def setUpClass(cls):
cls.df = create_spike_df()
tsq = cls.df.meta
cls.meta = tsq
nsamples, _ = tsq.shape[0], tsq.size.unique().max()
size = nsamples * tsq.shape[1], tsq.channel.nunique()
cls.rows, cls.columns = size
def setUp(self):
sp = create_spike_df()
thr = sp.threshold(4 * sp.std())
clr = sp.clear_refrac(thr)
binned = sp.bin(clr, binsize=10)
self.xc = sp.xcorr(binned, maxlags=10)
rawmap = np.array([1, 3, 2, 6, 7, 4, 8, 5, 13, 10, 12, 9, 14, 16, 11, 15]).reshape(4, 4)
self.elecmap = ElectrodeMap(rawmap)
self.dm = self.elecmap.distance_map(50, 125)
def setUp(self):
self.sp = create_spike_df()
def setUp(self):
self.spikes = create_spike_df()
self.threshes = 2e-5, 3e-5
self.mses = None, 2, 3
self.binsizes = 0, 1, randint(10, 12)
