"""
RocketLogger data file import tests.
Copyright (c) 2016-2020, ETH Zurich, Computer Engineering Group
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
* Redistributions of source code must retain the above copyright notice, this
list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above copyright notice,
this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution.
* Neither the name of the copyright holder nor the names of its
contributors may be used to endorse or promote products derived from
this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
"""
from rocketlogger.data import (
RocketLoggerData,
RocketLoggerDataError,
RocketLoggerDataWarning,
RocketLoggerFileError,
_ROCKETLOGGER_ADC_CLOCK_SCALE,
)
import os.path
from unittest import TestCase
import unittest
import numpy as np
import rocketlogger.data as rld
import os
if os.environ.get("MATPLOTLIB_AVAILABLE") == "true":
import matplotlib.pyplot as plt
if os.environ.get("PANDAS_AVAILABLE") == "true":
import pandas as pd
_TEST_FILE_DIR = "data"
_FULL_TEST_FILE = os.path.join(_TEST_FILE_DIR, "test_full.rld")
_SINGLE_BLOCK_FILE = os.path.join(_TEST_FILE_DIR, "test_single_block.rld")
_MIN_BLOCK_SIZE_FILE = os.path.join(_TEST_FILE_DIR, "test_min_block_size.rld")
_ANALOG_TEST_FILE = os.path.join(_TEST_FILE_DIR, "test_analog_only.rld")
_HIGH_CURRENT_TEST_FILE = os.path.join(_TEST_FILE_DIR, "test_high_current.rld")
_STEPS_TEST_FILE = os.path.join(_TEST_FILE_DIR, "test_steps.rld")
_INCOMPATIBLE_TEST_FILE = os.path.join(_TEST_FILE_DIR, "test_unsupported.rld")
_INEXISTENT_TEST_FILE = os.path.join(_TEST_FILE_DIR, "test_inexistent.rld")
_SINGLE_TEST_FILE = os.path.join(_TEST_FILE_DIR, "test_v3_only.rld")
_HEADER_UNALIGNED_TEST_FILE = os.path.join(_TEST_FILE_DIR, "test_header_unaligned.rld")
_TRUNCATED_TEST_FILE = os.path.join(_TEST_FILE_DIR, "test_truncated.rld")
_SPLIT_TEST_FILE = os.path.join(_TEST_FILE_DIR, "test_split.rld")
_NON_SPLIT_TEST_FILE = os.path.join(_TEST_FILE_DIR, "test_non_split.rld")
_SPLIT_TRUNCATED_TEST_FILE = os.path.join(_TEST_FILE_DIR, "test_split_truncated.rld")
_TEMP_FILE = os.path.join(_TEST_FILE_DIR, "temp_data.rld")
def _file_copy_byte_flipped(file_in, file_out, offset, mask=0xA5):
data = np.fromfile(file_in, np.uint8)
data[offset] = data[offset] ^ mask
data.tofile(
file_out,
)
[docs]class TestDecimation(TestCase):
[docs] def test_binary_decimation(self):
data_in = np.ones((100))
data_in[0:2:100] = 0
data_ref = np.ones((10))
data_out = rld._decimate_binary(data_in, 10)
self.assertAlmostEqual(sum(abs(data_out - data_ref)), 0)
[docs] def test_min_decimation(self):
data_in = np.ones((100))
data_in[0:100:10] = 0
data_ref = np.zeros((10))
data_out = rld._decimate_min(data_in, 10)
self.assertEqual(sum(abs(data_out - data_ref)), 0)
[docs] def test_max_decimation(self):
data_in = np.zeros((100))
data_in[0:100:10] = 1
data_ref = np.ones((10))
data_out = rld._decimate_max(data_in, 10)
self.assertAlmostEqual(sum(abs(data_out - data_ref)), 0)
[docs] def test_mean_decimation(self):
data_in = np.arange(0, 100)
data_ref = 4.5 + np.arange(0, 100, 10)
data_out = rld._decimate_mean(data_in, 10)
self.assertAlmostEqual(sum(abs(data_out - data_ref)), 0)
[docs]class TestFileImport(TestCase):
[docs] def test_normal(self):
data = RocketLoggerData(_FULL_TEST_FILE)
self.assertEqual(data.get_data().shape, (5000, 16))
[docs] def test_no_file(self):
with self.assertRaisesRegex(NotImplementedError, "data file creation"):
RocketLoggerData()
[docs] def test_inexistent_file(self):
with self.assertRaises(FileNotFoundError):
RocketLoggerData(_INEXISTENT_TEST_FILE)
[docs] def test_overload_existing(self):
data = RocketLoggerData(_FULL_TEST_FILE)
with self.assertRaisesRegex(RocketLoggerDataError, "file is already loaded"):
data.load_file(_FULL_TEST_FILE)
[docs] def test_with_decimation(self):
data = RocketLoggerData(_FULL_TEST_FILE, decimation_factor=10)
self.assertEqual(data._header["data_block_size"], 100)
[docs] def test_with_invalid_decimation(self):
with self.assertRaisesRegex(ValueError, "Decimation factor"):
RocketLoggerData(_FULL_TEST_FILE, decimation_factor=3)
[docs] def test_direct_import(self):
data = RocketLoggerData(_FULL_TEST_FILE, memory_mapped=False)
self.assertEqual(data.get_data("V1").shape, (5000, 1))
[docs] def test_direct_import_with_decimation(self):
data = RocketLoggerData(
_FULL_TEST_FILE, memory_mapped=False, decimation_factor=10
)
