# Convolutions - Computational Thinking

**URL:** https://discourse.julialang.org/t/convolutions-computational-thinking/121922
**Category:** General Usage
**Tags:** question
**Created:** [October 29, 2024, 3:14pm UTC](https://discourse.julialang.org/t/convolutions-computational-thinking/121922 "2024-10-29T15:14:36Z")
**Posts on this page:** 1
**Page:** 1

<div class="post-metadata">

### Author: ![elwwan](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/elwwan/32/211001_2.png) [@elwwan](https://discourse.julialang.org/u/elwwan)
#### Post date: [October 29, 2024, 3:14pm UTC](https://discourse.julialang.org/t/convolutions-computational-thinking/121922/1 "2024-10-29T15:14:36Z")

</div>

Hello, I’m trying to follow the computational thinking course to learn Julia unfortunately I am stuck at question 2.2 in homework 2.

This is the exercise is this :

 ![image](https://global.discourse-cdn.com/julialang/original/3X/8/9/89b6997f9a84328ae315a1dde202cd9ecbfe4065.png)  
Implement a new method `convolve(M, K)` that applies a convolution to a 2D array `M`, using a 2D kernel `K`. Use your new method `extend` from the last exercise.  
We already have the extend() function :

```julia
function extend(M, i, j)
	num_rows, num_columns = size(M)

	i = clamp(i, 1, num_rows)
	j = clamp(j, 1, num_columns)

	return M[i,j]
end

```

Unfortunately my function convole doesn’t seem to work properly. Here is what I have written so far :

```julia
function convolve(M::AbstractMatrix, K::AbstractMatrix)
  
  num_rows_K, num_columns_K = size(K)
  num_rows_M, num_columns_M = size(M)

  length_row = Int((num_rows_K-1)/2)
  length_col = Int((num_columns_K-1)/2)
	
  final = zeros(num_rows_M,num_columns_M)
    
  for row in 1:num_rows_M, col in 1:num_columns_M
    nearest_values = [extend(M, i, j) for i in row - length_row:row + length_row, 
										  j in col - length_col:col + length_col]
    weighted = nearest_values .* K
    total = sum(weighted)
    final[row, col] = total
  end
  return final
end

```

But is doesn’t work

I have tried to make the same thing in VSCode to make sure that it is working as it should, and I can’t figure out why it is not working since In VSCode

```julia
m = [1 1 1; 1 1 1; 1 1 1]
k = [1 1 1; 1 1 1; 1 1 1]

function extend(M, i, j)
	num_rows, num_columns = size(M)

	i = clamp(i, 1, num_rows)
	j = clamp(j, 1, num_columns)

	return M[i,j]
end

function convolve(M::AbstractMatrix, K::AbstractMatrix)
  
  num_rows_K, num_columns_K = size(K)
  num_rows_M, num_columns_M = size(M)

  length_row = Int((num_rows_K-1)/2)
  length_col = Int((num_columns_K-1)/2)
  final = zeros(num_rows_M,num_columns_M)
    
  for row in 1:num_rows_M, col in 1:num_columns_M
    nearest_values = [extend(M, i, j) for i in row - length_row:row + length_row, j in col - length_col:col+length_col]
    weighted = nearest_values .* K
    total = sum(weighted)
    final[row, col] = total
  end
  return final
end

convolve(m, k)

```

Results in a 3x3 matrix (which is what is expect):  
9.0 9.0 9.0  
9.0 9.0 9.0  
9.0 9.0 9.0

Thank you in advance !