def test_one_variable_parallel(self):
ppp = phenotypic_phase_plane(self.model,
['EX_o2_LPAREN_e_RPAREN_'],
view=MultiprocessingView())
assert_dataframes_equal(ppp, REFERENCE_PPP_o2_EcoliCore)
ppp = phenotypic_phase_plane(self.model,
'EX_o2_LPAREN_e_RPAREN_',
view=MultiprocessingView())
assert_dataframes_equal(ppp, REFERENCE_PPP_o2_EcoliCore)
def test_one_variable_sequential(self):
ppp = phenotypic_phase_plane(self.model,
['EX_o2_LPAREN_e_RPAREN_'],
view=SequentialView())
assert_dataframes_equal(ppp, REFERENCE_PPP_o2_EcoliCore)
ppp = phenotypic_phase_plane(self.model,
'EX_o2_LPAREN_e_RPAREN_',
view=SequentialView())
assert_dataframes_equal(ppp, REFERENCE_PPP_o2_EcoliCore)
def test_one_variable_sequential_yield(self, core_model):
ppp = phenotypic_phase_plane(core_model, ['EX_o2_LPAREN_e_RPAREN_'],
view=SequentialView())
assert_data_frames_equal(ppp,
REFERENCE_PPP_o2_EcoliCore,
sort_by=['EX_o2_LPAREN_e_RPAREN_'])
ppp = phenotypic_phase_plane(core_model,
'EX_o2_LPAREN_e_RPAREN_',
view=SequentialView())
assert_data_frames_equal(ppp,
REFERENCE_PPP_o2_EcoliCore,
sort_by=['EX_o2_LPAREN_e_RPAREN_'])
def plot(self,
plotter,
index=0,
grid=None,
width=None,
height=None,
title=None,
palette=None,
**kwargs):
wt_production = phenotypic_phase_plane(self._model,
objective=self._target,
variables=[self._biomass])
with self._model:
for ko in self.data_frame.loc[index, "reactions"]:
swap_cofactors(self._model.reactions.get_by_id(ko),
self._model, self._swap_pairs)
mt_production = phenotypic_phase_plane(self._model,
objective=self._target,
variables=[self._biomass])
if title is None:
title = "Production Envelope"
dataframe = DataFrame(columns=["ub", "lb", "value", "strain"])
for _, row in wt_production.iterrows():
_df = DataFrame([[
row['objective_upper_bound'], row['objective_lower_bound'],
row[self._biomass.id], "WT"
]],
columns=dataframe.columns)
dataframe = dataframe.append(_df)
for _, row in mt_production.iterrows():
_df = DataFrame([[
row['objective_upper_bound'], row['objective_lower_bound'],
row[self._biomass.id], "MT"
]],
columns=dataframe.columns)
dataframe = dataframe.append(_df)
plot = plotter.production_envelope(dataframe,
grid=grid,
width=width,
height=height,
title=title,
x_axis_label=self._biomass.id,
y_axis_label=self._target.id,
palette=palette)
plotter.display(plot)
def _init_search_grid(self, surface_only=False, improvements_only=True):
"""Initialize the grid of points to be scanned within the production envelope."""
self.envelope = phenotypic_phase_plane(
self.design_space_model, self.variables, objective=self.objective, points=self.points)
intervals = self.envelope[['objective_lower_bound', 'objective_upper_bound']].copy()
intervals['objective_lower_bound'] = float_floor(intervals.objective_lower_bound, ndecimals)
intervals['objective_upper_bound'] = float_ceil(intervals.objective_upper_bound, ndecimals)
max_distance = 0.
max_interval = None
for i, (lb, ub) in intervals.iterrows():
distance = abs(ub - lb)
if distance > max_distance:
max_distance = distance
max_interval = (lb, ub)
step_size = (max_interval[1] - max_interval[0]) / (self.points - 1)
grid = list()
minimal_reference_production = self.reference_flux_ranges['lower_bound'][self.objective]
for i, row in self.envelope.iterrows():
variables = row[self.variables]
lb = row.objective_lower_bound
if improvements_only:
lb = max(lb, minimal_reference_production) + step_size
ub = row.objective_upper_bound
if not surface_only:
coordinate = lb
while coordinate < ub:
grid.append(list(variables.values) + [coordinate])
coordinate += step_size
if improvements_only and ub <= minimal_reference_production:
continue
else:
grid.append(list(variables.values) + [ub])
columns = self.variables + [self.objective]
self.grid = DataFrame(grid, columns=columns)
def _init_search_grid(self, surface_only=False, improvements_only=True):
"""Initialize the grid of points to be scanned within the production envelope."""
self.envelope = phenotypic_phase_plane(
self.design_space_model, self.variables, objective=self.objective, points=self.points)
intervals = self.envelope[['objective_lower_bound', 'objective_upper_bound']].copy()
intervals['objective_lower_bound'] = float_floor(intervals.objective_lower_bound, ndecimals)
intervals['objective_upper_bound'] = float_ceil(intervals.objective_upper_bound, ndecimals)
max_distance = 0.
