If I have the following matrix, which the input format is a list of lists: B T E 0 1 0 0 1 1 0 2 1 1 2 0 How can I construct the following python matrix: Where the elements of D, merge the pairs (B,E) with it’s respective T. Example: (0,1) in the above matrix, have T =
Tag: matrix
Putting serial values in a matrix with Python
I have a stream of elements that are coming serially: (x0, y0, val0), (x1, y2, val1), … (xN, yN, valN), etc. x and y are the coordinates directly pointing where the val should be put in a matrix. I tried the following but it does not work (I expected the interpreter will automatically expand the matrix but it does not):
Integer overflow while calculating all possible sums of n*m matrix rows
I am using this code to compute all possible sum of a n x m matrix. The code is working absolutely fine and it is fast too when using arrays of 32-bit integers like [[777,675,888],[768,777,698]]. It is using the Numpy package. However, as soon as I use 128-bit integers or bigger, I start getting negative values. Its working fine with
Insert matrix inside another matrix using numpy without overwriting some original values
I need to insert a matrix inside another one using numpy The matrix i need to insert is like this one: While the other matrix is like this: The code i’m actually using this one: The problem matrix that i’m getting is this one: while the expected result is: The error is that, since the matrix contains 0, when i
create a matrix from combinations with values
I have some combinations like Any idea on how I efficiently can create a four by four matrix with these 0,1 values from all these combinations? So the result will be something like: Answer Imagine if the “combinations” are stored in a file in the following format (or similar): Then you can do: Example (using your sample data): Now df
comparing a number of lists in pairs
I have problem with 4 list each one got 4 number: P1= [3,1,3,4] P2= [5,4,3,7] P3= [7,4,8,1] P4= [10,3,2,1] I need to get the biggest number in combinational way like: Pair of 2: p1p2, p1p3, p1p4, p2p3, p2p4, p3p4 Pairs of 3: p1p2p3, p1p2p4, p1p3p4, p2p3p4 Pairs of 4: p1p2p3p4 The result for: p1p2= [5,4,3,7] p1p3= [7,4,8,4] p1p4= [10,3,3,4] ……
Python Numpy make a pattern with a square matrix of any dimension
I am having difficulties trying to generate a specific pattern that would work for any square matrix with any square dimension using NumPy For example: User input: n = 3 Output: User input: n = 5 Output: User input: n = 8 Output: Since a square matrix can be generated with any number in the form of (n x n),
Numpy insert matrix values with matrix index
I have the following code which creates a 4D grid matrix and I am looking to insert the rolled 2D vals matrix into this grid. If vals would be a 1D array and I would use a 1D insert_map array as a reference it would work, however using it in multiple dimensions seems to be an issue and it raises
Compute sum of power of large sparse matrix
Given a query vector (one-hot-vector) q with size of 50000×1 and a large sparse matrix A with size of 50000 x 50000 and nnz of A is 0.3 billion, I want to compute r=(A + A^2 + … + A^S)q (usually 4 <= S <=6). I can above equation iteratively using loop but I want to more fast method. First
how to convert lists of lists into array in python?
I am calculating the similarity scores for a pair of nodes in a graph, the result is a lists of lists as detailed below: example output here I have each node pair similarity scores How can i put this in matrix form with each column having nodes and rows bare the similarity score? Any help will be much appreciated here