def choose_variables()

in dowhy/causal_refuter.py [0:0]

• 41 lines of code
• 18 McCabe index (conditional complexity)

    def choose_variables(self, required_variables):
        '''
            This method provides a way to choose the confounders whose values we wish to
            modify for finding its effect on the ability of the treatment to affect the outcome.
        '''

        invert = None

        if required_variables is False:

            self.logger.info("All variables required: Running bootstrap adding noise to confounders, instrumental variables and effect modifiers.")
            return None

        elif required_variables is True:

            self.logger.info("All variables required: Running bootstrap adding noise to confounders, instrumental variables and effect modifiers.")
            return self._variables_of_interest

        elif type(required_variables) is int:

            if len(self._variables_of_interest) < required_variables:
                self.logger.error("Too many variables passed.\n The number of  variables is: {}.\n The number of variables passed: {}".format(
                    len(self._variables_of_interest),
                    required_variables )
                )
                raise ValueError("The number of variables in the required_variables is greater than the number of confounders, instrumental variables and effect modifiers")
            else:
                # Shuffle the confounders
                random.shuffle(self._variables_of_interest)
                return self._variables_of_interest[:required_variables]

        elif type(required_variables) is list:

           # Check if all are select or deselect variables
            if all(variable[0] == '-' for variable in required_variables):
                invert = True
                required_variables = [variable[1:] for variable in required_variables]
            elif all(variable[0] != '-' for variable in required_variables):
                invert = False
            else:
                self.logger.error("{} has both select and delect variables".format(required_variables))
                raise ValueError("It appears that there are some select and deselect variables. Note you can either select or delect variables at a time, but not both")

            # Check if all the required_variables belong to confounders, instrumental variables or effect
            if set(required_variables) - set(self._variables_of_interest) != set([]):
                self.logger.error("{} are not confounder, instrumental variable or effect modifier".format( list( set(required_variables) - set(self._variables_of_interest) ) ))
                raise ValueError("At least one of required_variables is not a valid variable name, or it is not a confounder, instrumental variable or effect modifier")

            if invert is False:
                return required_variables
            elif invert is True:
                return list( set(self._variables_of_interest) - set(required_variables) )

        else:
            self.logger.error("Incorrect type: {}. Expected an int,list or bool".format( type(required_variables) ) )
            raise TypeError("Expected int, list or bool. Got an unexpected datatype")