def test_vcv_cart2local_and_vcv_local2cart2_2X3(self):
lat = 0.0
lon = 0.0
v_cart = np.array([
[0.0, 0.0, 0.0],
[0.0, 0.0, 0.0],
])
with self.assertRaises(SystemExit):
statistics.vcv_cart2local(v_cart, lat, lon)
with self.assertRaises(SystemExit):
statistics.vcv_local2cart(v_cart, lat, lon)
def mga2020_to_mga94(zone, east, north, ell_ht=False, vcv=None):
"""
Performs conformal transformation of Map Grid of Australia 2020 to Map Grid of Australia 1994 Coordinates
using the reverse form of the GDA2020 Tech Manual v1.2 7 parameter similarity transformation parameters
:param zone: Zone Number - 1 to 60
:param east: Easting (m, within 3330km of Central Meridian)
:param north: Northing (m, 0 to 10,000,000m)
:param ell_ht: Ellipsoid Height (m) (optional)
:param vcv: Optional 3*3 numpy array in local enu units to propagate tf uncertainty
:return: MGA1994 Zone, Easting, Northing, Ellipsoid Height (if none provided, returns 0), and vcv matrix
"""
lat, lon, psf, gridconv = grid2geo(zone, east, north)
if ell_ht is False:
ell_ht_in = 0
else:
ell_ht_in = ell_ht
if vcv is not None:
vcv = vcv_local2cart(vcv, lat, lon)
x94, y94, z94 = llh2xyz(lat, lon, ell_ht_in)
x20, y20, z20, vcv94 = conform7(x94, y94, z94, -gda94_to_gda2020, vcv=vcv)
lat, lon, ell_ht_out = xyz2llh(x20, y20, z20)
if vcv94 is not None:
vcv94 = vcv_cart2local(vcv94, lat, lon)
if ell_ht is False:
ell_ht_out = 0
hemisphere, zone20, east20, north20, psf, gridconv = geo2grid(lat, lon)
return zone20, east20, north20, round(ell_ht_out, 4), vcv94
def test_vcv_local2cart_3X1(self):
expected_result = np.array([[1.41376457], [1.20291736], [1.22331807]])
result = statistics.vcv_cart2local(var, lat, lon)
np.testing.assert_almost_equal(expected_result, result)
self.assertEqual(type(expected_result), type(result))
def test_vcv_cart2local_3x3(self):
expected_result = np.array([[2.23971834, -1.86955194, 0.3599339],
[-1.86955194, 1.55096504, -0.29615085],
[0.3599339, -0.29615085, 0.06931662]])
result = statistics.vcv_cart2local(vcv, lat, lon)
np.testing.assert_almost_equal(expected_result, result)
self.assertEqual(type(expected_result), type(result))
def test_vcv_cart2local_and_vcv_local2cart2_1X3(self):
lat = 0.0
lon = 0.0
v_cart = np.array([
[0.0],
[0.0],
[0.0],
])
expected_result = np.array([
[0.0, 0.0, 0.0],
[0.0, 0.0, 0.0],
[0.0, 0.0, 0.0],
])
result_cart2local = statistics.vcv_cart2local(v_cart, lat, lon)
result_local2cart = statistics.vcv_local2cart(v_cart, lat, lon)
np.testing.assert_array_equal(expected_result, result_cart2local)
np.testing.assert_array_equal(expected_result, result_local2cart)
self.assertEqual(type(expected_result), type(result_cart2local))
self.assertEqual(type(expected_result), type(result_local2cart))
to_lat = hp2dec(stn[m['Second']]['P'])
to_lng = hp2dec(stn[m['Second']]['L'])
#Initialise the required matricies
at_sd = np.zeros([3, 3])
to_sd = np.zeros([3, 3])
orig_vcv = np.zeros([3, 3])
cal_vcv = np.zeros([3, 3])
orig_vcv[0, 0] = float(m['GPSBaseline']['SigmaXX'])
orig_vcv[0, 1] = float(m['GPSBaseline']['SigmaXY'])
orig_vcv[0, 2] = float(m['GPSBaseline']['SigmaXZ'])
orig_vcv[1, 1] = float(m['GPSBaseline']['SigmaYY'])
orig_vcv[1, 2] = float(m['GPSBaseline']['SigmaYZ'])
orig_vcv[2, 2] = float(m['GPSBaseline']['SigmaZZ'])
orig_enu = vcv_cart2local(orig_vcv, at_lat, at_lng)
# find and apply the centring error styling of the at and to station
# transform these from enu to xyz
if 'FirstStdDevSetupStyle' in m:
c = sd_styl[m['FirstStdDevSetupStyle']]['CentringStdDev']
v = sd_styl[m['FirstStdDevSetupStyle']]['VtStdDev']
at_sd[0, 0] = (c)**2 / float(m['Lscale'])
at_sd[1, 1] = (c)**2 / float(m['Pscale'])
at_sd[2, 2] = (v)**2 / float(m['Hscale'])
at_sd = at_sd / float(m['Vscale'])
if 'SecondStdDevSetupStyle' in m:
c = sd_styl[m['SecondStdDevSetupStyle']]['CentringStdDev']
v = sd_styl[m['SecondStdDevSetupStyle']]['VtStdDev']
to_sd[0, 0] = (c)**2 / float(m['Lscale'])
def test_vcv_cart2local_3X2(self):
v_cart = np.zeros((3, 2))
with self.assertRaises(ValueError):
statistics.vcv_cart2local(v_cart, 0.0, 0.0)
