comparison COBRAxy/utils/model_utils.py @ 505:96f512dff490 draft

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504:ef3df9b697b1

        pathway_data.append(row)

    return pd.DataFrame(pathway_data)



def build_cobra_model_from_csv(csv_path: str, model_id: str = "new_model") -> cobraModel:
    """
    Build a COBRApy model from a tabular file with reaction data.

    
    # set objective function
    set_objective_from_csv(model, df, obj_col="ObjectiveCoefficient")

    set_medium_from_data(model, df)
    
    print(f"Model completed: {len(model.reactions)} reactions, {len(model.metabolites)} metabolites")
    
    return model

505:96f512dff490

        pathway_data.append(row)

    return pd.DataFrame(pathway_data)

def set_annotation_pathways_from_data(model: cobraModel, df: pd.DataFrame):
    """Set reaction pathways based on 'Pathway_1', 'Pathway_2', ... columns in the dataframe."""
    pathway_cols = [col for col in df.columns if col.startswith('Pathway_')]
    if not pathway_cols:
        print("No 'Pathway_' columns found, skipping pathway annotation")
        return
    
    pathway_data = defaultdict(list)
    
    for idx, row in df.iterrows():
        reaction_id = str(row['ReactionID']).strip()
        if reaction_id not in model.reactions:
            continue
        
        pathways = []
        for col in pathway_cols:
            if pd.notna(row[col]) and str(row[col]).strip():
                pathways.append(str(row[col]).strip())
        
        if pathways:
            
            reaction = model.reactions.get_by_id(reaction_id)
            if len(pathways) == 1:
                reaction.annotation['pathways'] = pathways[0]
            else:
                reaction.annotation['pathways'] = pathways

            pathway_data[reaction_id] = pathways
    
    print(f"Annotated {len(pathway_data)} reactions with pathways.")

def build_cobra_model_from_csv(csv_path: str, model_id: str = "new_model") -> cobraModel:
    """
    Build a COBRApy model from a tabular file with reaction data.

    
    # set objective function
    set_objective_from_csv(model, df, obj_col="ObjectiveCoefficient")

    set_medium_from_data(model, df)

    set_annotation_pathways_from_data(model, df)
    
    print(f"Model completed: {len(model.reactions)} reactions, {len(model.metabolites)} metabolites")
    
    return model