sc-data-functions/functions_juice.py at main · ee-davies/sc-data-functions · GitHub

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import numpy as np
import pandas as pd
from datetime import timedelta
import spiceypy
import os.path

from functions_general import load_path


"""
JUICE SERVER DATA PATH
"""

juice_path=load_path(path_name='juice_path')
print(f"Juice path loaded: {juice_path}")

# Load path once globally
kernels_path = load_path(path_name='kernels_path')
print(f"Kernels path loaded: {kernels_path}")


"""
JUICE POSITION FUNCTIONS: coord maths, furnish kernels, and call position for each timestamp
Currently set to HEEQ, but will implement options to change
https://spiftp.esac.esa.int/data/SPICE/JUICE/kernels/
"""


def cart2sphere(x,y,z):
    r = np.sqrt(x**2+ y**2 + z**2) /1.495978707E8
    theta = np.arctan2(z,np.sqrt(x**2+ y**2)) * 360 / 2 / np.pi
    phi = np.arctan2(y,x) * 360 / 2 / np.pi
    return (r, theta, phi)


def juice_furnish():
    juice_path = kernels_path+'juice/'
    generic_path = kernels_path+'generic/'
    juice_kernels = os.listdir(juice_path)
    generic_kernels = os.listdir(generic_path)
    for kernel in juice_kernels:
        spiceypy.furnsh(os.path.join(juice_path, kernel))
    for kernel in generic_kernels:
        spiceypy.furnsh(os.path.join(generic_path, kernel))


def get_juice_pos(t):
    if spiceypy.ktotal('ALL') < 1:
        juice_furnish()
    try:
        pos = spiceypy.spkpos("JUICE", spiceypy.datetime2et(t), "HEEQ", "NONE", "SUN")[0] #calls positions in HEEQ; can be changed
        r, lat, lon = cart2sphere(pos[0],pos[1],pos[2])
        position = t, pos[0], pos[1], pos[2], r, lat, lon
        return position
    except Exception as e:
        print(e)
        return [t, None, None, None, None, None, None]


def get_juice_positions(time_series):
    positions = []
    for t in time_series:
        position = get_juice_pos(t)
        positions.append(position)
    df_positions = pd.DataFrame(positions, columns=['time', 'x', 'y', 'z', 'r', 'lat', 'lon'])
    return df_positions


def get_juice_positions_daily(start, end, cadence=1, dist_unit='au', ang_unit='deg'):
    t = start
    positions = []
    while t < end:
        position = get_juice_pos(t)
        positions.append(position)
        t += timedelta(days=cadence)
    df_positions = pd.DataFrame(positions, columns=['time', 'x', 'y', 'z', 'r', 'lat', 'lon'])
    if dist_unit == 'au':
        df_positions.x = df_positions.x/1.495978707E8
        df_positions.y = df_positions.y/1.495978707E8
        df_positions.z = df_positions.z/1.495978707E8
    if ang_unit == 'rad':
        df_positions.lat = df_positions.lat * np.pi / 180
        df_positions.lon = df_positions.lon * np.pi / 180
    spiceypy.kclear()
    return df_positions


def get_juice_positions_hourly(start, end, cadence=1, dist_unit='au', ang_unit='deg'):
    t = start
    positions = []
    while t < end:
        position = get_juice_pos(t)
        positions.append(position)
        t += timedelta(hours=cadence)
    df_positions = pd.DataFrame(positions, columns=['time', 'x', 'y', 'z', 'r', 'lat', 'lon'])
    if dist_unit == 'au':
        df_positions.x = df_positions.x/1.495978707E8
        df_positions.y = df_positions.y/1.495978707E8
        df_positions.z = df_positions.z/1.495978707E8
    if ang_unit == 'rad':
        df_positions.lat = df_positions.lat * np.pi / 180
        df_positions.lon = df_positions.lon * np.pi / 180
    spiceypy.kclear()
    return df_positions


def get_juice_positions_minute(start, end, cadence=1, dist_unit='au', ang_unit='deg'):
    t = start
    positions = []
    while t < end:
        position = get_juice_pos(t)
        positions.append(position)
        t += timedelta(minutes=cadence)
    df_positions = pd.DataFrame(positions, columns=['time', 'x', 'y', 'z', 'r', 'lat', 'lon'])
    if dist_unit == 'au':
        df_positions.x = df_positions.x/1.495978707E8
        df_positions.y = df_positions.y/1.495978707E8
        df_positions.z = df_positions.z/1.495978707E8
    if ang_unit == 'rad':
        df_positions.lat = df_positions.lat * np.pi / 180
        df_positions.lon = df_positions.lon * np.pi / 180
    spiceypy.kclear()
    return df_positions