I have the following data that I wish to plot in a bar graph in MatLab:
publications = [15 12 35 12 19 14 21 15 7 16 40 28 6 13 16 6 7 22 23 16 45];
bar(publications,0.4)
set(gca,'XTickLabel',{'G1','G2','G3','G4','G5','G6','G7','G8','G9','G10',...
'G11','G12','G14','G16','G17','G18','G19','G20','G21','G22','G23'})
However, when I execute this, I get the following plot:
Obviously the x-label is incorrect here as the first bar should have the x-label 'G1', the second should have 'G2', etc, until we get to the last bar which is supposed to have 'G23'.
If anyone knows how I can fix this, I would really, really appreciate it!
Add the following line:
set(gca,'XTick',1:numel(publications))
before you set the labels.
Now it depends how big your resulting plot is, because the labels are a little packed.
You may adjust fontsize or Orientation or the gaps between the bars.
Probably the publication names are a little longer so a 90° rotation is the best and you may find this answer or this link helpful.
Another suggestion would be to use barh and rotate after print:
publications = [15 12 35 12 19 14 21 15 7 16 40 28 6 13 16 6 7 22 23 16 45];
bh = barh(publications,0.4)
set(gca','XAxisLocation','top')
set(gca,'YTick',1:numel(publications))
set(gca,'YTickLabel',{'G1','G2','G3','G4','G5','G6','G7','G8','G9','G10',...
'G11','G12','G14','G16','G17','G18','G19','G20','G21','G22','G23'})
Related
I am using fminsearch to fit parameters for a system of DEs to observed data. I am not expecting to get a great fit.
fminsearch pretty quickly finds what appears to be an acceptable min for the objective function, but then does not stop. It's running for a really long time, and I cannot figure out why.
I am using the options
options = optimset('Display','iter','TolFun',1e-4,'TolX',1e-4,'MaxFunEvals',1000);
which I understood to mean that when the value of the objective function drops to below 1e-4 that would be considered sufficient. Alternatively when they could no longer change the parameters whatever is the best would be returned.
The output is
Iteration Func-count min f(x) Procedure
0 1 8.13911e+10
1 8 7.2565e+10 initial simplex
2 9 7.2565e+10 reflect
3 10 7.2565e+10 reflect
4 11 7.2565e+10 reflect
5 12 7.2565e+10 reflect
6 13 7.2565e+10 reflect
7 15 6.85149e+10 expand
8 16 6.85149e+10 reflect
9 17 6.85149e+10 reflect
10 19 6.20681e+10 expand
11 20 6.20681e+10 reflect
12 22 5.55199e+10 expand
13 23 5.55199e+10 reflect
14 25 4.86494e+10 expand
15 26 4.86494e+10 reflect
16 27 4.86494e+10 reflect
17 29 3.65616e+10 expand
18 30 3.65616e+10 reflect
19 31 3.65616e+10 reflect
20 33 2.82946e+10 expand
21 34 2.82946e+10 reflect
22 36 2.02985e+10 expand
23 37 2.02985e+10 reflect
24 39 1.20011e+10 expand
25 40 1.20011e+10 reflect
26 41 1.20011e+10 reflect
27 43 5.61651e+09 expand
28 44 5.61651e+09 reflect
29 45 5.61651e+09 reflect
30 47 2.1041e+09 expand
31 48 2.1041e+09 reflect
32 49 2.1041e+09 reflect
33 51 5.15751e+08 expand
34 52 5.15751e+08 reflect
35 53 5.15751e+08 reflect
36 55 7.99868e-05 expand
37 56 7.99868e-05 reflect
38 58 7.99835e-05 reflect
39 59 7.99835e-05 reflect
I have previously let this run for a lot longer and it's stuck with the same min f(x) for at least the next 30 print outs.
How do I set the options correctly so that when it finds a solution within an acceptable value for the objective function it stops?
Matlab requires that both TolX AND TolFun be satisfied before terminating ("Unlike other solvers, fminsearch stops when it satisfies both TolFun and TolX." See: https://www.mathworks.com/help/matlab/ref/fminsearch.html). You should check what the "x" value (your solution) is doing. I suspect that is changing more than your tolerance specification for each step. (i.e. the value of x is changing more than TolX between iterations but f(x) is not changing by more than TolFun).
I have read quite a lot about LibSVM library, but I would like to ask you for some advices in my particular case. The problem is that I have some 3D medical images (DCE-MRI) of a stomach. My goal is to perform a segmentation of a kidney, and find its three parts. Therefore, I need to train a classifier - I'm going to use SVM and neural network
Feature vectors:
What is available is the pixel (voxel) brightness value (I guess the value range is [0; 511]). In total, there are 71 frames, each taken every second. So the crucial feature of every voxel is how the voxel brightness/intensity is changing during the examination time. In my case, every part of a kidney has a different chart (see an example below), so the way how the voxels brightness is changing over the time will be used by the classifier.
Training sets:
Every training set is a vector of intensity value of one voxel (74 numbers). An example is presented below:
[22 29 21 7 19 12 23 25 33 28 25 5 21 18 27 21 11 11 26 12 12 31 15 15 12 29 17 34 30 11 12 24 35 28 27 26 29 22 15 23 24 14 14 37 241 313 350 349 382 402 333 344 332 366 339 383 383 379 394 398 402 357 346 379 365 376 366 365 360 363 376 383 389 385]
Summary and question to you:
I have many training sets consisting of 74 values from the range [0; 511]. I have 3 groups of voxels, which have a characteristic feature - the brightness is changing in the similar way. What I want to obtain is a classificator, which after getting one voxel vector with 74 numbers, will assess if the voxel belongs to one of these 3 groups, or to none of them.
