378 lines
10 KiB
C
378 lines
10 KiB
C
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/*++
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Copyright (c) 1995 Microsoft Corporation
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Module Name
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stats.c
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Abstract:
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Perform basic statistics on a sample array of data: Average, Standard Deviation Coefficient.
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Perform simple filtering of Data to meet a specified Standard Deviation Coeficient (Optional).
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Author:
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Dan Almosnino (danalm) 20-Nov-1995 - Wrote it
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Enviornment:
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User Mode
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Revision History:
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++*/
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#include "precomp.h"
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#include "stats.h"
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/*++
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Routine Description:
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Shell for statistic processing of data
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Arguments
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double *array, Raw data array
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long num_samples, Number of samples taken
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const filter_option, available options: HI_FILTER, LO_FILTER, HI_LO_FILTER, NO_FILTER
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long var_limit, Filter data so that its variation coefficient (StdDev/Average)
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Won't exceed var_limit (in whole percent units)
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PTEST_STATS stats) Pointer to struct that contains the calculated statistical data
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Members: double Average, StdDev(%) (variation coefficient),
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Minimum_Result, Maximum_Result
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long NumSamplesValid (after filtering)
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Notes: Minimum_Result and Max_Result are always before filtering.
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A negative value of StdDev means that the average was zero, and
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the number returned is the negative value of the standard deviation
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itself and not a relative number (coeficient of variation)
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Return Value
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TRUE for Success
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FALSE for Failure (Indicates a failure of one of the called functions due to either:
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Too small No. of original Samples or Valid Samples left after filtering, or
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Zero Arithmetic Average of data (filtering cannot continue), or
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Invalid filter option.
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--*/
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BOOL
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Get_Stats(
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double *array,
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long num_samples,
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const filter_option,
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long var_limit,
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PTEST_STATS stats)
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{
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double Averagetmp;
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double StdDevtmp;
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long NumSamplestmp;
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if(!GetAverage(array, num_samples, &Averagetmp))
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return FALSE;
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SortUp(array, num_samples);
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if(!GetStdDev(array, Averagetmp, num_samples, &StdDevtmp))
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return FALSE;
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stats->Minimum_Result = array[0];
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stats->Maximum_Result = array[num_samples - 1];
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if(filter_option == NO_FILTER)
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{
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stats->Average = Averagetmp;
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stats->StdDev = StdDevtmp;
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stats->NumSamplesValid = num_samples;
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return TRUE;
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}
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NumSamplestmp = num_samples;
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if(!FilterResults(array,&Averagetmp,&StdDevtmp,&NumSamplestmp,var_limit,filter_option))
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return FALSE;
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stats->Average = Averagetmp;
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stats->StdDev = StdDevtmp;
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stats->NumSamplesValid = NumSamplestmp;
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return TRUE;
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}
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/*++
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Routine Description:
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Calculate the arithmetic average of an array of numbers
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Arguments
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double Sample_Array - data array
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long No_Samples - number of samples to calculate the average of
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double *Average - pointer to the result
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Return Value
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TRUE for Success
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FALSE for Failure (No_Samples is zero)
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--*/
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BOOL
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GetAverage(
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double Sample_Array[],
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long No_Samples,
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double *Average)
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{
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long i;
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(*Average) = 0.0;
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if(No_Samples == 0)return FALSE;
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for(i = 0; i < No_Samples; i++)
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{
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(*Average) += Sample_Array[i];
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}
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(*Average) /= No_Samples;
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return TRUE;
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}
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/*++
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Routine Description:
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Calculate the standard deviation of a set of data
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Arguments
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double Sample_Array - The data array
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double Average - The arithmetic Average of the Sample_Array
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long No_Samples - Number of Samples to Calculate
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double *varcoef - The resulting coeficient of variation (StdDev / Average) in percent
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(If the average is zero then the standard deviation itself is returned in
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negative value)
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Return Value
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TRUE for Success
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FALSE for Failure (No. of Samples is less than two)
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--*/
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BOOL
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GetStdDev(
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double Sample_Array[],
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double Average,
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long No_Samples,
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double *varcoef)
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{
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long i;
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double tmp;
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double Sum = 0.0;
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if(No_Samples <= 1L)
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{
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return FALSE;
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}
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for(i=0; i<No_Samples; i++)
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{
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tmp = (Sample_Array[i] - Average);
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Sum += (tmp*tmp);
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}
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Sum /= (No_Samples - 1);
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if(fabs( (float)Average) < 1.E-6)
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{
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*varcoef = (-sqrt(Sum)); // return the Standard Deviation itself in negative sign for distinction
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}
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else
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{
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*varcoef = (100*sqrt(Sum)/Average); // return the variation coeficient in percents
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}
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return TRUE;
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}
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/*++
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Routine Description:
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Simplest Quick Sort routine (sorts-up an array of doubles)
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Arguments
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double *Array - Pointer to the array to be sorted (result is returned in the same address)
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long array_size - Size of array to be sorted
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Return Value
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none
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--*/
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void
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SortUp(
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double *array,
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long array_size)
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{
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long gap, i, j;
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double temp;
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for(gap = array_size/2; gap > 0; gap /= 2)
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for(i = gap; i < array_size; i++)
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for(j = i - gap; j >= 0 && array[j] > array[j + gap]; j -= gap)
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{
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temp = array[j];
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array[j] = array[j + gap];
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array[j + gap] = temp;
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}
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}
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/*++
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Routine Description:
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Filter a set of data to meet a pre-defined coeficient of variation
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Arguments
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double Sorted_Array - A pointer to a pre-sorted up array of data to be filtered
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double *tmpAverage - A pointer to the arithmetic average of the array of data.
