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1d6f7f65c0
* feat: corr_matrix kwargs as input for least squares fit * feat/tests: inverse covariance matrix and correlation matrix kwargs as input for least squares function * feat/tests/example: reduced new kwargs to 'inv_chol_cov_matrix' and outsourced the inversion & cholesky decomposition of the covariance matrix (function 'invert_corr_cov_cholesky(corr, covdiag)') * tests: added tests for inv_chol_cov_matrix kwarg for the case of combined fits * fix: renamed covdiag to inverrdiag needed for the cholesky decomposition and corrected its documentation * examples: added an example of a correlated combined fit to the least_squares documentation * feat/tests/fix(of typos): added function 'sort_corr()' (and a test of it) to sort correlation matrix according to a list of alphabetically sorted keys * docs: added more elaborate documentation/example of sort_corr(), fixed typos in documentation of invert_corr_cov_cholesky() |
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| .. | ||
| input | ||
| __init__.py | ||
| correlators.py | ||
| covobs.py | ||
| dirac.py | ||
| fits.py | ||
| integrate.py | ||
| linalg.py | ||
| misc.py | ||
| mpm.py | ||
| obs.py | ||
| roots.py | ||
| special.py | ||
| version.py | ||