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dataframe = pandas.DataFrame(columns=["lb", "ub", "strain", "reaction"])
for reaction_id, row in wt_fva_res.iterrows():
_df = pandas.DataFrame([[row['lower_bound'], row['upper_bound'], "WT", reaction_id]],
columns=dataframe.columns)
dataframe = dataframe.append(_df)
for reaction_id, row in strain_fva_res.iterrows():
_df = pandas.DataFrame([[row['lower_bound'], row['upper_bound'], "Strain %i" % index, reaction_id]],
columns=dataframe.columns)
dataframe = dataframe.append(_df)
plot = plotter.flux_variability_analysis(dataframe, grid=grid, width=width, height=height,
title=title, x_axis_label="Reactions", y_axis_label="Flux limits",
palette=palette)
plotter.display(plot)
upper, lower, description, unit = possible_estimates[estimate]
if title is None:
title = "Phenotypic Phase Plane ({})".format(description)
if len(self.variable_ids) == 1:
variable = self.variable_ids[0]
y_axis_label = self._axis_label(self.objective, self.nice_objective_id, unit)
x_axis_label = self._axis_label(variable, self.nice_variable_ids[0], '[mmol gDW^-1 h^-1]')
dataframe = pandas.DataFrame(columns=["ub", "lb", "value", "strain"])
for _, row in self.iterrows():
_df = pandas.DataFrame([[row[upper], row[lower], row[variable], "WT"]],
columns=dataframe.columns)
dataframe = dataframe.append(_df)
plot = plotter.production_envelope(dataframe, grid=grid, width=width, height=height,
title=title, y_axis_label=y_axis_label, x_axis_label=x_axis_label,
palette=palette, points=points, points_colors=points_colors)
elif len(self.variable_ids) == 2:
var_1 = self.variable_ids[0]
var_2 = self.variable_ids[1]
x_axis_label = self._axis_label(var_1, self.nice_variable_ids[0], '[mmol gDW^-1 h^-1]')
y_axis_label = self._axis_label(var_2, self.nice_variable_ids[1], '[mmol gDW^-1 h^-1]')
z_axis_label = self._axis_label(self.objective, self.nice_objective_id, unit)
dataframe = pandas.DataFrame(columns=["ub", "lb", "value1", "value2", "strain"])
for _, row in self.iterrows():
_df = pandas.DataFrame([[row[upper], row[lower],
row[var_1], row[var_2], "WT"]],
columns=dataframe.columns)
dataframe = dataframe.append(_df)
title = "Compare WT solution %i" % index if title is None else title
wt_fva_res = self.reference_fva.loc[variables]
strain_fva_res = self.nth_panel(index).loc[variables]
dataframe = pandas.DataFrame(columns=["lb", "ub", "strain", "reaction"])
for reaction_id, row in wt_fva_res.iterrows():
_df = pandas.DataFrame([[row['lower_bound'], row['upper_bound'], "WT", reaction_id]],
columns=dataframe.columns)
dataframe = dataframe.append(_df)
for reaction_id, row in strain_fva_res.iterrows():
_df = pandas.DataFrame([[row['lower_bound'], row['upper_bound'], "Strain %i" % index, reaction_id]],
columns=dataframe.columns)
dataframe = dataframe.append(_df)
plot = plotter.flux_variability_analysis(dataframe, grid=grid, width=width, height=height,
title=title, x_axis_label="Reactions", y_axis_label="Flux limits",
palette=palette)
plotter.display(plot)
def plot(self, index=None, grid=None, width=None, height=None, title=None, palette=None, **kwargs):
if index is None:
index = self.data_frame.index[0:10]
fva_result = self.data_frame.loc[index]
if title is None:
title = "Flux Variability Analysis"
dataframe = pandas.DataFrame(columns=["lb", "ub", "strain", "reaction"])
for reaction_id, row in fva_result.iterrows():
_df = pandas.DataFrame([[row['lower_bound'], row['upper_bound'], "WT", reaction_id]],
columns=dataframe.columns)
dataframe = dataframe.append(_df)
plot = plotter.flux_variability_analysis(dataframe, grid=grid, width=width, height=height,
title=title, y_axis_label="Reactions", x_axis_label="Flux limits",
palette=palette)
if grid is None:
plotter.display(plot)
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)
_df = pandas.DataFrame([[row[upper], row[lower],
row[var_1], row[var_2], "WT"]],
columns=dataframe.columns)
dataframe = dataframe.append(_df)
plot = plotter.production_envelope_3d(dataframe, grid=grid, width=width, height=height,
title=title, y_axis_label=y_axis_label, x_axis_label=x_axis_label,
z_axis_label=z_axis_label, palette=palette, points=points,
points_colors=points_colors)
else:
notice("Multi-dimensional plotting is not supported")
return
if grid is None:
plotter.display(plot)
def plot_production_envelopes(self, model, objective=None, title=None):
rows = int(ceil(len(self.pathways) / 2.0))
title = "Production envelops for %s" % self.pathways[0].product.name if title is None else title
grid = plotter.grid(n_rows=rows, title=title)
with grid:
for i, pathway in enumerate(self.pathways):
ppp = pathway.production_envelope(model, objective=objective)
ppp.plot(grid=grid, width=450, title="Pathway %i" % (i + 1))
def plot(self, grid=None, width=None, height=None, title=None, *args, **kwargs):
if title is None:
title = "FSEOF fluxes"
plot = plotter.line(self.data_frame, grid=grid, width=width, height=height, title=title, **kwargs)
if grid is None:
plotter.display(plot)
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)
index = self.data_frame.index[0:10]
fva_result = self.data_frame.loc[index]
if title is None:
title = "Flux Variability Analysis"
dataframe = pandas.DataFrame(columns=["lb", "ub", "strain", "reaction"])
for reaction_id, row in fva_result.iterrows():
_df = pandas.DataFrame([[row['lower_bound'], row['upper_bound'], "WT", reaction_id]],
columns=dataframe.columns)
dataframe = dataframe.append(_df)
plot = plotter.flux_variability_analysis(dataframe, grid=grid, width=width, height=height,
title=title, y_axis_label="Reactions", x_axis_label="Flux limits",
palette=palette)
if grid is None:
plotter.display(plot)