I've got a problem with my function. It's supposed to take the signal and time data and output two vectors of the times of the maximums and the maxima signals. What I've done is try to use the findpeaks function to create a pks and locs array, then initialise a blank array the same size as the locs array and then use a for statement to go through and reassign the zeros with the time data of the maximas.
function [ max_times, max_signal ] = local_max(time_data, signal_data)
%Finds the local maximum of data
[pks, locs] = findpeaks(signal_data);
max_times = zeros(size(locs));
for n = 1:size(locs);
max_times(n) = max_signal(locs(n));
end
clear 'locs'
end
This is the error I get:
Error: File: local_max.m Line: 7 Column: 10
The expression to the left of the equals sign is not a valid target for an assignment.
I don't quite understand what it means/ how I can solve it. Anyone able to help?
The reason why you get an error is because max_signal is not defined when you use it. You probably want:
max_times(n) = time_data(locs(n));
Also, looping is unnecessary. You can simply do:
[pks, locs] = findpeaks(signal_data);
max_times = time_data(locs);
The reason is that size(locs) will return [1, n], not a number. So you need to change
for n = 1:size(locs);
to
for n = 1:numel(locs);
Related
I have a vector Cycle() that can contain several elements with a variable size.
I want to extract from this vector all the values which are in the odd columns, i.e. Cycle(1), Cycle(3), Cycle(5) ... and save them into a new vector Rcycle.
That's my code:
Rcycle = zeros(1, length(cycle)/2);
Rcycle(1) = cycle(1);
for j=3:length(cycle);
for i=2:length(Rcycle);
Rcycle(i) = cycle(j);
j = j+2;
end
end
Also I want to extract from Cycle() the even columns and save them in a vector Lcycle. My code:
Lcycle = zeros(1, length(cycle)/2);
Lcycle(1) = cycle(2);
for k=4:length(cycle);
for i=2:length(cycle);
Lcycle(i) = cycle(k);
k = k+2;
end
end
By running this for a sample Cycle() with 12 elements I get the right results for Lcycle, but the wrong ones for Rcycle. Also I get the error that my matrix have exceeded its dimension.
Has anyone any idea how to solve this in a more smooth way?
Use vector indexing!
Rcyle=cycle(1:2:end); %// Take from cycle starting from 1, each 2, until the end
Lcycle=cycle(2:2:end);%// same, but start at 2.
I am working on a code to extract my AR(1)-GARCH(1) parameter, which I estimated using an AR(1)-GJR(1,1) model to individual matrices so that I can use them as variables in my calculations. As I have 16 time series variables, I combine the code with a loop in the following way:
for i=1:nIndices
AA_ARCH(:,i) = cell2mat(fit{i}.Variance.ARCH)';
end;
My problem is that for some variables is are no for AA_ARCH(:,i) the dimension is lower than nIndices. Naturally, when I try to export the estimates in the loop which specified the dimension of (:,i) and nIndices matlab reports a dimension mismatch. I would like to tell Matlab to replace the NaN with 0 instead of leaving the spot empty so that it is able to produce a (1,nIndices) matrix from AA_ARCH.
I thought of something like the this:
fit{i}.Variance.Leverage(isnan(fit{i}.Variance.Leverage))=0
but I wasn't able to combine this part with the previous code.
I would be very happy about any hints!
Best, Carolin
UPDATE:
Here is a fully a runnable version of my code which produces my problem. Notice that the code produces a dimension mismatch error because there is no ARCH and GARCH estimate in the fit.gjr(1,1) for time series 1. For these missing values I would like to have 0 as a placeholder in the extracted matrix.
returns = randn(2,750)';
T = size(returns,1);
nIndices = 2;
model = arima('AR', NaN, 'Variance', gjr(1,1));
residuals = NaN(T, nIndices);
variances = NaN(T, nIndices);
fit = cell(nIndices,1);
options = optimset('fmincon');
options = optimset(options, 'Display' , 'off', 'Diagnostics', 'off', ...
