def plot_inclusion(self,
burn=None,
inclusion_threshold=0,
unit_scale=True,
number_of_variables=None,
ax=None,
**kwargs):
"""A barplot showing the marginal inclusion probability of each variable.
"""
inc = self.inclusion_probs(burn=burn)
pos = self.coefficient_positive_probability(burn=burn)
colors = np.array([str(x) for x in pos])
index = np.argsort(inc.values)[::-1]
if number_of_variables is None:
number_of_variables = np.sum(inc >= inclusion_threshold)
inc = inc[index[:number_of_variables]]
pos = pos[index[:number_of_variables]]
colors = colors[index[:number_of_variables]]
foo = R.barplot(inc,
ax=ax,
color=colors[::-1],
linewidth=.25,
edgecolor="black",
xlab="Marginal Inclusion Probability",
ylab="Variable",
**kwargs)
return foo
def plot_inclusion_probs(coefficients,
burn,
xnames,
inclusion_threshold=0,
unit_scale=True,
number_of_variables=None,
ax=None,
**kwargs):
"""
"""
coef = coefficients[burn:, :]
inc = compute_inclusion_probabilities(coef)
pos = coefficient_positive_probability(coef)
colors = np.array([str(x) for x in pos])
index = np.argsort(inc.values)[::-1]
if number_of_variables is None:
number_of_variables = np.sum(inc >= inclusion_threshold)
inc = inc[index[:number_of_variables]]
pos = pos[index[:number_of_variables]]
colors = colors[index[:number_of_variables]]
ans = R.barplot(inc,
ax=ax,
color=colors[::-1],
linewidth=.25,
edgecolor="black",
xlab="Marginal Inclusion Probability",
ylab="Variable",
**kwargs)
return ans
