double_arr[0:2]:
data += hexlify_value("<d", num)
for num in single_arr[2:4]:
data += hexlify_value("<f", num)
for num in double_arr[2:4]:
data += hexlify_value("<d", num)
test_file = GeneratedFile()
test_file.add_segment(("kTocMetaData", "kTocRawData", "kTocNewObjList"),
segment_objects_metadata(
channel_metadata("/'group'/'single_channel'",
TDS_TYPE_FLOAT32_WITH_UNIT, 2),
channel_metadata("/'group'/'double_channel'",
TDS_TYPE_FLOAT64_WITH_UNIT, 2),
), data)
expected_data = {
('group', 'single_channel'): single_arr,
('group', 'double_channel'): double_arr,
}
return test_file, expected_data
def test_floating_point_data_types(tmp_path):
""" Test conversion of f32 and f64 types to HDF
"""
test_file = GeneratedFile()
test_file.add_segment(
("kTocMetaData", "kTocRawData", "kTocNewObjList"),
segment_objects_metadata(
channel_metadata("/'group'/'f32'", 9, 4),
channel_metadata("/'group'/'f64'", 10, 4),
),
hexlify_value('<f', 1) +
hexlify_value('<f', 2) +
hexlify_value('<f', 3) +
hexlify_value('<f', 4) +
hexlify_value('<d', 1) +
hexlify_value('<d', 2) +
hexlify_value('<d', 3) +
hexlify_value('<d', 4)
)
tdms_data = test_file.load()
h5_path = tmp_path / 'h5_data_test.h5'
h5 = tdms_data.as_hdf(h5_path)
for chan, expected_dtype in [
('f32', np.dtype('float32')),
('f64', np.dtype('float64'))]:
h5_channel = h5['group'][chan]
assert h5_channel.dtype == expected_dtype
np.testing.assert_almost_equal(h5_channel[...], [1.0, 2.0, 3.0, 4.0])
h5.close()
def object_with_no_metadata_in_segment():
""" Re-use an object without setting any new metadata and
re-using the data structure
"""
test_file = GeneratedFile()
test_file.add_segment(
("kTocMetaData", "kTocRawData", "kTocNewObjList"),
segment_objects_metadata(
channel_metadata("/'group'/'channel1'", TDS_TYPE_INT32, 2),
channel_metadata("/'group'/'channel2'", TDS_TYPE_INT32, 2),
), "01 00 00 00"
"02 00 00 00"
"03 00 00 00"
"04 00 00 00")
test_file.add_segment(
("kTocMetaData", "kTocRawData", "kTocNewObjList"),
segment_objects_metadata(
channel_metadata_with_repeated_structure("/'group'/'channel1'"),
channel_metadata_with_repeated_structure("/'group'/'channel2'"),
), "05 00 00 00"
"06 00 00 00"
"07 00 00 00"
"08 00 00 00")
expected_data = {
('group', 'channel1'): np.array([1, 2, 5, 6], dtype=np.int32),
('group', 'channel2'): np.array([3, 4, 7, 8], dtype=np.int32),
}
return test_file, expected_data
def incomplete_last_segment():
""" Test incomplete last segment, eg. if LabView crashed
"""
test_file = GeneratedFile()
test_file.add_segment(
("kTocMetaData", "kTocRawData", "kTocNewObjList"),
segment_objects_metadata(
channel_metadata("/'group'/'channel1'", TDS_TYPE_INT32, 2),
channel_metadata("/'group'/'channel2'", TDS_TYPE_INT32, 2),
), "01 00 00 00"
"02 00 00 00"
"03 00 00 00"
"04 00 00 00"
"05 00 00 00"
"06 00 00 00"
"07 00 00 00"
"08 00 00 00")
test_file.add_segment(("kTocRawData", ),
"", "09 00 00 00"
"0A 00 00 00"
"0B 00 00 00"
"0C 00 00 00",
incomplete=True)
expected_data = {
('group', 'channel1'): np.array([1, 2, 5, 6, 9, 10], dtype=np.int32),
('group', 'channel2'): np.array([3, 4, 7, 8, 11, 12], dtype=np.int32),
}
return test_file, expected_data
def less_data_than_expected_interleaved():
""" Add interleaved data segment and then a repeated segment without
any lead in or metadata, so data is read in chunks,
but the extra chunk does not have as much data as expected.
