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_3X3(self):
expected_result = np.array([[0.44517136, -1.15507667, 0.44844663],
[-1.15507667, 2.95156126, -1.15249271],
[0.44844663, -1.15249271, 0.46326737]])
result = statistics.vcv_local2cart(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))
if 'IncreaseReduce' in s:
if (s['IncreaseOrReduce'] == 'Increase'
and enu[0, 0] > orig_enu[0, 0]
and enu[1, 1] > orig_enu[1, 1]
and enu[2, 2] > orig_enu[2, 2]):
cal_enu = enu + at_sd + to_sd
elif (s['IncreaseOrReduce'] == 'Reduce'
and enu[0, 0] < orig_enu[0, 0]
and enu[1, 1] < orig_enu[1, 1]
and enu[2, 2] < orig_enu[2, 2]):
cal_enu = enu + at_sd + to_sd
if cal_enu.any != orig_enu.any:
#transform and apply to output file
vcv = vcv_local2cart(cal_enu, at_lat, at_lng)
new_vcv = ('\t\t\t<SigmaXX>' + str(vcv[0, 0]) +
'</SigmaXX>\n' + '\t\t\t<SigmaXY>' +
str(vcv[0, 1]) + '</SigmaXY>\n' +
'\t\t\t<SigmaXZ>' + str(vcv[0, 2]) +
'</SigmaXZ>\n' + '\t\t\t<SigmaYY>' +
str(vcv[1, 1]) + '</SigmaYY>\n' +
'\t\t\t<SigmaYZ>' + str(vcv[1, 2]) +
'</SigmaYZ>\n' + '\t\t\t<SigmaZZ>' +
str(vcv[2, 2]) + '</SigmaZZ>\n')
msr_out = (
msr_out.replace('<Sigma', '<!--Sigma').replace(
'</SigmaXX>', '</SigmaXX-->').replace(
'</SigmaXY>', '</SigmaXY-->').replace(
'</SigmaXZ>', '</SigmaXZ-->').replace(
def test_vcv_local2cart_3X2(self):
v_cart = np.zeros((3, 2))
with self.assertRaises(ValueError):
statistics.vcv_local2cart(v_cart, lat, lon)
def read_apu(apu_file, stns, read_metadata):
"""
Function to consume DynAdjust *.apu file and read contents into a DynaApu object
note: Variance matrix components are stored in XYZ rotation ONLY.
- ENU Variance matrix components are rotated back to XYZ.
- ENU Covariance block matrix components are rotated back to XYZ, at the position of the 'first' station.
:param apu_file: input *.apu file
:param stns: either None, or dictionary of station objects from earlier adj/xyz read
:param read_metadata: True/False switch to read metadata from file, or carry across from earlier xyz/adj read
:return: DynaApu object fields (dictionary of stations) apu options, metadata
"""
with open(apu_file) as apu_fh:
switches = Switches()
switches.header = True
rotate_vcv = False
pu_line = None
cov_count = 0
version = None
file_name = None
file_date = None
confidence_interval = None
vcv_blocks = False
variance_matrix_units = None
full_covariance_matrix = None
metadata = None
# set xyz_stns switch true to add apu info to existing stns dictionary from earlier xyz/adj read
if stns:
xyz_stns = True
else:
xyz_stns = False
stns = {}
for line_count, line in enumerate(apu_fh):
if switches.header:
version = pcommon.read_metadata(
line, 'Version:', version)
file_name = pcommon.read_metadata(
line, 'File name:', file_name)
file_date = pcommon.read_file_date(line, file_date)
confidence_interval = pcommon.read_metadata(
line, 'PU confidence interval',
confidence_interval)
variance_matrix_units = pcommon.read_metadata(
line, 'Variance matrix units ',
variance_matrix_units)
vcv_blocks = pcommon.read_metadata_tf(
line, 'Stations printed in blocks', vcv_blocks)
full_covariance_matrix = pcommon.read_metadata_tf(
line, 'Full covariance matrix',
full_covariance_matrix)
if "Positional uncertainty of adjusted station coordinates" in line:
pu_line = line_count + 5
switches.reset()
if variance_matrix_units == 'ENU':
rotate_vcv = True
if read_metadata:
metadata = DynaMetadata(epoch=None,
reference_frame=None,
geoid_model=None,
version=version)
apu_options = DynaApu.ApuOptions(
confidence_interval=confidence_interval,
variance_matrix_units=variance_matrix_units,
vcv_blocks=vcv_blocks,
full_covariance_matrix=full_covariance_matrix)
if pu_line:
if line_count == pu_line:
switches.stns = True
if switches.stns:
if line == '\n':
continue
if 'Block ' in line:
if len(line) < 30:
continue
if '-' * 30 in line:
continue
cols = line.split()
num_cols = len(cols)
