From 8b1adc0fe1f06c0a8c62b409038c0df59c630d0a Mon Sep 17 00:00:00 2001
From: Joerg Martin <joerg.martin@ptb.de>
Date: Mon, 7 Feb 2022 15:33:39 +0000
Subject: [PATCH] simulated datasets revised to show EiV effect
---
EIVPackage/EIVData/cubic.py | 4 ++--
EIVPackage/EIVData/linear.py | 2 +-
EIVPackage/EIVData/sine.py | 4 ++--
Experiments/configurations/eiv_cubic.json | 4 ++--
Experiments/configurations/eiv_linear.json | 2 +-
Experiments/configurations/eiv_quadratic.json | 2 +-
Experiments/configurations/eiv_sine.json | 4 ++--
Experiments/configurations/noneiv_cubic.json | 2 +-
Experiments/configurations/noneiv_linear.json | 2 +-
Experiments/configurations/noneiv_quadratic.json | 2 +-
Experiments/configurations/noneiv_sine.json | 2 +-
Experiments/plot_coverage_vs_q.py | 7 +++----
Experiments/plot_summary.py | 6 +++---
13 files changed, 21 insertions(+), 22 deletions(-)
diff --git a/EIVPackage/EIVData/cubic.py b/EIVPackage/EIVData/cubic.py
index dce6ea4..9d5e397 100644
--- a/EIVPackage/EIVData/cubic.py
+++ b/EIVPackage/EIVData/cubic.py
@@ -9,8 +9,8 @@ total_number_of_datapoints = 1000
input_range = [-1,1]
slope = 1.0
intercept = 0.0
-x_noise_strength = 0.1
-y_noise_strength = 0.1
+x_noise_strength = 0.2
+y_noise_strength = 0.05
func = lambda true_x: slope * true_x**3 + intercept
def load_data(seed=0, splitting_part=0.8, normalize=True,
diff --git a/EIVPackage/EIVData/linear.py b/EIVPackage/EIVData/linear.py
index 97d2cd9..2a1b0d7 100644
--- a/EIVPackage/EIVData/linear.py
+++ b/EIVPackage/EIVData/linear.py
@@ -10,7 +10,7 @@ input_range = [-1,1]
slope = 1.0
intercept = 0.0
x_noise_strength = 0.1
-y_noise_strength = 0.1
+y_noise_strength = 0.2
func = lambda true_x: slope * true_x + intercept
def load_data(seed=0, splitting_part=0.8, normalize=True,
diff --git a/EIVPackage/EIVData/sine.py b/EIVPackage/EIVData/sine.py
index cde80d3..2e9eabc 100644
--- a/EIVPackage/EIVData/sine.py
+++ b/EIVPackage/EIVData/sine.py
@@ -8,8 +8,8 @@ from EIVGeneral.manipulate_tensors import add_noise, normalize_tensor,\
total_number_of_datapoints = 2000
input_range = [-0.2,0.8]
intercept = 0.0
-x_noise_strength = 0.02
-y_noise_strength = 0.02
+x_noise_strength = 0.04
+y_noise_strength = 0.01
func = lambda true_x: true_x +\
torch.sin(2 * torch.pi * true_x) +\
torch.sin(4 * torch.pi * true_x)
diff --git a/Experiments/configurations/eiv_cubic.json b/Experiments/configurations/eiv_cubic.json
index 0e9f9e8..59c37c1 100644
--- a/Experiments/configurations/eiv_cubic.json
+++ b/Experiments/configurations/eiv_cubic.json
@@ -13,10 +13,10 @@
"std_y_update_points": [1,40],
"eiv_prediction_number_of_draws": [100,5],
"eiv_prediction_number_of_batches": 10,
- "init_std_y_list": [0.5],
+ "init_std_y_list": [0.05],
"gamma": 0.5,
"hidden_layers": [128, 128, 128, 128],
- "fixed_std_x": 0.10,
+ "fixed_std_x": 0.20,
"seed_range": [0,10],
"gpu_number": 1
}
diff --git a/Experiments/configurations/eiv_linear.json b/Experiments/configurations/eiv_linear.json
index 8b7ebe0..ce84949 100644
--- a/Experiments/configurations/eiv_linear.json
+++ b/Experiments/configurations/eiv_linear.json