'Algorithm', 'sqp', 'TolCon' , 1e-7);
for i = 1:nIndices
fit{i} = estimate(model, returns(:,i), 'print', false, 'options', options);
[residuals(:,i), variances(:,i)] = infer(fit{i}, returns(:,i));
end
for i=1:nIndices
AA_beta(:,i) = cell2mat(fit{i}.AR)';
AA_GARCH(:,i) = cell2mat(fit{i}.Variance.GARCH)';
AA_ARCH(:,i) = cell2mat(fit{i}.Variance.ARCH)';
AA_Leverage(:,i) = cell2mat(fit{i}.Variance.Leverage)';
end;
I have some general things to say about the code, but first a solution to your problem:
You can put a simple if/else structure in your loop to handle the case of an empty array:
for ind1=1:nIndices
AA_beta(:,ind1) = cell2mat(fit{ind1}.AR)'; %//'
%// GARCH
if isempty(cell2mat(fit{ind1}.Variance.GARCH)') %//'
AA_GARCH(1,ind1) = 0;
else
AA_GARCH(:,ind1) = cell2mat(fit{ind1}.Variance.GARCH)'; %//'
end
%// ARCH (same exact code, should probably be exported to a function)
if isempty(cell2mat(fit{ind1}.Variance.ARCH)') %//'
AA_ARCH(1,ind1) = 0;
else
AA_ARCH(:,ind1) = cell2mat(fit{ind1}.Variance.ARCH)'; %//'
end
AA_Leverage(:,ind1) = cell2mat(fit{ind1}.Variance.Leverage)'; %//'
end;
Side note: I initially tried something like this: soz = #(A)isempty(A)*0+~isempty(A)*A; as an inline replacement for the if/else, but it turns out that MATLAB doesn't handle [] + 0 the way I wanted (it results in [] instead of 0; unlike other languages like JS).
As for the other things I have to say:
I am a firm supporter of the notion that one shouldn't use i,j as loop indices, as this may cause compatibility problems in some cases where complex numbers are involved (e.g. if you loop index is i then 1*i now refers to the loop index instead of to the square root of -1).
Part of your problem was that the arrays you were writing into weren't preallocated - which also means the correct datatype was unknown to MATLAB at the time of their creation. Besides the obvious performance hit this entails, it could also result in errors like the one you encountered here. If, for example, you used cells for AA_beta etc. then they could contain empty values, which you could later replace with whichever placeholder your heart desired using a combination of cellfun and isempty. Bottom line: lint (aka the colorful square on the top right of the editor window) is your friend - don't ignore it :)
I was trying to plot function return values, one based on another. My function definition is:
function [final_speed, voltage] = find_final_speed(simulink_output)
As you can see, it returns two variables. I need a matrix that looks like this:
final_speed_1 voltage_1
final_speed_2 voltage_1
final_speed_3 voltage_1
final_speed_4 voltage_1
final_speed_5 voltage_1
In the end, voltages should be plotted on X axis, speeds on Y axis.
I originally tried this:
speedpervoltage = [find_final_speed(DATA_1); find_final_speed(DATA_2); ... ];
But that would only result in this matrix, all voltage info gone:
final_speed_1
final_speed_2
...
After all google searches and attempts failed, I did this:
[s1 v1] = find_final_speed(DATA_1);
[s2 v2] = find_final_speed(DATA_2);
[s... v...] = find_final_speed(DATA_...);
speedpervoltage = [0 0;s1 v1;s2 v2;s... v....;];
% Just contains the figure call along with graph properties.
plot_speedpervoltage(speedpervoltage);
This is really not optimal or practical solution. How can I do this more dynamically? Ideally, I'd like to have function create_speedpervoltage which would take array of data matrixes as argument:
plot_speedpervoltage(create_speedpervoltage([DATA_1 DATA_2 ...]));
if you know how many datasets you have, you encapsulate everything in a for loop like this:
Data = [DATA_1, DATA_2,....DATA_N] ;
outMat = [] ;
for i = 1 : length (Data)
[s v] = find_final_speed(Data(i));
outMat = [outMat ; s,v]
end
There is an easy way of doing this in Matlab. This answer is different from User1551892's answer because it doesn't dynamically reallocate the variable thus resulting in faster performance. The code is as follows.
% Declare Return Vectors
final_speed = zeros(20,1);
voltage = zeros(20,1);
% Loop through each data point
for i = 1: length( data )
[final_speed(i,:),voltage(i,:)] = find_final_speed( data(i) );
end
Now this assumes that data is a vector with each element corresponding to final and voltage speeds.
EDIT:
Another method to improve the speed even more is using arrayfun. Assuming your data is 1D, by feeding in the function as a handle into arrayfun, you can replace the 3 line loop with this line and preallocation with this code, which should give you even better performance and less lines.
[final_speed,voltage] = arrayfun( #find_final_speed, data );
Here is a solution with cellfun.
[s, v] = cellfun(#find_final_speed, [{DATA_1}, {DATA_2},... {DATA_N}]);
speedpervoltage = [s(:) v(:)];
I have the following piece of code:
for query = queryFiles
queryImage = imread(strcat('Queries/', query));
queryImage = im2single(rgb2gray(queryImage));
[qf,qd] = vl_covdet(queryImage, opts{:}) ;
for databaseEntry = databaseFiles
entryImage = imread(databaseEntry.name);
entryImage = im2single(rgb2gray(entryImage));
[df,dd] = vl_covdet(entryImage, opts{:}) ;
[matches, H] = matchFeatures(qf,qf,df,dd) ;
result = [result; query, databaseEntry, length(matches)];
end
end
It is my understanding that it should work as a Java/C++ for(query:queryFiles), however the query appears to be a copy of the queryFiles. How do I iterate through this vector normally?
