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Questions tagged [eigenvalue]

The eigenvalue is the factor by which the eigenvector is scaled when multiplied by the matrix.

The eigenvectors of a square matrix are the non-zero vectors that, after being multiplied by the matrix, remain parallel to the original vector. For each eigenvector, the corresponding eigenvalue is the factor by which the eigenvector is scaled when multiplied by the matrix. The prefix eigen- is adopted from the German word "eigen" for "own"[1] in the sense of a characteristic description. The eigenvectors are sometimes also called characteristic vectors. Similarly, the eigenvalues are also known as characteristic values.

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How to calculate covariance matrix of data frame

I have read data frame of sensor data, using pandas read_fwf function. I need to find covariance matrix of read 928991 x 8 matrix. Eventually, I want to find eigen vectors and eigen values, using principal component analysis algorithm for this…
YatShan
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Looking for variation accounted for by each principal coordinate (component, axis, etc.) in principal coordinates of neighborhood matrix analysis

After completing the pcnm analysis on the set of data I can call on all of the axes and kick out the newly created standarized values from the analysis. However, before I go putting these values into multiple regression or other analyses I would…
Matthew Acre
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Eig in Python giving different Eigenvalues?

So essentially what the problem is the eig function in Matlab and Python are giving me different things. I am reproducing data from a paper in order to confirm my numerical method is correct (So I know the answers- have them via Matlab) I have tried…
lnbmoco
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Finding eigen vectors using numpy.linalg.eig

I want to find the eigen vector for a matrix. I am using the numpy.linalg.eig library in python. The output obtained from this command is not giving eigen vector in the vector form. x = np.array([[0, 1], [-2, -3]]) val, vec=np.linalg.eig(x) vec…
Subham Kumar
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Intel MKL LAPACKE_dsyevd with n > 32766 --> Not enough memory to allocate work array in LAPACKE_dsyevd

I want to compute all eigenvalues and all eigenvectors of a real symmetric matrix using LAPACKE_dsyevd from Intel MKL (2019 Update 2). I'm having the following method in C#: public static class MKL { public static double[,]…
Wollmich
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Using eigenvalues and eigenvector to compress an image

I want to compress an image using eigenvalues and eigenvector, since I already done it using singular value decomposition, but I do something wrong while trying to compress it using eigenvalues and eigenvectors. Here is some code to see what I've…
user7375873
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Problem understanding Principal Component Analysis code

Can anyone please explain me this line of code? P = vectors.T.dot(C.T) at line 22 I have searched for online documentation but I found nothing. from numpy import array from numpy import mean from numpy import cov from numpy.linalg import eig #…
Harshal Sawant
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handling large non-sparse matrices for computing SVD

I have a large matrix (right now about 450000 x 50, might be even larger) that I want to compute its SVD decomposition. The matrix isn't sparse and numpy can't seem to handle it and exits with MemoryError. I tried using np.float16 and it didn't…
HadarM
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Getting different answers from scipy.linalg.eig()

I have two matrices R and F R = array([[ 0.89148867, 4.58007519, 15.70287019], [ 5.1065172 , 14.26381865, 34.50113854], [18.51056089, 36.78238723, 72.21058193]]) F = array([[ 4.9348022, 12.3370055, 24.674011 ], [12.3370055, 19.7392088,…
Tristan Greenwood
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Calculating eigenvectors/values of a 2x2 tensor

I'm implementing the system described within this paper, and I'm getting a little stuck. I only recently encountered tensors/eigenvalues etc so excuse me if this is a little simple! Given a 2x2 tensor, how can I calculate the major and minor…
Martin
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Identifying variables that make up Comp1, 2, 3 & 4 Eigenvalues in R

I have this eigenvalue output. How do I identify the variables that are embedded in Comp 1, 2, 3 & 4? eigenvalue percentage of variance cumulative percentage of variance comp 1 2.9839729 74.5993220 74.59932 comp…
Kayf4
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scipy.linalg.sparse.eigsh returns negative and non-consistent eigenvalues for positive semi-definite matrix

I try to use scipy.linalg.sparse.eigsh (let's call it method 1 : M1) to compute the smallest eigenvalues of the Laplacian matrix of a real symmetric semi-definite matrix W. As a benchmark, I ran the computation against scipy.linalg.eigh (method 2 :…
Nero
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Why the eigen function returns "number of items to replace is not a multiple of replacement length"?

I'm using for the question here the classic example of the Lotka-Volterra model with predation (2 ODEs, 6 parameters). I need to calculate the equilibrium point, which I know the analytical expression of, and the eigenvalues of the Jacobian matrix…
Elsa
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Calculating eigenvalues of matrix as a function of a parameter

I am trying to solve the eigenvalues of a 6x6 matrix as a function of a single parameter which I've called "e". As you can see from the code I evaluate the eigenvalues for a range of values in "detuning". I want to plot these 6 eigenvalues as a…
PhysicsMan
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Matching Largest Eigenvalues to Eigenvectors

In Python I've calculated the eigenvectors and eigenvalues of my data matrix X through eig(). I'm looking to find the top 2 principal components of the data (U = [u1 u2]). I know the top 2 components are the 2 eigenvectors corresponding to the 2…
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