class_docstr: Helper for VWAP-like computations.
  
  **Default Inputs:** None
  
  **Default Window Length:** None
class_docstr_tok: ["Helper","for","VWAP-like","computations",".","*","*","Default","Inputs",":","*","*","None","*","*","Default","Window","Length",":","*","*","None"]
code: def compute(self, today, assets, out, base, weight):
      out[:] = nansum(base * weight, axis=0) / nansum(weight, axis=0)
  
imports: from numbers import Number
  from numpy import arange, average, clip, copyto, exp, fmax, full, isnan, log, NINF, sqrt, sum, unique
  from zipline.pipeline.data import EquityPricing
  from zipline.utils.input_validation import expect_types
  from zipline.utils.math_utils import nanargmax, nanmax, nanmean, nanstd, nansum
  from zipline.utils.numpy_utils import float64_dtype, ignore_nanwarnings
  from .factor import CustomFactor
  from ..mixins import SingleInputMixin
label_desc: Use image node_id 1 for calling the WeightedAverageValue obj's underlying member method code with example usage: obj.compute(today, assets, out, base, weight) without return types