I seem to have the strange problem that when I plot the following, the bars of the two histograms do not seem to have the same width:
hold on
[N,X] = hist(feature_1(:,1))
Bh = bar(X,N,'facecolor',[0.7 0.2 0.2]);
[A,Y] = hist(feature_2(:,1))
Bh = bar(Y,A,'facecolor',[0.3 0.6 0.2]);
hold off
Why is that?
Thanks
Edit: Sorry for not providing input.
For instance, feature_1(:,1:5) =
[0.72507334
0.019627856
0.19571847
-0.23818338
1.6526113
0.23925941
0.69914567
0.15934853
0.28082907
-0.035707321
0.072205774
-0.15791744
0.81654513
0.19398287
-0.33666527
-0.24295111
-1.0770919
-1.2977802
0.67290813
-0.56841594
-0.28522778
-2.2450733
-1.4413888
-2.2216258
-0.46346179
1.8239603
1.6443830
1.3715266
0.34339836
-0.29903534]
and feature_2(:,1) =
[0.18098037
-0.81469119
-0.086869463
-0.67799056
1.1408544
1.2589806
1.0065788
0.64472252
-0.70849174
0.69045025
-0.0031675443
-0.82824785
0.15744546
-0.028384065
-0.065391541
-0.35754660
-1.0809286
-0.12427557
1.3792992
-0.28740802
1.7593855
-1.2061185
-3.0156419
-1.1680259
0.23381938
0.97127295
0.91487378
0.83101124
0.24949571
-0.96599007]
MATLAB suggests you use histogram() instead of hist().
If I had to guess why your bars are of different widths, it would be because you have different numbers of bins for each histogram, though don't take my word for it. (It also could be a stylistic thing, where the bars are offset so that you can see both colors, as hist() does not blend like histogram() does.)
You can solve the width problem by specifying the width using histogram():
histogram(feature_1(:,1:5),'BinWidth',.5);
hold on
histogram(feature_2(:,1),'BinWidth',.5);
If you run this code, you'll be able to see the differences in plotting styles:
subplot(2,1,1)
hold on
[N,X] = hist(feature_1(:,1:5));
Bh = bar(X,N,'facecolor',[0.7 0.2 0.2]);
[A,Y] = hist(feature_2(:,1));
Bh = bar(Y,A,'facecolor',[0.3 0.6 0.2]);
subplot(2,1,2)
histogram(feature_1(:,1:5),'BinWidth',.5,'FaceColor','r');
hold on
histogram(feature_2(:,1),'BinWidth',.5,'FaceColor','g');
Hope this helped somewhat!
I don't get the purpose but width is same for both, the bins are different. If you want to show both in a same figure for comparison purpose, then you must adapt this way
bar([X',Y'])
xlable('-->No of bins')
legend('Feature1','Feature2')
Related
Using Octave 4.2.1 on Windows with the qt graphics toolkit (I can't use gnuplot because it crashes in some other part of the code). I have a dataset which is 35x7x4 (35 data points for 7 conditions on 4 channels) - you can use random data for the purpose of this exercise.
I am trying to create 4 subplots (1 for each channel), with 7 bar graphs on each subplot (one per condition) to see how the distribution of data changes with each condition. Each of the 7x4 = 28 distributions has its own set of bins and frequencies, and I can't seem to be able to combine the 7 datasets on one graph (subplot).
Posting the whole of the code would be too complicated, but here's a simplified version:
nb_channels = 4;
nb_conditions = 7;
nbins = 15;
freq = zeros(nbins,nb_conditions,nb_channels);
xbin = zeros(nbins,nb_conditions,nb_channels);
plot_colours = [91 237 165 255 68 112 255;
155 125 165 192 114 173 0;
213 49 165 0 196 71 255];
plot_colours = plot_colours / 255;
for k = 1:nb_channels
for n = 1:nb_conditions
% some complex calculations to generate temp variable
[freq(:,n,k),xbin(:,n,k)] = hist(temp,nbins);
end
end
figure
for k = 1:nb_channels
subplot(2,2,k)
for n = 1:nb_conditions
bar(xbin(:,n,k),freq(:,n,k),'FaceColor',plot_colours(:,n))
hold on
end
hold off
legend('condition #1','condition #2','condition #3','condition #4','condition #5','condition #6','condition #7')
end
which gives something like this:
So you can't really see anything, all the bars are on top of each other. In addition, Octave doesn't support transparency property for patch objects (which is what bar charts use), so I can't overlay the histograms on top of each other, which I would really quite like to do.
