I am relatively new to R programming. I am writing a code that generates an array of numbers:
[1] 0.5077399, 0.4388107, 0.3858783, 0.3462711, 0.3170844, 0.2954411, 0.2789464, 0.2658839,
[9] 0.2551246, 0.2459498
Note: I manually separated the values by commas for ease on the eyes :)
I want to pick the first 3 numbers from this array that are below 0.3 - [0.2954411, 0.2658839, 0.2551246]. In addition to picking these values, I want to generate the numbers that represents where those three values exist within the array. In this case, I want the code to give me [6,7,8].
How would I write code to do this?
I greatly appreciate the help.
For a similar simulated set,
y <- c(2, 4,6, 8)
ind <- which(y < 6) ## for finding indices 1 and 2
val <- y[y<6] ## for picking values 2 and 4
Related
I'm starting with Python and I have a basic question with "for" loop
I have two array which contains a values of a same variables:
A = data_lac[:,0]
In the first array, I have values of area and in the second on, values of mean depth.
I would like to find a way to automatize my calculation with different value of a parameter. The equation is the following one:
g= (np.sqrt(A/pi))/n
Here I can calculte my "g" for each row. Now I want to have a loop with differents values of "n". I did this:
i=0
while i <= len(A)-1:
for n in range(2,6):
g[i] = (np.sqrt(A[i]/pi))/n
i += 1
break
In this case, I just have one column with the calculation for n = 2 but not the following one. I tried to add a second dimension to my array but I have an error message saying that I have too many indices for array.
In other, I would like this array:
g[len(A),5]
g has 5 columns each one calculating with a different "n"
Any tips would be very helpful,
Thanks
Update of the code:
data_lac=np.zeros((106,7))
data_lac[:,0:2]=np.loadtxt("/home...", delimiter=';', skiprows=1, usecols=(0,1))
data_lac[:,1]=data_lac[:,1]*0.001
#Initialisation
A = data_lac[:,0]
#example for A with 4 elements
A=[2.1, 32.0, 4.6, 25]
g = np.zeros((len(A),))
I believe you share the indexes within both loops. You were increasing the i (index for the upper while loop) inside the inner for loop (which index with n).
I guess you have A (1 dim array) and you want to produce G (2 dim array) with size of (Len(A, 5))
I am not sure I'm fully understand your require output but I believe you want something like:
i=0
while i <= len(A)-1:
for n in range(2,6):
g[i][n-2] = (np.sqrt(A[i]/pi))/n # n-2 is to get first index as 0 and last as 4
i += 1 # notice the increace of the i is for the upper while loop
break
Important - remember that in python indentation means a lot -> so make sure the i +=1 is under the while scope and not indent to be inside the for loop
Notice - G definition should be as:
g = np.zeros((len(A),4), dtype=float)
The way you define it (without the 4) cause it to be 1 dim array and not 2-dim
I am just learning matlab now. I faced a difficulty in creating an array of 3 elements in a row.
I wrote a code
Source = randi ([0,1],1,3);
which gave me output
[1,1,0].....
[0,1,1]....
but I was willing to get only one 1 and two zeros in the output instead of getting two 1 and one zero.
I know I am wrong because I am using randi function and gives random value of 0 & 1 and output I get can be [0,0,1] ... [1,0,0]... too.
My clear problem is to only get only one 1 if I repeat as many times. e.g. I should get only [0,0,1] or [0,1,0] or [1,0,0].
Hope I can get solution.
Thank you.
Ujwal
Here's a way using randperm:
n = 3; %// total number of elements
m = 1; %// number of ones
x = [ones(1,m) zeros(1,n-m)];
x = x(randperm(numel(x)));
Here is a couple of alternative solutions for your problem.
Create zero-filled matrix and set random element to one:
x = zeros(1, 3);
x(randi(3)) = 1;
Create 1x3 eye matrix and randomly circshift it:
x = circshift(eye(1,3), [0, randi(3)]);
I convert between data formats a lot. I'm sure this is quite common. In particular, I switch between arrays and lists. I'm trying to figure out if I'm doing it right, or if I'm missing any schemas that would greatly improve quality of life. Below I'll give some examples of how to achieve desired results in a couple situations.
Begin with the following array:
dat <- array(1:60, c(5,4,3))
Then, convert one or more of the dimensions of that array to a list. For clarification and current approaches, see the following:
1 dimension, array to list
# Convert 1st dim
dat_list1 <- unlist(apply(dat, 1, list),F,F) # this is what I usually do
# Convert 1st dim, (alternative approach)
library(plyr) # I don't use this approach often b/c I try to go base if I can
dat_list1a <- alply(dat, 1) # points for being concise!
