How to remove the value using Histogram

Question

Med Future 2023-1-24

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https://ww2.mathworks.cn/matlabcentral/answers/1899600-how-to-remove-the-value-using-histogram

评论： Star Strider 2023-1-27

histogram.mat

I have the following data, in which my original value is 15 which have count of 7360

I want to remove the remaining values which count less then 33% of orginal values or multiple of the original value

for example in this case I have 30,45 ,60,75 and 90 I want to remove this values. and value of 1 also

How can i do that in MATLAB

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Answer 1

Star Strider 2023-1-24

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https://ww2.mathworks.cn/matlabcentral/answers/1899600-how-to-remove-the-value-using-histogram#answer_1155145

在 MATLAB Online 中打开

I have only a vague idea of what you want to do, especially since the .mat file does not appear to contain the same data as depicted in the posted plot image.

Try this —

LD = load(websave('histogram','https://www.mathworks.com/matlabcentral/answers/uploaded_files/1272595/histogram.mat'))

LD = struct with fields:

ans: [8839×1 double]

v = LD.ans;

Ev = linspace(0, 100, 101)

Ev = 1×101

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29

figure

hh = histogram(v, Ev);

Vals = hh.Values;

Edgs = hh.BinEdges;

Retain = (Vals > max(Vals)/3);

Out = Vals(Retain)

Out = 1×2

2896 4568

OutBinsLowerEdge = Edgs(Retain)

OutBinsLowerEdge = 1×2

14 15

If you want to remove the associated data in the original file corresponding to those values, that would be relatively straightforward using logical indexing. Another approach would be to use histcounts, return the 'Bins' output, and index into that.

.

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Star Strider 2023-1-24

在 MATLAB Online 中打开

I still have no clear idea of what you want to do. It would help somewhat if youoposted the histogram call that produced the data you posted. I have no idea what that is.

If you want to eliminate only those values that are greater than less than

of the highest frequency values, one option would be:

LD = load(websave('histogram','https://www.mathworks.com/matlabcentral/answers/uploaded_files/1272595/histogram.mat'))

LD = struct with fields:

ans: [8839×1 double]

Data = LD.ans;

Ev = linspace(0, 100, 1001); % Change This To Produce The Values You Want

figure

hh = histogram(Data, Ev);

[N,Edges,Bin] = histcounts(Data, Ev);

Retain = N > max(N)/3;

FindBins = find(Retain)

FindBins = 1×2

150 151

RetainDataLv = (Bin >= FindBins(1)) & (Bin <= FindBins(2)); % Values In 'Bin' Corresponding To 'Retain' Test

RetainData = Data(RetainDataLv) % Return Desired Subset OF 'Data'

RetainData = 7360×1

15.0200 15.0100 14.9800 15.0100 15.0000 15.0150 14.9950 15.0050 15.0050 15.0050

See if this does what you want.

.

Star Strider 2023-1-25

在 MATLAB Online 中打开

I still do not understand ‘I want to Delete the remaining Values which have counts less than 33 of maximum counts of value’ so I am guessing that ‘33’ actually means 33 counts, although that also has an ambiguous reference. So I’m interpreting that as any bin with less than 33 counts less than the counts in the maximum bin.

LD = load(websave('seconddata','https://www.mathworks.com/matlabcentral/answers/uploaded_files/1273595/secondata.mat'));

NewDataset = LD.NewData

NewDataset = 1×16075

100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000

h=histogram(NewDataset,10000,"BinMethod","sturges",'BinWidth',1,'BinLimits',[1 100]);

[N,Edges,Bin] = histcounts(NewDataset,10000,"BinMethod","sturges",'BinWidth',1,'BinLimits',[1 100]);

Retain = N > max(N)-33;

FindBins = find(Retain)

FindBins = 99

RetainDataLv = (Bin == FindBins(1)); % Values In 'Bin' Corresponding To 'Retain' Test

RetainData = NewDataset(RetainDataLv) % Return Desired Subset OF 'Data'

RetainData = 1×3474

100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000

Using histcounts makes this easier.