@@ -13,7 +13,7 @@
"std_y_update_points": [1,40],
"eiv_prediction_number_of_draws": [100,5],
"eiv_prediction_number_of_batches": 10,
- "init_std_y_list": [0.5],
+ "init_std_y_list": [0.1],
"gamma": 0.5,
"hidden_layers": [128, 128, 128, 128],
"fixed_std_x": 0.10,
diff --git a/Experiments/configurations/eiv_quadratic.json b/Experiments/configurations/eiv_quadratic.json
index c774bbe..dc8a9cd 100644
--- a/Experiments/configurations/eiv_quadratic.json
+++ b/Experiments/configurations/eiv_quadratic.json
@@ -13,7 +13,7 @@
"std_y_update_points": [1,40],
"eiv_prediction_number_of_draws": [100,5],
"eiv_prediction_number_of_batches": 10,
- "init_std_y_list": [0.5],
+ "init_std_y_list": [0.1],
"gamma": 0.5,
"hidden_layers": [128, 128, 128, 128],
"fixed_std_x": 0.10,
diff --git a/Experiments/configurations/eiv_sine.json b/Experiments/configurations/eiv_sine.json
index 1195ea0..b6bf6d0 100644
--- a/Experiments/configurations/eiv_sine.json
+++ b/Experiments/configurations/eiv_sine.json
@@ -14,10 +14,10 @@
"eiv_number_of_forward_draws": 10,
"eiv_prediction_number_of_draws": [100,5],
"eiv_prediction_number_of_batches": 10,
- "init_std_y_list": [0.1],
+ "init_std_y_list": [0.01],
"gamma": 0.5,
"hidden_layers": [128, 128, 128, 128],
- "fixed_std_x": 0.02,
+ "fixed_std_x": 0.04,
"seed_range": [0,10],
"gpu_number": 1
}
diff --git a/Experiments/configurations/noneiv_cubic.json b/Experiments/configurations/noneiv_cubic.json
index 6f71af1..a325665 100644
--- a/Experiments/configurations/noneiv_cubic.json
+++ b/Experiments/configurations/noneiv_cubic.json
@@ -13,7 +13,7 @@
"std_y_update_points": [1,40] ,
"noneiv_prediction_number_of_draws": 100,
"noneiv_prediction_number_of_batches": 10,
- "init_std_y_list": [0.5],
+ "init_std_y_list": [0.05],
"gamma": 0.5,
"hidden_layers": [128, 128, 128, 128],
"seed_range": [0,10],
diff --git a/Experiments/configurations/noneiv_linear.json b/Experiments/configurations/noneiv_linear.json
index ae3040e..ff57b56 100644
--- a/Experiments/configurations/noneiv_linear.json
+++ b/Experiments/configurations/noneiv_linear.json
@@ -13,7 +13,7 @@
"std_y_update_points": [1,40] ,
"noneiv_prediction_number_of_draws": 100,
"noneiv_prediction_number_of_batches": 10,
- "init_std_y_list": [0.5],
+ "init_std_y_list": [0.1],
"gamma": 0.5,
"hidden_layers": [128, 128, 128, 128],
"seed_range": [0,10],
diff --git a/Experiments/configurations/noneiv_quadratic.json b/Experiments/configurations/noneiv_quadratic.json
index 4052637..d858851 100644
--- a/Experiments/configurations/noneiv_quadratic.json
+++ b/Experiments/configurations/noneiv_quadratic.json
@@ -13,7 +13,7 @@
"std_y_update_points": [1,40] ,
"noneiv_prediction_number_of_draws": 100,
"noneiv_prediction_number_of_batches": 10,
- "init_std_y_list": [0.5],
+ "init_std_y_list": [0.1],
"gamma": 0.5,
"hidden_layers": [128, 128, 128, 128],
"seed_range": [0,10],
diff --git a/Experiments/configurations/noneiv_sine.json b/Experiments/configurations/noneiv_sine.json
index cc88919..5191847 100644
--- a/Experiments/configurations/noneiv_sine.json
