so I have this array:
ab = 3
cd = 4
array = zeros(ab, cd);
which gives us an array looking like:
0 0 0 0
0 0 0 0
0 0 0 0
now I'd like to fill each line with certain values. I have two classes with two properties I substract from each other.
so the first entry in the first line should be computed by:
xxx = class1{1}.property - class2{1}.property
the second entry in the first line should be filled by:
xxx = class1{1}.property - class2{2}.property
third entry:
xxx = class1{1}.property - class2{3}.property
the first entry in the second line should be computed by:
xxx = class1{2}.property - class2{1}.property
I tried:
for cc = 1:ab
for hh = 1:cd
array(cc, hh) = class1{cc}.property - class2{hh}.property
end
end
However, matlab keeps telling me:"Subscripted assignment dimension mismatch."
I do understand what the problem means but I don't know how address it :/
edit:
the array should look like:
(class1{1}.property - class2{1}.property) (class1{1}.property - class2{2}.property)
(class1{2}.property - class2{1}.property) (class1{2}.property - class 2{2}.property)
As was said in comments, it's hard to know without more knowledge of the code, but it could be occurring because one or more of your class properties have more than one value. You could try something like the following to catch if the class properties are larger than 1 value.
for cc = 1:ab
for hh = 1:cd
temp = class1{cc}.property - class2{hh}.property;
if length(temp) > 1
keyboard
end
array(cc, hh) = temp;
end
end
The dimension mismatch error was due to me adding vectors (class1.property aswell as class2.property were vectors!)to each array entry.
Related
I have the following problem in my simulation.
A is an array 24 x 2. I am going to split it and get 4 or 12 array. It means that I group 6 or 2 array. It will be ok, if I use even "split" coefficient. If it is odd, I can"t split A.[ I can't group 5 or 7, because of 24/5=4*5 + 4 ( or 5*5 -1) or 24/7=7*3+3.
That's why I going to do the following:
If I have 24 x 2 and need group every 5 together:
block 1 : A(1,:), A(2,:),A(3,:),A(4,:),A(5,:)
block 2 : A(6,:), A(7,:),A(8,:),A(9,:),A(10,:)
block 3 : A(11,:), A(12,:),A(13,:),A(14,:),A(15,:)
block 4 : A(16,:), A(17,:),A(18,:),A(19,:),A(20,:)
block 5 : A(21,:), A(22,:),A(23,:),A(24,:), ?
As you can see the 5th block is not full, Matlab gives me an error. My idea is to create A(25,:)=0. For my simulation it will be ok.
I am going to simulate it as function:
A=rand(m,n)
w- # number of a vector that i would like group together ( in ex., it is `5`)
if mod(w,2)==0
if mod(m,2)==0
% do....
else
% remainder = 0
end
else
if mod(m,2)==0
% remainder = 0
else
%do...
end
I was going to simulate like above, but then I have noticed that it doesn't work. Because 24/10 = 2*10+4. So I should write something else
I can find the reminder as r = rem(24,5). As an example above, MatLab gives me r=4. then I can find a difference c= w-r =1 and after that, I don't know how to do that.
Could you suggest to me how to simulate such a calculation?
Determine the number of blocks needed, calculate the virtual amount of rows needed to fill these blocks, and add as many zero rows to A as the difference between the virtual and actual amount of rows. Since you didn't mention, what the actual output should look like (array, cell array, ...), I chose a reshaped array.
Here's the code:
m = 24;
n = 2;
w = 5;
A = rand(m, n)
% Determine number of blocks
n_blocks = ceil(m / w);
% Add zero rows to A
A(m+1:w*n_blocks, :) = 0
% Reshape A into desired format
A = reshape(A.', size(A, 1) / n_blocks * n, n_blocks).'
The output (shortened):
A =
0.9164959 0.1373036
0.5588065 0.1303052
0.4913387 0.6540321
0.5711623 0.1937039
0.7231415 0.8142444
0.9348675 0.8623844
[...]
0.8372621 0.4571067
0.5531564 0.9138423
A =
0.91650 0.13730
0.55881 0.13031
0.49134 0.65403
0.57116 0.19370
0.72314 0.81424
0.93487 0.86238
[...]