"""
test_file = GeneratedFile()
test_file.add_segment(
("kTocMetaData", "kTocRawData", "kTocNewObjList",
"kTocInterleavedData"),
segment_objects_metadata(
channel_metadata("/'group'/'channel1'", TDS_TYPE_INT32, 3),
channel_metadata("/'group'/'channel2'", TDS_TYPE_INT32, 3),
), "01 00 00 00"
"02 00 00 00"
"03 00 00 00"
"04 00 00 00"
"05 00 00 00"
"06 00 00 00"
"07 00 00 00"
"08 00 00 00"
"09 00 00 00"
"0A 00 00 00")
expected_data = {
('group', 'channel1'): np.array([1, 3, 5, 7, 9], dtype=np.int32),
('group', 'channel2'): np.array([2, 4, 6, 8, 10], dtype=np.int32),
}
return test_file, expected_data
def chunked_segment():
""" Add segment and then a repeated segment without
any lead in or metadata, so data is read in chunks
"""
test_file = GeneratedFile()
test_file.add_segment(
("kTocMetaData", "kTocRawData", "kTocNewObjList"),
segment_objects_metadata(
channel_metadata("/'group'/'channel1'", TDS_TYPE_INT32, 2),
channel_metadata("/'group'/'channel2'", TDS_TYPE_INT32, 2),
), "00 00 00 00"
"01 00 00 00"
"0A 00 00 00"
"0B 00 00 00"
"02 00 00 00"
"03 00 00 00"
"0C 00 00 00"
"0D 00 00 00")
test_file.add_segment(("kTocRawData", ), "", "04 00 00 00"
"05 00 00 00"
"0E 00 00 00"
"0F 00 00 00"
"06 00 00 00"
"07 00 00 00"
"10 00 00 00"
"11 00 00 00")
expected_data = {
('group', 'channel1'):
np.array([0, 1, 2, 3, 4, 5, 6, 7], dtype=np.int32),
('group', 'channel2'):
np.array([10, 11, 12, 13, 14, 15, 16, 17], dtype=np.int32),
}
return test_file, expected_data
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 chunked_interleaved_segment():
""" Add interleaved segment and then a repeated segment without
any lead in or metadata, so data is read in chunks
"""
test_file = GeneratedFile()
test_file.add_segment(
("kTocMetaData", "kTocRawData", "kTocNewObjList",
"kTocInterleavedData"),
segment_objects_metadata(
channel_metadata("/'group'/'channel1'", TDS_TYPE_INT32, 2),
channel_metadata("/'group'/'channel2'", TDS_TYPE_INT32, 2),
), "01 00 00 00"
"02 00 00 00"
"03 00 00 00"
"04 00 00 00"
"05 00 00 00"
"06 00 00 00"
"07 00 00 00"
"08 00 00 00")
test_file.add_segment(("kTocRawData", "kTocInterleavedData"), "",
"07 00 00 00"
"08 00 00 00"
"05 00 00 00"
"06 00 00 00"
"03 00 00 00"
"04 00 00 00"
"01 00 00 00"
"02 00 00 00")
expected_data = {
('group', 'channel1'): np.array([1, 3, 5, 7, 7, 5, 3, 1],
dtype=np.int32),
('group', 'channel2'): np.array([2, 4, 6, 8, 8, 6, 4, 2],
dtype=np.int32),
}
return test_file, expected_data
def remove_a_channel():
""" In the second segment, remove a channel.
