def test_no_name(self):
ptree = PropertyTree()
ptree.put_double('initial_voltage', 0)
ptree.put_double('final_voltage', 0)
ptree.put_double('scan_limit_1', 1)
ptree.put_double('scan_limit_2', 0)
ptree.put_double('step_size', 0.1)
ptree.put_double('scan_rate', 1)
ptree.put_int('cycles', 1)
cv = CyclicVoltammetry(ptree)
try:
cv.run(device)
except:
self.fail('calling run without data should not raise')
data = initialize_data()
cv.run(device, data)
voltage = array([0., 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.,
0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1, 0.],
dtype=float)
time = linspace(0, 2, 21)
try:
testing.assert_array_almost_equal(data['voltage'], voltage)
testing.assert_array_almost_equal(data['time'], time)
except AssertionError as e:
print(e)
self.fail()
def test_get_with_default_value(self):
ptree = PropertyTree()
# double
self.assertEqual(
ptree.get_double_with_default_value('missing_double', 3.14), 3.14)
ptree.put_double('present_double', 1.41)
self.assertEqual(
ptree.get_double_with_default_value('present_double', 3.14), 1.41)
# string
self.assertEqual(
ptree.get_string_with_default_value('missing_string', 'missing'),
'missing')
ptree.put_string('present_string', 'present')
self.assertEqual(
ptree.get_string_with_default_value('present_string', 'missing'),
'present')
# int
self.assertEqual(ptree.get_int_with_default_value('missing_int', 255),
255)
ptree.put_int('present_int', 0)
self.assertEqual(ptree.get_int_with_default_value('present_int', 255),
0)
# bool
self.assertEqual(
ptree.get_bool_with_default_value('missing_bool', True), True)
ptree.put_bool('present_bool', False)
self.assertEqual(
ptree.get_bool_with_default_value('present_bool', True), False)
def test_no_name(self):
ptree = PropertyTree()
ptree.put_double('initial_voltage', 0)
ptree.put_double('final_voltage', 0)
ptree.put_double('scan_limit_1', 1)
ptree.put_double('scan_limit_2', 0)
ptree.put_double('step_size', 0.1)
ptree.put_double('scan_rate', 1)
ptree.put_int('cycles', 1)
cv = CyclicVoltammetry(ptree)
try:
cv.run(device)
except:
self.fail('calling run without data should not raise')
data = initialize_data()
cv.run(device, data)
voltage = array([0., 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.,
0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1, 0.],
dtype=float)
time = linspace(0, 2, 21)
try:
testing.assert_array_almost_equal(data['voltage'], voltage)
testing.assert_array_almost_equal(data['time'], time)
except AssertionError as e:
print(e)
self.fail()
def test_verification_with_equivalent_circuit(self):
R = 50e-3 # ohm
R_L = 500 # ohm
C = 3 # farad
U_i = 2.7 # volt
U_f = 1.2 # volt
# setup experiment
ptree = PropertyTree()
ptree.put_double('discharge_power_lower_limit', 1e-2)
ptree.put_double('discharge_power_upper_limit', 1e+2)
ptree.put_int('steps_per_decade', 5)
ptree.put_double('initial_voltage', U_i)
ptree.put_double('final_voltage', U_f)
ptree.put_double('time_step', 15)
ptree.put_int('min_steps_per_discharge', 2000)
ptree.put_int('max_steps_per_discharge', 3000)
ragone = RagoneAnalysis(ptree)
# setup equivalent circuit database
device_database = PropertyTree()
device_database.put_double('series_resistance', R)
device_database.put_double('parallel_resistance', R_L)
device_database.put_double('capacitance', C)
# analytical solutions
E = {}
def E_SeriesRC(P):
U_0 = U_i / 2 + sqrt(U_i**2 / 4 - R * P)
return C / 2 * (-R * P * log(U_0**2 / U_f**2) + U_0**2 - U_f**2)
E['SeriesRC'] = E_SeriesRC
def E_ParallelRC(P):
U_0 = U_i / 2 + sqrt(U_i**2 / 4 - R * P)
tmp = (U_f**2 / R_L + P * (1 + R / R_L)) / \
(U_0**2 / R_L + P * (1 + R / R_L))
return C / 2 * (-R_L * P * log(tmp) - R * R_L /
