def test_plot_traces(self):
# Only checking that these do not throw errors
dat = NoInitRadarData(big=True)
fig, ax = plot.plot_traces(dat, 0)
fig, ax = plot.plot_traces(dat, [1, 1])
fig, ax = plot.plot_traces(dat, [1, 18])
with self.assertRaises(ValueError):
fig, ax = plot.plot_traces(dat, np.arange(10))
with self.assertRaises(IndexError):
fig, ax = plot.plot_traces(dat, 999)
# no nmo
fig, ax = plot.plot_traces(dat, 0, ydat='depth')
# with nmo
dat.nmo_depth = np.arange(10)
fig, ax = plot.plot_traces(dat, 0, ydat='depth')
with self.assertRaises(ValueError):
fig, ax = plot.plot_traces(dat, 0, ydat='dum')
# Make sure we handle axes rescaling ok
dat.data[:, 0] = 10
dat.data[:, 1] = -10
fig, ax = plot.plot_traces(dat, (0, 2))
def test_plot_specdense(self):
# Only checking that these do not throw errors
dat = NoInitRadarData(big=True)
dat.picks = Picks(dat)
dat.picks.samp1 = np.ones((2, len(dat.lat)))
dat.picks.samp2 = np.ones((2, len(dat.lat)))
dat.picks.samp3 = np.ones((2, len(dat.lat)))
fig, ax = plot.plot_specdense(dat, 3.0e-7)
plot.plot_specdense(dat, 3.0e-7, fig=fig)
plot.plot_specdense(dat, 3.0e-7, fig=fig, ax=ax)
plot.plot_specdense(dat, 3.0e-7, window='hamming')
plot.plot_specdense(dat, 3.0e-7, scaling='density')
# freq too low
with self.assertRaises(ValueError):
plot.plot_specdense(dat, -100)
with self.assertRaises(ValueError):
plot.plot_specdense(dat, 3.0e-7, scaling='dummy')
with self.assertRaises(ValueError):
plot.plot_specdense(dat, 3.0e-7, window='dummy')
def test_Kirchoff_cython(self):
data = NoInitRadarData(big=True)
data = mig_cython.migrationKirchhoff(data)
def testWriteWithFlags(self):
rd = NoInitRadarData()
rd.flags = RadarFlags()
rd.save(os.path.join(THIS_DIR, 'input_data', 'test_out.mat'))
def test_output_shp_nolayers_nogdal(self):
rd = NoInitRadarData()
with self.assertRaises(ImportError):
rd.output_shp(os.path.join(THIS_DIR, 'input_data', 'test.shp'))
def test_sustolt(self):
data = NoInitRadarData(big=True)
data.dt = 1.0e-9
data.travel_time = data.travel_time * 1.0e-9
data.fn = os.path.join(THIS_DIR, 'input_data', 'rectangle_sustolt.mat')
migrationlib.migrationSeisUnix(data)
def test_PhaseShiftConstant(self):
data = NoInitRadarData(big=True)
data = migrationlib.migrationPhaseShift(data)
def test_Stolt(self):
data = NoInitRadarData(big=True)
data = migrationlib.migrationStolt(data)
def test_kinematic_gps_control(self):
dats = [NoInitRadarData(big=True)]
gpslib.kinematic_gps_control(dats,
np.arange(0, 2.0, 0.1),
np.arange(40, 60., 1.),
np.arange(0., 2000., 100.),
np.arange(0., 20., 1.),
guess_offset=False)
self.assertTrue(np.allclose(np.arange(0, 2.0, 0.1), dats[0].lat))
self.assertTrue(np.allclose(np.arange(40, 60, 1), dats[0].long))
self.assertTrue(np.allclose(np.arange(0, 2000, 100), dats[0].elev))
with self.assertRaises(ValueError):
gpslib.kinematic_gps_control(dats,
np.arange(0, 2.0, 0.1),
np.arange(0, 200, 10),
np.arange(0, 2000, 100),
np.arange(0, 20, 1),
guess_offset=True)
dat = NoInitRadarData(big=True)
gpslib.kinematic_gps_control(dat,
np.arange(0, 2.0, 0.1),
np.arange(40, 60, 1),
np.arange(0, 2000, 100),
np.arange(0, 20, 1),
guess_offset=False)
self.assertTrue(np.allclose(np.arange(0, 2.0, 0.1), dat.lat))
self.assertTrue(np.allclose(np.arange(40, 60, 1), dat.long))
self.assertTrue(np.allclose(np.arange(0, 2000, 100), dat.elev))
# We should be allowed to be off by 360 in longitude
dat = NoInitRadarData(big=True)
gpslib.kinematic_gps_control(dat,
np.arange(0, 2.0, 0.1),
np.arange(40, 60, 1) - 360.,
np.arange(0, 2000, 100),
np.arange(0, 20, 1),
guess_offset=False)
self.assertTrue(np.allclose(np.arange(0, 2.0, 0.1), dats[0].lat))
self.assertTrue(np.allclose(np.arange(40, 60, 1), dats[0].long))
self.assertTrue(np.allclose(np.arange(0, 2000, 100), dats[0].elev))
# and off the other way
dat = NoInitRadarData(big=True)
dat.long = dat.long - 360.