# account for station names with spaces.
temp = line[0:20]
if temp != (' ' * 20):
num_cols = len(line[21:].split()) + 1
# Station variance line 1
if num_cols == 11:
stn = line[:20].strip()
lat = gc.hp2dms(float(line[23:36]))
lon = gc.hp2dms(float(line[38:51]))
hpu = float(line[51:62].strip())
vpu = float(line[62:73].strip())
smaj = float(line[73:86].strip())
smin = float(line[86:99].strip())
brg = float(line[99:112].strip())
vcv_11 = float(line[112:131].strip())
vcv_12 = float(line[131:150].strip())
vcv_13 = float(line[150:].strip())
continue
# Station variance line 2
elif num_cols == 2:
vcv_22 = float(line[131:150].strip())
vcv_23 = float(line[150:].strip())
continue
# Station variance line 3
elif num_cols == 1:
vcv_33 = float(line[150:].strip())
vcv = np.array([
[vcv_11, vcv_12, vcv_13],
[vcv_12, vcv_22, vcv_23],
[vcv_13, vcv_23, vcv_33],
])
if rotate_vcv:
vcv = gstat.vcv_local2cart(
vcv, lat.dec(), lon.dec())
# update existing or create new station object
if xyz_stns:
stns[stn].hpu = hpu
stns[stn].vpu = vpu
stns[stn].vpu = vpu
stns[stn].smaj = smaj
stns[stn].smin = smin
stns[stn].brg = brg
stns[stn].vcv = vcv
else:
apu_stn = Station(name=stn,
con=None,
lat=lat,
lon=lon,
ehgt=None,
ohgt=None,
sd_e=None,
sd_n=None,
sd_u=None,
description=None,
hpu=hpu,
vpu=vpu,
smaj=smaj,
smin=smin,
brg=brg,
vcv=vcv,
covariances={})
stns[stn] = apu_stn
# covariance block information
if full_covariance_matrix:
if num_cols == 4:
cov_stn = line[:20].strip()
cov_11 = float(line[113:131].strip())
cov_12 = float(line[132:150].strip())
cov_13 = float(line[151:169].strip())
cov_count = 1
elif num_cols == 3:
cov_count += 1
if cov_count == 2:
cov_21 = float(line[113:131].strip())
cov_22 = float(line[132:150].strip())
cov_23 = float(line[151:169].strip())
elif cov_count == 3:
cov_31 = float(line[113:131].strip())
cov_32 = float(line[132:150].strip())
cov_33 = float(line[151:169].strip())
cov = np.array([
[cov_11, cov_12, cov_13],
[cov_21, cov_22, cov_23],
[cov_31, cov_32, cov_33],
])
if rotate_vcv:
cov = gstat.vcv_local2cart(
cov, stns[stn].lat.dec(),
stns[stn].lon.dec())
if cov_stn not in stns[stn].covariances:
stns[stn].covariances[cov_stn] = cov
return stns, metadata, file_name, file_date, apu_options