This is rather easy question or maybe too easy question. But i tried to find the way to done these already and could not find even in GNUplot document. Might be my mistake or misunderstood something about array concept in GNUplot. My question is How to define and access array in GNUplot?
Please just provide easy example of array declaration, assign value of array over loop. i think that's enough and i think this will be useful for other people too.
If you are using Gnuplot 5.1 or superior and need a 1-d array, you simply define the array with size N, remembering that the indices go from 1 to N:
gnuplot> array A[3] #Array definition
gnuplot> A[1]=2
gnuplot> A[3]=4
gnuplot> print A[1]
2
gnuplot> print A #Print the array, with empty A[2]
[2,,4]
If you need more than one dimension or are using previous versions of Gnuplot, you can do the following:
Since there are no vector variables in previous versions of Gnuplot, two functions can be defined to get and set values to a behind the scenes variable whose name include the index. The functions are:
aGet(name, i) = value(sprintf("_%s_%i", name, i))
aSet(name, i, value) = sprintf("_%s_%i = %.16e", name, i, value)
To assign and retrieve values on the array A you do
eval aSet("A",2,3)
print aGet("A",2)
What these functions do is to access a variable called _A_2.
You can build similar function to work with matrices:
mGet(name, i, j) = value(sprintf("_%s_%i_%i", name, i, j))
mSet(name, i, j, value) = sprintf("_%s_%i_%i = %.16e", name, i, j, value)
(This answer will be obsolete with the next stable gnuplot release, as the 5.1 development tree now has native support for array variables.)
(The "splot" command in gnuplot uses the keyword "array" to define the size of NxM matrix that contains function values for a 3D plot. Nothing to do with array variables.)
Arrays like what a programmer knows from C, Pascal, Python, etc. do not exist in gnuplot today (gp5.0). They might get implemented one day, because they'd be highly useful to plot a family of curves with arbitrary (e.g. fitted) parameters.
If you are desperate about arrays in gnuplot, you can (ab)use the word() function (and other string functions) to achieve a somewhat limited substitute. It's also a bit cumbersome:
array = ""
f(a,x) = a*x
do for [i=1:5] {array = array.sprintf(" %.3f",i+rand(0)) }
print "array = ".array
set xr [0:]; set yr [0:30]
plot for [i=1:5] f(word(array,i),x) title word(array,i)." x"
This example writes a set of random numbers to a string variable named "array", and afterwards uses it to plot five linear functions that use the numbers in "array" for their slope. It's handy here that gnuplot autopromotes strings to numerics if used e.g. in an equation.
Inspired by #Karl 's answer, it looks even more like an array when putting the word function into another function:
array(n) = word("1 2 3 4 5 6 7 8 9", n)
print array(3)
This prints 3. So the indexing is one-based.
"Multiply" the array by 2:
print (b="", sum[i=1:9](b=b.(array(i)*2)." ", 0), b)
This prints 2 4 6 8 10 12 14 16 18. Here the sum function is (ab)used to loop over the array and its result is ignored.
And here is shorter, through less generic variant of #bmello's answer:
A_1=1.1; A_2=2.2; A_3=3.3
A(i) = value("A_".i)
print A(3)
For me it feels more intuitiv. The underscore _ can be seen simply as the set function. Also it is not limited to integer indices. Strings are also possible which give some dictionary-like behaviour.
Related
I've been learning Julia by trying to write a simple rigid body simulation, but I'm still somewhat confused about the assignment and mutating of variables.
I'm storing the points making up the shape of a body into an array of arrays where one vector holds the x,y,z coordinates of a point. For plotting the body with PyPlot the points are first transformed from local coordinates into world coordinates and then assigned to three arrays which hold the x, y, and z coordinates for the points respectively. I would like to have the three arrays only reference the array of arrays values instead of having copies of the values.
The relevant part of my code looks like this
type Rigidbody
n::Integer
k::Integer
bodyXYZ::Array{Array{Float64,1},2}
worldXYZ::Array{Array{Float64,1},2}
worldX::Array{Float64,2}
worldY::Array{Float64,2}
worldZ::Array{Float64,2}
Rotmat::Array{Float64,2}
x::Array{Float64,1}
end
# body.worldXYZ[1,1] = [x; y; z]
# and body.worldX[1,1] should be body.worldXYZ[1,1][1]
function body_to_world(body::Rigidbody)
for j in range(1, body.k)
for i in range(1, body.n)
body.worldXYZ[i,j] = body.x + body.Rotmat*body.bodyXYZ[i,j]
body.worldX[i,j] = body.worldXYZ[i,j][1]
body.worldY[i,j] = body.worldXYZ[i,j][2]
body.worldZ[i,j] = body.worldXYZ[i,j][3]
end
end
return nothing
end
After calling the body_to_world() and checking the elements with === they evaluate to true but if I then for example set
body.worldXYZ[1,1][1] = 99.999
the change is not reflected in body.worldX. The problem is probably something trivial but as can be seen from my code, I am a beginner and could use some help.
body.worldX[i,j] = body.worldXYZ[i,j][1]
You're setting a number to a number here. Numbers are not mutable, so body.worldX[i,j] won't refer back to body.worldXYZ[i,j][1]. What you're thinking of is that the value of an array will be a reference, but numbers don't have references, just the value themselves.
