From f8473d9b14c8c29608ed863a442d1ecc5a30cca8 Mon Sep 17 00:00:00 2001 From: Olivia Lynn Date: Tue, 20 Aug 2024 09:36:58 -0400 Subject: [PATCH 01/38] Add new need-interpolation checks; begin interpolation code --- src/tdastro/astro_utils/interpolation.py | 43 +++++++++++++++++++ src/tdastro/astro_utils/passbands.py | 34 +++++++++++++-- .../tdastro/astro_utils/test_interpolation.py | 11 +++++ 3 files changed, 84 insertions(+), 4 deletions(-) create mode 100644 src/tdastro/astro_utils/interpolation.py create mode 100644 tests/tdastro/astro_utils/test_interpolation.py diff --git a/src/tdastro/astro_utils/interpolation.py b/src/tdastro/astro_utils/interpolation.py new file mode 100644 index 00000000..51eed0af --- /dev/null +++ b/src/tdastro/astro_utils/interpolation.py @@ -0,0 +1,43 @@ +import numpy as np + + +def get_grid_step(grid: np.ndarray) -> float: + """Get the step size of a grid. + + Parameters + ---------- + grid : np.ndarray + The grid. + + Returns + ------- + float + The step size of the grid. + """ + # Get the step sizes of the grid + step_size = np.diff(grid) + + # Check if the step sizes are consistent across the grid + if not np.allclose(step_size, step_size[0]): + raise ValueError("The grid step sizes are not consistent.") + + # Return the step size + return step_size[0] + + +def grids_have_same_step(grid1: np.ndarray, grid2: np.ndarray) -> bool: + """Check if two grids have the same step size. + + Parameters + ---------- + grid1 : np.ndarray + The first grid. + grid2 : np.ndarray + The second grid. + + Returns + ------- + bool + True if the grids have the same step size, False otherwise. + """ + return np.isclose(get_grid_step(grid1), get_grid_step(grid2)) diff --git a/src/tdastro/astro_utils/passbands.py b/src/tdastro/astro_utils/passbands.py index 66670e14..97bb07fd 100644 --- a/src/tdastro/astro_utils/passbands.py +++ b/src/tdastro/astro_utils/passbands.py @@ -7,6 +7,8 @@ import numpy as np import scipy.integrate +from tdastro.astro_utils import interpolation + logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s") @@ -117,6 +119,10 @@ def __init__(self, survey, label, table_path=None, table_url=""): self.transmission_table = self._load_transmission_table() self.normalized_transmission_table = self._normalize_transmission_table() + def __str__(self) -> str: + """Return a string representation of the Passband.""" + return f"Passband: {self.full_name}" + def _load_transmission_table(self) -> np.ndarray: """Load a transmission table from a file or URL. @@ -183,7 +189,6 @@ def _normalize_transmission_table(self) -> np.ndarray: Notes ----- - We use transmission table here to represent S_b(λ). - - There is currently no interpolation implemented (but coming very soon). Returns ------- @@ -199,7 +204,9 @@ def _normalize_transmission_table(self) -> np.ndarray: normalized_transmissions = numerators / denominator return np.column_stack((wavelengths_angstrom, normalized_transmissions)) - def fluxes_to_bandflux(self, flux_density_matrix, wavelengths_angstrom) -> np.ndarray: + def fluxes_to_bandflux( + self, flux_density_matrix, wavelengths_angstrom, interpolate_to_grid=None + ) -> np.ndarray: """Calculate the bandflux for a given set of flux densities. This is eq. 7 from "On the Choice of LSST Flux Units" (Ivezić et al.): @@ -215,14 +222,33 @@ def fluxes_to_bandflux(self, flux_density_matrix, wavelengths_angstrom) -> np.nd A 2D array of flux densities where rows are times and columns are wavelengths. wavelengths_angstrom : np.ndarray An array of wavelengths in Angstroms corresponding to the columns of flux_density_matrix. + interpolate_to_grid : int, optional + The unit of the grid (in Angstrom) to which the flux density matrix and normalized transmission + table should be interpolated. Returns ------- np.ndarray An array of bandfluxes. """ - # Check that the grid of wavelengths_angstrom matches the band's transmission table - # NOTE: this is where we would handle interpolation and exterpolation as needed--PR incoming! + n_t_table = self.normalized_transmission_table + + # Interpolate the flux density matrix and normalized transmission table to the same grid, if needed + if interpolate_to_grid is not None: + wavelengths_angstrom = interpolation.to_grid( + interpolate_to_grid, wavelengths_angstrom, flux_density_matrix + ) + + elif not interpolation.grids_have_same_step(wavelengths_angstrom, n_t_table[:, 0]): + raise ValueError( + f"Interpolation needed: grids do not match. " + f"Flux density grid step size is{interpolation.get_grid_step(wavelengths_angstrom)}; " + f"Transmission table grid step size is " + f"{interpolation.get_grid_step(self.normalized_transmission_table[:, 0])}. " + f"Consider using the interpolate_to_grid parameter." + ) + + # TODO replace the following with forthcoming exterpolation astro_utils code # For now, min check: the bounds of the flux density grid are within the transmission table bounds if ( wavelengths_angstrom[-1] < self.normalized_transmission_table[-1, 0] diff --git a/tests/tdastro/astro_utils/test_interpolation.py b/tests/tdastro/astro_utils/test_interpolation.py new file mode 100644 index 00000000..0576eef5 --- /dev/null +++ b/tests/tdastro/astro_utils/test_interpolation.py @@ -0,0 +1,11 @@ +import numpy as np +from tdastro.astro_utils.interpolation import grids_have_same_step + + +def test_check_grids_same_step(): + """Test check_grids_same_step_size function.""" + a1 = np.array([1, 2, 3]) + a2 = np.array([11, 12, 13, 14, 15]) + a3 = np.array([1, 2, 3, 40]) + assert grids_have_same_step(a1, a2) + assert not grids_have_same_step(a1, a3) From b223a4e58346f82a28d10c6000d64c767d7f4f6f Mon Sep 17 00:00:00 2001 From: Olivia Lynn Date: Fri, 23 Aug 2024 12:30:57 -0400 Subject: [PATCH 02/38] Add support for nonuniform grids --- src/tdastro/astro_utils/interpolation.py | 103 ++++++++++++++-- src/tdastro/astro_utils/passbands.py | 96 +++++++++------ .../tdastro/astro_utils/test_interpolation.py | 112 +++++++++++++++++- 3 files changed, 264 insertions(+), 47 deletions(-) diff --git a/src/tdastro/astro_utils/interpolation.py b/src/tdastro/astro_utils/interpolation.py index 51eed0af..5e1f7df9 100644 --- a/src/tdastro/astro_utils/interpolation.py +++ b/src/tdastro/astro_utils/interpolation.py @@ -2,7 +2,7 @@ def get_grid_step(grid: np.ndarray) -> float: - """Get the step size of a grid. + """Get the step size of a grid if it is uniform; otherwise, return None. Parameters ---------- @@ -11,18 +11,12 @@ def get_grid_step(grid: np.ndarray) -> float: Returns ------- - float - The step size of the grid. + float or None + The step size of the grid if it is uniform, otherwise None. """ - # Get the step sizes of the grid - step_size = np.diff(grid) - - # Check if the step sizes are consistent across the grid - if not np.allclose(step_size, step_size[0]): - raise ValueError("The grid step sizes are not consistent.") - - # Return the step size - return step_size[0] + if np.allclose(np.diff(grid), np.diff(grid)[0]): + return np.diff(grid)[0] + return None def grids_have_same_step(grid1: np.ndarray, grid2: np.ndarray) -> bool: @@ -40,4 +34,87 @@ def grids_have_same_step(grid1: np.ndarray, grid2: np.ndarray) -> bool: bool True if the grids have the same step size, False otherwise. """ - return np.isclose(get_grid_step(grid1), get_grid_step(grid2)) + # If both grids have the same length, we can account for non-uniform grids + if len(grid1) == len(grid2): + return np.allclose(np.diff(grid1), np.diff(grid2)) + # If the grids have different lengths, they must be uniform to have the same step size + return get_grid_step(grid1) is not None and get_grid_step(grid1) == get_grid_step(grid2) + + +def interpolate_wavelengths(wavelengths: np.ndarray, new_grid_step: float) -> np.ndarray: + """Interpolate a grid of wavelengths to a new grid with a given step size. + + TODO add note about whether the upper bound is included in the new grid + + Parameters + ---------- + wavelengths : np.ndarray + The grid of wavelengths (must be strictly increasing). + new_grid_step : float + The step size of the new grid. + + Returns + ------- + np.ndarray + The interpolated grid. + """ + # Check that wavelengths are strictly increasing + if not np.all(np.diff(wavelengths) > 0): + raise ValueError("Wavelengths must be strictly increasing.") + new_grid = np.arange(wavelengths[0], wavelengths[-1] + new_grid_step, new_grid_step) + return new_grid + + +def interpolate_transmission_table(table: np.ndarray, new_wavelengths: np.ndarray) -> np.ndarray: + """Interpolate a 2 column table (such that the first column is x and the second column is y; eg, + a transmission table) to a new grid of x values. + + Parameters + ---------- + table : np.ndarray + The table to interpolate. Must be a 2D array with shape (n, 2). + new_wavelengths : np.ndarray + The new wavelengths grid to interpolate to. Must be a 1D array of length m. + + Returns + ------- + np.ndarray + The interpolated table, with shape (m, 2). + """ + if table.shape[1] != 2: + raise ValueError("Table must have exactly 2 columns.") + interpolated_transmissions = np.interp(new_wavelengths, table[:, 0], table[:, 1]) + return np.column_stack((new_wavelengths, interpolated_transmissions)) + + +def interpolate_matrix_along_wavelengths( + matrix: np.ndarray, wavelengths: np.ndarray, new_wavelengths: np.ndarray +) -> np.ndarray: + """Interpolate a matrix with columns corresponding to a vector of wavelengths. + + Parameters + ---------- + matrix : np.ndarray + A 2D matrix to interpolate, with size (n, m). + wavelengths : np.ndarray + The wavelengths corresponding to the matrix, with size m. + new_wavelengths : np.ndarray + The new grid of wavelengths to interpolate to, with size p. + + Returns + ------- + np.ndarray + The interpolated matrix, with size (n, p). + """ + if matrix.shape[1] != len(wavelengths): + raise ValueError( + f"Matrix has {matrix.shape[1]} columns, but {len(wavelengths)} wavelengths were given." + ) + new_matrix = np.array([np.interp(new_wavelengths, wavelengths, row) for row in matrix]) + return new_matrix + + +""" +TODO +- Different interpolation methods? +""" diff --git a/src/tdastro/astro_utils/passbands.py b/src/tdastro/astro_utils/passbands.py index 97bb07fd..2904a85a 100644 --- a/src/tdastro/astro_utils/passbands.py +++ b/src/tdastro/astro_utils/passbands.py @@ -96,7 +96,7 @@ class Passband: ---------- label : str The label of the passband. - survey : str + survey : str The survey to which the passband belongs. full_name : str The full name of the passband. @@ -204,8 +204,59 @@ def _normalize_transmission_table(self) -> np.ndarray: normalized_transmissions = numerators / denominator return np.column_stack((wavelengths_angstrom, normalized_transmissions)) + def _interpolate( + self, initial_fluxes, intial_wavelengths, initial_norm_trans_table, target_grid_step=None + ): + """Interpolate the flux density matrix and normalized transmission table to the same grid. + + Parameters + ---------- + initial_fluxes : np.ndarray + A 2D array of flux densities where rows are times and columns are wavelengths. + intial_wavelengths : np.ndarray + An array of wavelengths in Angstroms corresponding to the columns of initial_fluxes. + initial_norm_trans_table : np.ndarray + A 2D array of wavelengths and normalized transmissions. + target_grid_step : int, optional + The unit of the grid (in Angstrom) to which the flux density matrix and normalized transmission + table should be interpolated. + + Returns + ------- + tuple of np.ndarray + A tuple of interpolated flux densities, wavelengths, and normalized transmission table. + """ + if target_grid_step is None: + # If grids already match, we can just return the intial arrays + if interpolation.grids_have_same_step(intial_wavelengths, initial_norm_trans_table[:, 0]): + return (initial_fluxes, intial_wavelengths, initial_norm_trans_table) + # Otherwise, if the given wavelength grid is uniform, interpolate transmisison table to match + elif interpolation.get_grid_step(intial_wavelengths) is not None: + target_grid_step = interpolation.get_grid_step(intial_wavelengths) + # Otherwise, ask for target grid step + else: + raise ValueError( + "Interpolation needed; grids do not match. Consider using the target_grid_step parameter." + ) + + interp_wavelengths = intial_wavelengths + interp_fluxes = initial_fluxes + if target_grid_step != interpolation.get_grid_step(intial_wavelengths): + interp_wavelengths = interpolation.interpolate_wavelengths(intial_wavelengths, target_grid_step) + interp_fluxes = interpolation.interpolate_matrix_along_wavelengths( + initial_fluxes, intial_wavelengths, interp_wavelengths + ) + + interp_norm_trans_table = initial_norm_trans_table + if target_grid_step != interpolation.get_grid_step(initial_norm_trans_table[:, 0]): + interp_norm_trans_table = interpolation.interpolate_transmission_table( + initial_norm_trans_table, interp_wavelengths + ) + + return (interp_fluxes, interp_wavelengths, interp_norm_trans_table) + def fluxes_to_bandflux( - self, flux_density_matrix, wavelengths_angstrom, interpolate_to_grid=None + self, _flux_density_matrix, _wavelengths_angstrom, target_grid_step=None ) -> np.ndarray: """Calculate the bandflux for a given set of flux densities. @@ -222,7 +273,7 @@ def fluxes_to_bandflux( A 2D array of flux densities where rows are times and columns are wavelengths. wavelengths_angstrom : np.ndarray An array of wavelengths in Angstroms corresponding to the columns of flux_density_matrix. - interpolate_to_grid : int, optional + target_grid_step : float, optional The unit of the grid (in Angstrom) to which the flux density matrix and normalized transmission table should be interpolated. @@ -231,43 +282,22 @@ def fluxes_to_bandflux( np.ndarray An array of bandfluxes. """ - n_t_table = self.normalized_transmission_table - - # Interpolate the flux density matrix and normalized transmission table to the same grid, if needed - if interpolate_to_grid is not None: - wavelengths_angstrom = interpolation.to_grid( - interpolate_to_grid, wavelengths_angstrom, flux_density_matrix - ) - - elif not interpolation.grids_have_same_step(wavelengths_angstrom, n_t_table[:, 0]): - raise ValueError( - f"Interpolation needed: grids do not match. " - f"Flux density grid step size is{interpolation.get_grid_step(wavelengths_angstrom)}; " - f"Transmission table grid step size is " - f"{interpolation.get_grid_step(self.normalized_transmission_table[:, 0])}. " - f"Consider using the interpolate_to_grid parameter." - ) - - # TODO replace the following with forthcoming exterpolation astro_utils code - # For now, min check: the bounds of the flux density grid are within the transmission table bounds - if ( - wavelengths_angstrom[-1] < self.normalized_transmission_table[-1, 0] - or wavelengths_angstrom[0] > self.normalized_transmission_table[0, 0] - ): - raise ValueError( - f"Extrapolation needed: flux density interval [{wavelengths_angstrom[0]}, " - f"{wavelengths_angstrom[-1]}] is outside the transmission table interval " - f"[{self.normalized_transmission_table[0, 0]}, {self.normalized_transmission_table[-1, 0]}]." - ) + # Interpolate the flux density matrix and normalized transmission table to the same grid + (flux_density_matrix, wavelengths_angstrom, normalized_transmission_table) = self._interpolate( + _flux_density_matrix, + _wavelengths_angstrom, + self.normalized_transmission_table, + target_grid_step=target_grid_step, + ) # Get only the flux densities that are within the passband's wavelength range - passband_wavelengths = self.normalized_transmission_table[:, 0] + passband_wavelengths = normalized_transmission_table[:, 0] passband_wavelengths_indices = np.searchsorted(wavelengths_angstrom, passband_wavelengths) passband_flux_density_matrix = flux_density_matrix[:, passband_wavelengths_indices] # Calculate the bandflux as ∫ f(λ)φ_b(λ) dλ, # where f(λ) is the in-band flux density and φ_b(λ) is the normalized system response - integrand = passband_flux_density_matrix * self.normalized_transmission_table[:, 1] + integrand = passband_flux_density_matrix * normalized_transmission_table[:, 1] bandfluxes = scipy.integrate.trapezoid(integrand, x=passband_wavelengths) return bandfluxes diff --git a/tests/tdastro/astro_utils/test_interpolation.py b/tests/tdastro/astro_utils/test_interpolation.py index 0576eef5..b7d7573c 100644 --- a/tests/tdastro/astro_utils/test_interpolation.py +++ b/tests/tdastro/astro_utils/test_interpolation.py @@ -1,5 +1,12 @@ import numpy as np -from tdastro.astro_utils.interpolation import grids_have_same_step +import pytest +from tdastro.astro_utils.interpolation import ( + grids_have_same_step, + interpolate_matrix_along_wavelengths, + interpolate_transmission_table, + interpolate_wavelengths, +) +from tdastro.astro_utils.passbands import Passband def test_check_grids_same_step(): @@ -9,3 +16,106 @@ def test_check_grids_same_step(): a3 = np.array([1, 2, 3, 40]) assert grids_have_same_step(a1, a2) assert not grids_have_same_step(a1, a3) + + +def test_interpolate_wavelengths(): + """Test interpolate_wavelengths function.""" + wavelengths = np.array([1, 2, 3]) + new_grid_step = 0.5 + interp_wavelengths = interpolate_wavelengths(wavelengths, new_grid_step) + assert np.allclose(interp_wavelengths, np.array([1.0, 1.5, 2.0, 2.5, 3.0])) + + # Test non-uniform grid # TODO would this be better as its own unit test? what's the standard for this? + wavelengths = np.array([1, 2, 4]) + new_grid_step = 0.5 + interp_wavelengths = interpolate_wavelengths(wavelengths, new_grid_step) + assert np.allclose(interp_wavelengths, np.array([1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0])) + + # Test not strictly increasing grid + wavelengths = np.array([1, 2, 1]) + new_grid_step = 0.5 + with pytest.raises(ValueError): + interpolate_wavelengths(wavelengths, new_grid_step) + + +def test_interpolate_matrix_along_wavelengths(): + """Test interpolate_matrix_along_wavelengths function.""" + fluxes = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]) + wavelengths = np.array([1, 2, 3]) + new_grid_step = 0.5 + interp_wavelengths = interpolate_wavelengths(wavelengths, new_grid_step) + interp_fluxes = interpolate_matrix_along_wavelengths(fluxes, wavelengths, interp_wavelengths) + assert np.allclose( + interp_fluxes, + np.array([[1.0, 1.5, 2.0, 2.5, 3.0], [4.0, 4.5, 5.0, 5.5, 6.0], [7.0, 7.5, 8.0, 8.5, 9.0]]), + ) # TODO change to np assert? (and above) + + +def test_interpolate_transmission_table(): + """Test interpolate_transmission_table function.""" + wavelengths = np.array([0, 10, 20]) + transmissions = np.array([1, 2, 3]) + table = np.stack((wavelengths, transmissions), axis=-1) + new_wavelengths = np.linspace(0, 20, 7) + interp_transmissions = interpolate_transmission_table(table, new_wavelengths) + assert np.allclose( + interp_transmissions, + np.array( + [ + [0.0, 1.0], + [3.33333333, 1.33333333], + [6.66666667, 1.66666667], + [10.0, 2.0], + [13.33333333, 2.33333333], + [16.66666667, 2.66666667], + [20.0, 3.0], + ] + ), + ) + + # TODO test edge cases + + +def test_interpolate_passband(tmp_path): + """Test interpolate_passband function.""" + # Initial values + flux_density_matrix = np.array([[1.0, 1.0, 1.0], [1.0, 10.0, 1.0], [1.0, 0.0, 1.0]]) + wavelengths_angstrom = np.array([100.0, 105.0, 110.0]) + + # New values + new_grid_step = 1.0 + + # Make passband + survey = "TEST" + band_label = "a" + table_path = tmp_path / f"{survey}_{band_label}.dat" + transmission_table = "100 0.5\n" "110 1.0\n" + with open(table_path, "w") as f: + f.write(transmission_table) + + a_band = Passband(survey, band_label, table_path=table_path) + + # Interpolate + interpolated_matrix, interpolated_vector, interpolated_t_table = a_band._interpolate( + flux_density_matrix, + wavelengths_angstrom, + a_band.normalized_transmission_table, + target_grid_step=new_grid_step, + ) + + # Assert shape/size + assert interpolated_matrix.shape == (3, 11) + assert len(interpolated_vector) == 11 + assert len(interpolated_t_table) == 11 + + # Assert values + expected_matrix = np.array( + [ + [1.0] * 11, + [1.0, 2.8, 4.6, 6.4, 8.2, 10.0, 8.2, 6.4, 4.6, 2.8, 1.0], + [1.0, 0.8, 0.6, 0.4, 0.2, 0.0, 0.2, 0.4, 0.6, 0.8, 1.0], + ] + ) + assert np.allclose(interpolated_matrix, expected_matrix) + + # TODO add a test with a weird grid upper bound From d2046aaf658b1bb68ef8c0b19c1a8c37f75eb9e7 Mon Sep 17 00:00:00 2001 From: Olivia Lynn Date: Fri, 30 Aug 2024 13:09:32 -0400 Subject: [PATCH 03/38] Remove grids_have_same_step; Use np.allclose for Passband need interpolation check; Add has_uniform_step --- src/tdastro/astro_utils/interpolation.py | 21 ++++++++----------- src/tdastro/astro_utils/passbands.py | 6 +++--- .../tdastro/astro_utils/test_interpolation.py | 20 +++++++++++------- 3 files changed, 25 insertions(+), 22 deletions(-) diff --git a/src/tdastro/astro_utils/interpolation.py b/src/tdastro/astro_utils/interpolation.py index 5e1f7df9..7ab08aa6 100644 --- a/src/tdastro/astro_utils/interpolation.py +++ b/src/tdastro/astro_utils/interpolation.py @@ -19,26 +19,23 @@ def get_grid_step(grid: np.ndarray) -> float: return None -def grids_have_same_step(grid1: np.ndarray, grid2: np.ndarray) -> bool: - """Check if two grids have the same step size. +def has_uniform_step(grid: np.ndarray) -> bool: + """Check if a grid has a uniform step size. Parameters ---------- - grid1 : np.ndarray - The first grid. - grid2 : np.ndarray - The second grid. + grid : np.ndarray + The grid. Returns ------- bool - True if the grids have the same step size, False otherwise. + True if the grid has a uniform step size, False otherwise. If the grid has fewer than 2 elements, we + consider it to have a uniform step size. """ - # If both grids have the same length, we can account for non-uniform grids - if len(grid1) == len(grid2): - return np.allclose(np.diff(grid1), np.diff(grid2)) - # If the grids have different lengths, they must be uniform to have the same step size - return get_grid_step(grid1) is not None and get_grid_step(grid1) == get_grid_step(grid2) + if len(grid) < 2: + return True + return np.allclose(np.diff(grid), np.diff(grid)[0]) def interpolate_wavelengths(wavelengths: np.ndarray, new_grid_step: float) -> np.ndarray: diff --git a/src/tdastro/astro_utils/passbands.py b/src/tdastro/astro_utils/passbands.py index 2904a85a..869f6007 100644 --- a/src/tdastro/astro_utils/passbands.py +++ b/src/tdastro/astro_utils/passbands.py @@ -228,10 +228,10 @@ def _interpolate( """ if target_grid_step is None: # If grids already match, we can just return the intial arrays - if interpolation.grids_have_same_step(intial_wavelengths, initial_norm_trans_table[:, 0]): + if np.allclose(intial_wavelengths, initial_norm_trans_table[:, 0]): return (initial_fluxes, intial_wavelengths, initial_norm_trans_table) - # Otherwise, if the given wavelength grid is uniform, interpolate transmisison table to match - elif interpolation.get_grid_step(intial_wavelengths) is not None: + # Otherwise, if the given wavelength grid is uniform, set grid step to the step size + elif interpolation.has_uniform_step(intial_wavelengths): target_grid_step = interpolation.get_grid_step(intial_wavelengths) # Otherwise, ask for target grid step else: diff --git a/tests/tdastro/astro_utils/test_interpolation.py b/tests/tdastro/astro_utils/test_interpolation.py index b7d7573c..cf625592 100644 --- a/tests/tdastro/astro_utils/test_interpolation.py +++ b/tests/tdastro/astro_utils/test_interpolation.py @@ -1,7 +1,7 @@ import numpy as np import pytest from tdastro.astro_utils.interpolation import ( - grids_have_same_step, + has_uniform_step, interpolate_matrix_along_wavelengths, interpolate_transmission_table, interpolate_wavelengths, @@ -9,13 +9,19 @@ from tdastro.astro_utils.passbands import Passband -def test_check_grids_same_step(): - """Test check_grids_same_step_size function.""" +def test_has_uniform_step(): + """Test has_uniform_step function.""" a1 = np.array([1, 2, 3]) - a2 = np.array([11, 12, 13, 14, 15]) - a3 = np.array([1, 2, 3, 40]) - assert grids_have_same_step(a1, a2) - assert not grids_have_same_step(a1, a3) + assert has_uniform_step(a1) + + a2 = np.array([1, 2, 3, 40]) + assert not has_uniform_step(a2) + + a3 = np.array([]) + assert has_uniform_step(a3) + + a4 = np.array([1]) + assert has_uniform_step(a4) def test_interpolate_wavelengths(): From 10e76b95192d211f972cc8697e7d73913e0d3a52 Mon Sep 17 00:00:00 2001 From: Olivia Lynn Date: Fri, 30 Aug 2024 19:13:40 -0400 Subject: [PATCH 04/38] Extrapolation in --- .../interpolation-exterpolation-demo.ipynb | 178 ++++++++++++++++++ src/tdastro/astro_utils/interpolation.py | 6 - src/tdastro/astro_utils/passbands.py | 91 +++++++-- 3 files changed, 250 insertions(+), 25 deletions(-) create mode 100644 docs/notebooks/interpolation-exterpolation-demo.ipynb diff --git a/docs/notebooks/interpolation-exterpolation-demo.ipynb b/docs/notebooks/interpolation-exterpolation-demo.ipynb new file mode 100644 index 00000000..df763f25 --- /dev/null +++ b/docs/notebooks/interpolation-exterpolation-demo.ipynb @@ -0,0 +1,178 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Interpolation/Exterpolation Demo" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from tdastro.astro_utils.interpolation import (\n", + " get_grid_step,\n", + " has_uniform_step,\n", + " interpolate_matrix_along_wavelengths,\n", + " interpolate_transmission_table,\n", + " interpolate_wavelengths,\n", + ")\n", + "from tdastro.astro_utils.passbands import PassbandGroup" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Set Up PassbandGroup" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "passband_group = PassbandGroup(preset=\"LSST\")\n", + "print(passband_group)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "passband_group.passbands[\"u\"].normalized_transmission_table" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Set Up Spline Model" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "from tdastro.sources.spline_model import SplineModel\n", + "\n", + "# Load a model\n", + "input_times = np.array([1001.0, 1002.0, 1003.0, 1004.0, 1005.0])\n", + "input_wavelengths = np.linspace(2000.0, 10_000.0, 5)\n", + "input_fluxes = np.array(\n", + " [\n", + " [1.0, 5.0, 2.0, 3.0, 1.0],\n", + " [5.0, 10.0, 6.0, 7.0, 5.0],\n", + " [2.0, 6.0, 3.0, 4.0, 2.0],\n", + " [1.0, 5.0, 2.0, 3.0, 1.0],\n", + " [1.0, 5.0, 2.0, 3.0, 1.0],\n", + " ]\n", + ")\n", + "\n", + "spline_model = SplineModel(input_times, input_wavelengths, input_fluxes, time_degree=3, wave_degree=3)\n", + "\n", + "times = np.linspace(1000.0, 1006.0, 40)\n", + "wavelengths = np.linspace(2000.0, 11000.0, 30)\n", + "fluxes = spline_model.evaluate(times, wavelengths)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def plot_flux_spectrogram():\n", + " \"\"\"Plot a spectrogram to visualize the fluxes.