def test_numpy_data_2d(self):
DIM = 2
testdata = np.arange(20 * 21).reshape(20, 21)
error = 1. * np.ones(testdata.shape)
source = NumpyData(DataSource.GRAVITY, testdata, null_value=NUMPY_NULL)
X0, NP, DX = source.getDataExtents()
for i in range(DIM):
self.assertAlmostEqual(X0[i], 0., msg="Data origin wrong")
self.assertEqual(NP[i],
testdata.shape[DIM - i - 1],
msg="Wrong number of data points")
self.assertAlmostEqual(DX[i],
1000. / testdata.shape[DIM - i - 1],
msg="Wrong cell size")
domainbuilder = DomainBuilder(dim=3)
domainbuilder.addSource(source)
domainbuilder.setVerticalExtents(depth=-VMIN,
air_layer=VMAX,
num_cells=NE_V)
domainbuilder.setElementPadding(PAD_X, PAD_Y)
dom = domainbuilder.getDomain()
g, s = domainbuilder.getGravitySurveys()[0]
outfn = os.path.join(WORKDIR, '_npdata2d.csv')
saveDataCSV(outfn, g=g, s=s)
DV = (VMAX - VMIN) / NE_V
# check data
nx = NP[0] + 2 * PAD_X
ny = NP[1] + 2 * PAD_Y
nz = NE_V
z_data = int(np.round((ALT - VMIN) / DV) - 1)
out = np.genfromtxt(outfn,
delimiter=',',
skip_header=1,
dtype=np.float64)
# recompute nz since ripley might have adjusted number of elements
nz = len(out) // (nx * ny)
g_out = out[:, 0].reshape(nz, ny, nx)
s_out = out[:, 1].reshape(nz, ny, nx)
self.assertAlmostEqual(
np.abs(g_out[z_data, PAD_Y:PAD_Y + NP[1], PAD_X:PAD_X + NP[0]] -
testdata).max(),
0.,
msg="Difference in gravity data area")
self.assertAlmostEqual(
np.abs(s_out[z_data, PAD_Y:PAD_Y + NP[1], PAD_X:PAD_X + NP[0]] -
error).max(),
0.,
msg="Difference in error data area")
# overwrite data -> should only be padding value left
g_out[z_data, PAD_Y:PAD_Y + NP[1], PAD_X:PAD_X + NP[0]] = NUMPY_NULL
self.assertAlmostEqual(np.abs(g_out - NUMPY_NULL).max(),
0.,
msg="Wrong values in padding area")
def test_add_source_after_domain_built(self):
db = DomainBuilder()
source1a = NetCdfData(DataSource.GRAVITY, NC_DATA1, scale_factor=1.)
db.addSource(source1a)
_ = db.getDomain()
source1b = NetCdfData(DataSource.GRAVITY, NC_DATA1, scale_factor=2.)
self.assertRaises(Exception, db.addSource, source1b)
def test_cdf_with_padding(self):
source = NetCdfData(DataSource.GRAVITY, NC_DATA, ALT, scale_factor=1e-6)
domainbuilder=DomainBuilder()
domainbuilder.addSource(source)
domainbuilder.setVerticalExtents(depth=-VMIN, air_layer=VMAX, num_cells=NE_V)
domainbuilder.setElementPadding(PAD_X,PAD_Y)
dom=domainbuilder.getDomain()
g,s=domainbuilder.getGravitySurveys()[0]
outfn=os.path.join(WORKDIR, '_ncdata.csv')
saveDataCSV(outfn, g=g, s=s)
X0,NP,DX=source.getDataExtents()
DV=(VMAX-VMIN)/NE_V
# check metadata
self.assertEqual(NP, NC_SIZE, msg="Wrong number of data points")
# this only works if gdal is available
try:
import osgeo.osr
for i in range(len(NC_ORIGIN)):
self.assertAlmostEqual(X0[i], NC_ORIGIN[i], msg="Data origin wrong")
except ImportError:
print("Skipping test of data origin since gdal is not installed.")