0.83726 0.45711
0.55316 0.91384
0.00000 0.00000
A =
0.91650 0.13730 0.55881 0.13031 0.49134 0.65403 0.57116 0.19370 0.72314 0.81424
0.93487 0.86238 0.61128 0.15006 0.43861 0.07667 0.94387 0.85875 0.43247 0.03105
0.48887 0.67998 0.42381 0.77707 0.93337 0.96875 0.88552 0.43617 0.06198 0.80826
0.08087 0.48928 0.46514 0.69252 0.84122 0.77548 0.90480 0.16924 0.82599 0.82780
0.49048 0.00514 0.99615 0.42366 0.83726 0.45711 0.55316 0.91384 0.00000 0.00000
Hope that helps!
I have a dataset as such:
Case #|DateA |Drug.1|Drug.2|Drug.3|DateB.1 |DateB.2 |DateB.3 |IV.1|IV.2|IV.3
------|------|------|------|------|--------|---------|--------|----|----|----
1 |DateA1| X | Y | X |DateB1.1|DateB1.2 |DateB1.3| 1 | 0 | 1
2 |DateA2| X | Y | X |DateB2.1|DateB2.2 |DateB2.3| 1 | 0 | 1
3 |DateA3| Y | Z | X |DateB3.1|DateB3.2 |DateB3.3| 0 | 0 | 1
4 |DateA4| Z | Z | Z |DateB4.1|DateB4.2 |DateB4.3| 0 | 0 | 0
For each case, there are linked variables i.e. Drug.1 is linked with DateB.1 and IV.1 (Indicator Variable.1); Drug.2 is linked with DateB.2 and IV.2, etc.
The variable IV.1 only = 1 if Drug.1 is the case that I want to analyze (in this example, I want to analyze each receipt of Drug "X"), and so on for the other IV variables. Otherwise, IV = 0 if the drug for that scenario is not "X".
I want to calculate the difference between DateA and DateB for each instance where Drug "X" is received.
e.g. In the example above I want to calculate a new variable:
DateDiffA1_B1.1 = DateA1 - DateB1.1
DateDiffA1_B2.1 = DateA1 - DateB2.1
DateDiffA1_B1.3 = DateA1 - DateB1.3
DateDiffA1_B2.3 = DateA1 - DateB2.3
DateDiffA1_B3.3 = DateA1 - DateB3.3
I'm not sure if this new variable would need to be linked to each instance of Drug "X" as for the other variables, or if it could be a single variable that COUNTS all the instances for each case.
The end goal is to COUNT how many times each case had a date difference of <= 2 weeks when they received Drug "X". If they did not receive Drug "X", I do not want to COUNT the date difference.
I will eventually want to compare those who did receive Drug "X" with a date difference <= 2 weeks to those who did not, so having another indicator variable to help separate out these specific patients would be beneficial.
I am unsure about the best way to go about this; I suspect it will require a combination of IF and REPEAT functions using the IV variable, but I am relatively new with SPSS and syntax and am not sure how this should be coded to avoid errors.
Thanks for your help!
EDIT: It seems like I may need to use IV as a vector variable to loop through the linked variables in each case. I've tried the syntax below to no avail:
DATASET ACTIVATE DataSet1.
vector IV = IV.1 to IV.3.
loop #i = .1 to .3.
do repeat DateB = DateB.1 to DateB.3
/ DrugDateDiff = DateDiff.1 to DateDiff.3.
if IV(#i) = 1
/ DrugDateDiff = datediff(DateA, DateB, "days").
end repeat.
end loop.
execute.
Actually there is no need to add the vector and the loop, all you need can be done within one DO REPEAT:
compute N2W=0.
do repeat DateB = DateB.1 to DateB.3 /IV=IV.1 to IV.3 .
if IV=1 and datediff(DateA, DateB, "days")<=14 N2W = N2W + 1.
end repeat.
execute.