self.assertEqual(data._header["data_block_size"], 100)
self.assertEqual(data._header["sample_count"], 500)
self.assertEqual(data._header["sample_rate"], 100)
self.assertEqual(data.get_data("V1").shape, (500, 1))
[docs] def test_direct_vs_memory_mapped(self):
data_mm = RocketLoggerData(_FULL_TEST_FILE, memory_mapped=True)
data_ff = RocketLoggerData(_FULL_TEST_FILE, memory_mapped=False)
self.assertEqual(data_mm._header, data_ff._header)
self.assertEqual(len(data_mm._data), len(data_ff._data))
for i in range(len(data_mm._data)):
arrays_equal = np.array_equal(data_mm._data[i], data_ff._data[i])
self.assertTrue(arrays_equal)
[docs] def test_single_block_import(self):
data = RocketLoggerData(_SINGLE_BLOCK_FILE, memory_mapped=False)
self.assertEqual(data._header["data_block_count"], 1)
self.assertEqual(data.get_data("V1").shape, (1000, 1))
[docs] def test_min_block_size_import(self):
data = RocketLoggerData(_MIN_BLOCK_SIZE_FILE, memory_mapped=False)
self.assertEqual(data._header["data_block_size"], 1)
self.assertEqual(data.get_data("V1").shape, (5, 1))
[docs] @classmethod
def tearDownClass(cls):
try:
os.remove(_TEMP_FILE)
except FileNotFoundError:
pass
[docs]class TestFullFile(TestCase):
[docs] def setUp(self):
self.data = RocketLoggerData(_FULL_TEST_FILE)
[docs] def tearDown(self):
del self.data
[docs] def test_load(self):
self.assertIsInstance(self.data, RocketLoggerData)
[docs] def test_data_size(self):
self.assertEqual(self.data.get_data().shape, (5000, 16))
[docs] def test_channel_names(self):
self.assertEqual(
self.data.get_channel_names(),
sorted(
[
"DI1",
"DI2",
"DI3",
"DI4",
"DI5",
"DI6",
"I1L_valid",
"I2L_valid",
"V1",
"V2",
"V3",
"V4",
"I1L",
"I1H",
"I2L",
"I2H",
]
),
)
[docs]class TestSingleChannelFile(TestCase):
[docs] def setUp(self):
self.data = RocketLoggerData(_SINGLE_TEST_FILE)
[docs] def tearDown(self):
del self.data
[docs] def test_load(self):
self.assertIsInstance(self.data, RocketLoggerData)
[docs] def test_data_size(self):
self.assertEqual(self.data.get_data().shape, (5000, 1))
[docs] def test_channel_names(self):
self.assertEqual(self.data.get_channel_names(), ["V3"])
[docs]class TestJoinFile(TestCase):
[docs] def setUp(self):
self.data = RocketLoggerData(_SPLIT_TEST_FILE)
[docs] def tearDown(self):
del self.data
[docs] def test_load(self):
self.assertIsInstance(self.data, RocketLoggerData)
[docs] def test_data_size(self):
self.assertEqual(self.data.get_data().shape, (3 * 128000, 16))
[docs] def test_channel_names(self):
self.assertEqual(
self.data.get_channel_names(),
sorted(
[
"DI1",
"DI2",
"DI3",
"DI4",
"DI5",
"DI6",
"I1L_valid",
"I2L_valid",
"V1",
"V2",
"V3",
"V4",
"I1L",
"I1H",
"I2L",
"I2H",
]
),
)
[docs]class TestJoinMissmatch(TestCase):
[docs] def test_exclude_all(self):
with self.assertRaisesRegex(RocketLoggerDataError, "header not matching at field: start_time"):
RocketLoggerData(_NON_SPLIT_TEST_FILE)
[docs]class TestJoinExclude(TestCase):
[docs] def test_exclude_all(self):
with self.assertRaisesRegex(RocketLoggerDataError, "Could not load valid data"):
RocketLoggerData(_SPLIT_TEST_FILE, exclude_part=np.arange(0, 3))
[docs] def test_exclude_non_join(self):
with self.assertRaisesRegex(ValueError, "exclude_part"):
RocketLoggerData(
_SPLIT_TEST_FILE, join_files=False, exclude_part=np.arange(0, 3)
)
[docs]class TestJoinExcludeFirst(TestCase):
[docs] def setUp(self):
self.full_reference = RocketLoggerData(_SPLIT_TEST_FILE)
self.data = RocketLoggerData(_SPLIT_TEST_FILE, exclude_part=0)
[docs] def tearDown(self):
del self.full_reference
del self.data
[docs] def test_load(self):
self.assertIsInstance(self.data, RocketLoggerData)
[docs] def test_data_values(self):
reference_range = np.arange(128000, 3 * 128000)
reference = self.full_reference.get_data()[reference_range]
self.assertTrue(np.array_equal(self.data.get_data(), reference))
[docs] def test_data_timestamp_monotonic(self):
reference_range = np.arange(2, 3 * 2)
reference = self.full_reference._timestamps_monotonic[reference_range]
self.assertTrue(np.array_equal(self.data._timestamps_monotonic, reference))
[docs] def test_data_timestamp_realtime(self):
reference_range = np.arange(2, 3 * 2)
reference = self.full_reference._timestamps_realtime[reference_range]
self.assertTrue(np.array_equal(self.data._timestamps_realtime, reference))
[docs]class TestJoinExcludeLast(TestCase):
[docs] def setUp(self):
self.full_reference = RocketLoggerData(_SPLIT_TEST_FILE)
