Mercurial > repos > bimib > cobraxy
comparison COBRAxy/ras_to_bounds.py @ 123:258ff4208e52 draft
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author | luca_milaz |
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date | Mon, 14 Oct 2024 08:29:08 +0000 |
parents | 7e1ce04cf192 |
children | 67a79e4f037a |
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122:7e1ce04cf192 | 123:258ff4208e52 |
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123 Returns: | 123 Returns: |
124 None | 124 None |
125 """ | 125 """ |
126 for reaction in ras_row.index: | 126 for reaction in ras_row.index: |
127 scaling_factor = ras_row[reaction] | 127 scaling_factor = ras_row[reaction] |
128 if(scaling_factor not in [np.nan, None]): | 128 lower_bound=model.reactions.get_by_id(reaction).lower_bound |
129 lower_bound=model.reactions.get_by_id(reaction).lower_bound | 129 upper_bound=model.reactions.get_by_id(reaction).upper_bound |
130 upper_bound=model.reactions.get_by_id(reaction).upper_bound | 130 valMax=float((upper_bound)*scaling_factor) |
131 valMax=float((upper_bound)*scaling_factor) | 131 valMin=float((lower_bound)*scaling_factor) |
132 valMin=float((lower_bound)*scaling_factor) | 132 if upper_bound!=0 and lower_bound==0: |
133 if upper_bound!=0 and lower_bound==0: | 133 model.reactions.get_by_id(reaction).upper_bound=valMax |
134 model.reactions.get_by_id(reaction).upper_bound=valMax | 134 if upper_bound==0 and lower_bound!=0: |
135 if upper_bound==0 and lower_bound!=0: | 135 model.reactions.get_by_id(reaction).lower_bound=valMin |
136 model.reactions.get_by_id(reaction).lower_bound=valMin | 136 if upper_bound!=0 and lower_bound!=0: |
137 if upper_bound!=0 and lower_bound!=0: | 137 model.reactions.get_by_id(reaction).lower_bound=valMin |
138 model.reactions.get_by_id(reaction).lower_bound=valMin | 138 model.reactions.get_by_id(reaction).upper_bound=valMax |
139 model.reactions.get_by_id(reaction).upper_bound=valMax | |
140 pass | 139 pass |
141 | 140 |
142 def process_ras_cell(cellName, ras_row, model, rxns_ids, mediumRxns_ids, output_folder): | 141 def process_ras_cell(cellName, ras_row, model, rxns_ids, mediumRxns_ids, output_folder): |
143 """ | 142 """ |
144 Process a single RAS cell, apply bounds, and save the bounds to a CSV file. | 143 Process a single RAS cell, apply bounds, and save the bounds to a CSV file. |
246 | 245 |
247 # Concatenate all ras DataFrames into a single DataFrame | 246 # Concatenate all ras DataFrames into a single DataFrame |
248 ras_combined = pd.concat(ras_list, axis=0) | 247 ras_combined = pd.concat(ras_list, axis=0) |
249 # Normalize the RAS values by max RAS | 248 # Normalize the RAS values by max RAS |
250 ras_combined = ras_combined.div(ras_combined.max(axis=0)) | 249 ras_combined = ras_combined.div(ras_combined.max(axis=0)) |
250 ras_combined.dropna(axis=1, how='all', inplace=True) | |
251 #ras_combined = ras_combined.fillna(0) | 251 #ras_combined = ras_combined.fillna(0) |
252 #il ras c'è per tutti o non c'è per nessuno | 252 #il ras c'è per tutti o non c'è per nessuno |
253 | 253 |
254 | 254 |
255 | 255 |