for the following code:
from array import *
x=[]
x.append(0.232)
print (x)
for i in range(25):
x[i+1]=(1/(i+1))-5*x[i]
I have this error:
x[i+1]=(1/(i+1))-5*x[i]
IndexError: list assignment index out of range
This may be happening because I have defined x to be an empty array. But how do I define the array and perform the same operation otherwise?
list is not designed for efficient mathematical operations and therefore its better to use numpy arrays for doing mathematical operations. However, if you want to use list, you may define a list initialized with n zero's using
x=[0]*n
x[0] = 0.232
x[1] = ....
....
Remember, that a multidimensional list created using above approach will refer to same element in the array! For example:
l = [0,0,0]*5
will be creating five same list's inside another list not separate list's. So its a bad idea to create multidimensional array like this!
A better way would be to create arrays using numpy using following code:
from numpy import empty, zeros
x = empty(n) # or # x = zeros(n)
x[0] = 0.232
x[1] = ....
....
and
l = empty((3,5)) # or # l = zeros((3,5))
for a array with 3 rows and 5 columns.
Related
In essence this is what I want to create
import numpy as np
N = 100 # POPULATION SIZE
D = 30 # DIMENSIONALITY
lowerB = [-5.12] * D # LOWER BOUND (IN ALL DIMENSIONS)
upperB = [5.12] * D # UPPER BOUND (IN ALL DIMENSIONS)
# INITIALISATION PHASE
X = np.empty([N, D]) # EMPTY FLIES ARRAY OF SIZE: (N,D)
# INITIALISE FLIES WITHIN BOUNDS
for i in range(N):
for d in range(D):
X[i, d] = np.random.uniform(lowerB[d], upperB[d])
but I want to do so without the for loops to save time and use List comprehensions
I have try things like
np.array([(x,y)for x in range(N)for y in range(D)])
but this doesn’t get me to an array like array([100,30]). Does anyone know a tutorial or the correct documentation I should be looking at so I can learn exactly how to do this?
I have a numpy array A of size 10 with values ranging from 0-4. I want to create a new 2-D array B from this with its ith column being a vector corresponding to the ith element of A.
For example, the value 1 as the first element of A would correspond to B having a column vector [0,1,0,0,0] as it's first column. A having 4 as its third element would correspond to B having it's 3rd column as [0,0,0,1,0]
I have the following code:
import numpy as np
A = np.random.randint(0,5,10)
B = np.ones((5,10))
iden = np.identity(5, dtype=np.float64)
for i in range(0,10):
a = A[i]
B[:,i:i+1] = iden[:,a:a+1]
print A
print B
The code is doing what it's supposed to be doing but I am sure there are more efficient ways of doing this. Can anyone please suggest some?
That could be solved by initializing an array of zeros and then integer-indexing into it with indices from A and assigning 1s, like so -
M,N = 5,10
A = np.random.randint(0,M,N)
B = np.zeros((M,N))
B[A,np.arange(len(A))] = 1
I want to create a 2D list that can have elements of variable lengths inside, for example, if I have a 10x10 list in MATLAB, I can
define it with:
z = cell(10,10)
and start assigning some elements by doing this:
z{2}{3} = ones(3,1)
z{1}{1} = zeros(100,1)
z{1}{2} = []
z{1}{3} = randn(20,1)
...
What is the optimal way to define such empty 2D list in torch? Moreover, is there a way to exploit the tensor structure to do this?
In python, I can do something along this to define an empty 10x10 2D list:
z = [[None for j in range(10)] for i in range(10)]
My best guess for torch is doing something like
z = torch.Tensor(10,10)
for i=1,10 do
for j=1,10 do
z[{{i},{j}}] = torch.Tensor()
end
end
but, this does not work, and defining a tensor inside a tensor seems like a bad idea ...
