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QuaPy
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setting different colors to error drifts

This commit is contained in:
Alejandro Moreo Fernandez 2021-07-06 09:57:52 +02:00
parent 56bb60d8b6
commit fc228a722d
3 changed files with 11 additions and 8 deletions
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2
TweetSentQuant/experiments_NPP.py
View File

@ -74,7 +74,7 @@ def quantification_ensembles():
# will be skipped (by setting hyperparameters to None) # will be skipped (by setting hyperparameters to None)
hyper_none = None hyper_none = None
yield 'epaccmaeptr', EPACC(newLR(), optim='mae', policy='ptr', **common), hyper_none yield 'epaccmaeptr', EPACC(newLR(), optim='mae', policy='ptr', **common), hyper_none
yield 'epaccmaemae1k', EPACC(newLR(), optim='mae', policy='mae', **common), hyper_none yield 'epaccmaemae', EPACC(newLR(), optim='mae', policy='mae', **common), hyper_none
# yield 'esldmaeptr', EEMQ(newLR(), optim='mae', policy='ptr', **common), hyper_none # yield 'esldmaeptr', EEMQ(newLR(), optim='mae', policy='ptr', **common), hyper_none
# yield 'esldmaemae', EEMQ(newLR(), optim='mae', policy='mae', **common), hyper_none # yield 'esldmaemae', EEMQ(newLR(), optim='mae', policy='mae', **common), hyper_none

10
TweetSentQuant/gen_plots.py
View File

@ -82,13 +82,13 @@ new_methods_ae = ['svmmae' , 'epaccmaeptr', 'epaccmaemae', 'hdy', 'quanet']
new_methods_rae = ['svmmrae' , 'epaccmraeptr', 'epaccmraemrae', 'hdy', 'quanet'] new_methods_rae = ['svmmrae' , 'epaccmraeptr', 'epaccmraemrae', 'hdy', 'quanet']
plot_error_by_drift(gao_seb_methods+new_methods_ae, error_name='ae', path=plotdir) plot_error_by_drift(gao_seb_methods+new_methods_ae, error_name='ae', path=plotdir)
plot_error_by_drift(gao_seb_methods+new_methods_rae, error_name='rae', logscale=True, path=plotdir) # plot_error_by_drift(gao_seb_methods+new_methods_rae, error_name='rae', logscale=True, path=plotdir)
diagonal_plot(gao_seb_methods+new_methods_ae, error_name='ae', path=plotdir) # diagonal_plot(gao_seb_methods+new_methods_ae, error_name='ae', path=plotdir)
diagonal_plot(gao_seb_methods+new_methods_rae, error_name='rae', path=plotdir) # diagonal_plot(gao_seb_methods+new_methods_rae, error_name='rae', path=plotdir)
binary_bias_global(gao_seb_methods+new_methods_ae, error_name='ae', path=plotdir) # binary_bias_global(gao_seb_methods+new_methods_ae, error_name='ae', path=plotdir)
binary_bias_global(gao_seb_methods+new_methods_rae, error_name='rae', path=plotdir) # binary_bias_global(gao_seb_methods+new_methods_rae, error_name='rae', path=plotdir)
#binary_bias_bins(gao_seb_methods+new_methods_ae, error_name='ae', path=plotdir) #binary_bias_bins(gao_seb_methods+new_methods_ae, error_name='ae', path=plotdir)
#binary_bias_bins(gao_seb_methods+new_methods_rae, error_name='rae', path=plotdir) #binary_bias_bins(gao_seb_methods+new_methods_rae, error_name='rae', path=plotdir)

7
quapy/plot.py
View File

@ -208,13 +208,14 @@ def error_by_drift(method_names, true_prevs, estim_prevs, tr_prevs, n_bins=20, e
inds = np.digitize(tr_test_drifts, bins, right=True) inds = np.digitize(tr_test_drifts, bins, right=True)
inds_histogram_global += np.histogram(tr_test_drifts, density=True, bins=bins)[0] inds_histogram_global += np.histogram(tr_test_drifts, density=True, bins=bins)[0]
xs, ys, ystds = [], [], [] xs, ys, ystds, npoints = [], [], [], []
for ind in range(len(bins)): for ind in range(len(bins)):
selected = inds==ind selected = inds==ind
if selected.sum() > 0: if selected.sum() > 0:
xs.append(ind*binwidth) xs.append(ind*binwidth)
ys.append(np.mean(method_drifts[selected])) ys.append(np.mean(method_drifts[selected]))
ystds.append(np.std(method_drifts[selected])) ystds.append(np.std(method_drifts[selected]))
npoints.append(len(method_drifts[selected]))
xs = np.asarray(xs) xs = np.asarray(xs)
ys = np.asarray(ys) ys = np.asarray(ys)
@ -224,7 +225,9 @@ def error_by_drift(method_names, true_prevs, estim_prevs, tr_prevs, n_bins=20, e
min_x = min_x_method if min_x is None or min_x_method < min_x else min_x min_x = min_x_method if min_x is None or min_x_method < min_x else min_x
max_x = max_x_method if max_x is None or max_x_method > max_x else max_x max_x = max_x_method if max_x is None or max_x_method > max_x else max_x
ax.errorbar(xs, ys, fmt='-', marker='o', label=method, markersize=3, zorder=2) p = ax.errorbar(xs, ys, fmt='-', marker='o', label=method, markersize=3, zorder=2)
ax.scatter(xs, ys, s=npoints, marker="h", color=p[-1].get_color())
if show_std: if show_std:
ax.fill_between(xs, ys-ystds, ys+ystds, alpha=0.25) ax.fill_between(xs, ys-ystds, ys+ystds, alpha=0.25)