def get_spline(self):
tckx = interp.CubicHermiteSpline(self.ts, self.xs, self.vxs)
tcky = interp.CubicHermiteSpline(self.ts, self.ys, self.vys)
coeffx = {}
coeffy = {}
t = []
for i in range(len(self.ts) - 1):
coeffx[i], coeffy[i] = [], []
t.append(np.linspace(self.ts[i], self.ts[i + 1], 50))
for order in tckx.c:
for i in range(len(self.ts) - 1):
coeffx[i].append(order[i])
for order in tcky.c:
for i in range(len(self.ts) - 1):
coeffy[i].append(order[i])
x, y = [], []
for seg in coeffx:
x.append(coeffx[seg][0] * (t[seg] - self.ts[seg])**3 + coeffx[seg][1] * (t[seg] - self.ts[seg])**2 + coeffx[seg][2] * (t[seg] - self.ts[seg]) + coeffx[seg][3])
for seg in coeffy:
y.append(coeffy[seg][0] * (t[seg] - self.ts[seg])**3 + coeffy[seg][1] * (t[seg] - self.ts[seg])**2 + coeffy[seg][2] * (t[seg] - self.ts[seg]) + coeffy[seg][3])
x_plot, y_plot = [], []
for i in range(len(t)):
for j in range(len(t[i])):
x_plot.append(x[i][j])
y_plot.append(y[i][j])
return (x_plot, y_plot)
def approximate(self):
x_y_s = list(zip(self.racines, np.zeros(len(self.racines)))) + self.extrema
x_y_s = np.array(sorted(x_y_s, key=lambda x: x[0]))
xs = x_y_s[:, 0]
ys = x_y_s[:, 1]
dp = self.derivesPentes()
self.spline = spi.CubicHermiteSpline(xs, ys, dp)
def getTargetStates(observation_epochs,
target_id='Duende',
observer_id='I11',
ephemeris_dt='1h',
frame='ecliptic'):
"""Produce sun-observer state vectors at observation epochs.
Parameters:
-----------
observation_epochs ... Numpy array of observation epochs [JD]
target_id ... Horizons identifier target, e.g. 'Ceres'
observer_id ... Horizons identifier observer, e.g. 'I11'
ephemeris_dt ... Time step for ephemeris query.
Typically 1h since the actual times will be interpolated later.
frame ... coordinate frame (default 'ecliptic' or 'icrf')
Returns:
--------
target_positions ... Heliocentric target states at observation epochs in [au, au/day].
target_velocities
External Function Requirements:
-------------------------------
# Interpolation
import scipy.interpolate as spi
# time transform
mjd2jd ... change modified Julian date to Julian date, timescale TDB)
# NASA JPL HORIZONS API call wrapper
targetStatesFromHorizons ... Wrapper function for JPL Horizons state query via astropy
"""
tmin = tr.mjd2jd(np.min(observation_epochs))
tmax = tr.mjd2jd(np.max(observation_epochs))
#Start and stop times of the survey
tstart = 'JD' + str(tmin - 1.)
tstop = 'JD' + str(tmax + 1.)
epochs = np.unique(observation_epochs)
[target_mjd, target_xyz,
target_vxyz] = targetStatesFromHorizons(target_id, observer_id, tstart,
tstop, ephemeris_dt)
# Interpolate heliocentric observer positions to the actual observation epochs
ir = spi.CubicHermiteSpline(target_mjd,
target_xyz,
target_vxyz,
axis=1,
extrapolate=None)
target_positions = ir(observation_epochs).T
# Interpolate heliocentric observer velocities to the actual observation epochs
dirdt = ir.derivative(nu=1)
target_velocities = dirdt(observation_epochs).T
return target_positions, target_velocities
def per_spl(x, y):
assert len(x) == len(y) == 3
y[-1] = y[0] # shortcut
x, y = map(np.asarray, (x, y))
h = x[1:] - x[:-1]
m = (y[1:] - y[:-1]) / h
s = (m / h).sum() / (1. / h).sum()
#s = ((m / h)/ (1. / h)/2).sum()
print('NEW S : ', s)
return ipt.CubicHermiteSpline(x, y, [s, s, s])
def __init__(self,
curve: 'Curve',
*,
extrapolate: ty.Optional[ty.Union[bool, str]] = None):
super().__init__(curve)
self.spline = interp.CubicHermiteSpline(curve.t,
curve.data,
curve.frenet1,
axis=0,
extrapolate=extrapolate)
def getObserverInterpolant(tmin,
tmax,
origin='SSB',
observer_location='I11',
ephemeris_dt='1h',
frame='ecliptic'):
"""Produce sun-observer state vectors at observation epochs.
Parameters:
-----------
tmin,tmax ... float, float, start and stop time for interpolant [MJD]
origin ... str, origin of the coordinate system (e.g. 'Sun' or 'SSB' =Solar System Barycenter)
observer_location ... str, Horizons identifyer of observer location, e.g. 'I11'
ephemeris_dt ... float, Time step for ephemeris query.
Typically 1h since the actual times will be interpolated later.
frame ... str, Coordinate system reference frame: 'ecliptic' or 'ICRF'
Returns:
--------
ipos, ivel ... scipy interpolants [au], [au/day]
Heliocentric observer positions and velocity interpolants
as function of time [MJD].
