def run_mother_machine(time=5, out_dir='out'):
mother_machine_config = get_mother_machine_config()
experiment = mother_machine_experiment(mother_machine_config)
# simulate
settings = {
'emit_step': 5,
'total_time': time,
'return_raw_data': True}
data = simulate_experiment(experiment, settings)
# agents plot
plot_settings = {
'agents_key': 'agents'}
plot_agents_multigen(data, plot_settings, out_dir)
# snapshot plot
multibody_config = mother_machine_config['environment']['multibody']
agents = {time: time_data['agents'] for time, time_data in data.items()}
fields = {time: time_data['fields'] for time, time_data in data.items()}
snapshot_data = {
'agents': agents,
'fields': fields,
'config': multibody_config}
plot_config = {
'out_dir': out_dir,
'filename': 'snapshots'}
plot_snapshots(snapshot_data, plot_config)
def inclusion_plots_suite(data=None, out_dir=EXPERIMENT_OUT_DIR):
n_snapshots = 5
tagged_molecules = [('inclusion_body', ), (
'front',
'aggregate',
), (
'back',
'aggregate',
)]
# multigen plot
plot_settings = {}
plot_agents_multigen(data, plot_settings, out_dir)
# extract data for snapshots
bounds = LATTICE_CONFIG['multibody']['bounds']
agents, fields = format_snapshot_data(data)
# snapshots plot
plot_snapshots(bounds=bounds,
agents=agents,
fields=fields,
n_snapshots=n_snapshots,
out_dir=out_dir,
filename='inclusion_snapshots')
# tags plot
plot_tags(
data=data,
bounds=bounds,
tagged_molecules=tagged_molecules,
n_snapshots=n_snapshots,
convert_to_concs=False,
out_dir=out_dir,
)
def main():
if not os.path.exists(OUT_DIR):
os.makedirs(OUT_DIR)
data, experiment_config = run_experiment(start_locations=[[0.3, 0.3],
[0.5, 0.5]], )
# extract data
multibody_config = experiment_config['environment']['multibody']
agents = {time: time_data['agents'] for time, time_data in data.items()}
fields = {time: time_data['fields'] for time, time_data in data.items()}
# agents plot
agents_settings = {'agents_key': 'agents'}
plot_agents_multigen(data, agents_settings, OUT_DIR, 'agents')
# snapshot plot
snapshot_data = {
'agents': agents,
'fields': fields,
'config': multibody_config,
}
snapshot_config = {
'out_dir': OUT_DIR,
'filename': 'agents_snapshots',
}
plot_snapshots(snapshot_data, snapshot_config)
# Colony Metrics Plot
embedded_ts = timeseries_from_data(data)
colony_metrics_ts = embedded_ts['colony_global']
colony_metrics_ts['time'] = embedded_ts['time']
path_ts = path_timeseries_from_embedded_timeseries(colony_metrics_ts)
fig = plot_colony_metrics(path_ts)
fig.savefig(os.path.join(OUT_DIR, 'colonies'))
def plot_timeseries(data, out_dir, settings):
plot_settings = {
'agents_key': 'agents',
'title_size': 10,
'tick_label_size': 10,
}
plot_settings.update(settings)
plot_agents_multigen(data, plot_settings, out_dir)
def run_mother_machine(time=10, out_dir='out'):
config = get_mother_machine_config()
# configure the experiment
agent_ids = config.get('agent_ids', ['0'])
# get the environment composite
environment = Lattice(config.get('environment', {}))
composite = environment.generate({})
# add the agents
growth_division = GrowDivide(config.get('growth_division', {}))
for agent_id in agent_ids:
agent = growth_division.generate({'agent_id': agent_id})
composite.merge(composite=agent, path=('agents', agent_id))
experiment = Engine(
**{
'processes': composite['processes'],
'topology': composite['topology'],
'initial_state': config.get('initial_state', {}),
'progress_bar': True,
})
# simulate
settings = {'total_time': time, 'return_raw_data': True}
data = simulate_experiment(experiment, settings)
# agents plot
plot_settings = {'agents_key': 'agents'}
plot_agents_multigen(data, plot_settings, out_dir)
# snapshot plot
agents, fields = format_snapshot_data(data)
bounds = config['environment']['multibody']['bounds']
plot_snapshots(bounds,
agents=agents,
fields=fields,
n_snapshots=4,
out_dir=out_dir,
filename=f"mother_machine")
# make snapshot video
make_video(
data,
bounds,
plot_type='fields',
step=100,
out_dir=out_dir,
filename=f"mother_machine",
)
def plot_experiment_output(
data,
plot_settings={},
out_dir='out',
):
environment_config = plot_settings['environment_config']
agent_type = plot_settings.get('agent_type', 'agent')
plot_types = plot_settings['plot_types']
# extract data
multibody_config = environment_config['config']['multibody']
agents = {time: time_data['agents'] for time, time_data in data.items()}
fields = {time: time_data['fields'] for time, time_data in data.items()}
# pass to plots
if 'agents' in plot_types:
plot_settings = plot_types['agents']
plot_settings['agents_key'] = 'agents'
