Refactor test_select_by_time function

[DaniBodor]

Currently just one long code block. It feels like this could be made more modular in a nice loop structure, but I couldn't think of the right way of doing it (and ChatGPT didnt either).

eitprocessing/tests/test_sequence.py

Lines 250 to 326 in 2702352

	def test_select_by_time(
	draeger_data2: DraegerSequence,
	):
	# TODO (#82): this function is kinda ugly. Would be nice to refactor it
	# but I am struggling to think of a logical way to loop through.
	data = draeger_data2
	t22 = 55825.268
	t52 = 55826.768
	ms = 0.001
	# test illegal
	with pytest.warns(UserWarning):
	_ = data.select_by_time()
	with pytest.warns(UserWarning):
	_ = data.select_by_time(None, None)
	with pytest.warns(UserWarning):
	_ = data.select_by_time(None)
	with pytest.warns(UserWarning):
	_ = data.select_by_time(end = None)
	# test start only
	start_slices = [
	# (time, expectation if inclusive=True, expectation if inclusive=False)
	(t22, 22, 23),
	(t22 - ms, 22, 22),
	(t22 + ms, 23, 23),
	]
	for start_slicing in start_slices:
	sliced = data.select_by_time(
	start = start_slicing[0], start_inclusive=True)
	assert len(sliced) == len(data) - start_slicing[1]
	sliced = data.select_by_time(start = start_slicing[0], start_inclusive=False)
	assert len(sliced) == len(data) - start_slicing[2]
	# test end only
	end_slices = [
	# (time, expectation if inclusive=True, expectation if inclusive=False)
	(t52, 52, 51),
	(t52 - ms, 51, 51),
	(t52 + ms, 52, 52),
	]
	for end_slicing in end_slices:
	sliced = data.select_by_time(end = end_slicing[0], end_inclusive=True)
	assert len(sliced) == end_slicing[1]
	sliced = data.select_by_time(end = end_slicing[0], end_inclusive=False)
	assert len(sliced) == end_slicing[2]
	# test start and end
	for start_slicing in start_slices:
	for end_slicing in end_slices:
	# True/True
	sliced = data.select_by_time(start = start_slicing[0],
	end = end_slicing[0],
	start_inclusive=True,
	end_inclusive=True)
	assert len(sliced) == end_slicing[1]-start_slicing[1]
	# False/True
	sliced = data.select_by_time(start = start_slicing[0],
	end = end_slicing[0],
	start_inclusive=False,
	end_inclusive=True)
	assert len(sliced) == end_slicing[1]-start_slicing[2]
	# True/False
	sliced = data.select_by_time(start = start_slicing[0],
	end = end_slicing[0],
	start_inclusive=True,
	end_inclusive=False)
	assert len(sliced) == end_slicing[2]-start_slicing[1]
	# False/False
	sliced = data.select_by_time(start = start_slicing[0],
	end = end_slicing[0],
	start_inclusive=False,
	end_inclusive=False)
	assert len(sliced) == end_slicing[2]-start_slicing[2]