Mercurial > repos > bimib > cobraxy

comparison COBRAxy/flux_simulation_beta.py @ 484:1c6fcf97cabe draft

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author luca_milaz
date Tue, 23 Sep 2025 07:19:29 +0000
parents ecaf3c9852b3
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comparison
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483:1d1fa7e274bb 484:1c6fcf97cabe
423 423
424 return df_mean, df_median, df_quantiles 424 return df_mean, df_median, df_quantiles
425 425
426 def fluxes_analysis(model:cobra.Model, model_name:str, output_types:List)-> List[pd.DataFrame]: 426 def fluxes_analysis(model:cobra.Model, model_name:str, output_types:List)-> List[pd.DataFrame]:
427 """ 427 """
428 Performs flux analysis including pFBA, FVA, and sensitivity analysis. 428 Performs flux analysis including pFBA, FVA, and sensitivity analysis. The objective function
429 is assumed to be already set in the model.
429 430
430 Args: 431 Args:
431 model (cobra.Model): The COBRA model to analyze. 432 model (cobra.Model): The COBRA model to analyze.
432 model_name (str): Name of the model, used in filenames for output. 433 model_name (str): Name of the model, used in filenames for output.
433 output_types (List[str]): Types of analysis to perform (pFBA, FVA, sensitivity). 434 output_types (List[str]): Types of analysis to perform (pFBA, FVA, sensitivity).
440 df_FVA= pd.DataFrame() 441 df_FVA= pd.DataFrame()
441 df_sensitivity= pd.DataFrame() 442 df_sensitivity= pd.DataFrame()
442 443
443 for output_type in output_types: 444 for output_type in output_types:
444 if(output_type == "pFBA"): 445 if(output_type == "pFBA"):
445 model.objective = "Biomass"
446 solution = cobra.flux_analysis.pfba(model) 446 solution = cobra.flux_analysis.pfba(model)
447 fluxes = solution.fluxes 447 fluxes = solution.fluxes
448 df_pFBA.loc[0,[rxn.id for rxn in model.reactions]] = fluxes.tolist() 448 df_pFBA.loc[0,[rxn.id for rxn in model.reactions]] = fluxes.tolist()
449 df_pFBA = df_pFBA.reset_index(drop=True) 449 df_pFBA = df_pFBA.reset_index(drop=True)
450 df_pFBA.index = [model_name] 450 df_pFBA.index = [model_name]
461 df_FVA.loc[0, index_rxn+ "_max"] = fva.loc[index_rxn, "maximum"] 461 df_FVA.loc[0, index_rxn+ "_max"] = fva.loc[index_rxn, "maximum"]
462 df_FVA = df_FVA.reset_index(drop=True) 462 df_FVA = df_FVA.reset_index(drop=True)
463 df_FVA.index = [model_name] 463 df_FVA.index = [model_name]
464 df_FVA = df_FVA.astype(float).round(6) 464 df_FVA = df_FVA.astype(float).round(6)
465 elif(output_type == "sensitivity"): 465 elif(output_type == "sensitivity"):
466 model.objective = "Biomass"
467 solution_original = model.optimize().objective_value 466 solution_original = model.optimize().objective_value
468 reactions = model.reactions 467 reactions = model.reactions
469 single = cobra.flux_analysis.single_reaction_deletion(model) 468 single = cobra.flux_analysis.single_reaction_deletion(model)
470 newRow = [] 469 newRow = []
471 df_sensitivity = pd.DataFrame(columns = [rxn.id for rxn in reactions], index = [model_name]) 470 df_sensitivity = pd.DataFrame(columns = [rxn.id for rxn in reactions], index = [model_name])