⭐ sparse matrix
⭐ easy to play
⭐ Build to sovle problem
Run terminal or git bash and write : git clone https://github.com/koo039/Donut_Crush_Game.git
📦 Donut-Crush-Gamee_win.zip 31 MB [Windows]
💡 Native x64 one-click exe - Noo required.
📦 Donut-Crush-src_code 4.64 MB [Game_Src]
💡 python and pygame required.
📦 Donut-Crush-web_browser 4.4 MB [Web]
💡 You need to run it on your localhost. We explain how to do it below.
📦 Web_Site_online 4.4 MB [Web]
💡 You can play it online and i don't update it last verstion yet.
We use here web assembly( pygpag ) Python.
you just follow below if you're not intresting .
Download the web folder from above.
Open the command prompt or terminal you use, and type the following command:
cd CandyCrush_Web_brower/web # Navigate to this directory
python -m http.server # Start your local server And don't close your terminal. Go to your browser and type:
http://localhost:8000/- ESC Exit the game.
- Space for Pause.
- -> go right.
- <- go left.
When working on large-scale projects such as Recommendation Systems or Natural Language Processing (NLP), dealing with extensive matrices is inevitable. These matrices >often consist of millions or even billions of elements, leading to significant memory consumption. To tackle this issue, we recommend utilizing a sparse matrix data >structure. In sparse matrices, memory usage is optimized by representing only the non-zero elements along with their respective coordinates. Each element in a sparse matrix is >represented by a quintuple: (Val, I, J, PL, PC). Val: Represents the value of the matrix element. I, J: Denote the coordinates of the element within the matrix. PL, PC: Pointers to the next element in the same row (PL) and the next element in the same column (PC). Accessing the matrix is facilitated through two arrays: TL and TC. TL: Array of pointers representing the list heads of the row elements. TC: Array of pointers representing the list headers of the column elements. Refer to Figure 1-1 for a visual representation of this structure.
we've developed our Donut Crush game to address this issue, aiming to enhance our skills and gain valuable experience in game development , In the "Sparse matrix" folder above ,written in the C programming language, you can find the implementation of this solution. It aims to optimize memory usage in large-scale projects by utilizing a >sparse matrix data structure. This structure represents only the non-zero elements along with their coordinates, effectively reducing memory consumption. If you're >interested in understanding how the problem works and how the solution is implemented, you'll find detailed explanations and code in the 'dsa' folder.