We need to write a new object list in this case
"""
test_file = GeneratedFile()
test_file.add_segment(
("kTocMetaData", "kTocRawData", "kTocNewObjList"),
segment_objects_metadata(
channel_metadata("/'group'/'channel1'", TDS_TYPE_INT32, 2),
channel_metadata("/'group'/'channel2'", TDS_TYPE_INT32, 2),
), "01 00 00 00"
"02 00 00 00"
"03 00 00 00"
"04 00 00 00")
test_file.add_segment(("kTocMetaData", "kTocRawData", "kTocNewObjList"),
segment_objects_metadata(
channel_metadata("/'group'/'channel1'",
TDS_TYPE_INT32, 2), ),
"05 00 00 00"
"06 00 00 00")
expected_data = {
('group', 'channel1'): np.array([1, 2, 5, 6], dtype=np.int32),
('group', 'channel2'): np.array([3, 4], dtype=np.int32),
}
return test_file, expected_data
def incomplete_last_row_of_interleaved_data():
""" Test incomplete last row of interleaved data
"""
test_file = GeneratedFile()
test_file.add_segment(
("kTocMetaData", "kTocRawData", "kTocNewObjList",
"kTocInterleavedData"),
segment_objects_metadata(
channel_metadata("/'group'/'channel1'", TDS_TYPE_INT32, 2),
channel_metadata("/'group'/'channel2'", TDS_TYPE_INT32, 2),
), "01 00 00 00"
"02 00 00 00"
"03 00 00 00"
"04 00 00 00"
"05 00 00 00"
"06 00 00 00"
"07 00 00 00"
"08 00 00 00"
"09 00 00 00"
"0A 00 00 00"
"0B 00 00 00",
incomplete=True)
expected_data = {
('group', 'channel1'): np.array([1, 3, 5, 7, 9], dtype=np.int32),
('group', 'channel2'): np.array([2, 4, 6, 8, 10], dtype=np.int32),
}
return test_file, expected_data
def repeated_objects_without_data_in_segment_and_added_object():
""" Repeated objects with no data in new segment as well as a new channel with data
"""
test_file = GeneratedFile()
test_file.add_segment(
("kTocMetaData", "kTocRawData", "kTocNewObjList"),
segment_objects_metadata(
channel_metadata("/'group'/'channel1'", TDS_TYPE_INT32, 2),
channel_metadata("/'group'/'channel2'", TDS_TYPE_INT32, 2),
), "01 00 00 00"
"02 00 00 00"
"03 00 00 00"
"04 00 00 00")
test_file.add_segment(
("kTocMetaData", "kTocRawData", "kTocNewObjList"),
segment_objects_metadata(
channel_metadata_with_no_data("/'group'/'channel1'"),
channel_metadata_with_no_data("/'group'/'channel2'"),
channel_metadata("/'group'/'channel3'", TDS_TYPE_INT32, 2),
), "05 00 00 00"
"06 00 00 00")
expected_data = {
('group', 'channel1'): np.array([1, 2], dtype=np.int32),
('group', 'channel2'): np.array([3, 4], dtype=np.int32),
('group', 'channel3'): np.array([5, 6], dtype=np.int32),
}
return test_file, expected_data
def increase_channel_size():
""" In the second segment, increase the channel size of one channel
"""
test_file = GeneratedFile()
test_file.add_segment(
("kTocMetaData", "kTocRawData", "kTocNewObjList"),
segment_objects_metadata(
channel_metadata("/'group'/'channel1'", TDS_TYPE_INT32, 2),
channel_metadata("/'group'/'channel2'", TDS_TYPE_INT32, 2),
), "01 00 00 00"
"02 00 00 00"
"03 00 00 00"
"04 00 00 00")
test_file.add_segment(("kTocMetaData", "kTocRawData"),
segment_objects_metadata(
channel_metadata("/'group'/'channel2'",
TDS_TYPE_INT32, 4), ),
"05 00 00 00"
"06 00 00 00"
"07 00 00 00"
"08 00 00 00"
"09 00 00 00"
"0A 00 00 00")
expected_data = {
('group', 'channel1'): np.array([1, 2, 5, 6], dtype=np.int32),
('group', 'channel2'): np.array([3, 4, 7, 8, 9, 10], dtype=np.int32),
}
return test_file, expected_data
