def save_model(self):
"""
Tests if the correct parts are saved/loaded from disk using the
``save_model()`` method.
"""
ipath = os.path.join(myotest.DIR_DATA, 'lr-1991.mmt')
opath = os.path.join(myotest.DIR_OUT, 'loadsavetest.mmt')
if os.path.exists(opath):
os.remove(opath)
# Test example loading
m = myokit.load_model('example')
self.assertIsInstance(m, myokit.Model)
# Test file loading
m = myokit.load_model(ipath)
self.assertIsInstance(m, myokit.Model)
if os.path.exists(opath):
os.remove(opath)
try:
myokit.save_model(opath, m)
# Test no other parts were written
with open(opath, 'r') as f:
text = f.read()
self.assertTrue('[[model]]' in text)
self.assertFalse('[[protocol]]' in text)
self.assertFalse('[[script]]' in text)
# Test reloading
mm = myokit.load_model(opath)
self.assertIsInstance(mm, myokit.Model)
self.assertEqual(mm.code(), m.code())
finally:
os.remove(opath)
def test_easyml_exporter(self):
# Tests exporting a model
model1 = myokit.load_model('example')
model2 = myokit.load_model(os.path.join(DIR_DATA, 'heijman-2011.mmt'))
e = myokit.formats.easyml.EasyMLExporter()
with TemporaryDirectory() as d:
path = d.path('easy.model')
# Test with simple model
e.model(path, model1)
# Test with model containing markov models
with WarningCollector() as c:
e.model(path, model2)
self.assertIn('unsupported function: atan', c.text())
self.assertIn('unsupported function: sin', c.text())
self.assertEqual(c.count(), 6)
# Test with extra bound variables
model1.get('membrane.C').set_binding('hello')
e.model(path, model1)
# Test without V being a state variable
v = model1.get('membrane.V')
v.demote()
v.set_rhs(3)
e.model(path, model1)
# Test with invalid model
v.set_rhs('2 * V')
self.assertRaisesRegex(myokit.ExportError, 'valid model', e.model,
path, model1)
def test_save_model(self):
"""
Test if the correct parts are saved/loaded from disk using the
``save_model()`` method.
"""
ipath = os.path.join(DIR_DATA, 'lr-1991.mmt')
# Test example loading
m = myokit.load_model('example')
self.assertIsInstance(m, myokit.Model)
# Test file loading
m = myokit.load_model(ipath)
self.assertIsInstance(m, myokit.Model)
with TemporaryDirectory() as d:
opath = d.path('loadsave.mmt')
myokit.save_model(opath, m)
# Test no other parts were written
with open(opath, 'r') as f:
text = f.read()
self.assertTrue('[[model]]' in text)
self.assertFalse('[[protocol]]' in text)
self.assertFalse('[[script]]' in text)
# Test reloading
mm = myokit.load_model(opath)
self.assertIsInstance(mm, myokit.Model)
self.assertEqual(mm.code(), m.code())
def setUpClass(cls):
# Load models and protocols for use in testing
# Fiber model, tissue model, protocol
cls.mf = myokit.load_model(
os.path.join(DIR_DATA, 'dn-1985-normalised.mmt'))
cls.mt = myokit.load_model(os.path.join(DIR_DATA, 'lr-1991.mmt'))
# Fiber/Tissue sizes (small sim)
cls.nfx = 8
cls.nfy = 4
cls.ntx = 8
cls.nty = 6
# Standard protocols
cls.p1 = myokit.pacing.blocktrain(1000, 2, offset=.01)
# Protocol with error at t = 2
cls.p2 = myokit.Protocol()
cls.p2.schedule(period=0, duration=5, level=5e3, start=2)
# Protocol with error at t = 1.234 (in tissue?)
cls.p3 = myokit.Protocol()
cls.p3.schedule(period=0, duration=5, level=-1, start=1.234)
v = cls.mt.get('ina.m')
v.set_rhs('if(membrane.V < -100, 1e4, ' + v.rhs().code() + ')')
# Shared simulations
cls._s1 = None
def test_multiline_string_indent(self):
"""
Test what happens when you load save a string that gets auto-indented.
