diff --git a/dynamics_learning/dynamics_learning/testing/__init__.py b/dynamics_learning/dynamics_learning/testing/__init__.py index d8f99de1e8d48fb7d5b362f3ff3bd88405c1c6a9..a4983705baf2afa1829a47ca2b820f79dfeab19f 100644 --- a/dynamics_learning/dynamics_learning/testing/__init__.py +++ b/dynamics_learning/dynamics_learning/testing/__init__.py @@ -137,18 +137,13 @@ class Dataset: if date == "20240719_141438": continue dates.append(date) - - logger.info(dates) - self.most_recent_file = max( - dates - ) # FIXME this is not returning the most recent file + self.most_recent_file = max(dates) logger.info(f"Most recent file is set to {self.most_recent_file}.") return self.most_recent_file def _delete_files(self, files, most_recent_file: None): logger.info(f"Most recent file is {most_recent_file}.") for file in files: - logger.info(f"Checking {file.name}.") if most_recent_file: if most_recent_file not in file.name: local_file_path = Path(self.local_path + "/" + file.name) @@ -190,7 +185,6 @@ class Dataset: for file in files if file.metadata_form()["Robot UUID"][0] == ROBOT_UUID ] - logger.info(f"Filtered files: {filtered_files}") if filtered_files == []: logger.critical("No files found with given robot_uuid.") sys.exit(1) @@ -201,7 +195,6 @@ class Dataset: for file in files if file.metadata_form()["Robot UUID"][0] != ROBOT_UUID ] - logger.info(f"Files to delete: {delete_files}") if filtered_files: # check for the most recent file @@ -211,7 +204,6 @@ class Dataset: # delete all files with wrong robot_uuid if delete_files: - logger.log("I think this needs fixing") self._delete_files(delete_files, None) return self.analysis_file @@ -442,7 +434,7 @@ LSTM Implementation Output: Concluded color=rwth_style.green, ) - axs[joint_number // num_col, joint_number % num_col].scatter( # FIXME + axs[joint_number // num_col, joint_number % num_col].scatter( t_meas[window_size - 1 :], y_pred[:, joint_number], label="Prediction based on command trajectory (NN)",