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ENH: Implement Kendall discordance #110
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| Original file line number | Diff line number | Diff line change |
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@@ -158,6 +158,34 @@ inline double gdtr(double a, double b, double x) { return cephes::gdtr(a, b, x); | |
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| inline double gdtrc(double a, double b, double x) { return cephes::gdtrc(a, b, x); } | ||
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| inline int64_t kendall_dis(const std::vector<intptr_t> &x, const std::vector<intptr_t> &y) { | ||
| intptr_t sup = 1 + *std::max_element(y.begin(), y.end()); | ||
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Member
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Wait, I missed that the size of the scratch buffer depends on the values of
Member
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. It seems possible to use a different algorithm (Knight's merge-sort based algorithm) that won't require a buffer with size depending on the values of |
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| // Use of `>> 14` improves cache performance of the Fenwick tree (see gh-10108) | ||
| std::vector<intptr_t> arr(sup + ((sup - 1) >> 14), 0); | ||
| intptr_t i = 0, k = 0, size = static_cast<intptr_t>(x.size()), idx; | ||
| int64_t dis = 0; | ||
| while (i < size) { | ||
| while (k < size and x[i] == x[k]) { | ||
| dis += i; | ||
| idx = y[k]; | ||
| while (idx != 0) { | ||
| dis -= arr[idx + (idx >> 14)]; | ||
| idx = idx & (idx - 1); | ||
| } | ||
| ++k; | ||
| } | ||
| while (i < k) { | ||
| idx = y[i]; | ||
| while (idx < sup) { | ||
| arr[idx + (idx >> 14)] += 1; | ||
| idx += idx & -idx; | ||
| } | ||
| ++i; | ||
| } | ||
| } | ||
| return dis; | ||
| } | ||
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| inline double kolmogorov(double x) { return cephes::kolmogorov(x); } | ||
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| inline double kolmogc(double x) { return cephes::kolmogc(x); } | ||
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| @@ -0,0 +1,87 @@ | ||
| #include "../testing_utils.h" | ||
| #include <xsf/stats.h> | ||
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| /* | ||
| # Reference values computed with scipy.stats._kendall_dis | ||
| import numpy as np | ||
| from scipy.stats._stats import _kendall_dis | ||
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| rng = np.random.default_rng(123456789) | ||
| n = 150 | ||
| x_no_ties = rng.permutation(n) + 1 | ||
| y_no_ties = rng.permutation(n) + 1 | ||
| x_with_ties = rng.integers(1, n + 1, size=n) | ||
| y_with_ties = rng.integers(1, n + 1, size=n) | ||
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| # check "no_ties" arrays have no ties and "with_ties" arrays have ties | ||
| assert not len(np.unique(x_no_ties)) < len(x_no_ties) | ||
| assert len(np.unique(x_with_ties)) < len(x_with_ties) | ||
| assert not len(np.unique(y_no_ties)) < len(y_no_ties) | ||
| assert len(np.unique(y_with_ties)) < len(y_with_ties) | ||
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| for key_x, x in {"no_ties": x_no_ties, "with_ties": x_with_ties}.items(): | ||
| for key_y, y in {"no_ties": y_no_ties, "with_ties": y_with_ties}.items(): | ||
| print(f"x {key_x} and y {key_y}: disc = {_kendall_dis(x, y)}") | ||
| */ | ||
| TEST_CASE("kendall_dis test", "[kendall_dis][xsf_tests]") { | ||
| std::vector<intptr_t> x_no_ties = { | ||
| 81, 147, 93, 88, 65, 140, 89, 139, 72, 17, 43, 79, 19, 35, 101, 6, 53, 18, 149, 120, 90, 26, | ||
| 115, 42, 103, 98, 97, 96, 84, 54, 32, 102, 27, 108, 8, 68, 123, 94, 64, 134, 22, 124, 44, 41, | ||
| 50, 117, 116, 69, 138, 58, 91, 85, 21, 37, 49, 33, 80, 130, 75, 132, 83, 15, 51, 82, 127, 24, | ||
| 95, 114, 56, 109, 59, 34, 150, 119, 133, 107, 14, 4, 77, 31, 100, 92, 137, 122, 128, 136, 145, 55, | ||
| 48, 63, 29, 36, 105, 76, 5, 125, 38, 141, 113, 39, 45, 11, 148, 71, 111, 66, 28, 25, 110, 52, | ||
| 112, 118, 62, 74, 16, 3, 144, 67, 87, 57, 7, 70, 104, 30, 131, 86, 73, 9, 23, 142, 106, 60, | ||
| 143, 78, 129, 126, 99, 46, 10, 12, 2, 1, 121, 20, 40, 47, 146, 135, 13, 61 | ||
| }; | ||
| std::vector<intptr_t> y_no_ties = { | ||
