From f4542a4664452f8d18b2753b52160ef605a5b496 Mon Sep 17 00:00:00 2001
From: Steve Schmerler <git@elcorto.com>
Date: Sat, 17 May 2025 10:10:38 +0200
Subject: [PATCH] 01_one_dim: better plotting layout
---
BLcourse2.3/01_one_dim.py | 15 +++++++++------
1 file changed, 9 insertions(+), 6 deletions(-)
diff --git a/BLcourse2.3/01_one_dim.py b/BLcourse2.3/01_one_dim.py
index 9043f2a..66bafc5 100644
--- a/BLcourse2.3/01_one_dim.py
+++ b/BLcourse2.3/01_one_dim.py
@@ -354,11 +354,14 @@ for ii in range(n_iter):
# Plot hyper params and loss (negative log marginal likelihood) convergence
ncols = len(history)
-fig, axs = plt.subplots(ncols=ncols, nrows=1, figsize=(ncols * 5, 5))
-for ax, (p_name, p_lst) in zip(axs, history.items()):
- ax.plot(p_lst)
- ax.set_title(p_name)
- ax.set_xlabel("iterations")
+fig, axs = plt.subplots(
+ ncols=ncols, nrows=1, figsize=(ncols * 3, 3), layout="compressed"
+)
+with torch.no_grad():
+ for ax, (p_name, p_lst) in zip(axs, history.items()):
+ ax.plot(p_lst)
+ ax.set_title(p_name)
+ ax.set_xlabel("iterations")
# Values of optimized hyper params
pprint(extract_model_params(model))
@@ -387,7 +390,7 @@ with torch.no_grad():
post_pred_f = model(X_pred)
post_pred_y = likelihood(model(X_pred))
- fig, axs = plt.subplots(ncols=2, figsize=(12, 5), sharex=True, sharey=True)
+ fig, axs = plt.subplots(ncols=2, figsize=(14, 5), sharex=True, sharey=True)
fig_sigmas, ax_sigmas = plt.subplots()
for ii, (ax, post_pred, name, title) in enumerate(
zip(
--
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