nolds | Nonlinear measures for dynamical systems (based on one-dimensional time series) | Time Series Database library
kandi X-RAY | nolds Summary
kandi X-RAY | nolds Summary
nolds is a Python library typically used in Database, Time Series Database applications. nolds 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 nolds' or download it from GitHub, PyPI.
Nonlinear measures for dynamical systems (based on one-dimensional time series)
Nonlinear measures for dynamical systems (based on one-dimensional time series)
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Quality
Security
License
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Support
nolds has a low active ecosystem.
It has 208 star(s) with 53 fork(s). There are 13 watchers for this library.
It had no major release in the last 12 months.
There are 3 open issues and 19 have been closed. On average issues are closed in 111 days. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of nolds is 0.5.2
Quality
nolds has 0 bugs and 0 code smells.
Security
nolds has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
nolds code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
nolds 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
nolds 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.
Top functions reviewed by kandi - BETA
kandi has reviewed nolds and discovered the below as its top functions. This is intended to give you an instant insight into nolds implemented functionality, and help decide if they suit your requirements.
- Plot the given logistic map
- Run lyap_eap_e
- Logistic map
- Generate a tent map
- Plot a figure 2
- Calculate the squares of the data
- Calculate the log mid point distribution
- Calculate expected RS
- Load Financial Finance
- Compute hurst_mf_mf_stock_dm_dm
- Calculate the mean value of a time series
- Generates astress distance distribution
- Detrended data
- Plot differences between n values
- Plot barabasi - 1 plot
- Calculate a barabasi - traction
- Plots a straight line fitting
- Calculate the variance of a line
- Generate the barabasi - 2 plot
- Calculate expected H
- FGN function
- Generate a random FBM
- Plot a histogram of the hurst exponent exponent
- Default sampen with default tolerance
- Generate a sampen matrix
- Load brown72
Get all kandi verified functions for this library.
nolds Key Features
No Key Features are available at this moment for nolds.
nolds Examples and Code Snippets
No Code Snippets are available at this moment for nolds.
Community Discussions
Trending Discussions on nolds
QUESTION
TypeError: unhashable type on new computer but not old
Asked 2017-Jul-23 at 02:12
I just got a new computer, and now a bunch of my python scripts dont work because they return the following error:
...ANSWER
Answered 2017-Jul-23 at 02:12Add the argument show_labels=False to the run() call:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install nolds
You can install using 'pip install nolds' or download it from GitHub, PyPI.
You can use nolds 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.
You can use nolds 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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