Applying relative path changes in docstrings

HypVINN/run_prediction.py

@@ -11,8 +11,8 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-
 # IMPORTS
+import os.path
 from typing import TYPE_CHECKING, Optional, cast, Literal
 import argparse
 from pathlib import Path
@@ -32,6 +32,7 @@
     load_checkpoint_config_defaults,
 )
 from FastSurferCNN.utils.common import assert_no_root, SerialExecutor
+from FastSurferCNN.utils.parser_defaults import FASTSURFER_ROOT
 
 from HypVINN.config.hypvinn_files import HYPVINN_SEG_NAME
 from HypVINN.data_loader.data_utils import hypo_map_label2subseg, rescale_image
@@ -46,6 +47,8 @@
 from HypVINN.utils.stats_utils import compute_stats
 from HypVINN.utils.visualization_utils import plot_qc_images
 
+_doc_HYPVINN_SEG_NAME = os.path.relpath(HYPVINN_SEG_NAME, FASTSURFER_ROOT)
+
 logger = logging.get_logger(__name__)
 
 ##
@@ -183,7 +186,7 @@ def main(
         device: str = "auto",
         viewagg_device: str = "auto",
 ) -> int | str:
-    """
+    f"""
     Main function of the hypothalamus segmentation module.
 
     Parameters
@@ -208,8 +211,8 @@ def main(
         The path to the coronal configuration file.
     cfg_sag : Path
         The path to the sagittal configuration file.
-    hypo_segfile : str, default="{HYPVINN_SEG_NAME}"
-        The name of the hypothalamus segmentation file. Default is HYPVINN_SEG_NAME.
+    hypo_segfile : str, default="{_doc_HYPVINN_SEG_NAME}"
+        The name of the hypothalamus segmentation file. Default is {_doc_HYPVINN_SEG_NAME}.
     allow_root : bool, default=False
         Whether to allow running as root user. Default is False.
     qc_snapshots : bool, optional

HypVINN/utils/visualization_utils.py

@@ -11,14 +11,17 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-
+import os.path
 from pathlib import Path
 
 import numpy as np
 import nibabel as nib
 import matplotlib.pyplot as plt
 
 from HypVINN.config.hypvinn_files import HYPVINN_LUT
+from FastSurferCNN.utils.parser_defaults import FASTSURFER_ROOT
+
+_doc_HYPVINN_LUT = os.path.relpath(HYPVINN_LUT, FASTSURFER_ROOT)
 
 
 def remove_values_from_list(the_list, val):
@@ -48,7 +51,7 @@ def get_lut(lookup_table_path: Path = HYPVINN_LUT):
 
     Parameters
     ----------
-    lookup_table_path: Path, default="{HYPVINN_LUT}"
+    lookup_table_path: Path, default="{_doc_HYPVINN_LUT}"
         The path to the file from which the LUT will be constructed.
 
     Returns
@@ -77,7 +80,7 @@ def map_hyposeg2label(hyposeg: np.ndarray, lut_file: Path = HYPVINN_LUT):
     ----------
     hyposeg : np.ndarray
         The original segmentation map.
-    lut_file : Path, default="{HYPVINN_LUT}"
+    lut_file : Path, default="{_doc_HYPVINN_LUT}"
         The path to the lookup table file.
 
     Returns
@@ -255,7 +258,7 @@ def plot_qc_images(
         The path to the predicted image.
     padd : int, default=45
         The padding value for cropping the images and segmentations.
-    lut_file : Path, default="{HYPVINN_LUT}"
+    lut_file : Path, default="{_doc_HYPVINN_LUT}"
         The path to the lookup table file.
     slice_step : int, default=2
         The step size for selecting indices from the predicted segmentation.