| 39, 8, 58, 40, 55, 91, 57, 79, 117, 149, 29, 147, 150, 60, 93, 138, 36, 112, 122, 145, 137, 34, | ||
| 87, 19, 126, 26, 102, 86, 41, 105, 111, 146, 76, 143, 140, 136, 32, 18, 75, 67, 10, 17, 25, 22, | ||
| 119, 134, 43, 77, 14, 84, 101, 80, 103, 144, 46, 6, 124, 73, 38, 1, 68, 49, 74, 133, 114, 12, | ||
| 116, 118, 92, 63, 54, 106, 5, 121, 82, 33, 109, 69, 96, 16, 97, 95, 89, 61, 35, 27, 20, 37, | ||
| 56, 127, 108, 141, 142, 104, 135, 30, 13, 65, 45, 130, 83, 51, 23, 78, 44, 59, 110, 52, 81, 129, | ||
| 128, 2, 15, 53, 4, 132, 21, 64, 123, 148, 48, 139, 115, 100, 72, 71, 24, 90, 120, 9, 88, 98, | ||
| 113, 7, 70, 131, 66, 42, 62, 125, 31, 28, 3, 50, 107, 85, 99, 47, 11, 94 | ||
| }; | ||
| std::vector<intptr_t> x_with_ties = { | ||
| 45, 34, 80, 111, 115, 17, 129, 24, 29, 16, 98, 133, 59, 71, 131, 99, 41, 123, 44, 38, 42, 106, | ||
| 144, 82, 89, 59, 32, 75, 33, 99, 13, 84, 96, 88, 28, 85, 141, 101, 123, 65, 55, 70, 78, 124, | ||
| 4, 8, 83, 140, 24, 86, 40, 19, 120, 44, 111, 77, 105, 97, 94, 34, 46, 74, 119, 38, 41, 148, | ||
| 27, 145, 88, 88, 56, 30, 118, 35, 52, 123, 34, 97, 6, 15, 140, 27, 99, 54, 104, 18, 103, 102, | ||
| 12, 140, 134, 129, 90, 143, 95, 43, 70, 102, 22, 64, 62, 135, 147, 46, 123, 147, 55, 118, 70, 23, | ||
| 43, 41, 65, 134, 10, 29, 124, 105, 110, 119, 104, 102, 34, 26, 3, 15, 16, 52, 45, 24, 79, 49, | ||
| 89, 36, 149, 15, 113, 58, 108, 147, 28, 76, 99, 47, 95, 55, 146, 39, 42, 50 | ||
| }; | ||
| std::vector<intptr_t> y_with_ties = { | ||
| 97, 89, 31, 48, 54, 30, 120, 48, 61, 116, 35, 77, 33, 4, 139, 46, 52, 61, 104, 25, 109, 128, | ||
| 44, 77, 1, 28, 87, 43, 36, 139, 41, 76, 40, 82, 93, 49, 59, 110, 70, 110, 11, 130, 88, 65, | ||
| 27, 1, 60, 70, 98, 126, 103, 53, 109, 109, 133, 136, 25, 117, 36, 45, 20, 7, 89, 52, 129, 39, | ||
| 6, 93, 132, 120, 42, 66, 148, 141, 94, 106, 127, 86, 116, 41, 31, 47, 63, 23, 111, 48, 63, 108, | ||
| 120, 48, 46, 72, 18, 147, 65, 5, 59, 52, 111, 64, 20, 23, 105, 99, 92, 42, 107, 82, 16, 87, | ||
| 65, 37, 87, 31, 111, 15, 5, 76, 125, 91, 127, 30, 67, 100, 9, 136, 106, 68, 14, 74, 143, 97, | ||
| 86, 18, 28, 51, 23, 145, 133, 28, 94, 84, 72, 46, 103, 68, 12, 40, 80, 138 | ||
| }; | ||
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| // x_no_ties and y_no_ties | ||
| const int64_t res_no_no = xsf::kendall_dis(x_no_ties, y_no_ties); | ||
| const int64_t expected_no_no = 5943; | ||
| CAPTURE(x_no_ties, y_no_ties, res_no_no, expected_no_no); | ||
| REQUIRE(res_no_no == expected_no_no); | ||
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| // x_no_ties and y_with_ties | ||
| const int64_t res_no_with = xsf::kendall_dis(x_no_ties, y_with_ties); | ||
| const int64_t expected_no_with = 5444; | ||
| CAPTURE(x_no_ties, y_with_ties, res_no_with, expected_no_with); | ||
| REQUIRE(res_no_with == expected_no_with); | ||
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| // x_with_ties and y_no_ties | ||
| const int64_t res_with_no = xsf::kendall_dis(x_with_ties, y_no_ties); | ||
| const int64_t expected_with_no = 5942; | ||
| CAPTURE(x_with_ties, y_no_ties, res_with_no, expected_with_no); | ||
| REQUIRE(res_with_no == expected_with_no); | ||
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| // x_with_ties and y_with_ties | ||
| const int64_t res_with_with = xsf::kendall_dis(x_with_ties, y_with_ties); | ||
| const int64_t expected_with_with = 5443; | ||
| CAPTURE(x_with_ties, y_with_ties, res_with_with, expected_with_with); | ||
| REQUIRE(res_with_with == expected_with_with); | ||
| } |
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Does this need to be CuPy compatible in future? then
std::vectoris a no go from what I understood.There was a problem hiding this comment.
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Right, and I have cupy/cupy#9959 working now, so it's something we can actually try out now off of that branch.
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This should take three mdspan views, for
xandy, but also for the scratch buffer spacearr. No allocations inside of kernels. The SciPy gufunc should use the stateful functor pattern from https://github.com/steppi/scipy/blob/759ab1c458d56404dc8938a6074ebec8d290b449/scipy/special/mathieu.h to reuse the scratch buffer over the course of a single gufunc call. The CuPy gufunc will pre-allocate the scratch buffer space in Python wrapper.