.

Star Strider 2023-1-25

在 MATLAB Online 中打开

O.K. That requires one small change —

LD = load(websave('seconddata','https://www.mathworks.com/matlabcentral/answers/uploaded_files/1273595/secondata.mat'));

NewDataset = LD.NewData

NewDataset = 1×16075

100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000

h=histogram(NewDataset,10000,"BinMethod","sturges",'BinWidth',1,'BinLimits',[1 100]);

[N,Edges,Bin] = histcounts(NewDataset,10000,"BinMethod","sturges",'BinWidth',1,'BinLimits',[1 100]);

Retain = N > max(N)/3; % Retain Values In Bins Greater Than One-Third Of The Meximum Bin Count Value

FindBins = find(Retain)

FindBins = 99

RetainDataLv = (Bin == FindBins(1)); % Values In 'Bin' Corresponding To 'Retain' Test

RetainData = NewDataset(RetainDataLv) % Return Desired Subset OF 'Data'

RetainData = 1×3474

100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000

This returns the original values in bins that are greater than

of the maximum bin count value.

.

Star Strider 2023-1-26

编辑：Star Strider 2023-1-26

在 MATLAB Online 中打开

That must be different data.

Using slightly changed code on both available data —

LD = load(websave('seconddata','https://www.mathworks.com/matlabcentral/answers/uploaded_files/1273595/secondata.mat'));

NewDataset = LD.NewData(:)

NewDataset = 16075×1

100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000

h=histogram(NewDataset,10000,"BinMethod","sturges",'BinWidth',1,'BinLimits',[1 100]);

[N,Edges,Bin] = histcounts(NewDataset,10000,"BinMethod","sturges",'BinWidth',1,'BinLimits',[1 100]);

Retain = N > max(N)/3; % Retain Values In Bins Greater Than One-Third Of The Meximum Bin Count Value

FindBins = find(Retain)

FindBins = 99

RetainDataLv = (Bin == FindBins); % Values In 'Bin' Corresponding To 'Retain' Test

SzRD = size(RetainDataLv);

RetainData = NewDataset(any(RetainDataLv,min(SzRD))) % Return Desired Subset OF 'Data'

RetainData = 100.0000

LD = load(websave('histogram','https://www.mathworks.com/matlabcentral/answers/uploaded_files/1272595/histogram.mat'))

LD = struct with fields:

ans: [8839×1 double]

Data = LD.ans(:);

h=histogram(Data,10000,"BinMethod","sturges",'BinWidth',1,'BinLimits',[1 100]);

[N,Edges,Bin] = histcounts(Data,10000,"BinMethod","sturges",'BinWidth',1,'BinLimits',[1 100]);

Retain = N > max(N)/3; % Retain Values In Bins Greater Than One-Third Of The Meximum Bin Count Value

FindBins = find(Retain)

FindBins = 1×2

14 15

RetainDataLv = (Bin == FindBins); % Values In 'Bin' Corresponding To 'Retain' Test

SzRD = size(RetainDataLv)

SzRD = 1×2

8839 2

RetainData = Data(any(RetainDataLv,min(SzRD))) % Return Desired Subset OF 'Data'

RetainData = 7464×1

15.0200 15.0100 14.9800 15.0100 15.0000 15.0150 14.9950 15.0050 15.0050 15.0050

See if that does what you want.

EDIT — (26 Jan 2023 at 13:20)

Added ‘(:)’ in the assignment defining the data after the load call to force the data vectors to be column vectors.

.