(R + R_L) * P * log(tmp * U_0**2 / U_f**2))
E['ParallelRC'] = E_ParallelRC
for device_type in ['SeriesRC', 'ParallelRC']:
# create a device
device_database.put_string('type', device_type)
device = EnergyStorageDevice(device_database)
# setup experiment and measure
ragone.reset()
ragone.run(device)
P = ragone._data['power']
E_computed = ragone._data['energy']
# compute the exact solution
E_exact = E[device_type](P)
# ensure the error is small
max_percent_error = 100 * linalg.norm(
(E_computed - E_exact) / E_computed, inf)
self.assertLess(max_percent_error, 0.1)
def test_property_tree(self):
# ptree as container to store int, double, string, and bool
ptree = PropertyTree()
ptree.put_int('dim', 3)
self.assertEqual(ptree.get_int('dim'), 3)
ptree.put_double('path.to.pi', 3.14)
self.assertEqual(ptree.get_double('path.to.pi'), 3.14)
ptree.put_string('good.news', 'it works')
self.assertEqual(ptree.get_string('good.news'), 'it works')
ptree.put_bool('is.that.a.good.idea', False)
self.assertEqual(ptree.get_bool('is.that.a.good.idea'), False)
def test_verification_with_equivalent_circuit(self):
R = 50e-3 # ohm
R_L = 500 # ohm
C = 3 # farad
U_i = 2.7 # volt
U_f = 1.2 # volt
# setup experiment
ptree = PropertyTree()
ptree.put_double('discharge_power_lower_limit', 1e-2)
ptree.put_double('discharge_power_upper_limit', 1e+2)
ptree.put_int('steps_per_decade', 5)
ptree.put_double('initial_voltage', U_i)
ptree.put_double('final_voltage', U_f)
ptree.put_double('time_step', 15)
ptree.put_int('min_steps_per_discharge', 2000)
ptree.put_int('max_steps_per_discharge', 3000)
ragone = RagoneAnalysis(ptree)
# setup equivalent circuit database
device_database = PropertyTree()
device_database.put_double('series_resistance', R)
device_database.put_double('parallel_resistance', R_L)
device_database.put_double('capacitance', C)
# analytical solutions
E = {}
def E_SeriesRC(P):
U_0 = U_i / 2 + sqrt(U_i**2 / 4 - R * P)
return C / 2 * (-R * P * log(U_0**2 / U_f**2) + U_0**2 - U_f**2)
E['SeriesRC'] = E_SeriesRC
def E_ParallelRC(P):
U_0 = U_i / 2 + sqrt(U_i**2 / 4 - R * P)
tmp = (U_f**2 / R_L + P * (1 + R / R_L)) / \
(U_0**2 / R_L + P * (1 + R / R_L))
return C / 2 * (-R_L * P * log(tmp) - R * R_L / (R + R_L) * P * log(tmp * U_0**2 / U_f**2))
E['ParallelRC'] = E_ParallelRC
for device_type in ['SeriesRC', 'ParallelRC']:
# create a device
device_database.put_string('type', device_type)
device = EnergyStorageDevice(device_database)
# setup experiment and measure
ragone.reset()
ragone.run(device)
P = ragone._data['power']
E_computed = ragone._data['energy']
# compute the exact solution
E_exact = E[device_type](P)
# ensure the error is small
max_percent_error = 100 * linalg.norm(
(E_computed - E_exact) / E_computed,
inf)
self.assertLess(max_percent_error, 0.1)
def test_get_children(self):
ptree = PropertyTree()
# put child
child = PropertyTree()
child.put_double('prune', 6.10)
ptree.put_child('a.g', child)
self.assertEqual(ptree.get_double('a.g.prune'), 6.10)
# get child
ptree.put_string('child.name', 'clement')
ptree.put_int('child.age', -2)
child = ptree.get_child('child')
self.assertEqual(child.get_string('name'), 'clement')
self.assertEqual(child.get_int('age'), -2)
def test_retrieve_data(self):
ptree = PropertyTree()
ptree.put_string('type', 'SeriesRC')
ptree.put_double('series_resistance', 50e-3)
ptree.put_double('capacitance', 3)
device = EnergyStorageDevice(ptree)
ptree = PropertyTree()
ptree.put_string('type', 'RagoneAnalysis')
ptree.put_double('discharge_power_lower_limit', 1e-1)
ptree.put_double('discharge_power_upper_limit', 1e+1)
ptree.put_int('steps_per_decade', 1)
ptree.put_double('initial_voltage', 2.1)