self.data = RocketLoggerData(_SPLIT_TEST_FILE, exclude_part=2)
[docs] def tearDown(self):
del self.full_reference
del self.data
[docs] def test_load(self):
self.assertIsInstance(self.data, RocketLoggerData)
[docs] def test_data_values(self):
reference_range = np.arange(2 * 128000)
reference = self.full_reference.get_data()[reference_range]
self.assertTrue(np.array_equal(self.data.get_data(), reference))
[docs] def test_data_timestamp_monotonic(self):
reference_range = np.arange(2 * 2)
reference = self.full_reference._timestamps_monotonic[reference_range]
self.assertTrue(np.array_equal(self.data._timestamps_monotonic, reference))
[docs] def test_data_timestamp_realtime(self):
reference_range = np.arange(2 * 2)
reference = self.full_reference._timestamps_realtime[reference_range]
self.assertTrue(np.array_equal(self.data._timestamps_realtime, reference))
[docs]class TestJoinExcludeMultiple(TestCase):
[docs] def setUp(self):
self.full_reference = RocketLoggerData(_SPLIT_TEST_FILE)
self.data = RocketLoggerData(_SPLIT_TEST_FILE, exclude_part=[0, 2])
[docs] def tearDown(self):
del self.full_reference
del self.data
[docs] def test_load(self):
self.assertIsInstance(self.data, RocketLoggerData)
[docs] def test_data_values(self):
reference_range = np.arange(128000, 2 * 128000)
reference = self.full_reference.get_data()[reference_range]
self.assertTrue(np.array_equal(self.data.get_data(), reference))
[docs] def test_data_timestamp_monotonic(self):
reference_range = np.arange(2, 2 * 2)
reference = self.full_reference._timestamps_monotonic[reference_range]
self.assertTrue(np.array_equal(self.data._timestamps_monotonic, reference))
[docs] def test_data_timestamp_realtime(self):
reference_range = np.arange(2, 2 * 2)
reference = self.full_reference._timestamps_realtime[reference_range]
self.assertTrue(np.array_equal(self.data._timestamps_realtime, reference))
[docs]class TestJoinExcludeInt(TestCase):
[docs] def setUp(self):
self.full_reference = RocketLoggerData(_SPLIT_TEST_FILE)
self.data = RocketLoggerData(_SPLIT_TEST_FILE, exclude_part=1)
[docs] def tearDown(self):
del self.full_reference
del self.data
[docs] def test_load(self):
self.assertIsInstance(self.data, RocketLoggerData)
[docs] def test_data_values(self):
reference_range = np.concatenate(
(np.arange(128000), np.arange(2 * 128000, 3 * 128000))
)
reference = self.full_reference.get_data()[reference_range]
self.assertTrue(np.array_equal(self.data.get_data(), reference))
[docs] def test_data_timestamp_monotonic(self):
reference_range = np.concatenate((np.arange(2), np.arange(2 * 2, 3 * 2)))
reference = self.full_reference._timestamps_monotonic[reference_range]
self.assertTrue(np.array_equal(self.data._timestamps_monotonic, reference))
[docs] def test_data_timestamp_realtime(self):
reference_range = np.concatenate((np.arange(2), np.arange(2 * 2, 3 * 2)))
reference = self.full_reference._timestamps_realtime[reference_range]
self.assertTrue(np.array_equal(self.data._timestamps_realtime, reference))
[docs]class TestJoinExcludeList(TestCase):
[docs] def setUp(self):
self.full_reference = RocketLoggerData(_SPLIT_TEST_FILE)
self.data = RocketLoggerData(_SPLIT_TEST_FILE, exclude_part=[1])
[docs] def tearDown(self):
del self.full_reference
del self.data
[docs] def test_load(self):
self.assertIsInstance(self.data, RocketLoggerData)
[docs] def test_data_values(self):
reference_range = np.concatenate(
(np.arange(128000), np.arange(2 * 128000, 3 * 128000))
)
reference = self.full_reference.get_data()[reference_range]
self.assertTrue(np.array_equal(self.data.get_data(), reference))
[docs] def test_data_timestamp_monotonic(self):
reference_range = np.concatenate((np.arange(2), np.arange(2 * 2, 3 * 2)))
reference = self.full_reference._timestamps_monotonic[reference_range]
self.assertTrue(np.array_equal(self.data._timestamps_monotonic, reference))
[docs] def test_data_timestamp_realtime(self):
reference_range = np.concatenate((np.arange(2), np.arange(2 * 2, 3 * 2)))
reference = self.full_reference._timestamps_realtime[reference_range]
self.assertTrue(np.array_equal(self.data._timestamps_realtime, reference))
[docs]class TestJoinExcludeArray(TestCase):
[docs] def setUp(self):
self.full_reference = RocketLoggerData(_SPLIT_TEST_FILE)
self.data = RocketLoggerData(_SPLIT_TEST_FILE, exclude_part=np.arange(1, 2))
[docs] def tearDown(self):
del self.full_reference