Is there a better way to approach this? It seems that bar will only accept a vector for x data and not a matrix, so I am stuck in having to use hold on and loop through the various conditions, instead of using a matrix approach.
OK, so I'll try to answer my own question based on the suggestions made in the comments:
Suggestion 1: make all the bins the same
This does improve the results somewhat but it's still an issue due to the lack of transparency for patch objects.
Code changes:
nbins = 15;
xbin = linspace(5.8,6.5,nbins);
for k = 1:nb_channels
for n = 1:nb_conditions
% some complex calculations to generate temp variable
freq_flow(:,n,k) = hist(temp,xbin);
end
end
figure
for k = 1:nb_channels
subplot(2,2,k)
for n = 1:nb_conditions
bar(xbin,freq_flow(:,n,k),'FaceColor',plot_colours(:,n))
hold on
end
hold off
xlim([5.8 6.3])
legend('condition #1','condition #2','condition #3','condition #4','condition #5','condition #6','condition #7')
end
Which gives the following plot:
Suggestion 2: Use line plots instead of bar charts
This helps a bit more in terms of readability. However, the result is a bit "piece-wise".
Code changes:
figure
for k = 1:nb_channels
subplot(2,2,k)
for n = 1:nb_conditions
plot(xbin,freq_flow(:,n,k),'LineStyle','none','marker','.',...
'markersize',12,'MarkerEdgeColor',plot_colours(:,n),...
'MarkerFaceColor',plot_colours(:,n))
hold on
end
hold off
xlim([5.8 6.3])
legend('condition #1','condition #2','condition #3','condition #4','condition #5','condition #6','condition #7')
end
Which gives the following result:
The legend is a bit screwed but I can probably sort that out.
A variation on this I also tried was to plot just the points as markers, and then a fitted normal distribution on top. I won't post all the code here, but the result looks something like this:
Suggestion 3: transparency workaround with gnuplot
Unfortunately, before I even got to the transparency workaround, gnuplot keeps crashing when trying to plot the figure. There's something it doesn't like with subplots and legends I think (which is why I moved to qt graphics toolkit in the first place, as I had exactly the same issue in other parts of the code).
Solution 4: use 3D bar graph
I found this on SO: 3D histogram with gnuplot or octave
and used it as such:
figure
for k = 1:size(flow_factor,2)
subplot(2,2,k)
h = my_bar3(freq_flow(:,:,k));
fvcd = kron((1:numel(freq_flow(:,:,k)))', ones(6,1));
set(h, 'FaceVertexCData',fvcd, 'FaceColor','flat', 'CDataMapping','scaled')
colormap hsv; axis tight; view(50,25)
ylbl = cell(length(xbin),1);
for k=1:length(xbin)
ylb{k} = num2str(xbin(k));
end
set(gca,'YTick',1:2:nbins);
set(gca,'YTickLabel',ylb(1:2:end));
end
to produce:
Which isn't bad, but probably not as clear as the line plots.
Conclusion
On balance, I will probably end up using one of the line plots approaches, as they tend to be clearer.
let us suppose we have following code
function plot_test(x,y)
x_constucted=[ones(size(x)) x];
b = regress(y,x_constucted);
y_predicted=b(1)+b(2)*x;
scatter(x,y);
hold on
plot(x,y_predicted);
theString = sprintf('y = %.3f*x+%.3f ', b(2), b(1));
text(x(1), y_predicted(1), theString, 'FontSize', 8);
end
output of this equation is the following figure
my question is : how to align equation out of line? for instance on top left size? thanks in advance
If I understand you correctly, you want to move the printed equation out of the dots. Check out the text() function description. The first two values define the x and y position in your plot for the text.
x=1;
y=25;
To move it up, use the new variables in text(x,y,...). Hope that helps.
Some time ago I was looking for a solution for the same exact problem. As you may know, the legend command allows to specify a Location parameter and one of its many options is called best, described in the official Matlab documentation (here) as follows:
Inside axes where least conflict occurs with plot data
My workaround abuses this feature in order to find the best location to place a single text annotation inside the plot. The code below uses a build-in dataset since you didn't specify how your data looks like:
load carsmall;
x = [ones(size(Horsepower)) Horsepower];
y = MPG;
b = regress(y,x);
y_hat = b(1) + b(2) .* Horsepower;
scatter(Horsepower,y);
hold on;
plot(Horsepower,y_hat);
text_at_best(sprintf('y = %.3f*x+%.3f ',b(2),b(1)),'FontSize',12);
function h = text_at_best(txt,varargin)
l = legend(txt,[varargin{:}]);
t = annotation('textbox',varargin{:});
t.String = txt;
t.Position = l.Position;
t.LineStyle = 'None';
delete(l);
if nargout
h = t;
end
end
Here is the final result:
I don't know if this can fit your needs... but developing an algorithm for finding a non overlapping part of the plot in which to place a text looked like an overkill to me. Despite the text being quite far from the prediction line, it's still elegant, clear and comprehensible. The same goes with an even quicker workaround which consists in setting the regression equation as the plot title (blink blink).
