def fit_energy_dependence( data, envir, curve_loader, db_conn, constrained_background=False, retries=10, rms_filter=True ): for s, t, w, pp, z, bg in zip( data.Timestamp.values, data.temperature_start.values, data.W.values, data.PP, data.Z.values, data.BG.values ): curve = curve_loader(s) for i in range(0, retries): result = update_hanle( data=curve, temperature=t * U_.kelvin, wavelength=w * U_.nanometer, probe_intensity=pp * U_.watt, mbr_brf_displacement=z * U_.millimeter, probe_background=bg * U_.radian, constrain_background=False, rms_filter=rms_filter, db_conn=db_conn, **expand_kwargs(update_hanle, envir) ) print(result) if result is not None: print("Found better fit, updating db") else: print("Fit not updated")
def fit_power_dependence(data, envir, curve_loader, db_conn, constrained_background=False, retries=10, rms_filter=True): for s, t, w, pup in zip(data.Timestamp.values, data.temperature_start.values, data.W.values, data.PuP): curve = curve_loader(s) for i in range(0, retries): result = update_hanle( data=curve, temperature=t * U_.kelvin, wavelength=w * U_.nanometer, pump_intensity=pup * U_.watts, constrain_background=False, rms_filter=rms_filter, db_conn=db_conn, **expand_kwargs(update_hanle, envir) ) print(result) if result is not None: print("Found better fit, updating db") else: print("Fit not updated")