Mercurial > repos > bimib > cobraxy

comparison COBRAxy/ras_to_bounds.py @ 107:58919e82d96e draft

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Uploaded
author luca_milaz
date Sun, 13 Oct 2024 14:06:53 +0000
parents 1629671d4ca6
children 22cebbdb4b6d
comparison
equal deleted inserted replaced
106:1629671d4ca6 107:58919e82d96e
183 if(reaction == "EX_lac__L_e"): 183 if(reaction == "EX_lac__L_e"):
184 model2.reactions.get_by_id(reaction).lower_bound=float(0.0) 184 model2.reactions.get_by_id(reaction).lower_bound=float(0.0)
185 ''' 185 '''
186 for reaction, value in medium.items(): 186 for reaction, value in medium.items():
187 if value is not None: 187 if value is not None:
188 model.reactions.get_by_id(reaction).lower_bound = -float(value) 188 if(reaction != "EX_thbpt_e" and reaction != "EX_lac__L_e"):
189 model.reactions.get_by_id(reaction).lower_bound = -float(value)
190 if(reaction == "EX_lac__L_e"):
191 model.reactions.get_by_id(reaction).lower_bound = float(0.0)
192
189 193
190 # Perform Flux Variability Analysis (FVA) 194 # Perform Flux Variability Analysis (FVA)
191 df_FVA = cobra.flux_analysis.flux_variability_analysis(model, fraction_of_optimum=0, processes=1).round(8) 195 df_FVA = cobra.flux_analysis.flux_variability_analysis(model, fraction_of_optimum=0, processes=1).round(8)
192 196
193 # Set FVA bounds 197 # Set FVA bounds
197 201
198 if ras is not None: 202 if ras is not None:
199 #Parallel(n_jobs=cpu_count())(delayed(process_ras_cell)(cellName, ras_row, model, rxns_ids, output_folder) for cellName, ras_row in ras.iterrows()) 203 #Parallel(n_jobs=cpu_count())(delayed(process_ras_cell)(cellName, ras_row, model, rxns_ids, output_folder) for cellName, ras_row in ras.iterrows())
200 for cellName, ras_row in ras.iterrows(): 204 for cellName, ras_row in ras.iterrows():
201 process_ras_cell(cellName, ras_row, model, rxns_ids, output_folder) 205 process_ras_cell(cellName, ras_row, model, rxns_ids, output_folder)
202 break 206 break #just one cell for testing
203 else: 207 else:
204 model_new = model.copy() 208 model_new = model.copy()
205 apply_ras_bounds(model_new, pd.Series([1]*len(rxns_ids), index=rxns_ids), rxns_ids) 209 apply_ras_bounds(model_new, pd.Series([1]*len(rxns_ids), index=rxns_ids), rxns_ids)
206 bounds = pd.DataFrame([(rxn.lower_bound, rxn.upper_bound) for rxn in model_new.reactions], index=rxns_ids, columns=["lower_bound", "upper_bound"]) 210 bounds = pd.DataFrame([(rxn.lower_bound, rxn.upper_bound) for rxn in model_new.reactions], index=rxns_ids, columns=["lower_bound", "upper_bound"])
207 bounds.to_csv(output_folder + "bounds.csv", sep='\t', index=True) 211 bounds.to_csv(output_folder + "bounds.csv", sep='\t', index=True)