SPICE - Spin phase query utils function - using spin start and spin rate data.

[tech3371]

For a given input time, this function will need to return spin phase angle of spacecraft.

Function signature

def get_spacecarft_spin_phase(query_times: Union[float, np.ndarray]) -> Union[float, np.ndarray]:
"""
Compute the floating point spin phase using spin table [0, 1] at the input times.
"""
spin_table = get_spin_table()  # Start with this function?
spin_phase = (query_time - (spin_start_seconds + spin_start_subseconds)) / spin_period_sec

Could also add a function to get instrument spin phase (Put this in a new ticket?)

def get_instrument_spin_phase(query_times: Union[float, np.ndarray], instrument_id: IntEnum) -> Union[float, np.ndarray]:
instrument_spin_phase = get_spacecraft_spin_phase + get_instrument_phase_offset()

fixture function signature

def gen_spin_table(start_time: datetime, end_time: datetime = None) -> Path:
"""
Generate a pointing table CSV covering one or more days.

Parameters
-----------
start_time : provides the starting day of year
end_time : optionally specify end day of year. If not provided default to one day

Returns
--------
Path to CSV file

Tim's prototype code:

# Spin table contains the following fields:
# (spin_number, spin_start_sec, spin_start_subsec, spin_period_sec, spin_period_valid, spin_phas_valid, spin_period_source, thruster_firing)
seconds_per_point = 24 * 60 * 60

# get the very first spin start sclk
_, start_sclk_sec, start_sclk_ticks = parse_sclk_str(spice.sce2s(SC_ID, cov[0]))
_, end_sclk_sec, end_sclk_ticks = parse_sclk_str(spice.sce2s(SC_ID, cov[-1]))

# fill the whole year worth of spin data with assuming ideal 15 seccond spins
spin_dict = dict()
spin_start_sec = np.arange(start_sclk_sec, end_sclk_sec, 15, dtype=np.uint64)
spin_dict["spin_number"] = np.arange(spin_start_sec.size, dtype=np.uint64)
spin_dict["spin_start_sec"] = spin_start_sec
spin_dict["spin_start_subsec"] = np.full(spin_dict["spin_start_sec"].size, start_sclk_ticks * TICKS_TO_MS, dtype=np.uint64)
spin_dict["spin_period_sec"] = np.full(spin_dict["spin_start_sec"].size, 15.0, dtype=np.float64)
spin_dict["spin_period_valid"] = np.ones(spin_dict["spin_start_sec"].size, dtype=np.uint8)
spin_dict["spin_period_phase"] = np.ones(spin_dict["spin_start_sec"].size, dtype=np.uint8)
spin_dict["spin_period_source"] = np.zeros(spin_dict["spin_start_sec"].size, dtype=np.uint8)
spin_dict["thruster_firing"] = np.zeros(spin_dict["spin_start_sec"].size, dtype=np.uint8)

spin_start_float = np.arange(cov[0], cov[-1], 15)

# Set thruster firing flag. Intervals here indicate time during repointing
for i_pointing, interval in enumerate(cov[1:-1].reshape((-1, 2))):
    # set values where spin end time is greater than repoint start and spin start time is < repoint end
    firing_mask = np.logical_and(
        spin_start_float + spin_dict["spin_period_sec"] >= interval[0],
        spin_start_float < interval[1]
    )
    spin_dict["thruster_firing"][firing_mask] = 1
    spin_dict["spin_period_valid"][firing_mask] = 0

spin_df = pd.DataFrame.from_dict(spin_dict)
spin_df.to_csv("imap_2025_106_2026_105_v00.spin.csv", index=False)