multi-vector-simulator | vector Simulation Tool

by rl-institut Python Version: 1.1.1rc1 License: GPL-2.0

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

kandi X-RAY | multi-vector-simulator Summary

multi-vector-simulator is a Python library typically used in Manufacturing, Utilities, Energy, Utilities applications. multi-vector-simulator has no bugs, it has no vulnerabilities, it has build file available, it has a Strong Copyleft License and it has low support. You can install using 'pip install multi-vector-simulator' or download it from GitHub, PyPI.

Multi-vector Simulation Tool assessing and optimizing Local Energy Systems (LES) for the E-LAND project

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Quality

Security

License

Reuse

Support

multi-vector-simulator has a low active ecosystem.

It has 15 star(s) with 8 fork(s). There are 5 watchers for this library.

There were 5 major release(s) in the last 6 months.

There are 120 open issues and 352 have been closed. On average issues are closed in 146 days. There are 5 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of multi-vector-simulator is 1.1.1rc1

Quality

multi-vector-simulator has 0 bugs and 0 code smells.

Security

multi-vector-simulator has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

multi-vector-simulator code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

multi-vector-simulator is licensed under the GPL-2.0 License. This license is Strong Copyleft.

Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

Reuse

multi-vector-simulator releases are available to install and integrate.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

It has 17802 lines of code, 689 functions and 65 files.

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

Top functions reviewed by kandi - BETA

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

Create a Flask application
Translates the given optimization cap to yes or no
Convert the cost matrix to a pandas dataframe
Convert a dictionary of energy values to a pandas dataframe
Optimize constant efficiency
Return an item from a list
Returns the length of a list
Evaluate a dictionary
Processes fix cost matrix
Load a simulation setting from a JSON file
Determine the total demand and total demand for each sector
Calculate a constraint for minima
Calculate the minimum degree of anautonomy constraint
Create a report
Create a json file from csv files
Calculate the cost of each energy carrier
Get the timeseries for a given bus
Determine the result of an asset
Aggregate the total renewable and non renewable energies
Calculates the capex cost for an investment
Run a sensitivity analysis step
Calculates costs for a given asset
Calculates the net zero energy of a network
Checks the constant efficiency
Calculate the result of a storage function
Process the command line arguments

Get all kandi verified functions for this library.

multi-vector-simulator Key Features

No Key Features are available at this moment for multi-vector-simulator.

multi-vector-simulator Examples and Code Snippets

No Code Snippets are available at this moment for multi-vector-simulator.

Community Discussions

No Community Discussions are available at this moment for multi-vector-simulator.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install multi-vector-simulator

You can install using 'pip install multi-vector-simulator' or download it from GitHub, PyPI.
You can use multi-vector-simulator 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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