qndiag | Quasi-Newton algorithm for joint-diagonalization | Math library

by pierreablin Python Version: 0.1 License: MIT

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kandi X-RAY | qndiag Summary

qndiag is a Python library typically used in Utilities, Math applications. qndiag 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 qndiag' or download it from GitHub, PyPI.

This Python package contains code for fast joint-diagonalization of a set of positive definite symmetric matrices. The main function is qndiag, which takes as input a set of matrices of size (p, p), stored as a (n, p, p) array, C. It outputs a (p, p) array, B, such that the matrices B @ C[i] @ B.T (python), i.e. B * C(i,:,:) * B' (matlab/octave) are as diagonal as possible.

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qndiag has a low active ecosystem.

It has 16 star(s) with 5 fork(s). There are 6 watchers for this library.

It had no major release in the last 12 months.

There are 0 open issues and 1 have been closed. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of qndiag is 0.1

Quality

qndiag has no bugs reported.

Security

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

License

qndiag 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

qndiag 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, examples and code snippets are available.

Top functions reviewed by kandi - BETA

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

R Solve quadrature decomposition
Transform a set of matrices into a matrix
Performs line search
Computes the loss of a diagonal matrix
Transform a matrix into a matrix
Calculates the loss function of a diagonal matrix
Compute the gradient of a matrix

Get all kandi verified functions for this library.

qndiag Key Features

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qndiag Examples and Code Snippets

No Code Snippets are available at this moment for qndiag.

Community Discussions

Trending Discussions on qndiag

Unable to perform assignment because the size of the left side is 1-by-7-by-7 and the size of the right side is 6-by-6

AttributeError: 'str' object has no attribute 'dot'

AttributeError: 'dict' object has no attribute 'T' (T for transposition)

QUESTION

Unable to perform assignment because the size of the left side is 1-by-7-by-7 and the size of the right side is 6-by-6

Asked 2021-Jan-27 at 21:18

I am looking for a way to find same eigenvectors for 2 given matrices, this way I would make a joint diagonalisation. For this, I found out and tried to use qndiag (from https://github.com/pierreablin/qndiag.git ) from the following function :

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ANSWER

Answered 2021-Jan-27 at 21:18

From the documentation for eigs:

d = eigs(A) returns a vector of the six largest magnitude eigenvalues of matrix A.

If you want all seven, you need to call d = eigs(A,7) or d = eig(A). For a small matrix (e.g. < 1000 x 1000) it's usually easier to just get all the eigenvalues with eig, rather than get a subset with eigs.

Edit: Responding to your "Update 3"

for k=1:length(D) should be replaced by for k=1:n. This needs to be changed on two lines. Judging from your error message they are lines 231 and 236.

L = length(X) returns the length of the largest array dimension in X, which in your case is 7, i.e. too high for the first dimension.

Source https://stackoverflow.com/questions/65907134

QUESTION

AttributeError: 'str' object has no attribute 'dot'

Asked 2021-Jan-26 at 22:55

I am using the qndiag library to try to find a diagonalisation for 2 given matrices.

The github is here : qndiag libray

I am using this Python script to compute these 2 diagonalisation as closed as possible :

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ANSWER

Answered 2021-Jan-26 at 01:54

The issue lies in [D, B] = qndiag(C, 'max_iter', 1000, 'tol', 1e-3), B0 (which is the second param) gets assigned as a string not as an array! Then eventually B would be a string and hence the error message str object has no attribute 'dot' !, if you are only passing C matrix as parameter, just do [D, B] = qndiag(C).

Source https://stackoverflow.com/questions/65876513

QUESTION

AttributeError: 'dict' object has no attribute 'T' (T for transposition)

Asked 2021-Jan-26 at 22:55

I am using the qndiag library to try to find a diagonalisation for 2 given matrices.

The github is here : qndiag libray

The function qndiag is defined like this (not entirely source) :

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ANSWER

Answered 2021-Jan-25 at 00:11

As stated in the toy example you should be able to run your code if you would change this line

Source https://stackoverflow.com/questions/65877295

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

Vulnerabilities

No vulnerabilities reported

Install qndiag

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