o si@sddlZdZddZdS)Ng:0yE>cCst||\}}|tj|ddd}|tj|ddd}tj|ddddt}tj||ddd|}||}||}tj|dddtj|dddt}tjdt|ttjdS) uQ Scale-Invariant Signal-to-Distortion Ratio (SI-SDR) Args: reference: numpy.ndarray, [..., T] estimation: numpy.ndarray, [..., T] Returns: SI-SDR [1] SDR– Half- Baked or Well Done? http://www.merl.com/publications/docs/TR2019-013.pdf >>> np.random.seed(0) >>> reference = np.random.randn(100) >>> si_sdr(reference, reference) inf >>> si_sdr(reference, reference * 2) inf >>> si_sdr(reference, np.flip(reference)) -25.127672346460717 >>> si_sdr(reference, reference + np.flip(reference)) 0.481070445785553 >>> si_sdr(reference, reference + 0.5) 6.3704606032577304 >>> si_sdr(reference, reference * 2 + 1) 6.3704606032577304 >>> si_sdr([reference, reference], [reference * 2 + 1, reference * 1 + 0.5]) array([6.3704606, 6.3704606]) T)keepdims)axisr)r )dtype)npbroadcast_arraysmeansumEPSarraylog10float64) reference estimationreference_energyoptimal_scaling projectionnoiseratiorX/home/ubuntu/.local/lib/python3.10/site-packages/pb_bss_eval/evaluation/module_si_sdr.pysi_sdrs  r)numpyrr rrrrrs