def test_tuning_scripts(self):
data = self.sc.parallelize([(1, array([1.5, 2.3, 6.2, 5.1, 3.4, 2.1]))])
x1 = array([array([1, 0, 1, 0, 1, 0]), array([0, 1, 0, 1, 0, 1])])
x2 = array([array([1, 1, 0, 0, 0, 0]), array([0, 0, 1, 1, 0, 0]), array([0, 0, 0, 0, 1, 1])])
s = array([-pi / 4, pi / 4, pi / 3])
params = tuning(data, s, "circular", (x1, x2), "bilinear")
params.collect()
params = tuning(data, s, "gaussian", (x1, x2), "bilinear")
params.collect()
s = array([-pi / 2, -pi / 3, -pi / 4, pi / 4, pi / 3, pi / 2])
params = tuning(data, s, "gaussian")
params.collect()
def test_circular_tuning(self):
data = get_data_tuning(self)
params, stats, r, comps, latent, scores = tuning(data, FISH_BILINEAR_MODEL, "bilinear", "circular")
params.collect()
stats.collect()
r.collect()
scores.collect()
def test_tuning_scripts(self):
data = self.sc.parallelize([(1, array([1.5, 2.3, 6.2, 5.1, 3.4,
2.1]))])
x1 = array([array([1, 0, 1, 0, 1, 0]), array([0, 1, 0, 1, 0, 1])])
x2 = array([
array([1, 1, 0, 0, 0, 0]),
array([0, 0, 1, 1, 0, 0]),
array([0, 0, 0, 0, 1, 1])
])
s = array([-pi / 4, pi / 4, pi / 3])
params = tuning(data, s, "circular", (x1, x2), "bilinear")
params.collect()
params = tuning(data, s, "gaussian", (x1, x2), "bilinear")
params.collect()
s = array([-pi / 2, -pi / 3, -pi / 4, pi / 4, pi / 3, pi / 2])
params = tuning(data, s, "gaussian")
params.collect()
data.cache()
# compute mean map
vals = stats(data,"mean")
save(vals,outputdir,"mean_vals","matlab")
# compute local cor
if args.neighbourhood != 0:
cor = localcorr(data,args.neighbourhood)
save(cor,outputdir,"local_corr","matlab")
# if stim argument is not default
if args.stim != '-':
# parse into different stim names
p = re.compile('-')
stims = p.split(args.stim)
# compute regression
for i in range(len(stims)):
modelfile = os.path.join(args.datafolder, args.basename + stims[i])
stats, betas = regress(data, modelfile, args.regressmode)
tune = tuning(betas,modelfile, args.tuningmode)
out_name = "stats_" + stims[i]
save(stats, outputdir, out_name, "matlab")
out_name = "tune_" + stims[i]
save(tune, outputdir, out_name, "matlab")
