From 65b2731ff479b7e9ac17c596255e2cd0634dbf1e Mon Sep 17 00:00:00 2001 From: fjosw Date: Thu, 3 Mar 2022 10:12:18 +0000 Subject: [PATCH] Documentation updated --- docs/pyerrors/fits.html | 14 +++++--------- 1 file changed, 5 insertions(+), 9 deletions(-) diff --git a/docs/pyerrors/fits.html b/docs/pyerrors/fits.html index 4007e417..e1b07fc1 100644 --- a/docs/pyerrors/fits.html +++ b/docs/pyerrors/fits.html @@ -559,15 +559,11 @@ x0 = [0.1] * n_parms if kwargs.get('correlated_fit') is True: - cov = covariance(y) - covdiag = np.diag(1. / np.sqrt(np.diag(cov))) - corr = np.copy(cov) - for i in range(len(y)): - for j in range(len(y)): - corr[i][j] = cov[i][j] / np.sqrt(cov[i][i] * cov[j][j]) + corr = covariance(y, correlation=True) + covdiag = np.diag(1 / np.asarray(dy_f)) condn = np.linalg.cond(corr) - if condn > 1e4: - warnings.warn("Correlation matrix may be ill-conditioned! condition number: %1.2e" % (condn), RuntimeWarning) + if condn > 1e8: + warnings.warn("Correlation matrix may be ill-conditioned, condition number: %1.2e" % (condn), RuntimeWarning) chol = np.linalg.cholesky(corr) chol_inv = np.linalg.inv(chol) chol_inv = np.dot(chol_inv, covdiag) @@ -588,7 +584,7 @@ if output.method != 'Levenberg-Marquardt': if output.method == 'migrad': - fit_result = iminuit.minimize(chisqfunc, x0, tol=1e-4) # Stopping crieterion 0.002 * tol * errordef + fit_result = iminuit.minimize(chisqfunc, x0, tol=1e-4) # Stopping criterion 0.002 * tol * errordef output.iterations = fit_result.nfev else: fit_result = scipy.optimize.minimize(chisqfunc, x0, method=kwargs.get('method'), tol=1e-12)