def test_slicing(self):
# test also the indexing versus direct slicing
my_sig = np.random.rand(500,)
wg = WindowGenerator(ns=500, nswin=100, overlap=50)
# 1) get the window by
my_rms = np.zeros((wg.nwin,))
for first, last in wg.slices:
my_rms[wg.iw] = rms(my_sig[first:last])
my_rms_ = np.zeros((wg.nwin,))
for wsig in wg.slice(my_sig):
my_rms_[wg.iw] = rms(wsig)
assert(np.all(my_rms_ == my_rms))
def test_window_simple(self):
wg = WindowGenerator(ns=500, nswin=100, overlap=50)
sl = list(wg.firstlast)
self.assertTrue(wg.nwin == len(sl) == 9)
self.assertTrue(np.all(np.array([s[0] for s in sl]) == np.arange(0, wg.nwin) * 50))
self.assertTrue(np.all(np.array([s[1] for s in sl]) == np.arange(0, wg.nwin) * 50 + 100))
wg = WindowGenerator(ns=500, nswin=100, overlap=10)
sl = list(wg.firstlast)
first = np.array([0, 90, 180, 270, 360, 450])
last = np.array([100, 190, 280, 370, 460, 500])
self.assertTrue(wg.nwin == len(sl) == 6)
self.assertTrue(np.all(np.array([s[0] for s in sl]) == first))
self.assertTrue(np.all(np.array([s[1] for s in sl]) == last))
def test_firstlast_slices(self):
# test also the indexing versus direct slicing
my_sig = np.random.rand(500,)
wg = WindowGenerator(ns=500, nswin=100, overlap=50)
# 1) get the window by
my_rms = np.zeros((wg.nwin,))
for first, last in wg.firstlast:
my_rms[wg.iw] = rms(my_sig[first:last])
# test with slice_array method
my_rms_ = np.zeros((wg.nwin,))
for wsig in wg.slice_array(my_sig):
my_rms_[wg.iw] = rms(wsig)
self.assertTrue(np.all(my_rms_ == my_rms))
# test with the slice output
my_rms_ = np.zeros((wg.nwin,))
for sl in wg.slice:
my_rms_[wg.iw] = rms(my_sig[sl])
self.assertTrue(np.all(my_rms_ == my_rms))
def test_tscale(self):
wg = WindowGenerator(ns=500, nswin=100, overlap=50)
ts = wg.tscale(fs=1000)
self.assertTrue(ts[0] == (100 - 1) / 2 / 1000)
self.assertTrue((np.allclose(np.diff(ts), 0.05)))
def test_nwindows_computation(self):
for m in np.arange(0, 100):
wg = WindowGenerator(ns=500 + m, nswin=87 + m, overlap=11 + m)
sl = list(wg.firstlast)
self.assertTrue(wg.nwin == len(sl))
