I'm trying to calculate (in VBA Excel) the Average and StDev of an array with more than 65536 elements. Something like this:
Mitja = worksheetfunction.Average(array())
DesvTip = worksheetfunction.StDev(array())
While the dimension of the array is smaller than 65536 there is no problem but, when it's bigger it gives me an error!
I know that this VBA functions can't work with more than 65536 data so, how can I obtain this parameters in VBA?
Apreciate your comments. Thanks a lot! :))
You can calculate mean and standard deviation without having to store all the values. Just keep a running total of sum, sum of squares, and number of points. You can have as many points as integer number of points will allow that way.
Here's how I'd do it in Java. Feel free to crib.
package statistics;
/**
* Statistics
* #author Michael
* #link http://stackoverflow.com/questions/11978667/online-algorithm-for-calculating-standrd-deviation/11978689#11978689
* #link http://mathworld.wolfram.com/Variance.html
* #since 8/15/12 7:34 PM
*/
public class Statistics {
private int n;
private double sum;
private double sumsq;
public void reset() {
this.n = 0;
this.sum = 0.0;
this.sumsq = 0.0;
}
public synchronized void addValue(double x) {
++this.n;
this.sum += x;
this.sumsq += x*x;
}
public synchronized double calculateMean() {
double mean = 0.0;
if (this.n > 0) {
mean = this.sum/this.n;
}
return mean;
}
public synchronized double calculateVariance() {
double variance = 0.0;
if (this.n > 0) {
variance = Math.sqrt(this.sumsq-this.sum*this.sum/this.n)/this.n;
}
return variance;
}
public synchronized double calculateStandardDeviation() {
double deviation = 0.0;
if (this.n > 1) {
deviation = Math.sqrt((this.sumsq-this.sum*this.sum/this.n)/(this.n-1));
}
return deviation;
}
}
Use the following algorithm if the data is stored in an array x(1 to N, 1 to 1), where N is the number of data points
sum = 0# : sumsq = 0#
for i=1 to N
sum = sum + x(i,1)
sumsq = sumsq + x(i,1)^2
next i
average = sum/N
stddev = Sqr( sumsq/N^2 - sum^2/N^3 )
:Note:
To fill the array use the notation
Dim r as Range, x() as Variant
Set r = Range("A1").Resize(N,1)
x = r.Value
Thanks for both comments. Finally we did something similar. I hope it will be usefull for someone with the same problem. Our code:
sum = 0
sumq = 0
For i = 0 To ((2 * N) - 1)
sum = sum + h_normal(i)
Next i
media = sum / (2 * N)
For j = 0 To ((2 * N) - 1)
sumsq = sumsq + (h_normal(j) - media) ^ 2
Next j
desviaci(h - 1) = Math.Sqr(sumsq / ((2 * N) - 1))
Related
Source: https://www.geeksforgeeks.org/number-substrings-count-character-k/
Given a string and an integer k, find number of substrings in which all the different characters occurs exactly k times.
Looking for a solution in O(n), using two pointers/sliding window approach. I'm able to find only longest substrings satisfying this criteria but not substrings within that long substring.
For ex: ababbaba, k = 2
My solution finds abab, ababba etc, but not bb within ababba.
Can someone help me with the logic?
If you could edit your question to include your solution code, I'd be happy to help you with that.
For now I'm sharing my solution code (in java) which runs in O(n2). I've added enough comments to make the code self explanatory. Nonetheless the logic for the solution is as follows:
As you correctly pointed out, the problem can be solved using sliding window approach (with variable window size). The solution below considers all possible sub-strings, using nested for loops for setting start and end indices. For each sub-string, we check if every element in the sub-string occurs exactly k times.
To avoid recalculating the count for every sub-string, we maintain the count in a map, and keep putting new elements in the map as we increment the end index (slide the window). This ensures that our solution runs in O(n2) and not O(n3).
To further improve efficiency, we only check the count of individual elements if the sub-string's size matches our requirement. e.g. for n unique elements (keys in the map), the size of required sub-string would be n*k. If the sub-string's size doesn't match this value, there's no need to check how many times the individual characters occur.
import java.util.*;
/**
* Java program to count the number of perfect substrings in a given string. A
* substring is considered perfect if all the elements within the substring
* occur exactly k number of times.