ptree.put_double('final_voltage', 0.7)
ptree.put_double('time_step', 1.5)
ptree.put_int('min_steps_per_discharge', 20)
ptree.put_int('max_steps_per_discharge', 30)
ragone = Experiment(ptree)
with File('trash.hdf5', 'w') as fout:
ragone.run(device, fout)
performance_data = ragone._data
fin = File('trash.hdf5', 'r')
retrieved_data = retrieve_performance_data(fin)
fin.close()
# a few digits are lost when power is converted to string
self.assertLess(
linalg.norm(performance_data['power'] - retrieved_data['power'],
inf), 1e-12)
self.assertEqual(
linalg.norm(performance_data['energy'] - retrieved_data['energy'],
inf), 0.0)
# TODO: probably want to move this into its own test
ragoneplot = RagonePlot("ragone.png")
ragoneplot.update(ragone)
# check reset reinitialize the time step and empty the data
ragone.reset()
self.assertEqual(ragone._ptree.get_double('time_step'), 1.5)
self.assertFalse(ragone._data['power'])
self.assertFalse(ragone._data['energy'])
def test_verification_with_equivalent_circuit(self):
R = 50e-3 # ohm
R_L = 500 # ohm
C = 3 # farad
# setup EIS experiment
ptree = PropertyTree()
ptree.put_string('type', 'ElectrochemicalImpedanceSpectroscopy')
ptree.put_double('frequency_upper_limit', 1e+4)
ptree.put_double('frequency_lower_limit', 1e-6)
ptree.put_int('steps_per_decade', 3)
ptree.put_int('steps_per_cycle', 1024)
ptree.put_int('cycles', 2)
ptree.put_int('ignore_cycles', 1)
ptree.put_double('dc_voltage', 0)
ptree.put_string('harmonics', '3')
ptree.put_string('amplitudes', '5e-3')
ptree.put_string('phases', '0')
eis = Experiment(ptree)
# setup equivalent circuit database
device_database = PropertyTree()
device_database.put_double('series_resistance', R)
device_database.put_double('parallel_resistance', R_L)
device_database.put_double('capacitance', C)
# analytical solutions
Z = {}
Z['SeriesRC'] = lambda f: R + 1 / (1j * C * 2 * pi * f)
Z['ParallelRC'] = lambda f: R + R_L / (1 + 1j * R_L * C * 2 * pi * f)
for device_type in ['SeriesRC', 'ParallelRC']:
# create a device
device_database.put_string('type', device_type)
device = EnergyStorageDevice(device_database)
# setup experiment and measure
eis.reset()
eis.run(device)
f = eis._data['frequency']
Z_computed = eis._data['impedance']
# compute the exact solution
Z_exact = Z[device_type](f)
# ensure the error is small
max_phase_error_in_degree = linalg.norm(
angle(Z_computed) * 180 / pi - angle(Z_exact) * 180 / pi,
inf)
max_magniture_error_in_decibel = linalg.norm(
20 * log10(absolute(Z_exact)) - 20 *
log10(absolute(Z_computed)),
inf)
print(device_type)
print(
'-- max_phase_error_in_degree = {0}'.format(max_phase_error_in_degree))
print(
'-- max_magniture_error_in_decibel = {0}'.format(max_magniture_error_in_decibel))
self.assertLessEqual(max_phase_error_in_degree, 1)
self.assertLessEqual(max_magniture_error_in_decibel, 0.2)
def test_verification_with_equivalent_circuit(self):
R = 50e-3 # ohm
R_L = 500 # ohm
C = 3 # farad
# setup EIS experiment
ptree = PropertyTree()
ptree.put_string('type', 'ElectrochemicalImpedanceSpectroscopy')
ptree.put_double('frequency_upper_limit', 1e+4)
ptree.put_double('frequency_lower_limit', 1e-6)
ptree.put_int('steps_per_decade', 3)
ptree.put_int('steps_per_cycle', 1024)
ptree.put_int('cycles', 2)
ptree.put_int('ignore_cycles', 1)
ptree.put_double('dc_voltage', 0)
ptree.put_string('harmonics', '3')
ptree.put_string('amplitudes', '5e-3')
ptree.put_string('phases', '0')
eis = Experiment(ptree)
# setup equivalent circuit database
device_database = PropertyTree()
device_database.put_double('series_resistance', R)
device_database.put_double('parallel_resistance', R_L)
device_database.put_double('capacitance', C)
# analytical solutions
Z = {}
