from pandas import Series, DataFrame from minpower.config import user_config from minpower import powersystems, schedule, solve from minpower.generators import Generator from minpower.optimization import value, OptimizationError import nose from nose.tools import istest, with_setup, raises, set_trace from nose.tools import eq_ as assert_equal import logging logging.basicConfig(level=logging.CRITICAL, format='%(levelname)s: %(message)s') default_config = user_config.copy() def get_duals(): user_config.duals = True def reset_config(): # note - can't set a new user_config, because it would be a local variable # instead, we update it with the defaults # this only works if we aren't adding anything extra to the user_config user_config.update(default_config) try: assert (user_config == default_config) except: print DataFrame( dict(config=Series(user_config), default=Series(default_config)))
from minpower import powersystems, schedule, solve from minpower.generators import Generator from minpower.optimization import value, OptimizationError import nose from nose.tools import istest, with_setup, raises, set_trace from nose.tools import eq_ as assert_equal import logging logging.basicConfig( level=logging.CRITICAL, format='%(levelname)s: %(message)s') default_config = user_config.copy() def get_duals(): user_config.duals = True def reset_config(): # note - can't set a new user_config, because it would be a local variable # instead, we update it with the defaults # this only works if we aren't adding anything extra to the user_config user_config.update(default_config) try: assert(user_config == default_config) except: print DataFrame(dict(