def test_read_arrays_no_data_but_dstype():
"""This is a slightly-different error path than read_arrays()"""
with pytest.raises(IOErr) as err:
io.read_arrays(Data2DInt)
assert str(err.value) == "no arrays found to be loaded"
def test_read_arrays_data1d():
dset = io.read_arrays([1, 2, 3], (4, 5, 6), np.asarray([0.1, 0.2, 0.1]))
assert isinstance(dset, Data1D)
assert dset.name == ''
assert dset.x == pytest.approx(np.asarray([1, 2, 3]))
assert dset.y == pytest.approx(np.asarray([4, 5, 6]))
assert dset.staterror == pytest.approx(np.asarray([0.1, 0.2, 0.1]))
assert dset.syserror is None
# Check it creates NumPy arrays
assert isinstance(dset.x, np.ndarray)
assert isinstance(dset.y, np.ndarray)
assert isinstance(dset.staterror, np.ndarray)
def test_read_arrays_data1d_combined():
arg = np.asarray([[1, 4, 0.2, 0.1], [2, 5, 0.3, 0.05]])
dset = io.read_arrays(arg)
assert isinstance(dset, Data1D)
assert dset.name == ''
assert dset.x == pytest.approx(np.asarray([1, 2]))
assert dset.y == pytest.approx(np.asarray([4, 5]))
assert dset.staterror == pytest.approx(np.asarray([0.2, 0.3]))
assert dset.syserror == pytest.approx(np.asarray([0.1, 0.05]))
# Check it creates NumPy arrays
assert isinstance(dset.x, np.ndarray)
assert isinstance(dset.y, np.ndarray)
assert isinstance(dset.staterror, np.ndarray)
assert isinstance(dset.syserror, np.ndarray)
def test_read_arrays_not_an_array_type():
with pytest.raises(IOErr) as err:
io.read_arrays("foo")
assert str(err.value) == "'foo' must be a Numpy array, list, or tuple"
def test_read_arrays_not_enough_data(dstype, dname, nargs):
with pytest.raises(TypeError) as err:
io.read_arrays([1, 2, 3], dstype)
assert str(err.value) == f"data set '{dname}' takes at least {nargs} args"
def test_read_arrays_no_data():
"""This can run even with the dummy backend"""
with pytest.raises(IOErr) as err:
io.read_arrays()
assert str(err.value) == "no arrays found to be loaded"