--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/infernal.py	Tue Apr 22 13:56:22 2014 -0400
@@ -0,0 +1,128 @@
+# -*- coding: utf-8 -*-
+
+from galaxy.datatypes.data import Text
+from galaxy.datatypes.sniff import get_headers, get_test_fname
+from galaxy.datatypes.data import get_file_peek
+import subprocess
+import os
+
+from galaxy.datatypes.metadata import MetadataElement
+from galaxy.datatypes import metadata
+
+def count_special_lines( word, filename, invert = False ):
+    """
+        searching for special 'words' using the grep tool
+        grep is used to speed up the searching and counting
+        The number of hits is returned.
+    """
+    try:
+        cmd = ["grep", "-c"]
+        if invert:
+            cmd.append('-v')
+        cmd.extend([word, filename])
+        out = subprocess.Popen(cmd, stdout=subprocess.PIPE)
+        return int(out.communicate()[0].split()[0])
+    except:
+        pass
+    return 0
+
+def count_lines( filename, non_empty = False):
+    """
+        counting the number of lines from the 'filename' file
+    """
+    try:
+        if non_empty:
+            out = subprocess.Popen(['grep', '-cve', '^\s*$', filename], stdout=subprocess.PIPE)
+        else:
+            out = subprocess.Popen(['wc', '-l', filename], stdout=subprocess.PIPE)
+        return int(out.communicate()[0].split()[0])
+    except:
+        pass
+    return 0
+
+
+class Infernal_CM_1_1( Text ):
+    file_ext = "cm"
+
+    MetadataElement( name="number_of_models", default=0, desc="Number of covariance models", readonly=True, visible=True, optional=True, no_value=0 )
+
+    def set_peek( self, dataset, is_multi_byte=False ):
+        if not dataset.dataset.purged:
+            dataset.peek = get_file_peek( dataset.file_name, is_multi_byte=is_multi_byte )
+            if (dataset.metadata.number_of_models == 1):
+                dataset.blurb = "1 model"
+            else:
+                dataset.blurb = "%s models" % dataset.metadata.number_of_models
+            dataset.peek = data.get_file_peek( dataset.file_name, is_multi_byte=is_multi_byte )
+        else:
+            dataset.peek = 'file does not exist'
+            dataset.blurb = 'file purged from disc'
+
+    def sniff( self, filename ):
+        if count_special_lines("^INFERNAL1/a", filename) > 0:
+            return True
+        else:
+            return False
+
+    def set_meta( self, dataset, **kwd ):
+        """
+        Set the number of models in dataset.
+        """
+        dataset.metadata.number_of_models = count_special_lines("^INFERNAL1/a", dataset.file_name)
+
+    def split( cls, input_datasets, subdir_generator_function, split_params):
+        """
+        Split the input files by model records.
+        """
+        if split_params is None:
+            return None
+
+        if len(input_datasets) > 1:
+            raise Exception("CM-file splitting does not support multiple files")
+        input_files = [ds.file_name for ds in input_datasets]
+
+        chunk_size = None
+        if split_params['split_mode'] == 'number_of_parts':
+            raise Exception('Split mode "%s" is currently not implemented for CM-files.' % split_params['split_mode'])
+        elif split_params['split_mode'] == 'to_size':
+            chunk_size = int(split_params['split_size'])
+        else:
+            raise Exception('Unsupported split mode %s' % split_params['split_mode'])
+
+        def _read_cm_records( filename ):
+            lines = []
+            with open(filename) as handle:
+                for line in handle:
+                    if line.startswith("INFERNAL1/a") and lines:
+                        yield lines
+                        lines = [line]
+                    else:
+                        lines.append( line )
+            yield lines
+
+        def _write_part_cm_file( accumulated_lines ):
+            part_dir = subdir_generator_function()
+            part_path = os.path.join( part_dir, os.path.basename( input_files[0] ) )
+            part_file = open( part_path, 'w' )
+            part_file.writelines( accumulated_lines )
+            part_file.close()
+
+        try:
+            cm_records = _read_cm_records( input_files[0] )
+            cm_lines_accumulated = []
+            for counter, cm_record in enumerate( cm_records, start = 1):
+                cm_lines_accumulated.extend( cm_record )
+                if counter % chunk_size == 0:
+                    _write_part_cm_file( cm_lines_accumulated )
+                    cm_lines_accumulated = []
+            if cm_lines_accumulated:
+                _write_part_cm_file( cm_lines_accumulated )
+        except Exception,  e:
+            log.error('Unable to split files: %s' % str(e))
+            raise
+    split = classmethod(split)
+
+if __name__ == '__main__':
+    Infernal_CM_1_1()
+    Stockholm_1_0()
+