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")