From 407970a7d7bf559f55b29a59a499e155b68e6ad1 Mon Sep 17 00:00:00 2001
From: Joerg Martin <joerg.martin@ptb.de>
Date: Tue, 30 Aug 2022 17:26:09 +0200
Subject: [PATCH] average uncertainties
---
...onal.py => plot_diagonal_uncertainties.py} | 28 ++++++-------------
1 file changed, 8 insertions(+), 20 deletions(-)
rename Experiments/{plot_real_diagonal.py => plot_diagonal_uncertainties.py} (89%)
diff --git a/Experiments/plot_real_diagonal.py b/Experiments/plot_diagonal_uncertainties.py
similarity index 89%
rename from Experiments/plot_real_diagonal.py
rename to Experiments/plot_diagonal_uncertainties.py
index d2abda6..5401a44 100644
--- a/Experiments/plot_real_diagonal.py
+++ b/Experiments/plot_diagonal_uncertainties.py
@@ -62,19 +62,7 @@ train_data, test_data = load_data(normalize=normalize)
input_dim = train_data[0][0].numel()
output_dim = train_data[0][1].numel()
-# try:
-# gpu_number = eiv_conf_dict["gpu_number"]
-# device = torch.device(f'cuda:{gpu_number}')
-# try:
-# torch.tensor([0.0]).to(device)
-# except RuntimeError:
-# if torch.cuda.is_available():
-# print('Switched to GPU 0')
-# device = torch.device('cuda:0')
-# else:
-# print('No cuda available, using CPU')
-# device = torch.device('cpu')
-# except KeyError:
+# do computations on cpu
device = torch.device('cpu')
@@ -164,19 +152,19 @@ seed_list = range(noneiv_conf_dict["seed_range"][0],
noneiv_uncertainties = 0
eiv_uncertainties = 0
number_of_seeds = len(seed_list)
-out_dim = 0
number_of_steps = 100
for seed in tqdm(seed_list):
x_diagonal = create_diagonal(train=train_data, number_of_steps=number_of_steps)
- results = collect_predictions(x_diagonal,
- seed=seed)
- noneiv_uncertainties += 1/number_of_seeds * results['noneiv']['uncertainties'][..., out_dim]
- eiv_uncertainties += 1/number_of_seeds * results['eiv']['uncertainties'][..., out_dim]
+ results = collect_predictions(x_diagonal, seed=seed)
+ noneiv_uncertainties += 1/number_of_seeds * results['noneiv']['uncertainties'].mean(dim=-1)
+ eiv_uncertainties += 1/number_of_seeds * results['eiv']['uncertainties'].mean(dim=-1)
plt.figure(1)
plt.clf()
-plot_x = torch.linspace(0,1, steps=number_of_steps)
+plot_x = torch.linspace(0, 1, steps=number_of_steps)
plt.fill_between(plot_x, noneiv_uncertainties, color='b', alpha=0.5)
plt.fill_between(plot_x, eiv_uncertainties, color='r', alpha=0.5)
-plt.savefig('results/figures/intersection')
+plt.xlabel(r'$\lambda$')
+plt.ylabel(r'$u$')
+plt.savefig(f'results/figures/diagonal_uncertainties_{data}.pdf')
--
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