gpslib.kinematic_gps_control(dat,
np.arange(0, 2.0, 0.1),
np.arange(40, 60, 1),
np.arange(0, 2000, 100),
np.arange(0, 20, 1),
guess_offset=False)
self.assertTrue(np.allclose(np.arange(0, 2.0, 0.1), dats[0].lat))
self.assertTrue(np.allclose(np.arange(40, 60, 1), dats[0].long))
self.assertTrue(np.allclose(np.arange(0, 2000, 100), dats[0].elev))
dat = NoInitRadarData(big=True)
gpslib.kinematic_gps_control(dat,
np.arange(-1.0, 3.0, 0.1),
np.arange(20, 60, 1),
np.arange(-1000, 3000, 100),
np.arange(-10, 30, 1),
guess_offset=True)
# Multiple inputs
dats = [NoInitRadarData(big=True), NoInitRadarData(big=True)]
gpslib.kinematic_gps_control(dats,
np.arange(-1.0, 3.0, 0.1),
np.arange(40, 80, 1),
np.arange(-1000, 3000, 100),
np.arange(-10, 30, 1),
guess_offset=True)
# Bad timing
dat = NoInitRadarData(big=True)
dat.decday = dat.decday + 10
with self.assertRaises(ValueError):
gpslib.kinematic_gps_control(dat, np.arange(0, 2.0, 0.1),
np.arange(0, 20, 1),
np.arange(0, 2000, 100),
np.arange(0, 20, 1))
def test_HfiltRun(self):
radardata = NoInitRadarData()
radardata.horizontalfilt(0, 100)
# We taper in the hfilt, so this is not just zeros
self.assertTrue(
np.all(radardata.data == radardata.hfilt_target_output))
def test_AdaptiveRun(self):
radardata = NoInitRadarData()
radardata.adaptivehfilt()
# since we subtract average trace and all traces are identical, we should get zeros out
self.assertTrue(np.all(radardata.data <= 1.))
def test_process_vbp(self):
radardata = NoInitRadarData()
process.process([radardata], vbp=(0.1, 100.))
# The filter is not too good, so we have lots of residual
self.assertTrue(np.all(np.abs(radardata.data) < 1.0e-4))
def test_process_hfilt(self):
radardata = NoInitRadarData()
process.process([radardata], hfilt=(0, 100))
# We taper in the hfilt, so this is not just zeros
self.assertTrue(
np.all(radardata.data == radardata.hfilt_target_output))
def test_process_ahfilt(self):
radardata = NoInitRadarData()
process.process([radardata], ahfilt=True)
# We taper in the hfilt, so this is not just zeros
self.assertTrue(np.all(radardata.data <= 1.))
