I have For each element in listB, I want to extend it to a length-3 element by adding a number that is in listall but not in this element. My desired output is the following list: As a first step, I tried the following code: However, the output I got is: This is far from what I wanted. As each
Tag: arrays
Numpy 2D-array sets the value of a cell when it is not needed
I’m trying to write minesweeper in python. A bomb is a cell with a value less than 0. The values of cells that differ from the position of the bomb cell by one column and one row in all directions should increase by 1. But the values of cells that are far from the bomb often increase. Please help me
Is there a way to wrap every single entry of an numpy.ndarray into a separate array?
I’m facing some problems getting an array into the right shape to use it as an input into a convolutional neural net: My array has the shape (100,64,64), but I’d need it to be (100,64,64,1). I realize it looks a bit odd, but I basically want to pack every single entry into a separate array. A simplified example, with a
How to print each possible permutation of several arrays of strings on Python?
Let’s say I have the following arrays of strings: I want to print a list that contains all possible permutations of each element mentioned in the arrays above, following the order in which these arrays were set (i.e. it starts checking on Background, then goes to check Body, then Eyes, then Color, then Hands, and finishes on Extra). The first
Python – Group(Cluster/Sort) arrays based on ranking information
I have a dataframe looks like this: I converted the dataframe into 2D arrays like this: The score of each row 1-5 actually means the people give the scores to item A, B, C, D. I would like to identify the people who have the same ranking, for example the people think A > B > C > D. And
The most efficient way to sum all possible pairs (x_ik, y_j) for a given k?
I have two numpy array x with shape (n,m) and y with shape (p,). I would like to sum all possible pairs x[k, i] and y[j] to create a new numpy array z with shape (n, m*p). A naïve algorithm would be : This algorithm has a polynomial complexity : O(n*m*p) Knowing I am working on array with $n ~
Question about turning a list of numpy arrays into an object array
I have a question about turning a list of numpy arrays into an object array. This results in two very different outcomes: I assume that the difference comes from the fact that in testing_2_array not all arrays have the same size. Is there any way to force numpy to output testing_1_array in the same way as testing_2_output so that I
how to return None for empty array in python?
I have a dataframe with two columns. Column one contains an integer, the second column a list with multiple items, which also can be empty. I want to return a list with tuples, in which the first part of the tuple is the integer from col1, and the second part of the tuple is the integer from col2, listing in
Zipping two np.array into array
Im trying to combine following two np.arrays into a single array: The combination array must look like this [[i, pred, boxes],…]: I tried doing it this way, but it unfortunately didn’t work: Is there a way to do this? I tried other means but those tries were even worse. Answer Try hstack:
Normalize two arrays with second array the base for normalizing first array
In order to find the quality indicators like Generational Distance, Inverted Generational Distance, Epsilon Indicator, and HyperVolume for a Pareto front I want to normalize the values of approximation front obtained on solving the algorithm based on reference front which I assume encloses the approximation front. I have used the code below for normalization. However, it is for one array