\"\"\"\n", + " plt.imshow(fluxes.T, cmap=\"plasma\", interpolation=\"nearest\")\n", + "\n", + " # Add title, axis labels, and correct ticks\n", + " plt.title(\"Flux Spectrogram\")\n", + " plt.xlabel(\"Time (days)\")\n", + " plt.ylabel(\"Wavelength (Angstrom)\")\n", + " plt.xticks(np.arange(len(times))[::4], [f\"{round(time)}\" for time in times][::4])\n", + " plt.yticks(np.arange(len(wavelengths))[::2], [f\"{round(wave)}\" for wave in wavelengths][::2])\n", + "\n", + " # Add flux labels\n", + " for (j, i), label in np.ndenumerate(fluxes.T):\n", + " if i % 2 == 1:\n", + " plt.text(i, j, round(label, 1), ha=\"center\", va=\"center\", size=8)\n", + "\n", + " plt.show()\n", + "\n", + "\n", + "plot_flux_spectrogram()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Plot Lightcurve" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "bandfluxes = passband_group.fluxes_to_bandfluxes(fluxes, wavelengths)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def plot_lightcurve():\n", + " \"\"\"Plot the passband-normalized lightcurve.\"\"\"\n", + " fig, ax = plt.subplots()\n", + " ax.set_title(\"Passband-Normalized Lightcurve\")\n", + " ax.set_xlabel(\"Time (days)\")\n", + " ax.set_ylabel(\"Flux\")\n", + "\n", + " for i, label in enumerate(bandfluxes.keys()):\n", + " ax.plot(times, bandfluxes[label], marker=\"o\", label=label)\n", + "\n", + " ax.legend()\n", + " plt.show()\n", + "\n", + "\n", + "plot_lightcurve()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "tda", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.9" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/src/tdastro/astro_utils/interpolation.py b/src/tdastro/astro_utils/interpolation.py index 7ab08aa6..d0f5fb8c 100644 --- a/src/tdastro/astro_utils/interpolation.py +++ b/src/tdastro/astro_utils/interpolation.py @@ -109,9 +109,3 @@ def interpolate_matrix_along_wavelengths( ) new_matrix = np.array([np.interp(new_wavelengths, wavelengths, row) for row in matrix]) return new_matrix - - -""" -TODO -- Different interpolation methods? -""" diff --git a/src/tdastro/astro_utils/passbands.py b/src/tdastro/astro_utils/passbands.py index 869f6007..4ab6a045 100644 --- a/src/tdastro/astro_utils/passbands.py +++ b/src/tdastro/astro_utils/passbands.py @@ -6,6 +6,7 @@ import numpy as np import scipy.integrate +from scipy.interpolate import CubicSpline from tdastro.astro_utils import interpolation @@ -68,7 +69,9 @@ def _load_preset(self, preset): else: raise ValueError(f"Unknown passband preset: {preset}") - def fluxes_to_bandfluxes(self, flux_density_matrix, wavelengths_angstrom) -> np.ndarray: + def fluxes_to_bandfluxes( + self, flux_density_matrix, wavelengths_angstrom, target_grid_step=None + ) -> np.ndarray: """Calculate bandfluxes for all passbands in the group. Parameters @@ -77,6 +80,9 @@ def fluxes_to_bandfluxes(self, flux_density_matrix, wavelengths_angstrom) -> np. A 2D array of flux densities where rows are times and columns are wavelengths. wavelengths_angstrom : np.ndarray An array of wavelengths in Angstroms corresponding to the columns of flux_density_matrix. + target_grid_step : float, optional + The unit of the grid (in Angstrom) to which the flux density matrix and normalized transmission + table should be interpolated. Returns ------- @@ -85,7 +91,9 @@ def fluxes_to_bandfluxes(self, flux_density_matrix, wavelengths_angstrom) -> np. """ bandfluxes = {} for label, passband in self.passbands.items(): - bandfluxes[label] = passband.fluxes_to_bandflux(flux_density_matrix, wavelengths_angstrom) + bandfluxes[label] = passband.fluxes_to_bandflux( + flux_density_matrix, wavelengths_angstrom, target_grid_step=target_grid_step + ) return bandfluxes @@ -205,7 +213,7 @@ def _normalize_transmission_table(self) -> np.ndarray: return np.column_stack((wavelengths_angstrom, normalized_transmissions)) def _interpolate( - self, initial_fluxes, intial_wavelengths, initial_norm_trans_table, target_grid_step=None + self, initial_fluxes, initial_wavelengths, initial_norm_trans_table, target_grid_step=None ): """Interpolate the flux density matrix and normalized transmission table to the same grid. @@ -213,7 +221,7 @@ def _interpolate( ---------- initial_fluxes : np.ndarray A 2D array of flux densities where rows are times and columns are wavelengths. - intial_wavelengths : np.ndarray + initial_wavelengths : np.ndarray An array of wavelengths in Angstroms corresponding to the columns of initial_fluxes. initial_norm_trans_table : np.ndarray A 2D array of wavelengths and normalized transmissions. @@ -228,23 +236,23 @@ def _interpolate( """ if target_grid_step is None: # If grids already match, we can just return the intial arrays - if np.allclose(intial_wavelengths, initial_norm_trans_table[:, 0]): - return (initial_fluxes, intial_wavelengths, initial_norm_trans_table) + if np.array_equal(initial_wavelengths, initial_norm_trans_table[:, 0]): + return (initial_fluxes, initial_wavelengths, initial_norm_trans_table) # Otherwise, if the given wavelength grid is uniform, set grid step to the step size - elif interpolation.has_uniform_step(intial_wavelengths): - target_grid_step = interpolation.get_grid_step(intial_wavelengths) + elif interpolation.has_uniform_step(initial_wavelengths): + target_grid_step = interpolation.get_grid_step(initial_wavelengths) # Otherwise, ask for target grid step else: raise ValueError( "Interpolation needed; grids do not match. Consider using the target_grid_step parameter." ) - interp_wavelengths = intial_wavelengths + interp_wavelengths = initial_wavelengths interp_fluxes = initial_fluxes - if target_grid_step != interpolation.get_grid_step(intial_wavelengths): - interp_wavelengths = interpolation.interpolate_wavelengths(intial_wavelengths, target_grid_step) + if target_grid_step != interpolation.get_grid_step(initial_wavelengths): + interp_wavelengths = interpolation.interpolate_wavelengths(initial_wavelengths, target_grid_step) interp_fluxes = interpolation.interpolate_matrix_along_wavelengths( - initial_fluxes, intial_wavelengths, interp_wavelengths + initial_fluxes, initial_wavelengths, interp_wavelengths ) interp_norm_trans_table = initial_norm_trans_table @@ -282,17 +290,62 @@ def fluxes_to_bandflux( np.ndarray An array of bandfluxes. """ - # Interpolate the flux density matrix and normalized transmission table to the same grid - (flux_density_matrix, wavelengths_angstrom, normalized_transmission_table) = self._interpolate( - _flux_density_matrix, - _wavelengths_angstrom, - self.normalized_transmission_table, - target_grid_step=target_grid_step, + ##### Make sure wavelengths are strictly increasing in both cases + if not np.all(np.diff(_wavelengths_angstrom) > 0): + raise ValueError("Wavelengths must be strictly increasing.") + if not np.all(np.diff(self.normalized_transmission_table[:, 0]) > 0): + raise ValueError("Wavelengths must be strictly increasing.") + + ##### Pre-interpolation information + print( + f"Interp {self.full_name}: {_flux_density_matrix.shape}, {_wavelengths_angstrom.shape}, " + f"{self.normalized_transmission_table.shape} -> ", + end="", + ) + + ##### Determine the new grid + if target_grid_step is None: + raise ValueError("Target grid step must be provided.") + # TODO determine if we would want to automatically match the step of the given flux density matrix + # Ordinarily, this would be good, but consider cases where the flux density matrix is not uniform + # or is coarser than the transmission table + target_grid = np.arange( + self.normalized_transmission_table[0, 0], + self.normalized_transmission_table[-1, 0] + target_grid_step, + target_grid_step, + ) + + ##### Match flux density interval to target_grid interval, and interpolate if necessary + flux_density_matrix = [] + for row in _flux_density_matrix: + flux_density_spline = CubicSpline( + _wavelengths_angstrom, row, bc_type="not-a-knot", extrapolate=True + ) + flux_density_matrix.append(flux_density_spline(target_grid)) + flux_density_matrix = np.array(flux_density_matrix) + wavelengths_angstrom = target_grid + + ##### Match transmission table to target_grid interval, and interpolate if necessary + normalized_transmission_spline = CubicSpline( + self.normalized_transmission_table[:, 0], + self.normalized_transmission_table[:, 1], + bc_type="not-a-knot", + extrapolate=True, + ) + interpolated_transmissions = normalized_transmission_spline(target_grid) + normalized_transmission_table = np.column_stack((target_grid, interpolated_transmissions)) + + ##### Post-interpolation information + print( + f"{flux_density_matrix.shape}, {wavelengths_angstrom.shape}, " + f"{normalized_transmission_table.shape}" ) # Get only the flux densities that are within the passband's wavelength range passband_wavelengths = normalized_transmission_table[:, 0] - passband_wavelengths_indices = np.searchsorted(wavelengths_angstrom, passband_wavelengths) + passband_wavelengths_indices = np.searchsorted( + wavelengths_angstrom, passband_wavelengths + ) # TODO this should now be unnecessary passband_flux_density_matrix = flux_density_matrix[:, passband_wavelengths_indices] # Calculate the bandflux as ∫ f(λ)φ_b(λ) dλ, From fb68571c33f6421ceddb920d807f7bfea7216f44 Mon Sep 17 00:00:00 2001 From: Olivia Lynn Date: Mon, 2 Sep 2024 11:57:22 -0400 Subject: [PATCH 05/38] Simplify logic/lightly refactor interpolation --- .../interpolation-exterpolation-demo.ipynb | 2 +- src/tdastro/astro_utils/interpolation.py | 12 +- src/tdastro/astro_utils/passbands.py | 138 +++++------------- .../tdastro/astro_utils/test_interpolation.py | 53 ++++++- 4 files changed, 94 insertions(+), 111 deletions(-) diff --git a/docs/notebooks/interpolation-exterpolation-demo.ipynb b/docs/notebooks/interpolation-exterpolation-demo.ipynb index df763f25..64812e11 100644 --- a/docs/notebooks/interpolation-exterpolation-demo.ipynb +++ b/docs/notebooks/interpolation-exterpolation-demo.ipynb @@ -14,11 +14,11 @@ "outputs": [], "source": [ "from tdastro.astro_utils.interpolation import (\n", + " create_grid,\n", " get_grid_step,\n", " has_uniform_step,\n", " interpolate_matrix_along_wavelengths,\n", " interpolate_transmission_table,\n", - " interpolate_wavelengths,\n", ")\n", "from tdastro.astro_utils.passbands import PassbandGroup" ] diff --git a/src/tdastro/astro_utils/interpolation.py b/src/tdastro/astro_utils/interpolation.py index d0f5fb8c..ded30461 100644 --- a/src/tdastro/astro_utils/interpolation.py +++ b/src/tdastro/astro_utils/interpolation.py @@ -38,10 +38,11 @@ def has_uniform_step(grid: np.ndarray) -> bool: return np.allclose(np.diff(grid), np.diff(grid)[0]) -def interpolate_wavelengths(wavelengths: np.ndarray, new_grid_step: float) -> np.ndarray: +def create_grid(wavelengths: np.ndarray, new_grid_step: float) -> np.ndarray: """Interpolate a grid of wavelengths to a new grid with a given step size. - TODO add note about whether the upper bound is included in the new grid + If the interval between the original grid's upper and lower bounds is a multiple of the new grid step, + the upper bound will be included in the new grid. Parameters ---------- @@ -58,7 +59,12 @@ def interpolate_wavelengths(wavelengths: np.ndarray, new_grid_step: float) -> np # Check that wavelengths are strictly increasing if not np.all(np.diff(wavelengths) > 0): raise ValueError("Wavelengths must be strictly increasing.") - new_grid = np.arange(wavelengths[0], wavelengths[-1] + new_grid_step, new_grid_step) + + # Generate new grid, including the original upper bound if step size is a divisor of target interval + if (wavelengths[-1] - wavelengths[0]) % new_grid_step == 0: + new_grid = np.arange(wavelengths[0], wavelengths[-1] + new_grid_step, new_grid_step) + else: + new_grid = np.arange(wavelengths[0], wavelengths[-1], new_grid_step) return new_grid diff --git a/src/tdastro/astro_utils/passbands.py b/src/tdastro/astro_utils/passbands.py index 4ab6a045..94068881 100644 --- a/src/tdastro/astro_utils/passbands.py +++ b/src/tdastro/astro_utils/passbands.py @@ -212,57 +212,6 @@ def _normalize_transmission_table(self) -> np.ndarray: normalized_transmissions = numerators / denominator return np.column_stack((wavelengths_angstrom, normalized_transmissions)) - def _interpolate( - self, initial_fluxes, initial_wavelengths, initial_norm_trans_table, target_grid_step=None - ): - """Interpolate the flux density matrix and normalized transmission table to the same grid. - - Parameters - ---------- - initial_fluxes : np.ndarray - A 2D array of flux densities where rows are times and columns are wavelengths. - initial_wavelengths : np.ndarray - An array of wavelengths in Angstroms corresponding to the columns of initial_fluxes. - initial_norm_trans_table : np.ndarray - A 2D array of wavelengths and normalized transmissions. - target_grid_step : int, optional - The unit of the grid (in Angstrom) to which the flux density matrix and normalized transmission - table should be interpolated. - - Returns - ------- - tuple of np.ndarray - A tuple of interpolated flux densities, wavelengths, and normalized transmission table. - """ - if target_grid_step is None: - # If grids already match, we can just return the intial arrays - if np.array_equal(initial_wavelengths, initial_norm_trans_table[:, 0]): - return (initial_fluxes, initial_wavelengths, initial_norm_trans_table) - # Otherwise, if the given wavelength grid is uniform, set grid step to the step size - elif interpolation.has_uniform_step(initial_wavelengths): - target_grid_step = interpolation.get_grid_step(initial_wavelengths) - # Otherwise, ask for target grid step - else: - raise ValueError( - "Interpolation needed; grids do not match. Consider using the target_grid_step parameter." - ) - - interp_wavelengths = initial_wavelengths - interp_fluxes = initial_fluxes - if target_grid_step != interpolation.get_grid_step(initial_wavelengths): - interp_wavelengths = interpolation.interpolate_wavelengths(initial_wavelengths, target_grid_step) - interp_fluxes = interpolation.interpolate_matrix_along_wavelengths( - initial_fluxes, initial_wavelengths, interp_wavelengths - ) - - interp_norm_trans_table = initial_norm_trans_table - if target_grid_step != interpolation.get_grid_step(initial_norm_trans_table[:, 0]): - interp_norm_trans_table = interpolation.interpolate_transmission_table( - initial_norm_trans_table, interp_wavelengths - ) - - return (interp_fluxes, interp_wavelengths, interp_norm_trans_table) - def fluxes_to_bandflux( self, _flux_density_matrix, _wavelengths_angstrom, target_grid_step=None ) -> np.ndarray: @@ -290,67 +239,58 @@ def fluxes_to_bandflux( np.ndarray An array of bandfluxes. """ - ##### Make sure wavelengths are strictly increasing in both cases + # Make sure all given wavelengths are strictly increasing if not np.all(np.diff(_wavelengths_angstrom) > 0): - raise ValueError("Wavelengths must be strictly increasing.") + raise ValueError("Wavelengths corresponding to flux density matrix must be strictly increasing.") if not np.all(np.diff(self.normalized_transmission_table[:, 0]) > 0): - raise ValueError("Wavelengths must be strictly increasing.") - - ##### Pre-interpolation information - print( - f"Interp {self.full_name}: {_flux_density_matrix.shape}, {_wavelengths_angstrom.shape}, " - f"{self.normalized_transmission_table.shape} -> ", - end="", - ) + raise ValueError("Wavelengths in transmission table must be strictly increasing.") - ##### Determine the new grid + # Make sure we have a target grid step if target_grid_step is None: raise ValueError("Target grid step must be provided.") # TODO determine if we would want to automatically match the step of the given flux density matrix # Ordinarily, this would be good, but consider cases where the flux density matrix is not uniform # or is coarser than the transmission table - target_grid = np.arange( - self.normalized_transmission_table[0, 0], - self.normalized_transmission_table[-1, 0] + target_grid_step, - target_grid_step, - ) - ##### Match flux density interval to target_grid interval, and interpolate if necessary - flux_density_matrix = [] - for row in _flux_density_matrix: - flux_density_spline = CubicSpline( - _wavelengths_angstrom, row, bc_type="not-a-knot", extrapolate=True - ) - flux_density_matrix.append(flux_density_spline(target_grid)) - flux_density_matrix = np.array(flux_density_matrix) - wavelengths_angstrom = target_grid - - ##### Match transmission table to target_grid interval, and interpolate if necessary - normalized_transmission_spline = CubicSpline( - self.normalized_transmission_table[:, 0], - self.normalized_transmission_table[:, 1], - bc_type="not-a-knot", - extrapolate=True, - ) - interpolated_transmissions = normalized_transmission_spline(target_grid) - normalized_transmission_table = np.column_stack((target_grid, interpolated_transmissions)) + # Interpolate the flux density matrix and transmission table to the target grid + target_grid = interpolation.create_grid(self.normalized_transmission_table[:, 0], target_grid_step) - ##### Post-interpolation information - print( - f"{flux_density_matrix.shape}, {wavelengths_angstrom.shape}, " - f"{normalized_transmission_table.shape}" - ) + if np.array_equal(_wavelengths_angstrom, target_grid): + flux_density_matrix = [] + for row in _flux_density_matrix: + flux_density_spline = CubicSpline( + _wavelengths_angstrom, row, bc_type="not-a-knot", extrapolate=True + ) + flux_density_matrix.append(flux_density_spline(target_grid)) + flux_density_matrix = np.array(flux_density_matrix) + wavelengths_angstrom = target_grid + else: + flux_density_matrix = _flux_density_matrix + wavelengths_angstrom = _wavelengths_angstrom + + if np.array_equal(self.normalized_transmission_table[:, 0], target_grid): + normalized_transmission_spline = CubicSpline( + self.normalized_transmission_table[:, 0], + self.normalized_transmission_table[:, 1], + bc_type="not-a-knot", + extrapolate=True, + ) + interpolated_transmissions = normalized_transmission_spline(target_grid) + normalized_transmission_table = np.column_stack((target_grid, interpolated_transmissions)) + else: + normalized_transmission_table = self.normalized_transmission_table - # Get only the flux densities that are within the passband's wavelength range - passband_wavelengths = normalized_transmission_table[:, 0] - passband_wavelengths_indices = np.searchsorted( - wavelengths_angstrom, passband_wavelengths - ) # TODO this should now be unnecessary - passband_flux_density_matrix = flux_density_matrix[:, passband_wavelengths_indices] + # # Get only the flux densities that are within the passband's wavelength range + # passband_wavelengths = normalized_transmission_table[:, 0] + # passband_wavelengths_indices = np.searchsorted( + # wavelengths_angstrom, passband_wavelengths + # ) # note - this should now be unnecessary (post interpolation) + # passband_flux_density_matrix = flux_density_matrix[:, passband_wavelengths_indices] + # TODO let's add unit tests to make sure we don't need the above bit anymore # Calculate the bandflux as ∫ f(λ)φ_b(λ) dλ, # where f(λ) is the in-band flux density and φ_b(λ) is the normalized system response - integrand = passband_flux_density_matrix * normalized_transmission_table[:, 1] - bandfluxes = scipy.integrate.trapezoid(integrand, x=passband_wavelengths) + integrand = flux_density_matrix * normalized_transmission_table[:, 1] + bandfluxes = scipy.integrate.trapezoid(integrand, x=wavelengths_angstrom) return bandfluxes diff --git a/tests/tdastro/astro_utils/test_interpolation.py b/tests/tdastro/astro_utils/test_interpolation.py index cf625592..7e8e2f6c 100644 --- a/tests/tdastro/astro_utils/test_interpolation.py +++ b/tests/tdastro/astro_utils/test_interpolation.py @@ -1,10 +1,10 @@ import numpy as np import pytest from tdastro.astro_utils.interpolation import ( + create_grid, has_uniform_step, interpolate_matrix_along_wavelengths, interpolate_transmission_table, - interpolate_wavelengths, ) from tdastro.astro_utils.passbands import Passband @@ -24,24 +24,36 @@ def test_has_uniform_step(): assert has_uniform_step(a4) -def test_interpolate_wavelengths(): - """Test interpolate_wavelengths function.""" +def test_create_grid(): + """Test create_grid function.""" wavelengths = np.array([1, 2, 3]) new_grid_step = 0.5 - interp_wavelengths = interpolate_wavelengths(wavelengths, new_grid_step) + interp_wavelengths = create_grid(wavelengths, new_grid_step) assert np.allclose(interp_wavelengths, np.array([1.0, 1.5, 2.0, 2.5, 3.0])) - # Test non-uniform grid # TODO would this be better as its own unit test? what's the standard for this? + # Test non-uniform grid wavelengths = np.array([1, 2, 4]) new_grid_step = 0.5 - interp_wavelengths = interpolate_wavelengths(wavelengths, new_grid_step) + interp_wavelengths = create_grid(wavelengths, new_grid_step) assert np.allclose(interp_wavelengths, np.array([1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0])) # Test not strictly increasing grid wavelengths = np.array([1, 2, 1]) new_grid_step = 0.5 with pytest.raises(ValueError): - interpolate_wavelengths(wavelengths, new_grid_step) + create_grid(wavelengths, new_grid_step) + + # Test upper bound is included where the step size is a divisor of the upper bound + wavelengths = np.array([1, 4]) + new_grid_step = 1 + interp_wavelengths = create_grid(wavelengths, new_grid_step) + assert np.allclose(interp_wavelengths, np.array([1.0, 2.0, 3.0, 4.0])) + + # Test upper bound not included where the step size is not a divisor of the upper bound + wavelengths = np.array([1, 4]) + new_grid_step = 2 + interp_wavelengths = create_grid(wavelengths, new_grid_step) + assert np.allclose(interp_wavelengths, np.array([1.0, 3.0])) def test_interpolate_matrix_along_wavelengths(): @@ -49,7 +61,7 @@ def test_interpolate_matrix_along_wavelengths(): fluxes = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]) wavelengths = np.array([1, 2, 3]) new_grid_step = 0.5 - interp_wavelengths = interpolate_wavelengths(wavelengths, new_grid_step) + interp_wavelengths = create_grid(wavelengths, new_grid_step) interp_fluxes = interpolate_matrix_along_wavelengths(fluxes, wavelengths, interp_wavelengths) assert np.allclose( interp_fluxes, @@ -125,3 +137,28 @@ def test_interpolate_passband(tmp_path): assert np.allclose(interpolated_matrix, expected_matrix) # TODO add a test with a weird grid upper bound + + +# TODO add tests that check we don't modify the original data +# TODO add tests that check we don't call things we don't need to if the grid is already matched + + +""" + + ##### TEMP LOGGING: Pre-interpolation information + print( + f"Interp {self.full_name}: {_flux_density_matrix.shape}, {_wavelengths_angstrom.shape}, " + f"{self.normalized_transmission_table.shape} -> ", + end="", + ) + + + ##### Post-interpolation information + print( + f"{flux_density_matrix.shape}, {wavelengths_angstrom.shape}, " + f"{normalized_transmission_table.shape}" + ) + + + +""" From 51a0c111bceaa2a3e6c697e020b77df59b48718b Mon Sep 17 00:00:00 2001 From: Olivia Lynn Date: Mon, 2 Sep 2024 21:57:20 -0400 Subject: [PATCH 06/38] Move interpolation part of fluxes_to_bandflux to _interpolate; expand unit tests --- src/tdastro/astro_utils/passbands.py | 77 ++++++++++++------- .../tdastro/astro_utils/test_interpolation.py | 55 +++++++++---- 2 files changed, 89 insertions(+), 43 deletions(-) diff --git a/src/tdastro/astro_utils/passbands.py b/src/tdastro/astro_utils/passbands.py index 94068881..6070adbf 100644 --- a/src/tdastro/astro_utils/passbands.py +++ b/src/tdastro/astro_utils/passbands.py @@ -212,32 +212,24 @@ def _normalize_transmission_table(self) -> np.ndarray: normalized_transmissions = numerators / denominator return np.column_stack((wavelengths_angstrom, normalized_transmissions)) - def fluxes_to_bandflux( - self, _flux_density_matrix, _wavelengths_angstrom, target_grid_step=None - ) -> np.ndarray: - """Calculate the bandflux for a given set of flux densities. - - This is eq. 7 from "On the Choice of LSST Flux Units" (Ivezić et al.): - - F_b = ∫ f(λ)φ_b(λ) dλ - - where f(λ) is the specific flux of an object at the top of the atmosphere, and φ_b(λ) is the - normalized system response for given band b." + def _interpolate(self, _flux_density_matrix, _wavelengths_angstrom, target_grid_step) -> tuple: + """Interpolate the flux density matrix and transmission table to a target grid. Parameters ---------- - flux_density_matrix : np.ndarray + _flux_density_matrix : np.ndarray A 2D array of flux densities where rows are times and columns are wavelengths. - wavelengths_angstrom : np.ndarray - An array of wavelengths in Angstroms corresponding to the columns of flux_density_matrix. - target_grid_step : float, optional + _wavelengths_angstrom : np.ndarray + An array of wavelengths in Angstroms corresponding to the columns of _flux_density_matrix. + target_grid_step : float or None The unit of the grid (in Angstrom) to which the flux density matrix and normalized transmission table should be interpolated. Returns ------- - np.ndarray - An array of bandfluxes. + tuple + A tuple containing the interpolated flux density matrix, interpolated wavelengths, and + interpolated normalized transmission table. """ # Make sure all given wavelengths are strictly increasing if not np.all(np.diff(_wavelengths_angstrom) > 0): @@ -245,16 +237,18 @@ def fluxes_to_bandflux( if not np.all(np.diff(self.normalized_transmission_table[:, 0]) > 0): raise ValueError("Wavelengths in transmission table must be strictly increasing.") - # Make sure we have a target grid step + # Check we have enough data to interpolate + # TODO + + # Create target grid if target_grid_step is None: raise ValueError("Target grid step must be provided.") - # TODO determine if we would want to automatically match the step of the given flux density matrix - # Ordinarily, this would be good, but consider cases where the flux density matrix is not uniform - # or is coarser than the transmission table + # TODO consider defaulting to the grid to the given flux density matrix + # However, might be less desirable if flux density matrix is very sparse or irregularly stepped - # Interpolate the flux density matrix and transmission table to the target grid target_grid = interpolation.create_grid(self.normalized_transmission_table[:, 0], target_grid_step) + # Interpolate the flux density matrix if np.array_equal(_wavelengths_angstrom, target_grid): flux_density_matrix = [] for row in _flux_density_matrix: @@ -268,6 +262,7 @@ def fluxes_to_bandflux( flux_density_matrix = _flux_density_matrix wavelengths_angstrom = _wavelengths_angstrom + # Interpolate the normalized transmission table if np.array_equal(self.normalized_transmission_table[:, 0], target_grid): normalized_transmission_spline = CubicSpline( self.normalized_transmission_table[:, 0], @@ -280,14 +275,38 @@ def fluxes_to_bandflux( else: normalized_transmission_table = self.normalized_transmission_table - # # Get only the flux densities that are within the passband's wavelength range - # passband_wavelengths = normalized_transmission_table[:, 0] - # passband_wavelengths_indices = np.searchsorted( - # wavelengths_angstrom, passband_wavelengths - # ) # note - this should now be unnecessary (post interpolation) - # passband_flux_density_matrix = flux_density_matrix[:, passband_wavelengths_indices] - # TODO let's add unit tests to make sure we don't need the above bit anymore + return (flux_density_matrix, wavelengths_angstrom, normalized_transmission_table) + + def fluxes_to_bandflux( + self, _flux_density_matrix, _wavelengths_angstrom, target_grid_step=None + ) -> np.ndarray: + """Calculate the bandflux for a given set of flux densities. + + This is eq. 7 from "On the Choice of LSST Flux Units" (Ivezić et al.): + + F_b = ∫ f(λ)φ_b(λ) dλ + + where f(λ) is the specific flux of an object at the top of the atmosphere, and φ_b(λ) is the + normalized system response for given band b." + Parameters + ---------- + flux_density_matrix : np.ndarray + A 2D array of flux densities where rows are times and columns are wavelengths. + wavelengths_angstrom : np.ndarray + An array of wavelengths in Angstroms corresponding to the columns of flux_density_matrix. + target_grid_step : float, optional + The unit of the grid (in Angstrom) to which the flux density matrix and normalized transmission + table should be interpolated. + + Returns + ------- + np.ndarray + An array of bandfluxes. + """ + flux_density_matrix, wavelengths_angstrom, normalized_transmission_table = self._interpolate( + _flux_density_matrix, _wavelengths_angstrom, target_grid_step + ) # Calculate the bandflux as ∫ f(λ)φ_b(λ) dλ, # where f(λ) is the in-band flux density and φ_b(λ) is the normalized system response integrand = flux_density_matrix * normalized_transmission_table[:, 1] diff --git a/tests/tdastro/astro_utils/test_interpolation.py b/tests/tdastro/astro_utils/test_interpolation.py index 7e8e2f6c..3f416d21 100644 --- a/tests/tdastro/astro_utils/test_interpolation.py +++ b/tests/tdastro/astro_utils/test_interpolation.py @@ -94,15 +94,11 @@ def test_interpolate_transmission_table(): # TODO test edge cases -def test_interpolate_passband(tmp_path): +def test_interpolate_passband_simple(tmp_path): """Test interpolate_passband function.""" - # Initial values flux_density_matrix = np.array([[1.0, 1.0, 1.0], [1.0, 10.0, 1.0], [1.0, 0.0, 1.0]]) wavelengths_angstrom = np.array([100.0, 105.0, 110.0]) - # New values - new_grid_step = 1.0 - # Make passband survey = "TEST" band_label = "a" @@ -110,11 +106,11 @@ def test_interpolate_passband(tmp_path): transmission_table = "100 0.5\n" "110 1.0\n" with open(table_path, "w") as f: f.write(transmission_table) - a_band = Passband(survey, band_label, table_path=table_path) - # Interpolate - interpolated_matrix, interpolated_vector, interpolated_t_table = a_band._interpolate( + # Interpolate to grid of 1.0 + new_grid_step = 1.0 + interpolated_fluxes, interpolated_wavelengths, interpolated_t_table = a_band._interpolate( flux_density_matrix, wavelengths_angstrom, a_band.normalized_transmission_table, @@ -122,8 +118,8 @@ def test_interpolate_passband(tmp_path): ) # Assert shape/size - assert interpolated_matrix.shape == (3, 11) - assert len(interpolated_vector) == 11 + assert interpolated_fluxes.shape == (3, 11) + assert len(interpolated_wavelengths) == 11 assert len(interpolated_t_table) == 11 # Assert values @@ -134,13 +130,44 @@ def test_interpolate_passband(tmp_path): [1.0, 0.8, 0.6, 0.4, 0.2, 0.0, 0.2, 0.4, 0.6, 0.8, 1.0], ] ) - assert np.allclose(interpolated_matrix, expected_matrix) + assert np.allclose(interpolated_fluxes, expected_matrix) + assert np.allclose(interpolated_wavelengths, np.arange(100, 111)) + + # Check the original data was not modified + assert flux_density_matrix.shape == (3, 3) + assert wavelengths_angstrom.shape == (3,) + + +def test_interpolate_passband_none_needed(tmp_path): + """Test interpolate_passband function if no interpolation is needed for target grid.""" + flux_density_matrix = np.array([[1.0, 1.0, 1.0], [1.0, 10.0, 1.0], [1.0, 0.0, 1.0]]) + wavelengths_angstrom = np.array([100.0, 105.0, 110.0]) + + # Make passband + survey = "TEST" + band_label = "a" + table_path = tmp_path / f"{survey}_{band_label}.dat" + transmission_table = "100 0.5\n" "110 1.0\n" + with open(table_path, "w") as f: + f.write(transmission_table) + a_band = Passband(survey, band_label, table_path=table_path) - # TODO add a test with a weird grid upper bound + # Interpolate to grid of 10.0 (no interpolation) + new_grid_step = 10.0 + interpolated_fluxes, interpolated_wavelengths, interpolated_t_table = a_band._interpolate( + flux_density_matrix, + wavelengths_angstrom, + a_band.normalized_transmission_table, + target_grid_step=new_grid_step, + ) + # Assert shape/size + assert interpolated_fluxes.shape == (3, 3) + assert len(interpolated_wavelengths) == 3 + assert len(interpolated_t_table) == 3 -# TODO add tests that check we don't modify the original data -# TODO add tests that check we don't call things we don't need to if the grid is already matched + # Assert scipy.interpolate.CubicSpline was not called + # TODO """ From bb494d45b77bd07783aa5758779762de2f5b31a9 Mon Sep 17 00:00:00 2001 From: Olivia Lynn Date: Mon, 2 Sep 2024 21:58:28 -0400 Subject: [PATCH 07/38] Remove has_uniform_step --- .../interpolation-exterpolation-demo.ipynb | 1 - src/tdastro/astro_utils/interpolation.py | 19 ------------------- .../tdastro/astro_utils/test_interpolation.py | 16 ---------------- 3 files changed, 36 deletions(-) diff --git a/docs/notebooks/interpolation-exterpolation-demo.ipynb b/docs/notebooks/interpolation-exterpolation-demo.ipynb index 64812e11..5ab52125 100644 --- a/docs/notebooks/interpolation-exterpolation-demo.ipynb +++ b/docs/notebooks/interpolation-exterpolation-demo.ipynb @@ -16,7 +16,6 @@ "from tdastro.astro_utils.interpolation import (\n", " create_grid,\n", " get_grid_step,\n", - " has_uniform_step,\n", " interpolate_matrix_along_wavelengths,\n", " interpolate_transmission_table,\n", ")\n", diff --git a/src/tdastro/astro_utils/interpolation.py b/src/tdastro/astro_utils/interpolation.py index ded30461..027af20a 100644 --- a/src/tdastro/astro_utils/interpolation.py +++ b/src/tdastro/astro_utils/interpolation.py @@ -19,25 +19,6 @@ def get_grid_step(grid: np.ndarray) -> float: return None -def has_uniform_step(grid: np.ndarray) -> bool: - """Check if a grid has a uniform step size. - - Parameters - ---------- - grid : np.ndarray - The grid. - - Returns - ------- - bool - True if the grid has a uniform step size, False otherwise. If the grid has fewer than 2 elements, we - consider it to have a uniform step size. - """ - if len(grid) < 2: - return True - return np.allclose(np.diff(grid), np.diff(grid)[0]) - - def create_grid(wavelengths: np.ndarray, new_grid_step: float) -> np.ndarray: """Interpolate a grid of wavelengths to a new grid with a given step size. diff --git a/tests/tdastro/astro_utils/test_interpolation.py b/tests/tdastro/astro_utils/test_interpolation.py index 3f416d21..aa020104 100644 --- a/tests/tdastro/astro_utils/test_interpolation.py +++ b/tests/tdastro/astro_utils/test_interpolation.py @@ -2,28 +2,12 @@ import pytest from tdastro.astro_utils.interpolation import ( create_grid, - has_uniform_step, interpolate_matrix_along_wavelengths, interpolate_transmission_table, ) from tdastro.astro_utils.passbands import Passband -def test_has_uniform_step(): - """Test has_uniform_step function.""" - a1 = np.array([1, 2, 3]) - assert has_uniform_step(a1) - - a2 = np.array([1, 2, 3, 40]) - assert not has_uniform_step(a2) - - a3 = np.array([]) - assert has_uniform_step(a3) - - a4 = np.array([1]) - assert has_uniform_step(a4) - - def test_create_grid(): """Test create_grid function.""" wavelengths = np.array([1, 2, 3]) From 153ee0028ad57405c984cedbd4b198c7ed38ea1a Mon Sep 17 00:00:00 2001 From: Olivia Lynn Date: Tue, 3 Sep 2024 16:22:50 -0400 Subject: [PATCH 08/38] Expand unit tests --- .../tdastro/astro_utils/test_interpolation.py | 228 ++++++++++++++---- 1 file changed, 177 insertions(+), 51 deletions(-) diff --git a/tests/tdastro/astro_utils/test_interpolation.py b/tests/tdastro/astro_utils/test_interpolation.py index aa020104..c7f958d9 100644 --- a/tests/tdastro/astro_utils/test_interpolation.py +++ b/tests/tdastro/astro_utils/test_interpolation.py @@ -13,13 +13,13 @@ def test_create_grid(): wavelengths = np.array([1, 2, 3]) new_grid_step = 0.5 interp_wavelengths = create_grid(wavelengths, new_grid_step) - assert np.allclose(interp_wavelengths, np.array([1.0, 1.5, 2.0, 2.5, 3.0])) + np.testing.assert_allclose(interp_wavelengths, np.array([1.0, 1.5, 2.0, 2.5, 3.0])) # Test non-uniform grid wavelengths = np.array([1, 2, 4]) new_grid_step = 0.5 interp_wavelengths = create_grid(wavelengths, new_grid_step) - assert np.allclose(interp_wavelengths, np.array([1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0])) + np.testing.assert_allclose(interp_wavelengths, np.array([1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0])) # Test not strictly increasing grid wavelengths = np.array([1, 2, 1]) @@ -31,13 +31,13 @@ def test_create_grid(): wavelengths = np.array([1, 4]) new_grid_step = 1 interp_wavelengths = create_grid(wavelengths, new_grid_step) - assert np.allclose(interp_wavelengths, np.array([1.0, 2.0, 3.0, 4.0])) + np.testing.assert_allclose(interp_wavelengths, np.array([1.0, 2.0, 3.0, 4.0])) # Test upper bound not included where the step size is not a divisor of the upper bound wavelengths = np.array([1, 4]) new_grid_step = 2 interp_wavelengths = create_grid(wavelengths, new_grid_step) - assert np.allclose(interp_wavelengths, np.array([1.0, 3.0])) + np.testing.assert_allclose(interp_wavelengths, np.array([1.0, 3.0])) def test_interpolate_matrix_along_wavelengths(): @@ -47,10 +47,10 @@ def test_interpolate_matrix_along_wavelengths(): new_grid_step = 0.5 interp_wavelengths = create_grid(wavelengths, new_grid_step) interp_fluxes = interpolate_matrix_along_wavelengths(fluxes, wavelengths, interp_wavelengths) - assert np.allclose( + np.testing.assert_allclose( interp_fluxes, np.array([[1.0, 1.5, 2.0, 2.5, 3.0], [4.0, 4.5, 5.0, 5.5, 6.0], [7.0, 7.5, 8.0, 8.5, 9.0]]), - ) # TODO change to np assert? (and above) + ) def test_interpolate_transmission_table(): @@ -60,7 +60,7 @@ def test_interpolate_transmission_table(): table = np.stack((wavelengths, transmissions), axis=-1) new_wavelengths = np.linspace(0, 20, 7) interp_transmissions = interpolate_transmission_table(table, new_wavelengths) - assert np.allclose( + np.testing.assert_allclose( interp_transmissions, np.array( [ @@ -78,27 +78,31 @@ def test_interpolate_transmission_table(): # TODO test edge cases -def test_interpolate_passband_simple(tmp_path): - """Test interpolate_passband function.""" - flux_density_matrix = np.array([[1.0, 1.0, 1.0], [1.0, 10.0, 1.0], [1.0, 0.0, 1.0]]) - wavelengths_angstrom = np.array([100.0, 105.0, 110.0]) - - # Make passband +def _make_passband(transmission_table, path): + """Helper function to create a Passband object from a transmission table.""" survey = "TEST" band_label = "a" - table_path = tmp_path / f"{survey}_{band_label}.dat" - transmission_table = "100 0.5\n" "110 1.0\n" + table_path = path / f"{survey}_{band_label}.dat" with open(table_path, "w") as f: f.write(transmission_table) a_band = Passband(survey, band_label, table_path=table_path) + return a_band + + +def test_interpolate_passband_simple(tmp_path): + """Test _interpolate function.""" + flux_density_matrix = np.array([[1.0, 1.0, 1.0], [1.0, 10.0, 1.0], [1.0, 0.0, 1.0]]) + wavelengths_angstrom = np.array([100.0, 105.0, 110.0]) + + transmission_table = "100 0.5\n" "110 1.0\n" + a_band = _make_passband(transmission_table, tmp_path) # Interpolate to grid of 1.0 new_grid_step = 1.0 interpolated_fluxes, interpolated_wavelengths, interpolated_t_table = a_band._interpolate( flux_density_matrix, wavelengths_angstrom, - a_band.normalized_transmission_table, - target_grid_step=new_grid_step, + new_grid_step, ) # Assert shape/size @@ -107,42 +111,63 @@ def test_interpolate_passband_simple(tmp_path): assert len(interpolated_t_table) == 11 # Assert values - expected_matrix = np.array( - [ - [1.0] * 11, - [1.0, 2.8, 4.6, 6.4, 8.2, 10.0, 8.2, 6.4, 4.6, 2.8, 1.0], - [1.0, 0.8, 0.6, 0.4, 0.2, 0.0, 0.2, 0.4, 0.6, 0.8, 1.0], - ] - ) - assert np.allclose(interpolated_fluxes, expected_matrix) - assert np.allclose(interpolated_wavelengths, np.arange(100, 111)) + np.testing.assert_allclose(interpolated_wavelengths, np.arange(100, 111)) + np.testing.assert_allclose(interpolated_fluxes[0], [1.0] * 11) + assert np.isclose(interpolated_fluxes[1][0], 1.0) + assert np.isclose(interpolated_fluxes[1][5], 10.0) + assert np.isclose(interpolated_fluxes[1][10], 1.0) + assert np.isclose(interpolated_fluxes[2][0], 1.0) + assert np.isclose(interpolated_fluxes[2][5], 0.0) + assert np.isclose(interpolated_fluxes[2][10], 1.0) # Check the original data was not modified assert flux_density_matrix.shape == (3, 3) assert wavelengths_angstrom.shape == (3,) -def test_interpolate_passband_none_needed(tmp_path): - """Test interpolate_passband function if no interpolation is needed for target grid.""" +def test_interpolate_passband_coarser_grid(tmp_path): + """Test _interpolate function if target grid is coarser than current grid.""" flux_density_matrix = np.array([[1.0, 1.0, 1.0], [1.0, 10.0, 1.0], [1.0, 0.0, 1.0]]) wavelengths_angstrom = np.array([100.0, 105.0, 110.0]) - # Make passband - survey = "TEST" - band_label = "a" - table_path = tmp_path / f"{survey}_{band_label}.dat" transmission_table = "100 0.5\n" "110 1.0\n" - with open(table_path, "w") as f: - f.write(transmission_table) - a_band = Passband(survey, band_label, table_path=table_path) + a_band = _make_passband(transmission_table, tmp_path) - # Interpolate to grid of 10.0 (no interpolation) + # Interpolate to grid of 10.0 new_grid_step = 10.0 interpolated_fluxes, interpolated_wavelengths, interpolated_t_table = a_band._interpolate( flux_density_matrix, wavelengths_angstrom, - a_band.normalized_transmission_table, - target_grid_step=new_grid_step, + new_grid_step, + ) + + # Assert shape/size + assert interpolated_fluxes.shape == (3, 2) + assert len(interpolated_wavelengths) == 2 + assert len(interpolated_t_table) == 3 + + # Assert values + assert np.isclose(interpolated_wavelengths[0], 100.0) + assert np.isclose(interpolated_wavelengths[1], 110.0) + np.testing.assert_allclose(interpolated_fluxes[0], [1.0, 1.0]) + np.testing.assert_allclose(interpolated_fluxes[1], [1.0, 1.0]) + np.testing.assert_allclose(interpolated_fluxes[2], [1.0, 1.0]) + + +def test_interpolate_passband_none_needed(tmp_path): + """Test _interpolate function if no interpolation is needed for target grid.""" + flux_density_matrix = np.array([[1.0, 1.0, 1.0], [1.0, 10.0, 1.0], [1.0, 0.0, 1.0]]) + wavelengths_angstrom = np.array([100.0, 105.0, 110.0]) + + transmission_table = "100 0.5\n" "110 1.0\n" + a_band = _make_passband(transmission_table, tmp_path) + + # Interpolate to grid of 5.0 (no interpolation) + new_grid_step = 5.0 + interpolated_fluxes, interpolated_wavelengths, interpolated_t_table = a_band._interpolate( + flux_density_matrix, + wavelengths_angstrom, + new_grid_step, ) # Assert shape/size @@ -150,26 +175,127 @@ def test_interpolate_passband_none_needed(tmp_path): assert len(interpolated_wavelengths) == 3 assert len(interpolated_t_table) == 3 + # Assert values + np.testing.assert_allclose(interpolated_wavelengths, wavelengths_angstrom) + np.testing.assert_allclose(interpolated_fluxes, flux_density_matrix) + np.testing.assert_allclose(interpolated_t_table, np.array([100.0, 0.5], [110.0, 1.0])) + # Assert scipy.interpolate.CubicSpline was not called # TODO -""" +def test_extrapolate_fluxes(tmp_path): + """Test flux matrix extrapolation performed in _interpolate function.""" + flux_density_matrix = np.array([[1.0, 1.0, 1.0], [1.0, 10.0, 1.0], [1.0, 0.0, 1.0]]) + wavelengths_angstrom = np.array([100.0, 105.0, 110.0]) - ##### TEMP LOGGING: Pre-interpolation information - print( - f"Interp {self.full_name}: {_flux_density_matrix.shape}, {_wavelengths_angstrom.shape}, " - f"{self.normalized_transmission_table.shape} -> ", - end="", - ) + transmission_table = "100 0.5\n105 0.75\n110 1.0\n115 0.75\n120 0.5\n" + a_band = _make_passband(transmission_table, tmp_path) + # Interpolate to grid of 5.0 (no interpolation needed, but extrapolation is) + new_grid_step = 5.0 + interpolated_fluxes, interpolated_wavelengths, interpolated_t_table = a_band._interpolate( + flux_density_matrix, + wavelengths_angstrom, + new_grid_step, + ) - ##### Post-interpolation information - print( - f"{flux_density_matrix.shape}, {wavelengths_angstrom.shape}, " - f"{normalized_transmission_table.shape}" - ) + # Assert shape/size + assert interpolated_fluxes.shape == (3, 5) + assert len(interpolated_wavelengths) == 5 + assert len(interpolated_t_table) == 5 + # Assert values + np.testing.assert_allclose(interpolated_wavelengths, [100.0, 105.0, 110.0, 115.0, 120.0]) + np.testing.assert_allclose(interpolated_fluxes[0], [1.0, 1.0, 1.0, 1.0, 1.0]) + np.testing.assert_allclose(interpolated_fluxes[1][:3], [1.0, 10.0, 1.0]) + np.testing.assert_allclose(interpolated_fluxes[2][:3], [1.0, 0.0, 1.0]) + np.testing.assert_allclose(interpolated_t_table, a_band.normalized_transmission_table) -""" +def test_truncate_fluxes(tmp_path): + """Test flux matrix truncation performed in _interpolate function.""" + flux_density_matrix = np.array([[1.0, 1.0, 1.0], [1.0, 10.0, 1.0], [1.0, 0.0, 1.0]]) + wavelengths_angstrom = np.array([100.0, 105.0, 110.0]) + + transmission_table = "100 0.5\n105 0.75\n" + a_band = _make_passband(transmission_table, tmp_path) + + # Interpolate to grid of 5.0 (no interpolation needed, but truncation is) + new_grid_step = 5.0 + interpolated_fluxes, interpolated_wavelengths, interpolated_t_table = a_band._interpolate( + flux_density_matrix, + wavelengths_angstrom, + new_grid_step, + ) + + # Assert shape/size + assert interpolated_fluxes.shape == (3, 2) + assert len(interpolated_wavelengths) == 2 + assert len(interpolated_t_table) == 2 + + # Assert values + np.testing.assert_allclose(interpolated_wavelengths, [100.0, 105.0]) + np.testing.assert_allclose(interpolated_fluxes[0], [1.0, 1.0]) + np.testing.assert_allclose(interpolated_fluxes[1], [1.0, 10.0]) + np.testing.assert_allclose(interpolated_fluxes[2], [1.0, 0.0]) + np.testing.assert_allclose(interpolated_t_table, a_band.normalized_transmission_table) + + +def test_truncate_and_interpolate_fluxes(tmp_path): + """Test flux matrix truncation performed in _interpolate function.""" + flux_density_matrix = np.array([[1.0, 1.0, 1.0], [1.0, 10.0, 1.0], [1.0, 0.0, 1.0]]) + wavelengths_angstrom = np.array([100.0, 105.0, 110.0]) + + transmission_table = "100 0.5\n105 0.75\n" + a_band = _make_passband(transmission_table, tmp_path) + + # Interpolate to grid of 1.0 (both interpolation and truncation needed) + new_grid_step = 1.0 + interpolated_fluxes, interpolated_wavelengths, interpolated_t_table = a_band._interpolate( + flux_density_matrix, + wavelengths_angstrom, + new_grid_step, + ) + + # Assert shape/size + assert interpolated_fluxes.shape == (3, 6) + assert len(interpolated_wavelengths) == 6 + assert len(interpolated_t_table) == 6 + + # Assert values + np.testing.assert_allclose(interpolated_wavelengths, [100.0, 101.0, 102.0, 103.0, 104.0, 105.0]) + np.testing.assert_allclose(interpolated_fluxes[0], [1.0] * 6) + assert np.isclose(interpolated_fluxes[1][0], 1.0) + assert np.isclose(interpolated_fluxes[1][5], 10.0) + assert np.isclose(interpolated_fluxes[2][0], 1.0) + assert np.isclose(interpolated_fluxes[2][5], 0.0) + assert np.isclose(interpolated_t_table[0][0], 100.0) + assert np.isclose(interpolated_t_table[0][1], a_band.normalized_transmission_table[0][1]) + assert np.isclose(interpolated_t_table[5][0], 105.0) + assert np.isclose(interpolated_t_table[5][1], a_band.normalized_transmission_table[1][1]) + + +def test_extrapolate_out_of_range(tmp_path): + """Test flux matrix extrapolation when given fluxes are completely out of range for passband.""" + flux_density_matrix = np.array([[1.0, 1.0, 1.0], [1.0, 10.0, 1.0], [1.0, 0.0, 1.0]]) + wavelengths_angstrom = np.array([200.0, 205.0, 210.0]) + + transmission_table = "100 0.5\n110 1.0" + a_band = _make_passband(transmission_table, tmp_path) + + # Interpolate to grid of 5.0 (no interpolation needed, but extrapolation is) + new_grid_step = 5.0 + interpolated_fluxes, interpolated_wavelengths, interpolated_t_table = a_band._interpolate( + flux_density_matrix, + wavelengths_angstrom, + new_grid_step, + ) + + # Well, here we see the results of the extrapolation. + # Don't love the [-3959. -3590. -3239.] fluxes. + # TODO + with np.printoptions(precision=2, suppress=True): + print(interpolated_fluxes) + print(interpolated_wavelengths) + print(interpolated_t_table) From e69e0c9b3c45343c94e5bfa37fb294867ce8ceba Mon Sep 17 00:00:00 2001 From: Olivia Lynn Date: Tue, 3 Sep 2024 16:25:00 -0400 Subject: [PATCH 09/38] Refactor transmission table loading to handle wave_grid and pre-normalization downsampling/interpolation --- src/tdastro/astro_utils/passbands.py | 100 ++++++++++++++++++--------- 1 file changed, 69 insertions(+), 31 deletions(-) diff --git a/src/tdastro/astro_utils/passbands.py b/src/tdastro/astro_utils/passbands.py index 6070adbf..941e9ce9 100644 --- a/src/tdastro/astro_utils/passbands.py +++ b/src/tdastro/astro_utils/passbands.py @@ -103,11 +103,15 @@ class Passband: Attributes ---------- label : str - The label of the passband. + The label of the passband. This is the filter name: eg, "u". survey : str - The survey to which the passband belongs. + The survey to which the passband belongs: eg, "LSST". full_name : str - The full name of the passband. + The full name of the passband. This is the survey and label concatenated: eg, "LSST_u". + wave_grid : np.ndarray | float | None + The grid of wavelengths (Angstrom) to which the flux density matrix and transmission table should be + interpolated. If None, the grid will be interpolated to the grid of the flux density matrix. Default + is 5.0. table_path : str The path to the transmission table file. table_url : str @@ -118,36 +122,37 @@ class Passband: A 2D array of wavelengths and normalized transmissions. """ - def __init__(self, survey, label, table_path=None, table_url=""): + def __init__(self, survey, label, wave_grid=5.0, table_path=None, table_url=""): self.label = label self.survey = survey self.full_name = f"{survey}_{label}" + self.wave_grid = wave_grid self.table_path = table_path self.table_url = table_url - self.transmission_table = self._load_transmission_table() - self.normalized_transmission_table = self._normalize_transmission_table() + self.normalized_transmission_table = self._get_normalized_transmission_table() def __str__(self) -> str: """Return a string representation of the Passband.""" return f"Passband: {self.full_name}" - def _load_transmission_table(self) -> np.ndarray: - """Load a transmission table from a file or URL. - - Returns - ------- - np.ndarray - A 2D array where the first column is wavelengths (Angstrom) and the second column is transmission - values. - """ + def _get_normalized_transmission_table(self) -> np.ndarray: + # Check if the table file exists locally, and download it if it doesn't if self.table_path is None: self.table_path = os.path.join( os.path.dirname(__file__), f"passbands/{self.survey}/{self.label}.dat" ) os.makedirs(os.path.dirname(self.table_path), exist_ok=True) + if not os.path.exists(self.table_path): self._download_transmission_table() - return np.loadtxt(self.table_path) + + # Load the table, downsizing/interpolating as needed, and normalize it + loaded_table = self._load_transmission_table() + interpolated_transmissions = self._downsample_or_interpolate_transmission_table(loaded_table) + normalized_transmissions = self._normalize_transmission_table(interpolated_transmissions) + + # Return the table + return normalized_transmissions def _download_transmission_table(self) -> bool: """Download a transmission table from a URL. @@ -185,18 +190,56 @@ def _download_transmission_table(self) -> bool: logging.error(f"URL error occurred when downloading table for {self.full_name}: {e}") return False - def _normalize_transmission_table(self) -> np.ndarray: + def _load_transmission_table(self) -> np.ndarray: + """Load a transmission table from a file. + + Returns + ------- + np.ndarray + A 2D array of wavelengths and transmissions. + """ + # Load the table file + loaded_table = np.loadtxt(self.table_path) + + # Check that the table has the correct shape + if loaded_table.shape[1] != 2: + raise ValueError("Transmission table must have exactly 2 columns.") + + # Check that wavelengths are strictly increasing + if not np.all(np.diff(loaded_table[:, 0]) > 0): + raise ValueError("Wavelengths in transmission table must be strictly increasing.") + + return loaded_table + + def _downsample_or_interpolate_transmission_table(self, loaded_table) -> np.ndarray: + """Downsample or interpolate a transmission table to a desired grid. + + Returns + ------- + np.ndarray + A 2D array of wavelengths and transmissions. + """ + if self.wave_grid is not None: + if type(self.wave_grid) == float: + self.wave_grid = interpolation.create_grid(loaded_table[:, 0], self.wave_grid) + interpolated_transmissions = interpolation.interpolate_transmission_table( + loaded_table, self.wave_grid + ) + return interpolated_transmissions + + def _normalize_transmission_table(self, transmission_table) -> np.ndarray: """Calculate the value of phi_b for all wavelengths in a transmission table. This is eq. 8 from "On the Choice of LSST Flux Units" (Ivezić et al.): φ_b(λ) = S_b(λ)λ⁻¹ / ∫ S_b(λ)λ⁻¹ dλ - where S_b(λ) is the system response of the passband. + where S_b(λ) is the system response of the passband. Note we use transmission table as our S_b(λ). - Notes - ----- - - We use transmission table here to represent S_b(λ). + Parameters + ---------- + transmission_table : np.ndarray + A 2D array of wavelengths and transmissions. Returns ------- @@ -234,11 +277,6 @@ def _interpolate(self, _flux_density_matrix, _wavelengths_angstrom, target_grid_ # Make sure all given wavelengths are strictly increasing if not np.all(np.diff(_wavelengths_angstrom) > 0): raise ValueError("Wavelengths corresponding to flux density matrix must be strictly increasing.") - if not