max_interval = None
for i, (lb, ub) in intervals.iterrows():
distance = abs(ub - lb)
if distance > max_distance:
max_distance = distance
max_interval = (lb, ub)
step_size = (max_interval[1] - max_interval[0]) / (self.points - 1)
grid = list()
minimal_reference_production = self.reference_flux_ranges['lower_bound'][self.objective]
for i, row in self.envelope.iterrows():
variables = row[self.variables]
lb = row.objective_lower_bound
if improvements_only:
lb = max(lb, minimal_reference_production) + step_size
ub = row.objective_upper_bound
if not surface_only:
coordinate = lb
while coordinate < ub:
grid.append(list(variables.values) + [coordinate])
coordinate += step_size
if improvements_only and ub <= minimal_reference_production:
continue
else:
grid.append(list(variables.values) + [ub])
columns = self.variables + [self.objective]
self.grid = DataFrame(grid, columns=columns)
def test_two_variables_sequential(self, core_model):
ppp2d = phenotypic_phase_plane(
core_model, ['EX_o2_LPAREN_e_RPAREN_', 'EX_glc_LPAREN_e_RPAREN_'],
view=SequentialView())
assert_data_frames_equal(
ppp2d,
REFERENCE_PPP_o2_glc_EcoliCore,
sort_by=['EX_o2_LPAREN_e_RPAREN_', 'EX_glc_LPAREN_e_RPAREN_'])
def test_ppp_plotly(model):
"""Test if at least it doesn't raise an exception."""
production_envelope = phenotypic_phase_plane(
model,
variables=[
model.reactions.Biomass_Ecoli_core_N_lp_w_fsh_GAM_rp__Nmet2
],
objective=model.metabolites.succ_e,
)
# pass a grid argument so that it doesn't open a browser tab
production_envelope.plot(plotter, height=400, grid=[])
def plot(self, index=0, grid=None, width=None, height=None, title=None, palette=None, **kwargs):
wt_production = phenotypic_phase_plane(self._model, objective=self._target, variables=[self._biomass.id])
with TimeMachine() as tm:
for ko in self.data_frame.loc[index, "reactions"]:
self._model.reactions.get_by_id(ko).knock_out(tm)
mt_production = phenotypic_phase_plane(self._model, objective=self._target, variables=[self._biomass.id])
if title is None:
title = "Production Envelope"
dataframe = DataFrame(columns=["ub", "lb", "value", "strain"])
for _, row in wt_production.iterrows():
_df = DataFrame([[row['objective_upper_bound'], row['objective_lower_bound'], row[self._biomass.id], "WT"]],
columns=dataframe.columns)
dataframe = dataframe.append(_df)
for _, row in mt_production.iterrows():
_df = DataFrame([[row['objective_upper_bound'], row['objective_lower_bound'], row[self._biomass.id], "MT"]],
columns=dataframe.columns)
dataframe = dataframe.append(_df)
plot = plotter.production_envelope(dataframe, grid=grid, width=width, height=height, title=title,
x_axis_label=self._biomass.id, y_axis_label=self._target, palette=palette)
plotter.display(plot)
def test_one_variable_sequential_metabolite(self):
ppp = phenotypic_phase_plane(self.model, ['EX_o2_LPAREN_e_RPAREN_'], self.model.metabolites.o2_c, view=SequentialView())
assert_dataframes_equal(ppp, REFERENCE_PPP_o2_EcoliCore)
def test_two_variables_sequential(self):
ppp2d = phenotypic_phase_plane(self.model, ['EX_o2_LPAREN_e_RPAREN_', 'EX_glc_LPAREN_e_RPAREN_'],
view=SequentialView())
assert_dataframes_equal(ppp2d, REFERENCE_PPP_o2_glc_EcoliCore)
def test_two_variables_parallel(self):
ppp2d = phenotypic_phase_plane(self.model, ['EX_o2_LPAREN_e_RPAREN_', 'EX_glc_LPAREN_e_RPAREN_'],
view=MultiprocessingView())
assert_dataframes_equal(ppp2d, REFERENCE_PPP_o2_glc_EcoliCore)
def test_one_variable_sequential_metabolite(self, core_model):
ppp = phenotypic_phase_plane(core_model, ['EX_o2_LPAREN_e_RPAREN_'], core_model.metabolites.ac_c,
view=SequentialView())
assert_data_frames_equal(ppp, REFERENCE_PPP_o2_EcoliCore_ac, sort_by=['EX_o2_LPAREN_e_RPAREN_'])
def test_one_variable_parallel(self, core_model):
ppp = phenotypic_phase_plane(core_model, ['EX_o2_LPAREN_e_RPAREN_'], view=MultiprocessingView())
assert_data_frames_equal(ppp, REFERENCE_PPP_o2_EcoliCore, sort_by=['EX_o2_LPAREN_e_RPAREN_'])
ppp = phenotypic_phase_plane(core_model, 'EX_o2_LPAREN_e_RPAREN_', view=MultiprocessingView())
assert_data_frames_equal(ppp, REFERENCE_PPP_o2_EcoliCore, sort_by=['EX_o2_LPAREN_e_RPAREN_'])
def test_one_variable_sequential_metabolite(self):
ppp = phenotypic_phase_plane(self.model, ['EX_o2_LPAREN_e_RPAREN_'], self.model.metabolites.ac_c,
view=SequentialView())
assert_data_frames_equal(ppp, REFERENCE_PPP_o2_EcoliCore_ac, sort_by=['EX_o2_LPAREN_e_RPAREN_'])
def test_two_variables_parallel(self):
ppp2d = phenotypic_phase_plane(self.model, ['EX_o2_LPAREN_e_RPAREN_', 'EX_glc_LPAREN_e_RPAREN_'],
view=MultiprocessingView())
assert_data_frames_equal(ppp2d, REFERENCE_PPP_o2_glc_EcoliCore,
sort_by=['EX_o2_LPAREN_e_RPAREN_', 'EX_glc_LPAREN_e_RPAREN_'])
