def relog(_logf, _logt, _dt):
# Get first occurence of error
ifirstf, kfirstf = find_error_position(_logf)
ifirstt, kfirstt = find_error_position(_logt)
if kfirstf is None and kfirstt is None:
raise myokit.FindNanError('Error condition not found in logs.')
elif kfirstf is None:
ifirst = ifirstt
elif kfirstt is None:
ifirst = ifirstf
elif ifirstf == 0 or ifirstt == 0:
raise myokit.FindNanError(
'Unable to work with simulation logs where the error'
' condition is met in the very first data point.')
else:
ifirst = min(ifirstf, ifirstt)
# Position to start deep search at
istart = ifirst - 1
# Get last logged states before error
statef = []
statet = []
for dims in myokit._dimco(*self._ncellsf):
pre = '.'.join([str(x) for x in dims]) + '.'
for s in self._modelf.states():
statef.append(_logf[pre + s.qname()][istart])
for dims in myokit._dimco(*self._ncellst):
pre = '.'.join([str(x) for x in dims]) + '.'
for s in self._modelt.states():
statet.append(_logt[pre + s.qname()][istart])
# Get last time before error
time = _logf[time_varf][istart]
# Save current state & time
old_statef = self._statef
old_statet = self._statet
old_time = self._time
self._statef = statef
self._statet = statet
self._time = time
# Run until next time point, log every step
duration = _logf[time_varf][ifirst] - time
log = myokit.LOG_BOUND + myokit.LOG_STATE
_logf, _logt = self.run(duration,
logf=log,
logt=log,
log_interval=_dt,
report_nan=False)
# Reset simulation to original state
self._statef = old_statef
self._statet = old_statet
self._time = old_time
# Return new logs
return _logf, _logt
def relog(_log, _dt):
# Get first occurence of error
ifirst, kfirst = find_error_position(_log)
if kfirst is None:
raise myokit.FindNanError('Error condition not found in log.')
if ifirst == 0:
raise myokit.FindNanError(
'Unable to work with simulation logs where the error'
' condition is met in the very first data point.')
# Position to start deep search at
istart = ifirst - 1
# Get last logged state before error
state = []
for dims in myokit._dimco(*self._dims):
pre = '.'.join([str(x) for x in dims]) + '.'
for s in self._model.states():
state.append(_log[pre + s.qname()][istart])
# Get last time before error
time = _log[time_var][istart]
# Save current state & time
old_state = self._state
old_time = self._time
self._state = state
self._time = time
# Run until next time point, log every step
duration = _log[time_var][ifirst] - time
_log = self.run(duration,
log=myokit.LOG_BOUND + myokit.LOG_STATE,
log_interval=_dt,
report_nan=False)
# Reset simulation to original state
self._state = old_state
self._time = old_time
# Return new log
return _log
def find_error_position(_log):
# Find first occurence of out-of-bounds error
ifirst = None
kfirst = None
post = '.' + watch_var.qname()
lower, upper = safe_range
for dims in myokit._dimco(*self._dims):
key = '.'.join([str(x) for x in dims]) + post
ar = np.array(_log[key], copy=False)
i = np.where((ar < lower)
| (ar > upper)
| np.isnan(ar)
| np.isinf(ar))[0]
if len(i) > 0:
i = i[0]
if ifirst is None:
kfirst = key
ifirst = i
elif i < ifirst:
kfirst = key
ifirst = i
if i == 0:
break
return ifirst, kfirst