wehub-resource-sync
66 lines
2.7 KiB
Python
66 lines
2.7 KiB
Python
from __future__ import annotations
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from typing import Any
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import numpy as np
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import numpy.typing as npt
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import pytest
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from rerun._validators import flat_np_array_from_array_like
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VALID_CASES = [
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# 1D array: length is a multiple of dimension
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(np.array([1, 2, 3, 4, 5, 6]), 3),
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(np.array([10, 20, 30, 40]), 2),
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# 2D array: shape is (n, dimension)
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(np.array([[1, 2, 3], [4, 5, 6]]), 3),
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# 3D array with extra singleton dimensions: last non-singleton dimension is dimension
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(np.array([[[1, 2, 3]], [[4, 5, 6]]]), 3),
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# Edge case: multi-dimensional array where all non-first dimensions are singletons (defaults to 1)
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(np.array([[[1]]]), 1),
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# Array of shape (1, 1, 1, 3)
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(np.array([[[[1, 2, 3]]]]), 3),
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# Array of shape (1, 1, 2, 3)
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(np.array([[[[1, 2, 3], [4, 5, 6]]]]), 3),
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# Array of shape (2, 2, 3)
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(
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np.array([[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]]),
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3,
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),
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# Array of shape (5, 1, 1, 3)
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(np.arange(15).reshape(5, 1, 1, 3), 3),
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# Array of shape (2, 1, 2) where the last non-singleton dimension is 2
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(np.array([[[1, 2]], [[3, 4]]]), 2),
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]
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@pytest.mark.parametrize(["input_array", "dimension"], VALID_CASES)
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def test_flat_np_array_from_array_like_valid(input_array: npt.NDArray[Any], dimension: int) -> None:
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np.testing.assert_array_equal(flat_np_array_from_array_like(input_array, dimension), input_array.reshape(-1))
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INVALID_CASES = [
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# 1D array: length not a multiple of dimension
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(np.array([1, 2, 3, 4]), 3),
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(np.array([1, 2, 3]), 2),
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# 2D array: shape is (n, m) where m != dimension
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(np.array([[1, 2], [3, 4]]), 3),
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# 3D array: last non-singleton dimension is not equal to dimension
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(np.array([[[1, 2]], [[3, 4]]]), 3),
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# Edge case: multi-dimensional array where all non-first dimensions are singletons (defaults to 1) but dimension is not 1
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(np.array([[[1]]]), 2),
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# 3D array with shape (2, 2, 2): last non-singleton dimension is 2, not equal to expected 3
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(np.array([[[1, 2], [3, 4]], [[5, 6], [7, 8]]]), 3),
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# 2D array with shape (3, 4): last dimension is 4, expected 3
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(np.array([[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]]), 3),
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# 3D array with shape (1, 1, 4): last non-singleton dimension is 4, expected 3
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(np.array([[[1, 2, 3, 4]]]), 3),
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# 4D array with shape (1, 2, 1, 3): last non-singleton dimension is 3, expected 2
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(np.array([[[[1, 2, 3]], [[4, 5, 6]]]]), 2),
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]
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@pytest.mark.parametrize(["input_array", "dimension"], INVALID_CASES)
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def test_flat_np_array_from_array_like_invalid(input_array: npt.NDArray[Any], dimension: int) -> None:
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with pytest.raises(ValueError):
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flat_np_array_from_array_like(input_array, dimension)
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