commit
3541f559e3
|
@ -5,6 +5,7 @@ import numpy as np
|
|||
from matplotlib import cm
|
||||
from scipy.stats import ttest_ind_from_stats
|
||||
from matplotlib.ticker import ScalarFormatter
|
||||
import math
|
||||
|
||||
import quapy as qp
|
||||
|
||||
|
@ -272,9 +273,8 @@ def error_by_drift(method_names, true_prevs, estim_prevs, tr_prevs,
|
|||
if logscale:
|
||||
ax.set_yscale("log")
|
||||
ax.yaxis.set_major_formatter(ScalarFormatter())
|
||||
ax.yaxis.set_minor_formatter(ScalarFormatter())
|
||||
ax.yaxis.get_major_formatter().set_scientific(False)
|
||||
ax.yaxis.get_minor_formatter().set_scientific(False)
|
||||
ax.minorticks_off()
|
||||
|
||||
inds = np.digitize(tr_test_drifts, bins, right=True)
|
||||
|
||||
|
@ -306,13 +306,12 @@ def error_by_drift(method_names, true_prevs, estim_prevs, tr_prevs,
|
|||
|
||||
if show_density:
|
||||
ax2 = ax.twinx()
|
||||
densities = npoints/np.sum(npoints)
|
||||
ax2.bar([ind * binwidth-binwidth/2 for ind in range(len(bins))],
|
||||
max_y*npoints/np.max(npoints), alpha=0.15, color='g', width=binwidth, label='density')
|
||||
#ax2.set_ylabel("bar data")
|
||||
ax2.set_ylim(0,1)
|
||||
densities, alpha=0.15, color='g', width=binwidth, label='density')
|
||||
ax2.set_ylim(0,max(densities))
|
||||
ax2.spines['right'].set_color('g')
|
||||
ax2.tick_params(axis='y', colors='g')
|
||||
#ax2.yaxis.set_visible(False)
|
||||
|
||||
ax.set(xlabel=f'Distribution shift between training set and test sample',
|
||||
ylabel=f'{error_name.upper()} (true distribution, predicted distribution)',
|
||||
|
@ -325,9 +324,15 @@ def error_by_drift(method_names, true_prevs, estim_prevs, tr_prevs,
|
|||
|
||||
|
||||
ax.set_xlim(min_x, max_x)
|
||||
if logscale:
|
||||
#nice scale for the logaritmic axis
|
||||
ax.set_ylim(0,10 ** math.ceil(math.log10(max_y)))
|
||||
|
||||
|
||||
if show_legend:
|
||||
fig.legend(loc='right')
|
||||
fig.legend(loc='lower center',
|
||||
bbox_to_anchor=(1, 0.5),
|
||||
ncol=(len(method_names)+1)//2)
|
||||
|
||||
_save_or_show(savepath)
|
||||
|
||||
|
|
Loading…
Reference in New Issue