Review test functions and group test cases

[bobleesj]

Problem

Originally posted by @sbillinge in #255 (comment)

The majority of code has been listing "cases", but we can further scale our tests by grouping them:

From:

@pytest.mark.parametrize(
 "org_do_args, target_do_args, scale_inputs, expected",
 [
 # Case 1: same x-array and y-array, check offset
 (
{
 "xarray": np.array([10, 15, 25, 30, 60, 140]),
 "yarray": np.array([2, 3, 4, 5, 6, 7]),
 "xtype": "tth",
 "wavelength": 2 * np.pi,
 },
{
 "xarray": np.array([10, 15, 25, 30, 60, 140]),
 "yarray": np.array([2, 3, 4, 5, 6, 7]),
 "xtype": "tth",
 "wavelength": 2 * np.pi,
 },
{
 "q": None,
 "tth": 60,
 "d": None,
 "offset": 2.1,
 },
{"xtype": "tth", "yarray": np.array([4.1, 5.1, 6.1, 7.1, 8.1, 9.1])},
 ),
 # Case 2: same length x-arrays with exact x-value match
 (
{
 "xarray": np.array([10, 15, 25, 30, 60, 140]),
 "yarray": np.array([10, 20, 25, 30, 60, 100]),
 "xtype": "tth",
 "wavelength": 2 * np.pi,
 },
{
 "xarray": np.array([10, 20, 25, 30, 60, 140]),
 "yarray": np.array([2, 3, 4, 5, 6, 7]),
 "xtype": "tth",
 "wavelength": 2 * np.pi,
 },
{
 "q": None,
 "tth": 60,
 "d": None,
 "offset": 0,
 },
{"xtype": "tth", "yarray": np.array([1, 2, 2.5, 3, 6, 10])},
 ),
 # Case 3: same length x-arrays with approximate x-value match
 (
{
 "xarray": np.array([0.12, 0.24, 0.31, 0.4]),
 "yarray": np.array([10, 20, 40, 60]),
 "xtype": "q",
 "wavelength": 2 * np.pi,
 },
{
 "xarray": np.array([0.14, 0.24, 0.31, 0.4]),
 "yarray": np.array([1, 3, 4, 5]),
 "xtype": "q",
 "wavelength": 2 * np.pi,
 },
{
 "q": 0.1,
 "tth": None,
 "d": None,
 "offset": 0,
 },
{"xtype": "q", "yarray": np.array([1, 2, 4, 6])},
 ),
 # Case 4: different x-array lengths with approximate x-value match
 (
{
 "xarray": np.array([10, 25, 30.1, 40.2, 61, 120, 140]),
 "yarray": np.array([10, 20, 30, 40, 50, 60, 100]),
 "xtype": "tth",
 "wavelength": 2 * np.pi,
 },
{
 "xarray": np.array([20, 25.5, 32, 45, 50, 62, 100, 125, 140]),
 "yarray": np.array([1.1, 2, 3, 3.5, 4, 5, 10, 12, 13]),
 "xtype": "tth",
 "wavelength": 2 * np.pi,
 },
{
 "q": None,
 "tth": 60,
 "d": None,
 "offset": 0,
 },
 # Case 5 Scaling factor is calculated at index = 4 (tth=61) for self and index = 5 for target (tth=62)
{"xtype": "tth", "yarray": np.array([1, 2, 3, 4, 5, 6, 10])},
 ),
 ],
)
...

To:

@pytest.mark.parametrize(
 "wavelength, q, expected_tth",
 [
 # Case 1: Allow empty arrays for q
 # 1. Empty q values, no wavelength, return empty arrays
 (None, np.empty((0)), np.empty((0))),
 # 2. Empty q values, wavelength specified, return empty arrays
 (4 * np.pi, np.empty((0)), np.empty(0)),
 
 # Case 2: Allow wavelength to be missing.
 # Valid q values, no wavelength, return index array
 (
 None,
 np.array([0, 0.2, 0.4, 0.6, 0.8, 1]),
 np.array([0, 1, 2, 3, 4, 5]),
 ),

 # Case 3: Correctly specified q and wavelength
 # Expected tth values are 2*arcsin(q) in degrees
 (4 * np.pi, np.array([0, 1 / np.sqrt(2), 1.0]), np.array([0, 90.0, 180.0])),
 ],
)

Proposed solution

For all test functions diffpy.utils, review each test function and group test cases.

[bobleesj]

I think we could close this issue once #273 for test_diffraction_objects.py and #275 for test_transform.py are merged?

@sbillinge

[sbillinge]

closed as completed