code: def from_formula(
      cls,
      formula,
      vc_formulas,
      data,
      vcp_p=1,
      fe_p=2,
      vcp_names=None,
      vc_names=None,
  ):
      fam = families.Poisson()
      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 = PoissonBayesMixedGLM(
          endog=x.endog,
          exog=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 PoissonBayesMixedGLM obj's underlying member method code with example usage: obj.from_formula(cls, formula, vc_formulas, data, vcp_p, fe_p, vcp_names, vc_names) and returns: mod