I have 50 folders containing the same file name but different contents Data_220_beta_0.1_47.0_53.0ND.csv. I am skipping certain folders which is mentioned in list I. Now, when the code scans all the remaining folders, it looks for values which are different and X = [x for x in X if min(x) != max(x)] contains the lists with distinct values. How do
Tag: numpy
Eliminate for loop when indexing into array
I have two arrays: vals has shape (N,m) where N is ~1 million, and m is 3. The values are floats I have another array indices with shape (N,4). All values in indices are row indices in vals. (Additionally, unlike the example here, every row of indices contains unique values.). I would like replace the following for loop when creating
How to put number of a particular element in a particular row and column constraints in a matrix?
I have to basically create a symmetric matrix of NxN. Which has 1s and 0s randomly populated into it. However the only constraint is I need only one ‘1’ in any row and any column. I wrote a code to generate the matrix but it has more than one ‘1’ in any row or column. I need to follow the
Reading a text file using Pandas accurately in Python
I am trying to read B.txt using pandas. It prints the value of B but not as a list. I present the current and expected outputs. The current output is The expected output is Answer Add squeeze = True for Series, so ouput is B = [‘B=3’], select first value and split, select second value and convert to int:
How to improve performance of dataframe slices matching?
I need to improve the performance of the following dataframe slices matching. What I need to do is find the matching trips between 2 dataframes, according to the sequence column values with order conserved. My 2 dataframes: Expected output: This is the following code I’ m using: Despite working, this is very time costly and unefficient as my real dataframes
Dropping rows and finding the average of a speific column
I am trying to remove specific rows from the dataset and find the average of a specific column after the rows are removed without changing the original dataset Answer can you try this? I think there was a typo in your code
How to use cv2.fillpoly function properly [closed]
Closed. This question needs debugging details. It is not currently accepting answers. Edit the question to include desired behavior, a specific problem or error, and the shortest code necessary to reproduce the problem. This will help others answer the question. Closed 6 months ago. Improve this question I am trying to use the fillpoly function to fill two polygons at
Vectorize calculation of density of image regions
I am trying to implement an image stippling algorithm in python, and want to vectorize calculating the density (average luminance) of labelled image regions (Voronoi cells). Currently I’m able to do so using a loop, but this is too computationally intensive for large numbers of regions. How can I vectorize this operation? Answer The problem is not the loop but
how to make this javascript for-loop converted to python code with same or faster execution time?
Please help to optimize my python code, I wrote this JS code and tried to convert it to python that I need the execution time comparable to the original code. The original code follows for-loop in JS, I transferred the code literally by using pure python and numpy but I didn’t optimize it well resulting in poor execution time and
Delete all zeros slices from 4d numpy array
I pretend to remove slices from the third dimension of a 4d numpy array if it’s contains only zeros. I have a 4d numpy array of dimensions [256,256,336,6] and I need to delete the slices in the third dimension that only contains zeros. So the result would have a shape like this , e.g. [256,256,300,6] if 36 slices are fully