Question: how to start with LibSVM, any advices? From what I know now is that I should transform input values to be from the range [0; 1] or [-1; 1]. I have many training sets prepared belonging to one of these 3 groups. I will be grateful for any advice, as I'm a newbie and I just need some tips just to start.
You can train and use you model like this:
model=svmtrain(train_label,train_feature,'-c 1 -g 0.07 -h 0');
% the parameters can be modified
[label, accuracy, probablity]=svmpredict(test_label,test_feaure,model);
train_label must be a vector,if there are more than two kinds of input(0/1),it will be an nSVM automatically. If you have 3 classes, you can label them using {1,2,3}.Its length is equal to the number of samples.
The feature is not restricted. It can be what ever you want.
However, you'd better preprocess them to make the results better. For example, you can change range[0:511] to range[0:1] or minus the mean of the feature.
Notice that the testset data should be preprocessed in the same way.
Hope this will help you!
What I would like to do is create a choropleth map which is darker or lighter based on the number of data points in a particular area.
I have the following data:
RO-B, 9
PL-MZ, 24
SE-C, 3
DE-NI, 5
PL-DS, 14
ES-CM, 11
RO-IS, 2
DE-BY, 51
SE-Z, 18
CH-BE, 10
PL-WP, 1
ES-IB, 1
DE-BW, 21
DE-BE, 24
DE-BB, 1
IE-M, 26
ES-PV, 1
DE-SN, 6
CH-ZH, 31
ES-GA, 1
NL-GE, 2
IE-U, 1
ES-AN, 4
FR-J, 82
DE-HH, 34
PL-PD, 1
PL-LD, 6
GB-WLS, 60
GB-ENG, 8619
RO-BV, 45
CH-VD, 2
PL-SL, 1
DE-HE, 17
SE-I, 1
HU-PE, 4
PL-MA, 4
SE-AB, 3
CH-BS, 20
ES-CT, 31
DE-TH, 25
IE-C, 1
CZ-ST, 1
DE-NW, 29
NL-NH, 3
DE-RP, 9
CZ-PR, 4
IE-L, 134
HU-BU, 10
RO-CJ, 1
GB-NIR, 29
ES-MD, 33
CH-LU, 11
GB-SCT, 172
CH-GE, 3
BE-BRU, 30
BE-VLG, 25
It references the ISO3166-2 of a country and sub region, and the # corresponds to the amount of data points affiliated with that region.
I've seen this project on GitHub which seems to also use the same ISO3166-2 to reference countries.
I'm trying to figure out how I could modify their code to display my data points, such that if the number is higher the area would be darker, if the number is less it would be lighter.
It seems it should be possible, the first thing I was trying to do was modify this jsfiddle code, which seems to be very close to what I need, but I couldn't get it to work.
For instance this line:
osmeRegions.geoJSON('RU-MOW',
Seems to directly reference a ISO3166-2 code, but it's not as simple as just changing that (or maybe it is but I couldn't get that to work properly).
Does anyone know if I could possibly adapt the code from that project to create the map rendering I've described?
Or perhaps there's a different way to achieve the same goal?
I have a Matrix I like to put in a bar chart. This works, however the x-axis is not periodic, it follows the following numbers:
1 2 3 4 5 6 7 8 9 10 12 14 16 18 20 22 24 26 28 30 35 40 45 50 55 60 70 80 90
These values are stored in the variable Batchsizes, the Matrix is stored in the variable valuable
I use the following code:
figure;
bar(Batchsizes,valuable);
set(gca,'Xtick',Batchsizes(1:length(Batchsizes)));
The following output is generated:
As you can see, the graph is crowded on the left and wide on the right. I would like to have the bar groups evenly distributed over the x-axis so that the graph is evenly spaced while preserving the old x-labels.
Any help is really appreciated.
Remember the answer to your previous question? This is exactly the case when you do want to use XTickLabel (because now the ticks will be positioned at 1:1:29 but you want labels to have the values Batchsizes(1),Batchsizes(2),...). Here's one way to do it:
Batchsizes = [1:9, 10:2:28 30:5:55 60:10:90];
valuable = randi(35,numel(Batchsizes),3);
figure; bar(1:numel(Batchsizes),valuable);
set(gca,'XTick',1:numel(Batchsizes),...
'XTickLabel',cellstr(num2str(Batchsizes.')));
The result is:
I just started working with Breeze in Scala and I am trying to figure out how to extract columns from a DenseMatrix where the column indexes that I want to extract are in a list. For example, if you want to extract column 1,3 and 6 from a numpy array myArrayin Python you can write
myArray[:,[1,3,6]]
In Breeze I have tried something similar
myArray(::,(1,3,6))
but it creates a syntax error. I have looked at the Breeze Linear Algebra Cheat Sheet and but I only see the functionality to extract individual columns or contiguous columns. Is there any way to directly specify the columns that I want to extract as in my example?
I had the same problem; the fix that I found was to import numerics as well as linalg from breeze:
import breeze.numerics._
It's mentioned at the top of the cheat sheet you found, but it's very easy to miss, especially if you've searched for a particular operation (what happened to me).
We assign a dense matrix "dm" with the following contents:
import breeze.linalg._
val dm = DenseMatrix((0,1,2,3,4,5,6,7),
(8,9,10,11,12,13,14,15),
(16,17,18,19,20,21,22,23),
(24,25,26,27,28,29,30,31))
dm
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 30 31
If we want to extract columns of a matrix (e.g. 1,3,6), we could extract a part of matrix with columns indexing
dm(::,IndexedSeq(1,3,6))
1 3 6
9 11 14
17 19 22
25 27 30
or rows indexing
dm(IndexedSeq(1,3),::)
8 9 10 11 12 13 14 15
24 25 26 27 28 29 30 31
Thank you. Please feel free to comment