From 7b6a822430b39a03b0bcbfe7712ad7643211ea36 Mon Sep 17 00:00:00 2001
From: kohlhaasrebecca <rebecca.kohlhaas@outlook.com>
Date: Mon, 9 Dec 2024 17:53:13 +0100
Subject: [PATCH] More linting and reformatting with black
---
.../post_processing/post_processing.py | 36 +++++++++----------
1 file changed, 17 insertions(+), 19 deletions(-)
diff --git a/src/bayesvalidrox/post_processing/post_processing.py b/src/bayesvalidrox/post_processing/post_processing.py
index 3776743e4..4d311fe4e 100644
--- a/src/bayesvalidrox/post_processing/post_processing.py
+++ b/src/bayesvalidrox/post_processing/post_processing.py
@@ -36,7 +36,7 @@ class PostProcessing:
Name of the PostProcessing object to be used for saving the generated files.
The default is 'calib'.
out_dir : string
- Output directory in which the PostProcessing results are placed.
+ Output directory in which the PostProcessing results are placed.
The results are contained in a subfolder '/Outputs_PostProcessing_name'
The default is ''.
out_format : string
@@ -80,7 +80,7 @@ class PostProcessing:
self.stds = None
# -------------------------------------------------------------------------
- def plot_moments(self, plot_type: str = 'line'):
+ def plot_moments(self, plot_type: str = "line"):
"""
Plots the moments in a user defined output format (standard is pdf) in the directory
`Outputs_PostProcessing`.
@@ -104,8 +104,8 @@ class PostProcessing:
Standard deviation of the model outputs.
"""
- if plot_type not in ['bar', 'line']:
- raise AttributeError('The wanted plot-type is not supported.')
+ if plot_type not in ["bar", "line"]:
+ raise AttributeError("The wanted plot-type is not supported.")
bar_plot = bool(plot_type == "bar")
meta_model_type = self.engine.MetaModel.meta_model_type
@@ -304,10 +304,7 @@ class PostProcessing:
# Loop over the keys and compute RMSE error.
for key in self.engine.out_names:
# Root mena square
- self.rmse[key] = root_mean_squared_error(
- outputs[key],
- metamod_outputs[key]
- )
+ self.rmse[key] = root_mean_squared_error(outputs[key], metamod_outputs[key])
# Validation error
self.valid_error[key] = (self.rmse[key] ** 2) / np.var(
outputs[key], ddof=1, axis=0
@@ -377,7 +374,7 @@ class PostProcessing:
# Plot the evolution of the diagnostic criteria of the
# Sequential Experimental Design.
-
+
for plotidx, plot in enumerate(plot_list):
fig, ax = plt.subplots()
seq_dict = seq_list[plotidx]
@@ -627,7 +624,7 @@ class PostProcessing:
np.save(f"./{newpath}/seq_{plot_name}.npy", seq_values)
# -------------------------------------------------------------------------
- def sobol_indices(self, plot_type: str = 'line', save: bool = True):
+ def sobol_indices(self, plot_type: str = "line", save: bool = True):
"""
Visualizes and writes out Sobol' and Total Sobol' indices of the trained metamodel.
One file is created for each index and output key.
@@ -663,9 +660,9 @@ class PostProcessing:
raise AttributeError("Sobol indices only support PCE-type models!")
if metamod.meta_model_type.lower() not in ["pce", "apce"]:
raise AttributeError("Sobol indices only support PCE-type models!")
-
- if plot_type not in ['line', 'bar']:
- raise AttributeError('The wanted plot type is not supported.')
+
+ if plot_type not in ["line", "bar"]:
+ raise AttributeError("The wanted plot type is not supported.")
# Extract the necessary variables
max_order = np.max(metamod._pce_deg)
@@ -846,7 +843,7 @@ class PostProcessing:
)
else:
n_samples = samples.shape[0]
-
+
# Evaluate the original and the surrogate model
y_val = outputs
if y_val is None:
@@ -995,6 +992,7 @@ class PostProcessing:
bbox_inches="tight",
)
plt.close(fig)
+
# -------------------------------------------------------------------------
def _plot_validation_multi(self, out_mean, out_std, model_out):
"""
@@ -1018,15 +1016,15 @@ class PostProcessing:
# List of markers and colors
color = cycle((["b", "g", "r", "y", "k"]))
marker = cycle(("x", "d", "+", "o", "*"))
- metamod_name = self.engine.MetaModel.meta_model_type.lower()
-
+ metamod_name = self.engine.MetaModel.meta_model_type.lower()
+
# Plot the model vs PCE model
fig = plt.figure()
for _, key in enumerate(self.engine.out_names):
y_val = out_mean[key]
y_val_std = out_std[key]
y_val = model_out[key]
-
+
for idx in range(y_val.shape[0]):
plt.plot(
self.x_values,
@@ -1041,7 +1039,7 @@ class PostProcessing:
color=next(color),
marker=next(marker),
linestyle="--",
- label="$Y_{{{}}}^{{{}}}$".format(idx + 1, metamod_name)
+ label="$Y_{{{}}}^{{{}}}$".format(idx + 1, metamod_name),
)
plt.fill_between(
self.x_values,
@@ -1067,6 +1065,6 @@ class PostProcessing:
key = key.replace(" ", "_")
fig.savefig(
f"./{self.out_dir}/Model_vs_{metamod_name}Model_{key}.{self.out_format}",
- bbox_inches="tight"
+ bbox_inches="tight",
)
plt.close()
--
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