class_docstr: Term binding to a numexpr expression.
  
  Parameters
  ----------
  expr : string
      A string suitable for passing to numexpr.  All variables in 'expr'
      should be of the form "x_i", where i is the index of the corresponding
      factor input in 'binds'.
  binds : tuple
      A tuple of factors to use as inputs.
  dtype : np.dtype
      The dtype for the expression.
class_docstr_tok: ["Term","binding","to","a","numexpr","expression",".","Parameters","--","--","--","--","--","expr",":","string","A","string","suitable","for","passing","to","numexpr",".","All","variables","in","'expr'","should","be","of","the","form","``","x_i","''",",","where","i","is","the","index","of","the","corresponding","factor","input","in","'binds","'",".","binds",":","tuple","A","tuple","of","factors","to","use","as","inputs",".","dtype",":","np.dtype","The","dtype","for","the","expression","."]
docstr: Short repr to use when rendering Pipeline graphs.
docstr_tok: ["Short","repr","to","use","when","rendering","Pipeline","graphs","."]
code: def graph_repr(self):
      """Short repr to use when rendering Pipeline graphs."""
  
      # Replace any floating point numbers in the expression
      # with their scientific notation
      final = re.sub(
          r"[-+]?\d*\.\d+",
          lambda x: format(float(x.group(0)), ".2E"),
          self._expr,
      )
      # Graphviz interprets `\l` as "divide label into lines, left-justified"
      return "Expression:\\l  {}\\l".format(
          final,
      )
  
imports: import re
  from itertools import chain
  from numbers import Number
  import numexpr
  from numexpr.necompiler import getExprNames
  from numpy import full, inf
  from zipline.pipeline.term import Term, ComputableTerm
  from zipline.utils.numpy_utils import bool_dtype
label_desc: Use image node_id 11 for calling the NumericalExpression obj's underlying member method code with example usage: obj.graph_repr() and returns: str