def smear_gg():
ggn = nu.net_genegene()
img = array(ggn)
s = shape(img)
for i in range(s[1]):
img[:,i] = np.sort(img[:,i])[::-1]/ np.max(img[:,i])
sums = np.sum(img ** 2,0)
img = img[:, np.argsort(sums)[::-1]]
draw_smear(img[::xskip,::yskip])
def net_cluster_gg(k = k, reset = 0):
hardcopy = True
try:
if reset: raise Exception('compute')
out,sxs = nw.rn2(name, hardcopy = hardcopy)
if not sxs: raise Exception()
except Exception as e:
if e.args[0] != 'compute': raise Exception()
nw.claim_reset()
gg = nu.net_genegene(reset = mod(reset,2))
kmeans = mlpy.Kmeans(k)
clustered = kmeans.compute(gg[0:maxgenes,:])
means = kmeans.means
out = (clustered,means)
nw.wn2(name, (clustered, means) ,hardcopy = hardcopy)
return out