Dimensional | Swift matrices with friendly semantics | Math library

So let us say that we have a 2 dimensional list of numbers:

I have a two dimensional numpy arrays which describes a list of coordinates where something happens. There are two events on the scene and I would like to calculate where those two are. But I do have difficulties to distinguish those two since there isn't any good pattern from event to event.

Example:

I am solving this problem on dynamic array in which input first line contains two space-separated integers,n, the size of arr to create, and q, the number of queries, respectively. Each of the q subsequent lines contains a query string,queries[i]. it expects to return int[]: the results of each type 2 query in the order they are presented.

i tried to attempt as below and my code seems fine to me but it gives segmentation fault error. please help me where I am getting conceptually wrong. thanks.

problem: Declare a 2-dimensional array,arr , of n empty arrays. All arrays are zero indexed. Declare an integer,last answer , and initialize it to zero.

There are 2 types of queries, given as an array of strings for you to parse:

Query: 1 x y

Let idx=((queries[i][1]^last_answer)%n);. Append the integer y to arr[idx].

Query: 2 x y

Let idx=((queries[i][1]^last_answer)%n);. Assign last_answer=arr[idx][queries[i][2]%(arr[idx].size())] . Store the new value of last_answer to an answers array.

input: 2 5

1 0 5

1 1 7

1 0 3

2 1 0

2 1 1

output:

7

3

I am trying to make a next-word prediction model with LSTM + Mixture Density Network Based on this implementation(https://www.katnoria.com/mdn/).

Input: 300-dimensional word vectors*window size(5) and 21-dimensional array(c) representing topic distribution of the document, used to train hidden initial states.

Output: mixing coefficient*num_gaussians, variance*num_gaussians, mean*num_gaussians*300(vector size)

x.shape, y.shape, c.shape with an experimental 161 obserbations gives me such:

(TensorShape([161, 5, 300]), TensorShape([161, 300]), TensorShape([161, 21]))

I want to change all specific values in a 3D Ndarray image file.
I'm working on mapping a colormap to an image file.

For example :

How can I replicate matrix in Haskell Accelerate? For example, I have a matrix mat :: Matrix (Z :. 2 :. 5) .... I want to get a three-dimensional array with shape Z :. 9 :. 2 :. 5. I tried to use A.replicate (A.lift (Z :. 9 :. All)) mat, but I get an error

Couldn't match type ‘Z’ with ‘DIM0 :. Int’ Expected type: Acc (Array (SliceShape ((Z :. Int) :. All)) a) Actual type: Acc (Matrix a)

What does that mean?

And similarly, if I have a matrix with shape Z :. 9 :. 5, how can I get a three-dimensional array with shape Z :. 9 :. 2 :. 5?

I'm having a result array of X[k][i][j] (with k in Day range from 1 to 365, i in Task range from 1 to 200 and j in Repetition range from 0 to 365).

I know how to write a 2 dimensional array from cplex to excel but 3 dimensional array to excel seems like a problem.

Is there a way to write a 3 dimensional array from cplex to excel? I tried to use the method from this link but then it said that the constraint is conflict (Maybe because of my j range from 0 to 365?)

Could someone please help me out? Thank you so much in advance!

I have the following development that I am working on with the ElementTree and Pandas module in Python:

Please how do I use the .append() method to add a list with values (two dimensional lists) ?

For example if you are asked to Use the .append() method to add a list with the values of "computer science" and an associated grade value of 100 to our two-dimensional list of gradebook

How do you go about it?