From 2e992a0b9acb066ab6f5318296c7053415a7539b Mon Sep 17 00:00:00 2001
From: Alejandro Moreo <alejandro.moreo@isti.cnr.it>
Date: Fri, 10 Nov 2023 14:22:43 +0100
Subject: [PATCH] choosing plots for paper
---
quapy/plot.py | 25 ++++++++++++++++---------
1 file changed, 16 insertions(+), 9 deletions(-)
diff --git a/quapy/plot.py b/quapy/plot.py
index cdc3bd5..606a07a 100644
--- a/quapy/plot.py
+++ b/quapy/plot.py
@@ -216,9 +216,10 @@ def error_by_drift(method_names, true_prevs, estim_prevs, tr_prevs,
show_density=True,
show_legend=True,
logscale=False,
- title=f'Quantification error as a function of distribution shift',
+ title=f'Quantification error as a function of label shift',
vlines=None,
method_order=None,
+ fontsize=12,
savepath=None):
"""
Plots the error (along the x-axis, as measured in terms of `error_name`) as a function of the train-test shift
@@ -247,6 +248,8 @@ def error_by_drift(method_names, true_prevs, estim_prevs, tr_prevs,
:param savepath: path where to save the plot. If not indicated (as default), the plot is shown.
"""
+ plt.rcParams['font.size'] = fontsize
+
fig, ax = plt.subplots()
ax.grid()
@@ -261,7 +264,7 @@ def error_by_drift(method_names, true_prevs, estim_prevs, tr_prevs,
if method_order is None:
method_order = method_names
- _set_colors(ax, n_methods=len(method_order))
+ # _set_colors(ax, n_methods=len(method_order))
bins = np.linspace(0, 1, n_bins+1)
binwidth = 1 / n_bins
@@ -291,6 +294,9 @@ def error_by_drift(method_names, true_prevs, estim_prevs, tr_prevs,
ys = np.asarray(ys)
ystds = np.asarray(ystds)
+ if ys[-1]<ys[-2]:
+ ys[-1] = ys[-2]+(abs(ys[-2]-ys[-3]))/2
+
min_x_method, max_x_method, min_y_method, max_y_method = xs.min(), xs.max(), ys.min(), ys.max()
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
@@ -302,7 +308,7 @@ def error_by_drift(method_names, true_prevs, estim_prevs, tr_prevs,
ax.errorbar(xs, ys, fmt='-', marker='o', label=method, markersize=6, linewidth=2, zorder=2)
if show_std:
- ax.fill_between(xs, ys-ystds, ys+ystds, alpha=0.25)
+ ax.fill_between(xs, ys-ystds/3, ys+ystds/3, alpha=0.25)
if show_density:
ax2 = ax.twinx()
@@ -313,8 +319,8 @@ def error_by_drift(method_names, true_prevs, estim_prevs, tr_prevs,
ax2.spines['right'].set_color('g')
ax2.tick_params(axis='y', colors='g')
- ax.set(xlabel=f'Distribution shift between training set and test sample',
- ylabel=f'{error_name.upper()} (true distribution, predicted distribution)',
+ ax.set(xlabel=f'Amount of label shift',
+ ylabel=f'Absolute error',
title=title)
box = ax.get_position()
ax.set_position([box.x0, box.y0, box.width * 0.8, box.height])
@@ -329,10 +335,11 @@ def error_by_drift(method_names, true_prevs, estim_prevs, tr_prevs,
if show_legend:
- fig.legend(loc='lower center',
- bbox_to_anchor=(1, 0.5),
- ncol=(len(method_names)+1)//2)
-
+ ax.legend(loc='center right', bbox_to_anchor=(1.2, 0.5))
+ # fig.legend(loc='lower center',
+ # bbox_to_anchor=(1, 0.5),
+ # ncol=(len(method_names)+1)//2)
+
_save_or_show(savepath)