def cluster_structs(vecs,
ctype = 'mlpy',
k = None):
''' Return a list of cluster memberships in the form of an N-array having
k unique elements.
'''
if ctype == 'hcluster':
return hcluster.fclusterdata(vecs,1.1,criterion='inconsistent',method = 'complete' )
elif ctype == 'mlpy':
import mlpy
HC = mlpy.HCluster(method='euclidean', link='complete')
clusts = HC.compute(vecs )
cut = HC.cut(HC.heights[-k])
return cut
else:
raise Exception()
def get_clusters(aanTimbres): #linkage was example ... output didnt make sense to me. #return linkage(aanTimbres, method='complete') #was thinking, each instrument by each note maybe, but whatever return fclusterdata(aanTimbres, 50, criterion='maxclust')
def view3():
files = [l for l in os.listdir(cfg.dataPath("batch/tmp")) if "mcmc" in l]
fpaths = [os.path.join(cfg.dataPath("batch/tmp"), f) for f in files]
ids = [l[0:10] for l in files]
inps = [butils.load_data(i, "input") for i in ids]
idxs_good = nonzero(greater([elt.get("out_iter_num") for elt in inps], 2))[0]
inps = [inps[i] for i in idxs_good]
fpaths = [fpaths[i] for i in idxs_good]
fig = myplots.fignum(3, (35, 15))
ax = fig.add_axes([0, 0, 1, 1])
for f, inp in zip(fpaths, inps):
if inp["out_iter_num"] == 2:
continue
print inp["filename"]
data = sio.loadmat(f)
import compbio.utils.colors as mycolors
ct = mycolors.getct(len(data["gene_names"]))
term_list = [list(it.chain(*mod)) for mod in data["model"]]
fac_list = [list(it.chain(*t)) for t in term_list]
xvals, yvals, colors, rads = [], [], [], []
for i, terms in enumerate(term_list):
for j, term in enumerate(terms):
for k, fact in enumerate(term):
xvals.extend([i] * len(term))
yvals.extend([fact] * len(term))
colors.extend([ct[c] for c in sorted(term)])
rads.extend(((arange(1, len(term) + 1) ** 2) * 50)[::-1])
vecs = zeros((len(fac_list), len(fac_list)))
for i, fl in enumerate(fac_list):
for f in fl:
vecs[i, f] = 1
# plt.imshow(vecs)
# ax1 = fig.add_subplot(121)
# ax2 = fig.add_subplot(122)
import hcluster
clusters = hcluster.fclusterdata(vecs, 1.1, criterion="inconsistent", method="complete")
# ax1.imshow(vecs)
# ax2.imshow(vecs[argsort(clusters)])
# raise Exception()
csrt = argsort(argsort(clusters))
xvals2 = [csrt[x] for x in xvals]
# raise Exception()
plt.scatter(xvals2, yvals, rads, color=colors)
raise Exception()
raise Exception()