# check data
nx=NP[0]+2*PAD_X
ny=NP[1]+2*PAD_Y
nz=NE_V
z_data=int(np.round((ALT-VMIN)/DV)-1)
ref=np.genfromtxt(NC_REF, delimiter=',', dtype=np.float64)
g_ref=ref[:,0].reshape((NP[1],NP[0]))
s_ref=ref[:,1].reshape((NP[1],NP[0]))
out=np.genfromtxt(outfn, delimiter=',', skip_header=1, dtype=np.float64)
# recompute nz since ripley might have adjusted number of elements
nz=len(out)//(nx*ny)
g_out=out[:,0].reshape(nz,ny,nx)
s_out=out[:,1].reshape(nz,ny,nx)
self.assertAlmostEqual(np.abs(
g_out[z_data, PAD_Y:PAD_Y+NP[1], PAD_X:PAD_X+NP[0]]-g_ref).max(),
0., msg="Difference in gravity data area")
self.assertAlmostEqual(np.abs(
s_out[z_data, PAD_Y:PAD_Y+NP[1], PAD_X:PAD_X+NP[0]]-s_ref).max(),
0., msg="Difference in error data area")
# overwrite data -> should only be padding value left
g_out[z_data, PAD_Y:PAD_Y+NP[1], PAD_X:PAD_X+NP[0]]=NC_NULL
self.assertAlmostEqual(np.abs(g_out-NC_NULL).max(), 0.,
msg="Wrong values in padding area")
def test_numpy_data_2d(self):
DIM=2
testdata = np.arange(20*21).reshape(20,21)
error = 1.*np.ones(testdata.shape)
source = NumpyData(DataSource.GRAVITY, testdata, null_value=NUMPY_NULL)
X0,NP,DX=source.getDataExtents()
for i in range(DIM):
self.assertAlmostEqual(X0[i], 0., msg="Data origin wrong")
self.assertEqual(NP[i], testdata.shape[DIM-i-1], msg="Wrong number of data points")
self.assertAlmostEqual(DX[i], 1000./testdata.shape[DIM-i-1], msg="Wrong cell size")
domainbuilder=DomainBuilder(dim=3)
domainbuilder.addSource(source)
domainbuilder.setVerticalExtents(depth=-VMIN, air_layer=VMAX, num_cells=NE_V)
domainbuilder.setElementPadding(PAD_X, PAD_Y)
dom=domainbuilder.getDomain()
g,s=domainbuilder.getGravitySurveys()[0]
outfn=os.path.join(WORKDIR, '_npdata2d.csv')
saveDataCSV(outfn, g=g, s=s)
DV=(VMAX-VMIN)/NE_V
# check data
nx=NP[0]+2*PAD_X
ny=NP[1]+2*PAD_Y
nz=NE_V
z_data=int(np.round((ALT-VMIN)/DV)-1)
out=np.genfromtxt(outfn, delimiter=',', skip_header=1, dtype=np.float64)
# recompute nz since ripley might have adjusted number of elements
nz=len(out)//(nx*ny)
g_out=out[:,0].reshape(nz,ny,nx)
s_out=out[:,1].reshape(nz,ny,nx)
self.assertAlmostEqual(np.abs(
g_out[z_data, PAD_Y:PAD_Y+NP[1], PAD_X:PAD_X+NP[0]]-testdata).max(),
0., msg="Difference in gravity data area")
self.assertAlmostEqual(np.abs(
s_out[z_data, PAD_Y:PAD_Y+NP[1], PAD_X:PAD_X+NP[0]]-error).max(),
0., msg="Difference in error data area")
# overwrite data -> should only be padding value left
g_out[z_data, PAD_Y:PAD_Y+NP[1], PAD_X:PAD_X+NP[0]]=NUMPY_NULL
self.assertAlmostEqual(np.abs(g_out-NUMPY_NULL).max(), 0.,
msg="Wrong values in padding area")
def test_geodetic_domain(self):
COORDINATES = WGS84ReferenceSystem()
db = DomainBuilder(reference_system=COORDINATES)
source1a = NetCdfData(DataSource.GRAVITY,
NC_DATA1,
scale_factor=1.,
reference_system=COORDINATES)
db.addSource(source1a)
db.setVerticalExtents(depth=20000., air_layer=30000., num_cells=10)
dom = db.getDomain()
x = dom.getX()
self.assertAlmostEqual(inf(x[0]),
120.2,
delta=0.001,
msg="phi range wrong")
self.assertAlmostEqual(inf(x[1]),
-29.2,
delta=0.0001,
msg="lambda range wrong")
self.assertAlmostEqual(inf(x[2]),
-0.2,
msg="h range wrong" + str(x[2]))
# Cannot check upper bounds of coordinates with more than 1 rank
# because ripley may adjust internally.
if getMPISizeWorld() == 1:
self.assertAlmostEqual(sup(x[0]),
120.3,
delta=0.001,
msg="phi range wrong")
self.assertAlmostEqual(sup(x[1]),
-29.1,
delta=0.0001,
msg="lambda range wrong")
self.assertAlmostEqual(sup(x[2]),
0.3,
msg="h range wrong: " + str(x[2]))
def test_cartesian_domain(self):
db = DomainBuilder()
source1a = NetCdfData(DataSource.GRAVITY, NC_DATA1, scale_factor=1.)
db.addSource(source1a)
db.setVerticalExtents(depth=20000., air_layer=30000., num_cells=10)
dom = db.getDomain()
def test_mixing_utm_zones(self):
source1 = NetCdfData(DataSource.GRAVITY, NC_DATA1, scale_factor=1.)
source2 = NetCdfData(DataSource.GRAVITY, NC_DATA2, scale_factor=1.)