However, I would venture to say that if you're doing something like that, you're going about the problem wrong. You should probably be using types somewhere. Remember, types in Julia give good performance, so don't be afraid of them (and immutable types should be almost perfectly optimized after carneval's PR, so there's really no need to be afraid). Instead, I would make world::Array{Point,2} where
immutable Point{T}
x::T
y::T
z::T
end
Then you can get body.world[i,j].x for the x coordinate, etc. And then for free you can use map((i,j)->Ref(body.world[i,j].x),size(body.world)...) to get an array of references to the x's.
Or, you should be adding dispatches to your type. For example
import Base: size
size(RigidBody) = (n,k)
now size(body) outputs (n,k), as though it's an array. You can complete the array interface with getindex and setindex!. This kind of adding dispatches to your type will help clean up the code immensely.
The point of indexing is mainly to get the value. In MATLAB,
for a cell array, there is content indexing ({}), and thus cell indexing (()) is only for selecting a subset from the cell array, right?
Is there anything other advanced usage for it? Like using it as
a pointer and pass it to a function?
There is a heavily simplified answer. {}-indexing returns you the content, ()-indexing creates a subcell with the indexed elements. Let's take a simple example:
>> a=x(2)
a =
[2]
>> class(a)
ans =
cell
>> b=x{2}
b =
2
>> class(b)
ans =
double
Now continue with non-scalar elements. For the ()-indexing everything behaves as expected, you receive a subcell with the elements:
>> a=x(2:3)
a =
[2] [3]
The thing really special to Matlab is using {}-indexing with non-scalar indices. It returns a Comma-Separated List with all the contents. Now what is happening here:
>> b=x{2:3}
b =
2
The Comma-Separated List behaves similar to a function with two return arguments. You want only one value, only one value is assigned. The second value is lost. You can also use this to assign multiple elements to individual lists at once:
>> [a,b]=x{2:3} %old MATLAB versions require deal here
a =
2
b =
3
Now finally to a very powerful use case of comma separated lists. Assume you have some stupid function foo which requires many input arguments. In your code you could write something like:
foo(a,b,c,d,e,f)
Or, assuming you have all parameters stored in a cell:
foo(a{1},a{2},a{3},a{4},a{5},a{6})
Alternatively you can call the function using a comma separated list. Assuming a has 6 elements, this line is fully equivalent to the previous:
foo(a{:}) %The : is a short cut for 1:end, index the first to the last element
The same technique demonstrated here for input arguments can also be used for output arguments.
Regarding your final question about pointers. Matlab does not use pointers and it has no supplement for it (except handle in oop Matlab), but Matlab is very strong in optimizing the memory usage. Especially using Copy-on-write makes it unnecessary to have pointers in most cases. You typically end up with functions like
M=myMatrixOperation(M,parameter,parameter2)
Where you input your data and return it.
I'd like for my array to be of a set length using a simple format. Please, let me know how this is done.
What I already have:
arr[100]
Pseudocode: what I would like to have:
arr[4-20] or arr[$min_int THROUGH $max_int]
Additional detail edit: The int should be within the range array = (4, 20). The input may contain leading zeros. I'd like to keep the length of the array restricted (i.e., to 9 or 10 characters).
Arrays simply do not work this way in C. You will need to implement it yourself by only looping through valid indices (and wasting memory in the process) or by using a data structure better suited to the job, like a map (which you will have to find in a library or write yourself as it does not exist in the language).
#define ARRMINIDX 4
#define ARRMAXIDX 20
int arrmem[ARRMAXIDX+1-ARRMINIDX];
#define arr(x) arrmem[ARRMINIDX+(x)]
// process elements of arr
for( i = ARRMINIDX; i <= ARRMAXIDX; i++ )
dosomething(arr(i));
OTOH, this make not be what you want at all, given your comment
I want an array with 0-1 elements: a limited int or limited "numeric
int"--string mimicking an int.
which I can't make heads or tails of in this context. Are you saying that you want a string of 4-20 chars that represents an integer?
Is it possible to apply the idea of array in C to MATLAB
For example, if we have
Double array[10];
and if we want to assign a value we write for example
Array[5]=2;
Is there any way to write equivalent one in MATLAB ?
I'm not sure what you mean by "Is it possible to apply the idea of array in C to MATLAB". An array is just a 1D list of numbers (or other data types). MATLAB primarily is designed to work with matrices (MATLAB is short for Matrix laborartory) and an array or vector is simply a special case of a matrix. So I guess the answer to your question is yes, if I have understood correctly.
To initialise arrays or matrices in MATLAB we use zeros or ones:
>> array = zeros(1,5)
array =
0 0 0 0 0
We can then index elements of the array in the same way as C:
>> array(3) = 3
array =
0 0 3 0 0
Note, however, that MATLAB array indexing is one based whereas C arrays are zero based.