This syntax will first put a zero in the count variable N2W. Then it will loop through all the dates, and only if the matching IV is 1, the syntax will compare them to dateA, and add 1 to the count if the difference is <=2 weeks.
if you prefer to keep the count variable as missing when none of the IV are 1, instead of compute N2W=0. start the syntax with:
If any(1, IV.1 to IV.3) N2W=0.
I am trying to run this code:
function calcs.grps(Number,ion_color)
grp .. ion_color .. Y[Number] = (ion_py_mm)
grp .. ion_color .. Z[Number] = (ion_pz_mm)
end
in a Lua script, the arrays already exist (eg grp2Y,grp5Z etc) and I want to use this function to populate them based upon the two variables fed in. I keep getting the error ' '=' expected near '..' '. What am I doing wrong?
To flesh it out a bit:
I am 'flying' 120 ions in my simulation. This is actually 12 groups of 10 ions. The individual groups of 10 are distinguished by ion_color, which is an integer value from 1 to 12. The variable 'Number' just cycles through 1 to 10 each time before moving on to the next color. Once I have populated these arrays I want to get the standard deviation for each group.
Thank you!
You can't "construct" name of variable, but you can construct an index. Use two levels of nested tables.
function calcs.grps(Number,ion_color)
ion['grp' .. ion_color .. 'Y'][Number] = (ion_py_mm)
ion['grp' .. ion_color .. 'Z'][Number] = (ion_pz_mm)
end
Well, actually you can, since all global variables are just entries in _G table, but don't do that since it is bad - it is unreadable, makes stuff spill to other functions you didn't intend to, etc.
The technical answer to your question is to simply index _G, _G is a table which holds all global variables:
function calcs.grps(Number,ion_color)
_G['grp' .. ion_color .. Y'][Number] = (ion_py_mm)
_G['grp' .. ion_color .. 'Z'][Number] = (ion_pz_mm)
end
But I think the better question, is why aren't you organizing it like this...
local ions = {
Red = {
{
Y = 0, --Y property
Z = 0 --Z property
},
--Continue your red ions
},
NewColor = {
Y = 0, --Y property
Z = 0 --Z property
},
--Continue this color's ions
},
--You get the idea
}
function calcs.grps(color, number)
ions[color][number].Y = (ion_py_mm)
ions[color][number].Z = (ion_pz_mm)
end
Then you would pass a color, and a number indicating which ion of this color
It looks a lot cleaner, IMO.
I've been working on trying to port a small meanshift tracking program, which is sort of different from the meanshift that involves performing back-projection, from MATLAB to C, but I'm having some problems with it.
I don't know how to interpret some of the lines from MATLAB to C(OpenCV).
https://drive.google.com/drive/folders/0B2r9FmkcbNwAbHdtVEVkSW1SQW8
I put the 2 .m files, 1 .cpp file and a directory where pictures are placed for both programs to use on my googledrive.
"demo_MultiMeanShift_1st_ver_0413.m" is what I'd like to port to C,
"boxfilter.m" is the function that's found in the following website:
http://blog.csdn.net/wds555/article/details/23176313
(It's a Chinese website however)
and "Meanshift_demo.cpp" is what I've done so far.
There're mainly two parts that I don't know how to interpret from MATLAB to C:
1st part:
bas = zeros(hei,wid,N) ;
for i = 1 : 1 : N
bas(:,:,i) = boxfilter( ones(hei,wid), floor(r/i) ) ;
end
Ic_mean = zeros(hei,wid,dep,N) ;
for i = 1 : 1 : N
for d = 1 : 1 : dep
%Average pixel value(s) of the object being tracked
Ic_mean(pc(2)-(r+sw) : pc(2)+(r+sw), pc(1)-(r+sw) : pc(1)+(r+sw), d, i) = boxfilter(Ip(pc(2)-(r+sw) : pc(2)+(r+sw), pc(1)-(r+sw) : pc(1)+(r+sw),d), floor(r/i)) ./ bas(pc(2)-(r+sw) : pc(2)+(r+sw), pc(1)-(r+sw) : pc(1)+(r+sw),i);
%Ic_mean(:,:,d,i) = boxfilter(Ip(:,:,d), floor(r/i)) ./ bas(:,:,i);
end
end
dis = zeros(1,N) ;
2nd part:
for i = -sw + pc(2) : 2 : sw + pc(2)
for j = -sw + pc(1) : 2 : sw + pc(1)
for d = 1 : 1 : N
dis(d) = sqrt( ... % (p1(R1, G1, B1) - p2(R2, G2, B2))^2
( Ic_mean(i,j,1,d) - Ip_mean(pc(2),pc(1),1,d) )^2 ...
