spectro | clustered nods.js module | Runtime Evironment library
kandi X-RAY | spectro Summary
kandi X-RAY | spectro Summary
A clustered nods.js module to create spectrograms from pcm audio data
Support
Quality
Security
License
Reuse
Top functions reviewed by kandi - BETA
- Constructor for spectram
- draw the image
spectro Key Features
spectro Examples and Code Snippets
Community Discussions
Trending Discussions on spectro
QUESTION
I am getting the following error when I am trying to run a 1D CNN on a 7 band spectral data. The class labels are binary, and I want a single output. I am attaching the code and the outputs. Apparently, it seems that Conv1D is having some problems ingesting the 7 input bands. I have tried looking at the posts that are already out there, but without much success.
...ANSWER
Answered 2021-Oct-02 at 12:15The following is working for me
QUESTION
I have the following block of code:
...ANSWER
Answered 2021-Sep-22 at 06:54This might work for you (GNU sed):
QUESTION
I reformulate a first question that has been badly explained. I can't delete this question since I risk the blocking of my account, so don't blame me or be too rude on this point.
I try to check under which conditions on the Jacobian used to get the equality or the inequality between 2 Fisher matrices (so symmetric matrices).
The goal is too see if the projection (with Jacobian) and marginalisation (inversion of matrix and remove a row/column and reinversion) commute.
Each of these 2 Fisher matrices is computed slightly differently. These 2 matrices are Fisher matrices.
Actually, this is the computation of changing parameters between initial parameters for each row/column and final parameters for the final matrix. That's why in both computations, I am using the Jacobian J formulating the derivatives between initial and final parameters :
The formula is : F_final = J^T F_initial J
The first matrix has size 5x5 and the second one has 4x4 size. They are identical except the 4th row/column.
1) First Method : I inverse the initial Fisher 5x5 matrix (which gives a 5x5 covariance matrix). Then, I "marginalise", that is to say, I remove the 4th row/column of this covariance matrix. Then, I inverse again to get a final Fisher 4x4 matrix.
Finally, I perform a projection with a reduced Jacobian J' of size 4x4 (identical to the 5x5 Jacobian used in Second method but without 4th row/column) with formula : F_final = J'^T F_initial J : so I get at the end a 4x4 matrix
2) Second Method : For the second matrix to build : I am doing directly projection on 5x5 second matrix (which I recall is identical to the 4x4 except but with a supplementary 4th row/column).
I perform this projection with the Jacobian 5x5. Then I get the second projected matrix 5x5. Finally, I inverse this 5x5 to get covariance matrix and I remove the 4th row/column on this 5x5 matrix covariance, and I inverse again to get a 4x4 matrix new projected matrix.
I wonder under which conditions I could have equality between the 2 matrices 4x4. I don't know if my method is correct.
To show you a practical example, I put below a small Matlab script that tries to follow all the reasoning explained above :
...ANSWER
Answered 2021-Jul-11 at 11:22You might get a better answer on a mathematics site, eg math.stackexchange.com, than in a maths tag of a programming site.
I'm not entirely sure what you are trying to do, but if my interpretation is correct then the answer is no, the matrices are not in general equal.
The block matrix inversion lemma is useful here. For the case in hand, if we write
QUESTION
I have to solve the equality between 2 matrices 12x12 containing a lot of symbolic variables and with which I perform inversion of the matrix. There are only one unknown called SIGAM_O, and FISH_O_SYM(1,1), FISH_O_SYM(1,2) and FISH_O_SYM(2,2) (FISH_O_SYM(2,1) = FISH_O_SYM(1,2).
My system is solved fastly when I take for example 2 matrices 2x2, the inversion is pretty direct.
Now, with the case of 2 matrices 12x12, I need before actually to inverse a 31x31 matrix of symbolic variables (I marginalize after), since inversion takes a lot of time.
I would like to benefit from my GPU NVIDIA card to achieve this inversion faster but the GPU optimization is not supported currently for Symbolic arrays.
Below the script where you will find the line of inversion:
...ANSWER
Answered 2021-May-02 at 10:23(Posted answer on behalf of the question author in order to move it to the answer space).
I resolve this issue by doing simply:
QUESTION
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 :
...ANSWER
Answered 2021-Jan-27 at 21:18From 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.
QUESTION
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 :
...ANSWER
Answered 2021-Jan-26 at 01:54The 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).
QUESTION
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) :
...ANSWER
Answered 2021-Jan-25 at 00:11As stated in the toy example you should be able to run your code if you would change this line
QUESTION
I have requested that we have libsnd file installed on the hpc cluster. The admin said that I can test this via the following link:
https://raw.githubusercontent.com/erikd/libsndfile/master/examples/sndfile-to-text.c
...ANSWER
Answered 2020-Apr-15 at 19:33The module commands helps to define environment variables. It cannot compile a program, so the module load command you ran ends in error as module does not understand your request.
The libsndfile/1.0.28 modulefile should define useful variables for compilation, like LD_LIBRARY_PATH. You can check what environment variable the modulefile defines with:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install spectro
Support
Reuse Trending Solutions
Find, review, and download reusable Libraries, Code Snippets, Cloud APIs from over 650 million Knowledge Items
Find more librariesStay Updated
Subscribe to our newsletter for trending solutions and developer bootcamps
Share this Page