np.all(np.diff(self.normalized_transmission_table[:, 0]) > 0): - raise ValueError("Wavelengths in transmission table must be strictly increasing.") - - # Check we have enough data to interpolate - # TODO # Create target grid if target_grid_step is None: @@ -249,21 +287,21 @@ def _interpolate(self, _flux_density_matrix, _wavelengths_angstrom, target_grid_ target_grid = interpolation.create_grid(self.normalized_transmission_table[:, 0], target_grid_step) # Interpolate the flux density matrix - if np.array_equal(_wavelengths_angstrom, target_grid): - flux_density_matrix = [] + if not np.array_equal(_wavelengths_angstrom, target_grid): + interpolated_flux_density_matrix = [] for row in _flux_density_matrix: flux_density_spline = CubicSpline( _wavelengths_angstrom, row, bc_type="not-a-knot", extrapolate=True ) - flux_density_matrix.append(flux_density_spline(target_grid)) - flux_density_matrix = np.array(flux_density_matrix) + interpolated_flux_density_matrix.append(flux_density_spline(target_grid)) + flux_density_matrix = np.array(interpolated_flux_density_matrix) wavelengths_angstrom = target_grid else: flux_density_matrix = _flux_density_matrix wavelengths_angstrom = _wavelengths_angstrom # Interpolate the normalized transmission table - if np.array_equal(self.normalized_transmission_table[:, 0], target_grid): + if not np.array_equal(self.normalized_transmission_table[:, 0], target_grid): normalized_transmission_spline = CubicSpline( self.normalized_transmission_table[:, 0], self.normalized_transmission_table[:, 1], From b5120313da522779698a156bd2b0ce6affee1d30 Mon Sep 17 00:00:00 2001 From: Olivia Lynn Date: Tue, 3 Sep 2024 16:27:13 -0400 Subject: [PATCH 10/38] Rename wavelengths_angstrom to flux_wavelengths for readability --- src/tdastro/astro_utils/passbands.py | 32 ++++++++++++++-------------- 1 file changed, 16 insertions(+), 16 deletions(-) diff --git a/src/tdastro/astro_utils/passbands.py b/src/tdastro/astro_utils/passbands.py index 941e9ce9..b76298e8 100644 --- a/src/tdastro/astro_utils/passbands.py +++ b/src/tdastro/astro_utils/passbands.py @@ -70,7 +70,7 @@ def _load_preset(self, preset): raise ValueError(f"Unknown passband preset: {preset}") def fluxes_to_bandfluxes( - self, flux_density_matrix, wavelengths_angstrom, target_grid_step=None + self, flux_density_matrix, flux_wavelengths, target_grid_step=None ) -> np.ndarray: """Calculate bandfluxes for all passbands in the group. @@ -78,7 +78,7 @@ def fluxes_to_bandfluxes( ---------- flux_density_matrix : np.ndarray A 2D array of flux densities where rows are times and columns are wavelengths. - wavelengths_angstrom : np.ndarray + flux_wavelengths : np.ndarray An array of wavelengths in Angstroms corresponding to the columns of flux_density_matrix. target_grid_step : float, optional The unit of the grid (in Angstrom) to which the flux density matrix and normalized transmission @@ -92,7 +92,7 @@ def fluxes_to_bandfluxes( bandfluxes = {} for label, passband in self.passbands.items(): bandfluxes[label] = passband.fluxes_to_bandflux( - flux_density_matrix, wavelengths_angstrom, target_grid_step=target_grid_step + flux_density_matrix, flux_wavelengths, target_grid_step=target_grid_step ) return bandfluxes @@ -255,14 +255,14 @@ def _normalize_transmission_table(self, transmission_table) -> np.ndarray: normalized_transmissions = numerators / denominator return np.column_stack((wavelengths_angstrom, normalized_transmissions)) - def _interpolate(self, _flux_density_matrix, _wavelengths_angstrom, target_grid_step) -> tuple: + def _interpolate(self, _flux_density_matrix, _flux_wavelengths, target_grid_step) -> tuple: """Interpolate the flux density matrix and transmission table to a target grid. Parameters ---------- _flux_density_matrix : np.ndarray A 2D array of flux densities where rows are times and columns are wavelengths. - _wavelengths_angstrom : np.ndarray + _flux_wavelengths : np.ndarray An array of wavelengths in Angstroms corresponding to the columns of _flux_density_matrix. target_grid_step : float or None The unit of the grid (in Angstrom) to which the flux density matrix and normalized transmission @@ -275,7 +275,7 @@ def _interpolate(self, _flux_density_matrix, _wavelengths_angstrom, target_grid_ interpolated normalized transmission table. """ # Make sure all given wavelengths are strictly increasing - if not np.all(np.diff(_wavelengths_angstrom) > 0): + if not np.all(np.diff(_flux_wavelengths) > 0): raise ValueError("Wavelengths corresponding to flux density matrix must be strictly increasing.") # Create target grid @@ -287,18 +287,18 @@ def _interpolate(self, _flux_density_matrix, _wavelengths_angstrom, target_grid_ target_grid = interpolation.create_grid(self.normalized_transmission_table[:, 0], target_grid_step) # Interpolate the flux density matrix - if not np.array_equal(_wavelengths_angstrom, target_grid): + if not np.array_equal(_flux_wavelengths, target_grid): interpolated_flux_density_matrix = [] for row in _flux_density_matrix: flux_density_spline = CubicSpline( - _wavelengths_angstrom, row, bc_type="not-a-knot", extrapolate=True + _flux_wavelengths, row, bc_type="not-a-knot", extrapolate=True ) interpolated_flux_density_matrix.append(flux_density_spline(target_grid)) flux_density_matrix = np.array(interpolated_flux_density_matrix) - wavelengths_angstrom = target_grid + flux_wavelengths = target_grid else: flux_density_matrix = _flux_density_matrix - wavelengths_angstrom = _wavelengths_angstrom + flux_wavelengths = _flux_wavelengths # Interpolate the normalized transmission table if not np.array_equal(self.normalized_transmission_table[:, 0], target_grid): @@ -313,10 +313,10 @@ def _interpolate(self, _flux_density_matrix, _wavelengths_angstrom, target_grid_ else: normalized_transmission_table = self.normalized_transmission_table - return (flux_density_matrix, wavelengths_angstrom, normalized_transmission_table) + return (flux_density_matrix, flux_wavelengths, normalized_transmission_table) def fluxes_to_bandflux( - self, _flux_density_matrix, _wavelengths_angstrom, target_grid_step=None + self, _flux_density_matrix, _flux_wavelengths, target_grid_step=None ) -> np.ndarray: """Calculate the bandflux for a given set of flux densities. @@ -331,7 +331,7 @@ def fluxes_to_bandflux( ---------- flux_density_matrix : np.ndarray A 2D array of flux densities where rows are times and columns are wavelengths. - wavelengths_angstrom : np.ndarray + flux_wavelengths : np.ndarray An array of wavelengths in Angstroms corresponding to the columns of flux_density_matrix. target_grid_step : float, optional The unit of the grid (in Angstrom) to which the flux density matrix and normalized transmission @@ -342,12 +342,12 @@ def fluxes_to_bandflux( np.ndarray An array of bandfluxes. """ - flux_density_matrix, wavelengths_angstrom, normalized_transmission_table = self._interpolate( - _flux_density_matrix, _wavelengths_angstrom, target_grid_step + flux_density_matrix, flux_wavelengths, normalized_transmission_table = self._interpolate( + _flux_density_matrix, _flux_wavelengths, target_grid_step ) # Calculate the bandflux as ∫ f(λ)φ_b(λ) dλ, # where f(λ) is the in-band flux density and φ_b(λ) is the normalized system response integrand = flux_density_matrix * normalized_transmission_table[:, 1] - bandfluxes = scipy.integrate.trapezoid(integrand, x=wavelengths_angstrom) + bandfluxes = scipy.integrate.trapezoid(integrand, x=flux_wavelengths) return bandfluxes From dd1c86b1da02b5faf80bc4f592a5532d8740624f Mon Sep 17 00:00:00 2001 From: Olivia Lynn Date: Wed, 4 Sep 2024 10:49:11 -0400 Subject: [PATCH 11/38] Handle transmission table interp before normalization; allow user to reset target grid after initialization --- src/tdastro/astro_utils/passbands.py | 134 ++++++++++++++++----------- 1 file changed, 79 insertions(+), 55 deletions(-) diff --git a/src/tdastro/astro_utils/passbands.py b/src/tdastro/astro_utils/passbands.py index b76298e8..a1011c01 100644 --- a/src/tdastro/astro_utils/passbands.py +++ b/src/tdastro/astro_utils/passbands.py @@ -110,8 +110,10 @@ class Passband: The full name of the passband. This is the survey and label concatenated: eg, "LSST_u". wave_grid : np.ndarray | float | None The grid of wavelengths (Angstrom) to which the flux density matrix and transmission table should be - interpolated. If None, the grid will be interpolated to the grid of the flux density matrix. Default - is 5.0. + interpolated. If a float is given, wave_grid will be converted to a numpy array with a wave_grid step + matching the boundaries of the transmission table. If None, the transmission table will later be + interpolated to a grid with the same boundaries, but matching the step of the flux density matrix. + Default is 5.0. table_path : str The path to the transmission table file. table_url : str @@ -129,30 +131,26 @@ def __init__(self, survey, label, wave_grid=5.0, table_path=None, table_url=""): self.wave_grid = wave_grid self.table_path = table_path self.table_url = table_url - self.normalized_transmission_table = self._get_normalized_transmission_table() + + loaded_table = self._get_transmission_table() + self.processed_transmission_table = self._process_transmission_table(loaded_table) def __str__(self) -> str: """Return a string representation of the Passband.""" return f"Passband: {self.full_name}" - def _get_normalized_transmission_table(self) -> np.ndarray: + def _get_transmission_table(self) -> np.ndarray: # Check if the table file exists locally, and download it if it doesn't if self.table_path is None: self.table_path = os.path.join( os.path.dirname(__file__), f"passbands/{self.survey}/{self.label}.dat" ) os.makedirs(os.path.dirname(self.table_path), exist_ok=True) - if not os.path.exists(self.table_path): self._download_transmission_table() - # Load the table, downsizing/interpolating as needed, and normalize it - loaded_table = self._load_transmission_table() - interpolated_transmissions = self._downsample_or_interpolate_transmission_table(loaded_table) - normalized_transmissions = self._normalize_transmission_table(interpolated_transmissions) - - # Return the table - return normalized_transmissions + # Load the table + return self._load_transmission_table() def _download_transmission_table(self) -> bool: """Download a transmission table from a URL. @@ -211,6 +209,23 @@ def _load_transmission_table(self) -> np.ndarray: return loaded_table + def _process_transmission_table(self, loaded_table) -> np.ndarray: + """Process the transmission table: downsample or interpolate, then normalize. + + Parameters + ---------- + loaded_table : np.ndarray + A 2D array of wavelengths and transmissions. + + Returns + ------- + np.ndarray + A 2D array of wavelengths and normalized transmissions. + """ + interpolated_transmissions = self._downsample_or_interpolate_transmission_table(loaded_table) + normalized_transmissions = self._normalize_transmission_table(interpolated_transmissions) + return normalized_transmissions + def _downsample_or_interpolate_transmission_table(self, loaded_table) -> np.ndarray: """Downsample or interpolate a transmission table to a desired grid. @@ -246,8 +261,8 @@ def _normalize_transmission_table(self, transmission_table) -> np.ndarray: np.ndarray A 2D array of wavelengths and normalized transmissions. """ - wavelengths_angstrom = self.transmission_table[:, 0] - transmissions = self.transmission_table[:, 1] + wavelengths_angstrom = transmission_table[:, 0] + transmissions = transmission_table[:, 1] # Calculate the numerators and denominator numerators = transmissions / wavelengths_angstrom denominator = scipy.integrate.trapezoid(numerators, x=wavelengths_angstrom) @@ -255,8 +270,32 @@ def _normalize_transmission_table(self, transmission_table) -> np.ndarray: normalized_transmissions = numerators / denominator return np.column_stack((wavelengths_angstrom, normalized_transmissions)) - def _interpolate(self, _flux_density_matrix, _flux_wavelengths, target_grid_step) -> tuple: - """Interpolate the flux density matrix and transmission table to a target grid. + def set_transmission_table_to_new_grid(self, new_wave_grid) -> None: + """Set the transmission table to a new grid. + + A public wrapper for _process_transmission_table, first setting the wave grid and loading the + unprocessed transmission table. + + Parameters + ---------- + new_wave_grid : np.ndarray | float | None + The grid of wavelengths (Angstrom) to which the flux density matrix and transmission table should + be interpolated. A float will be converted to a numpy array with a grid step matching the + boundaries of the transmission table. If None, the transmission table will later be interpolated + to a grid maintaining the same boundaries, but matching the step of the flux density matrix. + """ + self.wave_grid = new_wave_grid + + if self.wave_grid is None: + return + + self.wave_grid = interpolation.create_grid(self.processed_transmission_table[:, 0], new_wave_grid) + + loaded_table = self._load_transmission_table() + self.processed_transmission_table = self._process_transmission_table(loaded_table) + + def _interpolate(self, _flux_density_matrix, _flux_wavelengths) -> tuple: + """Interpolate the flux density matrix to match the transmission table, which matches self.wave_grid. Parameters ---------- @@ -264,60 +303,48 @@ def _interpolate(self, _flux_density_matrix, _flux_wavelengths, target_grid_step A 2D array of flux densities where rows are times and columns are wavelengths. _flux_wavelengths : np.ndarray An array of wavelengths in Angstroms corresponding to the columns of _flux_density_matrix. - target_grid_step : float or None - The unit of the grid (in Angstrom) to which the flux density matrix and normalized transmission - table should be interpolated. Returns ------- tuple - A tuple containing the interpolated flux density matrix, interpolated wavelengths, and - interpolated normalized transmission table. + A tuple containing the interpolated flux density matrix and interpolated wavelengths. """ # Make sure all given wavelengths are strictly increasing if not np.all(np.diff(_flux_wavelengths) > 0): raise ValueError("Wavelengths corresponding to flux density matrix must be strictly increasing.") - # Create target grid - if target_grid_step is None: - raise ValueError("Target grid step must be provided.") - # TODO consider defaulting to the grid to the given flux density matrix - # However, might be less desirable if flux density matrix is very sparse or irregularly stepped - - target_grid = interpolation.create_grid(self.normalized_transmission_table[:, 0], target_grid_step) + # Get the target grid, if it is not already set; and, convert to array. + if self.wave_grid is None: + if not np.allclose(np.diff(_flux_wavelengths), np.diff(_flux_wavelengths)[0]): + raise ValueError( + "Flux density wavelengths must have a uniform step for interpolation. " + "Alternatively, provide a target grid step." + ) + self.wave_grid = interpolation.create_grid( + self.processed_transmission_table[:, 0], np.diff(_flux_wavelengths)[0] + ) + elif type(self.wave_grid) == float: + self.wave_grid = interpolation.create_grid( + self.processed_transmission_table[:, 0], self.wave_grid + ) # Interpolate the flux density matrix - if not np.array_equal(_flux_wavelengths, target_grid): + if not np.array_equal(_flux_wavelengths, self.wave_grid): interpolated_flux_density_matrix = [] for row in _flux_density_matrix: flux_density_spline = CubicSpline( _flux_wavelengths, row, bc_type="not-a-knot", extrapolate=True ) - interpolated_flux_density_matrix.append(flux_density_spline(target_grid)) + interpolated_flux_density_matrix.append(flux_density_spline(self.wave_grid)) flux_density_matrix = np.array(interpolated_flux_density_matrix) - flux_wavelengths = target_grid + flux_wavelengths = self.wave_grid else: flux_density_matrix = _flux_density_matrix flux_wavelengths = _flux_wavelengths - # Interpolate the normalized transmission table - if not np.array_equal(self.normalized_transmission_table[:, 0], target_grid): - normalized_transmission_spline = CubicSpline( - self.normalized_transmission_table[:, 0], - self.normalized_transmission_table[:, 1], - bc_type="not-a-knot", - extrapolate=True, - ) - interpolated_transmissions = normalized_transmission_spline(target_grid) - normalized_transmission_table = np.column_stack((target_grid, interpolated_transmissions)) - else: - normalized_transmission_table = self.normalized_transmission_table - - return (flux_density_matrix, flux_wavelengths, normalized_transmission_table) + return (flux_density_matrix, flux_wavelengths) - def fluxes_to_bandflux( - self, _flux_density_matrix, _flux_wavelengths, target_grid_step=None - ) -> np.ndarray: + def fluxes_to_bandflux(self, _flux_density_matrix, _flux_wavelengths) -> np.ndarray: """Calculate the bandflux for a given set of flux densities. This is eq. 7 from "On the Choice of LSST Flux Units" (Ivezić et al.): @@ -333,21 +360,18 @@ def fluxes_to_bandflux( A 2D array of flux densities where rows are times and columns are wavelengths. flux_wavelengths : np.ndarray An array of wavelengths in Angstroms corresponding to the columns of flux_density_matrix. - target_grid_step : float, optional - The unit of the grid (in Angstrom) to which the flux density matrix and normalized transmission - table should be interpolated. Returns ------- np.ndarray An array of bandfluxes. """ - flux_density_matrix, flux_wavelengths, normalized_transmission_table = self._interpolate( - _flux_density_matrix, _flux_wavelengths, target_grid_step - ) + # Interpolate flux density matrix to match the transmission table, which matches self.wave_grid + flux_density_matrix, flux_wavelengths = self._interpolate(_flux_density_matrix, _flux_wavelengths) + # Calculate the bandflux as ∫ f(λ)φ_b(λ) dλ, # where f(λ) is the in-band flux density and φ_b(λ) is the normalized system response - integrand = flux_density_matrix * normalized_transmission_table[:, 1] + integrand = flux_density_matrix * self.processed_transmission_table[:, 1] bandfluxes = scipy.integrate.trapezoid(integrand, x=flux_wavelengths) return bandfluxes From 477218c8367e8a688e73a7a36c191ada9d81bdee Mon Sep 17 00:00:00 2001 From: Olivia Lynn Date: Wed, 4 Sep 2024 14:59:45 -0400 Subject: [PATCH 12/38] Update unit tests; remove unit tests for now-removed functionality --- src/tdastro/astro_utils/interpolation.py | 33 ++- src/tdastro/astro_utils/passbands.py | 77 ++++- .../tdastro/astro_utils/test_interpolation.py | 263 ++---------------- tests/tdastro/astro_utils/test_passbands.py | 68 +++-- 4 files changed, 157 insertions(+), 284 deletions(-) diff --git a/src/tdastro/astro_utils/interpolation.py b/src/tdastro/astro_utils/interpolation.py index 027af20a..2977b727 100644 --- a/src/tdastro/astro_utils/interpolation.py +++ b/src/tdastro/astro_utils/interpolation.py @@ -19,33 +19,42 @@ def get_grid_step(grid: np.ndarray) -> float: return None -def create_grid(wavelengths: np.ndarray, new_grid_step: float) -> np.ndarray: - """Interpolate a grid of wavelengths to a new grid with a given step size. +def create_grid(bounds: np.ndarray | tuple, grid_step: float, increasing=True) -> np.ndarray: + """Create a new grid with given bounds and grid step. If the interval between the original grid's upper and lower bounds is a multiple of the new grid step, the upper bound will be included in the new grid. Parameters ---------- - wavelengths : np.ndarray - The grid of wavelengths (must be strictly increasing). - new_grid_step : float + bounds : np.ndarray | tuple + The bounds of the grid. If a tuple, it should be (lower_bound, upper_bound). If an array, the first + and last elements will be used as the lower and upper bounds, respectively. + grid_step : float The step size of the new grid. + increasing : bool, optional + Whether the grid should include checks that bounds are increasing. Default is True. Returns ------- np.ndarray - The interpolated grid. + The new grid. """ - # Check that wavelengths are strictly increasing - if not np.all(np.diff(wavelengths) > 0): - raise ValueError("Wavelengths must be strictly increasing.") + # Get bounds + if isinstance(bounds, tuple): + lower_bound, upper_bound = bounds + else: + lower_bound, upper_bound = bounds[0], bounds[-1] + + # Check lower bound is less than upper bound + if increasing and lower_bound >= upper_bound: + raise ValueError("Lower bound must be less than upper bound, or disable 'increasing' check.") # Generate new grid, including the original upper bound if step size is a divisor of target interval - if (wavelengths[-1] - wavelengths[0]) % new_grid_step == 0: - new_grid = np.arange(wavelengths[0], wavelengths[-1] + new_grid_step, new_grid_step) + if (upper_bound - lower_bound) % grid_step == 0: + new_grid = np.arange(lower_bound, upper_bound + grid_step, grid_step) else: - new_grid = np.arange(wavelengths[0], wavelengths[-1], new_grid_step) + new_grid = np.arange(lower_bound, upper_bound, grid_step) return new_grid diff --git a/src/tdastro/astro_utils/passbands.py b/src/tdastro/astro_utils/passbands.py index a1011c01..4b8d4be0 100644 --- a/src/tdastro/astro_utils/passbands.py +++ b/src/tdastro/astro_utils/passbands.py @@ -69,9 +69,18 @@ def _load_preset(self, preset): else: raise ValueError(f"Unknown passband preset: {preset}") - def fluxes_to_bandfluxes( - self, flux_density_matrix, flux_wavelengths, target_grid_step=None - ) -> np.ndarray: + def set_wave_grids(self, wave_grids: dict) -> None: + """Set the wave grid attribute for all passbands in the group. + + Parameters + ---------- + wave_grids : dict + A dictionary of passband labels and wave grids. + """ + for label, wave_grid in wave_grids.items(): + self.passbands[label].set_wave_grid(wave_grid) + + def fluxes_to_bandfluxes(self, flux_density_matrix, flux_wavelengths) -> np.ndarray: """Calculate bandfluxes for all passbands in the group. Parameters @@ -91,9 +100,7 @@ def fluxes_to_bandfluxes( """ bandfluxes = {} for label, passband in self.passbands.items(): - bandfluxes[label] = passband.fluxes_to_bandflux( - flux_density_matrix, flux_wavelengths, target_grid_step=target_grid_step - ) + bandfluxes[label] = passband.fluxes_to_bandflux(flux_density_matrix, flux_wavelengths) return bandfluxes @@ -128,17 +135,53 @@ def __init__(self, survey, label, wave_grid=5.0, table_path=None, table_url=""): self.label = label self.survey = survey self.full_name = f"{survey}_{label}" - self.wave_grid = wave_grid + self.table_path = table_path self.table_url = table_url - loaded_table = self._get_transmission_table() + + self.set_wave_grid(wave_grid, bounds=(loaded_table[0, 0], loaded_table[-1, 0])) + self.processed_transmission_table = self._process_transmission_table(loaded_table) def __str__(self) -> str: """Return a string representation of the Passband.""" return f"Passband: {self.full_name}" + def set_wave_grid(self, wave_grid: np.ndarray | float | None, bounds=None) -> None: + """Set the wave grid attribute, which is used for interpolation. + + Parameters + ---------- + wave_grid : np.ndarray | float | None + The grid of wavelengths (Angstrom) to which the flux density matrix and transmission table should + be interpolated. A float will be converted to a numpy array with a grid step matching the + boundaries of the transmission table. If None, the transmission table will later be interpolated + to a grid maintaining the same boundaries, but matching the step of the flux density matrix. + bounds : tuple, optional + The lower and upper bounds of the grid. If None, the bounds will be set to the minimum and + maximum wavelengths in the transmission table. + """ + self.wave_grid = wave_grid + print(f"SET WAVE GRID: {self.wave_grid}") + + if bounds is None and self.processed_transmission_table is None: + raise ValueError("Wave grid bounds must be provided if transmission table is not loaded.") + elif bounds is None: + bounds = (self.processed_transmission_table[0, 0], self.processed_transmission_table[-1, 0]) + + print(f"BOUNDS: {bounds}") + + # TODO should this check: + # 1. the bounds are within the transmission table + # 2. if the wave_grid was given as an array, but bounds were also given, that they match + + if isinstance(self.wave_grid, (float, int)): + self.wave_grid = interpolation.create_grid(bounds, self.wave_grid) + print(f" TO ARRAY: {self.wave_grid}") + + print(f" WAVEGRID: {self.wave_grid} (type: {type(self.wave_grid)})") + def _get_transmission_table(self) -> np.ndarray: # Check if the table file exists locally, and download it if it doesn't if self.table_path is None: @@ -199,6 +242,9 @@ def _load_transmission_table(self) -> np.ndarray: # Load the table file loaded_table = np.loadtxt(self.table_path) + with np.printoptions(precision=3, suppress=True): + print(f"LOADED TABLE:\n{loaded_table}") + # Check that the table has the correct shape if loaded_table.shape[1] != 2: raise ValueError("Transmission table must have exactly 2 columns.") @@ -222,12 +268,15 @@ def _process_transmission_table(self, loaded_table) -> np.ndarray: np.ndarray A 2D array of wavelengths and normalized transmissions. """ - interpolated_transmissions = self._downsample_or_interpolate_transmission_table(loaded_table) + interpolated_transmissions = self._interpolate_or_downsample_transmission_table(loaded_table) normalized_transmissions = self._normalize_transmission_table(interpolated_transmissions) + # with np.printoptions(precision=3, suppress=True): + # print(f"INTERPOLATED TRANSMISSIONS: {interpolated_transmissions}") + # print(f"NORMALIZED TRANSMISSIONS: {normalized_transmissions}") return normalized_transmissions - def _downsample_or_interpolate_transmission_table(self, loaded_table) -> np.ndarray: - """Downsample or interpolate a transmission table to a desired grid. + def _interpolate_or_downsample_transmission_table(self, loaded_table) -> np.ndarray: + """Interpolate or downsample a transmission table to a desired grid. Returns ------- @@ -294,7 +343,7 @@ def set_transmission_table_to_new_grid(self, new_wave_grid) -> None: loaded_table = self._load_transmission_table() self.processed_transmission_table = self._process_transmission_table(loaded_table) - def _interpolate(self, _flux_density_matrix, _flux_wavelengths) -> tuple: + def _interpolate_flux_densities(self, _flux_density_matrix, _flux_wavelengths) -> tuple: """Interpolate the flux density matrix to match the transmission table, which matches self.wave_grid. Parameters @@ -367,7 +416,9 @@ def fluxes_to_bandflux(self, _flux_density_matrix, _flux_wavelengths) -> np.ndar An array of bandfluxes. """ # Interpolate flux density matrix to match the transmission table, which matches self.wave_grid - flux_density_matrix, flux_wavelengths = self._interpolate(_flux_density_matrix, _flux_wavelengths) + flux_density_matrix, flux_wavelengths = self._interpolate_flux_densities( + _flux_density_matrix, _flux_wavelengths + ) # Calculate the bandflux as ∫ f(λ)φ_b(λ) dλ, # where f(λ) is the in-band flux density and φ_b(λ) is the normalized system response diff --git a/tests/tdastro/astro_utils/test_interpolation.py b/tests/tdastro/astro_utils/test_interpolation.py index c7f958d9..c537393e 100644 --- a/tests/tdastro/astro_utils/test_interpolation.py +++ b/tests/tdastro/astro_utils/test_interpolation.py @@ -2,10 +2,28 @@ import pytest from tdastro.astro_utils.interpolation import ( create_grid, + get_grid_step, interpolate_matrix_along_wavelengths, interpolate_transmission_table, ) -from tdastro.astro_utils.passbands import Passband + + +def test_get_grid_step(): + """Test get_grid_step function.""" + # Test uniform grid + grid = np.array([1, 2, 3]) + grid_step = get_grid_step(grid) + assert grid_step == 1 + + # Test non-uniform grid + grid = np.array([1, 2, 4]) + grid_step = get_grid_step(grid) + assert grid_step is None + + # Test non-uniform grid with equal differences + grid = np.array([1, 2, 2]) + grid_step = get_grid_step(grid) + assert grid_step is None def test_create_grid(): @@ -39,18 +57,7 @@ def test_create_grid(): interp_wavelengths = create_grid(wavelengths, new_grid_step) np.testing.assert_allclose(interp_wavelengths, np.array([1.0, 3.0])) - -def test_interpolate_matrix_along_wavelengths(): - """Test interpolate_matrix_along_wavelengths function.""" - fluxes = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]) - wavelengths = np.array([1, 2, 3]) - new_grid_step = 0.5 - interp_wavelengths = create_grid(wavelengths, new_grid_step) - interp_fluxes = interpolate_matrix_along_wavelengths(fluxes, wavelengths, interp_wavelengths) - np.testing.assert_allclose( - interp_fluxes, - np.array([[1.0, 1.5, 2.0, 2.5, 3.0], [4.0, 4.5, 5.0, 5.5, 6.0], [7.0, 7.5, 8.0, 8.5, 9.0]]), - ) + # TODO add tuple bounds test def test_interpolate_transmission_table(): @@ -78,224 +85,14 @@ def test_interpolate_transmission_table(): # TODO test edge cases -def _make_passband(transmission_table, path): - """Helper function to create a Passband object from a transmission table.""" - survey = "TEST" - band_label = "a" - table_path = path / f"{survey}_{band_label}.dat" - with open(table_path, "w") as f: - f.write(transmission_table) - a_band = Passband(survey, band_label, table_path=table_path) - return a_band - - -def test_interpolate_passband_simple(tmp_path): - """Test _interpolate function.""" - flux_density_matrix = np.array([[1.0, 1.0, 1.0], [1.0, 10.0, 1.0], [1.0, 0.0, 1.0]]) - wavelengths_angstrom = np.array([100.0, 105.0, 110.0]) - - transmission_table = "100 0.5\n" "110 1.0\n" - a_band = _make_passband(transmission_table, tmp_path) - - # Interpolate to grid of 1.0 - new_grid_step = 1.0 - interpolated_fluxes, interpolated_wavelengths, interpolated_t_table = a_band._interpolate( - flux_density_matrix, - wavelengths_angstrom, - new_grid_step, - ) - - # Assert shape/size - assert interpolated_fluxes.shape == (3, 11) - assert len(interpolated_wavelengths) == 11 - assert len(interpolated_t_table) == 11 - - # Assert values - np.testing.assert_allclose(interpolated_wavelengths, np.arange(100, 111)) - np.testing.assert_allclose(interpolated_fluxes[0], [1.0] * 11) - assert np.isclose(interpolated_fluxes[1][0], 1.0) - assert np.isclose(interpolated_fluxes[1][5], 10.0) - assert np.isclose(interpolated_fluxes[1][10], 1.0) - assert np.isclose(interpolated_fluxes[2][0], 1.0) - assert np.isclose(interpolated_fluxes[2][5], 0.0) - assert np.isclose(interpolated_fluxes[2][10], 1.0) - - # Check the original data was not modified - assert flux_density_matrix.shape == (3, 3) - assert wavelengths_angstrom.shape == (3,) - - -def test_interpolate_passband_coarser_grid(tmp_path): - """Test _interpolate function if target grid is coarser than current grid.""" - flux_density_matrix = np.array([[1.0, 1.0, 1.0], [1.0, 10.0, 1.0], [1.0, 0.0, 1.0]]) - wavelengths_angstrom = np.array([100.0, 105.0, 110.0]) - - transmission_table = "100 0.5\n" "110 1.0\n" - a_band = _make_passband(transmission_table, tmp_path) - - # Interpolate to grid of 10.0 - new_grid_step = 10.0 - interpolated_fluxes, interpolated_wavelengths, interpolated_t_table = a_band._interpolate( - flux_density_matrix, - wavelengths_angstrom, - new_grid_step, - ) - - # Assert shape/size - assert interpolated_fluxes.shape == (3, 2) - assert len(interpolated_wavelengths) == 2 - assert len(interpolated_t_table) == 3 - - # Assert values - assert np.isclose(interpolated_wavelengths[0], 100.0) - assert np.isclose(interpolated_wavelengths[1], 110.0) - np.testing.assert_allclose(interpolated_fluxes[0], [1.0, 1.0]) - np.testing.assert_allclose(interpolated_fluxes[1], [1.0, 1.0]) - np.testing.assert_allclose(interpolated_fluxes[2], [1.0, 1.0]) - - -def test_interpolate_passband_none_needed(tmp_path): - """Test _interpolate function if no interpolation is needed for target grid.""" - flux_density_matrix = np.array([[1.0, 1.0, 1.0], [1.0, 10.0, 1.0], [1.0, 0.0, 1.0]]) - wavelengths_angstrom = np.array([100.0, 105.0, 110.0]) - - transmission_table = "100 0.5\n" "110 1.0\n" - a_band = _make_passband(transmission_table, tmp_path) - - # Interpolate to grid of 5.0 (no interpolation) - new_grid_step = 5.0 - interpolated_fluxes, interpolated_wavelengths, interpolated_t_table = a_band._interpolate( - flux_density_matrix, - wavelengths_angstrom, - new_grid_step, - ) - - # Assert shape/size - assert interpolated_fluxes.shape == (3, 3) - assert len(interpolated_wavelengths) == 3 - assert len(interpolated_t_table) == 3 - - # Assert values - np.testing.assert_allclose(interpolated_wavelengths, wavelengths_angstrom) - np.testing.assert_allclose(interpolated_fluxes, flux_density_matrix) - np.testing.assert_allclose(interpolated_t_table, np.array([100.0, 0.5], [110.0, 1.0])) - - # Assert scipy.interpolate.CubicSpline was not called - # TODO - - -def test_extrapolate_fluxes(tmp_path): - """Test flux matrix extrapolation performed in _interpolate function.""" - flux_density_matrix = np.array([[1.0, 1.0, 1.0], [1.0, 10.0, 1.0], [1.0, 0.0, 1.0]]) - wavelengths_angstrom = np.array([100.0, 105.0, 110.0]) - - transmission_table = "100 0.5\n105 0.75\n110 1.0\n115 0.75\n120 0.5\n" - a_band = _make_passband(transmission_table, tmp_path) - - # Interpolate to grid of 5.0 (no interpolation needed, but extrapolation is) - new_grid_step = 5.0 - interpolated_fluxes, interpolated_wavelengths, interpolated_t_table = a_band._interpolate( - flux_density_matrix, - wavelengths_angstrom, - new_grid_step, - ) - - # Assert shape/size - assert interpolated_fluxes.shape == (3, 5) - assert len(interpolated_wavelengths) == 5 - assert len(interpolated_t_table) == 5 - - # Assert values - np.testing.assert_allclose(interpolated_wavelengths, [100.0, 105.0, 110.0, 115.0, 120.0]) - np.testing.assert_allclose(interpolated_fluxes[0], [1.0, 1.0, 1.0, 1.0, 1.0]) - np.testing.assert_allclose(interpolated_fluxes[1][:3], [1.0, 10.0, 1.0]) - np.testing.assert_allclose(interpolated_fluxes[2][:3], [1.0, 0.0, 1.0]) - np.testing.assert_allclose(interpolated_t_table, a_band.normalized_transmission_table) - - -def test_truncate_fluxes(tmp_path): - """Test flux matrix truncation performed in _interpolate function.""" - flux_density_matrix = np.array([[1.0, 1.0, 1.0], [1.0, 10.0, 1.0], [1.0, 0.0, 1.0]]) - wavelengths_angstrom = np.array([100.0, 105.0, 110.0]) - - transmission_table = "100 0.5\n105 0.75\n" - a_band = _make_passband(transmission_table, tmp_path) - - # Interpolate to grid of 5.0 (no interpolation needed, but truncation is) - new_grid_step = 5.0 - interpolated_fluxes, interpolated_wavelengths, interpolated_t_table = a_band._interpolate( - flux_density_matrix, - wavelengths_angstrom, - new_grid_step, - ) - - # Assert shape/size - assert interpolated_fluxes.shape == (3, 2) - assert len(interpolated_wavelengths) == 2 - assert len(interpolated_t_table) == 2 - - # Assert values - np.testing.assert_allclose(interpolated_wavelengths, [100.0, 105.0]) - np.testing.assert_allclose(interpolated_fluxes[0], [1.0, 1.0]) - np.testing.assert_allclose(interpolated_fluxes[1], [1.0, 10.0]) - np.testing.assert_allclose(interpolated_fluxes[2], [1.0, 0.0]) - np.testing.assert_allclose(interpolated_t_table, a_band.normalized_transmission_table) - - -def test_truncate_and_interpolate_fluxes(tmp_path): - """Test flux matrix truncation performed in _interpolate function.""" - flux_density_matrix = np.array([[1.0, 1.0, 1.0], [1.0, 10.0, 1.0], [1.0, 0.0, 1.0]]) - wavelengths_angstrom = np.array([100.0, 105.0, 110.0]) - - transmission_table = "100 0.5\n105 0.75\n" - a_band = _make_passband(transmission_table, tmp_path) - - # Interpolate to grid of 1.0 (both interpolation and truncation needed) - new_grid_step = 1.0 - interpolated_fluxes, interpolated_wavelengths, interpolated_t_table = a_band._interpolate( - flux_density_matrix, - wavelengths_angstrom, - new_grid_step, - ) - - # Assert shape/size - assert interpolated_fluxes.shape == (3, 6) - assert len(interpolated_wavelengths) == 6 - assert len(interpolated_t_table) == 6 - - # Assert values - np.testing.assert_allclose(interpolated_wavelengths, [100.0, 101.0, 102.0, 103.0, 104.0, 105.0]) - np.testing.assert_allclose(interpolated_fluxes[0], [1.0] * 6) - assert np.isclose(interpolated_fluxes[1][0], 1.0) - assert np.isclose(interpolated_fluxes[1][5], 10.0) - assert np.isclose(interpolated_fluxes[2][0], 1.0) - assert np.isclose(interpolated_fluxes[2][5], 0.0) - assert np.isclose(interpolated_t_table[0][0], 100.0) - assert np.isclose(interpolated_t_table[0][1], a_band.normalized_transmission_table[0][1]) - assert np.isclose(interpolated_t_table[5][0], 105.0) - assert np.isclose(interpolated_t_table[5][1], a_band.normalized_transmission_table[1][1]) - - -def test_extrapolate_out_of_range(tmp_path): - """Test flux matrix extrapolation when given fluxes are completely out of range for passband.""" - flux_density_matrix = np.array([[1.0, 1.0, 1.0], [1.0, 10.0, 1.0], [1.0, 0.0, 1.0]]) - wavelengths_angstrom = np.array([200.0, 205.0, 210.0]) - - transmission_table = "100 0.5\n110 1.0" - a_band = _make_passband(transmission_table, tmp_path) - - # Interpolate to grid of 5.0 (no interpolation needed, but extrapolation is) - new_grid_step = 5.0 - interpolated_fluxes, interpolated_wavelengths, interpolated_t_table = a_band._interpolate( - flux_density_matrix, - wavelengths_angstrom, - new_grid_step, +def test_interpolate_matrix_along_wavelengths(): + """Test interpolate_matrix_along_wavelengths function.""" + fluxes = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]) + wavelengths = np.array([1, 2, 3]) + new_grid_step = 0.5 + interp_wavelengths = create_grid(wavelengths, new_grid_step) + interp_fluxes = interpolate_matrix_along_wavelengths(fluxes, wavelengths, interp_wavelengths) + np.testing.assert_allclose( + interp_fluxes, + np.array([[1.0, 1.5, 2.0, 2.5, 3.0], [4.0, 4.5, 5.0, 5.5, 6.0], [7.0, 7.5, 8.0, 8.5, 9.0]]), ) - - # Well, here we see the results of the extrapolation. - # Don't love the [-3959. -3590. -3239.] fluxes. - # TODO - with np.printoptions(precision=2, suppress=True): - print(interpolated_fluxes) - print(interpolated_wavelengths) - print(interpolated_t_table) diff --git a/tests/tdastro/astro_utils/test_passbands.py b/tests/tdastro/astro_utils/test_passbands.py index c4bd58fe..7700263b 100644 --- a/tests/tdastro/astro_utils/test_passbands.py +++ b/tests/tdastro/astro_utils/test_passbands.py @@ -106,7 +106,7 @@ def test_passband_load_transmission_table(tmp_path): table_path = tmp_path / f"{survey}_{band_label}.dat" # Create a transmission table file - transmission_table = "1000 0.5\n1001 0.6\n1002 0.7\n" + transmission_table = "1000 0.5\n1005 0.6\n1010 0.7\n" with open(table_path, "w") as f: f.write(transmission_table) @@ -114,13 +114,10 @@ def test_passband_load_transmission_table(tmp_path): a_band = Passband(survey, band_label, table_path=table_path) # Check that the transmission table was loaded correctly - assert a_band.transmission_table.shape == (3, 2) - assert a_band.transmission_table[0, 0] == 1000 - assert a_band.transmission_table[0, 1] == 0.5 - assert a_band.transmission_table[1, 0] == 1001 - assert a_band.transmission_table[1, 1] == 0.6 - assert a_band.transmission_table[2, 0] == 1002 - assert a_band.transmission_table[2, 1] == 0.7 + assert a_band.processed_transmission_table.shape == (3, 2) + assert np.allclose(a_band.processed_transmission_table[:, 0], np.array([1000, 1005, 1010])) + assert a_band.processed_transmission_table[0, 1] < a_band.processed_transmission_table[1, 1] + assert a_band.processed_transmission_table[1, 1] < a_band.processed_transmission_table[2, 1] def test_passband_download_transmission_table(tmp_path): @@ -130,7 +127,7 @@ def test_passband_download_transmission_table(tmp_path): band_label = "a" table_path = tmp_path / f"{survey}_{band_label}.dat" table_url = f"http://example.com/{survey}/{band_label}.dat" - transmission_table = "1000 0.5\n1001 0.6\n1002 0.7\n" + transmission_table = "1000 0.5\n1005 0.6\n1010 0.7\n" def mock_urlretrieve(url, filename, *args, **kwargs): # Urlretrieve saves contents directly to filename with open(filename, "w") as f: @@ -145,13 +142,15 @@ def mock_urlretrieve(url, filename, *args, **kwargs): # Urlretrieve saves conte mocked_urlretrieve.assert_called_once_with(table_url, table_path) # Check that the transmission table was loaded correctly - assert a_band.transmission_table.shape == (3, 2) - assert a_band.transmission_table[0, 0] == 1000 - assert a_band.transmission_table[0, 1] == 0.5 - assert a_band.transmission_table[1, 0] == 1001 - assert a_band.transmission_table[1, 1] == 0.6 - assert a_band.transmission_table[2, 0] == 1002 - assert a_band.transmission_table[2, 1] == 0.7 + assert a_band.processed_transmission_table.shape == (3, 2) + assert a_band.processed_transmission_table[0, 0] == 1000 + assert a_band.processed_transmission_table[1, 0] == 1005 + assert a_band.processed_transmission_table[2, 0] == 1010 + + +def test_passband_interpolate_or_downsample_transmission_table(tmp_path): + """TODO""" + pass def test_passband_normalize_transmission_table(tmp_path): @@ -165,11 +164,21 @@ def test_passband_normalize_transmission_table(tmp_path): with open(table_path, "w") as f: f.write(transmission_table) - a_band = Passband(survey, band_label, table_path=table_path) + a_band = Passband(survey, band_label, table_path=table_path, wave_grid=100) # Compare results expected_result = np.array([[100.0, 0.0075], [200.0, 0.005625], [300.0, 0.00125]]) - assert np.allclose(a_band.normalized_transmission_table, expected_result) + assert np.allclose(a_band.processed_transmission_table, expected_result) + + +def test_set_transmission_table_to_new_grid(tmp_path): + """TODO""" + pass + + +def test_passband_flux_interpolate_flux_densities(tmp_path): + """TODO""" + pass def test_passband_fluxes_to_bandflux(tmp_path): @@ -183,7 +192,7 @@ def test_passband_fluxes_to_bandflux(tmp_path): with open(table_path, "w") as f: f.write(transmission_table) - a_band = Passband(survey, band_label, table_path=table_path) + a_band = Passband(survey, band_label, table_path=table_path, wave_grid=100.0) # Define some mock flux values and calculate our expected bandflux flux = np.array( @@ -196,11 +205,11 @@ def test_passband_fluxes_to_bandflux(tmp_path): ] ) expected_in_band_flux = np.trapz( - flux * a_band.normalized_transmission_table[:, 1], x=a_band.normalized_transmission_table[:, 0] + flux * a_band.processed_transmission_table[:, 1], x=a_band.processed_transmission_table[:, 0] ) # Compare results - in_band_flux = a_band.fluxes_to_bandflux(flux, a_band.normalized_transmission_table[:, 0]) + in_band_flux = a_band.fluxes_to_bandflux(flux, a_band.processed_transmission_table[:, 0]) np.allclose(in_band_flux, expected_in_band_flux) @@ -225,7 +234,9 @@ def test_passband_group_fluxes_to_bandfluxes(tmp_path): # Load the PassbandGroup object passbands = [] for band_label in band_labels: - passbands.append(Passband(survey, band_label, table_path=table_dir / f"{band_label}.dat")) + passbands.append( + Passband(survey, band_label, table_path=table_dir / f"{band_label}.dat", wave_grid=100.0) + ) test_passband_group = PassbandGroup(passbands=passbands) # Define some mock flux values and calculate our expected bandfluxes @@ -238,18 +249,23 @@ def test_passband_group_fluxes_to_bandfluxes(tmp_path): [1.0, 1.0, 1.0], ] ) - wavelengths = np.array([100, 200, 300]) + flux_wavelengths = np.array([100, 200, 300]) # Compare results - bandfluxes = test_passband_group.fluxes_to_bandfluxes(flux, wavelengths) + bandfluxes = test_passband_group.fluxes_to_bandfluxes(flux, flux_wavelengths) for label in test_passband_group.passbands: assert label in bandfluxes assert bandfluxes[label].shape == (5,) assert np.allclose( bandfluxes[label], np.trapz( - flux * test_passband_group.passbands[label].normalized_transmission_table[:, 1], - x=wavelengths, + flux * test_passband_group.passbands[label].processed_transmission_table[:, 1], + x=flux_wavelengths, axis=1, ), ) + + +def test_passbandgroup_set_wave_grids(tmp_path): + """TODO""" + pass From e7082d351aba083c0aeccc8f1083b711714de61e Mon Sep 17 00:00:00 2001 From: Olivia Lynn Date: Thu, 5 Sep 2024 19:48:05 -0400 Subject: [PATCH 13/38] Remove default spline-value-extrapolation; replace CublicSpline w/ InterpolatedUnivariateSpline; add option for extrapolation modes; increase unit test coverage --- src/tdastro/astro_utils/passbands.py | 47 ++++---- tests/tdastro/astro_utils/test_passbands.py | 119 ++++++++++++++++++-- 2 files changed, 137 insertions(+), 29 deletions(-) diff --git a/src/tdastro/astro_utils/passbands.py b/src/tdastro/astro_utils/passbands.py index 4b8d4be0..d2f4cdaa 100644 --- a/src/tdastro/astro_utils/passbands.py +++ b/src/tdastro/astro_utils/passbands.py @@ -6,7 +6,6 @@ import numpy as np import scipy.integrate -from scipy.interpolate import CubicSpline from tdastro.astro_utils import interpolation @@ -163,24 +162,18 @@ def set_wave_grid(self, wave_grid: np.ndarray | float | None, bounds=None) -> No maximum wavelengths in the transmission table. """ self.wave_grid = wave_grid - print(f"SET WAVE GRID: {self.wave_grid}") if bounds is None and self.processed_transmission_table is None: raise ValueError("Wave grid bounds must be provided if transmission table is not loaded.") elif bounds is None: bounds = (self.processed_transmission_table[0, 0], self.processed_transmission_table[-1, 0]) - print(f"BOUNDS: {bounds}") - # TODO should this check: # 1. the bounds are within the transmission table # 2. if the wave_grid was given as an array, but bounds were also given, that they match if isinstance(self.wave_grid, (float, int)): self.wave_grid = interpolation.create_grid(bounds, self.wave_grid) - print(f" TO ARRAY: {self.wave_grid}") - - print(f" WAVEGRID: {self.wave_grid} (type: {type(self.wave_grid)})") def _get_transmission_table(self) -> np.ndarray: # Check if the table file exists locally, and download it if it doesn't @@ -242,9 +235,6 @@ def _load_transmission_table(self) -> np.ndarray: # Load the table file loaded_table = np.loadtxt(self.table_path) - with np.printoptions(precision=3, suppress=True): - print(f"LOADED TABLE:\n{loaded_table}") - # Check that the table has the correct shape if loaded_table.shape[1] != 2: raise ValueError("Transmission table must have exactly 2 columns.") @@ -343,7 +333,9 @@ def set_transmission_table_to_new_grid(self, new_wave_grid) -> None: loaded_table = self._load_transmission_table() self.processed_transmission_table = self._process_transmission_table(loaded_table) - def _interpolate_flux_densities(self, _flux_density_matrix, _flux_wavelengths) -> tuple: + def _interpolate_flux_densities( + self, _flux_density_matrix, _flux_wavelengths, extrapolate="raise" + ) -> tuple: """Interpolate the flux density matrix to match the transmission table, which matches self.wave_grid. Parameters @@ -352,6 +344,11 @@ def _interpolate_flux_densities(self, _flux_density_matrix, _flux_wavelengths) - A 2D array of flux densities where rows are times and columns are wavelengths. _flux_wavelengths : np.ndarray An array of wavelengths in Angstroms corresponding to the columns of _flux_density_matrix. + extrapolate : str, optional + The method of extrapolation to use, passed to scipy.interpolate.InterpolatedUnivariateSpline. + Default is "raise", which will raise a ValueError if the interpolation goes out of bounds. Other + options are "constant" (pads with boundary value), "zeros" (pads with 0), and "extrapolate" (uses + spline extrapolation; not recommended). Returns ------- @@ -372,20 +369,24 @@ def _interpolate_flux_densities(self, _flux_density_matrix, _flux_wavelengths) - self.wave_grid = interpolation.create_grid( self.processed_transmission_table[:, 0], np.diff(_flux_wavelengths)[0] ) - elif type(self.wave_grid) == float: + elif isinstance(self.wave_grid, float): self.wave_grid = interpolation.create_grid( self.processed_transmission_table[:, 0], self.wave_grid ) # Interpolate the flux density matrix if not np.array_equal(_flux_wavelengths, self.wave_grid): - interpolated_flux_density_matrix = [] - for row in _flux_density_matrix: - flux_density_spline = CubicSpline( - _flux_wavelengths, row, bc_type="not-a-knot", extrapolate=True + # Initialize an array to store interpolated flux densities + interpolated_flux_density_matrix = np.empty((len(_flux_density_matrix), len(self.wave_grid))) + + # Interpolate each row individually + for i, row in enumerate(_flux_density_matrix): + interpolator = scipy.interpolate.InterpolatedUnivariateSpline( + _flux_wavelengths, row, ext=extrapolate ) - interpolated_flux_density_matrix.append(flux_density_spline(self.wave_grid)) - flux_density_matrix = np.array(interpolated_flux_density_matrix) + interpolated_flux_density_matrix[i, :] = interpolator(self.wave_grid) + + flux_density_matrix = interpolated_flux_density_matrix flux_wavelengths = self.wave_grid else: flux_density_matrix = _flux_density_matrix @@ -393,7 +394,7 @@ def _interpolate_flux_densities(self, _flux_density_matrix, _flux_wavelengths) - return (flux_density_matrix, flux_wavelengths) - def fluxes_to_bandflux(self, _flux_density_matrix, _flux_wavelengths) -> np.ndarray: + def fluxes_to_bandflux(self, _flux_density_matrix, _flux_wavelengths, extrapolate="raise") -> np.ndarray: """Calculate the bandflux for a given set of flux densities. This is eq. 7 from "On the Choice of LSST Flux Units" (Ivezić et al.): @@ -409,7 +410,11 @@ def fluxes_to_bandflux(self, _flux_density_matrix, _flux_wavelengths) -> np.ndar A 2D array of flux densities where rows are times and columns are wavelengths. flux_wavelengths : np.ndarray An array of wavelengths in Angstroms corresponding to the columns of flux_density_matrix. - + extrapolate : str, optional + The method of extrapolation to use, passed to scipy.interpolate.InterpolatedUnivariateSpline. + Default is "raise", which will raise a ValueError if the interpolation goes out of bounds. Other + options are "constant" (pads with boundary value), "zeros" (pads with 0), and "extrapolate" (uses + spline extrapolation; not recommended). Returns ------- np.ndarray @@ -417,7 +422,7 @@ def fluxes_to_bandflux(self, _flux_density_matrix, _flux_wavelengths) -> np.ndar """ # Interpolate flux density matrix to match the transmission table, which matches self.wave_grid flux_density_matrix, flux_wavelengths = self._interpolate_flux_densities( - _flux_density_matrix, _flux_wavelengths + _flux_density_matrix, _flux_wavelengths, extrapolate ) # Calculate the bandflux as ∫ f(λ)φ_b(λ) dλ, diff --git a/tests/tdastro/astro_utils/test_passbands.py b/tests/tdastro/astro_utils/test_passbands.py index 7700263b..6ba26452 100644 --- a/tests/tdastro/astro_utils/test_passbands.py +++ b/tests/tdastro/astro_utils/test_passbands.py @@ -1,6 +1,7 @@ from unittest.mock import patch import numpy as np +import pytest from tdastro.astro_utils.passbands import Passband, PassbandGroup @@ -176,9 +177,111 @@ def test_set_transmission_table_to_new_grid(tmp_path): pass -def test_passband_flux_interpolate_flux_densities(tmp_path): - """TODO""" - pass +def test_passband_interpolate_flux_densities_basic(tmp_path): # TODO break this into multiple functions + """Test the _interpolate_flux_densities method of the Passband class. Make sure values are interpolated as + expected.""" + # Initialize a Passband object + survey = "TEST" + band_label = "a" + table_path = tmp_path / f"{survey}_{band_label}.dat" + + transmission_table = "100 0.5\n200 0.75\n300 0.25\n400 0.5\n500 0.25\n600 0.5" + with open(table_path, "w") as f: + f.write(transmission_table) + + # Test interpolation is skipped when not needed + a_band = Passband(survey, band_label, table_path=table_path, wave_grid=100.0) + fluxes = np.array([[0.25, 0.5, 1.0, 1.0, 0.5, 0.25]]) + flux_wavelengths = np.array([100.0, 200.0, 300.0, 400.0, 500.0, 600.0]) + (result_fluxes, result_wavelengths) = a_band._interpolate_flux_densities(fluxes, flux_wavelengths) + np.testing.assert_allclose(result_fluxes, fluxes) + np.testing.assert_allclose(result_wavelengths, flux_wavelengths) + + # Test interpolation when fluxes span entire band + b_band = Passband(survey, band_label, table_path=table_path, wave_grid=50.0) + fluxes = np.array([[0.25, 0.5, 1.0, 1.0, 0.5, 0.25], [0.25, 0.5, 1.0, 1.0, 0.5, 0.25]]) + flux_wavelengths = np.array([100.0, 200.0, 300.0, 400.0, 500.0, 600.0]) + (result_fluxes, result_wavelengths) = b_band._interpolate_flux_densities(fluxes, flux_wavelengths) + + # Check wavelengths + expected_waves = np.arange(100, 601, 50) + np.testing.assert_allclose(result_wavelengths, expected_waves) + + # Check the interpolated fluxes, while being somewhat agnostic to the specific method of interpolation + assert result_fluxes.shape == (2, 11) + # Ends should be 0.25 + assert result_fluxes[0, 0] == 0.25 + assert result_fluxes[0, 10] == 0.25 + # First half of array should be increasing + assert np.all(np.diff(result_fluxes[0, :6]) > 0) + # Second half of array should be decreasing + assert np.all(np.diff(result_fluxes[0, 5:]) < 0) + + +def test_passband_interpolate_flux_densities_mismatched_bounds( + tmp_path, +): # TODO break this into multiple functions + """Test the _interpolate_flux_densities method of the Passband class. Make sure values are interpolated as + expected, out-of-bounds values are handled correctly, and padding is creating when needed.""" + # Initialize a Passband object + survey = "TEST" + band_label = "a" + table_path = tmp_path / f"{survey}_{band_label}.dat" + + transmission_table = "100 0.5\n200 0.75\n300 0.25\n400 0.5\n500 0.25\n600 0.5" + with open(table_path, "w") as f: + f.write(transmission_table) + + # Test interpolation when fluxes are out of bounds + a_band = Passband(survey, band_label, table_path=table_path, wave_grid=100.0) + fluxes = np.array([[0.25, 0.5, 1.0, 1.0, 0.5, 0.25]]) + flux_wavelengths = np.array([50.0, 100.0, 200.0, 300.0, 400.0, 500.0, 600.0, 650.0]) + with pytest.raises(ValueError): + a_band._interpolate_flux_densities(fluxes, flux_wavelengths, "raise") + + # Test padding (with no interpolation) when fluxes do not span the entire band (extrapolation="zeros") + b_band = Passband(survey, band_label, table_path=table_path, wave_grid=100.0) + fluxes = np.array([[0.5, 1.0, 0.5, 0.25], [0.5, 1.0, 0.5, 0.25]]) + flux_wavelengths = np.array([200.0, 300.0, 400.0, 500.0]) + (result_fluxes, result_wavelengths) = b_band._interpolate_flux_densities( + fluxes, flux_wavelengths, "zeros" + ) + expected_fluxes = np.array([[0.0, 0.5, 1.0, 0.5, 0.25, 0.0], [0.0, 0.5, 1.0, 0.5, 0.25, 0.0]]) + expected_waves = np.array([100, 200, 300, 400, 500, 600]) + np.testing.assert_allclose(result_fluxes, expected_fluxes) + np.testing.assert_allclose(result_wavelengths, expected_waves) + + # Test interpolation and padding when fluxes do not span the entire band + d_band = Passband(survey, band_label, table_path=table_path, wave_grid=50.0) + fluxes = np.array([[0.25, 0.75, 1.0, 0.25]]) + flux_wavelengths = np.array([200.0, 300.0, 400.0, 500.0]) + (result_fluxes, result_wavelengths) = d_band._interpolate_flux_densities( + fluxes, flux_wavelengths, "zeros" + ) + expected_waves = np.arange(100, 601, 50) + np.testing.assert_allclose(result_wavelengths, expected_waves) + assert result_fluxes.shape == (1, 11) + # Check zero-padding + assert np.isclose(result_fluxes[0, 0], 0.0) + assert np.isclose(result_fluxes[0, 1], 0.0) + assert np.isclose(result_fluxes[0, 9], 0.0) + assert np.isclose(result_fluxes[0, 10], 0.0) + # Check the ends of the given fluxes are preserved + assert np.isclose(result_fluxes[0, 2], 0.25) + assert np.isclose(result_fluxes[0, 8], 0.25) + # Check the increasing section (originally indices [0, 2]) is still increasing (now indices [2, 6]) + assert np.all(np.diff(result_fluxes[0, 2:6]) > 0) + # Check the decreasing section (originally indices [2, 3]) is still decreasing (now indices [6, 8]) + assert np.all(np.diff(result_fluxes[0, 6:8]) < 0) + + # Test interpolation when fluxes are out of bounds + e_band = Passband(survey, band_label, table_path=table_path, wave_grid=100.0) + fluxes = np.array([[0.25, 0.5, 1.0, 1.5, 1.5, 1.0, 0.5, 0.25]]) + flux_wavelengths = np.array([50.0, 100.0, 200.0, 300.0, 400.0, 500.0, 600.0, 650.0]) + (result_fluxes, result_wavelengths) = e_band._interpolate_flux_densities(fluxes, flux_wavelengths) + expected_waves = np.arange(100, 601, 100) + np.testing.assert_allclose(result_wavelengths, expected_waves) + np.testing.assert_allclose(result_fluxes, fluxes[:, 1:7]) def test_passband_fluxes_to_bandflux(tmp_path): @@ -253,13 +356,13 @@ def test_passband_group_fluxes_to_bandfluxes(tmp_path): # Compare results bandfluxes = test_passband_group.fluxes_to_bandfluxes(flux, flux_wavelengths) - for label in test_passband_group.passbands: - assert label in bandfluxes - assert bandfluxes[label].shape == (5,) + for band_name in test_passband_group.passbands: + assert band_name in bandfluxes + assert bandfluxes[band_name].shape == (5,) assert np.allclose( - bandfluxes[label], + bandfluxes[band_name], np.trapz( - flux * test_passband_group.passbands[label].processed_transmission_table[:, 1], + flux * test_passband_group.passbands[band_name].processed_transmission_table[:, 1], x=flux_wavelengths, axis=1, ), From b18cd637f8ae5096c4a8feaab24ed01f357df75f Mon Sep 17 00:00:00 2001 From: Olivia Lynn Date: Thu, 5 Sep 2024 20:12:07 -0400 Subject: [PATCH 14/38] Unit tests for all extrapolation modes; Remove mention of "extrapolation" option for ext parameter as it is not recommended --- src/tdastro/astro_utils/passbands.py | 6 ++--- tests/tdastro/astro_utils/test_passbands.py | 29 +++++++++++++++------ 2 files changed, 24 insertions(+), 11 deletions(-) diff --git a/src/tdastro/astro_utils/passbands.py b/src/tdastro/astro_utils/passbands.py index d2f4cdaa..e12a2236 100644 --- a/src/tdastro/astro_utils/passbands.py +++ b/src/tdastro/astro_utils/passbands.py @@ -335,7 +335,7 @@ def set_transmission_table_to_new_grid(self, new_wave_grid) -> None: def _interpolate_flux_densities( self, _flux_density_matrix, _flux_wavelengths, extrapolate="raise" - ) -> tuple: + ) -> tuple: # TODO maybe move this to interpolation.py? """Interpolate the flux density matrix to match the transmission table, which matches self.wave_grid. Parameters @@ -347,7 +347,7 @@ def _interpolate_flux_densities( extrapolate : str, optional The method of extrapolation to use, passed to scipy.interpolate.InterpolatedUnivariateSpline. Default is "raise", which will raise a ValueError if the interpolation goes out of bounds. Other - options are "constant" (pads with boundary value), "zeros" (pads with 0), and "extrapolate" (uses + options are "const" (pads with boundary value), "zeros" (pads with 0), and "extrapolate" (uses spline extrapolation; not recommended). Returns @@ -413,7 +413,7 @@ def fluxes_to_bandflux(self, _flux_density_matrix, _flux_wavelengths, extrapolat extrapolate : str, optional The method of extrapolation to use, passed to scipy.interpolate.InterpolatedUnivariateSpline. Default is "raise", which will raise a ValueError if the interpolation goes out of bounds. Other - options are "constant" (pads with boundary value), "zeros" (pads with 0), and "extrapolate" (uses + options are "const" (pads with boundary value), "zeros" (pads with 0), and "extrapolate" (uses spline extrapolation; not recommended). Returns ------- diff --git a/tests/tdastro/astro_utils/test_passbands.py b/tests/tdastro/astro_utils/test_passbands.py index 6ba26452..76488b67 100644 --- a/tests/tdastro/astro_utils/test_passbands.py +++ b/tests/tdastro/astro_utils/test_passbands.py @@ -177,7 +177,7 @@ def test_set_transmission_table_to_new_grid(tmp_path): pass -def test_passband_interpolate_flux_densities_basic(tmp_path): # TODO break this into multiple functions +def test_passband_interpolate_flux_densities_basic(tmp_path): """Test the _interpolate_flux_densities method of the Passband class. Make sure values are interpolated as expected.""" # Initialize a Passband object @@ -220,7 +220,7 @@ def test_passband_interpolate_flux_densities_basic(tmp_path): # TODO break this def test_passband_interpolate_flux_densities_mismatched_bounds( tmp_path, -): # TODO break this into multiple functions +): """Test the _interpolate_flux_densities method of the Passband class. Make sure values are interpolated as expected, out-of-bounds values are handled correctly, and padding is creating when needed.""" # Initialize a Passband object @@ -236,14 +236,18 @@ def test_passband_interpolate_flux_densities_mismatched_bounds( a_band = Passband(survey, band_label, table_path=table_path, wave_grid=100.0) fluxes = np.array([[0.25, 0.5, 1.0, 1.0, 0.5, 0.25]]) flux_wavelengths = np.array([50.0, 100.0, 200.0, 300.0, 400.0, 500.0, 600.0, 650.0]) - with pytest.raises(ValueError): - a_band._interpolate_flux_densities(fluxes, flux_wavelengths, "raise") - # Test padding (with no interpolation) when fluxes do not span the entire band (extrapolation="zeros") - b_band = Passband(survey, band_label, table_path=table_path, wave_grid=100.0) + # Test padding (with no interpolation) when fluxes do not span the entire band + a_band = Passband(survey, band_label, table_path=table_path, wave_grid=100.0) fluxes = np.array([[0.5, 1.0, 0.5, 0.25], [0.5, 1.0, 0.5, 0.25]]) flux_wavelengths = np.array([200.0, 300.0, 400.0, 500.0]) - (result_fluxes, result_wavelengths) = b_band._interpolate_flux_densities( + + # Case 1: with extrapolation="raise" + with pytest.raises(ValueError): + a_band._interpolate_flux_densities(fluxes, flux_wavelengths, "raise") + + # Case 2: with extrapolation="zeros" + (result_fluxes, result_wavelengths) = a_band._interpolate_flux_densities( fluxes, flux_wavelengths, "zeros" ) expected_fluxes = np.array([[0.0, 0.5, 1.0, 0.5, 0.25, 0.0], [0.0, 0.5, 1.0, 0.5, 0.25, 0.0]]) @@ -251,6 +255,15 @@ def test_passband_interpolate_flux_densities_mismatched_bounds( np.testing.assert_allclose(result_fluxes, expected_fluxes) np.testing.assert_allclose(result_wavelengths, expected_waves) + # Case 3: with extrapolation="constant" + (result_fluxes, result_wavelengths) = a_band._interpolate_flux_densities( + fluxes, flux_wavelengths, "const" + ) + expected_fluxes = np.array([[0.5, 0.5, 1.0, 0.5, 0.25, 0.25], [0.5, 0.5, 1.0, 0.5, 0.25, 0.25]]) + expected_waves = np.array([100, 200, 300, 400, 500, 600]) + np.testing.assert_allclose(result_fluxes, expected_fluxes) + np.testing.assert_allclose(result_wavelengths, expected_waves) + # Test interpolation and padding when fluxes do not span the entire band d_band = Passband(survey, band_label, table_path=table_path, wave_grid=50.0) fluxes = np.array([[0.25, 0.75, 1.0, 0.25]]) @@ -274,7 +287,7 @@ def test_passband_interpolate_flux_densities_mismatched_bounds( # Check the decreasing section (originally indices [2, 3]) is still decreasing (now indices [6, 8]) assert np.all(np.diff(result_fluxes[0, 6:8]) < 0) - # Test interpolation when fluxes are out of bounds + # Test handling when fluxes are out of bounds e_band = Passband(survey, band_label, table_path=table_path, wave_grid=100.0) fluxes = np.array([[0.25, 0.5, 1.0, 1.5, 1.5, 1.0, 0.5, 0.25]]) flux_wavelengths = np.array([50.0, 100.0, 200.0, 300.0, 400.0, 500.0, 600.0, 650.0]) From cabaf43ff6dae9a029d29702c2bd4d27eb6b7c0d Mon Sep 17 00:00:00 2001 From: Olivia Lynn Date: Thu, 5 Sep 2024 22:07:10 -0400 Subject: [PATCH 15/38] Decouple wave_grid and transmission table logic --- src/tdastro/astro_utils/passbands.py | 166 ++++++++------------ tests/tdastro/astro_utils/test_passbands.py | 71 ++++++++- 2 files changed, 133 insertions(+), 104 deletions(-) diff --git a/src/tdastro/astro_utils/passbands.py b/src/tdastro/astro_utils/passbands.py index e12a2236..40253e5d 100644 --- a/src/tdastro/astro_utils/passbands.py +++ b/src/tdastro/astro_utils/passbands.py @@ -68,7 +68,7 @@ def _load_preset(self, preset): else: raise ValueError(f"Unknown passband preset: {preset}") - def set_wave_grids(self, wave_grids: dict) -> None: + def set_transmission_table_grids(self, wave_grids: dict) -> None: """Set the wave grid attribute for all passbands in the group. Parameters @@ -77,7 +77,7 @@ def set_wave_grids(self, wave_grids: dict) -> None: A dictionary of passband labels and wave grids. """ for label, wave_grid in wave_grids.items(): - self.passbands[label].set_wave_grid(wave_grid) + self.passbands[label].set_transmission_table_grid(wave_grid) def fluxes_to_bandfluxes(self, flux_density_matrix, flux_wavelengths) -> np.ndarray: """Calculate bandfluxes for all passbands in the group. @@ -137,45 +137,23 @@ def __init__(self, survey, label, wave_grid=5.0, table_path=None, table_url=""): self.table_path = table_path self.table_url = table_url - loaded_table = self._get_transmission_table() - self.set_wave_grid(wave_grid, bounds=(loaded_table[0, 0], loaded_table[-1, 0])) - - self.processed_transmission_table = self._process_transmission_table(loaded_table) + self._load_transmission_table() + self._set_wave_grid_attr(wave_grid) + self._process_transmission_table() def __str__(self) -> str: """Return a string representation of the Passband.""" return f"Passband: {self.full_name}" - def set_wave_grid(self, wave_grid: np.ndarray | float | None, bounds=None) -> None: - """Set the wave grid attribute, which is used for interpolation. + def _load_transmission_table(self) -> np.ndarray: + """Load a transmission table from a file (or download it if it doesn't exist). - Parameters - ---------- - wave_grid : np.ndarray | float | None - The grid of wavelengths (Angstrom) to which the flux density matrix and transmission table should - be interpolated. A float will be converted to a numpy array with a grid step matching the - boundaries of the transmission table. If None, the transmission table will later be interpolated - to a grid maintaining the same boundaries, but matching the step of the flux density matrix. - bounds : tuple, optional - The lower and upper bounds of the grid. If None, the bounds will be set to the minimum and - maximum wavelengths in the transmission table. + Returns + ------- + np.ndarray + A 2D array of wavelengths and transmissions. """ - self.wave_grid = wave_grid - - if bounds is None and self.processed_transmission_table is None: - raise ValueError("Wave grid bounds must be provided if transmission table is not loaded.") - elif bounds is None: - bounds = (self.processed_transmission_table[0, 0], self.processed_transmission_table[-1, 0]) - - # TODO should this check: - # 1. the bounds are within the transmission table - # 2. if the wave_grid was given as an array, but bounds were also given, that they match - - if isinstance(self.wave_grid, (float, int)): - self.wave_grid = interpolation.create_grid(bounds, self.wave_grid) - - def _get_transmission_table(self) -> np.ndarray: # Check if the table file exists locally, and download it if it doesn't if self.table_path is None: self.table_path = os.path.join( @@ -185,8 +163,18 @@ def _get_transmission_table(self) -> np.ndarray: if not os.path.exists(self.table_path): self._download_transmission_table() - # Load the table - return self._load_transmission_table() + # Load the table file + loaded_table = np.loadtxt(self.table_path) + + # Check that the table has the correct shape + if loaded_table.shape[1] != 2: + raise ValueError("Transmission table must have exactly 2 columns.") + + # Check that wavelengths are strictly increasing + if not np.all(np.diff(loaded_table[:, 0]) > 0): + raise ValueError("Wavelengths in transmission table must be strictly increasing.") + + self._loaded_table = loaded_table def _download_transmission_table(self) -> bool: """Download a transmission table from a URL. @@ -224,50 +212,56 @@ def _download_transmission_table(self) -> bool: logging.error(f"URL error occurred when downloading table for {self.full_name}: {e}") return False - def _load_transmission_table(self) -> np.ndarray: - """Load a transmission table from a file. + def _set_wave_grid_attr(self, wave_grid: np.ndarray | float | None) -> None: + """Set the wave grid attribute. Note: only sets the attribute; does NOT process transmission table. - Returns - ------- - np.ndarray - A 2D array of wavelengths and transmissions. + Used to keep the type of wave_grid attribute as an array, even when set with a float. + + Parameters + ---------- + wave_grid : np.ndarray | float | None + The grid of wavelengths (Angstrom) to which the flux density matrix and transmission table should + be interpolated. A float will be converted to a numpy array with a grid step matching the + boundaries of the transmission table. If None, the transmission table will later be interpolated + to a grid maintaining the same boundaries, but matching the step of the flux density matrix. """ - # Load the table file - loaded_table = np.loadtxt(self.table_path) + self.wave_grid = wave_grid - # Check that the table has the correct shape - if loaded_table.shape[1] != 2: - raise ValueError("Transmission table must have exactly 2 columns.") + if isinstance(self.wave_grid, (float, int)): + if self._loaded_table is None: + raise ValueError( + "Transmission table must be loaded before setting wave grid with an integer or float." + ) + self.wave_grid = interpolation.create_grid(self._loaded_table[:, 0], self.wave_grid) - # Check that wavelengths are strictly increasing - if not np.all(np.diff(loaded_table[:, 0]) > 0): - raise ValueError("Wavelengths in transmission table must be strictly increasing.") + def set_transmission_table_grid(self, new_wave_grid) -> None: + """Updates wave_grid attr and sets the transmission table to the new grid. - return loaded_table + Parameters + ---------- + new_wave_grid : np.ndarray | float | None + The grid of wavelengths (Angstrom) to which the flux density matrix and transmission table should + be interpolated. A float will be converted to a numpy array with a grid step matching the + boundaries of the transmission table. If None, the transmission table will later be interpolated + to a grid maintaining the same boundaries, but matching the step of the flux density matrix. + """ + self._set_wave_grid_attr(new_wave_grid) + self._process_transmission_table() - def _process_transmission_table(self, loaded_table) -> np.ndarray: - """Process the transmission table: downsample or interpolate, then normalize. + def _process_transmission_table(self) -> np.ndarray: + """Process the transmission table: downsample or interpolate, then normalize.""" + interpolated_transmissions = self._interpolate_or_downsample_transmission_table(self._loaded_table) + normalized_transmissions = self._normalize_interpolated_transmission_table(interpolated_transmissions) + self.processed_transmission_table = normalized_transmissions + + def _interpolate_or_downsample_transmission_table(self, transmission_table) -> np.ndarray: + """Interpolate or downsample a transmission table to a desired grid. Parameters ---------- - loaded_table : np.ndarray + transmission_table : np.ndarray A 2D array of wavelengths and transmissions. - Returns - ------- - np.ndarray - A 2D array of wavelengths and normalized transmissions. - """ - interpolated_transmissions = self._interpolate_or_downsample_transmission_table(loaded_table) - normalized_transmissions = self._normalize_transmission_table(interpolated_transmissions) - # with np.printoptions(precision=3, suppress=True): - # print(f"INTERPOLATED TRANSMISSIONS: {interpolated_transmissions}") - # print(f"NORMALIZED TRANSMISSIONS: {normalized_transmissions}") - return normalized_transmissions - - def _interpolate_or_downsample_transmission_table(self, loaded_table) -> np.ndarray: - """Interpolate or downsample a transmission table to a desired grid. - Returns ------- np.ndarray @@ -275,13 +269,13 @@ def _interpolate_or_downsample_transmission_table(self, loaded_table) -> np.ndar """ if self.wave_grid is not None: if type(self.wave_grid) == float: - self.wave_grid = interpolation.create_grid(loaded_table[:, 0], self.wave_grid) + self.wave_grid = interpolation.create_grid(transmission_table[:, 0], self.wave_grid) interpolated_transmissions = interpolation.interpolate_transmission_table( - loaded_table, self.wave_grid + transmission_table, self.wave_grid ) return interpolated_transmissions - def _normalize_transmission_table(self, transmission_table) -> np.ndarray: + def _normalize_interpolated_transmission_table(self, transmission_table) -> np.ndarray: """Calculate the value of phi_b for all wavelengths in a transmission table. This is eq. 8 from "On the Choice of LSST Flux Units" (Ivezić et al.): @@ -309,30 +303,6 @@ def _normalize_transmission_table(self, transmission_table) -> np.ndarray: normalized_transmissions = numerators / denominator return np.column_stack((wavelengths_angstrom, normalized_transmissions)) - def set_transmission_table_to_new_grid(self, new_wave_grid) -> None: - """Set the transmission table to a new grid. - - A public wrapper for _process_transmission_table, first setting the wave grid and loading the - unprocessed transmission table. - - Parameters - ---------- - new_wave_grid : np.ndarray | float | None - The grid of wavelengths (Angstrom) to which the flux density matrix and transmission table should - be interpolated. A float will be converted to a numpy array with a grid step matching the - boundaries of the transmission table. If None, the transmission table will later be interpolated - to a grid maintaining the same boundaries, but matching the step of the flux density matrix. - """ - self.wave_grid = new_wave_grid - - if self.wave_grid is None: - return - - self.wave_grid = interpolation.create_grid(self.processed_transmission_table[:, 0], new_wave_grid) - - loaded_table = self._load_transmission_table() - self.processed_transmission_table = self._process_transmission_table(loaded_table) - def _interpolate_flux_densities( self, _flux_density_matrix, _flux_wavelengths, extrapolate="raise" ) -> tuple: # TODO maybe move this to interpolation.py? @@ -347,8 +317,7 @@ def _interpolate_flux_densities( extrapolate : str, optional The method of extrapolation to use, passed to scipy.interpolate.InterpolatedUnivariateSpline. Default is "raise", which will raise a ValueError if the interpolation goes out of bounds. Other - options are "const" (pads with boundary value), "zeros" (pads with 0), and "extrapolate" (uses - spline extrapolation; not recommended). + options are "const" (pads with boundary value) and "zeros" (pads with 0). Returns ------- @@ -413,8 +382,7 @@ def fluxes_to_bandflux(self, _flux_density_matrix, _flux_wavelengths, extrapolat extrapolate : str, optional The method of extrapolation to use, passed to scipy.interpolate.InterpolatedUnivariateSpline. Default is "raise", which will raise a ValueError if the interpolation goes out of bounds. Other - options are "const" (pads with boundary value), "zeros" (pads with 0), and "extrapolate" (uses - spline extrapolation; not recommended). + options are "const" (pads with boundary value) and "zeros" (pads with 0). Returns ------- np.ndarray diff --git a/tests/tdastro/astro_utils/test_passbands.py b/tests/tdastro/astro_utils/test_passbands.py index 76488b67..f6e059cb 100644 --- a/tests/tdastro/astro_utils/test_passbands.py +++ b/tests/tdastro/astro_utils/test_passbands.py @@ -154,8 +154,8 @@ def test_passband_interpolate_or_downsample_transmission_table(tmp_path): pass -def test_passband_normalize_transmission_table(tmp_path): - """Test the _normalize_transmission_table method of the Passband class.""" +def test_passband_normalize_interpolated_transmission_table(tmp_path): + """Test the _normalize_interpolated_transmission_table method of the Passband class.""" # Initialize a Passband object survey = "TEST" band_label = "a" @@ -382,6 +382,67 @@ def test_passband_group_fluxes_to_bandfluxes(tmp_path): ) -def test_passbandgroup_set_wave_grids(tmp_path): - """TODO""" - pass +def test_passbandgroup_set_transmission_table_grids(tmp_path): + """Test the set_wave_grid_att method of the PassbandGroup class. Note this""" + # Initialize a Passband object + survey = "TEST" + band_label = "a" + table_path = tmp_path / f"{survey}_{band_label}.dat" + + transmission_table = "100 0.5\n200 0.75\n300 0.25\n400 0.5\n500 0.25\n600 0.5" + with open(table_path, "w") as f: + f.write(transmission_table) + + # TODO update to match set_transmission_table_grids + + # # Test interpolation is skipped when not needed + # a_band = Passband(survey, band_label, table_path=table_path, wave_grid=100.0) + # np.testing.assert_allclose(a_band.wave_grid, np.array([100.0, 200.0, 300.0, 400.0, 500.0, 600.0])) + # np.testing.assert_allclose( + # a_band.processed_transmission_table[:, 0], + # np.array([100.0, 200.0, 300.0, 400.0, 500.0, 600.0]), + # ) + + # # Test that grid is reset successfully (but the transmission table is not yet interpolated) + # a_band._set_wave_grid_attr(50.0) + # np.testing.assert_allclose(a_band.wave_grid, np.arange(100.0, 601.0, 50.0)) + # np.testing.assert_allclose( + # a_band.processed_transmission_table[:, 0], + # np.array([100.0, 200.0, 300.0, 400.0, 500.0, 600.0]), + # ) + + # # Test we can handle a list as input + # a_band._set_wave_grid_attr([100, 200, 300, 400, 500, 600]) + # np.testing.assert_allclose(a_band.wave_grid, np.array([100.0, 200.0, 300.0, 400.0, 500.0, 600.0])) + + # # Test we can handle an int as input + # a_band._set_wave_grid_attr(50) + # np.testing.assert_allclose(a_band.wave_grid, np.arange(100.0, 601.0, 50.0)) + + +def test_passbandgroup_sreset_transmission_table_grid(tmp_path): + """Test the set_transmission_table_to_new_grid method of the PassbandGroup class.""" + # Initialize a Passband object + survey = "TEST" + band_label = "a" + table_path = tmp_path / f"{survey}_{band_label}.dat" + + transmission_table = "100 0.5\n200 0.75\n300 0.25\n400 0.5\n500 0.25\n600 0.5" + with open(table_path, "w") as f: + f.write(transmission_table) + + # Test interpolation is skipped when not needed + a_band = Passband(survey, band_label, table_path=table_path, wave_grid=100.0) + np.testing.assert_allclose(a_band.wave_grid, np.array([100.0, 200.0, 300.0, 400.0, 500.0, 600.0])) + np.testing.assert_allclose( + a_band.processed_transmission_table[:, 0], + np.array([100.0, 200.0, 300.0, 400.0, 500.0, 600.0]), + ) + + # Test that grid is reset successfully AND we have interpolated the transmission table as well + a_band.set_transmission_table_grid(50.0) + np.testing.assert_allclose(a_band.wave_grid, np.arange(100.0, 601.0, 50.0)) + np.testing.assert_allclose( + a_band.processed_transmission_table[:, 0], + np.array([100.0, 150.0, 200.0, 250.0, 300.0, 350.0, 400.0, 450.0, 500.0, 550.0, 600.0]), + ) From f536391cf438a2fb71f0ffc32b44f07f2f314fb7 Mon Sep 17 00:00:00 2001 From: Olivia Lynn Date: Fri, 6 Sep 2024 00:33:00 -0400 Subject: [PATCH 16/38] Expand unit test coverage --- src/tdastro/astro_utils/passbands.py | 30 +++-- tests/tdastro/astro_utils/test_passbands.py | 136 +++++++++++++------- 2 files changed, 105 insertions(+), 61 deletions(-) diff --git a/src/tdastro/astro_utils/passbands.py b/src/tdastro/astro_utils/passbands.py index 40253e5d..04e01033 100644 --- a/src/tdastro/astro_utils/passbands.py +++ b/src/tdastro/astro_utils/passbands.py @@ -68,16 +68,20 @@ def _load_preset(self, preset): else: raise ValueError(f"Unknown passband preset: {preset}") - def set_transmission_table_grids(self, wave_grids: dict) -> None: + def set_transmission_table_grids(self, wave_grid: float | int | None) -> None: """Set the wave grid attribute for all passbands in the group. Parameters ---------- - wave_grids : dict - A dictionary of passband labels and wave grids. + wave_grid : float | int | None + The grid of wavelengths (Angstrom) to which the flux density matrix and transmission table should + be interpolated. If a float or int is given, wave_grid will be converted to a numpy array with a + wave_grid step matching the boundaries of the transmission table. If None, the transmission table + will later be interpolated to a grid with the same boundaries, but matching the step of the flux + density matrix. """ - for label, wave_grid in wave_grids.items(): - self.passbands[label].set_transmission_table_grid(wave_grid) + for _, passband in self.passbands.items(): + passband.set_transmission_table_grid(wave_grid) def fluxes_to_bandfluxes(self, flux_density_matrix, flux_wavelengths) -> np.ndarray: """Calculate bandfluxes