def make_spline(collection, start_date):
collection = sorted(collection, key=lambda x: x.time)
collection = average_over(collection, 7)
dates = []
phi = []
lam = []
h = []
for elem in collection:
if (get_date(elem)-start_date).days >= 0:
dates.append((get_date(elem)-start_date).days)
phi.append(elem.pos[0])
lam.append(elem.pos[1])
h.append(elem.pos[2])
return (CubicSpline(dates, phi),CubicSpline(dates, lam), CubicSpline(dates, h), dates)
def make_spline(collection, start_date):
collection = sorted(collection, key=lambda x: x.time)
collection = average_over(collection, 7)
dates = [-1]
phi = [collection[0].pos[0]]
lam = [collection[0].pos[1]]
h = [collection[0].pos[2]]
for elem in collection:
if (get_date(elem) - start_date).days >= 0:
dates.append((get_date(elem) - start_date).days)
phi.append(elem.pos[0])
lam.append(elem.pos[1])
h.append(elem.pos[2])
return (scipy.interpolate.interp1d(dates, phi),
scipy.interpolate.interp1d(dates, lam),
scipy.interpolate.interp1d(dates, h), dates)
def graph_series(series):
series = sorted(series, key=lambda x: x.time)
series = average_over(series, 7)
p0 = np.array(series[0].pos)
phi, lam, h = p0
mat = np.array(
[[-1 * sin(lam), cos(lam), 0.],
[-1 * cos(lam) * sin(phi), -1 * sin(lam) * sin(phi),
cos(phi)], [cos(lam) * cos(phi),
sin(lam) * cos(phi),
sin(phi)]]).T
positions = []
errors = []
times = []
i = 0
for elem in series:
year = elem.time // 1000
days = elem.time - year * 1000
date = datetime.date.fromordinal(
datetime.date(year, 1, 1).toordinal() + days - 1)
if not (datetime.date(1999, 1, 1) <= date < datetime.date(2012, 1, 1)):
continue
times.append(date)
tmp = elem.pos - p0
positions.append(np.matmul(mat, tmp))
print(np.matmul(mat, tmp))
pos = np.zeros([3])
errors.append(elem.err)
plotpos = np.array(positions)
ploterr = np.array(errors)
errors = np.array(errors)
print(plotpos[:, 2])
times2 = []
mindate = times[0]
for elem in times:
times2.append((elem - mindate).days)
north = linregress(times2, plotpos[:, 0])
east = linregress(times2, plotpos[:, 1])
up, away = curve_fit(to_fit, times2, plotpos[:, 2])
print("{} mm/y".format(north[0] * 365 * 1000))
print("{} mm/y".format(east[0] * 365 * 1000))
print("{} mm/y".format(up[1] * 365 * 1000))
print(north)
print(east)
def make_spline(collection, start_date):
collection = sorted(collection, key=lambda x: x.time)
collection = average_over(collection, 7)
dates = [0]
phi = [collection[0].pos[0]]
lam = [collection[0].pos[1]]
h = [collection[0].pos[2]]
for elem in collection:
if (get_date(elem)-start_date).days >= 0:
dates.append((get_date(elem)-start_date).days)
phi.append(elem.pos[0])
lam.append(elem.pos[1])
h.append(elem.pos[2])
s = 0
smooth = 1000
dev = 0.1
cleanphi = outlierdet(np.array([dates,phi]).T,smooth,dev)
cleanlam = outlierdet(np.array([dates,lam]).T,smooth,dev)
n = 8
return (scipy.interpolate.UnivariateSpline(cleanphi[:,0][::n], cleanphi[:,1][::n], k=2, s=s),scipy.interpolate.UnivariateSpline(cleanlam[:,0][::n], cleanlam[:,1][::n], k=2, s=s), scipy.interpolate.UnivariateSpline(dates, h, s=s), dates)
def graph_series(series):
series = sorted(series, key=lambda x: x.time)
series = average_over(series, 7)
p0 = np.array(series[0].pos)
phi, lam, h = p0
mat = np.array(
[[-1 * sin(lam), cos(lam), 0.],
[-1 * cos(lam) * sin(phi), -1 * sin(lam) * sin(phi),
cos(phi)], [cos(lam) * cos(phi),
sin(lam) * cos(phi),
sin(phi)]]).T
positions = []
errors = []
times = []
i = 0
for elem in series:
year = elem.time // 1000
days = elem.time - year * 1000
date = datetime.date.fromordinal(
datetime.date(year, 1, 1).toordinal() + days - 1)
if not (datetime.date(1999, 1, 1) <= date < datetime.date(2012, 1, 1)):
continue
times.append(date)
tmp = p0 - elem.pos
positions.append(np.matmul(mat, tmp))
print(np.matmul(mat, tmp))
pos = np.zeros([3])
errors.append(elem.err)
plotpos = np.array(positions)
ploterr = np.array(errors)
errors = np.array(errors)
times2 = []
mindate = times[0]
for elem in times:
times2.append((elem - mindate).days)
north = linregress(times2, plotpos[:, 0])
east = linregress(times2, plotpos[:, 1])
up, away = curve_fit(to_fit, times2, plotpos[:, 2])
print("{} mm/y".format(north[0] * 365 * 1000))
print("{} mm/y".format(east[0] * 365 * 1000))
print("{} mm/y".format(up[1] * 365 * 1000))
print(north)
f, axarr = plt.subplots(3, sharex=True)
#f.suptitle(sys.argv[1].split("\\")[1][:4])
# for i in range(0,3):
# axarr[i].axhline(y=0, color='k')
# axarr[i].set_xlim([times[0], times[-1]])
# axarr[i].errorbar(times, plotpos[:, i], yerr=errors[:,i], linewidth=0.5, fmt='x', markersize=0.81)
for i in range(0, 3):
axarr[i].axhline(y=0, color='k')
axarr[i].set_xlim([times[0], times[-1]])
data = np.zeros([len(times), 2])
t = [t.toordinal() for t in times]
data[:, 0] = t
data[:, 1] = plotpos[:, 1]
#data = outlierdet(data, 3000, 1)
axarr[i].scatter(
data[:, 0], data[:, i], s=0.1
) #, yerr=errors[:,i], linewidth=0.5, fmt='x', markersize=0.81)
axarr[0].plot([mindate, times[-1]],
[north[1], north[1] + north[0] * times2[-1]])
axarr[1].plot([mindate, times[-1]],
[east[1], east[1] + east[0] * times2[-1]])
axarr[2].plot(
times,
list(map(lambda x: to_fit(x, up[0], up[1], up[2], up[3]), times2)))
plt.show()