def add_new_channel():
""" Add a new voltage channel, with the other two channels
remaining unchanged, so only the new channel is in metadata section
"""
test_file = GeneratedFile()
test_file.add_segment(
("kTocMetaData", "kTocRawData", "kTocNewObjList"),
segment_objects_metadata(
channel_metadata("/'group'/'channel1'", TDS_TYPE_INT32, 2),
channel_metadata("/'group'/'channel2'", TDS_TYPE_INT32, 2),
), "01 00 00 00"
"02 00 00 00"
"03 00 00 00"
"04 00 00 00")
test_file.add_segment(("kTocMetaData", "kTocRawData"),
segment_objects_metadata(
channel_metadata("/'group'/'channel3'",
TDS_TYPE_INT32, 2), ),
"05 00 00 00"
"06 00 00 00"
"07 00 00 00"
"08 00 00 00"
"09 00 00 00"
"0A 00 00 00")
expected_data = {
('group', 'channel1'): np.array([1, 2, 5, 6], dtype=np.int32),
('group', 'channel2'): np.array([3, 4, 7, 8], dtype=np.int32),
('group', 'channel3'): np.array([9, 10], dtype=np.int32),
}
return test_file, expected_data
def float_data():
""" Test reading a file with float valued data
"""
single_arr = np.array([0.123, 0.234, 0.345, 0.456], dtype=np.float32)
double_arr = np.array([0.987, 0.876, 0.765, 0.654], dtype=np.double)
data = ""
for num in single_arr[0:2]:
data += hexlify_value("<f", num)
for num in double_arr[0:2]:
data += hexlify_value("<d", num)
for num in single_arr[2:4]:
data += hexlify_value("<f", num)
for num in double_arr[2:4]:
data += hexlify_value("<d", num)
test_file = GeneratedFile()
test_file.add_segment(
("kTocMetaData", "kTocRawData", "kTocNewObjList"),
segment_objects_metadata(
channel_metadata("/'group'/'single_channel'", TDS_TYPE_FLOAT32, 2),
channel_metadata("/'group'/'double_channel'", TDS_TYPE_FLOAT64, 2),
), data)
expected_data = {
('group', 'single_channel'): single_arr,
('group', 'double_channel'): double_arr,
}
return test_file, expected_data
def test_slash_and_space_in_name():
"""Test name like '01/02/03 something'"""
group_1 = "01/02/03 something"
channel_1 = "04/05/06 another thing"
group_2 = "01/02/03 a"
channel_2 = "04/05/06 b"
test_file = GeneratedFile()
test_file.add_segment(
("kTocMetaData", "kTocRawData", "kTocNewObjList"),
segment_objects_metadata(
channel_metadata("/'{0}'/'{1}'".format(group_1, channel_1), 3, 2),
channel_metadata("/'{0}'/'{1}'".format(group_2, channel_2), 3, 2),
), "01 00 00 00"
"02 00 00 00"
"03 00 00 00"
"04 00 00 00")
tdms_data = test_file.load()
assert len(tdms_data.groups()) == 2
assert len(tdms_data[group_1].channels()) == 1
assert len(tdms_data[group_2].channels()) == 1
data_1 = tdms_data[group_1][channel_1].data
assert len(data_1) == 2
data_2 = tdms_data[group_2][channel_2].data
assert len(data_2) == 2
def single_segment_with_two_channels():
test_file = GeneratedFile()
test_file.add_segment(
("kTocMetaData", "kTocRawData", "kTocNewObjList"),
segment_objects_metadata(
channel_metadata("/'group'/'channel1'", TDS_TYPE_INT32, 2),
channel_metadata("/'group'/'channel2'", TDS_TYPE_INT32, 2),
), "01 00 00 00"
"02 00 00 00"
"03 00 00 00"
"04 00 00 00")
expected_data = {
('group', 'channel1'): np.array([1, 2], dtype=np.int32),
('group', 'channel2'): np.array([3, 4], dtype=np.int32),
}
return test_file, expected_data
def test_reading_subset_of_data(offset, length):
channel_data = np.arange(0, 100, 1, dtype=np.int32)
# Split data into different sized segments
segment_data = [
