docstr: Dot product of self by a vector *V* in sparse-dense to dense format
  *V* dense vector of shape (self.m,).
docstr_tok: ["Dot","product","of","self","by","a","vector","*","V","*","in","sparse-dense","to","dense","format","*","V","*","dense","vector","of","shape","(","self.m",",",")","."]
code: def dot(self, V):
      """
      Dot product of self by a vector *V* in sparse-dense to dense format
      *V* dense vector of shape (self.m,).
      """
      assert V.shape == (self.m,)
      return np.bincount(
          self.rows, weights=self.vals * V[self.cols], minlength=self.m
      )
  
imports: import numpy
  from matplotlib import _api
  from matplotlib.tri import Triangulation
  from matplotlib.tri._trifinder import TriFinder
  from matplotlib.tri._tritools import TriAnalyzer
label_desc: Use image node_id 2 for calling the _Sparse_Matrix_coo obj's underlying member method code with example usage: obj.dot(V) and returns: np