92095781e0
This module provides a fast 64bit implementation of basic statistics functions, including mean, variance and standard deviation in both weighted and unweighted variants, the unweighted variant has a 32bit limitation per sample to prevent overflow when squaring. Signed-off-by: Daniel Hill <daniel@gluo.nz> Signed-off-by: Kent Overstreet <kent.overstreet@linux.dev>
154 lines
4.9 KiB
C
154 lines
4.9 KiB
C
// SPDX-License-Identifier: GPL-2.0
|
|
#include <kunit/test.h>
|
|
|
|
#include "mean_and_variance.h"
|
|
|
|
#define MAX_SQR (SQRT_U64_MAX*SQRT_U64_MAX)
|
|
|
|
static void mean_and_variance_basic_test(struct kunit *test)
|
|
{
|
|
struct mean_and_variance s = {};
|
|
|
|
s = mean_and_variance_update(s, 2);
|
|
s = mean_and_variance_update(s, 2);
|
|
|
|
KUNIT_EXPECT_EQ(test, mean_and_variance_get_mean(s), 2);
|
|
KUNIT_EXPECT_EQ(test, mean_and_variance_get_variance(s), 0);
|
|
KUNIT_EXPECT_EQ(test, s.n, 2);
|
|
|
|
s = mean_and_variance_update(s, 4);
|
|
s = mean_and_variance_update(s, 4);
|
|
|
|
KUNIT_EXPECT_EQ(test, mean_and_variance_get_mean(s), 3);
|
|
KUNIT_EXPECT_EQ(test, mean_and_variance_get_variance(s), 1);
|
|
KUNIT_EXPECT_EQ(test, s.n, 4);
|
|
}
|
|
|
|
/*
|
|
* Test values computed using a spreadsheet from the psuedocode at the bottom:
|
|
* https://fanf2.user.srcf.net/hermes/doc/antiforgery/stats.pdf
|
|
*/
|
|
|
|
static void mean_and_variance_weighted_test(struct kunit *test)
|
|
{
|
|
struct mean_and_variance_weighted s = { .weight = 2 };
|
|
|
|
s.weight = 2;
|
|
|
|
mean_and_variance_weighted_update(&s, 10);
|
|
KUNIT_EXPECT_EQ(test, mean_and_variance_weighted_get_mean(s), 10);
|
|
KUNIT_EXPECT_EQ(test, mean_and_variance_weighted_get_variance(s), 0);
|
|
|
|
mean_and_variance_weighted_update(&s, 20);
|
|
KUNIT_EXPECT_EQ(test, mean_and_variance_weighted_get_mean(s), 12);
|
|
KUNIT_EXPECT_EQ(test, mean_and_variance_weighted_get_variance(s), 18);
|
|
|
|
mean_and_variance_weighted_update(&s, 30);
|
|
KUNIT_EXPECT_EQ(test, mean_and_variance_weighted_get_mean(s), 16);
|
|
KUNIT_EXPECT_EQ(test, mean_and_variance_weighted_get_variance(s), 72);
|
|
|
|
s = (struct mean_and_variance_weighted) { .weight = 2 };
|
|
|
|
mean_and_variance_weighted_update(&s, -10);
|
|
KUNIT_EXPECT_EQ(test, mean_and_variance_weighted_get_mean(s), -10);
|
|
KUNIT_EXPECT_EQ(test, mean_and_variance_weighted_get_variance(s), 0);
|
|
|
|
mean_and_variance_weighted_update(&s, -20);
|
|
KUNIT_EXPECT_EQ(test, mean_and_variance_weighted_get_mean(s), -12);
|
|
KUNIT_EXPECT_EQ(test, mean_and_variance_weighted_get_variance(s), 18);
|
|
|
|
mean_and_variance_weighted_update(&s, -30);
|
|
KUNIT_EXPECT_EQ(test, mean_and_variance_weighted_get_mean(s), -16);
|
|
KUNIT_EXPECT_EQ(test, mean_and_variance_weighted_get_variance(s), 72);
|
|
|
|
}
|
|
|
|
static void mean_and_variance_weighted_advanced_test(struct kunit *test)
|
|
{
|
|
struct mean_and_variance_weighted s = { .weight = 8 };
|
|
s64 i;
|
|
|
|
for (i = 10; i <= 100; i += 10)
