code: def from_formula(cls, formula, vc_formulas, data, vcp_p=1, fe_p=2):
      fam = families.Binomial()
      x = _BayesMixedGLM.from_formula(
          formula, vc_formulas, data, family=fam, vcp_p=vcp_p, fe_p=fe_p
      )
  
      # Copy over to the intended class structure
      mod = BinomialBayesMixedGLM(
          x.endog,
          x.exog,
          exog_vc=x.exog_vc,
          ident=x.ident,
          vcp_p=x.vcp_p,
          fe_p=x.fe_p,
          fep_names=x.fep_names,
          vcp_names=x.vcp_names,
          vc_names=x.vc_names,
      )
      mod.data = x.data
  
      return mod
  
imports: import numpy
  from scipy.optimize import minimize
  from scipy import sparse
  import statsmodels.base.model
  from statsmodels.iolib import summary2
  from statsmodels.genmod import families
  import pandas
  import warnings
  import patsy
label_desc: Use image node_id 2 for calling the BinomialBayesMixedGLM obj's underlying member method code with example usage: obj.from_formula(cls, formula, vc_formulas, data, vcp_p, fe_p) and returns: mod