<jupyter_start><jupyter_text>assumptios``cvridge`` has default kwarg `ndelays=10```cvridge`` can take list of ``feature_space`` instances, or list of arrays, or function and argument for loading```[(lambda x: load_my_data(x), '/path/to/one/feature_array), (lambda x: load_my_data(x), '/path/to/two/feature_array), (lambda x: load_my_data(x), '/path/to/tre/feature_array),```**CANNOT** have different temporal priors for different features**CAN** have complex mixture of gaussian temporal priors<jupyter_code>if 0:
    tiko.cvridge([A,B,C], [Aval, Bval, Cval], 
                 feature_prior=tiko.priors.SphericalPrior(),   # ridge
                 temporal_prior=tiko.priors.SphericalPrior())  # ridge
if 0:
    tiko.cvridge([A,B,C], [Aval, Bval, Cval], 
                 spatial_prior=tiko.priors.SphericalPrior(), # ridge
                 temporal_prior=tiko.priors.SmoothPrior(),   # temporal prior only    
                 )
if 0:
    temporal_prior = tiko.priors.SmoothPrior(order=2).set_prior(tiko.priors.SphericalPrior())
    tiko.cvridge([A,B,C], [Aval, Bval, Cval], 
                 feature_prior=tiko.priors.SphericalPrior(), # ridge
                 temporal_prior=temporal_prior,               # smooth temporal prior with wishart
if 0:
    tiko.cvridge([A,B,C], [Aval, Bval, Cval], 
                 feature_prior=[tiko.priors.SphericalPrior(),
                                tiko.priors.SphericalPrior(),
                                tiko.priors.SphericalPrior()], # banded ridge
                 temporal_prior=tiko.priors.SphericalPrior())   # FIR
if 0:
    spherical_prior = tiko.priors.SphericalPrior()
    tiko.cvridge([A,B,C], [Aval, Bval, Cval], 
                 feature_prior=[tiko.priors.SphericalPrior(),
                                tiko.priors.SphericalPrior(),
                                tiko.priors.SphericalPrior(),], # banded ridge
                 temporal_prior=tiko.priors.SmoothPrior())      # smooth FIR prior
if 0:
    tiko.cvridge([A,B,C], [Aval, Bval, Cval], 
                 feature_prior=[tiko.priors.SphericalPrior(),
                                tiko.priors.SphericalPrior(),
                                tiko.priors.SphericalPrior(),], # banded ridge
                 temporal_prior=tiko.priors.SmoothPrior().set_prior(tiko.priors.SphericalPrior)) # Wishart
if 0:
    tiko.cvridge([A,B,C], [Aval, Bval, Cval], 
                 feature_prior=tiko.priors.Prior(array),       # custom prior
                 temporal_prior=tiko.priors.SphericalPrior())  # ridge
if 0:
    tiko.cvridge([A,B,C], [Aval, Bval, Cval], 
                 feature_prior=tiko.priors.PriorFromPenalty(array),       # custom penalty
                 temporal_prior=tiko.priors.SphericalPrior())             # ridge
if 0:
    # custom penalty, rank-deficient
    custom_prior = tiko.priors.PriorFromPenalty(array).set_prior(tiko.priors.SphericalPrior())
    tiko.cvridge([A,B,C], [Aval, Bval, Cval], 
                 feature_prior=custom_prior,                              # custom penalty, rank-deficient!!!
                 temporal_prior=tiko.priors.SphericalPrior())             # ridge
if 0:
    # custom penalty, rank-deficient
    custom_prior = tiko.priors.PriorFromPenalty(array).set_prior(tiko.priors.SphericalPrior())
    temporal_prior = tiko.priors.SmoothPrior(order=2).set_prior(tiko.priors.SphericalPrior())
    tiko.cvridge([A,B,C], [Aval, Bval, Cval], 
                 feature_prior=custom_prior,           # custom penalty, rank-deficient, so wishart!
                 temporal_prior=temporal_prior)        # smooth temporal prior with wishart
if 0:
    # custom penalty, rank-deficient
    custom_prior_A = tiko.priors.Prior(arrayA),       # custom prior
    custom_prior_B = tiko.priors.Prior(arrayB),       # custom prior
    custom_prior_C = tiko.priors.Prior(arrayC),       # custom prior
    temporal_prior = tiko.priors.SmoothPrior(order=2).set_prior(tiko.priors.SphericalPrior())
    tiko.cvridge([A,B,C], [Aval, Bval, Cval], 
                 feature_prior=[custom_prior_A,           # custom prior
                                custom_prior_B,           # custom prior
                                custom_prior_C],          # custom prior
                 temporal_prior=temporal_prior)           # smooth temporal prior with wishart<jupyter_output><empty_output>
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