*
* #author Codextor
*/
public class PerfectSubstring {
public static void main(String[] args) {
String s = "aabbcc";
int k = 2;
System.out.println(perfectSubstring(s, k));
s = "aabccc";
k = 2;
System.out.println(perfectSubstring(s, k));
}
/**
* Returns the number of perfect substrings in the given string for the
* specified value of k
*
* #param s The string to check for perfect substrings
* #param k The number of times every element should occur within the substring
* #return int The number of perfect substrings
*/
public static int perfectSubstring(String s, int k) {
int finalCount = 0;
/*
* Set the initial starting index for the subarray as 0, and increment it with
* every iteration, till the last index of the string is reached.
*/
for (int start = 0; start < s.length(); start++) {
/*
* Use a HashMap to store the count of every character in the subarray. We'll
* start with an empty map everytime we update the starting index
*/
Map<Character, Integer> frequencyMap = new HashMap<>();
/*
* Set the initial ending index for the subarray equal to the starting index and
* increment it with every iteration, till the last index of the string is
* reached.
*/
for (int end = start; end < s.length(); end++) {
/*
* Get the count of the character at end index and increase it by 1. If the
* character is not present in the map, use 0 as the default count
*/
char c = s.charAt(end);
int count = frequencyMap.getOrDefault(c, 0);
frequencyMap.put(c, count + 1);
/*
* Check if the length of the subarray equals the desired length. The desired
* length is the number of unique characters we've seen so far (size of the map)
* multilied by k (the number of times each character should occur). If the
* length is as per requiremets, check if each element occurs exactly k times
*/
if (frequencyMap.size() * k == (end - start + 1)) {
if (check(frequencyMap, k)) {
finalCount++;
}
}
}
}
return finalCount;
}
/**
* Returns true if every value in the map is equal to k
*
* #param map The map whose values are to be checked
* #param k The required value for keys in the map
* #return true if every value in the map is equal to k
*/
public static boolean check(Map<Character, Integer> map, int k) {
/*
* Iterate through all the values (frequency of each character), comparing them
* with k
*/
for (Integer i : map.values()) {
if (i != k) {
return false;
}
}
return true;
}
}
For a given value k and a string s of length n with alphabet size D, we can solve the problem in O(n*D).
We need to find sub-strings with each character having exactly k-occurences
Minimum size of such sub-string = k (when only one character is there)
Maximum size of such sub-string = k*D (when all characters are there)
So we will check for all sub-strings of sizes in range [k, k*D]
from collections import defaultdict
ALPHABET_SIZE = 26
def check(count, k):
for v in count.values():
if v != k and v != 0:
return False
return True
def countSubstrings(s, k):
total = 0
for d in range(1, ALPHABET_SIZE + 1):
size = d * k
count = defaultdict(int)
l = r = 0
while r < len(s):
count[s[r]] += 1
# if window size exceed `size`, then fix left pointer and count
if r - l + 1 > size:
count[s[l]] -= 1
l += 1
# if window size is adequate then check and update count
if r - l + 1 == size:
total += check(count, k)
r += 1
return total
def main():
string1 = "aabbcc"
k1 = 2
print(countSubstrings(string1, k1)) # output: 6
string2 = "bacabcc"
k2 = 2
print(countSubstrings(string2, k2)) # output: 2
main()
I can't give you a O(n) solution but I can give you a O(k*n) solution (better than O(n^2) mentioned in the geeksforgeeks page).
The idea is that max no. elements are 26. So, we don't have to check all the substrings, we just have to check substrings with length<=26*k (26*k length is the case when all elements will occur k times. If length is more than that then at least one element will have to occur at least k+1 times). Also, we need to check only those substrings whose lengths are a factor of k.
So, check all 26*k*l possible substrings! (assuming k<<l). Thus, solution is O(k*n) but with a bit high constant (26).
