Trying to remove Nans when plotting histogram, pdf and cdf

Question

Nathaniel Porter 2022-2-25

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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1658645-trying-to-remove-nans-when-plotting-histogram-pdf-and-cdf

评论： Nathaniel Porter 2022-2-26

InsulinReadings.mat

clear;
load InsulinReadings.mat
xX2 = InsulinReadings;
xX2(xX2==0)=missing;
A2 = mean(xX2,'all',"omitnan")
B2 = median(xX2,'all',"omitnan")
C2 = max(xX2,[],'all',"omitnan")
D2 = min(xX2,[],'all', "omitnan")
figure
histogram(InsulinReadings(~isnan(InsulinReadings),128,'Normalization')
Invalid expression. When calling a function or indexing a variable, use parentheses. Otherwise, check for mismatched delimiters.
xlabel('Insulin ng/dL')
%Now get pdf
[D PD] = allfitdist(xX2,'PDF');
xlabel('Insulin ng/dL');
%Now get the CDF
[D PD] = allfitdist(xGlucoseReadings,'CDF');
xlabel('Insulin ng/dL')

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Answer 1

Voss 2022-2-25

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https://ww2.mathworks.cn/matlabcentral/answers/1658645-trying-to-remove-nans-when-plotting-histogram-pdf-and-cdf#answer_904685

在 MATLAB Online 中打开

InsulinReadings.mat

I think you basically have it right. I just "fixed" a syntax error on the line where you call histogram(). ("fixed" is in quotes because I can't be sure what you're going for there.)

(Also, looks like allfitdist.m has been removed from the File Exchange, so I can't run it, but maybe your copy does the right thing here - I don't know.)

clear;

load InsulinReadings.mat

xX2 = InsulinReadings;

xX2(xX2==0)=missing;

A2 = mean(xX2,'all',"omitnan")

A2 = 296.9102

B2 = median(xX2,'all',"omitnan")

B2 = 86.4899

C2 = max(xX2,[],'all',"omitnan")

C2 = 1.0226e+04

D2 = min(xX2,[],'all', "omitnan")

D2 = 3.6900e-07

figure

histogram(InsulinReadings(~isnan(InsulinReadings)),128)%,'Normalization')

xlabel('Insulin ng/dL')

%Now get pdf

[D PD] = allfitdist(xX2,'PDF');

Unrecognized function or variable 'allfitdist'.

xlabel('Insulin ng/dL');

%Now get the CDF

[D PD] = allfitdist(xGlucoseReadings,'CDF');

xlabel('Insulin ng/dL')

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Voss 2022-2-25

在 MATLAB Online 中打开

InsulinReadings.mat

I see.

Well, they're not necessarily zeros, they're just values that fall within the first bin of the histogram (i.e., closer to zero than to the right edge of the second bin). I guess it makes sense to plot a histogram of xX2 rather than InsulinReadings since xX2 has the zeros replaced with NaNs (but you still get a lot of small values).

If you want to remove any value that would be in the first bin of the histogram, you have to know what your histogram edges are before creating the histogram (which is ok), or you could replace any value less than some threshold with a NaN (or a 0, then replace all the 0s with NaNs like you're already doing), but then you have to choose some threshold, so your histogram will depend on that choice.

clear;

load InsulinReadings.mat

xX2 = InsulinReadings;

nnz(xX2 == 0) % 41209 zeros

ans = 41209

nnz(isnan(xX2)) % 0 NaNs

ans = 0

xX2(xX2==0)=missing;

nnz(isnan(xX2)) % now 41209 NaNs

ans = 41209

figure

h = histogram(xX2(~isnan(xX2)),128);%,'Normalization')

xlabel('Insulin ng/dL')

% now make a new histogram with values in the first bin replaced with NaNs

edges = get(h,'BinEdges');

xX2(xX2 < edges(2)) = NaN;

figure();

h = histogram(xX2(~isnan(xX2)),128);%,'Normalization')

xlabel('Insulin ng/dL')

Voss 2022-2-25

在 MATLAB Online 中打开

InsulinReadings.mat

There probably are built-in functions, but I don't know what they are off the top of my head (maybe search the documentation).

It's relatively straighforward to calculate a PDF and CDF from the properties of the histogram:

clear;

load InsulinReadings.mat

xX2 = InsulinReadings;

xX2(xX2==0)=missing;

figure();

h = histogram(xX2(~isnan(xX2)),128);%,'Normalization')

% now make a new histogram with values in the first bin replaced with NaNs

edges = get(h,'BinEdges');

xX2(xX2 < edges(2)) = NaN;

figure();

h = histogram(xX2(~isnan(xX2)),128);%,'Normalization')

xlabel('Insulin ng/dL')

% pdf and cdf

figure();

edges = get(h,'BinEdges');

counts = get(h,'BinCounts');

bin_centers = (edges(1:end-1)+edges(2:end))/2;

total_counts = sum(counts);

pdf = counts/total_counts;

cdf = cumsum(counts)/total_counts;

plot(bin_centers,pdf,'LineWidth',2);

hold on

plot(bin_centers,cdf,'LineWidth',2);

xlim(bin_centers([1 end]));

legend('PDF','CDF');

Nathaniel Porter 2022-2-26

Okay thanks

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