Z['SeriesRC'] = lambda f: R + 1 / (1j * C * 2 * pi * f)
Z['ParallelRC'] = lambda f: R + R_L / (1 + 1j * R_L * C * 2 * pi * f)
for device_type in ['SeriesRC', 'ParallelRC']:
# create a device
device_database.put_string('type', device_type)
device = EnergyStorageDevice(device_database)
# setup experiment and measure
eis.reset()
eis.run(device)
f = eis._data['frequency']
Z_computed = eis._data['impedance']
# compute the exact solution
Z_exact = Z[device_type](f)
# ensure the error is small
max_phase_error_in_degree = linalg.norm(
angle(Z_computed) * 180 / pi - angle(Z_exact) * 180 / pi,
inf)
max_magniture_error_in_decibel = linalg.norm(
20 * log10(absolute(Z_exact)) - 20 *
log10(absolute(Z_computed)),
inf)
print(device_type)
print(
'-- max_phase_error_in_degree = {0}'.format(max_phase_error_in_degree))
print(
'-- max_magniture_error_in_decibel = {0}'.format(max_magniture_error_in_decibel))
self.assertLessEqual(max_phase_error_in_degree, 1)
self.assertLessEqual(max_magniture_error_in_decibel, 0.2)
def test_time_steps(self):
ptree = PropertyTree()
ptree.put_int('stages', 2)
ptree.put_int('cycles', 1)
ptree.put_double('time_step', 1.0)
ptree.put_string('stage_0.mode', 'hold')
ptree.put_string('stage_0.end_criterion', 'time')
ptree.put_double('stage_0.duration', 2.0)
ptree.put_string('stage_1.mode', 'rest')
ptree.put_string('stage_1.end_criterion', 'time')
ptree.put_double('stage_1.duration', 1.0)
ptree.put_double('stage_1.time_step', 0.1)
multi = MultiStage(ptree)
data = initialize_data()
steps = multi.run(device, data)
self.assertEqual(steps, 12)
self.assertEqual(steps, len(data['time']))
self.assertAlmostEqual(data['time'][5], 2.4)
self.assertAlmostEqual(data['voltage'][0], data['voltage'][1])
self.assertAlmostEqual(data['current'][3], 0.0)
def test_setup_frequency_range(self):
ptree = PropertyTree()
ptree.put_string('type', 'ElectrochemicalImpedanceSpectroscopy')
# specify the upper and lower bounds of the range
# the number of points per decades controls the spacing on the log
# scale
ptree.put_double('frequency_upper_limit', 1e+2)
ptree.put_double('frequency_lower_limit', 1e-1)
ptree.put_int('steps_per_decade', 3)
eis = Experiment(ptree)
print(eis._frequencies)
f = eis._frequencies
self.assertEqual(len(f), 10)
self.assertAlmostEqual(f[0], 1e+2)
self.assertAlmostEqual(f[3], 1e+1)
self.assertAlmostEqual(f[9], 1e-1)
# or directly specify the frequencies
frequencies = [3, 2e3, 0.1]
eis = Experiment(ptree, frequencies)
self.assertTrue(all(equal(frequencies, eis._frequencies)))
def test_setup_frequency_range(self):
ptree = PropertyTree()
ptree.put_string('type', 'ElectrochemicalImpedanceSpectroscopy')
# specify the upper and lower bounds of the range
# the number of points per decades controls the spacing on the log
# scale
ptree.put_double('frequency_upper_limit', 1e+2)
ptree.put_double('frequency_lower_limit', 1e-1)
ptree.put_int('steps_per_decade', 3)
eis = Experiment(ptree)
print(eis._frequencies)
f = eis._frequencies
self.assertEqual(len(f), 10)
self.assertAlmostEqual(f[0], 1e+2)
self.assertAlmostEqual(f[3], 1e+1)
self.assertAlmostEqual(f[9], 1e-1)
# or directly specify the frequencies
frequencies = [3, 2e3, 0.1]
eis = Experiment(ptree, frequencies)
self.assertTrue(all(equal(frequencies, eis._frequencies)))
def test_time_steps(self):
ptree = PropertyTree()
ptree.put_int('stages', 2)
ptree.put_int('cycles', 1)
ptree.put_double('time_step', 1.0)
ptree.put_string('stage_0.mode', 'hold')
ptree.put_string('stage_0.end_criterion', 'time')
ptree.put_double('stage_0.duration', 2.0)
ptree.put_string('stage_1.mode', 'rest')
ptree.put_string('stage_1.end_criterion', 'time')
ptree.put_double('stage_1.duration', 1.0)
ptree.put_double('stage_1.time_step', 0.1)
multi = MultiStage(ptree)
data = initialize_data()
steps = multi.run(device, data)
self.assertEqual(steps, 12)
self.assertEqual(steps, len(data['time']))
self.assertAlmostEqual(data['time'][5], 2.4)
self.assertAlmostEqual(data['voltage'][0], data['voltage'][1])
self.assertAlmostEqual(data['current'][3], 0.0)
def test_retrieve_data(self):
ptree = PropertyTree()
ptree.put_string('type', 'SeriesRC')
ptree.put_double('series_resistance', 50e-3)
ptree.put_double('capacitance', 3)
device = EnergyStorageDevice(ptree)
ptree = PropertyTree()
ptree.put_string('type', 'RagoneAnalysis')
ptree.put_double('discharge_power_lower_limit', 1e-1)
ptree.put_double('discharge_power_upper_limit', 1e+1)
ptree.put_int('steps_per_decade', 1)
ptree.put_double('initial_voltage', 2.1)
ptree.put_double('final_voltage', 0.7)
ptree.put_double('time_step', 1.5)
ptree.put_int('min_steps_per_discharge', 20)
ptree.put_int('max_steps_per_discharge', 30)
ragone = Experiment(ptree)
with File('trash.hdf5', 'w') as fout:
ragone.run(device, fout)
performance_data = ragone._data
fin = File('trash.hdf5', 'r')
retrieved_data = retrieve_performance_data(fin)
fin.close()
# a few digits are lost when power is converted to string
self.assertLess(linalg.norm(performance_data['power'] -
retrieved_data['power'], inf), 1e-12)
self.assertEqual(linalg.norm(performance_data['energy'] -
retrieved_data['energy'], inf), 0.0)
# TODO: probably want to move this into its own test
ragoneplot = RagonePlot("ragone.png")
ragoneplot.update(ragone)
# check reset reinitialize the time step and empty the data
ragone.reset()
self.assertEqual(ragone._ptree.get_double('time_step'), 1.5)
self.assertFalse(ragone._data['power'])
self.assertFalse(ragone._data['energy'])
def test_retrieve_data(self):
ptree = PropertyTree()
ptree.put_string('type', 'SeriesRC')
ptree.put_double('series_resistance', 100e-3)
ptree.put_double('capacitance', 2.5)
device = EnergyStorageDevice(ptree)
ptree = PropertyTree()
ptree.put_string('type', 'ElectrochemicalImpedanceSpectroscopy')
ptree.put_double('frequency_upper_limit', 1e+2)
ptree.put_double('frequency_lower_limit', 1e-1)
ptree.put_int('steps_per_decade', 1)
ptree.put_int('steps_per_cycle', 64)
ptree.put_int('cycles', 2)
ptree.put_int('ignore_cycles', 1)
ptree.put_double('dc_voltage', 0)
ptree.put_string('harmonics', '3')
ptree.put_string('amplitudes', '5e-3')
ptree.put_string('phases', '0')
eis = Experiment(ptree)
with File('trash.hdf5', 'w') as fout:
eis.run(device, fout)
spectrum_data = eis._data
with File('trash.hdf5', 'r') as fin:
retrieved_data = retrieve_impedance_spectrum(fin)
print(spectrum_data['impedance'] - retrieved_data['impedance'])
print(retrieved_data)
self.assertEqual(linalg.norm(spectrum_data['frequency'] -
retrieved_data['frequency'], inf), 0.0)
# not sure why we don't get equality for the impedance
self.assertLess(linalg.norm(spectrum_data['impedance'] -
retrieved_data['impedance'], inf), 1e-10)
def setup_expertiment():
eis_database = PropertyTree()
eis_database.put_double('frequency_upper_limit', 1e+4)
eis_database.put_double('frequency_lower_limit', 1e-6)
eis_database.put_int('steps_per_decade', 3)
eis_database.put_int('steps_per_cycle', 1024)
eis_database.put_int('cycles', 2)
eis_database.put_int('ignore_cycles', 1)
eis_database.put_double('dc_voltage', 0)
eis_database.put_string('harmonics', ' 3')
eis_database.put_string('amplitudes', ' 5e-3')
eis_database.put_string('phases', '0')
return eis_database
def test_retrieve_data(self):
ptree = PropertyTree()
ptree.put_string('type', 'SeriesRC')
ptree.put_double('series_resistance', 100e-3)
ptree.put_double('capacitance', 2.5)