plot_agents_multigen(data, plot_settings, out_dir, agent_type)
if 'snapshots' in plot_types:
plot_config = plot_types['snapshots']
field_ids = plot_types['snapshots']['fields']
plot_fields = {
time: {
field_id: field_instance[field_id]
for field_id in field_ids}
for time, field_instance in fields.items()}
data = {
'agents': agents,
'fields': plot_fields,
'config': multibody_config}
plot_config.update({
'out_dir': out_dir,
'filename': agent_type + '_snapshots',
})
plot_snapshots(data, plot_config)
if 'tags' in plot_types:
plot_config = plot_types['tags']
data = {
'agents': agents,
'config': multibody_config}
plot_config.update({
'out_dir': out_dir,
'filename': agent_type + '_tags',
})
plot_tags(data, plot_config)
def plot_multigen(output,
variables=None,
out_dir=None,
filename=None,
**kwargs):
if filename and not out_dir:
out_dir = 'out'
plot_settings = {
'include_paths': variables,
'skip_paths': [
('internal_counts', ),
('cobra_external', ),
],
'remove_zeros': False,
'column_width': 8,
'row_height': 1.5,
'title_on_y_axis': True,
'stack_column': True,
'tick_label_size': 10,
'title_size': 10,
**kwargs
}
fig = plot_agents_multigen(output, plot_settings, out_dir, filename)
return fig
def plot_timeseries(t_index):
time_indices = np.array(range(0, t_index + 1))
current_data = {
time_vec[index]: agent_data[time_vec[index]]
for index in time_indices
}
fig = plot_agents_multigen(current_data, dict(plot_settings, **kwargs))
return fig
def main():
out_dir = os.path.join(COMPOSITE_OUT_DIR, NAME)
if not os.path.exists(out_dir):
os.makedirs(out_dir)
grow_divide = False
grow_divide_exchange = True
if grow_divide:
output = test_grow_divide(2000)
plot_settings = {}
plot_agents_multigen(output, plot_settings, out_dir, 'grow_divide')
if grow_divide_exchange:
output = test_grow_divide_exchange(2000)
plot_settings = {}
plot_agents_multigen(output, plot_settings, out_dir,
'grow_divide_exchange')
def inclusion_plots_suite(data=None, out_dir=EXPERIMENT_OUT_DIR):
n_snapshots = 8
tagged_molecules = [
('inclusion_body', ),
(
'front',
'aggregate',
),
(
'back',
'aggregate',
),
]
# multigen plot
plot_settings = {}
plot_agents_multigen(data, plot_settings, out_dir)
# extract data for snapshots
multibody_config = lattice_config['multibody']
agents = {time: time_data['agents'] for time, time_data in data.items()}
# snapshots plot
plot_data = {
'agents': agents,
'config': multibody_config,
}
plot_config = {'n_snapshots': n_snapshots, 'out_dir': out_dir}
plot_snapshots(plot_data, plot_config)
# tags plot
plot_config = {
'tagged_molecules': tagged_molecules,
'n_snapshots': n_snapshots,
'convert_to_concs': False,
'out_dir': out_dir
}
plot_tags(plot_data, plot_config)
def plot_multigen_fig(output, agent_colors=None, out_dir='out'):
""" plot multi-generational timeseries over the entire simulation """
plot_config = copy.deepcopy(MULTIGEN_PLOT_CONFIG)
plot_config['agent_colors'] = agent_colors
# plot multigen
multigen_fig = plot_agents_multigen(output, plot_config)
# add colony mass to multigen_fig
colony_mass, time_vec = calculate_colony_mass(output)
# convert to hours
time_vec = [time / 3600 for time in time_vec]
# get mass axis to replace with colony mass
allaxes = multigen_fig.get_axes()
ax = None
for axis in allaxes:
if axis.get_title() == 'boundary \nmass':
ax = axis
# replace with colony mass
ax.clear()
set_axes(ax, True, sci_notation=MULTIGEN_PLOT_CONFIG['sci_notation'])
ax.plot(time_vec,
colony_mass,
linewidth=MULTIGEN_PLOT_CONFIG['linewidth'],
color='darkslategray')
ax.set_xlim([time_vec[0], time_vec[-1]])
ax.set_title('total colony mass (fg)',
rotation=0,
fontsize=MULTIGEN_PLOT_CONFIG['title_size'])
ax.set_xlabel('time (hr)')
ax.spines['bottom'].set_position(('axes', -0.2))
# save
save_fig_to_dir(multigen_fig, 'spatial_multigen.pdf', out_dir)
def run_compartment(out_dir='out'):
data = test_inclusion_body(total_time=4000)
plot_settings = {}
plot_agents_multigen(data, plot_settings, out_dir)
if not os.path.exists(out_dir):
os.makedirs(out_dir)
agent_id = '0'
compartment = GrowthDivision({'agent_id': agent_id})
# settings for simulation and plot
settings = {
'environment': {
'volume': 1e-6 * units.L, # L
'ports': {
'fields': ('fields', ),
'external': (
'boundary',
'external',
),
'global': ('boundary', ),
'dimensions': ('dimensions', ),
},
},
'outer_path':
('agents', agent_id), # TODO -- need to set the agent_id through here?
'return_raw_data': True,
'timestep': 1,
'total_time': 500
}
output_data = simulate_compartment_in_experiment(compartment, settings)
plot_settings = {}
plot_agents_multigen(output_data, plot_settings, out_dir)
