2 files changed, 12 insertions, 19 deletions
diff --git a/wqflask/wqflask/my_pylmm/pyLMM/genotype.py b/wqflask/wqflask/my_pylmm/pyLMM/genotype.py
index e2457f6b..f5d9ee8c 100644
--- a/wqflask/wqflask/my_pylmm/pyLMM/genotype.py
+++ b/wqflask/wqflask/my_pylmm/pyLMM/genotype.py
@@ -18,20 +18,19 @@
 
 import numpy as np
 from collections import Counter
+import operator
 
 def replace_missing_with_MAF(snp_g):
     """
     Replace the missing genotype with the minor allele frequency (MAF)
     in the snp row
     """
-    g1 = np.copy(snp_g)
-    cnt = Counter(g1)
-    print cnt
-    min_val = min(cnt.itervalues())
-    print "min_val=",min_val
-    l = [k for k, v in cnt.iteritems() if v == min_val and not np.isnan(k)]
-    print "l=",l[0]
-    return [l[0] if np.isnan(snp) else snp for snp in g1] 
+    cnt = Counter(snp_g)
+    tuples = sorted(cnt.items(), key=operator.itemgetter(1))
+    l2 = [t for t in tuples if not np.isnan(t[0])]
+    maf = l2[0][0]
+    res = np.array([maf if np.isnan(snp) else snp for snp in snp_g])
+    return res
     
 def normalize(ind_g):
     """
diff --git a/wqflask/wqflask/my_pylmm/pyLMM/runlmm.py b/wqflask/wqflask/my_pylmm/pyLMM/runlmm.py
index ffe25fcf..0b8830d4 100644
--- a/wqflask/wqflask/my_pylmm/pyLMM/runlmm.py
+++ b/wqflask/wqflask/my_pylmm/pyLMM/runlmm.py
@@ -115,18 +115,12 @@ if cmd == 'redis':
     assert(options.testing and round(ps[-1],4)==0.3461)
 elif cmd == 'kinship':
     G = g
-    print G.shape, "\n", G
+    print "Original G",G.shape, "\n", G
     if options.maf_normalization:
-        g1 = np.apply_along_axis( genotype.replace_missing_with_MAF, axis=0, arr=g )
-        print "MAF: ",g1
-    sys.exit()
-    for ind_g in g:
-        if len(gn)>=8000: break
-        if options.skip_genotype_normalization:
-            gn.append(ind_g)
-        else:
-            gn.append( genotype.normalize(ind_g) )
-        G = np.array(gn)
+        G = np.apply_along_axis( genotype.replace_missing_with_MAF, axis=0, arr=g )
+        print "MAF replacements: \n",G
+    if not options.skip_genotype_normalization:
+        G = np.apply_along_axis( genotype.normalize, axis=1, arr=G)
             
     print G.shape, "\n", G
     K = kinship_full(G,options)