changeset 285:7a098cb82865 draft

Uploaded

--- a/marea_2/ras_to_bounds.py	Sun Aug 04 18:38:11 2024 +0000
+++ b/marea_2/ras_to_bounds.py	Sun Aug 04 18:38:30 2024 +0000
@@ -103,6 +103,17 @@
 
 
 def apply_ras_bounds(model, ras_row, rxns_ids):
+    """
+    Adjust the bounds of reactions in the model based on RAS values.
+
+    Args:
+        model (cobra.Model): The metabolic model to be modified.
+        ras_row (pd.Series): A row from a RAS DataFrame containing scaling factors for reaction bounds.
+        rxns_ids (list of str): List of reaction IDs to which the scaling factors will be applied.
+    
+    Returns:
+        None
+    """
     for reaction in rxns_ids:
         if reaction in ras_row.index and pd.notna(ras_row[reaction]):
             rxn = model.reactions.get_by_id(reaction)
@@ -111,12 +122,37 @@
             rxn.upper_bound *= scaling_factor
 
 def process_ras_cell(cellName, ras_row, model, rxns_ids, output_folder):
+    """
+    Process a single RAS cell, apply bounds, and save the bounds to a CSV file.
+
+    Args:
+        cellName (str): The name of the RAS cell (used for naming the output file).
+        ras_row (pd.Series): A row from a RAS DataFrame containing scaling factors for reaction bounds.
+        model (cobra.Model): The metabolic model to be modified.
+        rxns_ids (list of str): List of reaction IDs to which the scaling factors will be applied.
+        output_folder (str): Folder path where the output CSV file will be saved.
+    
+    Returns:
+        None
+    """
     model_new = model.copy()
     apply_ras_bounds(model_new, ras_row, rxns_ids)
     bounds = pd.DataFrame([(rxn.lower_bound, rxn.upper_bound) for rxn in model_new.reactions], index=rxns_ids, columns=["lower_bound", "upper_bound"])
     bounds.to_csv(output_folder + cellName + ".csv", sep='\t', index=True)
 
 def generate_bounds(model: cobra.Model, medium: dict, ras=None, output_folder='output/') -> pd.DataFrame:
+    """
+    Generate reaction bounds for a metabolic model based on medium conditions and optional RAS adjustments.
+    
+    Args:
+        model (cobra.Model): The metabolic model for which bounds will be generated.
+        medium (dict): A dictionary where keys are reaction IDs and values are the medium conditions.
+        ras (pd.DataFrame, optional): A DataFrame with RAS scaling factors for different cell types. Defaults to None.
+        output_folder (str, optional): Folder path where output CSV files will be saved. Defaults to 'output/'.
+
+    Returns:
+        pd.DataFrame: DataFrame containing the bounds of reactions in the model.
+    """
     rxns_ids = [rxn.id for rxn in model.reactions]
     
     # Set medium conditions