comparison COBRAxy/ras_to_bounds.py @ 114:a7a079f6a4cd draft

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113:1961a091484c

        mediumRxns_ids (list of str): List of reaction IDs in the medium. Their RAS is set to zero, but they are already set in the model.
    Returns:
        None
    """
    for reaction in rxns_ids:
        if reaction in ras_row.index and ras_row[reaction] not in mediumRxns_ids:
            scaling_factor = ras_row[reaction]
            lower_bound=model.reactions.get_by_id(reaction).lower_bound
            upper_bound=model.reactions.get_by_id(reaction).upper_bound
            valMax=float((upper_bound)*scaling_factor)
            valMin=float((lower_bound)*scaling_factor)

    
    # Set FVA bounds
    for reaction in rxns_ids:
        model.reactions.get_by_id(reaction).lower_bound = float(df_FVA.loc[reaction, "minimum"])
        model.reactions.get_by_id(reaction).upper_bound = float(df_FVA.loc[reaction, "maximum"])

    #warning(str(model.reactions.get_by_id("EX_Lcystin_e").lower_bound))

    if ras is not None:
        #Parallel(n_jobs=cpu_count())(delayed(process_ras_cell)(cellName, ras_row, model, rxns_ids, output_folder) for cellName, ras_row in ras.iterrows())
        for cellName, ras_row in ras.iterrows():
            process_ras_cell(cellName, ras_row, model, rxns_ids, mediumRxns_ids, output_folder)

114:a7a079f6a4cd

        mediumRxns_ids (list of str): List of reaction IDs in the medium. Their RAS is set to zero, but they are already set in the model.
    Returns:
        None
    """
    for reaction in rxns_ids:
        if reaction in ras_row.index and reaction not in mediumRxns_ids:
            scaling_factor = ras_row[reaction]
            lower_bound=model.reactions.get_by_id(reaction).lower_bound
            upper_bound=model.reactions.get_by_id(reaction).upper_bound
            valMax=float((upper_bound)*scaling_factor)
            valMin=float((lower_bound)*scaling_factor)

    
    # Set FVA bounds
    for reaction in rxns_ids:
        model.reactions.get_by_id(reaction).lower_bound = float(df_FVA.loc[reaction, "minimum"])
        model.reactions.get_by_id(reaction).upper_bound = float(df_FVA.loc[reaction, "maximum"])

    if ras is not None:
        #Parallel(n_jobs=cpu_count())(delayed(process_ras_cell)(cellName, ras_row, model, rxns_ids, output_folder) for cellName, ras_row in ras.iterrows())
        for cellName, ras_row in ras.iterrows():
            process_ras_cell(cellName, ras_row, model, rxns_ids, mediumRxns_ids, output_folder)