This is a follow up to the question asked here (however in the link it is asked in python): Create 2D lists in python with variable length indexed vectors
From the documentation I've read, tensors only support primitive numeric data types. You won't be able to use tensor for your intended usage. Leverage tables.
local function makeMatrix(initialVal, ...)
local isfunc = type(initialVal) == "function"
local dimtable = {...}
local function helper(depth)
if depth == 0 then
return isfunc and initialVal() or initialVal
else
local plane = {}
for i = 1, dimtable[depth] do
plane[i] = helper(depth-1)
end
return plane
end
end
return helper(#dimtable)
end
p = makeMatrix(0, 2, 3, 5) -- makes 3D matrix of size 2x3x5 with all elements initialized to 0
makeMatrix(torch.Tensor, m ,n)
Answer from Torch's Google Group forums. Agreeing that tables is the solution:
z = {}
for i=1,10 do
z[i] = {}
for j=1,10 do
z[i][j] = torch.Tensor()
end
end
I am currently looking for an efficient way to slice multidimensional matrices in MATLAB. Ax an example, say I have a multidimensional matrix such as
A = rand(10,10,10)
I would like obtain a subset of this matrix (let's call it B) at certain indices along each dimension. To do this, I have access to the index vectors along each dimension:
ind_1 = [1,4,5]
ind_2 = [1,2]
ind_3 = [1,2]
Right now, I am doing this rather inefficiently as follows:
N1 = length(ind_1)
N2 = length(ind_2)
N3 = length(ind_3)
B = NaN(N1,N2,N3)
for i = 1:N1
for j = 1:N2
for k = 1:N3
B(i,j,k) = A(ind_1(i),ind_2(j),ind_3(k))
end
end
end
I suspect there is a smarter way to do this. Ideally, I'm looking for a solution that does not use for loops and could be used for an arbitrary N dimensional matrix.
Actually it's very simple:
B = A(ind_1, ind_2, ind_3);
As you see, Matlab indices can be vectors, and then the result is the Cartesian product of those vector indices. More information about Matlab indexing can be found here.
If the number of dimensions is unknown at programming time, you can define the indices in a cell aray and then expand into a comma-separated list:
ind = {[1 4 5], [1 2], [1 2]};
B = A(ind{:});
You can reference data in matrices by simply specifying the indices, like in the following example:
B = A(start:stop, :, 2);
In the example:
start:stop gets a range of data between two points
: gets all entries
2 gets only one entry
In your case, since all your indices are 1D, you could just simply use:
C = A(x_index, y_index, z_index);
my program in R creates an n-dimensional array.
PVALUES = array(0, dim=dimensions)
where dimensions = c(x,y,z, ... )
The dimensions will depend on a particular input. So, I want to create a general-purpose code that will:
Store a particular element in the array
Read a particular element from the array
From reading this site I learned how to do #2 - read an element from the array
ll=list(x,y,z, ...)
element_xyz = do.call(`[`, c(list(PVALUES), ll))
Please help me solving #1, that is storing an element to the n-dimensional array.
Let me rephrase my question
Suppose I have a 4-dimensional array. I can store a value and read a value from this array:
PVALUES[1,1,1,1] = 43 #set a value
data = PVALUES[1,1,1,1] #use a value
How can I perform the same operations using a function of a vector of indexes:
indexes = c(1,1,1,1)
set(PVALUES, indexes) = 43
data = get(PVALUES, indexes) ?
Thank you
Thanks for helpful response.
I will use the following solution:
PVALUES = array(0, dim=dimensions) #Create an n-dimensional array
dimensions = c(x,y,z,...,n)
Set a value to PVALUES[x,y,z,...,n]:
y=c(x,y,z,...,n)
PVALUES[t(y)]=26
Reading a value from PVALUES[x,y,z,...,n]:
y=c(x,y,z,...,n)
data=PVALUES[t(y)]
The indexing of arrays can be done with matrices having the same number of columns as there are dimensions:
# Assignment with "[<-"
newvals <- matrix( c( x,y,z,vals), ncol=4)
PVALUES[ newvals[ ,-4] ] <- vals
# Reading values with "["
PVALUES[ newvals[ ,-4] ]