pypong | Slightly modified clone of Pong classic game | Game Engine library

by skamieniarz Python Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | pypong Summary

pypong is a Python library typically used in Gaming, Game Engine, Pygame applications. pypong has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However pypong build file is not available. You can download it from GitHub.

A slightly modified clone of Pong classic game implemented with Python and pyxel.

Support

Quality

Security

License

Reuse

Support

pypong has a low active ecosystem.

It has 54 star(s) with 10 fork(s). There are 5 watchers for this library.

It had no major release in the last 6 months.

pypong has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of pypong is current.

Quality

pypong has 0 bugs and 0 code smells.

Security

pypong has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

pypong code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

pypong is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

pypong releases are not available. You will need to build from source code and install.

pypong has no build file. You will be need to create the build yourself to build the component from source.

pypong saves you 152 person hours of effort in developing the same functionality from scratch.

It has 378 lines of code, 25 functions and 9 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed pypong and discovered the below as its top functions. This is intended to give you an instant insight into pypong implemented functionality, and help decide if they suit your requirements.

Updates the menu
Updates the paddling position
Determines if the paddings are inside the paddings
Score the event
Check the game score
Updates the selected option
Tests if the edge is up
Resets the state to start
Draws the box
Gets the center coordinate of the text
Draw the button
Return the center coordinate of a list of texts
Display the displayed buttons
Display the winner

Get all kandi verified functions for this library.

pypong Key Features

No Key Features are available at this moment for pypong.

pypong Examples and Code Snippets

No Code Snippets are available at this moment for pypong.

Community Discussions

Trending Discussions on pypong

Spawning multiple instances of a class at different x position pygame

neural network does not learn (loss stays the same)

QUESTION

Spawning multiple instances of a class at different x position pygame

Asked 2019-Nov-10 at 02:38

I'm making a Pong clone in pygame, but I'm having trouble spawning the paddles. My paddle class looks like this:

...

ANSWER

Answered 2019-Nov-10 at 02:38

So the class that you've defined has some issues, and I think it's worth going over some of the basics first and then having a look at your class second. I've split the answer up into those two sections, so you can skip ahead if you must.

A python class can "see" the variables that are passed to it or defined within it. We do that passing and defining in the __init__ method:

Source https://stackoverflow.com/questions/58785082

QUESTION

neural network does not learn (loss stays the same)

Asked 2019-Feb-14 at 13:05

My project partner and I are currently facing a problem in our latest university project. Our mission is to implement a neural network that plays the game Pong. We are giving the ball position the ball speed and the position of the paddles to our network and have three outputs: UP DOWN DO_NOTHING. After a player has 11 points we train the network with all states, the made decisions and the reward of the made decisions (see reward_cal()). The problem we are facing is, that the loss is constantly staying at a specific value only depending on the learning rate. Because of this the network always makes the same decision even though we reward it as terribly wrong.

Please help us find out what we did wrong we are thankful for every advise! Below is our code pls feel free to ask if there are any questions. We are pretty new to this topic so pls don't be rude if there is something completly stupid :D

this is our code:

...

ANSWER

Answered 2019-Feb-14 at 13:05

That's evil 'relu' showing its power.

Relu has a "zero" region without gradients. When all your outputs get negative, Relu makes all of them equal to zero and kills backpropagation.

The easiest solution for using Relus safely is to add BatchNormalization layers before them:

Source https://stackoverflow.com/questions/54688502

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install pypong

You can download it from GitHub.
You can use pypong like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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