I have been trying to plot two vectors against some x values on the same graph. And I want to set the numerical x labels manually, as characters. But the final result looks weird.
vars = {'50', '100', '250', '500'};
inducing_p = linspace(1,4,4);
ind_table_mse = [0.9051 0.8911 0.8770 0.8688];
ind_table_mseF = [0.9155 0.9070 0.8796 0.8708];
plot(inducing_p, ind_table_mse);
hold on;
plot(inducing_p, ind_table_mseF);
title('ASA Flight Delay Dataset','interpreter','latex');
xlabel('Inducing points','interpreter','latex');
ylabel('MSE','interpreter','latex');
set(gca,'XTickLabel',vars);
xtickangle(45);
And I get this graph, which is not at all of what I indented. As, I would like to see only 50 100 250 500 labels on x. Any suggestions please?
You have first to modify the location of the ticks in your figure
figure
plot(inducing_p, ind_table_mse);
hold on;
plot(inducing_p, ind_table_mseF);
title('ASA Flight Delay Dataset','interpreter','latex');
xlabel('Inducing points','interpreter','latex');
ylabel('MSE','interpreter','latex');
set(gca,'XTick',[1 2 3 4]); %%%% HERE
set(gca,'XTickLabel',vars);
xtickangle(45);
The weird behavior is indeed due to the fact that you specify less labels than ticks. So Matlab just repeats them.
Im trying to write a code in Matlab to calculate an area of influence type question. This is an exert from my data (Weighting, x-coord, y-coord):
M =
15072.00 486.00 -292
13269.00 486.00 -292
12843.00 414.00 -267
10969.00 496.00 -287
9907.00 411.00 -274
9718.00 440.00 -265
9233.00 446.00 -253
9138.00 462.00 -275
8830.00 496.00 -257
8632.00 432.00 -253
R =
-13891.00 452.00 -398
-13471.00 461.00 -356
-12035.00 492.00 -329
-11309.00 413.00 -353
-11079.00 467.00 -375
-10659.00 493.00 -333
-10643.00 495.00 -338
-10121.00 455.00 -346
-9795.00 456.00 -367
-8927.00 485.00 -361
-8765.00 467.00 -351
I want to make a function to calculate the sum of the weightings at any given position based on a circle of influence of 30 for each coordinate.
I have thought of using a for loop to calculate each point independently and summing the result but seems unnecessarily complicated and inefficient.
I also thought of assigning an intensity of color to each circle and overlaying them but I dont know how to change color intensity based on value here is my attempt so far (I would like to have a visual of the result):
function [] = Influence()
M = xlsread('MR.xlsx','A4:C310');
R = xlsread('MR.xlsx','E4:G368');
%these are my values around 300 coordinates
%M are negative values and R positive, I want to see which are dominant in their regions
hold on
scatter(M(:,2),M(:,3),3000,'b','filled')
scatter(R(:,2),R(:,3),3000,'y','filled')
axis([350 650 -450 -200])
hold off
end
%had to use a scalar of 3000 for some reason as it isnt correlated to the graph size
I'd appreciate any ideas/solutions thank you
This is the same but with ca. 2000 data points
How about this:
r_influence = 30; % radius of influence
r = #(p,A) sqrt((p(1)-A(:,2)).^2 + (p(2)-A(:,3)).^2); % distance
wsum = #(p,A) sum(A(find(r(p,A)<=r_influence),1)); % sum where distance less than roi
% compute sum on a grid
xrange = linspace(350,550,201);
yrange = linspace(-200,-450,201);
[XY,YX] = meshgrid(xrange,yrange);
map_M = arrayfun(#(p1,p2) wsum([p1,p2],M),XY,YX);
map_R = arrayfun(#(p1,p2) wsum([p1,p2],R),XY,YX);
figure(1);
clf;
imagesc(xrange,yrange,map_M + map_R);
colorbar;
Gives a picture like this:
Is that what you are looking for?
I am using Matlab to fit some data in 2 coordinates (x,y) with a poly1 curve.