"""
# Create model with multi-line meta-data property
d1 = 'First line\n\nSecond line'
m1 = myokit.Model()
m1.meta['desc'] = d1
e = m1.add_component('engine')
v = e.add_variable('time')
v.set_binding('time')
v.set_rhs(0)
# Store to disk
with TemporaryDirectory() as d:
opath = d.path('multiline.mmt')
myokit.save_model(opath, m1)
# Load and compare the meta-data string
m2 = myokit.load_model(opath)
d2 = m2.meta['desc']
self.assertEqual(d1, d2)
# Create model with indented multi-line meta-data property
d1 = ' First line\n\n Second line'
dr = 'First line\n\nSecond line'
m1 = myokit.Model()
m1.meta['desc'] = d1
e = m1.add_component('engine')
v = e.add_variable('time')
v.set_binding('time')
v.set_rhs(0)
# Store to disk
with TemporaryDirectory() as d:
opath = d.path('multiline.mmt')
myokit.save_model(opath, m1)
# Load and compare the meta-data string
m2 = myokit.load_model(opath)
d2 = m2.meta['desc']
self.assertEqual(d2, dr)
# Create model with strangely indented multi-line meta-data property
d1 = ' First line\n\n Second line'
dr = 'First line\n\n Second line'
m1 = myokit.Model()
m1.meta['desc'] = d1
e = m1.add_component('engine')
v = e.add_variable('time')
v.set_binding('time')
v.set_rhs(0)
# Store to disk
with TemporaryDirectory() as d:
opath = d.path('multiline.mmt')
myokit.save_model(opath, m1)
# Load and compare the meta-data string
m2 = myokit.load_model(opath)
d2 = m2.meta['desc']
self.assertEqual(d2, dr)
def step(source, ref, ini, raw):
"""
Loads a model and evaluates the state vector derivatives.
"""
import sys
import myokit
# Parse reference file, if given
if ref and not raw:
print('Reading reference file...')
try:
ref = myokit.load_model(ref[0])
print('Reference model loaded successfully.')
except Exception:
ref = myokit.load_state(ref[0])
print('Reference file read successfully.')
# Parse initial value file, if given
if ini:
if not raw:
print('Reading initial value file...')
ini = myokit.load_state(ini[0])
if not raw:
print('Initial value file read successfully.')
# Load myokit model
try:
if not raw:
print('Reading model from ' + source + '...')
model = myokit.load_model(source)
if not raw:
print('Model ' + model.name() + ' read successfully.')
except myokit.ParseError as ex:
print(myokit.format_parse_error(ex, source))
sys.exit(1)
# Ensure proper ordering of reference and initial value files
if ref and not isinstance(ref, myokit.Model):
ref = model.map_to_state(ref)
# Evaluate all derivatives, show the results
try:
if raw:
derivs = model.eval_state_derivatives(state=ini)
print('\n'.join([myokit.strfloat(x) for x in derivs]))
else:
print(myokit.step(model, initial=ini, reference=ref))
except myokit.NumericalError as ee:
e = 'Numerical error'
n = line_width - len(e) - 2
print('-' * int(n / 2) + ' ' + e + ' ' + '-' * (n - int(n / 2)))
print('A numerical error occurred:')
print(str(ee))
def compare(model1, model2):
"""
Compares two models.
"""
import myokit
# Load models
m1 = myokit.load_model(model1)
m2 = myokit.load_model(model2)
# Compare
myokit.ModelComparison(m1, m2, live=True)
def test_opencl_exporter_errors(self):
# Checks the errors raised by the OpenCL exporter.
e = myokit.formats.exporter('opencl')
# Label membrane_potential must be set
m = myokit.load_model('example')
m.label('membrane_potential').set_label(None)
self.assertRaisesRegex(ValueError, 'membrane_potential', self._test, e,
m)
# Binding diffusion_current must be set
m = myokit.load_model('example')
m.binding('diffusion_current').set_binding(None)
self.assertRaisesRegex(ValueError, 'diffusion_current', self._test, e,
m)
def test_advanced_units(self):
"""
Tests the new unit syntax where literals have units.
