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  • src/sas/sascalc/invariant/invariant.py

    r574adc7 rdbfd307  
    344344        else: 
    345345            A = np.vstack([linearized_data.x / linearized_data.dy, 1.0 / linearized_data.dy]).T 
    346             (p, residuals, _, _) = np.linalg.lstsq(A, linearized_data.y / linearized_data.dy) 
     346            # CRUFT: numpy>=1.14.0 allows rcond=None for the following default 
     347            rcond = np.finfo(float).eps * max(A.shape) 
     348            p, residuals, _, _ = np.linalg.lstsq(A, linearized_data.y / linearized_data.dy, 
     349                                                 rcond=rcond) 
    347350 
    348351            # Get the covariance matrix, defined as inv_cov = a_transposed * a 
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