I managed to sort the problem out. It was mainly to my MATLAB ignorance. I wasn't aware of cell arrays and that's the reason I had this problem. That and the required transposition.
From your code it appears that queryFiles is a numeric vector. Maybe it's a column vector? In that case you should convert it into a row:
for query = queryFiles.'
This is because the for loop in Matlab picks a column at each iteration. If your vector is a single column, it picks the whole vector in just one iteration.
In MATLAB, the for construct expects a row vector as input:
for ii = 1:5
will work (loops 5 times with ii = 1, 2, ...)
x = 1:5;
for ii = x
works the same way
However, when you have something other than a row vector, you would simply get a copy (or a column of data at a time).
To help you better, you need to tell us what the data type of queryFiles is. I am guessing it might be a cell array of strings since you are concatenating with a file path (look at fullfile function for the "right" way to do this). If so, then a "safe" approach is:
for ii = 1:numel(queryFiles)
query = queryFiles{ii}; % or queryFiles(ii)
It is often helpful to know what loop number you are in, and in this case ii provides that count for you. This approach is robust even when you don't know ahead of time what the shape of queryFiles is.
Here is how you can loop over all elements in queryFiles, this works for scalars, row vectors, column vectors and even high dimensional matrices:
for query = queryFiles(:)'
% Do stuff
end
Is queryFiles a cell array? The safest way to do this is to use an index:
for i = 1:numel(queryFiles)
query = queryFiles{i};
...
end
I'm trying to write some code to calculate a cumulative distribution function in matlab. When I try to actually put my results into an array it yells at me.
tempnum = ordered1(1);
k=2;
while(k<538)
count = 1;
while(ordered1(k)==tempnum)
count = count + 1;
k = k + 1;
end
if(ordered1(k)~=tempnum)
output = [output;[(count/537),tempnum]];
k = k + 1;
tempnum = ordered1(k);
end
end
The errors I'm getting look like this
??? Error using ==> vertcat
CAT arguments dimensions are not consistent.
Error in ==> lab8 at 1164
output = [output;[(count/537),tempnum]];
The line to add to the output matrice was given to me by my TA. He didn't teach us much syntax throughout the year so I'm not really sure what I'm doing wrong. Any help is greatly appreciated.
If you're building the matrix output from scratch, you should make sure it hasn't already been initialized to anything. To do this, you can set it to the empty matrix at the beginning of your code:
output = [];
Also, if you know how large output is going to be, your code will run more efficiently if you preallocate the array output and index into the array to assign values instead of appending values to it. In your case, output should have the same number of rows as there are unique values in the array ordered1, so you could use the function UNIQUE to preallocate output:
nRows = numel(unique(ordered1)); %# Get the number of unique values
output = zeros(nRows,2); %# Initialize output
You would then have to keep a separate counter (say r) to track which index into output you will be adding to next:
...
output(r,:) = [count/537 tempnum]; %# Overwrite a row in output
r = r+1; %# Increment the row index
...
Some additional advice...
Even if you solve the error you are getting, you're going to run into more with the code you have above:
I believe you are actually computing a probability density function (or PDF) with your code. In order to get the cumulative distribution function (or CDF), you have to perform a cumulative sum over the final values in the first column of output. You can do this with the function CUMSUM:
output(:,1) = cumsum(output(:,1));
Your loop will throw an error when it reaches the last element of ordered1. The value of k can become 538 in your inner while loop, which will then cause an error to be thrown when you try to access ordered1(k) anywhere. To get around this, you will have to add checks to the value of k at a number of points in your code. One such point is your inner while loop, which can be rewritten as:
while (k <= 537) && (ordered1(k) == tempnum)
count = count + 1;
k = k + 1;
end
This solution uses the short-circuit AND operator &&, which will first check if (k <= 537) is true or false. If it is false (i.e. k > 537), the second logical check is skipped since its result doesn't matter, and you avoid the error that would result from evaluating ordered1(k).
Bonus MATLAB coolness...
MATLAB has a lot of cool functions that can do a lot of the work for you. One such function is ACCUMARRAY. Your TA may want you to do things using loops like you have above, but you can actually reduce your whole code to just a few lines like so:
nValues = numel(ordered1); %# Get the number of values
p = accumarray(ordered1,ones(size(ordered1)))./nValues; %# Create a PDF
output = [cumsum(p) unique(ordered1)]; %# Create the CDF output