channel_data[0:10],
channel_data[10:20],
channel_data[20:60],
channel_data[60:80],
channel_data[80:90],
channel_data[90:100],
]
hex_segment_data = [
"".join(hexlify_value('<i', x) for x in data) for data in segment_data
]
test_file = GeneratedFile()
test_file.add_segment(
("kTocMetaData", "kTocRawData", "kTocNewObjList"),
segment_objects_metadata(channel_metadata("/'group'/'channel1'", 3,
5), ), hex_segment_data[0])
for hex_data in hex_segment_data[1:]:
test_file.add_segment(("kTocRawData", ), "", hex_data)
with test_file.get_tempfile() as temp_file:
with TdmsFile.open(temp_file.file) as tdms_file:
channel_subset = tdms_file['group']['channel1'].read_data(
offset, length)
expected_data = channel_data[offset:offset + length]
assert len(channel_subset) == len(expected_data)
np.testing.assert_equal(channel_subset, expected_data)
def test_read_raw_timestamp_data():
""" Test reading timestamp data as a raw TDMS timestamps
"""
test_file = GeneratedFile()
seconds = 3672033330
second_fractions = 1234567890 * 10**10
test_file.add_segment(
("kTocMetaData", "kTocRawData", "kTocNewObjList"),
segment_objects_metadata(
channel_metadata("/'group'/'channel1'", 0x44, 4), ),
hexlify_value("<Q", 0) + hexlify_value("<q", seconds) +
hexlify_value("<Q", second_fractions) + hexlify_value("<q", seconds) +
hexlify_value("<Q", 0) + hexlify_value("<q", seconds + 1) +
hexlify_value("<Q", second_fractions) +
hexlify_value("<q", seconds + 1))
expected_seconds = np.array([seconds, seconds, seconds + 1, seconds + 1],
np.dtype('int64'))
expected_second_fractions = np.array(
[0, second_fractions, 0, second_fractions], np.dtype('uint64'))
with test_file.get_tempfile() as temp_file:
tdms_data = TdmsFile.read(temp_file.file, raw_timestamps=True)
data = tdms_data['group']['channel1'][:]
assert isinstance(data, TimestampArray)
np.testing.assert_equal(data.seconds, expected_seconds)
np.testing.assert_equal(data.second_fractions,
expected_second_fractions)
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 segment_without_data():
test_file = GeneratedFile()
test_file.add_segment(("kTocMetaData", "kTocNewObjList"),
segment_objects_metadata(
channel_metadata("/'group'/'channel1'",
TDS_TYPE_INT32, 2), ), "")
test_file.add_segment(
("kTocMetaData", "kTocNewObjList", "kTocRawData"),
segment_objects_metadata(
channel_metadata_with_repeated_structure("/'group'/'channel1'"), ),
"01 00 00 00"
"02 00 00 00")
test_file.add_segment(
("kTocMetaData", "kTocNewObjList"),
segment_objects_metadata(
channel_metadata_with_repeated_structure("/'group'/'channel1'"), ),
"")
test_file.add_segment(
("kTocMetaData", "kTocNewObjList", "kTocRawData"),
segment_objects_metadata(
channel_metadata_with_repeated_structure("/'group'/'channel1'"), ),
"03 00 00 00"
"04 00 00 00")
expected_data = {
('group', 'channel1'): np.array([1, 2, 3, 4], dtype=np.int32),
}
return test_file, expected_data
def test_read_with_mismatching_index_file():
""" Test that reading data when the index file doesn't match the data file raises an error
"""
test_file = GeneratedFile()
test_file.add_segment(
("kTocMetaData", "kTocRawData", "kTocNewObjList"),
segment_objects_metadata(
channel_metadata("/'group'/'channel1'", 3, 2),
channel_metadata("/'group'/'channel2'", 3, 2),
),
"01 00 00 00" "02 00 00 00"