"""
model = 'br-1977-units.mmt'
m = myokit.load_model(os.path.join(myotest.DIR_DATA, model))
m.validate()
def test_piecewise(self):
"""
Tests a model with a piecewise statement
"""
m = myokit.load_model(os.path.join(myotest.DIR_DATA,
'conditional.mmt'))
# Test evaluation
x = m.get('test.x')
y = m.get('test.y')
xo = m.get('test.xo')
yo = m.get('test.yo')
s = m.state()
i = m.get('membrane.V').indice()
# Test x, xo, y, yo
s[i] = -80
m.set_state(s)
self.assertEqual(x.rhs().eval(), 3)
self.assertEqual(xo.rhs().eval(), 3)
self.assertEqual(y.rhs().eval(), 2)
self.assertEqual(yo.rhs().eval(), 2)
s[i] = -10
m.set_state(s)
self.assertEqual(x.rhs().eval(), 2)
self.assertEqual(xo.rhs().eval(), 2)
self.assertEqual(y.rhs().eval(), 2)
self.assertEqual(yo.rhs().eval(), 2)
s[i] = 30
m.set_state(s)
self.assertEqual(x.rhs().eval(), 1)
self.assertEqual(xo.rhs().eval(), 1)
self.assertEqual(y.rhs().eval(), 1)
self.assertEqual(yo.rhs().eval(), 1)
# Test code() output by cloning
m.clone()
def test_strip_expression_units(self):
"""
Test :meth:`strip_expression_units`.
"""
from myokit._parsing import parse_model, strip_expression_units
m1 = myokit.load_model('example')
m2 = parse_model(m1.code())
self.assertEqual(m1.code(), m2.code())
m2 = parse_model(strip_expression_units(m1.code()))
c1 = m1.code()
c2 = m2.code()
self.assertNotEqual(c1, c2)
self.assertTrue(len(c2) < len(c1))
self.assertEqual(m1.eval_state_derivatives(),
m2.eval_state_derivatives())
m2 = parse_model(strip_expression_units(m1.code().splitlines()))
c1 = m1.code()
c2 = m2.code()
self.assertNotEqual(c1, c2)
self.assertTrue(len(c2) < len(c1))
self.assertEqual(m1.eval_state_derivatives(),
m2.eval_state_derivatives())
def activation(self):
"""
Tests the activation experiment class.
"""
# Load model
m = os.path.join(myotest.DIR_DATA, 'lr-1991.mmt')
m = myokit.load_model(m)
# Create experiment
c = m.get('ina')
g = c.add_variable('g')
g.set_rhs('m^3 * h * j')
m.validate()
a = common.Activation(m, 'ina.g')
# Test
a.times()
a.traces()
a.peaks(normalize=True)
a.peaks(normalize=False)
a.fit_boltzmann()
a.convert_g2i()
a.times()
a.traces()
a.peaks(normalize=True)
a.peaks(normalize=False)
a.fit_boltzmann()
def setUpClass(cls):
# Load model, simulation etc. only once
fname = os.path.join(DIR_DATA, 'clancy-1999-fitting.mmt')
model = myokit.load_model(fname)
# Extract the Markov model of INa
parameters = ['ina.p1', 'ina.p2']
cls._boundaries = [[1e-3, 10], [1e-3, 10]]
markov_model = markov.LinearModel.from_component(
model.get('ina'),
parameters=parameters,
current='ina.i',
)
# Create an analytical markov model simulation
cls._sim = markov.AnalyticalSimulation(markov_model)
# Voltages to test at
r = 10
cls._voltages = np.arange(-70, -10 + r, r)
# Times to evaluate at
times = np.concatenate((np.linspace(0, 4, 100), np.linspace(4, 8, 20)))
# Generate reference traces
cls._references = []
for v in cls._voltages:
cls._sim.set_membrane_potential(v)
x, i = cls._sim.solve(times)
cls._references.append(i)
# Give a hint
# p1 = 0.1027 / 3.802 ~ 0.0270
# p2 = 0.20 / 3.802 ~ 0.0526
cls._hint = [0.0269, 0.052]
def create_manual(self):
"""
Tests manual creation of a Markov model
"""
# Load model
fname = os.path.join(myotest.DIR_DATA, 'clancy-1999-fitting.mmt')
model = myokit.load_model(fname)
# Select a number of states and parameters
states = [
'ina.C3',
'ina.C2',
'ina.C1',
'ina.IF',
'ina.IS',
'ina.O',
]
parameters = [
'ina.p1',
'ina.p2',
'ina.p3',
'ina.p4',
]
current = 'ina.i'
# Create a markov model
m = markov.LinearModel(model, states, parameters, current)
# Create a simulation
s = markov.AnalyticalSimulation(m)
# Times to evaluate at
times = np.linspace(0, 100, 5)
# Voltages to test at
voltages = np.arange(-70, 0, 30)
# Generate traces
for v in voltages:
s.set_membrane_potential(v)
x, i = s.solve(times)
def GPB_HF_Moreno(cell_type = None):
m = myokit.load_model('grandi-2010_modified.mmt')
