spm1d | One-Dimensional Statistical Parametric Mapping in Python | Machine Learning library

by 0todd0000 Python Version: 0.4.32 License: GPL-3.0

X-Ray Key Features Code Snippets(1)Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | spm1d Summary

spm1d is a Python library typically used in Artificial Intelligence, Machine Learning, Numpy applications. spm1d has no vulnerabilities, it has build file available, it has a Strong Copyleft License and it has low support. However spm1d has 2 bugs. You can install using 'pip install spm1d' or download it from GitHub, PyPI.

One-Dimensional Statistical Parametric Mapping in Python and MATLAB. spm1d uses Random Field Theory expectations regarding the behavior of smooth, one-dimensional Gaussian fields to make statistical inferences regarding a set of one-dimensional continua. MATLAB source code:

Support

Quality

Security

License

Reuse

Support

spm1d has a low active ecosystem.

It has 58 star(s) with 20 fork(s). There are 10 watchers for this library.

There were 4 major release(s) in the last 6 months.

There are 16 open issues and 235 have been closed. On average issues are closed in 63 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of spm1d is 0.4.32

Quality

spm1d has 2 bugs (1 blocker, 0 critical, 0 major, 1 minor) and 1342 code smells.

Security

spm1d has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

spm1d code analysis shows 0 unresolved vulnerabilities.

There are 64 security hotspots that need review.

License

spm1d is licensed under the GPL-3.0 License. This license is Strong Copyleft.

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

Reuse

spm1d 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.

spm1d saves you 7389 person hours of effort in developing the same functionality from scratch.

It has 15477 lines of code, 908 functions and 353 files.

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

Top functions reviewed by kandi - BETA

kandi has reviewed spm1d and discovered the below as its top functions. This is intended to give you an instant insight into spm1d implemented functionality, and help decide if they suit your requirements.

Cluster the locations of the extents
Interpolate from y to y
Compute endpoints
Estimate the hyperparameters
Compute the design matrix
Estimate the FWHM from a matrix
Calculate the residuals for each sample
Extract the residuals for each group
Compute the minima of a given array
Calculates the p - values for a given covariance matrix
Compute ANOVA
Calculate weather index
Compute an ANOVA
Plot an error cloud
Hotellings 2
Generate a sample of a multirandn
Calculate the cluster clustering
Perform clustering clustering
Calculate the DCA Coefficient
Calculate an ANOVA
Calculate an Aov3 model
Plot mean and SD
Plot a filled filled array
Generate an ANOVA using an ANOVA
Assemble the design matrix
Compute the p - value p

Get all kandi verified functions for this library.

spm1d Key Features

No Key Features are available at this moment for spm1d.

spm1d Examples and Code Snippets

Nested Anova in python with Spm1d. Can't print f statistics and p values

Python

Lines of Code : 23

License : Strong Copyleft (CC BY-SA 4.0)

Copy

p = FFi.get_p_values()
print(p)

([0.016584151119287904], [])

print( FFi[0] )
print( FFi[1] )

SPM{F} inference field
   SPM.effect    :   Main A
   SPM.z         :

Community Discussions

Trending Discussions on spm1d

Nested Anova in python with Spm1d. Can't print f statistics and p values

ImportError: No module named 'spm1d

QUESTION

Nested Anova in python with Spm1d. Can't print f statistics and p values

Asked 2019-Apr-28 at 14:51

I'm looking for a simple solution to perform multi-factor ANOVA analysis in python. A 2-factor nested ANOVA is what I'm after, and the SPM1D python module is one way to do that, however I am having an issue.

http://www.spm1d.org/doc/Stats1D/anova.html#two-way-nested-anova

for any of the nested approach examples, there is never any F-statistic or p_values printed, nor can I find any way to print them or send them to a variable.

To go through the motions of running one of their examples, where B is nested inside A, with Y observations:

...

ANSWER

Answered 2019-Apr-28 at 14:51

The easiest way to get the p values is to use the get_p_values method that you mention, you just need to call the method by adding () to the end.

Source https://stackoverflow.com/questions/48273276

QUESTION

ImportError: No module named 'spm1d

Asked 2017-Apr-08 at 08:29

I have Python 3.5.2 |Anaconda 4.2.0 (x86_64)| on my Mac laptop and I am facing this problem:

import spm1d

Traceback (most recent call last):

ImportError: No module named 'spm1d'

I searched about the problem and I did not find any solution.

Thank you in advance

...

ANSWER

Answered 2017-Apr-08 at 08:29

It means that the module (spm1d) is not installed, you have to install the module before import, open terminal bash run the command: easy_install spm1d

or you can refer to the official document below for more detail: http://www.spm1d.org/install/InstallationPython.html

Hope it will work for you.

Source https://stackoverflow.com/questions/43289658

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

Vulnerabilities

No vulnerabilities reported

Install spm1d

You can install using 'pip install spm1d' or download it from GitHub, PyPI.
You can use spm1d 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: