floor | A C++ Compute/Graphics Library and Toolchain enabling same-source CUDA/Host/Metal/OpenCL/Vulkan C++ | GPU library

I have source (src) image(s) I wish to align to a destination (dst) image using an Affine Transformation whilst retaining the full extent of both images during alignment (even the non-overlapping areas).

I am already able to calculate the Affine Transformation rotation and offset matrix, which I feed to scipy.ndimage.interpolate.affine_transform to recover the dst-aligned src image.

The problem is that, when the images are not fuly overlapping, the resultant image is cropped to only the common footprint of the two images. What I need is the full extent of both images, placed on the same pixel coordinate system. This question is almost a duplicate of this one - and the excellent answer and repository there provides this functionality for OpenCV transformations. I unfortunately need this for scipy's implementation.

Much too late, after repeatedly hitting a brick wall trying to translate the above question's answer to scipy, I came across this issue and subsequently followed to this question. The latter question did give some insight into the wonderful world of scipy's affine transformation, but I have as yet been unable to crack my particular needs.

The transformations from src to dst can have translations and rotation. I can get translations only working (an example is shown below) and I can get rotations only working (largely hacking around the below and taking inspiration from the use of the reshape argument in scipy.ndimage.interpolation.rotate). However, I am getting thoroughly lost combining the two. I have tried to calculate what should be the correct offset (see this question's answers again), but I can't get it working in all scenarios.

Translation-only working example of padded affine transformation, which follows largely this repo, explained in this answer:

This is a dumb question, And I can't believe I asked for a solution, Well now that I am pretty good I answered it. So, Firstly I create the variable number then I add two properties to it's prototype called oldValue and randomize then I set randomize to a random decimal number between 0 and 1 using Math.random(), I store the value of the number variable before any further changes, In the property I added to the prototype called oldValue, After that I check if the randomize is less than 0.5 or more than 0.5 if less then I decrement a random number between 50-100 else I increment with a number between 50-100, At last I console.log() the changes.

I wonder how can we filter rows with the same values in columns using dplyr package? I tried doing something in opposite to what was asked and proposed in this question but nothing worked.

I used the approach with apply function but received the following error:

I'm trying to create a board game with p5.js (Javascript)

To set up the game board which is a 6 by 6 grid, I have to fill the grid with 6 colors in a way that no horizontal or vertical touching cells have the same color. And all 6 colors have to be used in 6 cells.

But now I'm struggling a bit creating an algorithm that places the colors randomly but keeping the rules.

I tried to start at the top left corner, filling with a random color. Then I start to fill the cell to the left and the bottom with a different color.

The problem is, that when the script wants to fill the last few cells, there are no colors left to use (either already 6 cells filled or a remaining color is a neighbor)

Example: Still two cells need to be red, but only one place is left for red (under white):

I have large file with many information

I know Python // rounds towards negative infinity and in C++ / is truncating, rounding towards 0.

And here's what I know so far:

I am currently doing a javascript course on udemy and ran into a problem with a small coding challenge. The code is supposed to pick a random person from an array. My code works on their test platform, but i cant get it to work in the chrome developer tools.

My problem requires me to summarize data across multiple columns, but each column must be summarized by a multi-variate function of three other columns.

I have a data frame with hundreds of columns carrying different statistical information about a dataset. Here is a similarly structured, smaller dataframe.

I have a simple chat app using Firebase v9, with these components from parent to child in this hierarchical order: ChatSection, Chat, ChatLine, EditMessage.

I have a custom hook named useChatService holding the list of messages in state, the hook is called in ChatSection, the hook returns the messages and I pass them from ChatSection in a prop to Chat, then I loop through messages and create a ChatLine component for every message.

I can click the Edit button in front of each message, it shows the EditMessage component so I can edit the text, then when I press "Enter", the function updateMessage gets executed and updates the message in the db, but then every single ChatLine gets rerendered again, which is a problem as the list gets bigger.

EDIT 2: I've completed the code to make a working example with Firebase v9 so you can visualize the rerenders I'm talking about after every (add, edit or delete) of a message. I'm using ReactDevTools Profiler to track rerenders.

• Here is the full updated code: CodeSandbox
• Also deployed on: Netlify

ChatSection.js: