def test_pickle_support(self):
import pickle
src = PropertyTree()
src.put_double('pi', 3.14)
src.put_string('greet', 'bonjour')
p = pickle.dumps(src)
dst = pickle.loads(p)
self.assertEqual(dst.get_double('pi'), 3.14)
self.assertEqual(dst.get_string('greet'), 'bonjour')
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_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_consistency_pycap_simulation(self):
#
# weak run test; simply ensures that Dualfoil object
# can be run with pycap.Charge
#
df1 = Dualfoil(path=path) # will use pycap
df2 = Dualfoil(path=path) # manual runs
im = df_manip.InputManager(path=path)
# testing a charge-to-hold-const-voltage
# manual
# use InputManager to set the input file
c = -12.0 # constant current
im.add_new_leg(c, 5.0, 1)
df1.run()
df1.outbot.update_output()
v = 4.54 # constant voltage
im.add_new_leg(v, 5.0, 0)
df1.run()
df1.outbot.update_output()
# pycap simulation
# build a ptree input
ptree = PropertyTree()
ptree.put_double('time_step', 300.0) # 5 minutes
ptree.put_string('charge_mode', 'constant_current')
ptree.put_double('charge_current', 12.0)
ptree.put_string('charge_stop_at_1', 'voltage_greater_than')
ptree.put_double('charge_voltage_limit', 4.54)
ptree.put_bool('charge_voltage_finish', True)
# hold end voltage after either 5 minutes have passed
# OR current falls under 1 ampere
ptree.put_double('charge_voltage_finish_max_time', 300.0)
ptree.put_double('charge_voltage_finish_current_limit', 1.0)
const_current_const_voltage = Charge(ptree)
const_current_const_voltage.run(df2)
# check the output lists of both devices
o1 = df1.outbot.output
o2 = df2.outbot.output
self.assertEqual(len(o1['time']), len(o2['time']))
for i in range(len(o1['time'])):
self.assertAlmostEqual(o1['time'][i], o2['time'][i])
# BELOW: relaxed delta for voltage
# REASON: dualfoil cuts off its voltages at 5
# decimal places, meaning that this end-digit
# is subject to roundoff errors
error = 1e-5
self.assertAlmostEqual(o1['voltage'][i],
o2['voltage'][i],
delta=error)
self.assertAlmostEqual(o1['current'][i], o2['current'][i])
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_force_discharge(self):
ptree = PropertyTree()
ptree.put_string('mode', 'constant_voltage')
ptree.put_double('voltage', 0.0)
ptree.put_string('end_criterion', 'current_less_than')
ptree.put_double('current_limit', 1e-5)
ptree.put_double('time_step', 1.0)
stage = Stage(ptree)
data = initialize_data()
steps = stage.run(device, data)
self.assertGreaterEqual(steps, 1)
self.assertEqual(steps, len(data['time']))
self.assertAlmostEqual(data['voltage'][-1], 0.0)
self.assertLessEqual(data['current'][-1], 1e-5)
def test_constant_current_charge_for_given_time(self):
ptree = PropertyTree()
ptree.put_string('mode', 'constant_current')
ptree.put_double('current', 5e-3)
ptree.put_string('end_criterion', 'time')
ptree.put_double('duration', 15.0)
ptree.put_double('time_step', 0.1)
stage = Stage(ptree)
data = initialize_data()
steps = stage.run(device, data)
self.assertEqual(steps, 150)
self.assertEqual(steps, len(data['time']))
self.assertAlmostEqual(data['time'][-1], 15.0)
self.assertAlmostEqual(data['current'][-1], 5e-3)
def test_charge_constant_current(self):
ptree = PropertyTree()
ptree.put_string('charge_mode', 'constant_current')
ptree.put_double('charge_current', 10e-3)
ptree.put_string('charge_stop_at_1', 'voltage_greater_than')
ptree.put_double('charge_voltage_limit', 1.4)
ptree.put_double('time_step', 0.2)
charge = Charge(ptree)
data = initialize_data()
charge.run(device, data)
self.assertAlmostEqual(data['current'][0], 10e-3)
self.assertAlmostEqual(data['current'][-1], 10e-3)
self.assertGreaterEqual(data['voltage'][-1], 1.4)
self.assertAlmostEqual(data['time'][1] - data['time'][0], 0.2)
def test_charge_constant_voltage(self):
ptree = PropertyTree()
ptree.put_string('charge_mode', 'constant_voltage')
ptree.put_double('charge_voltage', 1.4)
ptree.put_string('charge_stop_at_1', 'current_less_than')
ptree.put_double('charge_current_limit', 1e-6)
ptree.put_string('charge_stop_at_2', 'time')
ptree.put_double('charge_max_duration', 60)
ptree.put_double('time_step', 0.2)
charge = Charge(ptree)
data = initialize_data()
charge.run(device, data)
self.assertTrue(data['time'][-1] >= 60
or abs(data['current'][-1]) <= 1e-6)
self.assertAlmostEqual(data['voltage'][-1], 1.4)
def test_get_array(self):
ptree = PropertyTree()
# array of double
ptree.put_string('array_double', '3.14,1.41')
array_double = ptree.get_array_double('array_double')
self.assertEqual(array_double, [3.14, 1.41])
# ... string
ptree.put_string('array_int', '1,2,3')
array_int = ptree.get_array_int('array_int')
self.assertEqual(array_int, [1, 2, 3])
# ... int
ptree.put_string('array_string', 'uno,dos,tres,cuatro')
array_string = ptree.get_array_string('array_string')
self.assertEqual(array_string, ['uno', 'dos', 'tres', 'cuatro'])
# ... bool
ptree.put_string('array_bool', 'true,FALSE,False')
array_bool = ptree.get_array_bool('array_bool')
self.assertEqual(array_bool, [True, False, False])
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_current_limit(self):
# lower
ptree = PropertyTree()
ptree.put_string('end_criterion', 'current_less_than')
ptree.put_double('current_limit', -5e-3)
self.assertRaises(RuntimeError, EndCriterion.factory, ptree)
ptree.put_double('current_limit', 0.0)
self.assertRaises(RuntimeError, EndCriterion.factory, ptree)
ptree.put_double('current_limit', 5e-3)
current_limit = EndCriterion.factory(ptree)
device.evolve_one_time_step_constant_current(5.0, 0.0)
self.assertTrue(current_limit.check(NaN, device))
device.evolve_one_time_step_constant_current(5.0, 0.002)
self.assertTrue(current_limit.check(NaN, device))
device.evolve_one_time_step_constant_current(5.0, -0.001)
self.assertTrue(current_limit.check(180.0, device))
device.evolve_one_time_step_constant_current(5.0, 0.005)
self.assertTrue(current_limit.check(180.0, device))
device.evolve_one_time_step_constant_current(5.0, 0.007)
self.assertFalse(current_limit.check(180.0, device))
device.evolve_one_time_step_constant_current(5.0, -15e3)
self.assertFalse(current_limit.check(180.0, device))
# upper
ptree.put_string('end_criterion', 'current_greater_than')
ptree.put_double('current_limit', -5e-3)
self.assertRaises(RuntimeError, EndCriterion.factory, ptree)
ptree.put_double('current_limit', 0.0)
self.assertRaises(RuntimeError, EndCriterion.factory, ptree)
ptree.put_double('current_limit', 5e-3)
current_limit = EndCriterion.factory(ptree)
device.evolve_one_time_step_constant_current(5.0, -1e-3)
self.assertFalse(current_limit.check(NaN, device))
device.evolve_one_time_step_constant_current(5.0, 0.002)
self.assertFalse(current_limit.check(NaN, device))
device.evolve_one_time_step_constant_current(5.0, 0.005)
self.assertTrue(current_limit.check(NaN, device))
device.evolve_one_time_step_constant_current(5.0, -0.2)
self.assertTrue(current_limit.check(NaN, device))
device.evolve_one_time_step_constant_current(5.0, 3.0)
self.assertTrue(current_limit.check(NaN, device))
def test_compound_criterion(self):
ptree = PropertyTree()
ptree.put_string('end_criterion', 'compound')
ptree.put_string('criterion_0.end_criterion', 'time')
ptree.put_double('criterion_0.duration', 5.0)
ptree.put_string('criterion_1.end_criterion', 'voltage_greater_than')
ptree.put_double('criterion_1.voltage_limit', 2.0)
# no default value for now
self.assertRaises(KeyError, EndCriterion.factory, ptree)
ptree.put_string('logical_operator', 'bad_operator')
self.assertRaises(RuntimeError, EndCriterion.factory, ptree)
ptree.put_string('logical_operator', 'or')
compound_criterion = EndCriterion.factory(ptree)
compound_criterion.reset(0.0, device)
device.evolve_one_time_step_constant_voltage(0.1, 1.0)
self.assertFalse(compound_criterion.check(3.0, device))
self.assertTrue(compound_criterion.check(5.0, device))
device.evolve_one_time_step_constant_voltage(0.1, 2.0)
self.assertTrue(compound_criterion.check(3.0, device))
self.assertTrue(compound_criterion.check(5.0, device))
ptree.put_string('logical_operator', 'and')
compound_criterion = EndCriterion.factory(ptree)
compound_criterion.reset(0.0, device)
device.evolve_one_time_step_constant_voltage(0.1, 1.0)
self.assertFalse(compound_criterion.check(3.0, device))
self.assertFalse(compound_criterion.check(5.0, device))
device.evolve_one_time_step_constant_voltage(0.1, 2.0)
self.assertFalse(compound_criterion.check(3.0, device))
self.assertTrue(compound_criterion.check(5.0, device))
ptree.put_string('logical_operator', 'xor')
compound_criterion = EndCriterion.factory(ptree)
compound_criterion.reset(0.0, device)
device.evolve_one_time_step_constant_voltage(0.1, 1.0)
self.assertFalse(compound_criterion.check(3.0, device))
self.assertTrue(compound_criterion.check(5.0, device))
device.evolve_one_time_step_constant_voltage(0.1, 2.0)
self.assertTrue(compound_criterion.check(3.0, device))
self.assertFalse(compound_criterion.check(5.0, device))
def test_builders(self):
for AbstractClass in [Observer, Observable]:
# AbstractClass takes a PropertyTree as argument.
self.assertRaises(TypeError, AbstractClass)
# The PropertyTree must specify what concrete class derived from
# AbstractClass to instantiate.
ptree = PropertyTree()
self.assertRaises(KeyError, AbstractClass, ptree)
# The derived concrete class must be registerd in the dictionary
# that holds the builders.
ptree.put_string('type', 'Invalid')
self.assertRaises(KeyError, AbstractClass, ptree)
# Now declare a concrete class.
class ConcreteClass(AbstractClass):
def __new__(cls, *args, **kwargs):
return object.__new__(ConcreteClass)
def __init__(*args, **kwargs):
pass
# Here is how to register a derived concrete class to the base
# abstract class.
AbstractClass._builders['ConcreteClass'] = ConcreteClass
# Now instantiation works.
ptree.put_string('type', 'ConcreteClass')
AbstractClass(ptree)
# Also can build directly from derived class.
ConcreteClass()
# Remove from the dictionary.
del AbstractClass._builders['ConcreteClass']
self.assertRaises(KeyError, AbstractClass, ptree)
def test_voltage_limit(self):
ptree = PropertyTree()
ptree.put_double('voltage_limit', 1.7)
# upper limit
ptree.put_string('end_criterion', 'voltage_greater_than')
voltage_limit = EndCriterion.factory(ptree)
voltage_limit.reset(5.0, device)
device.evolve_one_time_step_constant_voltage(0.2, 1.3)
self.assertFalse(voltage_limit.check(0.0, device))
self.assertFalse(voltage_limit.check(60.0, device))
device.evolve_one_time_step_constant_voltage(0.2, 1.7)
self.assertTrue(voltage_limit.check(45.0, device))
device.evolve_one_time_step_constant_voltage(0.2, 2.1)
self.assertTrue(voltage_limit.check(45.0, device))
# lower limit
ptree.put_string('end_criterion', 'voltage_less_than')
voltage_limit = EndCriterion.factory(ptree)
voltage_limit.reset(0.0, device)
device.evolve_one_time_step_constant_voltage(0.2, 1.3)
self.assertTrue(voltage_limit.check(0.0, device))
device.evolve_one_time_step_constant_voltage(0.2, 1.7)
self.assertTrue(voltage_limit.check(45.0, device))
device.evolve_one_time_step_constant_voltage(0.2, 2.1)
self.assertFalse(voltage_limit.check(45.0, device))
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_accuracy_pycap_simulation(self):
#
# tests the accuracy of a pycap simulation against a
# straight run dualfoil sim with different timesteps
#
df1 = Dualfoil(path=path) # manual runs
df2 = Dualfoil(path=path) # pycap simulation
im = df_manip.InputManager(path=path)
# testing a charge-to-hold-const-voltage
# manual
# use InputManager to set the input file
c = -10.0 # constant charge current
# charge for 5 minutes straight
im.add_new_leg(c, 5, 1)
df1.run()
df1.outbot.update_output()
v = 4.539 # expected voltage after 5 minutes
# hold constant voltage for 3 minutes straight
im.add_new_leg(v, 3.0, 0)
df1.run()
df1.outbot.update_output()
# pycap simulation
# build a ptree input
ptree = PropertyTree()
ptree.put_double('time_step', 30.0) # 30 second time step
ptree.put_string('charge_mode', 'constant_current')
ptree.put_double('charge_current', 10.0)
ptree.put_string('charge_stop_at_1', 'voltage_greater_than')
ptree.put_double('charge_voltage_limit', v)
ptree.put_bool('charge_voltage_finish', True)
# hold end voltage after either 3 minutes have passed
# OR current falls under 1 ampere
ptree.put_double('charge_voltage_finish_max_time', 180.0)
ptree.put_double('charge_voltage_finish_current_limit', 1.0)
const_current_const_voltage = Charge(ptree)
const_current_const_voltage.run(df2)
o1 = df1.outbot.output # contains sim1 output
o2 = df2.outbot.output # contains sim2 output
# affirm we make it this far and have usable data
self.assertTrue(len(o1['time']) > 0)
self.assertTrue(len(o2['time']) > 0)
# lengths of data should be different
self.assertFalse(len(o1['time']) == len(o2['time']))
# TEST LOGIC:
# -Merge the two outputs into one, sorted by
# increasing time stamps.
# -Compare the consistency of the two simulations
# by checking for smooth changes within the curves
# of the combined output lists
o1['time'].extend(o2['time'])
time = ar(o1['time']) # nparray
o1['voltage'].extend(o2['voltage'])
voltage = ar(o1['voltage']) # nparray
o1['current'].extend(o2['current'])
current = ar(o1['current']) # np array
# create a dictionary with the combined output lists
output = {'time': time, 'voltage': voltage, 'current': current}
# sort based on time, keeping the three types aligned
key = argsort(output['time'])
# for using the key to sort the list
tmp = {'time': [], 'voltage': [], 'current': []}
for i in key:
tmp['time'].append(output['time'][i])
tmp['voltage'].append(output['voltage'][i])
tmp['current'].append(output['current'][i])
# reassign ordered set to `output` as nparrays
output['time'] = ar(tmp['time'])
output['voltage'] = ar(tmp['voltage'])
output['current'] = ar(tmp['current'])