Star Strider 2023-1-26

在 MATLAB Online 中打开

Changed —

LD = load(websave('seconddata','https://www.mathworks.com/matlabcentral/answers/uploaded_files/1273595/secondata.mat'));

NewDataset = LD.NewData(:)

NewDataset = 16075×1

100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000

h=histogram(NewDataset,10000,"BinMethod","sturges",'BinWidth',1,'BinLimits',[1 10000]);

[N,Edges,Bin] = histcounts(NewDataset,10000,"BinMethod","sturges",'BinWidth',1,'BinLimits',[1 10000]);

Retain = N > max(N)/3; % Retain Values In Bins Greater Than One-Third Of The Meximum Bin Count Value

FindBins = find(Retain)

FindBins = 1×5

99 100 150 200 250

RetainDataLv = (Bin == FindBins); % Values In 'Bin' Corresponding To 'Retain' Test

SzRD = size(RetainDataLv);

[~,idx] = min(SzRD);

RetainData = NewDataset(any(RetainDataLv,idx)) % Return Desired Subset OF 'Data'

RetainData = 10289×1

100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000

LD = load(websave('histogram','https://www.mathworks.com/matlabcentral/answers/uploaded_files/1272595/histogram.mat'));

Data = LD.ans(:);

h=histogram(Data,10000,"BinMethod","sturges",'BinWidth',1,'BinLimits',[1 10000]);

[N,Edges,Bin] = histcounts(Data,10000,"BinMethod","sturges",'BinWidth',1,'BinLimits',[1 10000]);

Retain = N > max(N)/3; % Retain Values In Bins Greater Than One-Third Of The Meximum Bin Count Value

FindBins = find(Retain)

FindBins = 1×2

14 15

RetainDataLv = (Bin == FindBins); % Values In 'Bin' Corresponding To 'Retain' Test

SzRD = size(RetainDataLv)

SzRD = 1×2

8839 2

[~,idx] = min(SzRD);

RetainData = Data(any(RetainDataLv,idx)) % Return Desired Subset OF 'Data'

RetainData = 7464×1

15.0200 15.0100 14.9800 15.0100 15.0000 15.0150 14.9950 15.0050 15.0050 15.0050

This appears to work.

.

Med Future 2023-1-27

在 MATLAB Online 中打开

secondata.mat

@Star Strider @Image Analyst Same Error with secondata

Can you please solve this

Arrays have incompatible sizes for this operation.

Data=NewData;
h=histogram(Data,10000,"BinMethod","sturges",'BinWidth',1,'BinLimits',[1 10000]);
[N,Edges,Bin] = histcounts(Data,10000,"BinMethod","sturges",'BinWidth',1,'BinLimits',[1 10000]);
Retain = N > max(N)/3;                                          % Retain Values In Bins Greater Than One-Third Of The Meximum Bin Count Value
FindBins = find(Retain)
RetainDataLv = (Bin == FindBins);                               % Values In 'Bin' Corresponding To 'Retain' Test
SzRD = size(RetainDataLv)
[~,idx] = min(SzRD);
RetainData = Data(any(RetainDataLv,idx)) 

Star Strider 2023-1-27

在 MATLAB Online 中打开

You need to force ‘Data’ to be a column vector to work with my code, using the ‘(:)’ operator:

Data=NewData(:);

I decided to do this to make my code compatible with all the data sets, since some are row vectors and some are coliumn vectors.

Try this —

LD = load(websave('secondata','https://www.mathworks.com/matlabcentral/answers/uploaded_files/1275815/secondata.mat'));

Data = LD.NewData(:) % Force Column Vector

Data = 16075×1

100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000

h=histogram(Data,10000,"BinMethod","sturges",'BinWidth',1,'BinLimits',[1 10000]);

[N,Edges,Bin] = histcounts(Data,10000,"BinMethod","sturges",'BinWidth',1,'BinLimits',[1 10000]);

Retain = N > max(N)/3; % Retain Values In Bins Greater Than One-Third Of The Meximum Bin Count Value

FindBins = find(Retain)

FindBins = 1×5

99 100 150 200 250

RetainDataLv = (Bin == FindBins); % Values In 'Bin' Corresponding To 'Retain' Test

SzRD = size(RetainDataLv);

[~,idx] = min(SzRD);

RetainData = Data(any(RetainDataLv,idx)) % Return Desired Subset OF 'Data'

RetainData = 10289×1

100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000 100.0000

That should work with all the data vectors, regardless of whether their initial orientation is as row or column vectors.

.

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How to remove the value using Histogram

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How to remove the value using Histogram

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