def test_cove_reader(n=10000): plt.interactive(True) try: FIG = plt.figure() Q = Queue() bs_reader = BS3Reader(COVEProtocolHandler, Q, verbose=True, ident='TestCOVE') bs_reader.start() for _ in xrange(n): print Q.qsize() try: item = Q.get(block=True, timeout=2) FIG.clf() plt.imshow(item.data_lst[-1], shape=item.data_lst[-1].shape, figure=FIG) except Empty: continue except Exception, ex: print ex
# # Acknowledgements: # Philipp Meier <*****@*****.**> #_____________________________________________________________________________ # ##---IMPORTS from numpy.testing import assert_equal, assert_almost_equal import scipy as sp from scipy.io import loadmat from botmpy.common import TimeSeriesCovE, mcvec_from_conc, VERBOSE from botmpy.nodes import BOTMNode from spikeplot import plt plt.interactive(False) ##---TESTS def get_input_data(tf): noise = loadmat('/home/phil/matlab.mat')['noise'].T nc = noise.shape[1] spike_proto_sc = sp.cos(sp.linspace(-sp.pi, 3 * sp.pi, tf)) spike_proto_sc *= sp.hanning(tf) scale = sp.linspace(0, 2, tf) cvals = [(5., .5), (4., 9.), (3., 3.), (7., 2.5)] xi1 = sp.vstack([spike_proto_sc * cvals[i][0] * scale for i in xrange(nc)]).T xi2 = sp.vstack([spike_proto_sc * cvals[i][1] * scale[::-1] for i in xrange(nc)]).T temps = sp.asarray([xi1, xi2])