# BELOW: first 20 seconds are identical time stamps;
# skip these to avoid errors from incorrect sorting
# REASON FOR ERROR: Dualfoil only prints time data as
# precice as minutes to three decimal places. So when
# the following is generated....
# Manual Run | Pycap Simulation
# (min) (V) (amp) | (min) (V) (amp)
# .001 4.52345 10.0 | .001 4.52345 10.0
# .001 4.52349 10.0 | .001 4.52349 10.0
# ... ...
# ...python's `sorted()` function has no way of
# distinguishing entries; it instead returns this:
# [
# (.001, 4.52345, 10.0),
# (.001, 4.52349, 10.0), <- these two should
# (.001, 4.52345, 10.0), <- be switched
# (.001, 4.52349, 10.0)
# ]
# SOLUTION: consistency test affirms that the exact same
# time step will produce same current and voltage, so
# skip ahead to first instance where time stamps will
# be out of alignment
i = 0
while output['time'][i] <= 0.4: # 24 seconds
i = i + 1
index_limit = len(output['time']) - 1
# go through and affirm smoothness of curve
while i < index_limit:
# Check if time values are the same to 3 decimal places.
# If so, current and voltage are not guarunteed
# to also be exactly the same, but should be close
if output['time'][i] == output['time'][i - 1]:
# affirm that current is virtually the same
self.assertAlmostEqual(output['current'][i],
output['current'][i - 1])
# BELOW: delta is eased slightly
# REASON: `sorted()` can't tell which entry came
# first from same time-stamp if from different
# simulations; allow for this with error
error = 3e-5
self.assertAlmostEqual(output['voltage'][i],
output['voltage'][i - 1],
delta=error)
else:
# Time values are different
# Check to affirm that the variable NOT being held
# constant is steadily increasing / decreasing
# First part happens in first 4 minutes
if output['time'][i] <= 5.0: # part 1, const currrent
# current should be equal
self.assertEqual(output['current'][i],
output['current'][i - 1])
# voltage should not have decreased
self.assertTrue(output['voltage'][i],
output['voltage'][i - 1])
else: # part 2, const voltage
# current should be getting less positive
self.assertTrue(
output['current'][i] <= output['current'][i - 1],
msg=(output['current'][i - 2:i + 10],
output['time'][i - 2:i + 10]))
# voltage should decrease, then stay at 4.54
if output['voltage'][i - 1] == 4.54:
self.assertEqual(output['voltage'][i],
output['voltage'][i - 1])
else:
self.assertTrue(
output['voltage'][i] <= output['voltage'][i - 1])
# update index
i = i + 1
# Copyright (c) 2016, the Cap authors.
#
# This file is subject to the Modified BSD License and may not be distributed
# without copyright and license information. Please refer to the file LICENSE
# for the text and further information on this license.
from pycap import PropertyTree, EnergyStorageDevice
from pycap import Charge
from pycap import initialize_data
from mpi4py import MPI
import unittest
comm = MPI.COMM_WORLD
filename = 'series_rc.info'
ptree = PropertyTree()
ptree.parse_info(filename)
device = EnergyStorageDevice(ptree, comm)
class capChargeTestCase(unittest.TestCase):
def test_charge_constant_current(self):
ptree = PropertyTree()
ptree.put_string('charge_mode', 'constant_current')
ptree.put_double('charge_current', 10e-3)
ptree.put_string('charge_stop_at_1', 'voltage_greater_than')
ptree.put_double('charge_voltage_limit', 1.4)
ptree.put_double('time_step', 0.2)
charge = Charge(ptree)
data = initialize_data()
charge.run(device, data)
self.assertAlmostEqual(data['current'][0], 10e-3)
def test_constructor(self):
self.assertRaises(TypeError, EndCriterion)
self.assertRaises(RuntimeError, EndCriterion, PropertyTree())
def test_invalid_end_criterion(self):
ptree = PropertyTree()
ptree.put_string('end_criterion', 'bad_name')
self.assertRaises(RuntimeError, EndCriterion.factory, ptree)
def test_always_statisfied(self):
ptree = PropertyTree()
ptree.put_string('end_criterion', 'skip')
always_statisfied = EndCriterion.factory(ptree)
always_statisfied.reset(0.0, device)
self.assertTrue(always_statisfied.check(NaN, device))
def test_never_statisfied(self):
ptree = PropertyTree()
ptree.put_string('end_criterion', 'none')
never_statisfied = EndCriterion.factory(ptree)
never_statisfied.reset(0.0, device)
self.assertFalse(never_statisfied.check(NaN, device))
