[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

Author: pre-commit-ci[bot]

src/virtualship/cli/commands.py

@@ -28,7 +28,7 @@
     "--mfp_file",
     type=str,
     default=None,
-    help="Partially initialise a project from an exported xlsx or csv file from NIOZ' Marine Facilities Planning tool (specifically the \"Export Coordinates > DD\" option). User edits are required after initialisation.",
+    help='Partially initialise a project from an exported xlsx or csv file from NIOZ\' Marine Facilities Planning tool (specifically the "Export Coordinates > DD" option). User edits are required after initialisation.',
 )
 def init(path, mfp_file):
     """
@@ -53,11 +53,13 @@ def init(path, mfp_file):
         )
 
     config.write_text(utils.get_example_config())
-    
+
     if mfp_file:
         # Generate schedule.yaml from the MPF file
         click.echo(f"Generating schedule from {mfp_file}...")
-        mfp_to_yaml(mfp_file, str(path))  # Pass the path to save in the correct directory
+        mfp_to_yaml(
+            mfp_file, str(path)
+        )  # Pass the path to save in the correct directory
     else:
         # Create a default example schedule
         schedule.write_text(utils.get_example_schedule())

src/virtualship/utils.py

@@ -1,10 +1,10 @@
+import os
 from functools import lru_cache
 from importlib.resources import files
 from typing import TextIO
-import pandas as pd
-import numpy as np
-import os
 
+import numpy as np
+import pandas as pd
 import yaml
 from pydantic import BaseModel
 
@@ -42,12 +42,12 @@ def _generic_load_yaml(data: str, model: BaseModel) -> BaseModel:
     return model.model_validate(yaml.safe_load(data))
 
 
-
 def mfp_to_yaml(excel_file_path: str, save_directory: str):
     """
     Generates a YAML file (`schedule.yaml`) with spatial and temporal information based on instrument data from MFP excel file.
 
-    Parameters:
+    Parameters
+    ----------
     - excel_file_path (str): Path to the Excel file containing coordinate and instrument data.
     - save_directory (str): Directory where `schedule.yaml` will be saved.
 
@@ -56,10 +56,13 @@ def mfp_to_yaml(excel_file_path: str, save_directory: str):
     2. Determines the maximum depth and buffer based on the instruments present.
     3. Ensures longitude and latitude values remain valid after applying buffer adjustments.
     4. Saves `schedule.yaml` in the specified directory.
-    """
 
+    """
     # Read data from Excel
-    coordinates_data = pd.read_excel(excel_file_path, usecols=["Station Type", "Name", "Latitude", "Longitude", "Instrument"])
+    coordinates_data = pd.read_excel(
+        excel_file_path,
+        usecols=["Station Type", "Name", "Latitude", "Longitude", "Instrument"],
+    )
     coordinates_data = coordinates_data.dropna()
 
     # Define maximum depth and buffer for each instrument
@@ -70,14 +73,22 @@ def mfp_to_yaml(excel_file_path: str, save_directory: str):
     }
 
     # Extract unique instruments from dataset
-    unique_instruments = np.unique(np.hstack(coordinates_data["Instrument"].apply(lambda a: a.split(", ")).values))
+    unique_instruments = np.unique(
+        np.hstack(coordinates_data["Instrument"].apply(lambda a: a.split(", ")).values)
+    )
 
     # Determine the maximum depth based on the unique instruments
-    maximum_depth = max(instrument_properties.get(inst, {"depth": 0})["depth"] for inst in unique_instruments)
+    maximum_depth = max(
+        instrument_properties.get(inst, {"depth": 0})["depth"]
+        for inst in unique_instruments
+    )
     minimum_depth = 0
 
     # Determine the buffer based on the maximum buffer of the instruments present
-    buffer = max(instrument_properties.get(inst, {"buffer": 0})["buffer"] for inst in unique_instruments)
+    buffer = max(
+        instrument_properties.get(inst, {"buffer": 0})["buffer"]
+        for inst in unique_instruments
+    )
 
     # Adjusted spatial range
     min_longitude = coordinates_data["Longitude"].min() - buffer
@@ -98,10 +109,10 @@ def mfp_to_yaml(excel_file_path: str, save_directory: str):
             },
             "time_range": {
                 "start_time": "",  # Blank start time
-                "end_time": "",    # Blank end time
-            }
+                "end_time": "",  # Blank end time
+            },
         },
-        "waypoints": []
+        "waypoints": [],
     }
 
     # Populate waypoints
@@ -112,16 +123,16 @@ def mfp_to_yaml(excel_file_path: str, save_directory: str):
                 "instrument": instrument,
                 "location": {
                     "latitude": row["Latitude"],
-                    "longitude": row["Longitude"]
+                    "longitude": row["Longitude"],
                 },
-                "time": ""  # Blank time
+                "time": "",  # Blank time
             }
             yaml_output["waypoints"].append(waypoint)
 
     # Ensure save directory exists
     os.makedirs(save_directory, exist_ok=True)
-    
+
     # Save the YAML file
     yaml_file_path = os.path.join(save_directory, SCHEDULE)
-    with open(yaml_file_path, 'w') as file:
+    with open(yaml_file_path, "w") as file:
         yaml.dump(yaml_output, file, default_flow_style=False)