def plot_state_components(self,
burn: int = None,
time: np.array = None,
same_scale: bool = True,
ylim: tuple = None,
fig=None,
components=None,
**kwargs):
"""
Plot the contribution of each state model.
Args:
burn:
TODO: Finish this. Use fig.add_gridspec instead of plt.subplots, so
that each figure can subgrid if needed.
See https://matplotlib.org/3.1.1/tutorials/intermediate/gridspec.html
"""
if fig is None:
fig = plt.figure(constrained_layout=True)
if components is None:
state_models = self._state_models
else:
state_models = self._state_models[components]
if burn is None:
burn = self.suggest_burn()
elif burn < 0:
burn = 0
if time is None:
time = self.original_series.index
if same_scale is True and ylim is None:
ylim = _find_ylim(state_models, burn)
nr, nc = R.plot_grid_shape(len(state_models))
outer_grid = fig.add_gridspec(nr, nc)
plot_index = 0
for i in range(nr):
for j in range(nc):
if plot_index < len(state_models):
state_model = state_models[plot_index]
state_model.plot_state_contribution(
fig=fig,
gridspec=outer_grid[i, j],
time=time,
burn=burn,
ylim=ylim,
**kwargs)
plot_index += 1
def plot_coefficients(self,
subset=None,
fig=None,
ylim=None,
same_scale: bool = True,
burn: int = None,
**kwargs):
"""
Plot some or all of the model coefficients on the same figure.
Args:
subset: Identifies the subset of coefficients to be plotted. 'None'
means plot all coefficients. Otherwise 'subset' must be an object
that can be used to index a numpy array, such as a vector of
integers or booleans.
fig: The plt.Figure object on which to draw the plots. If None a new
Figure will be created and drawn upon function exit.
ylim: A pair of numbers giving the lower and upper limits of the Y
axes. If specified then all plots will be drawn with the same
values.
same_scale: This is ignored if ylim is specified. Otherwise, True
indicates that the Y axes should all be drawn on the same scale.
False means each coefficient is plotted on its own scale.
kw_args: Additional keyword arguments are ignored.
burn: The number of MCMC iteration to discard as burn-in.
Returns:
The Figure object on which the plots are drawn.
"""
if subset is None:
coef = self._beta_draws
else:
coef = self._beta_draws[:, subset, :]
if burn is None:
burn = self.suggest_burn()
if burn > 0:
coef = coef[burn:, :, :]
call_show = fig is None
if fig is None:
fig = plt.figure()
nr, nc = R.plot_grid_shape(coef.shape[1])
sharey = same_scale or (ylim is not None)
ax = fig.subplots(nr, nc, sharex=True, sharey=sharey)
index = 0
if same_scale and (ylim is None):
ylim = R.data_range(self._beta_draws)
for col in range(nc):
for row in range(nr):
if index < coef.shape[1]:
self.plot_single_coefficient(coef[:, index, :],
ax=ax[row][col],
ylim=ylim)
index += 1
if call_show:
fig.set_tight_layout(True)
fig.show()
return fig
