def test1():
app = QApplication([])
settings = PickleSettings(applicationname='testOE3')
w = OscillationDetection(analogsignal=ana,
settings=settings,
session=session,
mapped_classes=dbinfo.mapped_classes)
w.show()
app.exec_()
def test2():
"""create new db"""
app = QApplication([])
settings = PickleSettings(applicationname='testOE3')
w = CreateDB(settings=settings)
w.exec_()
w.create_a_new_db()
def test1():
"""open existing db"""
app = QApplication([])
settings = PickleSettings(applicationname='testOE3')
w = OpenDB(settings=settings)
w.exec_()
print w.get_opendb_kargs()
def test2():
app = QApplication([])
settings = PickleSettings(applicationname='testOE3')
w1 = ToolChainWidget(spikesorter=spikesorter, settings=settings)
#~ w1.change_toolchain(FromFullBandSignalToClustered, )
w1.change_toolchain(FromFullBandSignalToDetection)
w1.show()
app.exec_()
def test3():
""" With settings """
app = QApplication([ ])
settings = PickleSettings(applicationname = 'testOE3')
w = ParamWidget( Parameters, title = 'with settings',
settings = settings, settingskey = 'a good dataset')
w.show()
app.exec_()
for k,v in w.to_dict().items():
print k,v
def test1():
"""
simple test
"""
kargs = dict(url = url,
myglobals = globals(),
use_global_session = False,
object_number_in_cache = 3000,
relationship_lazy = 'dynamic',
)
dbinfo = open_db(**kargs)
dbinfo.kargs_reopen = kargs
session = dbinfo.Session()
app = QApplication([ ])
settings = PickleSettings(applicationname = 'testOE3')
#~ settings = None
w = MainExplorer(dbinfo = dbinfo, settings = settings, name = url)
ok = w.show()
app.exec_()
def test1():
app = QApplication([])
colors = ['c', 'g', 'r', 'b', 'k', 'm', 'y'] * 100
nstates = 5
ndim = 8
n = 40
data = np.zeros((0, ndim), 'f')
for i in range(ndim):
d = np.random.randn(n, ndim)
d = d * (1. + np.random.randn() / 4) + np.random.randn() * 5
data = np.concatenate((data, d), axis=0)
settings = PickleSettings(applicationname='testOE3')
w = NDViewer(
settings=settings,
show_tour=True,
show_select_tools=True,
)
codebook, distor = cluster.vq.kmeans(data, nstates)
dataLabels, distor = cluster.vq.vq(data, codebook)
w.change_point(data[:, 1:5])
w.change_point(data, dataLabels)
def display_selection():
print np.where(w.actualSelection)
w.selection_changed.connect(display_selection)
w.show()
app.exec_()