mirror of
https://github.com/koverstreet/bcachefs-tools.git
synced 2025-01-23 00:07:07 +03:00
149 lines
4.3 KiB
C
149 lines
4.3 KiB
C
// SPDX-License-Identifier: GPL-2.0
|
|
/*
|
|
* Functions for incremental mean and variance.
|
|
*
|
|
* This program is free software; you can redistribute it and/or modify it
|
|
* under the terms of the GNU General Public License version 2 as published by
|
|
* the Free Software Foundation.
|
|
*
|
|
* This program is distributed in the hope that it will be useful, but WITHOUT
|
|
* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
|
|
* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for
|
|
* more details.
|
|
*
|
|
* Copyright © 2022 Daniel B. Hill
|
|
*
|
|
* Author: Daniel B. Hill <daniel@gluo.nz>
|
|
*
|
|
* Description:
|
|
*
|
|
* This is includes some incremental algorithms for mean and variance calculation
|
|
*
|
|
* Derived from the paper: https://fanf2.user.srcf.net/hermes/doc/antiforgery/stats.pdf
|
|
*
|
|
* Create a struct and if it's the weighted variant set the w field (weight = 2^k).
|
|
*
|
|
* Use mean_and_variance[_weighted]_update() on the struct to update it's state.
|
|
*
|
|
* Use the mean_and_variance[_weighted]_get_* functions to calculate the mean and variance, some computation
|
|
* is deferred to these functions for performance reasons.
|
|
*
|
|
* see lib/math/mean_and_variance_test.c for examples of usage.
|
|
*
|
|
* DO NOT access the mean and variance fields of the weighted variants directly.
|
|
* DO NOT change the weight after calling update.
|
|
*/
|
|
|
|
#include <linux/bug.h>
|
|
#include <linux/compiler.h>
|
|
#include <linux/export.h>
|
|
#include <linux/limits.h>
|
|
#include <linux/math.h>
|
|
#include <linux/math64.h>
|
|
#include <linux/mean_and_variance.h>
|
|
#include <linux/module.h>
|
|
|
|
/**
|
|
* fast_divpow2() - fast approximation for n / (1 << d)
|
|
* @n: numerator
|
|
* @d: the power of 2 denominator.
|
|
*
|
|
* note: this rounds towards 0.
|
|
*/
|
|
s64 fast_divpow2(s64 n, u8 d)
|
|
{
|
|
return (n + ((n < 0) ? ((1 << d) - 1) : 0)) >> d;
|
|
}
|
|
|
|
/**
|
|
* mean_and_variance_update() - update a mean_and_variance struct @s1 with a new sample @v1
|
|
* and return it.
|
|
* @s1: the mean_and_variance to update.
|
|
* @v1: the new sample.
|
|
*
|
|
* see linked pdf equation 12.
|
|
*/
|
|
struct mean_and_variance mean_and_variance_update(struct mean_and_variance s1, s64 v1)
|
|
{
|
|
return mean_and_variance_update_inlined(s1, v1);
|
|
}
|
|
EXPORT_SYMBOL_GPL(mean_and_variance_update);
|
|
|
|
/**
|
|
* mean_and_variance_get_mean() - get mean from @s
|
|
*/
|
|
s64 mean_and_variance_get_mean(struct mean_and_variance s)
|
|
{
|
|
return div64_u64(s.sum, s.n);
|
|
}
|
|
EXPORT_SYMBOL_GPL(mean_and_variance_get_mean);
|
|
|
|
/**
|
|
* mean_and_variance_get_variance() - get variance from @s1
|
|
*
|
|
* see linked pdf equation 12.
|
|
*/
|
|
u64 mean_and_variance_get_variance(struct mean_and_variance s1)
|
|
{
|
|
u128 s2 = u128_div(s1.sum_squares, s1.n);
|
|
u64 s3 = abs(mean_and_variance_get_mean(s1));
|
|
|
|
return u128_to_u64(u128_sub(s2, u128_square(s3)));
|
|
}
|
|
EXPORT_SYMBOL_GPL(mean_and_variance_get_variance);
|
|
|
|
/**
|
|
* mean_and_variance_get_stddev() - get standard deviation from @s
|
|
*/
|
|
u32 mean_and_variance_get_stddev(struct mean_and_variance s)
|
|
{
|
|
return int_sqrt64(mean_and_variance_get_variance(s));
|
|
}
|
|
EXPORT_SYMBOL_GPL(mean_and_variance_get_stddev);
|
|
|
|
/**
|
|
* mean_and_variance_weighted_update() - exponentially weighted variant of mean_and_variance_update()
|
|
* @s1: ..
|
|
* @s2: ..
|
|
*
|
|
* see linked pdf: function derived from equations 140-143 where alpha = 2^w.
|
|
* values are stored bitshifted for performance and added precision.
|
|
*/
|
|
struct mean_and_variance_weighted mean_and_variance_weighted_update(struct mean_and_variance_weighted s1,
|
|
s64 x)
|
|
{
|
|
return mean_and_variance_weighted_update_inlined(s1, x);
|
|
}
|
|
EXPORT_SYMBOL_GPL(mean_and_variance_weighted_update);
|
|
|
|
/**
|
|
* mean_and_variance_weighted_get_mean() - get mean from @s
|
|
*/
|
|
s64 mean_and_variance_weighted_get_mean(struct mean_and_variance_weighted s)
|
|
{
|
|
return fast_divpow2(s.mean, s.w);
|
|
}
|
|
EXPORT_SYMBOL_GPL(mean_and_variance_weighted_get_mean);
|
|
|
|
/**
|
|
* mean_and_variance_weighted_get_variance() -- get variance from @s
|
|
*/
|
|
u64 mean_and_variance_weighted_get_variance(struct mean_and_variance_weighted s)
|
|
{
|
|
// always positive don't need fast divpow2
|
|
return s.variance >> s.w;
|
|
}
|
|
EXPORT_SYMBOL_GPL(mean_and_variance_weighted_get_variance);
|
|
|
|
/**
|
|
* mean_and_variance_weighted_get_stddev() - get standard deviation from @s
|
|
*/
|
|
u32 mean_and_variance_weighted_get_stddev(struct mean_and_variance_weighted s)
|
|
{
|
|
return int_sqrt64(mean_and_variance_weighted_get_variance(s));
|
|
}
|
|
EXPORT_SYMBOL_GPL(mean_and_variance_weighted_get_stddev);
|
|
|
|
MODULE_AUTHOR("Daniel B. Hill");
|
|
MODULE_LICENSE("GPL");
|