There are few observation which will help optimize the solution
Notice that, you don't need to check every possible size substrings, you just need to check substrings of size k, 2k, 3k so on up to ALPHABET_SIZE * k (remember Pigeonhole principle)
You can pre-calculate frequency of alphabets till certain index from any end and later you can use it to find the frequency of alphabets between any two indexes in O(26)
C++ Implementation of your problem in O(n * ALPHABET_SIZE^2)
I have added comments and diagrams to help you out in understanding code quickly
diagram 1
diagram 2
#include <bits/stdc++.h>
#define ll long long
#define ALPHABET_SIZE 26
using namespace std;
int main()
{
ios_base::sync_with_stdio(false);
cin.tie(NULL);
cout.tie(NULL);
int n, k;
string s;
cin >> n >> k;
cin >> s;
ll cnt = 0;
/**
* It will be storing frequency of each alphabets
**/
vector<int> f(ALPHABET_SIZE, 0);
/**
* It will store alphabets frequency till that index
**/
vector<vector<int>> v;
v.push_back(f);
/**
* Scan array from left to right and calculate the frequency of each alphabets till that index
* Now push that frequency array in v
* This loop will run for n times
**/
for (int i = 1; i <= n; i++)
{
f[s[i - 1] - 'a']++;
v.push_back(f);
}
/**
* This loop will run for k times
**/
for (int i = 0; i < k; i++)
{
/**
* start is the lower bound (left end from where window will start sliding)
**/
int start = i;
/**
* end is the upper bound (right end till where window will be sliding)
**/
int end = (n / k) * k + i;
if (end > n)
{
end -= k;
}
/**
* This loop will run for n/k times
**/
for (int j = start; j <= end; j += k)
{
/**
* This is a ALPHABET_SIZE * k size window
* It will be sliding between start and end (inclusive)
* This loop will run for at most ALPHABET_SIZE times
**/
for (int d = j + k; d <= min(ALPHABET_SIZE * k + j, end); d += k)
{
/**
* A flag to check weather substring is valid or not
**/
bool flag = true;
/**
* Check if frequencies at two different indexes differ only by zero or k (element wise)
* Note that frequencies at two different index can't be same
* This loop will run for ALPHABET_SIZE times
**/
for (int idx = 0; idx < ALPHABET_SIZE; idx++)
{
if (abs(v[j][idx] - v[d][idx]) != k && abs(v[j][idx] - v[d][idx]) != 0)
{
flag = false;
}
}
/**
* Increase the total count if flag is true
**/
if (flag)
{
cnt++;
}
}
}
}
/**
* Print the total count
**/
cout << cnt;
return 0;
}
if you want solution in simple way and not worried about time complexity. Here is the solution.
public class PerfecSubstring {
public static void main(String[] args) {
String st = "aabbcc";
int k = 2;
System.out.println(perfect(st, k));
}
public static int perfect(String st, int k) {
int count = 0;
for (int i = 0; i < st.length(); i++) {
for (int j = st.length(); j > i; j--) {
String sub = st.substring(i, j);
if (sub.length() > k && check(sub, k)) {
System.out.println(sub);
count++;
}
}
}
return count;
}
public static boolean check(String st, int k) {
Map<Character, Integer> map = new HashMap<>();
for (int i = 0; i < st.length(); i++) {
Character c = st.charAt(i);
map.put(c, map.getOrDefault(c, 0) + 1);
}
return map.values().iterator().next() == k && new HashSet<>(map.values()).size() == 1;
}
}
Here is an answer I did in C#, with O(n^2) complexity. I probably should have used a helper method to avoid having a large chunk of code, but it does the job. :)
namespace CodingChallenges
{
using System;
using System.Collections.Generic;
class Solution
{
// Returns the number of perfect substrings of repeating character value 'num'.
public static int PerfectSubstring(string str, int num)
{
int count = 0;
for (int startOfSliceIndex = 0; startOfSliceIndex < str.Length - 1; startOfSliceIndex++)
{
for (int endofSliceIndex = startOfSliceIndex + 1; endofSliceIndex < str.Length; endofSliceIndex++)
{
Dictionary<char, int> dict = new Dictionary<char, int>();
string slice = str.Substring(startOfSliceIndex, (endofSliceIndex - startOfSliceIndex) + 1);
for (int i = 0; i < slice.Length; i++)
{
if (dict.ContainsKey(slice[i]))
{
dict[slice[i]]++;
}
else
{
dict[slice[i]] = 1;
}
}
bool isPerfect = true;
foreach (var entry in dict)
{
if (entry.Value != num)
{
isPerfect = false;
}
}
if (isPerfect)
{
Console.WriteLine(slice);
count++;
}
}
}
if (count == 1)
{
Console.WriteLine(count + " perfect substring.");
}
else
{
Console.WriteLine(count + " perfect substrings.");
}
return count;
}
public static void Main(string[] args)
{
string test = "1102021222";
PerfectSubstring(test, 2);
}
}
}
This solution works in O(n*D)
I think it can be upgraded to be O(n) by replacing the hash_map(frozenset(head_sum_mod_k.items())) with a map implementation that updates its hash rather than recalculating it -
this can be done because only one entry of head_sum_mod_k is changed per iteration.
