def __call__(self, population, num_generations, num_evaluations, args):
if self.progress is None:
self.max_evaluations = args.get('max_evaluations', 50000)
self.progress = ProgressBar(maxval=self.max_evaluations,
widgets=["Running Optimization", Bar(), Percentage()])
self.progress.start()
if num_evaluations % args.get('n', 1) == 0:
if num_evaluations > self.max_evaluations:
self.progress.update(self.max_evaluations)
else:
self.progress.update(num_evaluations)
class ProgressObserver(object):
"""
Progress bar to in command line. It keeps track of the progress during heuristic optimization.
"""
__name__ = "Progress Observer"
def __init__(self):
self.progress = None
def __call__(self, population, num_generations, num_evaluations, args):
if self.progress is None:
self.max_evaluations = args.get('max_evaluations', 50000)
self.progress = ProgressBar(maxval=self.max_evaluations,
widgets=["Running Optimization", Bar(), Percentage()])
self.progress.start()
if num_evaluations % args.get('n', 1) == 0:
if num_evaluations > self.max_evaluations:
self.progress.update(self.max_evaluations)
else:
self.progress.update(num_evaluations)
def reset(self):
self.progress = None
def end(self):
self.progress.finish()
class ProgressObserver(object):
"""
Progress bar to in command line. It keeps track of the progress during heuristic optimization.
"""
__name__ = "Progress Observer"
def __init__(self):
self.progress = None
def __call__(self, population, num_generations, num_evaluations, args):
if self.progress is None:
self.max_evaluations = args.get('max_evaluations', 50000)
self.progress = ProgressBar(maxval=self.max_evaluations,
widgets=["Running Optimization", Bar(), Percentage()])
self.progress.start()
if num_evaluations % args.get('n', 1) == 0:
if num_evaluations > self.max_evaluations:
self.progress.update(self.max_evaluations)
else:
self.progress.update(num_evaluations)
def reset(self):
self.progress = None
def end(self):
self.progress.finish()
self.progress = None
def _process_solutions(self):
processed_solutions = DataFrame(columns=[
"reactions", "size", "fva_min", "fva_max", "target_flux",
"biomass_flux", "yield", "fitness"
])
if len(self._swaps) == 0:
logger.warn("No solutions found")
self._processed_solutions = processed_solutions
else:
progress = ProgressBar(
maxval=len(self._swaps),
widgets=["Processing solutions: ",
Bar(), Percentage()])
for i, solution in progress(enumerate(self._swaps)):
try:
processed_solutions.loc[
i] = process_reaction_swap_solution(
self._model, solution[0], self._simulation_method,
self._simulation_kwargs, self._biomass,
self._target, self._substrate,
self._objective_function, self._swap_pairs)
except OptimizationError as e:
logger.error(e)
processed_solutions.loc[i] = [
numpy.nan for _ in processed_solutions.columns
]
self._processed_solutions = processed_solutions
def _process_knockouts(self):
progress = ProgressBar(
maxval=len(self._knockouts),
widgets=["Processing solutions: ",
Bar(), Percentage()])
self._processed_knockouts = DataFrame(columns=[
"reactions", "size", self._target, "biomass", "fva_min", "fva_max"
])
for i, knockouts in progress(enumerate(self._knockouts)):
try:
with self._model:
[
self._model.reactions.get_by_id(ko).knock_out()
for ko in knockouts
]
fva = flux_variability_analysis(self._model,
fraction_of_optimum=0.99,
reactions=[self.target])
self._processed_knockouts.loc[i] = [
knockouts,
len(knockouts), self.production[i], self.biomass[i],
fva.lower_bound(self.target),
fva.upper_bound(self.target)
]
except OptimizationError:
self._processed_knockouts.loc[i] = [
numpy.nan for _ in self._processed_knockouts.columns
]
def _process_message(self, message):
i = message['index']
if i not in self.progress_bar:
label = "Island %i" % (i + 1)
self.progress_bar[i] = ProgressBar(maxval=message['max_evaluations'],
widgets=[label, Bar(), Percentage()])
self.progress_bar[message['index']].start()
self.progress_bar[message['index']].set(message['progress'])
def __call__(self, population, num_generations, num_evaluations, args):
if self.progress is None:
self.max_evaluations = args.get('max_evaluations', 50000)
self.progress = ProgressBar(maxval=self.max_evaluations,
widgets=["Running Optimization", Bar(), Percentage()])
self.progress.start()
if num_evaluations % args.get('n', 1) == 0:
if num_evaluations > self.max_evaluations:
self.progress.update(self.max_evaluations)
else:
self.progress.update(num_evaluations)
def _process_message(self, message):
i = message['index']
if i not in self.progress_bar:
print("")
label = "Island %i: " % (i + 1)
pos = abs(len(self.clients) - i)
writer = self.TerminalWriter((self.terminal.height or 1) - pos, self.terminal)
self.progress_bar[i] = ProgressBar(maxval=message['max_evaluations'],
widgets=[label, Bar(), Percentage()],
fd=writer)
self.progress_bar[i].start()
self.progress_bar[i].update(message['num_evaluations'])