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General validator function for checking dimensions and coordinates (#294
) * replace time dim validator with more generic validator * constrain kinematic functions to cartesian coordinates * renamed new validator to validate_dims_coords * add examples in validator docstring * unit tests for the new validator * Apply suggestions from code review do note validate x,y space coordinates specifically. Co-authored-by: Chang Huan Lo <[email protected]> * reuse fixture valid_poses_dataset_uniform_linear_motion * combine two unit tests into one * expose public `compute_time_derivative` function * Refactor test * Update refs to `compute_time_derivative` --------- Co-authored-by: Chang Huan Lo <[email protected]>
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,61 @@ | ||
| """Validators for data arrays.""" | ||
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| import xarray as xr | ||
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| from movement.utils.logging import log_error | ||
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| def validate_dims_coords( | ||
| data: xr.DataArray, required_dim_coords: dict | ||
| ) -> None: | ||
| """Validate dimensions and coordinates in a data array. | ||
| This function raises a ValueError if the specified dimensions and | ||
| coordinates are not present in the input data array. | ||
| Parameters | ||
| ---------- | ||
| data : xarray.DataArray | ||
| The input data array to validate. | ||
| required_dim_coords : dict | ||
| A dictionary of required dimensions and their corresponding | ||
| coordinate values. If you don't need to specify any | ||
| coordinate values, you can pass an empty list. | ||
| Examples | ||
| -------- | ||
| Validate that a data array contains the dimension 'time'. No specific | ||
| coordinates are required. | ||
| >>> validate_dims_coords(data, {"time": []}) | ||
| Validate that a data array contains the dimensions 'time' and 'space', | ||
| and that the 'space' dimension contains the coordinates 'x' and 'y'. | ||
| >>> validate_dims_coords(data, {"time": [], "space": ["x", "y"]}) | ||
| Raises | ||
| ------ | ||
| ValueError | ||
| If the input data does not contain the required dimension(s) | ||
| and/or the required coordinate(s). | ||
| """ | ||
| missing_dims = [dim for dim in required_dim_coords if dim not in data.dims] | ||
| error_message = "" | ||
| if missing_dims: | ||
| error_message += ( | ||
| f"Input data must contain {missing_dims} as dimensions.\n" | ||
| ) | ||
| missing_coords = [] | ||
| for dim, coords in required_dim_coords.items(): | ||
| missing_coords = [ | ||
| coord for coord in coords if coord not in data.coords.get(dim, []) | ||
| ] | ||
| if missing_coords: | ||
| error_message += ( | ||
| "Input data must contain " | ||
| f"{missing_coords} in the '{dim}' coordinates." | ||
| ) | ||
| if error_message: | ||
| raise log_error(ValueError, error_message) |
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,56 @@ | ||
| import re | ||
| from contextlib import nullcontext as does_not_raise | ||
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| import pytest | ||
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| from movement.validators.arrays import validate_dims_coords | ||
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| def expect_value_error_with_message(error_msg): | ||
| """Expect a ValueError with the specified error message.""" | ||
| return pytest.raises(ValueError, match=re.escape(error_msg)) | ||
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| valid_cases = [ | ||
| ({"time": []}, does_not_raise()), | ||
| ({"time": [0, 1]}, does_not_raise()), | ||
| ({"space": ["x", "y"]}, does_not_raise()), | ||
| ({"time": [], "space": []}, does_not_raise()), | ||
| ({"time": [], "space": ["x", "y"]}, does_not_raise()), | ||
| ] # Valid cases (no error) | ||
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| invalid_cases = [ | ||
| ( | ||
| {"spacetime": []}, | ||
| expect_value_error_with_message( | ||
| "Input data must contain ['spacetime'] as dimensions." | ||
| ), | ||
| ), | ||
| ( | ||
| {"time": [0, 100], "space": ["x", "y"]}, | ||
| expect_value_error_with_message( | ||
| "Input data must contain [100] in the 'time' coordinates." | ||
| ), | ||
| ), | ||
| ( | ||
| {"space": ["x", "y", "z"]}, | ||
| expect_value_error_with_message( | ||
| "Input data must contain ['z'] in the 'space' coordinates." | ||
| ), | ||
| ), | ||
| ] # Invalid cases (raise ValueError) | ||
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| @pytest.mark.parametrize( | ||
| "required_dims_coords, expected_exception", | ||
| valid_cases + invalid_cases, | ||
| ) | ||
| def test_validate_dims_coords( | ||
| valid_poses_dataset_uniform_linear_motion, # fixture from conftest.py | ||
| required_dims_coords, | ||
| expected_exception, | ||
| ): | ||
| """Test validate_dims_coords for both valid and invalid inputs.""" | ||
| position_array = valid_poses_dataset_uniform_linear_motion["position"] | ||
| with expected_exception: | ||
| validate_dims_coords(position_array, required_dims_coords) |