This article describes matrix/array indexing in MATLAB.
You can define your own class, override the [] operator.
I described the mechanism in Here
Since it is a custom function, you might as well change the 1-based indexing to 0-based indexing.
Regarding the constructor, I doubt that you can do it.
Anyhow, why would you want to do it?
You will confuse all of the Matlab users, and cause havoc.
When in Rome, do as Romans do.
Yes you can. Arrays are used in C and MATLAB and they can be used for the same functions. Except, please keep in mind the array-indexing of C and MATLAB are different.
The first element of a C array has an index of zero. i.e. in X = [10 20 30 40], x[0] will return 10. But in MATLAB, this will give an error. To access the number 10, you have to use the expression x[1] in MATLAB.
There is no indexing operator []. You must use () for indexing array.
If you write
x = 1:10;
x[2]
then you'll get the following error
x[2]
|
Error: Unbalanced or unexpected parenthesis or bracket.
Is there any way to "vector" assign an array of struct.
Currently I can
edges(1000000) = struct('weight',1.0); //This really does not assign the value, I checked on 2009A.
for i=1:1000000; edges(i).weight=1.0; end;
But that is slow, I want to do something more like
edges(:).weight=[rand(1000000,1)]; //with or without the square brackets.
Any ideas/suggestions to vectorize this assignment, so that it will be faster.
Thanks in advance.
This is much faster than deal or a loop (at least on my system):
N=10000;
edge(N) = struct('weight',1.0); % initialize the array
values = rand(1,N); % set the values as a vector
W = mat2cell(values, 1,ones(1,N)); % convert values to a cell
[edge(:).weight] = W{:};
Using curly braces on the right gives a comma separated value list of all the values in W (i.e. N outputs) and using square braces on the right assigns those N outputs to the N values in edge(:).weight.
You can try using the Matlab function deal, but I found it requires to tweak the input a little (using this question: In Matlab, for a multiple input function, how to use a single input as multiple inputs?), maybe there is something simpler.
n=100000;
edges(n)=struct('weight',1.0);
m=mat2cell(rand(n,1),ones(n,1),1);
[edges(:).weight]=deal(m{:});
Also I found that this is not nearly as fast as the for loop on my computer (~0.35s for deal versus ~0.05s for the loop) presumably because of the call to mat2cell. The difference in speed is reduced if you use this more than once but it stays in favor of the for loop.
You could simply write:
edges = struct('weight', num2cell(rand(1000000,1)));
Is there something requiring you to particularly use a struct in this way?
Consider replacing your array of structs with simply a separate array for each member of the struct.
weights = rand(1, 1000);
If you have a struct member which is an array, you can make an extra dimension:
matrices = rand(3, 3, 1000);
If you just want to keep things neat, you could put these arrays into a struct:
edges.weights = weights;
edges.matrices = matrices;
But if you need to keep an array of structs, I think you can do
[edges.weight] = rand(1, 1000);
The reason that the structs in your example don't get initialized properly is that the syntax you're using only addresses the very last element in the struct array. For a nonexistent array, the rest of them get implicitly filled in with structs that have the default value [] in all their fields.
To make this behavior clear, try doing a short array with clear edges; edges(1:3) = struct('weight',1.0) and looking at each of edges(1), edges(2), and edges(3). The edges(3) element has 1.0 in its weight like you want; the others have [].
The syntax for efficiently initializing an array of structs is one of these.
% Using repmat and full assignment
edges = repmat(struct('weight', 1.0), [1 1000]);
% Using indexing
% NOTE: Only correct if variable is uninitialized!!!
edges(1:1000) = struct('weight', 1.0); % QUESTIONABLE
Note the 1:1000 instead of just 1000 when indexing in to the uninitialized edges array.
There's a problem with the edges(1:1000) form: if edges is already initialized, this syntax will just update the values of selected elements. If edges has more than 1000 elements, the others will be left unchanged, and your code will be buggy. Or if edges is a different type, you could get an error or weird behavior depending on its existing datatype. To be safe, you need to do clear edges before initializing using the indexing syntax. So it's better to just do full assignment with the repmat form.
BUT: Regardless of how you initialize it, an array-of-structs like this is always going to be inherently slow to work with for larger data sets. You can't do real "vectorized" operations on it because your primitive arrays are all broken up in to separate mxArrays inside each struct element. That includes the field assignment in your question – it is not possible to vectorize that. Instead, you should switch a struct-of-arrays like Brian L's answer suggests.
You can use a reverse struct and then do all operations without any errors
like this
x.E(1)=1;
x.E(2)=3;
x.E(2)=8;
x.E(3)=5;
and then the operation like the following
x.E
ans =
3 8 5
or like this
x.E(1:2)=2
x =
E: [2 2 5]
or maybe this
x.E(1:3)=[2,3,4]*5
x =
E: [10 15 20]
It is really faster than for_loop and you do not need other big functions to slow your program.