# Original grandi model does not contain late channel. Changes from Tenor et al.
# Late Na+ current. +900%
inal = m.get('inal.GNal') # GNal multiplied by both junc and sl
inal.set_rhs(myokit.Multiply(myokit.Number(10.0), inal.rhs()))
# Transient outward K+ current -36%
ito = m.get('ito.ito')
ito.set_rhs(myokit.Multiply(myokit.Number(0.64), ito.rhs()))
# Inward rectifier K+ current. -25% in HF
ik1 = m.get('ik1.I_k1')
ik1.set_rhs(myokit.Multiply(myokit.Number(0.75), ik1.rhs()))
# Na+/ K+ pump current- Between -42% and -10% in literature. Taken mean:-26%
inak = m.get('inak.I_nak')
inak.set_rhs(myokit.Multiply(myokit.Number(0.9), inak.rhs()))
# Background Na+ current +1600% in moreno (2013) from rabbit HF data
inab = m.get('inab.GNaB') # Then slow and junc = 0, as both multiplied by GNaB
inab.set_rhs(myokit.Multiply(myokit.Number(1.0), inab.rhs()))
# Sarco/ endoplasmic reticulum Ca2+ pump current: -36% in HF human patients
serca = m.get('caflux.J_serca')
serca.set_rhs(myokit.Multiply(myokit.Number(0.64), serca.rhs()))
# SR Ca2+ leak. +350% from rabbit HF data
leak = m.get('caflux.J_SRleak')
leak.set_rhs(myokit.Multiply(myokit.Number(4.5), leak.rhs()))
return(m)
def test_activation(self):
# Test the activation experiment class.
with WarningCollector():
import myokit.lib.common as common
# Load model
m = os.path.join(DIR_DATA, 'lr-1991.mmt')
m = myokit.load_model(m)
# Create experiment
c = m.get('ina')
g = c.add_variable('g')
g.set_rhs('m^3 * h * j')
m.validate()
a = common.Activation(m, 'ina.g')
# Test
a.times()
a.traces()
a.peaks(normalize=True)
a.peaks(normalize=False)
a.fit_boltzmann()
a.convert_g2i()
a.times()
a.traces()
a.peaks(normalize=True)
a.peaks(normalize=False)
a.fit_boltzmann()
def test_equals(self):
# Check that equality takes both code() and unames into account
# Test without custom reserved names
m1 = myokit.load_model('example')
m2 = m1.clone()
self.assertIsInstance(m2, myokit.Model)
self.assertFalse(m1 is m2)
self.assertEqual(m1, m2)
self.assertEqual(m1, m1)
# Test with none-model
self.assertNotEqual(m1, None)
self.assertNotEqual(m1, m1.code())
# Add reserved names
m1.reserve_unique_names('bertie')
self.assertNotEqual(m1, m2)
m1.reserve_unique_names('clair')
self.assertNotEqual(m1, m2)
m2.reserve_unique_names('clair', 'bertie')
self.assertEqual(m1, m2)
# Add reserved name prefixes
m1.reserve_unique_name_prefix('aa', 'bb')
m1.reserve_unique_name_prefix('cc', 'dd')
self.assertNotEqual(m1, m2)
m2.reserve_unique_name_prefix('aa', 'bb')
m2.reserve_unique_name_prefix('cc', 'ee')
self.assertNotEqual(m1, m2)
m2.reserve_unique_name_prefix('cc', 'dd')
self.assertEqual(m1, m2)
def simulate_aps(scales, model_file, beats=2, cl=1000, prepace=100,
stimulate=True):
"""
Generate APs using the given scalings.