for all passbands in the group. @@ -98,8 +102,8 @@ def fluxes_to_bandfluxes(self, flux_density_matrix, flux_wavelengths) -> np.ndar A dictionary of bandfluxes with passband labels as keys. """ bandfluxes = {} - for label, passband in self.passbands.items(): - bandfluxes[label] = passband.fluxes_to_bandflux(flux_density_matrix, flux_wavelengths) + for name, passband in self.passbands.items(): + bandfluxes[name] = passband.fluxes_to_bandflux(flux_density_matrix, flux_wavelengths) return bandfluxes @@ -212,16 +216,16 @@ def _download_transmission_table(self) -> bool: logging.error(f"URL error occurred when downloading table for {self.full_name}: {e}") return False - def _set_wave_grid_attr(self, wave_grid: np.ndarray | float | None) -> None: + def _set_wave_grid_attr(self, wave_grid: np.ndarray | float | int | None) -> None: """Set the wave grid attribute. Note: only sets the attribute; does NOT process transmission table. Used to keep the type of wave_grid attribute as an array, even when set with a float. Parameters ---------- - wave_grid : np.ndarray | float | None + wave_grid : np.ndarray | float | int | None The grid of wavelengths (Angstrom) to which the flux density matrix and transmission table should - be interpolated. A float will be converted to a numpy array with a grid step matching the + be interpolated. A float or int will be converted to a numpy array with a grid step matching the boundaries of the transmission table. If None, the transmission table will later be interpolated to a grid maintaining the same boundaries, but matching the step of the flux density matrix. """ @@ -234,14 +238,14 @@ def _set_wave_grid_attr(self, wave_grid: np.ndarray | float | None) -> None: ) self.wave_grid = interpolation.create_grid(self._loaded_table[:, 0], self.wave_grid) - def set_transmission_table_grid(self, new_wave_grid) -> None: + def set_transmission_table_grid(self, new_wave_grid: np.ndarray | float | int | None) -> None: """Updates wave_grid attr and sets the transmission table to the new grid. Parameters ---------- - new_wave_grid : np.ndarray | float | None + new_wave_grid : np.ndarray | float | int | None The grid of wavelengths (Angstrom) to which the flux density matrix and transmission table should - be interpolated. A float will be converted to a numpy array with a grid step matching the + be interpolated. A float or int will be converted to a numpy array with a grid step matching the boundaries of the transmission table. If None, the transmission table will later be interpolated to a grid maintaining the same boundaries, but matching the step of the flux density matrix. """ diff --git a/tests/tdastro/astro_utils/test_passbands.py b/tests/tdastro/astro_utils/test_passbands.py index f6e059cb..5533198c 100644 --- a/tests/tdastro/astro_utils/test_passbands.py +++ b/tests/tdastro/astro_utils/test_passbands.py @@ -150,8 +150,28 @@ def mock_urlretrieve(url, filename, *args, **kwargs): # Urlretrieve saves conte def test_passband_interpolate_or_downsample_transmission_table(tmp_path): - """TODO""" - pass + """Test down-sampling and interpolation of the transmission table.""" + # Initialize a Passband object + survey = "TEST" + band_label = "a" + table_path = tmp_path / f"{survey}_{band_label}.dat" + + transmission_table = "100 0.5\n200 0.75\n300 0.25\n" + with open(table_path, "w") as f: + f.write(transmission_table) + + a_band = Passband(survey, band_label, table_path=table_path, wave_grid=100) + print(a_band.processed_transmission_table) + + # Downsample the transmission table + a_band._set_wave_grid_attr(200) + table = a_band._interpolate_or_downsample_transmission_table(a_band._loaded_table) + np.testing.assert_allclose(table[:, 0], [100, 300]) + + # Interpolate the transmission table + a_band._set_wave_grid_attr(50) + table = a_band._interpolate_or_downsample_transmission_table(a_band._loaded_table) + np.testing.assert_allclose(table[:, 0], np.arange(100, 301, 50)) def test_passband_normalize_interpolated_transmission_table(tmp_path): @@ -167,14 +187,44 @@ def test_passband_normalize_interpolated_transmission_table(tmp_path): a_band = Passband(survey, band_label, table_path=table_path, wave_grid=100) + # Normalize the transmission table (skipping interpolation as grid already matches) + a_band._normalize_interpolated_transmission_table(a_band._loaded_table) + # Compare results expected_result = np.array([[100.0, 0.0075], [200.0, 0.005625], [300.0, 0.00125]]) assert np.allclose(a_band.processed_transmission_table, expected_result) + # TODO add edge cases + + +def test_passband_process_transmission_table(tmp_path): + """Test the _process_transmission_table method of the Passband class: correct methods are called.""" + + # Initialize a Passband object + survey = "TEST" + band_label = "a" + table_path = tmp_path / f"{survey}_{band_label}.dat" + + transmission_table = "100 0.5\n200 0.75\n300 0.25\n" + with open(table_path, "w") as f: + f.write(transmission_table) + + a_band = Passband(survey, band_label, table_path=table_path, wave_grid=100) + + # Mock the methods that _process_transmission_table wraps + with patch.object( + a_band, "_interpolate_or_downsample_transmission_table" + ) as mock_interp_table, patch.object( + a_band, "_normalize_interpolated_transmission_table" + ) as mock_norm_table: + # Call the _process_transmission_table method + a_band._process_transmission_table() -def test_set_transmission_table_to_new_grid(tmp_path): - """TODO""" - pass + # Check that each method is called once with the correct arguments + mock_interp_table.assert_called_once_with(a_band._loaded_table) + mock_norm_table.assert_called_once() + + # TODO edge cases? def test_passband_interpolate_flux_densities_basic(tmp_path): @@ -329,12 +379,12 @@ def test_passband_fluxes_to_bandflux(tmp_path): np.allclose(in_band_flux, expected_in_band_flux) -def test_passband_group_fluxes_to_bandfluxes(tmp_path): - """Test the fluxes_to_bandfluxes method of the PassbandGroup class.""" +def make_passband_group(path): + """Helper function to create a PassbandGroup object for testing.""" # Initialize requirements for PassbandGroup object survey = "TEST" band_labels = ["a", "b", "c"] - table_dir = tmp_path / survey + table_dir = path / survey table_dir.mkdir() transmission_tables = { @@ -353,7 +403,12 @@ def test_passband_group_fluxes_to_bandfluxes(tmp_path): passbands.append( Passband(survey, band_label, table_path=table_dir / f"{band_label}.dat", wave_grid=100.0) ) - test_passband_group = PassbandGroup(passbands=passbands) + return PassbandGroup(passbands=passbands) + + +def test_passband_group_fluxes_to_bandfluxes(tmp_path): + """Test the fluxes_to_bandfluxes method of the PassbandGroup class.""" + test_passband_group = make_passband_group(tmp_path) # Define some mock flux values and calculate our expected bandfluxes flux = np.array( @@ -382,45 +437,7 @@ def test_passband_group_fluxes_to_bandfluxes(tmp_path): ) -def test_passbandgroup_set_transmission_table_grids(tmp_path): - """Test the set_wave_grid_att method of the PassbandGroup class. Note this""" - # Initialize a Passband object - survey = "TEST" - band_label = "a" - table_path = tmp_path / f"{survey}_{band_label}.dat" - - transmission_table = "100 0.5\n200 0.75\n300 0.25\n400 0.5\n500 0.25\n600 0.5" - with open(table_path, "w") as f: - f.write(transmission_table) - - # TODO update to match set_transmission_table_grids - - # # Test interpolation is skipped when not needed - # a_band = Passband(survey, band_label, table_path=table_path, wave_grid=100.0) - # np.testing.assert_allclose(a_band.wave_grid, np.array([100.0, 200.0, 300.0, 400.0, 500.0, 600.0])) - # np.testing.assert_allclose( - # a_band.processed_transmission_table[:, 0], - # np.array([100.0, 200.0, 300.0, 400.0, 500.0, 600.0]), - # ) - - # # Test that grid is reset successfully (but the transmission table is not yet interpolated) - # a_band._set_wave_grid_attr(50.0) - # np.testing.assert_allclose(a_band.wave_grid, np.arange(100.0, 601.0, 50.0)) - # np.testing.assert_allclose( - # a_band.processed_transmission_table[:, 0], - # np.array([100.0, 200.0, 300.0, 400.0, 500.0, 600.0]), - # ) - - # # Test we can handle a list as input - # a_band._set_wave_grid_attr([100, 200, 300, 400, 500, 600]) - # np.testing.assert_allclose(a_band.wave_grid, np.array([100.0, 200.0, 300.0, 400.0, 500.0, 600.0])) - - # # Test we can handle an int as input - # a_band._set_wave_grid_attr(50) - # np.testing.assert_allclose(a_band.wave_grid, np.arange(100.0, 601.0, 50.0)) - - -def test_passbandgroup_sreset_transmission_table_grid(tmp_path): +def test_passband_set_transmission_table_grid(tmp_path): """Test the set_transmission_table_to_new_grid method of the PassbandGroup class.""" # Initialize a Passband object survey = "TEST" @@ -446,3 +463,26 @@ def test_passbandgroup_sreset_transmission_table_grid(tmp_path): a_band.processed_transmission_table[:, 0], np.array([100.0, 150.0, 200.0, 250.0, 300.0, 350.0, 400.0, 450.0, 500.0, 550.0, 600.0]), ) + + +def test_passband_group_set_transmission_table_grid(tmp_path): + """Test the set_transmission_table_to_new_grid method of the PassbandGroup class.""" + test_passband_group = make_passband_group(tmp_path) + + # Test that grid is reset successfully AND we have interpolated the transmission table as well + with patch.object(Passband, "set_transmission_table_grid") as mock_set_grid: + # Call the method with a float + test_passband_group.set_transmission_table_grid(50.0) + + # Check that the method was called for each Passband object + assert mock_set_grid.call_count == len(test_passband_group.passbands) + for _ in test_passband_group.passbands: + mock_set_grid.assert_any_call(50.0) + + # Call the method with None + test_passband_group.set_transmission_table_grid(None) + + # Check that the method was called for each Passband object + assert mock_set_grid.call_count == 2 * len(test_passband_group.passbands) + for _ in test_passband_group.passbands: + mock_set_grid.assert_any_call(None) From a847fb31ab7c6c8ccb6c43310d7af73309fb0ebe Mon Sep 17 00:00:00 2001 From: Olivia Lynn Date: Fri, 6 Sep 2024 11:59:03 -0400 Subject: [PATCH 17/38] Code quality checks; Start moving interpolation into passbands file --- src/tdastro/astro_utils/interpolation.py | 22 --- src/tdastro/astro_utils/passbands.py | 165 +++++++++++------- .../tdastro/astro_utils/test_interpolation.py | 3 +- tests/tdastro/astro_utils/test_passbands.py | 4 - 4 files changed, 105 insertions(+), 89 deletions(-) diff --git a/src/tdastro/astro_utils/interpolation.py b/src/tdastro/astro_utils/interpolation.py index 2977b727..175cfa96 100644 --- a/src/tdastro/astro_utils/interpolation.py +++ b/src/tdastro/astro_utils/interpolation.py @@ -58,28 +58,6 @@ def create_grid(bounds: np.ndarray | tuple, grid_step: float, increasing=True) - return new_grid -def interpolate_transmission_table(table: np.ndarray, new_wavelengths: np.ndarray) -> np.ndarray: - """Interpolate a 2 column table (such that the first column is x and the second column is y; eg, - a transmission table) to a new grid of x values. - - Parameters - ---------- - table : np.ndarray - The table to interpolate. Must be a 2D array with shape (n, 2). - new_wavelengths : np.ndarray - The new wavelengths grid to interpolate to. Must be a 1D array of length m. - - Returns - ------- - np.ndarray - The interpolated table, with shape (m, 2). - """ - if table.shape[1] != 2: - raise ValueError("Table must have exactly 2 columns.") - interpolated_transmissions = np.interp(new_wavelengths, table[:, 0], table[:, 1]) - return np.column_stack((new_wavelengths, interpolated_transmissions)) - - def interpolate_matrix_along_wavelengths( matrix: np.ndarray, wavelengths: np.ndarray, new_wavelengths: np.ndarray ) -> np.ndarray: diff --git a/src/tdastro/astro_utils/passbands.py b/src/tdastro/astro_utils/passbands.py index 04e01033..afef565a 100644 --- a/src/tdastro/astro_utils/passbands.py +++ b/src/tdastro/astro_utils/passbands.py @@ -18,7 +18,7 @@ class PassbandGroup: Attributes ---------- passbands : dict - A dictionary of Passband objects. + A dictionary of Passband objects. Note the keys are the full names of the passbands (eg, "LSST_u"). """ def __init__(self, preset=None, passbands=None): @@ -39,7 +39,7 @@ def __init__(self, preset=None, passbands=None): if passbands is not None: self.passbands = {} for passband in passbands: - self.passbands[passband.label] = passband # This overrides any preset passbands + self.passbands[passband.filter] = passband # This overrides any preset passbands def __str__(self) -> str: """Return a string representation of the PassbandGroup.""" @@ -48,7 +48,7 @@ def __str__(self) -> str: f"{', '.join([passband.full_name for passband in self.passbands.values()])}" ) - def _load_preset(self, preset): + def _load_preset(self, preset: str) -> None: """Load a pre-defined set of passbands. Parameters @@ -58,12 +58,12 @@ def _load_preset(self, preset): """ if preset == "LSST": self.passbands = { - "u": Passband("LSST", "u"), - "g": Passband("LSST", "g"), - "r": Passband("LSST", "r"), - "i": Passband("LSST", "i"), - "z": Passband("LSST", "z"), - "y": Passband("LSST", "y"), + "LSST_u": Passband("LSST", "u"), + "LSST_g": Passband("LSST", "g"), + "LSST_r": Passband("LSST", "r"), + "LSST_i": Passband("LSST", "i"), + "LSST_z": Passband("LSST", "z"), + "LSST_y": Passband("LSST", "y"), } else: raise ValueError(f"Unknown passband preset: {preset}") @@ -83,7 +83,9 @@ def set_transmission_table_grids(self, wave_grid: float | int | None) -> None: for _, passband in self.passbands.items(): passband.set_transmission_table_grid(wave_grid) - def fluxes_to_bandfluxes(self, flux_density_matrix, flux_wavelengths) -> np.ndarray: + def fluxes_to_bandfluxes( + self, flux_density_matrix: np.ndarray, flux_wavelengths: np.ndarray + ) -> np.ndarray: """Calculate bandfluxes for all passbands in the group. Parameters @@ -99,11 +101,11 @@ def fluxes_to_bandfluxes(self, flux_density_matrix, flux_wavelengths) -> np.ndar Returns ------- dict - A dictionary of bandfluxes with passband labels as keys. + A dictionary of bandfluxes with passband names as keys. """ bandfluxes = {} - for name, passband in self.passbands.items(): - bandfluxes[name] = passband.fluxes_to_bandflux(flux_density_matrix, flux_wavelengths) + for full_name, passband in self.passbands.items(): + bandfluxes[full_name] = passband.fluxes_to_bandflux(flux_density_matrix, flux_wavelengths) return bandfluxes @@ -112,32 +114,59 @@ class Passband: Attributes ---------- - label : str - The label of the passband. This is the filter name: eg, "u". survey : str The survey to which the passband belongs: eg, "LSST". + filter : str + The filter of the passband. This is the filter name: eg, "u". full_name : str - The full name of the passband. This is the survey and label concatenated: eg, "LSST_u". - wave_grid : np.ndarray | float | None + The full name of the passband. This is the survey and filter concatenated: eg, "LSST_u". + _wave_grid : np.ndarray | float | None The grid of wavelengths (Angstrom) to which the flux density matrix and transmission table should be - interpolated. If a float is given, wave_grid will be converted to a numpy array with a wave_grid step - matching the boundaries of the transmission table. If None, the transmission table will later be - interpolated to a grid with the same boundaries, but matching the step of the flux density matrix. - Default is 5.0. + interpolated. Use the _set_wave_grid_attr method to set this value. Default step is 5.0. table_path : str The path to the transmission table file. table_url : str The URL to download the transmission table file. - transmission_table : np.ndarray + _loaded_table : np.ndarray + A 2D array of wavelengths and transmissions. This is the table loaded from the file, and is neither + interpolated nor normalized. + processed_transmission_table : np.ndarray A 2D array where the first col is wavelengths (Angstrom) and the second col is transmission values. - normalized_transmission_table : np.ndarray - A 2D array of wavelengths and normalized transmissions. + This table is both interpolated to the _wave_grid and normalized to calculate phi_b(λ). """ - def __init__(self, survey, label, wave_grid=5.0, table_path=None, table_url=""): - self.label = label + def __init__( + self, + survey: str, + filter: str, + wave_grid: float = 5.0, + table_path: str | None = None, + table_url: str | None = None, + ): + """Initialize a Passband object. + + Parameters + ---------- + survey : str + The survey to which the passband belongs: eg, "LSST". + filter : str + The filter of the passband. This is the filter name: eg, "u". + wave_grid : np.ndarray | float | int | None, optional + The grid of wavelengths (Angstrom) to which the flux density matrix and transmission table should + be interpolated. A float or int will be converted to a numpy array with a grid step matching the + boundaries of the transmission table. If None, the transmission table will later be interpolated + to a grid maintaining the same boundaries, but matching the step of the flux density matrix. + Default is 5.0. + table_path : str, optional + The path to the transmission table file. If None, the table path will be set to a default path; + if no file exists at this location, the file will be downloaded from table_url. + table_url : str, optional + The URL to download the transmission table file. If None, the table URL will be set to + a default URL based on the survey and filter. Default is None. + """ self.survey = survey - self.full_name = f"{survey}_{label}" + self.filter = filter + self.full_name = f"{survey}_{filter}" self.table_path = table_path self.table_url = table_url @@ -150,25 +179,29 @@ def __str__(self) -> str: """Return a string representation of the Passband.""" return f"Passband: {self.full_name}" - def _load_transmission_table(self) -> np.ndarray: - """Load a transmission table from a file (or download it if it doesn't exist). + def _load_transmission_table(self) -> None: + """Load a transmission table from a file (or download it if it doesn't exist). Table must have 2 + columns: wavelengths and transmissions; wavelengths must be strictly increasing. Returns ------- np.ndarray A 2D array of wavelengths and transmissions. """ - # Check if the table file exists locally, and download it if it doesn't + # Check if the table file exists locally, and download it if it does not if self.table_path is None: self.table_path = os.path.join( - os.path.dirname(__file__), f"passbands/{self.survey}/{self.label}.dat" + os.path.dirname(__file__), f"passbands/{self.survey}/{self.filter}.dat" ) os.makedirs(os.path.dirname(self.table_path), exist_ok=True) if not os.path.exists(self.table_path): self._download_transmission_table() # Load the table file - loaded_table = np.loadtxt(self.table_path) + try: + loaded_table = np.loadtxt(self.table_path) + except OSError as e: + raise OSError(f"Error reading transmission table from file: {e}") from e # Check that the table has the correct shape if loaded_table.shape[1] != 2: @@ -187,14 +220,19 @@ def _download_transmission_table(self) -> bool: ------- bool True if the download was successful, False otherwise. + + Raises + ------ + NotImplementedError + If no table_url has been set and the survey is not supported for transmission table download. """ - if self.table_url == "": + if self.table_url is None: if self.survey == "LSST": # TODO consider: https://github.com/lsst/throughputs/blob/main/baseline/filter_g.dat # Or check with Mi's link (unless that was above) self.table_url = ( f"http://svo2.cab.inta-csic.es/svo/theory/fps3/getdata.php" - f"?format=ascii&id=LSST/LSST.{self.label}" + f"?format=ascii&id=LSST/LSST.{self.filter}" ) else: raise NotImplementedError( @@ -219,7 +257,7 @@ def _download_transmission_table(self) -> bool: def _set_wave_grid_attr(self, wave_grid: np.ndarray | float | int | None) -> None: """Set the wave grid attribute. Note: only sets the attribute; does NOT process transmission table. - Used to keep the type of wave_grid attribute as an array, even when set with a float. + Used to keep the type of _wave_grid attribute as an array, even when set with a float. TODO reword Parameters ---------- @@ -229,17 +267,17 @@ def _set_wave_grid_attr(self, wave_grid: np.ndarray | float | int | None) -> Non boundaries of the transmission table. If None, the transmission table will later be interpolated to a grid maintaining the same boundaries, but matching the step of the flux density matrix. """ - self.wave_grid = wave_grid - - if isinstance(self.wave_grid, (float, int)): + if isinstance(wave_grid, (float, int)): if self._loaded_table is None: raise ValueError( "Transmission table must be loaded before setting wave grid with an integer or float." ) - self.wave_grid = interpolation.create_grid(self._loaded_table[:, 0], self.wave_grid) + self._wave_grid = interpolation.create_grid(self._loaded_table[:, 0], wave_grid) + else: + self._wave_grid = wave_grid def set_transmission_table_grid(self, new_wave_grid: np.ndarray | float | int | None) -> None: - """Updates wave_grid attr and sets the transmission table to the new grid. + """Updates _wave_grid attr and sets the transmission table to the new grid. Parameters ---------- @@ -252,7 +290,7 @@ def set_transmission_table_grid(self, new_wave_grid: np.ndarray | float | int | self._set_wave_grid_attr(new_wave_grid) self._process_transmission_table() - def _process_transmission_table(self) -> np.ndarray: + def _process_transmission_table(self) -> None: """Process the transmission table: downsample or interpolate, then normalize.""" interpolated_transmissions = self._interpolate_or_downsample_transmission_table(self._loaded_table) normalized_transmissions = self._normalize_interpolated_transmission_table(interpolated_transmissions) @@ -271,13 +309,18 @@ def _interpolate_or_downsample_transmission_table(self, transmission_table) -> n np.ndarray A 2D array of wavelengths and transmissions. """ - if self.wave_grid is not None: - if type(self.wave_grid) == float: - self.wave_grid = interpolation.create_grid(transmission_table[:, 0], self.wave_grid) - interpolated_transmissions = interpolation.interpolate_transmission_table( - transmission_table, self.wave_grid - ) - return interpolated_transmissions + if self._wave_grid is None: + return transmission_table + if isinstance(self._wave_grid, (float, int)): + self._set_wave_grid_attr(self._wave_grid) + + if transmission_table.shape[1] != 2: + raise ValueError("Transmission table must have exactly 2 columns.") + + interpolated_transmissions = np.interp( + self._wave_grid, transmission_table[:, 0], transmission_table[:, 1] + ) # TODO maybe match this to interpolation method we use for flux densities + return np.column_stack((self._wave_grid, interpolated_transmissions)) def _normalize_interpolated_transmission_table(self, transmission_table) -> np.ndarray: """Calculate the value of phi_b for all wavelengths in a transmission table. @@ -309,8 +352,8 @@ def _normalize_interpolated_transmission_table(self, transmission_table) -> np.n def _interpolate_flux_densities( self, _flux_density_matrix, _flux_wavelengths, extrapolate="raise" - ) -> tuple: # TODO maybe move this to interpolation.py? - """Interpolate the flux density matrix to match the transmission table, which matches self.wave_grid. + ) -> tuple: + """Interpolate the flux density matrix to match the transmission table, which matches self._wave_grid. Parameters ---------- @@ -333,34 +376,34 @@ def _interpolate_flux_densities( raise ValueError("Wavelengths corresponding to flux density matrix must be strictly increasing.") # Get the target grid, if it is not already set; and, convert to array. - if self.wave_grid is None: + if self._wave_grid is None: if not np.allclose(np.diff(_flux_wavelengths), np.diff(_flux_wavelengths)[0]): raise ValueError( "Flux density wavelengths must have a uniform step for interpolation. " "Alternatively, provide a target grid step." ) - self.wave_grid = interpolation.create_grid( + self._wave_grid = interpolation.create_grid( self.processed_transmission_table[:, 0], np.diff(_flux_wavelengths)[0] ) - elif isinstance(self.wave_grid, float): - self.wave_grid = interpolation.create_grid( - self.processed_transmission_table[:, 0], self.wave_grid + elif isinstance(self._wave_grid, float): + self._wave_grid = interpolation.create_grid( + self.processed_transmission_table[:, 0], self._wave_grid ) # Interpolate the flux density matrix - if not np.array_equal(_flux_wavelengths, self.wave_grid): + if not np.array_equal(_flux_wavelengths, self._wave_grid): # Initialize an array to store interpolated flux densities - interpolated_flux_density_matrix = np.empty((len(_flux_density_matrix), len(self.wave_grid))) + interpolated_flux_density_matrix = np.empty((len(_flux_density_matrix), len(self._wave_grid))) # Interpolate each row individually for i, row in enumerate(_flux_density_matrix): - interpolator = scipy.interpolate.InterpolatedUnivariateSpline( + spline = scipy.interpolate.InterpolatedUnivariateSpline( _flux_wavelengths, row, ext=extrapolate ) - interpolated_flux_density_matrix[i, :] = interpolator(self.wave_grid) + interpolated_flux_density_matrix[i, :] = spline(self._wave_grid) flux_density_matrix = interpolated_flux_density_matrix - flux_wavelengths = self.wave_grid + flux_wavelengths = self._wave_grid else: flux_density_matrix = _flux_density_matrix flux_wavelengths = _flux_wavelengths @@ -392,7 +435,7 @@ def fluxes_to_bandflux(self, _flux_density_matrix, _flux_wavelengths, extrapolat np.ndarray An array of bandfluxes. """ - # Interpolate flux density matrix to match the transmission table, which matches self.wave_grid + # Interpolate flux density matrix to match the transmission table, which matches self._wave_grid flux_density_matrix, flux_wavelengths = self._interpolate_flux_densities( _flux_density_matrix, _flux_wavelengths, extrapolate ) diff --git a/tests/tdastro/astro_utils/test_interpolation.py b/tests/tdastro/astro_utils/test_interpolation.py index c537393e..231c57d3 100644 --- a/tests/tdastro/astro_utils/test_interpolation.py +++ b/tests/tdastro/astro_utils/test_interpolation.py @@ -57,8 +57,6 @@ def test_create_grid(): interp_wavelengths = create_grid(wavelengths, new_grid_step) np.testing.assert_allclose(interp_wavelengths, np.array([1.0, 3.0])) - # TODO add tuple bounds test - def test_interpolate_transmission_table(): """Test interpolate_transmission_table function.""" @@ -83,6 +81,7 @@ def test_interpolate_transmission_table(): ) # TODO test edge cases + # TODO moved ths into passband's _interpolate_or_downsample_transmission_table def test_interpolate_matrix_along_wavelengths(): diff --git a/tests/tdastro/astro_utils/test_passbands.py