def plot_predicted(self, xlab="fitted", ylab="actual"):
"""A plot of predicted values vs actual values.
"""
fig, ax = R.plot(self.fitted_values,
self.residuals + self.fitted_values,
xlab=xlab,
ylab=ylab)
return fig, ax
def plot_residual(self,
hexbin_threshold=1e+5,
xlab="fitted",
ylab="residual"):
"""A plot of the residuals vs the predicted values.
"""
fig, ax = R.plot(self.fitted_values,
self.residuals,
hexbin_threshold=hexbin_threshold,
xlab=xlab,
ylab=ylab)
if len(self.residuals) > hexbin_threshold:
abs_resid = np.abs(self.residuals)
n = len(abs_resid) - 100
top_resids = np.argpartition(abs_resid, n)[n:]
ax.scatter(self.fitted_values[top_resids],
self.residuals[top_resids],
s=5,
color="yellow")
ax.axhline(color="black", linewidth=.5)
return fig, ax