|
|
mean_and_variance_weighted_update(&s, i);
|
|
|
|
KUNIT_EXPECT_EQ(test, mean_and_variance_weighted_get_mean(s), 11);
|
|
KUNIT_EXPECT_EQ(test, mean_and_variance_weighted_get_variance(s), 107);
|
|
|
|
s = (struct mean_and_variance_weighted) { .weight = 8 };
|
|
|
|
for (i = -10; i >= -100; i -= 10)
|
|
mean_and_variance_weighted_update(&s, i);
|
|
|
|
KUNIT_EXPECT_EQ(test, mean_and_variance_weighted_get_mean(s), -11);
|
|
KUNIT_EXPECT_EQ(test, mean_and_variance_weighted_get_variance(s), 107);
|
|
|
|
}
|
|
|
|
static void mean_and_variance_fast_divpow2(struct kunit *test)
|
|
{
|
|
s64 i;
|
|
u8 d;
|
|
|
|
for (i = 0; i < 100; i++) {
|
|
d = 0;
|
|
KUNIT_EXPECT_EQ(test, fast_divpow2(i, d), div_u64(i, 1LLU << d));
|
|
KUNIT_EXPECT_EQ(test, abs(fast_divpow2(-i, d)), div_u64(i, 1LLU << d));
|
|
for (d = 1; d < 32; d++) {
|
|
KUNIT_EXPECT_EQ_MSG(test, abs(fast_divpow2(i, d)),
|
|
div_u64(i, 1 << d), "%lld %u", i, d);
|
|
KUNIT_EXPECT_EQ_MSG(test, abs(fast_divpow2(-i, d)),
|
|
div_u64(i, 1 << d), "%lld %u", -i, d);
|
|
}
|
|
}
|
|
}
|
|
|
|
static void mean_and_variance_u128_basic_test(struct kunit *test)
|
|
{
|
|
u128_u a = u64s_to_u128(0, U64_MAX);
|
|
u128_u a1 = u64s_to_u128(0, 1);
|
|
u128_u b = u64s_to_u128(1, 0);
|
|
u128_u c = u64s_to_u128(0, 1LLU << 63);
|
|
u128_u c2 = u64s_to_u128(U64_MAX, U64_MAX);
|
|
|
|
KUNIT_EXPECT_EQ(test, u128_hi(u128_add(a, a1)), 1);
|
|
KUNIT_EXPECT_EQ(test, u128_lo(u128_add(a, a1)), 0);
|
|
KUNIT_EXPECT_EQ(test, u128_hi(u128_add(a1, a)), 1);
|
|
KUNIT_EXPECT_EQ(test, u128_lo(u128_add(a1, a)), 0);
|
|
|
|
KUNIT_EXPECT_EQ(test, u128_lo(u128_sub(b, a1)), U64_MAX);
|
|
KUNIT_EXPECT_EQ(test, u128_hi(u128_sub(b, a1)), 0);
|
|
|
|
KUNIT_EXPECT_EQ(test, u128_hi(u128_shl(c, 1)), 1);
|
|
KUNIT_EXPECT_EQ(test, u128_lo(u128_shl(c, 1)), 0);
|
|
|
|
KUNIT_EXPECT_EQ(test, u128_hi(u128_square(U64_MAX)), U64_MAX - 1);
|
|
KUNIT_EXPECT_EQ(test, u128_lo(u128_square(U64_MAX)), 1);
|
|
|
|
KUNIT_EXPECT_EQ(test, u128_lo(u128_div(b, 2)), 1LLU << 63);
|
|
|
|
KUNIT_EXPECT_EQ(test, u128_hi(u128_div(c2, 2)), U64_MAX >> 1);
|
|
KUNIT_EXPECT_EQ(test, u128_lo(u128_div(c2, 2)), U64_MAX);
|
|
|
|
KUNIT_EXPECT_EQ(test, u128_hi(u128_div(u128_shl(u64_to_u128(U64_MAX), 32), 2)), U32_MAX >> 1);
|
|
KUNIT_EXPECT_EQ(test, u128_lo(u128_div(u128_shl(u64_to_u128(U64_MAX), 32), 2)), U64_MAX << 31);
|
|
}
|
|
|
|
static struct kunit_case mean_and_variance_test_cases[] = {
|
|
KUNIT_CASE(mean_and_variance_fast_divpow2),
|
|
KUNIT_CASE(mean_and_variance_u128_basic_test),
|
|
KUNIT_CASE(mean_and_variance_basic_test),
|
|
KUNIT_CASE(mean_and_variance_weighted_test),
|
|
KUNIT_CASE(mean_and_variance_weighted_advanced_test),
|
|
{}
|
|
};
|
|
|
|
static struct kunit_suite mean_and_variance_test_suite = {
|
|
.name = "mean and variance tests",
|
|
.test_cases = mean_and_variance_test_cases
|
|
};
|
|
|
|
kunit_test_suite(mean_and_variance_test_suite);
|
|
|
|
MODULE_AUTHOR("Daniel B. Hill");
|
|
MODULE_LICENSE("GPL");
|