+ ( Ic_mean(i,j,2,d) - Ip_mean(pc(2),pc(1),2,d) )^2 ...
+ ( Ic_mean(i,j,3,d) - Ip_mean(pc(2),pc(1),3,d) )^2 );
end
if disMin > mean(dis)
disMin = mean(dis) ;
i_hold = i ;
j_hold = j ;
end
end
end
In MATLAB I can read, access and change pixel values directly, such as:
Img(x,y) = 0 to set some pixel value to be 0
or
Img(:,:,1) = 1 to set the pixels of certain channel to all be 0.
Can I also do those things as rapidly as what's shown above is in OpenCV?
In MATLAB I can read, access and change pixel values directly, such
as:
Img(x,y) = 0 to set some pixel value to be 0 or Img(:,:,1) = 1 to set
the pixels of certain channel to all be 0.
Can I also do those things as rapidly as what's shown above is in
OpenCV?
Of course this is possible. To set value of single pixel use:
img.at<img_single_element_type>(y,x) = 0;
where img_single_element_type depends on mat type and might be double, unsigned char, int, etc... See documentation for more information.
To set values in whole image (or part of image) use setTo method.
I don't know much about Matlab, so i can't help you with porting this code, but look at this and this project. It's similar project (object tracker - Open TLD(Tracking Learning Detection) aka Predator) written in Matlab(first link) and ported to C++(second link). Hope it helps.
I have an array with a set of chronological serial numbers and another source array with random serial numbers associated with a numeric value. The code creates a new cell array in MATLAB with the perfectly chronological serial numbers in one column and in the next column it inserts the associated numeric value if the serial numbers match in both original source arrays. If they don't the code simply copies the previous associated value until there is a new match.
j = 1;
A = {random{1:end,1}};
B = cell2mat(A);
value = random{1,2};
data = cell(length(serial), 1);
data(:,1) = serial(:,1);
h = waitbar(0,'Please Wait...');
steps = length(serial);
for k = 1:length(serial)
[row1, col1, vec1] = find(B == serial{k,1});
tf1 = isempty(vec1);
if (tf1 == 0)
prices = random{col1,2};
data(j,2) = num2cell(value);
j = j + 1;
else
data(j,2) = num2cell(value);
j = j + 1;
end
waitbar(k/steps,h,['Please Wait... ' num2str(k/steps*100) ' %'])
end
close(h);
Right now, the run-time for the code is approximately 4 hours. I would like to make this code run faster. Please suggest any methods to do so.
UPDATE
source input (serial)
1
2
3
4
5
6
7
source input (random)
1 100
2 105
4 106
7 107
desired output (data)
SR No Value
1 100
2 105
3 105
4 106
5 106
6 106
7 107
Firstly, run the MATLAB profiler (see 'doc profile') and see where the bulk of the execution time is occuring.
Secondly, don't update the waitbar on every iteration> Particularly if serial contains a large (> 100) number of elements.
Do something like:
if (mod(k, 100)==0) % update on every 100th iteration
waitbar(k/steps,h,['Please Wait... ' num2str(k/steps*100) ' %'])
end
Some points:
Firstly it would help a lot if you gave us some sample input and output data.
Why do you initialize data as one column and then fill it's second in the loop? Rather initialize it as 2 columns upfront: data = cell(length(serial), 2);
Is j ever different from k, they look identical to me and you could just drop both the j = j + 1 lines.
tf1 = isempty(vec1); if (tf1 == 0)... is the same as the single line: if (!isempty(vec1)) or even better if(isempty(vec1)) and then swap the code from your else and your if.
But I think you can probably find a fast vecotrized solution if you provide some (short) sample input and output data.