def plot_comparison(self, file=None):
"""
Creates a plot with a comparison of simulation results
(fittest individual) vs. measured result.
:param file: string, path to the file. If ``None``, file not created.
:return: Axes
"""
simulated = self.get_sim_res()
measured = self.pop.ideal.copy()
return plots.plot_comparison(simulated, measured, file)
def validate(self, vp=None):
"""
Performs a simulation with estimated parameters
for the previously selected validation period. Other period
can be chosen with the `vp` argument. User chosen `vp` in this method
does not override the validation period chosen during instantiation
of this class.
Parameters
----------
vp: tuple or None
Validation period given as a tuple of start and stop time in
seconds.
Returns
-------
dict
Validation error, keys: 'tot', '<var1>', '<var2>', ...
pandas.DataFrame
Simulation result
"""
# Get estimates
est = self.final
est.index = [0] # Reset index (needed by model.set_param())
self.logger.info("Validation of parameters: {}".format(
str(est.iloc[0].to_dict())))
# Slice data
if vp is None:
start, stop = self.vp[0], self.vp[1]
else:
start, stop = vp[0], vp[1]
inp_slice = self.inp.loc[start:stop]
ideal_slice = self.ideal.loc[start:stop]
# Initialize IC parameters and add to known
if self.ic_param:
for par in self.ic_param:
ic = ideal_slice[self.ic_param[par]].iloc[0]
self.known[par] = ic
# Initialize model
model = Model(self.fmu_path)
model.set_input(inp_slice)
model.set_param(est)
model.set_param(self.known)
model.set_outputs(list(self.ideal.columns))
# Simulate and get error
try:
result = model.simulate()
except Exception as e:
msg = "Problem found inside FMU. Did you set all parameters?"
self.logger.error(str(e))
self.logger.error(msg)
raise e
err = modestpy.estim.error.calc_err(result, ideal_slice)
# Create validation plot
ax = plot_comparison(result, ideal_slice, f=None)
fig = figures.get_figure(ax)
fig.set_size_inches(Estimation.FIG_SIZE)
fig.savefig(os.path.join(self.workdir, "validation.png"),
dpi=Estimation.FIG_DPI)
# Remove temp dirs
self._clean()
# Return
return err, result
def plot_comparison(self, file=None):
return plots.plot_comparison(self.res, self.ideal, file)