Nashpy | A python library for 2 player games
kandi X-RAY | Nashpy Summary
kandi X-RAY | Nashpy Summary
Nashpy is a Python library. Nashpy has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However Nashpy build file is not available. You can install using 'pip install Nashpy' or download it from GitHub, PyPI.
This library implements the following algorithms for Nash equilibria on 2 player games:. Nashpy has a small set of Python dependencies: it only requires numpy and scipy so is straightforward to install on all operating systems.
This library implements the following algorithms for Nash equilibria on 2 player games:. Nashpy has a small set of Python dependencies: it only requires numpy and scipy so is straightforward to install on all operating systems.
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Support
Nashpy has a low active ecosystem.
It has 260 star(s) with 52 fork(s). There are 8 watchers for this library.
There were 1 major release(s) in the last 6 months.
There are 23 open issues and 48 have been closed. On average issues are closed in 71 days. There are 1 open pull requests and 0 closed requests.
It has a neutral sentiment in the developer community.
The latest version of Nashpy is 0.0.41
Quality
Nashpy has 0 bugs and 41 code smells.
Security
Nashpy has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
Nashpy code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
Nashpy is licensed under the MIT License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.
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Nashpy releases are available to install and integrate.
Deployable package is available in PyPI.
Nashpy has no build file. You will be need to create the build yourself to build the component from source.
Installation instructions, examples and code snippets are available.
Nashpy saves you 682 person hours of effort in developing the same functionality from scratch.
It has 1579 lines of code, 82 functions and 27 files.
It has high code complexity. Code complexity directly impacts maintainability of the code.
Top functions reviewed by kandi - BETA
kandi has reviewed Nashpy and discovered the below as its top functions. This is intended to give you an instant insight into Nashpy implemented functionality, and help decide if they suit your requirements.
- Wrapper for stochastic ficts
- Starts stochastic fictically
- Calculates the probability response to a given function
- Updates the play count
- The vertex enumeration
- Return non - trivial vertices in halfspace
- Build the halfspaces of a given matrix
- Perform vertex enumeration
- Return support_enumeration
- Return a generator of equilibria
- Return whether the given strategy supports support
- Solve inequality strategies
- Compute the fixation probability
- Process Moran
- Calculate the fixation probability for a given matrix A
- Compute the score of all individual individuals
- Returns a fictitious play
- Generate a sequence of play_counts
- Returns the best response to a given player
- Compute the asymmetric replicator of payoff matrices
- Calculate asymmetric replicates
- Checks if the payoff matrix is the best response
- Return True if A is a best response
- Compute the payoff matrix
- Compute the derivative of the replacement function
- Process moran process
Get all kandi verified functions for this library.
Nashpy Key Features
No Key Features are available at this moment for Nashpy.
Nashpy Examples and Code Snippets
No Code Snippets are available at this moment for Nashpy.
Community Discussions
Trending Discussions on Nashpy
QUESTION
Why on earth can I not import nashpy into my Python library?
Asked 2018-Dec-05 at 05:00
import nashpy as nash
ANSWER
Answered 2018-Dec-05 at 05:00If you look at the line which is causing the error, you'll see this:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install Nashpy
To install Nashpy on Fedora, use:.
Support
Full documentation is available here: http://nashpy.readthedocs.io/.
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