del self.data
[docs] def test_load(self):
self.assertIsInstance(self.data, RocketLoggerData)
[docs] def test_data_values(self):
reference_range = np.concatenate(
(np.arange(128000), np.arange(2 * 128000, 3 * 128000))
)
reference = self.full_reference.get_data()[reference_range]
self.assertTrue(np.array_equal(self.data.get_data(), reference))
[docs] def test_data_timestamp_monotonic(self):
reference_range = np.concatenate((np.arange(2), np.arange(2 * 2, 3 * 2)))
reference = self.full_reference._timestamps_monotonic[reference_range]
self.assertTrue(np.array_equal(self.data._timestamps_monotonic, reference))
[docs] def test_data_timestamp_realtime(self):
reference_range = np.concatenate((np.arange(2), np.arange(2 * 2, 3 * 2)))
reference = self.full_reference._timestamps_realtime[reference_range]
self.assertTrue(np.array_equal(self.data._timestamps_realtime, reference))
[docs]class TestNoJoinFile(TestCase):
[docs] def setUp(self):
self.data = RocketLoggerData(_SPLIT_TEST_FILE, join_files=False)
[docs] def tearDown(self):
del self.data
[docs] def test_load(self):
self.assertIsInstance(self.data, RocketLoggerData)
[docs] def test_data_size(self):
self.assertEqual(self.data.get_data().shape, (128000, 16))
[docs] def test_channel_names(self):
self.assertEqual(
self.data.get_channel_names(),
sorted(
[
"DI1",
"DI2",
"DI3",
"DI4",
"DI5",
"DI6",
"I1L_valid",
"I2L_valid",
"V1",
"V2",
"V3",
"V4",
"I1L",
"I1H",
"I2L",
"I2H",
]
),
)
[docs]class TestRecoveryFile(TestCase):
[docs] def test_no_recovery(self):
with self.assertRaisesRegex(RocketLoggerDataError, "corrupt data: file size"):
RocketLoggerData(_TRUNCATED_TEST_FILE)
[docs] def test_with_decimation(self):
with self.assertWarnsRegex(RocketLoggerDataWarning, "corrupt data: recovered"):
data = RocketLoggerData(
_TRUNCATED_TEST_FILE, recovery=True, decimation_factor=10
)
self.assertEqual(data._header["data_block_size"], 100)
[docs] def test_with_invalid_decimation(self):
with self.assertRaisesRegex(ValueError, "Decimation factor"):
RocketLoggerData(_TRUNCATED_TEST_FILE, recovery=True, decimation_factor=3)
[docs] def test_direct_import(self):
with self.assertWarnsRegex(RocketLoggerDataWarning, "corrupt data: recovered"):
data = RocketLoggerData(
_TRUNCATED_TEST_FILE, recovery=True, memory_mapped=False
)
self.assertEqual(data.get_data("V3").shape, (4000, 1))
[docs] def test_direct_import_with_decimation(self):
with self.assertWarnsRegex(RocketLoggerDataWarning, "corrupt data: recovered"):
data = RocketLoggerData(
_TRUNCATED_TEST_FILE,
recovery=True,
memory_mapped=False,
decimation_factor=10,
)
self.assertEqual(data._header["data_block_size"], 100)
self.assertEqual(data._header["sample_count"], 400)
self.assertEqual(data._header["sample_rate"], 100)
self.assertEqual(data.get_data("V3").shape, (400, 1))
[docs]class TestRecoverySplitFile(TestCase):
[docs] def test_no_recovery(self):
with self.assertRaisesRegex(RocketLoggerDataError, "corrupt data: file size"):
RocketLoggerData(_SPLIT_TRUNCATED_TEST_FILE)
[docs] def test_with_decimation(self):
with self.assertWarnsRegex(RocketLoggerDataWarning, "corrupt data: recovered"):
data = RocketLoggerData(
_SPLIT_TRUNCATED_TEST_FILE, recovery=True, decimation_factor=10
)
self.assertEqual(data._header["data_block_size"], 6400)
[docs] def test_with_invalid_decimation(self):
with self.assertRaisesRegex(ValueError, "Decimation factor"):
RocketLoggerData(
_SPLIT_TRUNCATED_TEST_FILE, recovery=True, decimation_factor=3
)
[docs] def test_direct_import(self):
with self.assertWarnsRegex(RocketLoggerDataWarning, "corrupt data: recovered"):
data = RocketLoggerData(
_SPLIT_TRUNCATED_TEST_FILE, recovery=True, memory_mapped=False
)
self.assertEqual(data.get_data().shape, (3 * 64000, 16))
[docs] def test_direct_import_with_decimation(self):
with self.assertWarnsRegex(RocketLoggerDataWarning, "corrupt data: recovered"):
data = RocketLoggerData(
_SPLIT_TRUNCATED_TEST_FILE,
recovery=True,
memory_mapped=False,
decimation_factor=10,
)
self.assertEqual(data._header["data_block_size"], 6400)
self.assertEqual(data._header["sample_count"], 3 * 6400)
self.assertEqual(data._header["sample_rate"], 6400)
self.assertEqual(data.get_data().shape, (3 * 6400, 16))
[docs]class TestChannelHandling(TestCase):
[docs] def setUp(self):
self.data = RocketLoggerData(_FULL_TEST_FILE)
[docs] def tearDown(self):
del self.data
[docs] def test_get_single_channel_index(self):