"03 00 00 00" "04 00 00 00"
)
test_file.add_segment(
("kTocMetaData", "kTocRawData", "kTocNewObjList"),
segment_objects_metadata(
channel_metadata("/'group'/'channel1'", 3, 2),
channel_metadata("/'group'/'channel2'", 3, 2),
),
"01 00 00 00" "02 00 00 00"
"03 00 00 00" "04 00 00 00"
)
test_file_with_index = GeneratedFile()
test_file_with_index.add_segment(
("kTocMetaData", "kTocRawData", "kTocNewObjList"),
segment_objects_metadata(
channel_metadata("/'group'/'channel1'", 3, 3),
channel_metadata("/'group'/'channel2'", 3, 3),
),
"01 00 00 00" "02 00 00 00" "03 00 00 00"
"04 00 00 00" "05 00 00 00" "06 00 00 00"
)
test_file_with_index.add_segment(
("kTocMetaData", "kTocRawData", "kTocNewObjList"),
segment_objects_metadata(
channel_metadata("/'group'/'channel1'", 3, 3),
channel_metadata("/'group'/'channel2'", 3, 3),
),
"01 00 00 00" "02 00 00 00" "03 00 00 00"
"04 00 00 00" "05 00 00 00" "06 00 00 00"
)
with test_file.get_tempfile(delete=False) as tdms_file:
with test_file_with_index.get_tempfile_with_index() as tdms_file_with_index_path:
# Move index file from second file to match the name of the first file
new_index_file = tdms_file.name + '_index'
copyfile(tdms_file_with_index_path + '_index', new_index_file)
try:
tdms_file.file.close()
with pytest.raises(ValueError) as exc_info:
_ = TdmsFile.read(tdms_file.name)
assert 'Check that the tdms_index file matches the tdms data file' in str(exc_info.value)
finally:
os.remove(new_index_file)
os.remove(tdms_file.name)
def extra_padding_after_metadata():
test_file = GeneratedFile()
test_file.add_segment(
("kTocMetaData", "kTocRawData", "kTocNewObjList"),
segment_objects_metadata(
channel_metadata("/'group'/'channel1'", TDS_TYPE_INT32, 2), ) +
"00 00 00 00 00 00 00 00", "01 00 00 00"
"02 00 00 00")
test_file.add_segment(
("kTocMetaData", "kTocRawData", "kTocNewObjList"),
segment_objects_metadata(
channel_metadata("/'group'/'channel1'", TDS_TYPE_INT32, 2), ) +
"00 00 00 00 00 00 00 00", "03 00 00 00"
"04 00 00 00")
expected_data = {
('group', 'channel1'): np.array([1, 2, 3, 4], dtype=np.int32),
}
return test_file, expected_data
def get_contiguous_file():
test_file = GeneratedFile()
data_chunk = np.repeat(np.array([1, 2, 3, 4], dtype=np.dtype('int32')),
100)
data_array = np.tile(data_chunk, 10)
data = data_array.tobytes()
test_file.add_segment(
("kTocMetaData", "kTocRawData", "kTocNewObjList"),
segment_objects_metadata(
channel_metadata("/'group'/'channel1'", TDS_TYPE_INT32, 100),
channel_metadata("/'group'/'channel2'", TDS_TYPE_INT32, 100),
channel_metadata("/'group'/'channel3'", TDS_TYPE_INT32, 100),
channel_metadata("/'group'/'channel4'", TDS_TYPE_INT32, 100),
),
data,
binary_data=True)
for _ in range(0, 9):
test_file.add_segment(("kTocRawData", ), "", data, binary_data=True)
return test_file
def channel_without_data():
test_file = GeneratedFile()
test_file.add_segment(("kTocMetaData", "kTocNewObjList"),
segment_objects_metadata(
channel_metadata("/'group'/'channel1'",
TDS_TYPE_INT32, 2), ), "")
expected_data = {
('group', 'channel1'): np.array([], dtype=np.dtype('int32')),
}
return test_file, expected_data
def alternating_data_objects_reusing_obj_list():
""" Alternating segments with different objects with data,
reusing the object list from the last segment.
