def test_spikes(self):
"""
Make a simple case with spikes offset on each trace.
"""
test_data = np.zeros((100, 100))
index = np.arange(0, 100)
test_data[index, index] = 1.0
maxlag = 5
dip = dipsteer(test_data, 1, 1, maxlag)
# Output should be all -1 except for the edge effects
same = np.allclose(dip[maxlag:-maxlag, maxlag:-maxlag],
-test_data[maxlag:-maxlag, maxlag:-maxlag], .01)
self.assertTrue(same)
# Answer should not change if we increase the stepout
stepout = 4
maxlag = 1
dip = dipsteer(test_data, 1, stepout, maxlag)
diff = (dip[maxlag * stepout:100 -
(maxlag * stepout), stepout * maxlag:100 -
(stepout * maxlag)] +
test_data[maxlag * stepout:100 -
(maxlag * stepout), maxlag * stepout:100 -
(stepout * maxlag)])
diff = diff[1:-1, 1:-1]
# Output should be all -1 except for the edge effects
same = np.allclose(diff, np.zeros(diff.shape), .01)
self.assertTrue(same)
def test_spikes(self):
"""
Make a simple case with spikes offset on each trace.
"""
test_data = np.zeros((100, 100))
index = np.arange(0, 100)
test_data[index, index] = 1.0
maxlag = 5
dip = dipsteer(test_data, 1, 1, maxlag)
# Output should be all -1 except for the edge effects
same = np.allclose(dip[maxlag:-maxlag, maxlag:-maxlag],
-test_data[maxlag:-maxlag, maxlag:-maxlag],
.01)
self.assertTrue(same)
# Answer should not change if we increase the stepout
stepout = 4
maxlag = 1
dip = dipsteer(test_data, 1, stepout, maxlag)
diff = (dip[maxlag*stepout:100-(maxlag*stepout),
stepout * maxlag:100-(stepout*maxlag)] +
test_data[maxlag * stepout:100-(maxlag * stepout),
maxlag*stepout:100-(stepout*maxlag)])
diff = diff[1:-1, 1:-1]
# Output should be all -1 except for the edge effects
same = np.allclose(diff, np.zeros(diff.shape), .01)
self.assertTrue(same)
def test_wavelet(self):
# Make a dipping reflectivity field
data = np.zeros((150, 100))
data[0, :] = np.arange(100) / 10.0
dips = np.arange(0, 100, 2)
dips = np.concatenate([dips, dips[::-1]])
window_size = 10
freq = 20.0
duration = 1
wavelet = ricker(window_size, duration, freq)
for i in range(dips.size):
data[:, i] = np.convolve(wavelet,
np.roll(data[:, i], dips[i]),
mode='same')
stepout = 1
maxlag = 2
dip = dipsteer(data,
window_size,
stepout=stepout,
maxlag=maxlag,
overlap=0.5)
undipped = np.zeros(dips.shape)
for i in range(dips.size):
undipped[i] = (dip[dips[i], i])
check = undipped[maxlag * stepout:-maxlag * stepout]
test = np.zeros(check.shape)
test[0:test.size // 2 - 1] = -2.0
test[(test.size // 2) - 1] = -1
test[(test.size // 2)] = 1
test[(test.size // 2) + 1:] = 2
self.assertTrue(np.allclose(test, check))
def test_wavelet(self):
# Make a dipping reflectivity field
data = np.zeros((150, 100))
data[0, :] = np.arange(100) / 10.0
dips = np.arange(0, 100, 2)
dips = np.concatenate([dips, dips[::-1]])
window_size = 10
freq = 20.0
duration = 1
wavelet = ricker(window_size, duration, freq)
for i in range(dips.size):
data[:, i] = np.convolve(wavelet,
np.roll(data[:, i], dips[i]),
mode='same')
stepout = 1
maxlag = 2
dip = dipsteer(data, window_size, stepout=stepout,
maxlag=maxlag, overlap=0.5)
undipped = np.zeros(dips.shape)
for i in range(dips.size):
undipped[i] = (dip[dips[i], i])
check = undipped[maxlag*stepout:-maxlag*stepout]
test = np.zeros(check.shape)
test[0: test.size//2 - 1] = -2.0
test[(test.size//2) - 1] = -1
test[(test.size//2)] = 1
test[(test.size//2)+1:] = 2
self.assertTrue(np.allclose(test, check))