index = self.data._get_channel_index("V1")
self.assertEqual(index, 10)
[docs] def test_get_invalid_channel_index(self):
temp = self.data._get_channel_index("A")
self.assertEqual(temp, None)
[docs] def test_get_channel_name(self):
name = self.data._get_channel_name(10)
self.assertEqual(name, "V1")
[docs] def test_get_channel_name_list(self):
names = self.data._get_channel_name([10, 11])
self.assertListEqual(names, ["V1", "V2"])
[docs] def test_channel_add(self):
channel_info = self.data._header["channels"][10].copy()
channel_info["name"] = "A1"
self.data.add_channel(
channel_info, np.ones_like(self.data.get_data("V1").squeeze())
)
self.assertTrue("A1" in self.data.get_channel_names())
[docs] def test_channel_add_binary(self):
channel_info = self.data._header["channels"][0].copy()
channel_info["name"] = "B1"
self.data.add_channel(
channel_info, np.ones_like(self.data.get_data("DI1").squeeze())
)
self.assertTrue("B1" in self.data.get_channel_names())
[docs] def test_channel_add_existing(self):
channel_info = self.data._header["channels"][10].copy()
with self.assertRaisesRegex(ValueError, "name already in use"):
self.data.add_channel(
channel_info, np.ones_like(self.data.get_data("V1").squeeze())
)
[docs] def test_channel_add_no_unit(self):
channel_info = self.data._header["channels"][10].copy()
del channel_info["unit_index"]
with self.assertRaisesRegex(ValueError, "unit not defined"):
self.data.add_channel(
channel_info, np.ones_like(self.data.get_data("V1").squeeze())
)
[docs] def test_channel_add_no_scale(self):
channel_info = self.data._header["channels"][10].copy()
del channel_info["scale"]
with self.assertRaisesRegex(ValueError, "scale not defined"):
self.data.add_channel(
channel_info, np.ones_like(self.data.get_data("V1").squeeze())
)
[docs] def test_channel_add_no_data_size(self):
channel_info = self.data._header["channels"][10].copy()
del channel_info["data_size"]
with self.assertRaisesRegex(ValueError, "size not defined"):
self.data.add_channel(
channel_info, np.ones_like(self.data.get_data("V1").squeeze())
)
[docs] def test_channel_add_no_name(self):
channel_info = self.data._header["channels"][10].copy()
del channel_info["name"]
with self.assertRaisesRegex(ValueError, "name undefined"):
self.data.add_channel(
channel_info, np.ones_like(self.data.get_data("V1").squeeze())
)
[docs] def test_channel_add_no_link(self):
channel_info = self.data._header["channels"][10].copy()
del channel_info["valid_link"]
with self.assertRaisesRegex(ValueError, "link not defined"):
self.data.add_channel(
channel_info, np.ones_like(self.data.get_data("V1").squeeze())
)
[docs] def test_channel_add_invalid_info(self):
with self.assertRaisesRegex(TypeError, "Channel info structure"):
self.data.add_channel(
None, np.ones_like(self.data.get_data("V1").squeeze())
)
[docs] def test_channel_add_invalid_unit(self):
channel_info = self.data._header["channels"][10].copy()
channel_info["name"] = "A1"
channel_info["unit_index"] = -1
with self.assertRaisesRegex(ValueError, "invalid channel unit"):
self.data.add_channel(
channel_info, np.ones_like(self.data.get_data("V1").squeeze())
)
[docs] def test_channel_add_invalid_scale(self):
channel_info = self.data._header["channels"][10].copy()
channel_info["name"] = "A1"
channel_info["scale"] = "micro"
with self.assertRaisesRegex(TypeError, "invalid scale"):
self.data.add_channel(
channel_info, np.ones_like(self.data.get_data("V1").squeeze())
)
[docs] def test_channel_add_invalid_data_size(self):
channel_info = self.data._header["channels"][10].copy()
channel_info["name"] = "A1"
channel_info["data_size"] = "int8"
with self.assertRaisesRegex(TypeError, "invalid data size"):
self.data.add_channel(
channel_info, np.ones_like(self.data.get_data("V1").squeeze())
)
[docs] def test_channel_add_invalid_link(self):
channel_info = self.data._header["channels"][10].copy()
channel_info["name"] = "A1"
channel_info["valid_link"] = None
with self.assertRaisesRegex(TypeError, "invalid link"):
self.data.add_channel(
channel_info, np.ones_like(self.data.get_data("V1").squeeze())
)
[docs] def test_channel_add_inexistent_link(self):
channel_info = self.data._header["channels"][10].copy()
channel_info["name"] = "A1"
channel_info["valid_link"] = len(self.data._header["channels"])
with self.assertRaisesRegex(ValueError, "invalid link"):
self.data.add_channel(
channel_info, np.ones_like(self.data.get_data("V1").squeeze())
)
