From d37a25cc33bb072137118cc87884a60abdc0612c Mon Sep 17 00:00:00 2001
From: kohlhaasrebecca <rebecca.kohlhaas@outlook.com>
Date: Wed, 11 Dec 2024 21:24:04 +0100
Subject: [PATCH] Fix test
---
src/bayesvalidrox/post_processing/post_processing.py | 9 +++++----
1 file changed, 5 insertions(+), 4 deletions(-)
diff --git a/src/bayesvalidrox/post_processing/post_processing.py b/src/bayesvalidrox/post_processing/post_processing.py
index d67e3529f..08bb5eb25 100644
--- a/src/bayesvalidrox/post_processing/post_processing.py
+++ b/src/bayesvalidrox/post_processing/post_processing.py
@@ -844,11 +844,11 @@ class PostProcessing:
y_val = outputs
if y_val is None:
y_val, _ = self.engine.Model.run_model_parallel(samples, key_str="valid")
- y_pce_val, _ = self.engine.eval_metamodel(samples=samples)
+ y_metamod_val, _ = self.engine.eval_metamodel(samples=samples)
# Fit the data(train the model)
- for key in y_pce_val.keys():
- residuals = y_val[key] - y_pce_val[key]
+ for key in y_metamod_val.keys():
+ residuals = y_val[key] - y_metamod_val[key]
# ------ Residuals vs. predicting variables ------
# Check the assumptions of linearity and independence
@@ -874,7 +874,8 @@ class PostProcessing:
# ------ Fitted vs. residuals ------
# Check the assumptions of linearity and independence
- plt.scatter(x=y_pce_val[key], y=residuals, color="blue", edgecolor="k")
+ for i in range(y_metamod_val[key].shape[0]):
+ plt.scatter(x=y_metamod_val[key][i,:], y=residuals[i,:], color="blue", edgecolor="k")
plt.title(f"{key}: Residuals vs. fitted values")
plt.grid(True)
plt.hlines(
--
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