comparison mothur/lib/galaxy/datatypes/metagenomics.py @ 32:ec8df51e841a

Fixes courtesy of Peter Briggs: metagenomics.py: - Groups class: Fix for when second column not present - Axes class: make 'sniff' method more sensitive to try and restrict arbitrary tabular data uploads being sniffed as this type mothur_wrapper.py: - update cmd_dict['chimera.perseus'], to use correct inputs - add --beta option (needed for chimera.perseus tool) - add function for converting input floats from scientific notation (e.g. 1e-6, which mothur can't handle) to decimal format (e.g. 0.00001, which it can) chimera.perseus.xml: - add output data item for the "accnos" file (not previous captured in the history) trim.flows.xml: - cosmetic change: base name for additional output data items is now "trim.flows", rather than "logfile" (clarifies history items) shhh.flows.xml: - cosmetic change: update default value specified in help for mindiff to be consistent with that given in the mothur documentation

31:a3eed59297ea

        group_names = set() 
        try:
            fh = open( dataset.file_name )
            for line in fh:
                fields = line.strip().split('\t')
                group_names.add(fields[1])
            dataset.metadata.groups = []
            dataset.metadata.groups += group_names
        finally:
            fh.close()

                        if len(fields) != col_cnt :
                            return False
                        try:
                            for i in range(1, col_cnt):
                                check = float(fields[i])
                                # Also test for whether value is an integer
                                try:
                                    check = int(fields[i])
                                except ValueError:
                                    all_integers = False

32:ec8df51e841a

        group_names = set() 
        try:
            fh = open( dataset.file_name )
            for line in fh:
                fields = line.strip().split('\t')
                try:
                    group_names.add(fields[1])
                except IndexError:
                    # Ignore missing 2nd column
                    pass
            dataset.metadata.groups = []
            dataset.metadata.groups += group_names
        finally:
            fh.close()

                        if len(fields) != col_cnt :
                            return False
                        try:
                            for i in range(1, col_cnt):
                                check = float(fields[i])
                                # Check abs value is <= 1.0
                                if abs(check) > 1.0:
                                    return False
                                # Also test for whether value is an integer
                                try:
                                    check = int(fields[i])
                                except ValueError:
                                    all_integers = False