The problem is that I can't find a way to make the fitting line longer.
I need it from (180, 930) to (191, 944), but instead Matlab just draw the fitting line near the data, which is between those two coordinates.
Is there some argument to the fit command (or some preferences in the cftool) that can help me out?
Moreover, I've tried the "Adjust axes limits" option in the cftool, but it didn't help at all.
I've searched through the already asked questions, but I haven't found anything related to this.
I'm new to this program, therefore I'm sorry if this is a stupid question
Thanks in advance,
Giovanni
EDIT:
The code for the first image is:
[FitUp,goodnessUP] = fit(AKaterMatrix1msDX(:,1),AKaterMatrix1msDX(:,2),'poly1')
[FitDown,goodnessDOWN] = fit(AKaterMatrix1msDX(:,1),AKaterMatrix1msDX(:,3),'poly1')
plot(FitUp,'b')
hold on
plot(FitDown,'b')
hold on
errorbar(AKaterMatrix1msDX(:,1),AKaterMatrix1msDX(:,2),AKaterMatrix1msDX(:,4),'--r')
hold on
errorbar(AKaterMatrix1msDX(:,1),AKaterMatrix1msDX(:,3),AKaterMatrix1msDX(:,4),'--r')
The code for the second is:
[FitUp,goodnessUP] = fit(AKaterMatrix1msDX(:,1),AKaterMatrix1msDX(:,2),'poly1')
[FitDown,goodnessDOWN] = fit(AKaterMatrix1msDX(:,1),AKaterMatrix1msDX(:,3),'poly1')
plot(FitDown,'b')
hold on
plot(FitUp,'b')
hold on
errorbar(AKaterMatrix1msDX(:,1),AKaterMatrix1msDX(:,2),AKaterMatrix1msDX(:,4),'--r')
hold on
errorbar(AKaterMatrix1msDX(:,1),AKaterMatrix1msDX(:,3),AKaterMatrix1msDX(:,4),'--r')
Here you can find the two fits, it appears that the first fit is not cropped, while the second after the hold on is:
https://docs.google.com/file/d/0B749BCu7mnZHaEhITUZ1YzdfVDA/edit?usp=sharing
https://docs.google.com/file/d/0B749BCu7mnZHeDVTOGRuSkktUmc/edit?usp=sharing
You just need to be careful when and how you set the hold. First make some dummy data
AKaterMatrix1msDX(:, 1) = 185:189;
AKaterMatrix1msDX(:, 2) = 2*rand(5, 1)+933;
AKaterMatrix1msDX(:, 3) = 2*rand(5, 1)+940;
AKaterMatrix1msDX(:, 4) = 2*rand(5, 1);
Next, and this is the key part, set the axis to be what you want and turn hold on
figure
axis([180, 191, 930, 944]);
hold on
This do exactly what you did
[FitUp,goodnessUP] = fit(AKaterMatrix1msDX(:,1),AKaterMatrix1msDX(:,2),'poly1')
[FitDown,goodnessDOWN] = fit(AKaterMatrix1msDX(:,1),AKaterMatrix1msDX(:,3),'poly1')
plot(FitUp,'b')
hold on
plot(FitDown,'b')
hold on
errorbar(AKaterMatrix1msDX(:,1),AKaterMatrix1msDX(:,2),AKaterMatrix1msDX(:,4),'--r')
hold on
errorbar(AKaterMatrix1msDX(:,1),AKaterMatrix1msDX(:,3),AKaterMatrix1msDX(:,4),'--r')
If you don't need a lot of fit statistics, polyfit followed by polyval can give you your fit:
X = AKaterMatrix1msDX(:,1);
Y = AKaterMatrix1msDX(:,2);
dY = AKaterMatrix1msDX(:,4);
[a,S] = polyfit(X,Y)
extraPlotRange = 10;
newX = linspace(min(X)-extraPlotRange,max(X)+extraPlotRange,100);
[fitY,delta] = polyval(a,newX);
plot(X,Y)
hold on
plot(newX,fitY)
plot(newX,fitY+delta,':b')
plot(newX,fitY-delta,':b')
errorbar(X,Y,dY,'--r')
hold off
This will not, unfortunately, give you the same goodness of fit statistics that you might need, only the confidence intervals of the fit.
The other option, if you want to stay with fit, would be to get the fit coefficients using coeffvalues. Those fit coefficients would be the same as you get from polyfit.
aUp = coeffvalues(FitUp);
aDown = coeffValues(FitDown);
fitYup = polyval(aUp,newX);
fitYdown = polyval(aDown,newX);
etc.