143 lines
3.5 KiB
PowerShell
143 lines
3.5 KiB
PowerShell
<#
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DISKSPD - VM Fleet
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Copyright(c) Microsoft Corporation
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All rights reserved.
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MIT License
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED *AS IS*, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.
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#>
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param(
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$csvfile,
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[string]$delimeter = "`t",
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[string]$xcol = $(throw "please specify column containing x values"),
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[string]$ycol = $(throw "please specify column containing y values"),
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[string[]]$idxcol,
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[switch]$zerointercept = $false
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)
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# given the input data, produce the linear fit coefficients for
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#
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# zerointercept = true: y = bx
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# !zerointercept = true: y = a + bx
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#
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# specify the column containing the x and y measurements
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# a single index column can be used to differentiate rows which should be
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# used for the fit (i.e., "test1", "test2", ...).
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#
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# method: ordinary least squares
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function do-linfit(
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[string] $xcol,
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[string] $ycol,
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[string] $key
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)
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{
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BEGIN
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{
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$sumxy = [decimal]0
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$sumx2 = [decimal]0
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$sumx = [decimal]0
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$sumy = [decimal]0
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$n = 0
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$pipe = @()
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}
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PROCESS
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{
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$x = [decimal]$_.$xcol
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$y = [decimal]$_.$ycol
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$sumxy += $x*$y
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$sumx2 += $x*$x
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$sumx += $x
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$sumy += $y
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$n += 1
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# accumulate pipeline for second pass
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$pipe += $_
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}
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END
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{
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if ($n -eq 0) {
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Write-Error "ERROR: no measurements matched"
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return
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}
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# perform requested fit
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$a = 0
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$b = 0
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if ($zerointercept) {
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$a = 0
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$b = ($sumxy/$sumx2)
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} else {
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$b = ($sumxy - (($sumx*$sumy)/$n)) / ($sumx2 - (($sumx*$sumx)/$n))
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$a = ($sumy - $b*$sumx)/$n
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}
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# calculate r2 (coefficient of determination) with respect to the fit
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$meany = $sumy/$n
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# total sum of squares
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$sstot = [decimal]0
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$pipe |% {
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$v = [decimal]$_.$ycol - $meany
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$sstot += $v*$v
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}
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# residual sum of squares
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$ssres = [decimal]0
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$pipe |% {
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$v = [decimal]$_.$ycol - ($a + $b*[decimal]$_.$xcol)
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$ssres += $v*$v
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}
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$r2 = 1 - ($ssres/$sstot)
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new-object -TypeName psobject -Property @{ 'A' = $a; 'B' = $b; 'R2' = $r2; 'N' = $n; 'Key' = $key; 'X' = $xcol; 'Y' = $ycol }
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}
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}
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# process the results into a hash keyed by the index columns
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$h = @{}
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import-csv -Path $csvfile -Delimiter $delimeter |% {
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$key = ""
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foreach ($col in $idxcol) {
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$key += "$col $($_.$col)"
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}
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$h[$key] += ,$_
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}
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$h.Keys |% {
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$h[$_] | do-linfit -xcol $xcol -ycol $ycol -key $_
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} |