[docs] def test_channel_add_invalid_name(self):
channel_info = self.data._header["channels"][10].copy()
channel_info["name"] = 100
with self.assertRaisesRegex(TypeError, "invalid name"):
self.data.add_channel(
channel_info, np.ones_like(self.data.get_data("V1").squeeze())
)
[docs] def test_channel_add_overlength_name(self):
channel_info = self.data._header["channels"][10].copy()
channel_info["name"] = "over_length_channel_name"
with self.assertRaisesRegex(ValueError, "name too long"):
self.data.add_channel(
channel_info, np.ones_like(self.data.get_data("V1").squeeze())
)
[docs] def test_channel_remove(self):
self.data.remove_channel("V4")
self.assertFalse("V4" in self.data.get_channel_names())
[docs] def test_channel_add_remove(self):
channel_info = self.data._header["channels"][10].copy()
channel_info["name"] = "A1"
self.data.add_channel(
channel_info, np.ones_like(self.data.get_data("V1").squeeze())
)
self.assertTrue("A1" in self.data.get_channel_names())
self.data.remove_channel("A1")
self.assertFalse("A1" in self.data.get_channel_names())
[docs] def test_channel_remove_inexistent(self):
with self.assertRaisesRegex(KeyError, "not found"):
self.data.remove_channel("A")
[docs]class TestChannelMerge(TestCase):
[docs] def test_channel_names(self):
data = RocketLoggerData(_FULL_TEST_FILE)
self.assertEqual(
data.get_channel_names(),
sorted(
[
"DI1",
"DI2",
"DI3",
"DI4",
"DI5",
"DI6",
"I1L_valid",
"I2L_valid",
"V1",
"V2",
"V3",
"V4",
"I1L",
"I1H",
"I2L",
"I2H",
]
),
)
[docs] def test_merge_drop_channel_names(self):
data = RocketLoggerData(_FULL_TEST_FILE)
data.merge_channels(keep_channels=False)
self.assertEqual(
data.get_channel_names(),
sorted(
[
"DI1",
"DI2",
"DI3",
"DI4",
"DI5",
"DI6",
"V1",
"V2",
"V3",
"V4",
"I1",
"I2",
]
),
)
[docs] def test_merge_keep_channel_names(self):
data = RocketLoggerData(_FULL_TEST_FILE)
data.merge_channels(keep_channels=True)
self.assertEqual(
data.get_channel_names(),
sorted(
[
"DI1",
"DI2",
"DI3",
"DI4",
"DI5",
"DI6",
"I1L_valid",
"I2L_valid",
"V1",
"V2",
"V3",
"V4",
"I1L",
"I1H",
"I1",
"I2L",
"I2H",
"I2",
]
),
)
[docs] def test_merge_drop_merge_again(self):
data = RocketLoggerData(_FULL_TEST_FILE)
data.merge_channels(keep_channels=False)
with self.assertWarnsRegex(RocketLoggerDataWarning, "No channels found"):
data.merge_channels()
[docs] def test_merge_keep_merge_again(self):
data = RocketLoggerData(_FULL_TEST_FILE)
data.merge_channels(keep_channels=True)
with self.assertRaisesRegex(RocketLoggerDataError, "already in use"):
data.merge_channels()
[docs] def test_merge_inexistent_channels(self):
data = RocketLoggerData(_SINGLE_TEST_FILE)
with self.assertWarnsRegex(RocketLoggerDataWarning, "No channels found"):
data.merge_channels(keep_channels=False)
[docs] def test_merge_channel_count(self):
data = RocketLoggerData(_FULL_TEST_FILE)
self.assertEqual(len(data._header["channels"]), 16)
data.merge_channels(keep_channels=False)
self.assertEqual(len(data._header["channels"]), 12)
[docs] def test_merge_keep_channel_count(self):
data = RocketLoggerData(_FULL_TEST_FILE)
self.assertEqual(len(data._header["channels"]), 16)
data.merge_channels(keep_channels=True)
self.assertEqual(len(data._header["channels"]), 18)
[docs] def test_merge_calculation_overflow(self):
data = RocketLoggerData(_HIGH_CURRENT_TEST_FILE)
# manual merge with large data type
ch_data = data.get_data(["I2L", "I2H"])
ch_valid = data.get_data("I2L_valid").flatten()
ch_merged = ch_valid * ch_data[:, 0] + (1 - ch_valid) * ch_data[:, 1]
data.merge_channels(keep_channels=False)
self.assertAlmostEqual(sum(abs(data.get_data("I2").flatten() - ch_merged)), 0)
[docs] def test_merge_keep_calculation_overflow(self):
data = RocketLoggerData(_HIGH_CURRENT_TEST_FILE)
# manual merge with large data type
ch_data = data.get_data(["I2L", "I2H"])
ch_valid = data.get_data("I2L_valid").flatten()
ch_merged = ch_valid * ch_data[:, 0] + (1 - ch_valid) * ch_data[:, 1]
data.merge_channels(keep_channels=True)
self.assertAlmostEqual(sum(abs(data.get_data("I2").flatten() - ch_merged)), 0)
[docs]class TestDataHandling(TestCase):
[docs] def setUp(self):
self.data = RocketLoggerData(_FULL_TEST_FILE)
[docs] def tearDown(self):
del self.data
[docs] def test_load(self):
self.assertIsInstance(self.data, RocketLoggerData)
[docs] def test_header_dict(self):
temp = self.data.get_header()
header = {
"data_block_count": 5,
"data_block_size": 1000,
"file_version": 2,