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Upon exit will contain the resulting average of the filtered data.
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double *tmpSD - A pointer to the variation coefficient (in percent) of the input array of data.
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Upon exit will contain the resulting variation coefficient of the filtered data
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after the constraint was met.
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long *tmpNumSamples - A pointer to the number of samples to be filtered.
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Upon return will contain the number of valid samples left after the filtering.
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long limit - The pre defined coefficient of variation (StdDev / Average)to be met
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(in whole percents).
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const filter_option - One of the following:
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HI_FILTER - filter eliminates the high values from top down until limit is met
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LO_FILTER - filter eliminates the low values from bottom up until limit is met
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HI_LO_FILTER- filter eliminates both high and low values in this order until limit is met
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other - routine will return a FALSE
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Return Value
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TRUE for Success
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FALSE for failure (Either number of samples left after sequential filtering passes is less than three,
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or for some reason the filtered average became zero,
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or the filter option is an invalid value)
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--*/
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BOOL
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FilterResults(
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double Sorted_Array[],
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double *tmpAverage,
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double *tmpSD,
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long *tmpNumSamples,
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long limit,
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const filter_option)
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{
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switch (filter_option)
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{
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case HI_FILTER:
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{
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while(*tmpSD > (double)limit)
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{
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if(*tmpNumSamples <= 2)return FALSE;
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(*tmpAverage) *= (*tmpNumSamples);
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(*tmpAverage) -= Sorted_Array[(*tmpNumSamples) - 1];
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(*tmpNumSamples)--;
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(*tmpAverage) /= (*tmpNumSamples);
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GetStdDev(Sorted_Array, *tmpAverage, *tmpNumSamples, &(*tmpSD));
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}
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if(*tmpSD < 0)return FALSE;
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}
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break;
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case LO_FILTER:
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{
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while(*tmpSD > (double)limit)
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{
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if(*tmpNumSamples <= 2)return FALSE;
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(*tmpAverage) *= (*tmpNumSamples);
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(*tmpAverage) -= (*Sorted_Array);
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Sorted_Array++;
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(*tmpNumSamples)--;
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(*tmpAverage) /= (*tmpNumSamples);
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GetStdDev(Sorted_Array, *tmpAverage, *tmpNumSamples, &(*tmpSD));
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}
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if(*tmpSD < 0)return FALSE;
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}
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break;
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case HI_LO_FILTER:
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{
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while(*tmpSD > (double)limit)
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{
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if(*tmpNumSamples <= 2)return FALSE;
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if(fabs((*Sorted_Array) - (*tmpAverage)) > fabs(Sorted_Array[*tmpNumSamples - 1] - *tmpAverage))
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{
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(*tmpAverage) *= (*tmpNumSamples);
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(*tmpAverage) -= (*Sorted_Array);
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Sorted_Array++;
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}
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else
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{
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(*tmpAverage) *= (*tmpNumSamples);
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(*tmpAverage) -= Sorted_Array[(*tmpNumSamples) - 1];
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}
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(*tmpNumSamples)--;
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(*tmpAverage) /= (*tmpNumSamples);
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GetStdDev(Sorted_Array, *tmpAverage, *tmpNumSamples, &(*tmpSD));
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}
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if(*tmpSD < 0)return FALSE;
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}
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break;
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default:
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return FALSE;
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} //switch filter_option
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return TRUE;
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}
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