Updated non autoregressive images in thesis

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2024-04-19 16:19:18 +02:00
parent afa70fc3b3
commit e0fbf54347
16 changed files with 41 additions and 41 deletions

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@@ -322,19 +322,17 @@ Because of error propagation in the autoregressive model, the outputted quantile
% figure with 2 models compared (left with 4 row examples and right with 4 row examples), autoregressive vs non-autoregressive
\begin{figure}[ht]
\centering
\begin{adjustbox}{width=1.3\textwidth,center}
\begin{subfigure}[b]{0.7\textwidth}
\includegraphics[width=\textwidth]{images/quantile_regression/naqr_linear_model_samples/NAQR_NRV_Load_Wind_PV_NP-Example_864_samples.png}
\caption{Autoregressive model}
\label{fig:linear_model_sample_comparison_autoregressive}
\end{subfigure}
\hfill
\begin{subfigure}[b]{0.7\textwidth}
\includegraphics[width=\textwidth]{images/quantile_regression/naqr_linear_model_samples/NAQR_NRV_Load_Wind_PV_NP-Example_864_samples.png}
\caption{Non-autoregressive model}
\label{fig:linear_model_sample_comparison_non_autoregressive}
\end{subfigure}
\end{adjustbox}
\begin{subfigure}[b]{0.49\textwidth}
\includegraphics[width=\textwidth]{images/quantile_regression/naqr_linear_model_samples/NAQR_NRV_Load_Wind_PV_NP-Example_864_samples.png}
\caption{Autoregressive model}
\label{fig:linear_model_sample_comparison_autoregressive}
\end{subfigure}
\hfill
\begin{subfigure}[b]{0.49\textwidth}
\includegraphics[width=\textwidth]{images/quantile_regression/naqr_linear_model_samples/NAQR_NRV_Load_Wind_PV_NP-Example_864_samples.png}
\caption{Non-autoregressive model}
\label{fig:linear_model_sample_comparison_non_autoregressive}
\end{subfigure}
\caption{Comparison of the autoregressive and non-autoregressive linear models. The plots show the confidence intervals calculated from 1000 generated full-day NRV samples. The samples were generated using input features NRV, Load, Wind, PV, Net Position and the quarter embedding.}
\label{fig:linear_model_sample_comparison}
\end{figure}

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@@ -1,4 +1,4 @@
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@@ -1412,37 +1412,37 @@ Underfull \hbox (badness 10000) in paragraph at lines 259--265
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@@ -3,7 +3,7 @@ from src.utils.clearml import ClearMLHelper
#### ClearML ####
clearml_helper = ClearMLHelper(project_name="Thesis/NrvForecast")
task = clearml_helper.get_task(
task_name="AQR: Linear Baseline + Load + PV + Wind + Net Position + Quarter"
task_name="AQR: Linear Baseline + Load + PV + Wind + Net Position + Quarter (dim 5)"
)
task.execute_remotely(queue_name="default", exit_process=True)

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@@ -2,7 +2,9 @@ from src.utils.clearml import ClearMLHelper
#### ClearML ####
clearml_helper = ClearMLHelper(project_name="Thesis/NAQR: Linear")
task = clearml_helper.get_task(task_name="NAQR: Linear (extra test)")
task = clearml_helper.get_task(
task_name="NAQR: Linear + Load + PV + Wind + Net Position"
)
task.execute_remotely(queue_name="default", exit_process=True)
from src.policies.PolicyEvaluator import PolicyEvaluator
@@ -27,16 +29,16 @@ from src.models.time_embedding_layer import TimeEmbedding
data_config = DataConfig()
data_config.NRV_HISTORY = True
data_config.LOAD_HISTORY = False
data_config.LOAD_FORECAST = False
data_config.LOAD_HISTORY = True
data_config.LOAD_FORECAST = True
data_config.WIND_FORECAST = False
data_config.WIND_HISTORY = False
data_config.WIND_FORECAST = True
data_config.WIND_HISTORY = True
data_config.PV_FORECAST = False
data_config.PV_HISTORY = False
data_config.PV_FORECAST = True
data_config.PV_HISTORY = True
data_config.NOMINAL_NET_POSITION = False
data_config.NOMINAL_NET_POSITION = True
data_config = task.connect(data_config, name="data_features")