from copy import deepcopy
def countKPerfectSequences(string:str, k):
print(f'Processing \'{string}\', k={k}')
# init running sum
head_sum = {char: 0 for char in string}
tail_sum = deepcopy(head_sum)
tail_position = 0
# to match both 0 & k sequence lengths, test for mod k == 0
head_sum_mod_k = deepcopy(head_sum)
occurrence_positions = {frozenset(head_sum_mod_k.items()): [0]}
# iterate over string
perfect_counter = 0
for i, val in enumerate(string):
head_sum[val] += 1
head_sum_mod_k[val] = head_sum[val] % k
while head_sum[val] - tail_sum[val] > k:
# update tail to avoid longer than k sequnces
tail_sum[string[tail_position]] += 1
tail_position += 1
# print(f'str[{tail_position}..{i}]=\'{string[tail_position:i+1]}\', head_sum_mod_k={head_sum_mod_k} occurrence_positions={occurrence_positions}')
# get matching sequences between head and tail
indices = list(filter(lambda i: i >= tail_position, occurrence_positions.get(frozenset(head_sum_mod_k.items()), [])))
# for start in indices:
# print(f'{string[start:i+1]}')
perfect_counter += len(indices)
# add head
indices.append(i+1)
occurrence_positions[frozenset(head_sum_mod_k.items())] = indices
return perfect_counter
I'm using simple moving average in Math.Net, but now that I also need to calculate EMA (exponential moving average) or any kind of weighted moving average, I don't find it in the library.
I looked over all methods under MathNet.Numerics.Statistics and beyond, but didn't find anything similar.
Is it missing in library or I need to reference some additional package?
I don't see any EMA in MathNet.Numerics, however it's trivial to program. The routine below is based on the definition at Investopedia.
public double[] EMA(double[] x, int N)
{
// x is the input series
// N is the notional age of the data used
// k is the smoothing constant
double k = 2.0 / (N + 1);
double[] y = new double[x.Length];
y[0] = x[0];
for (int i = 1; i < x.Length; i++) y[i] = k * x[i] + (1 - k) * y[i - 1];
return y;
}
Occasionally I found this package: https://daveskender.github.io/Stock.Indicators/docs/INDICATORS.html It targets to the latest .NET framework and has very detailed documents.
Try this:
public IEnumerable<double> EMA(IEnumerable<double> items, int notationalAge)
{
double k = 2.0d / (notationalAge + 1), prev = 0.0d;
var e = items.GetEnumerator();
if (!e.MoveNext()) yield break;
yield return prev = e.Current;
while(e.MoveNext())
{
yield return prev = (k * e.Current) + (1 - k) * prev;
}
}
It will still work with arrays, but also List, Queue, Stack, IReadOnlyCollection, etc.
Although it's not explicitly stated I also get the sense this is working with money, in which case it really ought to use decimal instead of double.
Here's the link to the question..
http://www.codechef.com/problems/J7
I figured out that 2 edges have to be equal in order to give the maximum volume, and then used x, x, a*x as the lengths of the three edges to write the equations -
4*x + 4*x + 4*a*x = P (perimeter) and,
2*x^2 + 4*(a*x *x) = S (total area of the box)
so from the first equation I got x in terms of P and a, and then substituted it in the second equation and then got a quadratic equation with the unknown being a. and then I used the greater root of a and got x.
But this method seems to be giving the wrong answer! :|
I know that there isn't any logical error in this. Maybe some formatting error?
