def ts_from_list(A,
B,
C,
T,
initype,
sA=[],
sB=[],
sC=[],
stat='STAT',
name='NoName'):
tsout = time_series.TimeSeriePoint()
if len(sA) == 0:
for a, b, c, t in zip(A, B, C, T):
pt = time_series.Point(a, b, c, t, initype)
tsout.add_point(pt)
else:
for a, b, c, t, sa, sb, sc in zip(A, B, C, T, sA, sB, sC):
pt = time_series.Point(a, b, c, t, initype, sa, sb, sc)
tsout.add_point(pt)
tsout.stat = stat
tsout.name = name
if initype == 'ENU':
tsout.boolENU = True
else:
tsout.boolENU = False
return tsout
def rotate_pt_cls_solo(tsattin,
pointin,
Rtype='R1',
xyzreftuple=([1, 0, 0], [0, 1, 0], [0, 0, 1]),
angtype='deg'):
''' ENTREE : tsattin : une TS d'attitude (N angles)
pointin : UN Point en entrée
SORTIE : une TSpoint de N points '''
attlisttmp = tsattin.to_list()
R = attlisttmp[0]
P = attlisttmp[1]
Y = attlisttmp[2]
T = attlisttmp[3]
A, B, C, _, _ = pointin()
ptrotlis = XXX.rotate_points(R, P, Y, [np.array([A, B, C])], Rtype,
xyzreftuple, angtype)
ptrotlis = utils.shrink_listoflist(ptrotlis)
tsout = time_series.TimeSeriePoint()
for p, t in zip(ptrotlis, T):
#print p
tsout.add_point(
time_series.Point(p[0], p[1], p[2], t, initype=pointin.initype))
return tsout
def mean_list_of_pts(ptslisin):
""" useful for merge fct
ONLY IMPLEMENTED FOR ENU coords for the moment """
E = np.nanmean([p.E for p in ptslisin])
N = np.nanmean([p.N for p in ptslisin])
U = np.nanmean([p.U for p in ptslisin])
sE = np.nanmean([p.sE for p in ptslisin])
sN = np.nanmean([p.sN for p in ptslisin])
sU = np.nanmean([p.sU for p in ptslisin])
Tlis = [p.T for p in ptslisin]
T = ((np.max(Tlis) - np.min(Tlis)) / 2.) + np.min(Tlis)
pt = time_series.Point(E, N, U, T, 'ENU', sE, sN, sU, ptslisin[0].name)
return pt
def refENU_for_tslist(tslist_in, tsref_marker=0):
"""
tsref_marker : indice of the reference time serie OR the 'all' keyword
in this case all the time series mean position will be averaged
"""
if tsref_marker == 'all':
refENU_stk = []
for ts in tslist_in:
refENUtmp = ts.mean_posi()
refENU_stk.append(refENUtmp)
X = np.mean([renu.X for renu in refENU_stk])
Y = np.mean([renu.Y for renu in refENU_stk])
Z = np.mean([renu.Z for renu in refENU_stk])
refENU = time_series.Point(X, Y, Z, 0, initype='XYZ')
else:
refENU = tslist_in[tsref_marker].mean_posi()
for ts in tslist_in:
ts.ENUcalc(refENU)
return refENU