Hello guys i am trying to implement an algortihm to remove water from underwater images and make image more noticable , but i got an errror ValueError: max() arg is an empty sequence , at the function homomorpic on this line r = max(np.ravel(result[:,:i])) , the error is caused because the result array is empty but i filled it above
Tag: arrays
Numpy Mean element wise over 3D arrays
I want to take the mean of 9 arrays element wise so to have one I need something fast. The first bit of code takes forever. And with numpy mean without specifying an axis I get one value. I dont want to specify an axis. I want to take the mean element by element. with output: juneMean[‘wind’][:,:,:] how do I
Conditional formatting of arrays in Numpy Python
I am trying to make a function where if the last value of order is 1 then the code will append 1 to orders and then append the number 20 to the value array as well. If the last value is 0 in order then it will append 1 to order and append the number 15 to value. Expected Output:
Iterating through multiple rows using multiple values from nested dictionary to update data frame in python
I created nested dictionary to keep multiple values for each combination, example rows in the dictionary is as follows:- dict = {‘A’: {B: array([1,2,3,4,5,6,7,8,9,10]), C: array([array([1,2,3,4,5,6,7,8,9,10],…}} There are multiple As and in that multiple arrays for each array. Now I want to updated the data frame which has following rows: Col 1 Col 2 Col 3 Col 4 A B
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),
Loading multiple 2d arrays with different shapes into a new array on a third dimension
I’m currently struggling with a probably rather simple question but I can’t get my head around it. Assuming I have the follow two 2d arrays with different shapes, I can combine them into a new array using: So far so good! But how would I do this if I have a large list where I’d have to iterate over? Here
How to using numpy.argsort on a 2D array to sort another 2D array
I use numpy.argsort all the time for 1D data, but it seems to behaving differently in 2D. For example, let’s say I want to argsort this array along axis 1 so the items in each row are in ascending order All fine so far. Each row in the above gives the order to how the columns should be rearranged in
sum the elements of 2 NumPy arrays
I am trying the sum the elements of these arrays…..but it is throwing this error in jupiter notebook Answer You first need to append the two arrays together, then you can take the total sum.
Stuck in this question and couldn’t understand the code for the sum of subarray
I am stuck in the end function part of the question and arr[start]/arr[end] as well I fail to understand the code. The question is as follows: Given an unsorted array A of size N that contains only non-negative integers, find a continuous sub-array which adds to a given number S. You don’t need to read input or print anything. The
Overwriting an array in Numpy function Python
I am trying to write a numpy function that iterates with itself to update the values of its function. If for example Random_numb was equal to [50, 74, 5, 69, 50]. So the calculations would go like, 10* 50 = 500 for the first calculation, with the equation Starting_val = Starting_val * Random_numb. The Starting_Val would equal to 500 so