2 files changed, 49 insertions, 1 deletions
diff --git a/wqflask/wqflask/my_pylmm/pyLMM/convertlmm.py b/wqflask/wqflask/my_pylmm/pyLMM/convertlmm.py
index 35fccef4..012e96b2 100644
--- a/wqflask/wqflask/my_pylmm/pyLMM/convertlmm.py
+++ b/wqflask/wqflask/my_pylmm/pyLMM/convertlmm.py
@@ -23,7 +23,6 @@ import numpy as np
 # from lmm import LMM, run_other
 import input
 
-
 usage = """
 python convertlmm.py [--kinship] infile 
 
diff --git a/wqflask/wqflask/my_pylmm/pyLMM/runlmm.py b/wqflask/wqflask/my_pylmm/pyLMM/runlmm.py
index df86f718..4a640d6d 100644
--- a/wqflask/wqflask/my_pylmm/pyLMM/runlmm.py
+++ b/wqflask/wqflask/my_pylmm/pyLMM/runlmm.py
@@ -17,4 +17,53 @@
 # You should have received a copy of the GNU Affero General Public License
 # along with this program.  If not, see <http://www.gnu.org/licenses/>.
 
+from optparse import OptionParser
+import sys
+import os
+import numpy as np
+# from lmm import LMM, run_other
+import csv
 
+
+usage = """
+python runlmm.py [options] command
+
+  runlmm.py processing multiplexer reads standard input types and calls the routines
+
+  Current commands are:
+
+    parse        : only parse input files
+
+  try --help for more information
+"""
+
+parser = OptionParser(usage=usage)
+# parser.add_option("-f", "--file", dest="input file",
+#                   help="In", metavar="FILE")
+parser.add_option("--kinship",dest="kinship",
+                  help="Kinship file format")
+parser.add_option("-q", "--quiet",
+                  action="store_false", dest="verbose", default=True,
+                  help="don't print status messages to stdout")
+
+(options, args) = parser.parse_args()
+
+if len(args) != 1:
+    print usage
+    sys.exit(1)
+
+cmd = args[0]
+print "Command: ",cmd
+
+if options.kinship:
+    K1 = []
+    print options.kinship
+    with open(options.kinship,'r') as tsvin:
+        assert(tsvin.readline().strip() == "# Kinship format version 1.0")
+        tsvin.readline()
+        tsvin.readline()
+        tsv = csv.reader(tsvin, delimiter='\t')
+        for row in tsv:
+            ns = np.genfromtxt(row[1:])
+            K1.append(ns) # <--- slow
+    K = np.array(K1)