def solve_model(self, configuration):
"""Solve the parameterised version of the model. This assumes
that parameterise_model has already been called and that hence
a parameterised version of the model exists in a file named
self.paramed_file"""
start_time = configuration.start_time
stop_time = configuration.stop_time
data_points = int((stop_time - start_time) /
configuration.out_interval)
biopepa_command = [ "java",
"-jar",
"biopepa.jar",
"timeseries",
self.paramed_file,
"--no-warnings",
"--solver",
"dopr-adaptive",
"--timeStep",
str(configuration.interval),
"--startTime",
str(start_time),
"--stopTime",
str(stop_time),
"--dataPoints",
str(data_points),
# "--output-file",
# csvfile
]
biopepa_returncode = run_command(biopepa_command)
biopepa_process = Popen(biopepa_command, stdout=PIPE, stderr=PIPE)
output, errorout = biopepa_process.communicate()
if errorout:
logging.error ("The biopepa process produced output on stderr")
logging.error (errorout)
logging.error ("The biopepa command was: ")
logging.error (" ".join(biopepa_command))
if biopepa_returncode != 0:
logging.error ("biopepa process failed to return")
sys.exit(1)
# A bug in pylint causes it to complain about this, it incorrectly
# thinks that 'output' is of type list, but it is of type string.
output_lines = output.split("\n")
timecourse = timeseries.parse_csv(output_lines.__iter__(), ", ")
return timecourse
def solve_model(self, configuration):
"""Solve the given model and return a timeseries, or None
if solving the model has failed for some reason"""
# We need a relatively portable way to check that this command
# succeeds. Because we are constrained for the moment to using
# os.system, I'm a little unsure about simply checking the return
# code. So for now I'm removing the results file and subsequently
# I will check if it exists.
# We should be able to update this to use subprocess, but for now
# this is better than the alternative of reading in the previous
# time series.
# We have updated this with the user of subprocess, but I'm leaving
# it in for now since it seems quite robust, but it would certainly
# be a slight optimistation to avoid doing this.
model_dir = os.path.dirname(self.model_exec)
results_file_prefix = os.path.join(model_dir, "model")
results_file = results_file_prefix + "_RHS.dat"
if os.path.exists(results_file):
# I'm not sure about this try-except block, I'm trying to
# overcome what appears to be a bug in sbsi-numerics which creates
# these weird files with nothing in them and setuid's with ????
try:
os.remove(results_file)
except OSError:
pass
# This could also be run without mpi.
mpirun_command = [ "mpirun",
self.model_exec,
"model_name", # Could get model name from xml file
str(configuration.stop_time),
str(configuration.start_time),
str(configuration.max_times),
str(configuration.interval),
str(configuration.out_interval),
str(configuration.atol),
str(configuration.reltol),
results_file_prefix,
]
if self.param_filename:
mpirun_command.append(self.param_filename)
mpi_returncode = run_command(mpirun_command)
# So we check if the results file actually exists and if
# not we assume it failed. Also now I can actually check
# the return code
if not os.path.exists(results_file) or mpi_returncode != 0:
message = "Model solving failed"
logging.warning(message)
raise SolverError(message)
logging.debug("stop-time == " + str(configuration.stop_time))
logging.debug("start-time == " + str(configuration.start_time))
logging.debug("max-times == " + str(configuration.max_times))
logging.debug("interval == " + str(configuration.interval))
logging.debug("out-interval == " + str(configuration.out_interval))
logging.debug("atol == " + str(configuration.atol))
logging.debug("reltol == " + str(configuration.reltol))
# We should remove the parameter overrides file here in case
# we wish to simply solve the model on its own later.
# This is actually solved because we have updated the solver file
# such that it doesn't simply look to see if UserModel/param_overrides
# file is there, but instead demands that it is specified on the
# command-line if one is to be used.
# if os.path.exists(self.param_filename):
# os.remove(self.param_filename)
csv_file = open(results_file, "r")
timecourse = timeseries.parse_csv(csv_file, "\t")
csv_file.close()
return timecourse
