How to use the numexpr.necompiler.getType function in numexpr

names, normal variables names, column paths and variable paths
        (all are tuples).
        """

        # Variable names for column and normal variables.
        colnames, varnames = [], []
        # Column paths and types for each of the previous variable.
        colpaths, vartypes = [], []
        for (var, val) in condvars.items():
            if hasattr(val, 'pathname'):  # column
                colnames.append(var)
                colpaths.append(val.pathname)
            else:  # array
                try:
                    varnames.append(var)
                    vartypes.append(numexpr_getType(val))  # expensive
                except ValueError:
                    # This is more clear than the error given by Numexpr.
                    raise TypeError( "variable ``%s`` has data type ``%s``, "
                                     "not allowed in conditions"
                                     % (var, val.dtype.name) )
        colnames, varnames = tuple(colnames), tuple(varnames)
        colpaths, vartypes = tuple(colpaths), tuple(vartypes)
        condkey = (condition, colnames, varnames, colpaths, vartypes)
        return condkey

values = self.values
        types_ = []
        for name in self.names:
            value = vars_[name]
            if hasattr(value, 'atom'):
                types_.append(value.atom)
            elif hasattr(value, 'dtype'):
                types_.append(value)
            else:
                # try to convert into a NumPy array
                value = np.array(value)
                types_.append(value)
            values.append(value)

        # Create a signature for the expression
        signature = [(name, getType(type_))
                     for (name, type_) in zip(self.names, types_)]

        # Compile the expression
        self._compiled_expr = NumExpr(expr, signature, **kwargs)

        # Guess the shape for the outcome and the maindim of inputs
        self.shape, self.maindim = self._guess_shape()