From a69a71fee97863f6fe03946bfdde71ceb736b09f Mon Sep 17 00:00:00 2001
From: Joerg Martin <joerg.martin@ptb.de>
Date: Wed, 8 Jun 2022 12:17:23 +0000
Subject: [PATCH] summary plot updated
---
Experiments/evaluate_metrics.py | 2 +-
Experiments/plot_summary.py | 20 +++++++++++++++-----
2 files changed, 16 insertions(+), 6 deletions(-)
diff --git a/Experiments/evaluate_metrics.py b/Experiments/evaluate_metrics.py
index cfae6f4..4a59088 100644
--- a/Experiments/evaluate_metrics.py
+++ b/Experiments/evaluate_metrics.py
@@ -267,7 +267,7 @@ def collect_metrics(x_y_pairs, seed=0,
lin_pred, lin_unc = linear_pred_unc(x_train, y_train, sigma_y, design_matrix, x, device=device)
assert true_y is not None
lin_coverage = linear_coverage(lin_pred, lin_unc, true_y)
- metrics['lin'] = {'coverage': lin_coverage}
+ metrics['lin'] = {'true_coverage_numerical': lin_coverage}
return metrics
diff --git a/Experiments/plot_summary.py b/Experiments/plot_summary.py
index 90eacc8..9c12534 100644
--- a/Experiments/plot_summary.py
+++ b/Experiments/plot_summary.py
@@ -82,14 +82,14 @@ for i, ([(eiv_metric_mean, eiv_metric_std),
width = 1.0,
bottom = eiv_metric_mean - eiv_bar_size,
color=colors[0],
- alpha=1.0)
+ alpha=0.5)
plt.plot(i+1, noneiv_metric_mean, '^', color=colors[1], markersize=16, zorder=0)
plt.bar(i+1,
height = 2 * k *noneiv_bar_size,
width = 1.0,
bottom = noneiv_metric_mean - k* noneiv_bar_size,
color=colors[1],
- alpha=1.0)
+ alpha=0.5)
plt.ylim(bottom=0, top=ymax)
ax = plt.gca()
ax.set_xticks(np.arange(1,len(data_list)+1))
@@ -102,13 +102,14 @@ plt.savefig('results/figures/RMSE_bar_plot.pdf')
metric = 'true_coverage_numerical'
data_list = ['linear','quadratic','cubic','sine']
-colors = ['red', 'blue']
+colors = ['red', 'blue','black']
ymax = 1.0
minimal_bar_size = ymax * 1.5e-3
# read out EiV and non-EiV results for all datasets
metric_results = [
(save_readout(results[data]['eiv'], metric),
- save_readout(results[data]['noneiv'], metric))
+ save_readout(results[data]['noneiv'], metric),
+ save_readout(results[data]['lin'], metric))
for data in data_list]
# create figure
@@ -118,7 +119,8 @@ plt.gcf().canvas.manager.set_window_title('coverage (ground truth)')
# plot bars
for i, ([(eiv_metric_mean, eiv_metric_std),
- (noneiv_metric_mean, noneiv_metric_std)],\
+ (noneiv_metric_mean, noneiv_metric_std),
+ (lin_metric_mean, lin_metric_std)],\
data) in\
enumerate(zip(metric_results, data_list)):
if eiv_metric_mean is not None:
@@ -127,6 +129,7 @@ for i, ([(eiv_metric_mean, eiv_metric_std),
assert noneiv_metric_std is not None
eiv_bar_size = max(eiv_metric_std, minimal_bar_size)
noneiv_bar_size = max(noneiv_metric_std, minimal_bar_size)
+ lin_bar_size = max(lin_metric_std, minimal_bar_size)
plt.plot(i+1, eiv_metric_mean, '^', color=colors[0], markersize=16)
plt.bar(i+1,
height = 2*eiv_bar_size,
@@ -141,6 +144,13 @@ for i, ([(eiv_metric_mean, eiv_metric_std),
bottom = noneiv_metric_mean - k* noneiv_bar_size,
color=colors[1],
alpha=0.5)
+ plt.plot(i+1, lin_metric_mean, '^', color=colors[2], markersize=16)
+ plt.bar(i+1,
+ height = 2 * k *lin_bar_size,
+ width = 0.3,
+ bottom = lin_metric_mean - k* lin_bar_size,
+ color=colors[2],
+ alpha=0.5)
plt.axhline(0.95,0.0,1.0,color='k', linestyle='dashed')
plt.ylim(bottom=0, top=ymax)
ax = plt.gca()
--
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