def test_profile_mut_bin_noerr(self):
        """ Test the ability of sortseq_tools.profile_mut to compute mutation rates
        """

        print '\nIn test_profile_mut_bin_noerr_...'
        library_files = glob.glob(self.input_dir+'library_*.txt')
        library_files += glob.glob(self.input_dir+'dataset_*.txt')
        good_bin_num = 2
        bad_bin_num = 5
        for file_name in library_files:
            print '\t%s ='%file_name,
            description = file_name.split('_')[-1].split('.')[0]
            executable = lambda:\
                profile_mut.main(io.load_dataset(file_name),bin=good_bin_num,err=False)
            print '(bin=%d)'%good_bin_num,

            # If bad or library, then profile_mut.main should raise SortSeqError
            if ('_bad' in file_name) or ('library' in file_name):
                try:
                    self.assertRaises(SortSeqError,executable)
                    print 'badtype,',
                except:
                    print 'good (ERROR).'
                    raise

            # If good, then profile_mut.main should produce a valid df
            elif '_good' in file_name:
                try:
                    df = executable()
                    qc.validate_profile_mut(df)
                    out_file = self.output_dir+\
                        'profile_mut_bin_noerr_%s.txt'%description
                    io.write(df,out_file)           # Test writing
                    io.load_profile_mut(out_file)   # Test loading
                    print 'good,',

                except:
                    print 'bad (ERROR).'
                    raise

            # There are no other options
            else:
                raise SortSeqError('Unrecognized class of file_name.')

            # Should always raise an error if bin num is too large
            executable = lambda:\
                profile_mut.main(io.load_dataset(file_name),bin=bad_bin_num)
            print '(bin=%d)'%bad_bin_num,
            try:
                self.assertRaises(SortSeqError,executable)
                print 'badtype.'
            except:
                print 'good (ERROR).'
                raise
    def test_profile_mut_total_err(self):
        """ Test the ability of sortseq_tools.profile_mut to compute mutation rates based on total count values
        """

        print '\nIn test_profile_mut_total_err...'
        library_files = glob.glob(self.input_dir+'library_*.txt')
        library_files += glob.glob(self.input_dir+'dataset_*.txt')
        for file_name in library_files:
            print '\t%s ='%file_name,
            description = file_name.split('_')[-1].split('.')[0]
            executable = lambda: profile_mut.main(io.load_dataset(file_name),err=True)

            # If good, then profile_mut.main should produce a valid df
            if '_good' in file_name:
                try:
                    df = executable()
                    qc.validate_profile_mut(df)
                    out_file = self.output_dir+\
                        'profile_mut_total_err_%s.txt'%description
                    io.write(df,out_file)
                    io.load_profile_mut(out_file)
                    print 'good.'
                except:
                    print 'bad (ERROR).'
                    raise

            # If bad, then profile_mut.main should raise SortSeqError
            elif '_bad' in file_name:
                try:
                    self.assertRaises(SortSeqError,executable)
                    print 'badtype.'
                except:
                    print 'good (ERROR).'
                    raise

            # There are no other options
            else:
                raise SortSeqError('Unrecognized class of file_name.')