+++ b/Experiments/configurations/noneiv_sine.json
@@ -13,7 +13,7 @@
"std_y_update_points": [1,40] ,
"noneiv_prediction_number_of_draws": 100,
"noneiv_prediction_number_of_batches": 10,
- "init_std_y_list": [0.1],
+ "init_std_y_list": [0.01],
"gamma": 0.5,
"hidden_layers": [128, 128, 128, 128],
"seed_range": [0,10],
diff --git a/Experiments/plot_coverage_vs_q.py b/Experiments/plot_coverage_vs_q.py
index 9bc59a3..5cb7f8f 100644
--- a/Experiments/plot_coverage_vs_q.py
+++ b/Experiments/plot_coverage_vs_q.py
@@ -13,6 +13,7 @@ import torch.backends.cudnn
from torch.utils.data import DataLoader
from matplotlib.pyplot import cm
import matplotlib.pyplot as plt
+from tqdm import tqdm
from EIVArchitectures import Networks
from EIVTrainingRoutines import train_and_store
@@ -94,7 +95,7 @@ plt.ylabel('coverage')
# datasets to plot and their coloring
datasets = ['linear', 'quadratic','cubic','sine']
-colors = ['cyan', 'magenta', 'yellow', 'green']
+colors = ['#084519', '#7D098D', '#77050C', '#09017F']
def compute_coverages(data, eiv, number_of_draws):
"""
@@ -148,7 +149,6 @@ def compute_coverages(data, eiv, number_of_draws):
= load_data(seed=0, return_ground_truth=True,
normalize=normalize)
- print(f"Computing {'EiV' if eiv else 'non-EiV'} coverage for {long_dataname}")
# train_data only used for finding dimensions
input_dim = train_data[0][0].numel()
@@ -233,14 +233,13 @@ def compute_coverages(data, eiv, number_of_draws):
return numerical_coverage, theoretical_coverage
# loop through data
-for data, color in zip(datasets, colors):
+for data, color in tqdm(zip(datasets, colors)):
# compute coverages
eiv_coverages = compute_coverages(data=data, eiv=True,
number_of_draws=[100,5])
noneiv_coverages = compute_coverages(data=data, eiv=False,
number_of_draws=100)
# create plots
- plt.figure(1)
coverage_diagonal_plot(eiv_coverages, noneiv_coverages,
color=color, against_theoretical=False, label=data)
diff --git a/Experiments/plot_summary.py b/Experiments/plot_summary.py
index c3d8c0d..c0863c6 100644
--- a/Experiments/plot_summary.py
+++ b/Experiments/plot_summary.py
@@ -80,7 +80,7 @@ for i, ([(eiv_metric_mean, eiv_metric_std),
bottom = noneiv_metric_mean - k* noneiv_metric_std,
color=colors[1],
alpha=0.5)
-plt.ylim(bottom=0, top=y_max)
+plt.ylim(bottom=0, top=ymax)
ax = plt.gca()
ax.set_xticks(np.arange(1,len(data_list)+1))
ax.set_xticklabels(data_list, rotation='vertical')
@@ -127,7 +127,7 @@ for i, ([(eiv_metric_mean, eiv_metric_std),
color=colors[1],
alpha=0.5)
plt.axhline(0.95,0.0,1.0,color='k', linestyle='dashed')
-plt.ylim(bottom=0, top=y_max)
+plt.ylim(bottom=0, top=ymax)
ax = plt.gca()
ax.set_xticks(np.arange(1,len(data_list)+1))
ax.set_xticklabels(data_list, rotation='vertical')
@@ -173,7 +173,7 @@ for i, ([(eiv_metric_mean, eiv_metric_std),
bottom = noneiv_metric_mean - k* noneiv_metric_std,
color=colors[1],
alpha=0.5)
-plt.ylim(bottom=0, top=y_max)
+plt.ylim(bottom=0, top=ymax)
ax = plt.gca()
ax.set_xticks(np.arange(1,len(data_list)+1))
ax.set_xticklabels(data_list, rotation='vertical')
--
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