device = EnergyStorageDevice(ptree)
ptree = PropertyTree()
ptree.put_string('type', 'ElectrochemicalImpedanceSpectroscopy')
ptree.put_double('frequency_upper_limit', 1e+2)
ptree.put_double('frequency_lower_limit', 1e-1)
ptree.put_int('steps_per_decade', 1)
ptree.put_int('steps_per_cycle', 64)
ptree.put_int('cycles', 2)
ptree.put_int('ignore_cycles', 1)
ptree.put_double('dc_voltage', 0)
ptree.put_string('harmonics', '3')
ptree.put_string('amplitudes', '5e-3')
ptree.put_string('phases', '0')
eis = Experiment(ptree)
with File('trash.hdf5', 'w') as fout:
eis.run(device, fout)
spectrum_data = eis._data
with File('trash.hdf5', 'r') as fin:
retrieved_data = retrieve_impedance_spectrum(fin)
print(spectrum_data['impedance'] - retrieved_data['impedance'])
print(retrieved_data)
self.assertEqual(linalg.norm(spectrum_data['frequency'] -
retrieved_data['frequency'], inf), 0.0)
# not sure why we don't get equality for the impedance
self.assertLess(linalg.norm(spectrum_data['impedance'] -
retrieved_data['impedance'], inf), 1e-10)
def test_fourier_analysis(self):
ptree = PropertyTree()
ptree.put_int('steps_per_cycle', 3)
ptree.put_int('cycles', 1)
ptree.put_int('ignore_cycles', 0)
ptree.put_string('harmonics', '1')
# uninitialized data
data = {}
self.assertRaises(KeyError, fourier_analysis, data, ptree)
# empty data
data = initialize_data()
self.assertRaises(IndexError, fourier_analysis, data, ptree)
# bad data
data['time'] = array([1, 2, 3], dtype=float)
data['current'] = array([4, 5, 6], dtype=float)
data['voltage'] = array([7, 8], dtype=float)
self.assertRaises(AssertionError, fourier_analysis, data, ptree)
# poor data (size not a power of 2)
data['voltage'] = array([7, 8, 9], dtype=float)
with catch_warnings():
simplefilter("error")
self.assertRaises(RuntimeWarning, fourier_analysis, data, ptree)
# data unchanged after analyze
dummy = array([1, 2, 3, 4, 5, 6, 7, 8], dtype=float)
data['time'] = dummy
data['current'] = dummy
data['voltage'] = dummy
# ptree needs to be updated
self.assertRaises(AssertionError, fourier_analysis, data, ptree)
ptree.put_int('steps_per_cycle', 4)
ptree.put_int('cycles', 2)
ptree.put_int('ignore_cycles', 0)
fourier_analysis(data, ptree)
self.assertTrue(all(equal(data['time'], dummy)))
self.assertTrue(all(equal(data['current'], dummy)))
self.assertTrue(all(equal(data['voltage'], dummy)))
def test_fourier_analysis(self):
ptree = PropertyTree()
ptree.put_int('steps_per_cycle', 3)
ptree.put_int('cycles', 1)
ptree.put_int('ignore_cycles', 0)
ptree.put_string('harmonics', '1')
# uninitialized data
data = {}
self.assertRaises(KeyError, fourier_analysis, data, ptree)
# empty data
data = initialize_data()
self.assertRaises(IndexError, fourier_analysis, data, ptree)
# bad data
data['time'] = array([1, 2, 3], dtype=float)
data['current'] = array([4, 5, 6], dtype=float)
data['voltage'] = array([7, 8], dtype=float)
self.assertRaises(AssertionError, fourier_analysis, data, ptree)
# poor data (size not a power of 2)
data['voltage'] = array([7, 8, 9], dtype=float)
with catch_warnings():
simplefilter("error")
self.assertRaises(RuntimeWarning, fourier_analysis, data, ptree)
# data unchanged after analyze
dummy = array([1, 2, 3, 4, 5, 6, 7, 8], dtype=float)
data['time'] = dummy
data['current'] = dummy
data['voltage'] = dummy
# ptree needs to be updated
self.assertRaises(AssertionError, fourier_analysis, data, ptree)
ptree.put_int('steps_per_cycle', 4)
ptree.put_int('cycles', 2)
ptree.put_int('ignore_cycles', 0)
fourier_analysis(data, ptree)
self.assertTrue(all(equal(data['time'], dummy)))
self.assertTrue(all(equal(data['current'], dummy)))
self.assertTrue(all(equal(data['voltage'], dummy)))