domainbuilder = DomainBuilder()
domainbuilder.addSource(source1)
self.assertRaises(ValueError, domainbuilder.addSource, source2)
def test_add_garbage(self):
db = DomainBuilder()
self.assertRaises(TypeError, db.addSource, 42)
def test_cdf_with_padding_ellipsoid(self):
ref = WGS84ReferenceSystem()
source = NetCdfData(DataSource.GRAVITY,
NC_DATA,
ALT,
reference_system=ref,
scale_factor=1e-6)
domainbuilder = DomainBuilder(reference_system=ref)
domainbuilder.addSource(source)
domainbuilder.setVerticalExtents(depth=-VMIN,
air_layer=VMAX,
num_cells=NE_V)
domainbuilder.setElementPadding(PAD_X, PAD_Y)
dom = domainbuilder.getDomain()
g, s = domainbuilder.getGravitySurveys()[0]
outfn = os.path.join(WORKDIR, '_ncdata.csv')
saveDataCSV(outfn, g=g, s=s)
X0, NP, DX = source.getDataExtents()
DV = (VMAX - VMIN) / NE_V
# check metadata
self.assertEqual(NP, NC_SIZE, msg="Wrong number of data points")
for i in range(len(NC_ORIGIN)):
self.assertAlmostEqual(X0[i],
NC_ORIGIN_WGS84[i],
msg="Data origin wrong")
# check data
nx = NP[0] + 2 * PAD_X
ny = NP[1] + 2 * PAD_Y
nz = NE_V
z_data = int(np.round((ALT - VMIN) / DV) - 1)
ref = np.genfromtxt(NC_REF, delimiter=',', dtype=np.float64)
g_ref = ref[:, 0].reshape((NP[1], NP[0]))
s_ref = ref[:, 1].reshape((NP[1], NP[0]))
out = np.genfromtxt(outfn,
delimiter=',',
skip_header=1,
dtype=np.float64)
# recompute nz since ripley might have adjusted number of elements
nz = len(out) // (nx * ny)
g_out = out[:, 0].reshape(nz, ny, nx)
s_out = out[:, 1].reshape(nz, ny, nx)
self.assertAlmostEqual(
np.abs(g_out[z_data, PAD_Y:PAD_Y + NP[1], PAD_X:PAD_X + NP[0]] -
g_ref).max(),
0.,
msg="Difference in gravity data area")
self.assertAlmostEqual(
np.abs(s_out[z_data, PAD_Y:PAD_Y + NP[1], PAD_X:PAD_X + NP[0]] -
s_ref).max(),
0.,
msg="Difference in error data area")
# overwrite data -> should only be padding value left
g_out[z_data, PAD_Y:PAD_Y + NP[1], PAD_X:PAD_X + NP[0]] = NC_NULL
self.assertAlmostEqual(np.abs(g_out - NC_NULL).max(),
0.,
msg="Wrong values in padding area")
def _ers_tester(self, filename):
source = ErMapperData(DataSource.GRAVITY,
headerfile=filename,
altitude=ALT,
scale_factor=1e-6)
domainbuilder = DomainBuilder()
domainbuilder.addSource(source)
domainbuilder.setVerticalExtents(depth=-VMIN,
air_layer=VMAX,
num_cells=NE_V)
domainbuilder.setElementPadding(PAD_X, PAD_Y)
dom = domainbuilder.getDomain()
g, s = domainbuilder.getGravitySurveys()[0]
outfn = os.path.join(WORKDIR, '_ersdata.csv')
saveDataCSV(outfn, g=g, s=s)
X0, NP, DX = source.getDataExtents()
DV = (VMAX - VMIN) / NE_V
# check metadata
self.assertEqual(NP, ERS_SIZE, msg="Wrong number of data points")
# this test only works if gdal is available
try:
import osgeo.osr
for i in range(len(ERS_ORIGIN)):
self.assertAlmostEqual(X0[i],
ERS_ORIGIN[i],
msg="Data origin wrong")
except ImportError:
print("Skipping test of data origin since gdal is not installed.")
# check data
nx = NP[0] + 2 * PAD_X
ny = NP[1] + 2 * PAD_Y
nz = NE_V
z_data = int(np.round((ALT - VMIN) / DV) - 1)
ref = np.genfromtxt(ERS_REF, delimiter=',', dtype=np.float64)
g_ref = ref[:, 0].reshape((NP[1], NP[0]))
s_ref = ref[:, 1].reshape((NP[1], NP[0]))
out = np.genfromtxt(outfn,
delimiter=',',
skip_header=1,
dtype=np.float64)
# recompute nz since ripley might have adjusted number of elements
nz = len(out) // (nx * ny)
g_out = out[:, 0].reshape(nz, ny, nx)
s_out = out[:, 1].reshape(nz, ny, nx)
self.assertAlmostEqual(
np.abs(g_out[z_data, PAD_Y:PAD_Y + NP[1], PAD_X:PAD_X + NP[0]] -
g_ref).max(),
0.,
msg="Difference in gravity data area")
self.assertAlmostEqual(
np.abs(s_out[z_data, PAD_Y:PAD_Y + NP[1], PAD_X:PAD_X + NP[0]] -
s_ref).max(),
0.,
msg="Difference in error data area")
# overwrite data -> should only be padding value left
g_out[z_data, PAD_Y:PAD_Y + NP[1], PAD_X:PAD_X + NP[0]] = ERS_NULL
self.assertAlmostEqual(np.abs(g_out - ERS_NULL).max(),
0.,
msg="Wrong values in padding area")
