logplot | Awesome interactive plots from custom logs | Data Visualization library

by jerry-git Python Version: 1.0.4 License: MIT

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

kandi X-RAY | logplot Summary

logplot is a Python library typically used in Analytics, Data Visualization, Jupyter applications. logplot has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install logplot' or download it from GitHub, PyPI.

Awesome interactive plots from custom logs

Support

Quality

Security

License

Reuse

Support

logplot has a low active ecosystem.

It has 25 star(s) with 1 fork(s). There are 3 watchers for this library.

It had no major release in the last 12 months.

There are 8 open issues and 9 have been closed. On average issues are closed in 6 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of logplot is 1.0.4

Quality

logplot has no bugs reported.

Security

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

License

logplot 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

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

Deployable package is available in PyPI.

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

Installation instructions are not available. Examples and code snippets are available.

Top functions reviewed by kandi - BETA

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

Create a legend
Return the next colour
Handle click event
Open the log viewer
Plot a log plot
Return the absolute path to the user config file

Get all kandi verified functions for this library.

logplot Key Features

No Key Features are available at this moment for logplot.

logplot Examples and Code Snippets

Plotting logs

Python

Lines of Code : 3

License : Permissive (MIT)

Copy

$ logplot path/to/log -c path/to/conf/file

$ logplot doc/examples/log.txt -c doc/examples/user_conf.yaml

$ logplot doc/examples/log_huge.txt -c doc/examples/user_conf_huge.yaml

LogPlot,Installation

Python

Lines of Code : 1

License : Permissive (MIT)

Copy

$ pip3 install logplot

Community Discussions

Trending Discussions on logplot

nicer ticks for logarithmic Axes3D

LogLinear and LogLog plots in android

QUESTION

nicer ticks for logarithmic Axes3D

Asked 2017-May-01 at 19:32

creating a log Axes3D object is an issue (see here)

a workaround is

...

ANSWER

Answered 2017-May-01 at 19:32

You can use the following format:

Source https://stackoverflow.com/questions/43725107

QUESTION

LogLinear and LogLog plots in android

Asked 2017-Apr-13 at 09:49

I want my application to be able to display frequency response graphs but I cannot find any graphing library that has this functionality. I am currently using MPAndroidChart for some other charts (and it is great !) but sadly I could not find any way to use it to do log plots. I have also tried using numAndroidCharts (numcharts logplot example), but that library seems broken/outdated since i couldn't even get the example code to work properly. Is there anyway that you know of to achieve this ?

...

ANSWER

Answered 2017-Apr-13 at 09:49

I use MPAndroidChart with a log scale with converted values.

For example if your value is 1E-5:

Source https://stackoverflow.com/questions/43388383

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

Vulnerabilities

No vulnerabilities reported

Install logplot

You can install using 'pip install logplot' or download it from GitHub, PyPI.
You can use logplot 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 .

Find more information at: