def s_ith_nn_d_dist(self, i, xlab=None, ylab=None, title=None,
figsize=(5, 5), ax=None, **kwargs):
"""
Plot the distances of the i-th nearest neighbor of all samples.
"""
x = self.s_ith_nn_d(i)
return hist_dens_plot(x, title=title, xlab=xlab, ylab=ylab,
figsize=figsize, ax=ax, **kwargs)
def f_ind_dist(self,
f_ind,
sample_filter=None,
xlab=None,
ylab=None,
title=None,
figsize=(5, 5),
ax=None,
**kwargs):
xf = self.f_ind_x_vec(f_ind, sample_filter)
return hist_dens_plot(xf,
title=title,
xlab=xlab,
ylab=ylab,
figsize=figsize,
ax=ax,
**kwargs)
def s_ind_dist(self,
s_ind,
feature_filter=None,
xlab=None,
ylab=None,
title=None,
figsize=(5, 5),
ax=None,
**kwargs):
xf = self.s_ind_x_vec(s_ind, feature_filter)
return hist_dens_plot(xf,
title=title,
xlab=xlab,
ylab=ylab,
figsize=figsize,
ax=ax,
**kwargs)
def f_cv_dist(self,
f_cv_filter=None,
xlab=None,
ylab=None,
title=None,
figsize=(5, 5),
ax=None,
**kwargs):
"""
Plot the distribution of the feature sum of each sample, (n_samples,).
"""
xf = self.f_cv(f_cv_filter)
return hist_dens_plot(xf,
title=title,
xlab=xlab,
ylab=ylab,
figsize=figsize,
ax=ax,
**kwargs)
def s_sum_dist(self,
s_sum_filter=None,
xlab=None,
ylab=None,
title=None,
figsize=(5, 5),
ax=None,
**kwargs):
"""
Plot the distribution of the sample sum of each feature, (n_features,).
"""
xf = self.s_sum(s_sum_filter)
return hist_dens_plot(xf,
title=title,
xlab=xlab,
ylab=ylab,
figsize=figsize,
ax=ax,
**kwargs)
def s_n_above_threshold_dist(self,
closed_threshold,
xlab=None,
ylab=None,
title=None,
figsize=(5, 5),
ax=None,
**kwargs):
"""
Plot the distribution of the the number of above threshold samples
of each feature, (n_features,).
"""
xf = self.s_n_above_threshold(closed_threshold)
return hist_dens_plot(xf,
title=title,
xlab=xlab,
ylab=ylab,
figsize=figsize,
ax=ax,
**kwargs)
