From 1346c0db688b95fa9a8bc080f27d9e69a8041ba2 Mon Sep 17 00:00:00 2001 From: Laura Sandoval <46567335+laspsandoval@users.noreply.github.com> Date: Fri, 22 Nov 2024 14:46:03 -0700 Subject: [PATCH] Ultra l1c pset updates (#1059) * Ultra l1c pset updates --- imap_processing/spice/geometry.py | 76 +++++++ .../imap_ena_sim_metakernel.template | 4 +- imap_processing/tests/spice/test_geometry.py | 51 +++++ .../l1/dps_exposure_helio_45_E12.cdf | Bin 166800 -> 168921 bytes .../l1/dps_exposure_helio_45_E24.cdf | Bin 166800 -> 169566 bytes .../ultra/unit/test_ultra_l1c_pset_bins.py | 53 +---- imap_processing/ultra/constants.py | 5 + .../ultra/l1c/ultra_l1c_pset_bins.py | 189 +++++++----------- 8 files changed, 214 insertions(+), 164 deletions(-) diff --git a/imap_processing/spice/geometry.py b/imap_processing/spice/geometry.py index 4f54a0f68..950004124 100644 --- a/imap_processing/spice/geometry.py +++ b/imap_processing/spice/geometry.py @@ -19,6 +19,7 @@ import numpy.typing as npt import pandas as pd import spiceypy as spice +from numpy.typing import NDArray from imap_processing.spice.kernels import ensure_spice @@ -489,3 +490,78 @@ def basis_vectors( ... spacecraft_z = basis_vectors[:, 2] """ return np.moveaxis(get_rotation_matrix(et, from_frame, to_frame), -1, -2) + + +def cartesian_to_spherical( + v: NDArray, +) -> NDArray: + """ + Convert cartesian coordinates to spherical coordinates. + + Parameters + ---------- + v : np.ndarray + A NumPy array with shape (n, 3) where each + row represents a vector + with x, y, z-components. + + Returns + ------- + spherical_coords : np.ndarray + A NumPy array with shape (n, 3), where each row contains + the spherical coordinates (r, azimuth, elevation): + + - r : Distance of the point from the origin. + - azimuth : angle in the xy-plane in radians [0, 2*pi]. + - elevation : angle from the z-axis in radians [-pi/2, pi/2]. + """ + # Magnitude of the velocity vector + magnitude_v = np.linalg.norm(v, axis=-1, keepdims=True) + + vhat = v / magnitude_v + + # Elevation angle (angle from the z-axis, range: [-pi/2, pi/2]) + el = np.arcsin(vhat[..., 2]) + + # Azimuth angle (angle in the xy-plane, range: [0, 2*pi]) + az = np.arctan2(vhat[..., 1], vhat[..., 0]) + + # Ensure azimuth is from 0 to 2PI + az = az % (2 * np.pi) + spherical_coords = np.stack( + (np.squeeze(magnitude_v), np.degrees(az), np.degrees(el)), axis=-1 + ) + + return spherical_coords + + +def spherical_to_cartesian(spherical_coords: NDArray) -> NDArray: + """ + Convert spherical coordinates to Cartesian coordinates. + + Parameters + ---------- + spherical_coords : np.ndarray + A NumPy array with shape (n, 3), where each row contains + the spherical coordinates (r, azimuth, elevation): + + - r : Distance of the point from the origin. + - azimuth : angle in the xy-plane in radians [0, 2*pi]. + - elevation : angle from the z-axis in radians [-pi/2, pi/2]. + + Returns + ------- + cartesian_coords : np.ndarray + Cartesian coordinates. + """ + r = spherical_coords[..., 0] + azimuth = spherical_coords[..., 1] + elevation = spherical_coords[..., 2] + + x = r * np.cos(elevation) * np.cos(azimuth) + y = r * np.cos(elevation) * np.sin(azimuth) + z = r * np.sin(elevation) + + cartesian_coords = np.stack((x, y, z), axis=-1) + + return cartesian_coords diff --git a/imap_processing/tests/spice/test_data/imap_ena_sim_metakernel.template b/imap_processing/tests/spice/test_data/imap_ena_sim_metakernel.template index c14d7a30d..b320a4014 100644 --- a/imap_processing/tests/spice/test_data/imap_ena_sim_metakernel.template +++ b/imap_processing/tests/spice/test_data/imap_ena_sim_metakernel.template @@ -3,4 +3,6 @@ {SPICE_TEST_DATA_PATH}/imap_spk_demo.bsp {SPICE_TEST_DATA_PATH}/sim_1yr_imap_attitude.bc {SPICE_TEST_DATA_PATH}/imap_wkcp.tf -{SPICE_TEST_DATA_PATH}/de440s.bsp \ No newline at end of file +{SPICE_TEST_DATA_PATH}/de440s.bsp +{SPICE_TEST_DATA_PATH}/imap_science_0001.tf +{SPICE_TEST_DATA_PATH}/sim_1yr_imap_pointing_frame.bc \ No newline at end of file diff --git a/imap_processing/tests/spice/test_geometry.py b/imap_processing/tests/spice/test_geometry.py index b71a6873e..e64bdcd95 100644 --- a/imap_processing/tests/spice/test_geometry.py +++ b/imap_processing/tests/spice/test_geometry.py @@ -9,6 +9,7 @@ SpiceBody, SpiceFrame, basis_vectors, + cartesian_to_spherical, frame_transform, get_instrument_spin_phase, get_rotation_matrix, @@ -17,6 +18,7 @@ get_spin_data, imap_state, instrument_pointing, + spherical_to_cartesian, ) from imap_processing.spice.kernels import ensure_spice @@ -335,3 +337,52 @@ def test_basis_vectors(): SpiceFrame.ECLIPJ2000, ), ) + + +def test_cartesian_to_spherical(): + """Tests cartesian_to_spherical function.""" + + step = 0.05 + x = np.arange(-1, 1 + step, step) + y = np.arange(-1, 1 + step, step) + z = np.arange(-1, 1 + step, step) + x, y, z = np.meshgrid(x, y, z) + + cartesian_points = np.stack((x.ravel(), y.ravel(), z.ravel()), axis=-1) + + for point in cartesian_points: + r, az, el = cartesian_to_spherical(point) + r_spice, colat_spice, slong_spice = spice.recsph(point) + + # Convert SPICE co-latitude to elevation + el_spice = 90 - np.degrees(colat_spice) + az_spice = np.degrees(slong_spice) + + # Normalize azimuth to [0, 360] + az_spice = az_spice % 360 + + np.testing.assert_allclose(r, r_spice, atol=1e-5) + np.testing.assert_allclose(az, az_spice, atol=1e-5) + np.testing.assert_allclose(el, el_spice, atol=1e-5) + + +def test_spherical_to_cartesian(): + """Tests spherical_to_cartesian function.""" + + azimuth = np.linspace(0, 2 * np.pi, 50) + elevation = np.linspace(-np.pi / 2, np.pi / 2, 50) + theta, elev = np.meshgrid(azimuth, elevation) + r = 1.0 + + spherical_points = np.stack( + (r * np.ones_like(theta).ravel(), theta.ravel(), elev.ravel()), axis=-1 + ) + + # Convert elevation to colatitude for SPICE + colat = np.pi / 2 - spherical_points[:, 2] + + for i in range(len(colat)): + cartesian_coords = spherical_to_cartesian(np.array([spherical_points[i]])) + 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Returns ------- - energy_bin_edges : np.ndarray - Array of energy bin edges. + intervals : list[tuple[float, float]] + Energy bins. energy_midpoints : np.ndarray Array of energy bin midpoints. """ - # TODO: these value will almost certainly change. - alpha = 0.2 # deltaE/E - energy_start = 3.385 # energy start for the Ultra grids - n_bins = 23 # number of energy bins - # Calculate energy step - energy_step = (1 + alpha / 2) / (1 - alpha / 2) + energy_step = (1 + UltraConstants.ALPHA / 2) / (1 - UltraConstants.ALPHA / 2) # Create energy bins. - energy_bin_edges = energy_start * energy_step ** np.arange(n_bins + 1) + energy_bin_edges = UltraConstants.ENERGY_START * energy_step ** np.arange( + UltraConstants.N_BINS + 1 + ) # Add a zero to the left side for outliers and round to nearest 3 decimal places. energy_bin_edges = np.around(np.insert(energy_bin_edges, 0, 0), 3) energy_midpoints = (energy_bin_edges[:-1] + energy_bin_edges[1:]) / 2 - return energy_bin_edges, energy_midpoints + intervals = [ + (float(energy_bin_edges[i]), float(energy_bin_edges[i + 1])) + for i in range(len(energy_bin_edges) - 1) + ] + + return intervals, energy_midpoints def build_spatial_bins( - spacing: float = 0.5, + az_spacing: float = 0.5, + el_spacing: float = 0.5, ) -> tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray]: """ Build spatial bin boundaries for azimuth and elevation. Parameters ---------- - spacing : float, optional - The bin spacing in degrees (default is 0.5 degrees). + az_spacing : float, optional + The azimuth bin spacing in degrees (default is 0.5 degrees). + el_spacing : float, optional + The elevation bin spacing in degrees (default is 0.5 degrees). Returns ------- @@ -65,124 +73,71 @@ def build_spatial_bins( Array of elevation bin midpoint values. """ # Azimuth bins from 0 to 360 degrees. - az_bin_edges = np.arange(0, 360 + spacing, spacing) - az_bin_midpoints = az_bin_edges[:-1] + spacing / 2 # Midpoints between edges + az_bin_edges = np.arange(0, 360 + az_spacing, az_spacing) + az_bin_midpoints = az_bin_edges[:-1] + az_spacing / 2 # Midpoints between edges # Elevation bins from -90 to 90 degrees. - el_bin_edges = np.arange(-90, 90 + spacing, spacing) - el_bin_midpoints = el_bin_edges[:-1] + spacing / 2 # Midpoints between edges + el_bin_edges = np.arange(-90, 90 + el_spacing, el_spacing) + el_bin_midpoints = el_bin_edges[:-1] + el_spacing / 2 # Midpoints between edges return az_bin_edges, el_bin_edges, az_bin_midpoints, el_bin_midpoints -def cartesian_to_spherical( - v: NDArray, -) -> tuple[np.ndarray, np.ndarray, np.ndarray]: - """ - Convert cartesian coordinates to spherical coordinates. - - Parameters - ---------- - v : np.ndarray - A NumPy array with shape (n, 3) where each - row represents a vector - with x, y, z-components. - - Returns - ------- - az : np.ndarray - The azimuth angles in degrees. - el : np.ndarray - The elevation angles in degrees. - r : np.ndarray - The radii, or magnitudes, of the vectors. - """ - vx = v[:, 0] - vy = v[:, 1] - vz = v[:, 2] - - # Magnitude of the velocity vector - magnitude_v = np.sqrt(vx**2 + vy**2 + vz**2) - - vhat_x = -vx / magnitude_v - vhat_y = -vy / magnitude_v - vhat_z = -vz / magnitude_v - - # Elevation angle (angle from the z-axis, range: [-pi/2, pi/2]) - el = np.arcsin(vhat_z) - - # Azimuth angle (angle in the xy-plane, range: [0, 2*pi]) - az = np.arctan2(vhat_y, vhat_x) - - # Ensure azimuth is from 0 to 2PI - az = az % (2 * np.pi) - - return np.degrees(az), np.degrees(el), magnitude_v - - -def spherical_to_cartesian( - r: np.ndarray, theta: np.ndarray, phi: np.ndarray -) -> tuple[np.ndarray, np.ndarray, np.ndarray]: - """ - Convert spherical coordinates to Cartesian coordinates. - - Parameters - ---------- - r : np.ndarray - Radius. - theta : np.ndarray - Azimuth angle in radians. - phi : array-like or float - Elevation angle in radians. - - Returns - ------- - x, y, z : tuple - Cartesian coordinates. - """ - x = r * np.cos(phi) * np.cos(theta) - y = r * np.cos(phi) * np.sin(theta) - z = r * np.sin(phi) - - return x, y, z - - def get_histogram( - v: tuple[np.ndarray, np.ndarray, np.ndarray], + vhat: tuple[np.ndarray, np.ndarray, np.ndarray], energy: np.ndarray, az_bin_edges: np.ndarray, el_bin_edges: np.ndarray, - energy_bin_edges: np.ndarray, + energy_bin_edges: list[tuple[float, float]], ) -> NDArray: """ Compute a 3D histogram of the particle data. Parameters ---------- - v : tuple[np.ndarray, np.ndarray, np.ndarray] - The x,y,z-components of the velocity vector. + vhat : tuple[np.ndarray, np.ndarray, np.ndarray] + The x,y,z-components of the unit velocity vector. energy : np.ndarray The particle energy. az_bin_edges : np.ndarray Array of azimuth bin boundary values. el_bin_edges : np.ndarray Array of elevation bin boundary values. - energy_bin_edges : np.ndarray + energy_bin_edges : list[tuple[float, float]] Array of energy bin edges. Returns ------- hist : np.ndarray A 3D histogram array. + + Notes + ----- + The histogram will now work properly for overlapping energy bins, i.e. + the same energy value can fall into multiple bins if the intervals overlap. """ - az, el, _ = cartesian_to_spherical(v) + spherical_coords = cartesian_to_spherical(vhat) + az, el = ( + spherical_coords[..., 1], + spherical_coords[..., 2], + ) - # 3D binning. - hist, _ = np.histogramdd( - sample=(az, el, energy), bins=[az_bin_edges, el_bin_edges, energy_bin_edges] + # Initialize histogram + hist_total = np.zeros( + (len(az_bin_edges) - 1, len(el_bin_edges) - 1, len(energy_bin_edges)) ) - return hist + for i, (e_min, e_max) in enumerate(energy_bin_edges): + # Filter data for current energy bin. + mask = (energy >= e_min) & (energy < e_max) + hist, _ = np.histogramdd( + sample=(az[mask], el[mask], energy[mask]), + bins=[az_bin_edges, el_bin_edges, [e_min, e_max]], + ) + # Assign 2D histogram to current energy bin. + hist_total[:, :, i] = hist[:, :, 0] + + return hist_total def get_pointing_frame_exposure_times( @@ -211,19 +166,17 @@ def get_pointing_frame_exposure_times( return exposure -@ensure_spice -@typing.no_type_check def get_helio_exposure_times( time: np.ndarray, sc_exposure: np.ndarray, -) -> np.ndarray: +) -> NDArray: """ Compute a 3D array of the exposure in the helio frame. Parameters ---------- time : np.ndarray - Median time of pointing. + Median time of pointing in J2000 seconds. sc_exposure : np.ndarray Spacecraft exposure. @@ -237,7 +190,7 @@ def get_helio_exposure_times( These calculations are performed once per pointing. """ # Get bins and midpoints. - energy_bin_edges, energy_midpoints = build_energy_bins() + _, energy_midpoints = build_energy_bins() az_bin_edges, el_bin_edges, az_bin_midpoints, el_bin_midpoints = ( build_spatial_bins() ) @@ -252,15 +205,12 @@ def get_helio_exposure_times( # Radial distance. r = np.ones(el_grid.shape) - x, y, z = spherical_to_cartesian(r, np.radians(az_grid), np.radians(el_grid)) - - # Reshape and combine the Cartesian coordinates into a 2D array. - cartesian = np.vstack( - [x.flatten(order="F"), y.flatten(order="F"), z.flatten(order="F")] - ) + spherical_coords = np.stack((r, np.radians(az_grid), np.radians(el_grid)), axis=-1) + cartesian_coords = spherical_to_cartesian(spherical_coords) + cartesian = cartesian_coords.reshape(-1, 3, order="F").T # Spacecraft velocity in the pointing (DPS) frame wrt heliosphere. - state, lt = spice.spkezr("IMAP", time, "IMAP_DPS", "NONE", "SUN") + state = imap_state(time, ref_frame=SpiceFrame.IMAP_DPS) # Extract the velocity part of the state vector spacecraft_velocity = state[3:6] @@ -273,7 +223,7 @@ def get_helio_exposure_times( / 1e3 ) - # Use Compton-Getting to transform the velocity wrt spacecraft + # Use Galilean Transform to transform the velocity wrt spacecraft # to the velocity wrt heliosphere. # energy_velocity * cartesian -> apply the magnitude of the velocity # to every position on the grid in the despun grid. @@ -284,10 +234,11 @@ def get_helio_exposure_times( helio_velocity.T, axis=1, keepdims=True ) # Converts vectors from Cartesian coordinates (x, y, z) - # into spherical coordinates - az, el, _ = cartesian_to_spherical(-helio_normalized) + # into spherical coordinates. + spherical_coords = cartesian_to_spherical(helio_normalized) + az, el = spherical_coords[..., 1], spherical_coords[..., 2] - # Bin the coordinates. + # Assign values from sc_exposure directly to bins. az_idx = np.digitize(az, az_bin_edges) - 1 el_idx = np.digitize(el, el_bin_edges[::-1]) - 1