python Programming Glossary: covariance

http://stackoverflow.com/questions/12301071/multidimensional-confidence-intervals

Plots an `nstd` sigma ellipse based on the mean and covariance of a point cloud points an Nx2 array . Parameters points An.. Plots an `nstd` sigma error ellipse based on the specified covariance matrix `cov` . Additional keyword arguments are passed on to.. on to the ellipse patch artist. Parameters cov The 2x2 covariance matrix to base the ellipse on pos The location of the center..

Getting standard errors on fitted parameters using the optimize.leastsq method in python

http://stackoverflow.com/questions/14581358/getting-standard-errors-on-fitted-parameters-using-the-optimize-leastsq-method-i

the terminology. From what I understand all I need is the covariance matrix that goes with my fitted parameters so I can square root.. parameters. I have a vague memory of reading that the covariance matrix is what is output from the optimize.leastsq method anyway... matrix to multiply the outputted Jacobian by to get my covariance matrix Any help would be greatly appreciated. I am very new..

Principal component analysis in Python

http://stackoverflow.com/questions/1730600/principal-component-analysis-in-python

SVD will be slower than computing the eigenvectors of the covariance matrix. I was hoping to find a premade debugged implementation..

Solve equation with a set of points

http://stackoverflow.com/questions/18619131/solve-equation-with-a-set-of-points

fluo #fit the data return the best fit parameters and the covariance matrix #popt pcov curve_fit myFunc x yn popt pcov curve_fit.. len x #fit the data return the best fit parameters and the covariance matrix popt pcov curve_fit myFunc x yn print popt print pcov..

Fitting a line in 3D

http://stackoverflow.com/questions/2298390/fitting-a-line-in-3d

the line whose direction vector is the eigenvector of the covariance matrix corresponding to the largest eigenvalue that passes through..

How to sort my paws?

http://stackoverflow.com/questions/4502656/how-to-sort-my-paws

fuzzy nature of images i.e. adjacent pixels have a high covariance simply looking at the difference of an image from a template.. linear algebra for speed. We can work directly with the covariance matrix of the training data set def make_eigenpaws paw_data.. 0 paw_data average_paw # Determine the eigenvectors of the covariance matrix of the data cov np.cov paw_data.T eigvals eigvecs np.linalg.eig..