Here's the main code that I've written :
{
public static void main(String[] args)
{
TheBestBox box = new TheBestBox();
reader = box.new InputReader(System.in);
writer = box.new OutputWriter(System.out);
getAttributes();
writer.flush();
reader.close();
writer.close();
}
public static void getAttributes()
{
t = reader.nextInt(); // t is the number of test cases in the question
for (int i = 0; i < t; i++)
{
p = reader.nextInt(); // p is the perimeter given as input
area = reader.nextInt(); // area of the whole sheet, given as input
a = findRoot(); // the fraction by which the third side differs by the first two
side = (double) p / (4 * (2 + a)); // length of the first and the second sides (equal)
height = a * side; // assuming that the base is a square, the height has to be the side which differs from the other two
// writer.println(side * side * height);
// System.out.printf("%.2f\n", (side * side * height));
writer.println(String.format("%.2f", (side * side * height))); // just printing out the final answer
}
}
public static double findRoot() // the method to find the 2 possible fractions by which the height can differ from the other two sides and return the bigger one of them
{
double a32, b, discriminant, root1, root2;
a32 = 32 * area - p * p;
b = 32 * area - 2 * p * p;
discriminant = Math.sqrt(b * b - 4 * 8 * area * a32);
double temp;
temp = 2 * 8 * area;
root1 = (- b + discriminant) / temp;
root2 = (- b - discriminant) / temp;
return Math.max(root1, root2);
}
}
could someone please help me out with this? Thank You. :)
I also got stuck in this question and realized that can be done by making equation of V(volume) in terms of one side say 'l' and using differentiation to find maximum volume in terms of any one side 'l'.
So, equations are like this :-
P = 4(l+b+h);
S = 2(l*b+b*h+l*h);
V = l*b*h;
so equation in l for V = (l^3) - (l^2)P/4 + lS/2 -------equ(1)
After differentiation we get:-
d(V)/d(l) = 3*(l^2) - l*P/2 + S/2;
to get max V we need to equate above equation to zero(0) and get the value of l.
So, solutions to a quadratic equation will be:-
l = ( P + sqrt((P^2)-24S) ) / 24;
so substitute this l in equation(1) to get max volume.
I have a DICOM series, with following origin, spacing and extent:
int nExtent[6];
double dSpacing[3];
double dOrigin[3];
m_pReader->GetOutputInformation(0)->Get(vtkStreamingDemandDrivenPipeline::WHOLE_EXTENT(), nExtent);
m_pReader->GetOutput()->GetSpacing(dSpacing);
m_pReader->GetOutput()->GetOrigin(dOrigin);
where m_pReader is vtkDICOMReader object ...
dOrigin is 0, 0, 0;
dSpacing id 0.447266, 0.447266, 3.998718;
nExtent is 0, 511, 0, 511, 0, 43;
the series is AXIAL.
Now, if I slice the series through AXIAL plan, I could slice the series by 44 slices, like that:
double deltaY = 0.0;
delta += 1.0;
pReslice->Update();
double dSliceSpacing = pReslice->GetOutput()->GetSpacing()[2];
vtkMatrix4x4* pMatrix = pReslice->GetResliceAxes();
// move the dCenter dPoint that we are slicing through
double dPoint[4];
double dCenter[4];
dPoint[0] = 0.0;
dPoint[1] = 0.0;
dPoint[2] = dSliceSpacing * deltaY;
dPoint[3] = 1.0;
pMatrix->MultiplyPoint(dPoint, dCenter);
pMatrix->SetElement(0, 3, dCenter[0]);
pMatrix->SetElement(1, 3, dCenter[1]);
pMatrix->SetElement(2, 3, dCenter[2]);
Everything is allright ...
The problem: if I slice the series through CORONAL plan, the slices number are not 44 !! But how many ? How can I know the slice number if the plan is CORONAL or SAGITTAL ?
On Coronal and Sagittal slicing its more about position instead of slice index.
You need to calculate your min/max origin for each axis (x,y,z)
e.g.
myOriginMax.X = myOrigin.X + ((ImageDimension.SizeX - 1) * mySpacing.X);
You can compute your new origin in your slicing Event, where _positionDelta is your inc/dec value. (more or less pseudo code)
e.g.