"""
test_file = GeneratedFile()
test_file.add_segment(
("kTocMetaData", "kTocRawData", "kTocNewObjList"),
segment_objects_metadata(
channel_metadata("/'group'/'channel1'", TDS_TYPE_INT32, 2),
channel_metadata_with_no_data("/'group'/'channel2'"),
), "01 00 00 00"
"02 00 00 00")
test_file.add_segment(
("kTocMetaData", "kTocRawData"),
segment_objects_metadata(
channel_metadata_with_no_data("/'group'/'channel1'"),
channel_metadata("/'group'/'channel2'", TDS_TYPE_INT32, 2),
), "03 00 00 00"
"04 00 00 00")
test_file.add_segment(
("kTocMetaData", "kTocRawData"),
segment_objects_metadata(
channel_metadata_with_repeated_structure("/'group'/'channel1'"),
channel_metadata_with_no_data("/'group'/'channel2'"),
), "05 00 00 00"
"06 00 00 00")
test_file.add_segment(
("kTocMetaData", "kTocRawData"),
segment_objects_metadata(
channel_metadata_with_no_data("/'group'/'channel1'"),
channel_metadata_with_repeated_structure("/'group'/'channel2'"),
), "07 00 00 00"
"08 00 00 00")
expected_data = {
('group', 'channel1'): np.array([1, 2, 5, 6], dtype=np.int32),
('group', 'channel2'): np.array([3, 4, 7, 8], dtype=np.int32),
}
return test_file, expected_data
def single_segment_with_interleaved_data_of_different_width():
test_file = GeneratedFile()
test_file.add_segment(
("kTocMetaData", "kTocRawData", "kTocNewObjList",
"kTocInterleavedData"),
segment_objects_metadata(
channel_metadata("/'group'/'channel1'", TDS_TYPE_INT8, 2),
channel_metadata("/'group'/'channel2'", TDS_TYPE_INT16, 2),
channel_metadata("/'group'/'channel3'", TDS_TYPE_INT32, 2),
), "01"
"01 00"
"01 00 00 00"
"02"
"02 00"
"02 00 00 00"
"03"
"03 00"
"03 00 00 00")
expected_data = {
('group', 'channel1'): np.array([1, 2, 3], dtype=np.int8),
('group', 'channel2'): np.array([1, 2, 3], dtype=np.int16),
('group', 'channel3'): np.array([1, 2, 3], dtype=np.int32),
}
return test_file, expected_data
def no_metadata_segment():
""" Add a segment with two channels, then a second
segment with the same metadata as before,
so there is only the lead in and binary data
"""
test_file = GeneratedFile()
test_file.add_segment(
("kTocMetaData", "kTocRawData", "kTocNewObjList"),
segment_objects_metadata(
channel_metadata("/'group'/'channel1'", TDS_TYPE_INT32, 2),
channel_metadata("/'group'/'channel2'", TDS_TYPE_INT32, 2),
), "01 00 00 00"
"02 00 00 00"
"03 00 00 00"
"04 00 00 00")
test_file.add_segment(("kTocRawData", ), "", "05 00 00 00"
"06 00 00 00"
"07 00 00 00"
"08 00 00 00")
expected_data = {
('group', 'channel1'): np.array([1, 2, 5, 6], dtype=np.int32),
('group', 'channel2'): np.array([3, 4, 7, 8], dtype=np.int32),
}
return test_file, expected_data
def segment_with_zero_data_length():
""" kTocRawData is set but data length is zero
"""
test_file = GeneratedFile()
test_file.add_segment(
("kTocMetaData", "kTocRawData", "kTocNewObjList"),
segment_objects_metadata(
channel_metadata("/'group'/'channel1'", TDS_TYPE_INT32, 2),
channel_metadata("/'group'/'channel2'", TDS_TYPE_INT32, 2),
), "01 00 00 00"
"02 00 00 00"
"03 00 00 00"
"04 00 00 00")
test_file.add_segment(
("kTocMetaData", "kTocRawData"),
segment_objects_metadata(
channel_metadata("/'group'/'channel1'", TDS_TYPE_INT32, 0),
channel_metadata("/'group'/'channel2'", TDS_TYPE_INT32, 0),
), "")
expected_data = {
('group', 'channel1'): np.array([1, 2], dtype=np.int32),
('group', 'channel2'): np.array([3, 4], dtype=np.int32),
}
return test_file, expected_data