External Function Requirements:
-------------------------------
# Interpolation
import scipy.interpolate as spi
# time transform
mjd2jd ... change modified Julian date to Julian date, timescale TDB)
# NASA JPL HORIZONS API call wrapper
observerStatesFromHorizons ... Wrapper function for JPL Horizons state query via astropy
"""
tminjd = tr.mjd2jd(tmin)
tmaxjd = tr.mjd2jd(tmax)
#Start and stop times of the survey
tstart = 'JD' + str(tminjd - 1.)
tstop = 'JD' + str(tmaxjd + 1.)
try:
# Get observer locations (caution: choose the right plane of reference and direction of the vectors!)
# check query by copy/pasting the output of print(observer_sun.uri) into a webbrowser if there are problems.
if (origin == 'SSB' or origin == '@0'):
observer_origin = Horizons(id='Sun',
location=observer_location,
id_type='majorbody',
epochs={
'start': tstart,
'stop': tstop,
'step': ephemeris_dt
})
origin_barycenter = Horizons(id='Sun',
location='@0',
id_type='majorbody',
epochs={
'start': tstart,
'stop': tstop,
'step': ephemeris_dt
})
if (frame == 'ecliptic'):
oo = observer_origin.vectors(refplane='ecliptic')
ob = origin_barycenter.vectors(refplane='ecliptic')
elif (frame == 'ICRF' or frame == 'J2000' or frame == 'earth'
or frame == 'icrf'):
oo = observer_origin.vectors(refplane='earth')
ob = origin_barycenter.vectors(refplane='earth')
else:
raise Exception('Error: requested frame unknown.')
observer_xyz = (
-1) * (np.array([oo['x'], oo['y'], oo['z']]).astype('float') +
np.array([ob['x'], ob['y'], ob['z']]).astype('float'))
observer_vxyz = (-1) * (
np.array([oo['vx'], oo['vy'], oo['vz']]).astype('float') +
np.array([ob['vx'], ob['vy'], ob['vz']]).astype('float'))
observer_jd = np.array(oo['datetime_jd']).astype('float')
else:
observer_origin = Horizons(id=origin,
location=observer_location,
id_type='majorbody',
epochs={
'start': tstart,
'stop': tstop,
'step': ephemeris_dt
})
if (frame == 'ecliptic'):
obs = observer_origin.vectors(refplane='ecliptic')
elif (frame == 'ICRF' or frame == 'J2000' or frame == 'earth'
or frame == 'icrf'):
obs = observer_orignin.vectors(refplane='earth')
else:
raise Exception('Error: requested frame unknown.')
#We need the sun-observer vector not the observer-sun vector
observer_xyz = (-1) * np.array([obs['x'], obs['y'], obs['z']
]).astype('float')
observer_vxyz = (-1) * np.array([obs['vx'], obs['vy'], obs['vz']
]).astype('float')
observer_jd = np.array(obs['datetime_jd']).astype('float')
except:
print(
"Error: potential online ephemeris query failure. Make sure internet connectivity is available."
)
raise
observer_mjd = tr.jd2mjd(observer_jd)
# Interpolate heliocentric observer positions to the actual observation epochs
ipos = spi.CubicHermiteSpline(observer_mjd,
observer_xyz,
observer_vxyz,
axis=1,
extrapolate=None)
# Interpolate heliocentric observer velocities to the actual observation epochs
ivel = spi.CubicSpline(observer_mjd,
observer_vxyz,
axis=1,
extrapolate=None)
return ipos, ivel
import numpy as np
import sympy as sp
import scipy.interpolate as spi
import matplotlib.pyplot as plt
#Ejercicio Splines
#Jose Calderon - Santiago Fernandez - Mariana Galavis - German Velasco
#Principales referencias durante el desarrollo del codigo:
#https://docs.scipy.org/doc/scipy/reference/tutorial/interpolate.html
#https://docs.scipy.org/doc/scipy/reference/generated/scipy.interpolate.CubicHermiteSpline.html
xn = np.array([0, 1, 2], float)
y = np.array([10.5, 15.33, 5.789], float)
dydx = np.array(
[1, (y[1] - y[0]) / (xn[1] - xn[0]),
(y[2] - y[1]) / (xn[2] - xn[1])], float)
a = spi.CubicHermiteSpline(xn, y, dydx)
arr = np.array([a.c[0, 0], a.c[1, 0], a.c[2, 0], a.c[3, 0]])
x = sp.Symbol('x')
fun = arr[3] * x**0 + arr[2] * x**1 + arr[1] * x**2 + arr[0] * x**3
xnew = np.linspace(0, 2, 50)
plt.plot(xnew, a(xnew), 'r--')
plt.show()
print("La funcion del MENOR grado tres que pasa por los puntos es f(x) = {}".
format(fun))
import scipy.interpolate as interp
import matplotlib.pyplot as plt
import numpy as np
x_points = np.array([0, 1, 2, 3])
y_points = np.array([12,14,22,39])
dydx_values = np.array([20, 5, 3, -20])
tck = interp.CubicHermiteSpline(x_points, y_points, dydx_values)
deriv = tck.derivative()
x = []
y = []
coeff = {}
d_coeff = {}
print(tck.c)
for i in range(len(x_points) - 1):
coeff[i] = []
d_coeff[i] = []
x.append(np.linspace(x_points[i], x_points[i + 1], 100))
for order in tck.c:
for i in range(len(x_points) - 1):
coeff[i].append(order[i])
for order in deriv.c:
for i in range(len(x_points) - 1):
d_coeff[i].append(order[i])