"""
# Load model
model = myokit.load_model(model_file)
# Apply scalings
for var in scales:
scale = scales[var]
v = model.get(var)
v.set_rhs(myokit.Multiply(myokit.Number(scale), v.rhs()))
# Simulate with modified model
sim = myokit.Simulation(model)
# Add stimulus
if stimulate:
protocol = myokit.pacing.blocktrain(period=cl, duration=1,
offset=50)
sim.set_protocol(protocol)
# Pre-pace for some beats
sim.pre(prepace * cl)
# Log some beats and return
log = ['engine.time', 'membrane.V']
log = ['environment.time', 'membrane.V']
log = ['membrane.V']
return sim.run(beats * cl, log=log, log_interval=DT).npview()
def test_component_dependency_graph(self):
# Test create_ and plot_ component dependency graph method, to show
# digraph plot of variable dependencies.
# Nodes are placed at random, so seed the generator for consistent
# output (otherwise we risk missing full cover on some runs).
random.seed(1)
# Load model
model = myokit.load_model('example')
# Select matplotlib backend that doesn't require a screen
import matplotlib
matplotlib.use('template')
# Create plot
self.assertFalse(model.has_interdependent_components())
deps.plot_component_dependency_graph(model)
# Add cyclical component dependencies, plot again
# This time, the acylical plotting code can't be used.
v = model.get('ina').add_variable('ion')
v.set_rhs('membrane.i_ion')
self.assertTrue(model.has_interdependent_components())
deps.plot_component_dependency_graph(model)
def test_stan_exporter(self):
# Basic test
self._test(myokit.formats.exporter('stan'))
# Test with parameters and output variable specified
# Load model
m = myokit.load_model('example')
# Guess parameters
parameters = []
for v in m.get('ina').variables(const=True):
if v.name()[:1] == 'p':
parameters.append(v)
parameters.sort(key=lambda v: myokit._natural_sort_key(v.name()))
# Set output
output = 'ina.INa'
# Export to stan
e = myokit.formats.stan.StanExporter()
with TemporaryDirectory() as d:
dpath = d.path('out')
ret = e.runnable(dpath, m, parameters=parameters, output=output)
self.assertIsNone(ret)
self.assertTrue(os.path.isdir(dpath))
self.assertTrue(len(os.listdir(dpath)) > 0)
def test_linear_model_steady_state_1(self):
# Test finding the steady-state of the Clancy model
# Create model
filename = os.path.join(DIR_DATA, 'clancy-1999-fitting.mmt')
model = myokit.load_model(filename)
m = markov.LinearModel.from_component(model.get('ina'))
# Get steady state
ss = np.array(m.steady_state())
# Check that this is a valid steady state
self.assertTrue(np.all(ss >= 0))
self.assertTrue(np.all(ss <= 1))
# Check that derivatives with ss are close to zero
ss = list(ss)
model.set_state(ss + ss) # Model has 2 ina's
derivs = model.evaluate_derivatives()
for i in range(len(ss)):
self.assertAlmostEqual(0, derivs[i])
# Try with awful parameters
self.assertRaisesRegex(markov.LinearModelError,
'positive eigenvalues',
m.steady_state,
parameters=[-1] * 21)
def test_easyml_exporter(self):
# Tests exporting a model
model = myokit.load_model('example')
with TemporaryDirectory() as d:
path = d.path('easy.model')
# Test with simple model
e = myokit.formats.easyml.EasyMLExporter()
e.model(path, model)