"mac_address": "12:34:56:78:90:ab",
"sample_count": 5000,
"sample_rate": 1000,
"start_time": np.datetime64("2017-05-10T09:05:17.438817080"),
}
self.assertDictEqual(temp, header)
[docs] def test_get_single_channel(self):
temp = self.data.get_data("V1")
self.assertEqual(temp.shape[1], 1)
[docs] def test_get_invalid_channel(self):
with self.assertRaisesRegex(KeyError, "not found"):
self.data.get_data("A")
[docs] def test_get_all_channels(self):
temp = self.data.get_data("all")
self.assertEqual(temp.shape[1], len(self.data.get_channel_names()))
[docs] def test_get_set_of_channels(self):
channel_names = ["DI1", "DI3", "I1L_valid", "V1", "V3", "I1L"]
temp = self.data.get_data(channel_names)
self.assertEqual(temp.shape[1], len(channel_names))
[docs] def test_get_single_channel_unit(self):
temp = self.data.get_unit("V1")
self.assertListEqual(temp, ["voltage"])
[docs] def test_get_invalid_channel_unit(self):
with self.assertRaisesRegex(KeyError, "not found"):
self.data.get_unit("A")
[docs] def test_get_all_channels_unit(self):
temp = self.data.get_unit("all")
channel_units = (
["binary"] * 6
+ (["current"] * 2 + ["data valid (binary)"]) * 2
+ ["voltage"] * 4
)
self.assertListEqual(temp, channel_units)
[docs] def test_get_set_of_channels_unit(self):
channel_names = ["DI1", "DI3", "I1L_valid", "V1", "V3", "I1L"]
channel_units = [
"binary",
"binary",
"data valid (binary)",
"voltage",
"voltage",
"current",
]
temp = self.data.get_unit(channel_names)
self.assertListEqual(temp, channel_units)
[docs] def test_get_single_channel_validity(self):
temp = self.data.get_validity("V1")
self.assertEqual(temp.shape[1], 1)
self.assertTrue(np.all(temp))
[docs] def test_get_invalid_channel_validity(self):
with self.assertRaisesRegex(KeyError, "not found"):
self.data.get_validity("A")
[docs] def test_get_all_channels_validity(self):
temp = self.data.get_validity("all")
self.assertEqual(temp.shape[1], len(self.data.get_channel_names()))
[docs] def test_get_set_of_channels_validity(self):
channel_names = ["DI1", "DI3", "I1L_valid", "V1", "V3", "I1L"]
temp = self.data.get_validity(channel_names)
self.assertEqual(temp.shape[1], len(channel_names))
[docs] def test_get_time_default(self):
temp = self.data.get_time()
self.assertEqual(temp.shape[0], self.data._header["sample_count"])
self.assertIsInstance(temp[0], float)
[docs] def test_get_time_relative(self):
temp = self.data.get_time(time_reference="relative")
self.assertEqual(temp.shape[0], self.data._header["sample_count"])
self.assertIsInstance(temp[0], float)
[docs] def test_get_time_absolute_local(self):
temp = self.data.get_time(time_reference="local")
self.assertEqual(temp.shape[0], self.data._header["sample_count"])
self.assertEqual(temp.dtype, np.dtype("datetime64[ns]"))
[docs] def test_get_time_absolute_network(self):
temp = self.data.get_time(time_reference="network")
self.assertEqual(temp.shape[0], self.data._header["sample_count"])
self.assertEqual(temp.dtype, np.dtype("datetime64[ns]"))
[docs] def test_get_time_invalid_reference(self):
with self.assertRaisesRegex(ValueError, "Time reference"):
self.data.get_time(time_reference="invalid")
[docs] def test_get_time_relative_scaling(self):
temp = self.data.get_time(time_reference="relative")
dtemp = np.diff(temp).mean()
dt = 1 / _ROCKETLOGGER_ADC_CLOCK_SCALE / self.data.get_header()["sample_rate"]
self.assertAlmostEqual(dtemp / dt, 1)
[docs] def test_get_time_absolute_local_scaling(self):
temp = self.data.get_time(time_reference="local")
dtemp = np.diff(temp).mean()
dt = (
np.timedelta64(10 ** 9, "ns")
/ _ROCKETLOGGER_ADC_CLOCK_SCALE
/ self.data.get_header()["sample_rate"]
)
self.assertAlmostEqual(dtemp / dt, 1, places=4)
[docs] def test_get_time_absolute_network_scaling(self):
temp = self.data.get_time(time_reference="network")
dtemp = np.diff(temp).mean()
dt = (
np.timedelta64(10 ** 9, "ns")
/ _ROCKETLOGGER_ADC_CLOCK_SCALE
/ self.data.get_header()["sample_rate"]
)
self.assertAlmostEqual(dtemp / dt, 1, places=4)
[docs] def test_get_filename(self):
temp = self.data.get_filename()
self.assertEqual(temp, os.path.abspath(_FULL_TEST_FILE))
[docs]@unittest.skipUnless(
os.environ.get("PANDAS_AVAILABLE") == "true", "requires optional pandas dependency"
)
class TestDataframe(TestCase):
[docs] def setUp(self):
self.data = RocketLoggerData(_FULL_TEST_FILE)
[docs] def tearDown(self):
del self.data
[docs] def test_load(self):
