diff options
| -rw-r--r-- | wqflask/wqflask/my_pylmm/pyLMM/runlmm.py | 22 |
1 files changed, 11 insertions, 11 deletions
diff --git a/wqflask/wqflask/my_pylmm/pyLMM/runlmm.py b/wqflask/wqflask/my_pylmm/pyLMM/runlmm.py index e64ca0e6..d22e2912 100644 --- a/wqflask/wqflask/my_pylmm/pyLMM/runlmm.py +++ b/wqflask/wqflask/my_pylmm/pyLMM/runlmm.py @@ -88,29 +88,28 @@ if options.geno: g = tsvreader.geno(options.geno) print g.shape -def normalizeGenotype(G): +def normalizeGenotype(g1): + g = np.copy(g1) # avoid side effects # Run for every SNP list (num individuals) - x = True - np.isnan(G) # Matrix of True/False - m = G[x].mean() # Global mean value + x = True - np.isnan(g) # Matrix of True/False + m = g[x].mean() # Global mean value # print m - s = np.sqrt(G[x].var()) # Global stddev + s = np.sqrt(g[x].var()) # Global stddev # print s - G[np.isnan(G)] = m # Plug-in mean values for missing + g[np.isnan(g)] = m # Plug-in mean values for missing if s == 0: - G = G - m # Subtract the mean + g = g - m # Subtract the mean else: - G = (G - m) / s # Normalize the deviation - return G + g = (g - m) / s # Normalize the deviation + return g gn = [] for snp in g: gn.append( normalizeGenotype(snp) ) -gn = g - print("Before",g) -gT = g.T +gT = np.array(gn).T print("After",gT) G = np.array(gT) print "G shape",G.shape @@ -129,6 +128,7 @@ if cmd == 'redis': print G ps, ts = gn2_load_redis('testrun','other',np.array(k),y,G,options.testing) print np.array(ps) + assert(options.testing and ps[0]==0.726205761108) elif cmd == 'kinship': gn = [] for snp in G.T: |