Mercurial > repos > bimib > cobraxy
changeset 531:1fc5c1edb0ef draft default tip
Uploaded
| author | francesco_lapi |
|---|---|
| date | Wed, 22 Oct 2025 13:30:18 +0000 |
| parents | 352c51a39e23 |
| children | |
| files | COBRAxy/ras_generator.py |
| diffstat | 1 files changed, 19 insertions(+), 12 deletions(-) [+] |
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--- a/COBRAxy/ras_generator.py Wed Oct 22 12:18:07 2025 +0000 +++ b/COBRAxy/ras_generator.py Wed Oct 22 13:30:18 2025 +0000 @@ -282,7 +282,7 @@ def compute(self, or_expression=np.sum, # type of operation to do in case of an or expression (sum, max, mean) and_expression=np.min, # type of operation to do in case of an and expression(min, sum) - drop_na_rows=True, # if True remove the nan rows of the ras matrix + drop_na_rows=False, # if True remove the nan rows of the ras matrix drop_duplicates=False, # if true, remove duplicates rows ignore_nan=True, # if True, ignore NaN values in GPR evaluation (e.g., A or NaN -> A) print_progressbar=True, # if True, print the progress bar @@ -327,18 +327,25 @@ else: # Evaluate the GPR expression using AST # For single gene, AST handles it fine: ast.parse("GENE_A") works - try: + # more genes in the formula + check_only_and=("and" in rule and "or" not in rule) #only and + check_only_or=("or" in rule and "and" not in rule) #only or + if check_only_and or check_only_or: + #or/and sequence + matrix = self.count_df_filtered.loc[genes_present].values + #compute for all cells + if check_only_and: + ras_df[ind] = self.and_function(matrix, axis=0) + else: + ras_df[ind] = self.or_function(matrix, axis=0) + else: + # complex expression (e.g. A or (B and C)) + data = self.count_df_filtered.loc[genes_present] # dataframe of genes in the GPRs tree = ast.parse(rule, mode="eval").body - data = self.count_df_filtered.loc[genes_present] - - # Evaluate for each cell/sample - for j, col in enumerate(data.columns): - gene_values = dict(zip(data.index, data[col].values)) - ras_df[ind, j] = self._evaluate_ast(tree, gene_values, self.or_function, self.and_function, ignore_nan) - except: - # If parsing fails, keep as NaN - pass - + values_by_cell = [dict(zip(data.index, data[col].values)) for col in data.columns] + for j, values in enumerate(values_by_cell): + ras_df[ind, j] =self._evaluate_ast(tree, values, self.or_function, self.and_function, ignore_nan) + if print_progressbar: pbar.update(ind + 1)