self.assertIsInstance(self.data, RocketLoggerData)
[docs] def test_get_dataframe(self):
temp = self.data.get_dataframe()
self.assertIsInstance(temp, pd.DataFrame)
self.assertEqual(temp.shape[1], len(self.data.get_channel_names()))
self.assertListEqual(list(temp.columns), self.data.get_channel_names())
[docs] def test_get_single_channel(self):
temp = self.data.get_dataframe("V1")
self.assertEqual(temp.shape[1], 1)
self.assertListEqual(list(temp.columns), (["V1"]))
[docs] def test_get_invalid_channel(self):
with self.assertRaisesRegex(KeyError, "not found"):
self.data.get_dataframe("A")
[docs] def test_get_all_channels(self):
temp = self.data.get_dataframe("all")
self.assertIsInstance(temp, pd.DataFrame)
self.assertEqual(temp.shape[1], len(self.data.get_channel_names()))
self.assertListEqual(list(temp.columns), self.data.get_channel_names())
[docs] def test_get_set_of_channels(self):
channel_names = ["DI1", "DI3", "I1L_valid", "V1", "V3", "I1L"]
temp = self.data.get_dataframe(channel_names)
self.assertIsInstance(temp, pd.DataFrame)
self.assertEqual(temp.shape[1], len(channel_names))
self.assertListEqual(list(temp.columns), channel_names)
[docs] def test_get_default_time(self):
temp = self.data.get_dataframe()
index = temp.index
self.assertIsInstance(temp, pd.DataFrame)
self.assertEqual(temp.shape[0], self.data._header["sample_count"])
self.assertEqual(index.shape[0], self.data._header["sample_count"])
self.assertIsInstance(index[0], float)
[docs] def test_get_relative_time(self):
temp = self.data.get_dataframe(time_reference="relative")
index = temp.index
self.assertIsInstance(temp, pd.DataFrame)
self.assertEqual(temp.shape[0], self.data._header["sample_count"])
self.assertEqual(index.shape[0], self.data._header["sample_count"])
self.assertIsInstance(index[0], float)
[docs] def test_get_absolute_local_time(self):
temp = self.data.get_dataframe(time_reference="local")
index = temp.index
self.assertIsInstance(temp, pd.DataFrame)
self.assertEqual(temp.shape[0], self.data._header["sample_count"])
self.assertEqual(index.shape[0], self.data._header["sample_count"])
self.assertEqual(index.dtype, np.dtype("datetime64[ns]"))
[docs] def test_get_absolute_network_time(self):
temp = self.data.get_dataframe(time_reference="network")
index = temp.index
self.assertIsInstance(temp, pd.DataFrame)
self.assertEqual(temp.shape[0], self.data._header["sample_count"])
self.assertEqual(index.shape[0], self.data._header["sample_count"])
self.assertEqual(index.dtype, np.dtype("datetime64[ns]"))
[docs]@unittest.skipUnless(
os.environ.get("MATPLOTLIB_AVAILABLE") == "true",
"requires optional matplotlib dependency",
)
class TestDataPlot(TestCase):
[docs] def setUp(self):
self.data = RocketLoggerData(_STEPS_TEST_FILE)
[docs] def tearDown(self):
plt.close("all")
del self.data
[docs] def test_load(self):
self.assertIsInstance(self.data, RocketLoggerData)
[docs] def test_plot_all(self):
self.data.plot()
[docs] def test_plot_merged(self):
self.data.merge_channels()
self.data.plot()
[docs] def test_plot_invalid(self):
with self.assertRaisesRegex(KeyError, "not found"):
self.data.plot(["A"])
[docs] def test_plot_voltage(self):
self.data.plot(["voltages"])
[docs] def test_plot_current(self):
self.data.plot(["currents"])
[docs] def test_plot_digital(self):
self.data.plot(["digital"])
[docs] def test_plot_single(self):
self.data.plot("V1")
[docs] def test_plot_multi_single(self):
self.data.plot(["V1", "I1L", "DI1"])
[docs]@unittest.skipUnless(
os.environ.get("MATPLOTLIB_AVAILABLE") == "true",
"requires optional matplotlib dependency",
)
class TestDataPlotDecimate(TestCase):
[docs] def setUp(self):
self.data = RocketLoggerData(_STEPS_TEST_FILE, decimation_factor=10)
[docs] def tearDown(self):
plt.close("all")
del self.data
[docs] def test_load(self):
self.assertIsInstance(self.data, RocketLoggerData)
[docs] def test_plot_all(self):
self.data.plot()
[docs] def test_plot_merged(self):
self.data.merge_channels()
self.data.plot()
[docs] def test_plot_invalid(self):
with self.assertRaisesRegex(KeyError, "not found"):
self.data.plot(["A"])
[docs] def test_plot_voltage(self):
self.data.plot(["voltages"])
[docs] def test_plot_current(self):
self.data.plot(["currents"])
[docs] def test_plot_digital(self):
self.data.plot(["digital"])
[docs] def test_plot_single(self):
self.data.plot("V1")
[docs] def test_plot_multi_single(self):
self.data.plot(["V1", "I1L", "DI1"])