# Test with extra bound variables
model.get('membrane.C').set_binding('hello')
e.model(path, model)
# Test without V being a state variable
v = model.get('membrane.V')
v.demote()
v.set_rhs(3)
e.model(path, model)
# Test with invalid model
v.set_rhs('2 * V')
self.assertRaisesRegex(myokit.ExportError, 'valid model', e.model,
path, model)
def test_linear_combination(self):
# Tests _linear_combination()
# Load model, to create interesting RHS
fname = os.path.join(DIR_DATA, 'clancy-1999-fitting.mmt')
model = myokit.load_model(fname)
v1 = model.get('ina.C1')
v2 = model.get('ina.C2')
v3 = model.get('ina.C3')
v4 = model.get('ina.IF')
v5 = model.get('ina.IS')
v6 = model.get('ina.O')
# Test C1 rhs
f = markov._linear_combination(v1.rhs(), [v1, v2, v3, v4, v5, v6])
self.assertEqual(f[0].code(), '-(ina.a13 + ina.b12 + ina.b3)')
self.assertEqual(f[1].code(), 'ina.a12')
self.assertIsNone(f[2])
self.assertEqual(f[3].code(), 'ina.a3')
self.assertIsNone(f[4])
self.assertEqual(f[5].code(), 'ina.b13')
# Test double appearances
v1.set_rhs('2 * C1 - 3 * C1 + C1 * sqrt(O) + C2 * IF')
f = markov._linear_combination(v1.rhs(), [v1, v2, v3])
self.assertEqual(f[0].code(), '2 + -3 + sqrt(ina.O)')
self.assertEqual(f[1].code(), 'ina.IF')
self.assertIsNone(f[2])
def __init__(self, protocol, temperature, sine_wave=False):
# Load model
model = myokit.load_model(model_file)
# Set reversal potential
model.get('nernst.EK').set_rhs(erev(temperature))
# Add sine-wave equation to model
if sine_wave:
model.get('membrane.V').set_rhs(
'if(engine.time >= 3000.1 and engine.time < 6500.1,' +
' - 30' + ' + 54 * sin(0.007 * (engine.time - 2500.1))' +
' + 26 * sin(0.037 * (engine.time - 2500.1))' +
' + 10 * sin(0.190 * (engine.time - 2500.1))' +
', engine.pace)')
# Create simulation
self.simulation = myokit.Simulation(model)
# Add protocol
if isinstance(protocol, myokit.Protocol):
self.simulation.set_protocol(protocol)
else:
# Apply data-clamp
times, voltage = protocol
self.simulation.set_fixed_form_protocol(times, voltage)
# Set max step size
self.simulation.set_max_step_size(0.1)
# Set solver tolerances to values used by Kylie
self.simulation.set_tolerance(1e-8, 1e-8)
def test_show_expressions_for(self):
# Test :meth:`Model.show_expressions_for(variable)`.
m = myokit.load_model('example')
e = m.show_expressions_for(m.get('ina.INa'))
self.assertIn('ina.INa is a function of', e)
self.assertEqual(len(e.splitlines()), 22)
def test_hh_model_steady_state(self):
# Test the method HHModel.steady_state().
# Create model
fname = os.path.join(DIR_DATA, 'lr-1991-fitting.mmt')
model = myokit.load_model(fname)
m = hh.HHModel.from_component(model.get('ina'))
# Get steady state
ss = np.array(m.steady_state())
# Check that this is a valid steady state
self.assertTrue(np.all(ss >= 0))
self.assertTrue(np.all(ss <= 1))
# Test if derivatives are zero
for k, x in enumerate(['ina.m', 'ina.h', 'ina.j']):
x = model.get(x)
x.set_state_value(ss[k])
self.assertAlmostEqual(x.eval(), 0)
# Test arguments
m.steady_state(-20, m.default_parameters())
self.assertRaisesRegex(ValueError, 'parameter vector size',
m.steady_state, -20, [1])
def test_get(self):