def test_vbp_badftype(self):
radardata = NoInitRadarData()
with self.assertRaises(ValueError):
radardata.vertical_band_pass(0.1, 100., filttype='dummy')
def test_HighPassNotspaced(self):
radardata = NoInitRadarData()
with self.assertRaises(ImpdarError):
# We have a screwed up filter here because of sampling vs. frequency used
radardata.highpass(1000.0)
def test_WinAvgExp(self):
radardata = NoInitRadarData()
radardata.winavg_hfilt(11, taper='full')
self.assertTrue(
np.all(radardata.data == radardata.hfilt_target_output))
def test_SaveFails(self):
print(SEGY)
data = NoInitRadarData()
with self.assertRaises(ImportError):
data.save_as_segy(os.path.join(THIS_DIR, 'input_data', 'shots0001_0200_resave.segy'))
def test_WinAvgExpBadwinavg(self):
# Tests the check on whether win_avg < tnum
radardata = NoInitRadarData()
radardata.winavg_hfilt(data_dummy.shape[1] + 10, taper='full')
self.assertTrue(
np.all(radardata.data == radardata.hfilt_target_output))
def test_Kirchhoff(self):
data = NoInitRadarData(big=True)
data = migrationlib.migrationKirchhoff(data)
def test_WinAvgPexp(self):
radardata = NoInitRadarData()
radardata.winavg_hfilt(11, taper='pexp', filtdepth=-1)
self.assertTrue(np.all(radardata.data == radardata.pexp_target_output))
def test_PhaseShiftLateral(self):
data = NoInitRadarData(big=True)
data = migrationlib.migrationPhaseShift(data,
vel_fn=os.path.join(
THIS_DIR, 'input_data',
'velocity_lateral.txt'))
def test_WinAvgbadtaper(self):
radardata = NoInitRadarData()
with self.assertRaises(ValueError):
radardata.winavg_hfilt(11, taper='not_a_taper', filtdepth=-1)
def test_output_shp_nolayers(self):
rd = NoInitRadarData()
rd.output_shp(os.path.join(THIS_DIR, 'input_data', 'test.shp'))
def test_vbp_butter(self):
radardata = NoInitRadarData()
radardata.vertical_band_pass(0.1, 100., filttype='butter')
# The filter is not too good, so we have lots of residual
self.assertTrue(np.all(np.abs(radardata.data) < 1.0e-4))
def test_WriteNoFLags(self):
rd = NoInitRadarData()
rd.save(os.path.join(THIS_DIR, 'input_data', 'test_out.mat'))
os.remove(os.path.join(THIS_DIR, 'input_data', 'test_out.mat'))
def test_plot_picks(self, mock_show):
# Only checking that these do not throw errors
dat = NoInitRadarData(big=True)
fig, ax = plot.plot_picks(dat, np.arange(int(dat.tnum)),
dat.travel_time)
dat.picks = Picks(dat)
dat.picks.picknums = [2, 10]
dat.picks.samp1 = np.ones((2, len(dat.lat)))
dat.picks.samp2 = np.ones((2, len(dat.lat)))
dat.picks.samp3 = np.ones((2, len(dat.lat)))
fig, ax = plot.plot_picks(dat, np.arange(int(dat.tnum)),
dat.travel_time)
plot.plot_picks(dat,
np.arange(int(dat.tnum)),
dat.travel_time,
fig=fig)
plot.plot_picks(dat,
np.arange(int(dat.tnum)),
dat.travel_time,
fig=fig,
ax=ax)
plot.plot_picks(dat,
np.arange(int(dat.tnum)),
dat.travel_time,
colors='g',
fig=fig,
ax=ax)
plot.plot_picks(dat,
np.arange(int(dat.tnum)),
dat.travel_time,
colors='gmm',
fig=fig,
ax=ax)
plot.plot_picks(dat,
np.arange(int(dat.tnum)),
dat.travel_time,
colors=['c', 'g'],
fig=fig,
ax=ax)
plot.plot_picks(dat,
np.arange(int(dat.tnum)),
dat.travel_time,
colors=['cmy', 'brb'],
fig=fig,
ax=ax)
plot.plot_picks(dat,
np.arange(int(dat.tnum)),
dat.travel_time,
colors=['cm', 'br'],
fig=fig,
ax=ax)
plot.plot_picks(dat,
np.arange(int(dat.tnum)),
dat.travel_time,
colors=True,
fig=fig,
ax=ax)
plot.plot_picks(dat,
np.arange(int(dat.tnum)),
dat.travel_time,
colors=False,
fig=fig,
ax=ax)
plot.plot_picks(dat,
np.arange(int(dat.tnum)),
dat.travel_time,
colors=['c', 'm', 'b'],
just_middle=False,
fig=fig,
ax=ax)
with self.assertRaises(ValueError):
plot.plot_picks(dat,
np.arange(int(dat.tnum)),
dat.travel_time,
colors=['c', 'm', 'b'],
just_middle=True,
fig=fig,
ax=ax)
def test_WriteRead(self):
# We are going to create a really bad file (most info missing) and see if we recover it or get an error
rd = NoInitRadarData()
rd.save(os.path.join(THIS_DIR, 'input_data', 'test_out.mat'))
RadarData(os.path.join(THIS_DIR, 'input_data', 'test_out.mat'))
def test_TimeWavenumber(self):
data = NoInitRadarData(big=True)
data = mig_python.migrationTimeWavenumber(data)