status: passed
duration: 898.984s
Captured stdout call
{'F_Hz': array([0.0000000e+00, 7.8125000e-03, 1.5625000e-02, ..., 4.9984375e+01,
       4.9992188e+01, 5.0000000e+01]), 'data': array([-4.8860516e-03+0.0000000e+00j, -4.5855157e-03+8.9761830e-05j,
       -4.3419674e-03+2.4111182e-04j, ...,  1.5403209e-09+2.9354810e-08j,
        1.2409613e-08+4.0623608e-08j,  2.2163795e-09+3.6025902e-08j]), 'F_nyquist_Hz': None, 'delay_s': 0, 'hints': [{'fitter_update_validate': <function sign_validate_and_plot_hint.<locals>.sign_validate_plot at 0x7eff83ff5ee0>, 'fitter_check_validate': <function sign_validate_and_plot_hint.<locals>.sign_validate_plot at 0x7eff83ff5ee0>, 'rational_fitter_validate': <function rational_fitter_validate at 0x7eff849a3240>}]}
TEE_LOGFILE None
A []
B []
------------:SNR Fix Test:
------------:rational fitting:
4P   0.05    chebychev rational fit
RELDEG:  0 0 0
3P   0.33    Initial Order: (Z=20, P=20, Z-P=0)
3P   0.40    Fastdrop Order: (Z=18, P=18, Z-P=0)
4P   0.42    mag fitting and phase patching
--------------:rational fitting:sample variance (from magnitude):
3A   7.94      Weight Scaling determined:  0.9295889280291497
3A   7.94      Weight Scaling Used  0.9641519216540253
------------:Q-ranked order reduction:
4P  36.79    order reduced annealing
5P  46.77  zero flipping, maxzp 40, residuals=7.98e+01, 2.56e+02, reldeg=-22
------------:selective order reduction:
5P 114.27    order reduced to 39, residuals=6.25e+01, reldeg=-21
5P 163.01    order reduced to 39, residuals=5.97e+01, reldeg=-22
5P 171.70    order reduced to 37, residuals=5.94e+01, reldeg=-22
5P 203.35    order reduced to 37, residuals=5.90e+01, reldeg=-24
5P 220.82    order reduced to 36, residuals=5.91e+01, reldeg=-23
5P 252.71    order reduced to 36, residuals=5.85e+01, reldeg=-25
5P 287.30    order reduced to 34, residuals=5.83e+01, reldeg=-25
5P 319.62    order reduced to 34, residuals=5.10e+01, reldeg=-27
5P 369.46    order reduced to 34, residuals=4.99e+01, reldeg=-28
5P 419.82    order reduced to 32, residuals=4.94e+01, reldeg=-27
5P 463.91    order reduced to 32, residuals=4.94e+01, reldeg=-28
5P 509.02    order reduced to 31, residuals=4.92e+01, reldeg=-27
5P 553.14    order reduced to 31, residuals=4.69e+01, reldeg=-28
5P 581.54    order reduced to 30, residuals=4.66e+01, reldeg=-27
5P 610.67    order reduced to 30, residuals=4.64e+01, reldeg=-29
5P 636.87    order reduced to 29, residuals=4.63e+01, reldeg=-28
2A 673.75  Baseline fit residuals: 6.43e+02, at order 29
------------:successive order reduction:
5P 701.77    order reduced to 28, residuals=2.75e+02
5P 722.09    order reduced to 27, residuals=6.02e+01
5P 746.68    order reduced to 26, residuals=6.37e+01
5P 767.34    order reduced to 25, residuals=6.85e+01
5P 787.05    order reduced to 24, residuals=6.84e+01
5P 807.18    order reduced to 23, residuals=6.85e+01
5P 824.49    order reduced to 21, residuals=6.90e+01
5P 836.65    order reduced to 20, residuals=6.87e+01
5P 849.65    order reduced to 18, residuals=7.54e+01
5P 858.41    order reduced to 16, residuals=4.57e+01
5P 865.88    order reduced to 15, residuals=4.14e+01
5P 869.51    order reduced to 14, residuals=4.29e+01
5P 873.27    order reduced to 13, residuals=4.48e+01
5P 878.62    order reduced to 12, residuals=4.37e+01
5P 881.02    order reduced to 11, residuals=4.53e+01
5P 884.27    order reduced to 10, residuals=1.16e+01
5P 887.81    order reduced to 9, residuals=1.12e+01
5P 888.54    order reduced to 8, residuals=1.16e+01
5P 890.80    order reduced to 7, residuals=1.16e+01
5P 891.25    order reduced to 6, residuals=1.17e+01
5P 891.54    order reduced to 4, residuals=2.46e+01
5P 891.74    order reduced to 2, residuals=5.92e+01
BASELINE:  29
------------:investigations:
2I 891.96    max(z, p)       ChiSq.
                   order    avg. res.    med. res.    max. res.
             -----------  -----------  -----------  -----------
                       2      59.2377      75.0691     1673.08
                       4      24.6445      22.8512      405.758
                       6      11.7043      11.6484      141.975
                       7      11.5822      11.6931      148.44
                       9      11.2175      12.1042      159.094
Captured stderr call
3W   0.00  Estimating SNR from sample variance with nearby points (SNR_est_width=10 > 0).
           This technique works semi-OK, but could probably be much better..
           use the resulting fit to estimate the sample variance and generate
           improved SNR estimates, iterate.
3W   0.02  6015 SNR<1 element(s) dropped (of 6401).
           Too many low SNR elements confuses the rational nonparametric fitter.
3W   0.04    The number of effective data points N=(ΣW^2)^2/(ΣW^4)=3.79e-01*len(W)
             [where W=SNR] is below the configured 'SNR_regularize_scale'=10,
             given the maximum SNR=49.74241939769682. Now Finding an SNR ceiling that balances
             the ratio with max SNR.
3W   0.04    Using SNR<20.64128132953338 ceiling.
3W   0.38    Fitter_checkpoint improvement succeed, None
3W  34.02  Fitter_checkpoint improvement succeed, None
3W  36.78    Fitter_checkpoint improvement succeed, None
3W 114.26    Fitter_checkpoint improvement succeed, None
3W 162.99    Fitter_checkpoint improvement succeed, None
3W 171.69    Fitter_checkpoint improvement succeed, None
3W 203.34    Fitter_checkpoint improvement succeed, None
3W 220.81    Fitter_checkpoint improvement succeed, None
3W 252.70    Fitter_checkpoint improvement succeed, None
3W 287.29    Fitter_checkpoint improvement succeed, None
3W 319.61    Fitter_checkpoint improvement succeed, None
3W 369.45    Fitter_checkpoint improvement succeed, None
3W 419.81    Fitter_checkpoint improvement succeed, None
3W 463.90    Fitter_checkpoint improvement succeed, None
3W 509.01    Fitter_checkpoint improvement succeed, None
3W 553.13    Fitter_checkpoint improvement succeed, None
3W 581.53    Fitter_checkpoint improvement succeed, None
3W 610.66    Fitter_checkpoint improvement succeed, None
3W 636.86    Fitter_checkpoint improvement succeed, None