# Test Model.get().
m = myokit.load_model('example')
# Get by name
v = m.get('membrane.V')
self.assertEqual(v.qname(), 'membrane.V')
self.assertIsInstance(v, myokit.Variable)
# Get by variable ref (useful for handling unknown input type)
w = m.get(v)
self.assertIs(w, v)
# Get nested
a = m.get('ina.m.alpha')
self.assertEqual(a.qname(), 'ina.m.alpha')
self.assertIsInstance(a, myokit.Variable)
# Get component
c = m.get('membrane')
self.assertEqual(c.qname(), 'membrane')
self.assertIsInstance(c, myokit.Component)
# Get with filter
a = m.get('ina.m.alpha', myokit.Variable)
self.assertEqual(a.qname(), 'ina.m.alpha')
self.assertIsInstance(a, myokit.Variable)
self.assertRaises(KeyError, m.get, 'ina.m.alpha', myokit.Component)
self.assertRaises(KeyError, m.get, 'ina', myokit.Variable)
m.get('ina', myokit.Component)
# Get non-existent
self.assertRaises(KeyError, m.get, 'membrane.bert')
self.assertRaises(KeyError, m.get, 'bert.bert')
def test_against_cvode(self):
# Validate against a cvode sim.
# Get a model
fname = os.path.join(DIR_DATA, 'lr-1991-fitting.mmt')
model = myokit.load_model(fname)
model.get('membrane.V').set_binding('pace')
# Create a protocol
vs = [-30, -20, -10]
p = myokit.pacing.steptrain(vsteps=vs,
vhold=-120,
tpre=8,
tstep=2,
tpost=0)
t = p.characteristic_time()
# Run an analytical simulation
dt = 0.01
m = hh.HHModel.from_component(model.get('ina'))
s1 = hh.AnalyticalSimulation(m, p)
d1 = s1.run(t, log_interval=dt).npview()
s2 = myokit.Simulation(model, p)
s2.set_tolerance(1e-8, 1e-8)
d2 = s2.run(t, log_interval=dt).npview()
# Test protocol output is the same
e = np.abs(d1['membrane.V'] - d2['membrane.V'])
self.assertEqual(np.max(e), 0)
# Test current output is very similar
e = np.abs(d1['ina.INa'] - d2['ina.INa'])
self.assertLess(np.max(e), 2e-4)
def test_recovery(self):
# Test the recovery experiment class.
with WarningCollector():
import myokit.lib.common as common
# Load model
m = os.path.join(DIR_DATA, 'lr-1991.mmt')
m = myokit.load_model(m)
# Create experiment
c = m.get('ina')
g = c.add_variable('g')
g.set_rhs('m^3 * h * j')
m.validate()
r = common.Recovery(m, 'ina.g')
# Test
n = 20
r.set_pause_duration(0.1, 10, n)
d = r.ratio()
self.assertEqual(len(d), 2)
self.assertIn('engine.time', d)
self.assertIn('ina.g', d)
self.assertEqual(n, len(d['engine.time']))
self.assertEqual(n, len(d['ina.g']))
x = d['engine.time']
self.assertTrue(np.all(x[1:] > x[:-1]))
x = d['ina.g'] # This is a monotonically increasing function
self.assertTrue(np.all(x[1:] > x[:-1]))
def test_simultaneous_event_error(self):
# Test raising of errors on rescheduled periodic events
p = myokit.Protocol()
p.schedule(1, 0, 1, 1000)
p.schedule(1, 3000, 1)
s = AnsicEventBasedPacing(p)
t = s.next_time()
self.assertEqual(t, 1)
s.advance(t)
t = s.next_time()
self.assertEqual(t, 1000)
s.advance(t)
t = s.next_time()
self.assertEqual(t, 1001)
s.advance(t)
t = s.next_time()
self.assertEqual(t, 2000)
self.assertRaises(myokit.SimultaneousProtocolEventError, s.advance, t)
# Test raising of errors in simulation
p = myokit.Protocol()
p.schedule(1, 0, 1, 10)
p.schedule(1, 30, 1)
m = myokit.load_model('example')
s = myokit.Simulation(m, p)
self.assertRaises(myokit.SimultaneousProtocolEventError, s.run, 40)