double[] _origin = myImageReslice.GetResliceAxesOrigin();
if(_view == "SAGITTAL")
{
_origin[0] = Math.Min(_origin[0] + _positionDelta * mySpacing.X, myOriginMax.X);
}
else if(_view == "CORONAL")
{
_origin[1] = Math.Min(_origin[1] + _positionDelta * mySpacing.Y, myOriginMax.Y);
}
else //AXIAL
{
_origin[2] = Math.Min(_origin[2] + _positionDelta * mySpacing.Z, myOriginMax.Z);
}
myImageReslice.SetReliceAxesOrigin(_origin[0], _origin[1], _origin[2]);
Render();
Yes, it is another compute method ... in my case I have m_pReslice for axial plan, m_pReslice2 for coronal plan, and m_pReslice3 for sagittal plan ... I don't know if is the proper architecture, but applying your algorithm I arrive in the same place :)
m_pReslice->GetResliceAxesOrigin(dOrigin);
int nSizeX = nExtent[0] + nExtent[1];
int nSizeY = nExtent[2] + nExtent[3];
int nSizeZ = nExtent[4] + nExtent[5];
double dOriginMax[3];
dOriginMax[0] = dOrigin[0] + ((nSizeX - 1) * dSpacing[0]);
dOriginMax[1] = dOrigin[1] + ((nSizeY - 1) * dSpacing[1]);
dOriginMax[2] = dOrigin[2] + ((nSizeZ - 1) * dSpacing[2]);
dOrigin[0] = min(dOrigin[0] + 1.0 * dSpacing[0], dOriginMax[0]);
dOrigin[1] = min(dOrigin[1] + 1.0 * dSpacing[1], dOriginMax[1]);
dOrigin[2] = min(dOrigin[2] + 1.0 * dSpacing[2], dOriginMax[2]);
m_pReslice->SetResliceAxesOrigin(dOrigin);
this is the case for m_pReslice (axial plan) ... if I apply the algorithm for m_pReslice2 (coronal) and for m_pReslice3 (sagittal), I still don't know how may slices I have in coronal case (or sagittal) ...
Ok, so I have a histogram (represented by an array of ints), and I'm looking for the best way to find local maxima and minima. Each histogram should have 3 peaks, one of them (the first one) probably much higher than the others.
I want to do several things:
Find the first "valley" following the first peak (in order to get rid of the first peak altogether in the picture)
Find the optimum "valley" value in between the remaining two peaks to separate the picture
I already know how to do step 2 by implementing a variant of Otsu.
But I'm struggling with step 1
In case the valley in between the two remaining peaks is not low enough, I'd like to give a warning.
Also, the image is quite clean with little noise to account for
What would be the brute-force algorithms to do steps 1 and 3? I could find a way to implement Otsu, but the brute-force is escaping me, math-wise. As it turns out, there is more documentation on doing methods like otsu, and less on simply finding peaks and valleys. I am not looking for anything more than whatever gets the job done (i.e. it's a temporary solution, just has to be implementable in a reasonable timeframe, until I can spend more time on it)
I am doing all this in c#
Any help on which steps to take would be appreciated!
Thank you so much!
EDIT: some more data:
most histogram are likely to be like the first one, with the first peak representing background.
Use peakiness-test. It's a method to find all the possible peak between two local minima, and measure the peakiness based on a formula. If the peakiness higher than a threshold, the peak is accepted.
Source: UCF CV CAP5415 lecture 9 slides
Below is my code:
public static List<int> PeakinessTest(int[] histogram, double peakinessThres)
{
int j=0;
List<int> valleys = new List<int> ();
//The start of the valley
int vA = histogram[j];
int P = vA;
//The end of the valley
int vB = 0;
//The width of the valley, default width is 1
int W = 1;
//The sum of the pixels between vA and vB
int N = 0;
//The measure of the peaks peakiness
double peakiness=0.0;
int peak=0;
bool l = false;
try
{
while (j < 254)
{
l = false;
vA = histogram[j];
P = vA;
W = 1;
N = vA;
int i = j + 1;
//To find the peak
while (P < histogram[i])
{
P = histogram[i];
W++;
N += histogram[i];
i++;
}
//To find the border of the valley other side
peak = i - 1;
vB = histogram[i];
N += histogram[i];
i++;
W++;
l = true;
while (vB >= histogram[i])
{
vB = histogram[i];
W++;
N += histogram[i];
i++;
}
//Calculate peakiness
peakiness = (1 - (double)((vA + vB) / (2.0 * P))) * (1 - ((double)N / (double)(W * P)));
if (peakiness > peakinessThres & !valleys.Contains(j))
{
//peaks.Add(peak);
valleys.Add(j);
valleys.Add(i - 1);
}
j = i - 1;
}
}
catch (Exception)
{
if (l)
{
vB = histogram[255];
peakiness = (1 - (double)((vA + vB) / (2.0 * P))) * (1 - ((double)N / (double)(W * P)));
if (peakiness > peakinessThres)
valleys.Add(255);
//peaks.Add(255);
return valleys;
}
}
//if(!valleys.Contains(255))
// valleys.Add(255);
return valleys;
}