def test_rest(self):
ptree = PropertyTree()
ptree.put_string('mode', 'rest')
evolve_one_time_step = TimeEvolution.factory(ptree)
evolve_one_time_step(device, 0.1)
self.assertEqual(device.get_current(), 0.0)
def test_invalid_time_evolution(self):
ptree = PropertyTree()
ptree.put_string('mode', 'unexpected')
self.assertRaises(RuntimeError, TimeEvolution.factory, ptree)
def test_constructor(self):
self.assertRaises(TypeError, TimeEvolution)
self.assertRaises(RuntimeError, TimeEvolution, PropertyTree())
#!/usr/bin/env python
from puq import dump_hdf5
from optparse import OptionParser
from pycap import PropertyTree, EnergyStorageDevice
from pycap import measure_impedance_spectrum
from numpy import real, imag, log10, absolute, angle
# read uq database
uq_database = PropertyTree()
uq_database.parse_xml('uq.xml')
# get number of parameters
params = uq_database.get_int('uq.params')
# usage
usage = 'usage: %prog'
for p in range(params):
usage += ' --param_' + str(p) + ' val_' + str(p)
parser = OptionParser(usage)
# register options
for p in range(params):
parser.add_option('--param_' + str(p), type=float)
# parse the command line arguments
(options, args) = parser.parse_args()
# make device database
device_database = PropertyTree()
device_database.parse_xml('super_capacitor.xml')
# adjust the parameters in the database
options_dict = vars(options)
for var in options_dict:
def run():
# parse uq database
input_database = PropertyTree()
input_database.parse_xml('uq.xml')
uq_database = input_database.get_child('uq')
# declare parameters
params = uq_database.get_int('params')
parameter_list = []
for p in range(params):
parameter_database = uq_database.get_child('param_' + str(p))
distribution_type = parameter_database.get_string('distribution_type')
parameter_name = parameter_database.get_string('name')
if distribution_type == 'uniform':
parameter_range = parameter_database.get_array_double('range')
parameter_list.append(
UniformParameter('param_' + str(p),
parameter_name,
min=parameter_range[0],
max=parameter_range[1]))
elif distribution_type == 'normal':
parameter_mean = parameter_database.get_double('mean')
parameter_standard_deviation = parameter_database.get_double(
'standard_deviation')
parameter_list.append(
NormalParameter('param_' + str(p),
parameter_name,
mean=parameter_mean,
dev=parameter_standard_deviation))
else:
raise RuntimeError('invalid distribution type ' +
distribution_type + ' for param_' + str(p))
# create a host
host_database = uq_database.get_child('host')
host_type = host_database.get_string('type')
if host_type == "Interactive":
host = InteractiveHost(
cpus=host_database.get_int_with_default_value('cpus', 1),
cpus_per_node=host_database.get_int_with_default_value(
'cpus_per_node', 0))
elif host_type == "PBS":
host = PBSHost(
host_database.get_string('env'),
cpus=host_database.get_int_with_default_value('cpus', 0),
cpus_per_node=host_database.get_int_with_default_value(
'cpus_per_node', 0),
qname=host_database.get_string_with_default_value(
'qname', 'standby'),
walltime=host_database.get_string_with_default_value(
'walltime', '1:00:00'),
modules=host_database.get_string_with_default_value('modules', ''),
pack=host_database.get_int_with_default_value('pack', 1),
qlimit=host_database.get_int_with_default_value('qlimit', 200))
else:
raise RuntimeError('invalid host type ' + host_type)
# pick UQ method
method = uq_database.get_string('method')
if method == 'SmolyakSparseGrid':
level = uq_database.get_int('level')
uq = Smolyak(parameter_list, level=level)
elif method == 'MonteCarlo':
samples = uq_database.get_int('samples')
uq = MonteCarlo(parameter_list, num=samples)
elif method == 'LatinHypercubeSampling':
samples = uq_database.get_int('samples')
uq = LHS(parameter_list, num=samples)
else:
raise RuntimeError('invalid UQ method ' + method)
# make a test program
test_program_database = uq_database.get_child('test_program')
description = test_program_database.get_string('description')
executable_name = test_program_database.get_string('executable')
for p in range(params):
executable_name += ' --param_' + str(p) + ' $param_' + str(p)
prog = TestProgram(exe=executable_name, desc=description)
# run
return Sweep(uq, host, prog)
