def test_two_ramps_smoke_test(self):
mdl = goodVehicle()
V = np.hstack((np.r_[0:100:2], np.r_[100:0:-2]))
mdl['cycle_run'] = {'v_target': V}
experiment = Experiment(mdl)
mdl = experiment.run()
def test_two_ramps_smoke_test(self):
mdl = goodVehicle()
V = np.hstack((np.r_[0:100:2], np.r_[100:0:-2]))
mdl['cycle_run'] = {'v_target': V}
experiment = Experiment(mdl)
mdl = experiment.run()
def test_badCycle(self):
mdl = goodVehicle()
mdl['params'] = params = {}
mdl['cycle_run'] = 1
with assertRaisesRegex(self, PandasError, 'DataFrame constructor not properly called'):
experiment = Experiment(mdl)
mdl = experiment.run()
def test_badCycle(self):
mdl = goodVehicle()
mdl['params'] = params = {}
mdl['cycle_run'] = 1
with assertRaisesRegex(self, PandasError,
'DataFrame constructor not properly called'):
experiment = Experiment(mdl)
mdl = experiment.run()
def test_two_ramps_with_slope(self):
V = np.hstack((np.r_[0:100:2], np.r_[100:0:-2]))
SLOPE = np.random.rand(V.shape[0])
v_columns = ('v_class', 'v_target')
for col in v_columns:
mdl = goodVehicle()
mdl['cycle_run'] = pd.DataFrame({
col: V,
'slope': SLOPE,
})
proc = Experiment(mdl)
mdl = proc.run()
#print(pd.DataFrame(mdl['cycle_run']))
cycle_run = mdl['cycle_run']
self.assertIn('slope', cycle_run)
self.assertIn('gears', cycle_run)
for vcol in v_columns:
npt.assert_array_equal(V, cycle_run[vcol], "V_Column(%s) not overriden!"%vcol)
def test_two_ramps_with_slope(self):
V = np.hstack((np.r_[0:100:2], np.r_[100:0:-2]))
SLOPE = np.random.rand(V.shape[0])
v_columns = ('v_class', 'v_target')
for col in v_columns:
mdl = goodVehicle()
mdl['cycle_run'] = pd.DataFrame({
col: V,
'slope': SLOPE,
})
proc = Experiment(mdl)
mdl = proc.run()
#print(pd.DataFrame(mdl['cycle_run']))
cycle_run = mdl['cycle_run']
self.assertIn('slope', cycle_run)
self.assertIn('gears', cycle_run)
for vcol in v_columns:
npt.assert_array_equal(V, cycle_run[vcol],
"V_Column(%s) not overriden!" % vcol)