# minus points to alply for being slow (in this case)
> microbenchmark(unlist(apply(dat, 1, list),F,F), alply(dat, 1))
Unit: microseconds
expr min lq mean median uq max neval
unlist(apply(dat, 1, list), F, F) 40.515 43.519 50.6531 50.4925 53.113 88.412 100
alply(dat, 1) 1479.418 1511.823 1684.5598 1595.4405 1842.693 2605.351 100
1 dimension, list to array
# Convert elements of list into new array dimension
# bonus points for converting to original array
dat_array1_0 <- simplify2array(dat_list1)
aperm.key1 <- sapply(dim(dat), function(x)which(dim(dat_array1_0)==x))
dat_array1 <- aperm(dat_array1_0,aperm.key1)
In general, these are the tasks I'm trying to accomplish, although sometimes it's in multiple dimensions or the lists are nested, or some such other complication. So I'm asking if anyone has a "better" (concise, efficient) way of doing either of these things, but bonus points if a suggested approach can handle other related scenarios too.
Im semi-new with matlab, i've been using it in my course for a while now, but never really been taken in by it.
I have a vector of quite a large size, it is a sound file to be accurate. I'm required to take every 128 elements from this vector, and add them to a matrix.
So matrix row 1 will contain the first 128 (1-128) elements, matrix row 2 will contain the second 128 (128-256) etc...
How can I go about doing this? I've looked up the matlab mathworks help files and havent been able to find anything. I know I can append matrices using z = [x,y] but its not working for me...
Appreciate any help, thanks!
You can do this with the reshape command:
>> A = [1 2 3 4 5 6];
>> B = reshape(A, 3, 2)'
B =
1 2 3
4 5 6
Look at the reshape command. If you start with a (N*128 by 1) vector then with reshape(A,[N,128]) you should get a (N by 128) matrix.
As others said reshape command is the right tool for you. But before you start using reshape, you would like to make sure two things:
usually for any sound file there will be some header information, you need to start reading from the file position after the header information. you can find online manuals to get the size of header-data, for example the canonical sound data format can be found here: https://ccrma.stanford.edu/courses/422/projects/WaveFormat/
If the format of your sound file is something else then you'll have to find it out.
the number of samples to be read should be either truncated or padded to multiple of 128 since you want a matrix of N*128 size
This can be done slightly more conveniently even, as reshape can compute one of its argument itself
In MarkD's answer:
A = [1 2 3 4 5 6];
B = reshape(A, 3, 2)'
replace the second line with
B = reshape(A, 3, [])'
The [] input tells reshape: determine yourself what this should be (length(A)/3 in your case)
I have three 1-d arrays where elements are some values and I want to compare every element in one array to all elements in other two.
For example:
a=[2,4,6,8,12]
b=[1,3,5,9,10]
c=[3,5,8,11,15]
I want to know if there are same values in different arrays (in this case there are 3,5,8)
The answer given by AB is correct, but it is specific for the case when you have 3 arrays that you are comparing. There is another alternative that will easily scale to any number of arrays of arbitrary size. The only assumption is that each individual array contains unique (i.e. non-repeated) values:
>> allValues = sort([a(:); b(:); c(:)]); %# Collect all of the arrays
>> repeatedValues = allValues(diff(allValues) == 0) %# Find repeated values
repeatedValues =
3
5
8
If the arrays contains repeated values, you will need to call UNIQUE on each of them before using the above solution.
Leo is almost right, should be
unique([intersect(a,[b,c]), intersect(b,c)])
c(ismember(c,a)|ismember(c,b)),
ans =
3 5 8
I think this works for all matrices.
Define what you mean by compare. If the arrays are of the same length, and you are comparing equality then you can just do foo == bar -- it's vectorized. If you need to compare in the less than/greater than sense, you can do sign(foo-bar). If the arrays are not the same length and/or you aren't comparing element-wise -- please clarify what you'd like the output of the comparison to be. For instance,
foo = 1:3;
bar = [1,2,4];
baz = 1:2;
sign(repmat(foo',1,length([bar,baz])) - repmat([bar, baz],length(foo),1))
# or, more concisely:
bsxfun(#(x,y)sign(x-y),foo',[bar,baz])
does what you ask for, but there is probably a better way depending on what you want as an output.
EDIT (OP clarified question):
To find common elements in the 3 arrays, you can simply do:
>> [intersect(a,[b,c]), intersect(b,c)]
ans =
8 3 5