Mercurial > repos > bimib > cobraxy
comparison COBRAxy/flux_simulation_beta.py @ 430:f49c951c9fe6 draft
Uploaded
| author | francesco_lapi |
|---|---|
| date | Wed, 10 Sep 2025 14:53:36 +0000 |
| parents | 27c5a67f1ee6 |
| children | a6e45049c1b9 |
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| 429:0485c4b1943d | 430:f49c951c9fe6 |
|---|---|
| 77 | 77 |
| 78 parser.add_argument('-nb', '--n_batches', | 78 parser.add_argument('-nb', '--n_batches', |
| 79 type = int, | 79 type = int, |
| 80 required = True, | 80 required = True, |
| 81 help = 'choose how many batches') | 81 help = 'choose how many batches') |
| 82 | |
| 83 parser.add_argument('-opt', '--perc_opt', | |
| 84 type = float, | |
| 85 default=0.9, | |
| 86 required = False, | |
| 87 help = 'choose the fraction of optimality for FVA (0-1)') | |
| 82 | 88 |
| 83 parser.add_argument('-ot', '--output_type', | 89 parser.add_argument('-ot', '--output_type', |
| 84 type = str, | 90 type = str, |
| 85 required = True, | 91 required = True, |
| 86 help = 'output type') | 92 help = 'output type') |
| 357 df_pFBA.loc[0,[rxn.id for rxn in model.reactions]] = fluxes.tolist() | 363 df_pFBA.loc[0,[rxn.id for rxn in model.reactions]] = fluxes.tolist() |
| 358 df_pFBA = df_pFBA.reset_index(drop=True) | 364 df_pFBA = df_pFBA.reset_index(drop=True) |
| 359 df_pFBA.index = [model_name] | 365 df_pFBA.index = [model_name] |
| 360 df_pFBA = df_pFBA.astype(float).round(6) | 366 df_pFBA = df_pFBA.astype(float).round(6) |
| 361 elif(output_type == "FVA"): | 367 elif(output_type == "FVA"): |
| 362 fva = cobra.flux_analysis.flux_variability_analysis(model, fraction_of_optimum=0, processes=1).round(8) | 368 fva = cobra.flux_analysis.flux_variability_analysis(model, fraction_of_optimum=ARGS.perc_opt, processes=1).round(8) |
| 363 columns = [] | 369 columns = [] |
| 364 for rxn in fva.index.to_list(): | 370 for rxn in fva.index.to_list(): |
| 365 columns.append(rxn + "_min") | 371 columns.append(rxn + "_min") |
| 366 columns.append(rxn + "_max") | 372 columns.append(rxn + "_max") |
| 367 df_FVA= pd.DataFrame(columns = columns) | 373 df_FVA= pd.DataFrame(columns = columns) |