b/tests/tdastro/astro_utils/test_passbands.py index 5533198c..bdc1c884 100644 --- a/tests/tdastro/astro_utils/test_passbands.py +++ b/tests/tdastro/astro_utils/test_passbands.py @@ -194,8 +194,6 @@ def test_passband_normalize_interpolated_transmission_table(tmp_path): expected_result = np.array([[100.0, 0.0075], [200.0, 0.005625], [300.0, 0.00125]]) assert np.allclose(a_band.processed_transmission_table, expected_result) - # TODO add edge cases - def test_passband_process_transmission_table(tmp_path): """Test the _process_transmission_table method of the Passband class: correct methods are called.""" @@ -224,8 +222,6 @@ def test_passband_process_transmission_table(tmp_path): mock_interp_table.assert_called_once_with(a_band._loaded_table) mock_norm_table.assert_called_once() - # TODO edge cases? - def test_passband_interpolate_flux_densities_basic(tmp_path): """Test the _interpolate_flux_densities method of the Passband class. Make sure values are interpolated as From 37ac48847a32bf625984eb7e812def03eea7db91 Mon Sep 17 00:00:00 2001 From: Olivia Lynn Date: Fri, 6 Sep 2024 16:50:27 -0400 Subject: [PATCH 18/38] Add option to specify spline degree to SED interpolation; Add safety checks in various other methods --- src/tdastro/astro_utils/passbands.py | 100 ++++++++++++---- tests/tdastro/astro_utils/test_passbands.py | 125 ++++++++++---------- 2 files changed, 135 insertions(+), 90 deletions(-) diff --git a/src/tdastro/astro_utils/passbands.py b/src/tdastro/astro_utils/passbands.py index afef565a..c7a193f2 100644 --- a/src/tdastro/astro_utils/passbands.py +++ b/src/tdastro/astro_utils/passbands.py @@ -37,9 +37,8 @@ def __init__(self, preset=None, passbands=None): self._load_preset(preset) if passbands is not None: - self.passbands = {} for passband in passbands: - self.passbands[passband.filter] = passband # This overrides any preset passbands + self.passbands[passband.full_name] = passband def __str__(self) -> str: """Return a string representation of the PassbandGroup.""" @@ -296,9 +295,12 @@ def _process_transmission_table(self) -> None: normalized_transmissions = self._normalize_interpolated_transmission_table(interpolated_transmissions) self.processed_transmission_table = normalized_transmissions - def _interpolate_or_downsample_transmission_table(self, transmission_table) -> np.ndarray: + def _interpolate_or_downsample_transmission_table(self, transmission_table: np.ndarray) -> np.ndarray: """Interpolate or downsample a transmission table to a desired grid. + Note that if self._wave_grid is None, this method will return the original transmission table, as + we will later interpolate the transmission table to match the flux density matrix. + Parameters ---------- transmission_table : np.ndarray @@ -308,6 +310,11 @@ def _interpolate_or_downsample_transmission_table(self, transmission_table) -> n ------- np.ndarray A 2D array of wavelengths and transmissions. + + Raises + ------ + ValueError + If the transmission table does not have exactly 2 columns. """ if self._wave_grid is None: return transmission_table @@ -317,12 +324,13 @@ def _interpolate_or_downsample_transmission_table(self, transmission_table) -> n if transmission_table.shape[1] != 2: raise ValueError("Transmission table must have exactly 2 columns.") - interpolated_transmissions = np.interp( - self._wave_grid, transmission_table[:, 0], transmission_table[:, 1] - ) # TODO maybe match this to interpolation method we use for flux densities + spline = scipy.interpolate.InterpolatedUnivariateSpline( + transmission_table[:, 0], transmission_table[:, 1], ext="raise", k=1 + ) + interpolated_transmissions = spline(self._wave_grid) return np.column_stack((self._wave_grid, interpolated_transmissions)) - def _normalize_interpolated_transmission_table(self, transmission_table) -> np.ndarray: + def _normalize_interpolated_transmission_table(self, transmission_table: np.ndarray) -> np.ndarray: """Calculate the value of phi_b for all wavelengths in a transmission table. This is eq. 8 from "On the Choice of LSST Flux Units" (Ivezić et al.): @@ -340,18 +348,35 @@ def _normalize_interpolated_transmission_table(self, transmission_table) -> np.n ------- np.ndarray A 2D array of wavelengths and normalized transmissions. + Raises + ------ + ValueError + If the transmission table is the wrong size or the calculated denominator is zero. """ + if transmission_table.size == 0: + raise ValueError("Transmission table is empty, cannot normalize.") + elif transmission_table.shape[1] != 2: + raise ValueError("Transmission table must have exactly 2 columns.") + wavelengths_angstrom = transmission_table[:, 0] transmissions = transmission_table[:, 1] # Calculate the numerators and denominator numerators = transmissions / wavelengths_angstrom denominator = scipy.integrate.trapezoid(numerators, x=wavelengths_angstrom) + + if denominator == 0: + raise ValueError("Denominator is zero, cannot normalize.") + # Calculate phi_b for each wavelength normalized_transmissions = numerators / denominator return np.column_stack((wavelengths_angstrom, normalized_transmissions)) def _interpolate_flux_densities( - self, _flux_density_matrix, _flux_wavelengths, extrapolate="raise" + self, + _flux_density_matrix: np.ndarray, + _flux_wavelengths: np.ndarray, + extrapolate_mode: str = "raise", + spline_degree: int = 1, ) -> tuple: """Interpolate the flux density matrix to match the transmission table, which matches self._wave_grid. @@ -361,34 +386,53 @@ def _interpolate_flux_densities( A 2D array of flux densities where rows are times and columns are wavelengths. _flux_wavelengths : np.ndarray An array of wavelengths in Angstroms corresponding to the columns of _flux_density_matrix. - extrapolate : str, optional - The method of extrapolation to use, passed to scipy.interpolate.InterpolatedUnivariateSpline. + extrapolate_mode : str, optional + The mode of extrapolation to use, passed to scipy.interpolate.InterpolatedUnivariateSpline. Default is "raise", which will raise a ValueError if the interpolation goes out of bounds. Other options are "const" (pads with boundary value) and "zeros" (pads with 0). + spline_degree : int, optional + The degree of the spline to use for interpolation; must be 1 <= spline_degree <= 5. Default is 1, + which is linear interpolation. Returns ------- tuple A tuple containing the interpolated flux density matrix and interpolated wavelengths. + + Raises + ------ + ValueError + If the wavelengths in the flux density matrix are not strictly increasing, if the spline degree is + invalid, or if the _wave_grid attribute is not set and the flux density matrix wavelengths (which + would then be used to determine the grid step) do not have a uniform step. """ # Make sure all given wavelengths are strictly increasing if not np.all(np.diff(_flux_wavelengths) > 0): raise ValueError("Wavelengths corresponding to flux density matrix must be strictly increasing.") - # Get the target grid, if it is not already set; and, convert to array. + # Make sure the degree of the spline is valid + if (spline_degree < 1) or (spline_degree > 5): + raise ValueError("Spline degree must be between 0 and 5.") + elif spline_degree > len(_flux_wavelengths): + raise ValueError( + "Spline degree is greater than the number of wavelengths. Add more wavelengths to the flux " + "density matrix or reduce the spline_degree parameter." + ) + + # Make sure grid is an array if not None + if isinstance(self._wave_grid, (float, int)): + self._set_wave_grid_attr(self._wave_grid) + + # If grid is None, we use the flux density matrix grid step to interpolate the transmission table if self._wave_grid is None: if not np.allclose(np.diff(_flux_wavelengths), np.diff(_flux_wavelengths)[0]): raise ValueError( - "Flux density wavelengths must have a uniform step for interpolation. " - "Alternatively, provide a target grid step." + "Flux density wavelengths must have a uniform step to interpolate transmission to match. " + "Alternatively, provide a target grid step with the set_transmission_table_grid method." ) - self._wave_grid = interpolation.create_grid( - self.processed_transmission_table[:, 0], np.diff(_flux_wavelengths)[0] - ) - elif isinstance(self._wave_grid, float): - self._wave_grid = interpolation.create_grid( - self.processed_transmission_table[:, 0], self._wave_grid - ) + # Update transmission table step to match the flux density matrix step (preserving boundaries) + flux_grid_step = np.diff(_flux_wavelengths)[0] + self.set_transmission_table_grid(flux_grid_step) # Interpolate the flux density matrix if not np.array_equal(_flux_wavelengths, self._wave_grid): @@ -398,7 +442,7 @@ def _interpolate_flux_densities( # Interpolate each row individually for i, row in enumerate(_flux_density_matrix): spline = scipy.interpolate.InterpolatedUnivariateSpline( - _flux_wavelengths, row, ext=extrapolate + _flux_wavelengths, row, ext=extrapolate_mode, k=spline_degree ) interpolated_flux_density_matrix[i, :] = spline(self._wave_grid) @@ -410,7 +454,9 @@ def _interpolate_flux_densities( return (flux_density_matrix, flux_wavelengths) - def fluxes_to_bandflux(self, _flux_density_matrix, _flux_wavelengths, extrapolate="raise") -> np.ndarray: + def fluxes_to_bandflux( + self, _flux_density_matrix, _flux_wavelengths, extrapolate_mode="raise", spline_degree=1 + ) -> np.ndarray: """Calculate the bandflux for a given set of flux densities. This is eq. 7 from "On the Choice of LSST Flux Units" (Ivezić et al.): @@ -426,10 +472,14 @@ def fluxes_to_bandflux(self, _flux_density_matrix, _flux_wavelengths, extrapolat A 2D array of flux densities where rows are times and columns are wavelengths. flux_wavelengths : np.ndarray An array of wavelengths in Angstroms corresponding to the columns of flux_density_matrix. - extrapolate : str, optional - The method of extrapolation to use, passed to scipy.interpolate.InterpolatedUnivariateSpline. + extrapolate_mode : str, optional + The mode of extrapolation to use, passed to scipy.interpolate.InterpolatedUnivariateSpline. Default is "raise", which will raise a ValueError if the interpolation goes out of bounds. Other options are "const" (pads with boundary value) and "zeros" (pads with 0). + spline_degree : int, optional + The degree of the spline to use for interpolation; must be 1 <= spline_degree <= 5. Default is 1, + which is linear interpolation. + Returns ------- np.ndarray @@ -437,7 +487,7 @@ def fluxes_to_bandflux(self, _flux_density_matrix, _flux_wavelengths, extrapolat """ # Interpolate flux density matrix to match the transmission table, which matches self._wave_grid flux_density_matrix, flux_wavelengths = self._interpolate_flux_densities( - _flux_density_matrix, _flux_wavelengths, extrapolate + _flux_density_matrix, _flux_wavelengths, extrapolate_mode, spline_degree ) # Calculate the bandflux as ∫ f(λ)φ_b(λ) dλ, diff --git a/tests/tdastro/astro_utils/test_passbands.py b/tests/tdastro/astro_utils/test_passbands.py index bdc1c884..9199833b 100644 --- a/tests/tdastro/astro_utils/test_passbands.py +++ b/tests/tdastro/astro_utils/test_passbands.py @@ -14,12 +14,12 @@ def test_passband_init(): # Test that the PassbandGroup class can be initialized with a preset lsst_passband_group = PassbandGroup(preset="LSST") assert len(lsst_passband_group.passbands) == 6 - assert "u" in lsst_passband_group.passbands - assert "g" in lsst_passband_group.passbands - assert "r" in lsst_passband_group.passbands - assert "i" in lsst_passband_group.passbands - assert "z" in lsst_passband_group.passbands - assert "y" in lsst_passband_group.passbands + assert "LSST_u" in lsst_passband_group.passbands + assert "LSST_g" in lsst_passband_group.passbands + assert "LSST_r" in lsst_passband_group.passbands + assert "LSST_i" in lsst_passband_group.passbands + assert "LSST_z" in lsst_passband_group.passbands + assert "LSST_y" in lsst_passband_group.passbands # Test that the PassbandGroup class can be initialized with a list of Passband objects lsst_gri_passbands = [ @@ -29,33 +29,9 @@ def test_passband_init(): ] lsst_gri_passband_group = PassbandGroup(passbands=lsst_gri_passbands) assert len(lsst_gri_passband_group.passbands) == 3 - assert "g" in lsst_gri_passband_group.passbands - assert "r" in lsst_gri_passband_group.passbands - assert "i" in lsst_gri_passband_group.passbands - - # Test that the PassbandGroup class can be initialized with non-LSST passbands - gaia_passbands = [ - Passband( - "GAIA", - "0.Gbp", - table_url="http://svo2.cab.inta-csic.es/svo/theory/fps3/getdata.php?format=ascii&id=GAIA/GAIA0.Gbp", - ), - Passband( - "GAIA", - "0.G", - table_url="http://svo2.cab.inta-csic.es/svo/theory/fps3/getdata.php?format=ascii&id=GAIA/GAIA0.G", - ), - Passband( - "GAIA", - "0.Grp", - table_url="http://svo2.cab.inta-csic.es/svo/theory/fps3/getdata.php?format=ascii&id=GAIA/GAIA0.Grp", - ), - ] - gaia_passband_group = PassbandGroup(passbands=gaia_passbands) - assert len(gaia_passband_group.passbands) == 3 - assert "0.Gbp" in gaia_passband_group.passbands - assert "0.G" in gaia_passband_group.passbands - assert "0.Grp" in gaia_passband_group.passbands + assert "LSST_g" in lsst_gri_passband_group.passbands + assert "LSST_r" in lsst_gri_passband_group.passbands + assert "LSST_i" in lsst_gri_passband_group.passbands # Test that the PassbandGroup class raises an error for an unknown preset try: @@ -77,28 +53,6 @@ def test_passband_str(): == "PassbandGroup containing 6 passbands: LSST_u, LSST_g, LSST_r, LSST_i, LSST_z, LSST_y" ) - gaia_passbands = [ - Passband( - "GAIA", - "0.Gbp", - table_url="http://svo2.cab.inta-csic.es/svo/theory/fps3/getdata.php?format=ascii&id=GAIA/GAIA0.Gbp", - ), - Passband( - "GAIA", - "0.G", - table_url="http://svo2.cab.inta-csic.es/svo/theory/fps3/getdata.php?format=ascii&id=GAIA/GAIA0.G", - ), - Passband( - "GAIA", - "0.Grp", - table_url="http://svo2.cab.inta-csic.es/svo/theory/fps3/getdata.php?format=ascii&id=GAIA/GAIA0.Grp", - ), - ] - gaia_passband_group = PassbandGroup(passbands=gaia_passbands) - assert ( - str(gaia_passband_group) == "PassbandGroup containing 3 passbands: GAIA_0.Gbp, GAIA_0.G, GAIA_0.Grp" - ) - def test_passband_load_transmission_table(tmp_path): """Test the _load_transmission_table method of the Passband class.""" @@ -161,7 +115,6 @@ def test_passband_interpolate_or_downsample_transmission_table(tmp_path): f.write(transmission_table) a_band = Passband(survey, band_label, table_path=table_path, wave_grid=100) - print(a_band.processed_transmission_table) # Downsample the transmission table a_band._set_wave_grid_attr(200) @@ -258,10 +211,53 @@ def test_passband_interpolate_flux_densities_basic(tmp_path): # Ends should be 0.25 assert result_fluxes[0, 0] == 0.25 assert result_fluxes[0, 10] == 0.25 - # First half of array should be increasing - assert np.all(np.diff(result_fluxes[0, :6]) > 0) - # Second half of array should be decreasing - assert np.all(np.diff(result_fluxes[0, 5:]) < 0) + # Beginning should be increasing + assert np.all(np.diff(result_fluxes[0, :5]) > 0) + # End should be decreasing + assert np.all(np.diff(result_fluxes[0, 7:]) < 0) + + +def test_passband_interpolate_flux_densities_degrees(tmp_path): + """Test the _interpolate_flux_densities method of the Passband class. Make sure values are interpolated as + expected.""" + # Initialize a Passband object + survey = "TEST" + band_label = "a" + table_path = tmp_path / f"{survey}_{band_label}.dat" + + transmission_table = "100 0.5\n200 0.75\n300 0.25\n400 0.5\n500 0.25\n600 0.5" + with open(table_path, "w") as f: + f.write(transmission_table) + + a_band = Passband(survey, band_label, table_path=table_path, wave_grid=50.0) + fluxes = np.array([[0.25, 0.5, 1.0, 1.0, 0.5, 0.25], [0.25, 0.5, 1.0, 1.0, 0.5, 0.25]]) + flux_wavelengths = np.array([100.0, 200.0, 300.0, 400.0, 500.0, 600.0]) + + # Test we can run with default degrees + (result_fluxes, result_wavelengths) = a_band._interpolate_flux_densities(fluxes, flux_wavelengths) + assert result_fluxes.shape == (2, 11) + assert result_wavelengths.shape == (11,) + + # Test we can run with degrees 1-5 + for degree in range(1, 6): + (result_fluxes, result_wavelengths) = a_band._interpolate_flux_densities( + fluxes, flux_wavelengths, spline_degree=degree + ) + assert result_fluxes.shape == (2, 11) + assert result_wavelengths.shape == (11,) + + # Test we raise an error for invalid degrees + with pytest.raises(ValueError): + a_band._interpolate_flux_densities(fluxes, flux_wavelengths, spline_degree=0) + + with pytest.raises(ValueError): + a_band._interpolate_flux_densities(fluxes, flux_wavelengths, spline_degree=6) + + # Test we raise an error if number of degrees is greater than number of points + fluxes = np.array([[0.25, 0.5]]) + flux_wavelengths = np.array([100.0, 200.0]) + with pytest.raises(ValueError): + a_band._interpolate_flux_densities(fluxes, flux_wavelengths, spline_degree=3) def test_passband_interpolate_flux_densities_mismatched_bounds( @@ -390,7 +386,6 @@ def make_passband_group(path): } for band_label in band_labels: with open(table_dir / f"{band_label}.dat", "w") as f: - print("Writing", band_label, "to", table_dir / f"{band_label}.dat") f.write(transmission_tables[band_label]) # Load the PassbandGroup object @@ -446,7 +441,7 @@ def test_passband_set_transmission_table_grid(tmp_path): # Test interpolation is skipped when not needed a_band = Passband(survey, band_label, table_path=table_path, wave_grid=100.0) - np.testing.assert_allclose(a_band.wave_grid, np.array([100.0, 200.0, 300.0, 400.0, 500.0, 600.0])) + np.testing.assert_allclose(a_band._wave_grid, np.array([100.0, 200.0, 300.0, 400.0, 500.0, 600.0])) np.testing.assert_allclose( a_band.processed_transmission_table[:, 0], np.array([100.0, 200.0, 300.0, 400.0, 500.0, 600.0]), @@ -454,7 +449,7 @@ def test_passband_set_transmission_table_grid(tmp_path): # Test that grid is reset successfully AND we have interpolated the transmission table as well a_band.set_transmission_table_grid(50.0) - np.testing.assert_allclose(a_band.wave_grid, np.arange(100.0, 601.0, 50.0)) + np.testing.assert_allclose(a_band._wave_grid, np.arange(100.0, 601.0, 50.0)) np.testing.assert_allclose( a_band.processed_transmission_table[:, 0], np.array([100.0, 150.0, 200.0, 250.0, 300.0, 350.0, 400.0, 450.0, 500.0, 550.0, 600.0]), @@ -468,7 +463,7 @@ def test_passband_group_set_transmission_table_grid(tmp_path): # Test that grid is reset successfully AND we have interpolated the transmission table as well with patch.object(Passband, "set_transmission_table_grid") as mock_set_grid: # Call the method with a float - test_passband_group.set_transmission_table_grid(50.0) + test_passband_group.set_transmission_table_grids(50.0) # Check that the method was called for each Passband object assert mock_set_grid.call_count == len(test_passband_group.passbands) @@ -476,7 +471,7 @@ def test_passband_group_set_transmission_table_grid(tmp_path): mock_set_grid.assert_any_call(50.0) # Call the method with None - test_passband_group.set_transmission_table_grid(None) + test_passband_group.set_transmission_table_grids(None) # Check that the method was called for each Passband object assert mock_set_grid.call_count == 2 * len(test_passband_group.passbands) From cd62bd8f5c78917454caf458d420450038f99e8d Mon Sep 17 00:00:00 2001 From: Olivia Lynn Date: Mon, 9 Sep 2024 10:24:18 -0400 Subject: [PATCH 19/38] Move interpolation functions fully into passbands --- src/tdastro/astro_utils/interpolation.py | 85 ---------------- .../tdastro/astro_utils/test_interpolation.py | 97 ------------------- 2 files changed, 182 deletions(-) delete mode 100644 src/tdastro/astro_utils/interpolation.py delete mode 100644 tests/tdastro/astro_utils/test_interpolation.py diff --git a/src/tdastro/astro_utils/interpolation.py b/src/tdastro/astro_utils/interpolation.py deleted file mode 100644 index 175cfa96..00000000 --- a/src/tdastro/astro_utils/interpolation.py +++ /dev/null @@ -1,85 +0,0 @@ -import numpy as np - - -def get_grid_step(grid: np.ndarray) -> float: - """Get the step size of a grid if it is uniform; otherwise, return None. - - Parameters - ---------- - grid : np.ndarray - The grid. - - Returns - ------- - float or None - The step size of the grid if it is uniform, otherwise None. - """ - if np.allclose(np.diff(grid), np.diff(grid)[0]): - return np.diff(grid)[0] - return None - - -def create_grid(bounds: np.ndarray | tuple, grid_step: float, increasing=True) -> np.ndarray: - """Create a new grid with given bounds and grid step. - - If the interval between the original grid's upper and lower bounds is a multiple of the new grid step, - the upper bound will be included in the new grid. - - Parameters - ---------- - bounds : np.ndarray | tuple - The bounds of the grid. If a tuple, it should be (lower_bound, upper_bound). If an array, the first - and last elements will be used as the lower and upper bounds, respectively. - grid_step : float - The step size of the new grid. - increasing : bool, optional - Whether the grid should include checks that bounds are increasing. Default is True. - - Returns - ------- - np.ndarray - The new grid. - """ - # Get bounds - if isinstance(bounds, tuple): - lower_bound, upper_bound = bounds - else: - lower_bound, upper_bound = bounds[0], bounds[-1] - - # Check lower bound is less than upper bound - if increasing and lower_bound >= upper_bound: - raise ValueError("Lower bound must be less than upper bound, or disable 'increasing' check.") - - # Generate new grid, including the original upper bound if step size is a divisor of target interval - if (upper_bound - lower_bound) % grid_step == 0: - new_grid = np.arange(lower_bound, upper_bound + grid_step, grid_step) - else: - new_grid = np.arange(lower_bound, upper_bound, grid_step) - return new_grid - - -def interpolate_matrix_along_wavelengths( - matrix: np.ndarray, wavelengths: np.ndarray, new_wavelengths: np.ndarray -) -> np.ndarray: - """Interpolate a matrix with columns corresponding to a vector of wavelengths. - - Parameters - ---------- - matrix : np.ndarray - A 2D matrix to interpolate, with size (n, m). - wavelengths : np.ndarray - The wavelengths corresponding to the matrix, with size m. - new_wavelengths : np.ndarray - The new grid of wavelengths to interpolate to, with size p. - - Returns - ------- - np.ndarray - The interpolated matrix, with size (n, p). - """ - if matrix.shape[1] != len(wavelengths): - raise ValueError( - f"Matrix has {matrix.shape[1]} columns, but {len(wavelengths)} wavelengths were given." - ) - new_matrix = np.array([np.interp(new_wavelengths, wavelengths, row) for row in matrix]) - return new_matrix diff --git a/tests/tdastro/astro_utils/test_interpolation.py b/tests/tdastro/astro_utils/test_interpolation.py deleted file mode 100644 index 231c57d3..00000000 --- a/tests/tdastro/astro_utils/test_interpolation.py +++ /dev/null @@ -1,97 +0,0 @@ -import numpy as np -import pytest -from tdastro.astro_utils.interpolation import ( - create_grid, - get_grid_step, - interpolate_matrix_along_wavelengths, - interpolate_transmission_table, -) - - -def test_get_grid_step(): - """Test get_grid_step function.""" - # Test uniform grid - grid = np.array([1, 2, 3]) - grid_step = get_grid_step(grid) - assert grid_step == 1 - - # Test non-uniform grid - grid = np.array([1, 2, 4]) - grid_step = get_grid_step(grid) - assert grid_step is None - - # Test non-uniform grid with equal differences - grid = np.array([1, 2, 2]) - grid_step = get_grid_step(grid) - assert grid_step is None - - -def test_create_grid(): - """Test create_grid function.""" - wavelengths = np.array([1, 2, 3]) - new_grid_step = 0.5 - interp_wavelengths = create_grid(wavelengths, new_grid_step) - np.testing.assert_allclose(interp_wavelengths, np.array([1.0, 1.5, 2.0, 2.5, 3.0])) - - # Test non-uniform grid - wavelengths = np.array([1, 2, 4]) - new_grid_step = 0.5 - interp_wavelengths = create_grid(wavelengths, new_grid_step) - np.testing.assert_allclose(interp_wavelengths, np.array([1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0])) - - # Test not strictly increasing grid - wavelengths = np.array([1, 2, 1]) - new_grid_step = 0.5 - with pytest.raises(ValueError): - create_grid(wavelengths, new_grid_step) - - # Test upper bound is included where the step size is a divisor of the upper bound - wavelengths = np.array([1, 4]) - new_grid_step = 1 - interp_wavelengths = create_grid(wavelengths, new_grid_step) - np.testing.assert_allclose(interp_wavelengths, np.array([1.0, 2.0, 3.0, 4.0])) - - # Test upper bound not included where the step size is not a divisor of the upper bound - wavelengths = np.array([1, 4]) - new_grid_step = 2 - interp_wavelengths = create_grid(wavelengths, new_grid_step) - np.testing.assert_allclose(interp_wavelengths, np.array([1.0, 3.0])) - - -def test_interpolate_transmission_table(): - """Test interpolate_transmission_table function.""" - wavelengths = np.array([0, 10, 20]) - transmissions = np.array([1, 2, 3]) - table = np.stack((wavelengths, transmissions), axis=-1) - new_wavelengths = np.linspace(0, 20, 7) - interp_transmissions = interpolate_transmission_table(table, new_wavelengths) - np.testing.assert_allclose( - interp_transmissions, - np.array( - [ - [0.0, 1.0], - [3.33333333, 1.33333333], - [6.66666667, 1.66666667], - [10.0, 2.0], - [13.33333333, 2.33333333], - [16.66666667, 2.66666667], - [20.0, 3.0], - ] - ), - ) - - # TODO test edge cases - # TODO moved ths into passband's _interpolate_or_downsample_transmission_table - - -def test_interpolate_matrix_along_wavelengths(): - """Test interpolate_matrix_along_wavelengths function.""" - fluxes = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]) - wavelengths = np.array([1, 2, 3]) - new_grid_step = 0.5 - interp_wavelengths = create_grid(wavelengths, new_grid_step) - interp_fluxes = interpolate_matrix_along_wavelengths(fluxes, wavelengths, interp_wavelengths) - np.testing.assert_allclose( - interp_fluxes, - np.array([[1.0, 1.5, 2.0, 2.5, 3.0], [4.0, 4.5, 5.0, 5.5, 6.0], [7.0, 7.5, 8.0, 8.5, 9.0]]), - ) From 76b78634ade0450bc5574df7e95d098f287821e9 Mon Sep 17 00:00:00 2001 From: Olivia Lynn Date: Mon, 9 Sep 2024 22:45:27 -0400 Subject: [PATCH 20/38] Finish unit tests --- src/tdastro/astro_utils/passbands.py | 123 ++-- .../astro_utils/test_passband_groups.py | 153 +++++ tests/tdastro/astro_utils/test_passbands.py | 551 +++++++++--------- 3 files changed, 504 insertions(+), 323 deletions(-) create mode 100644 tests/tdastro/astro_utils/test_passband_groups.py diff --git a/src/tdastro/astro_utils/passbands.py b/src/tdastro/astro_utils/passbands.py index c7a193f2..45155dd5 100644 --- a/src/tdastro/astro_utils/passbands.py +++ b/src/tdastro/astro_utils/passbands.py @@ -7,8 +7,6 @@ import numpy as np import scipy.integrate -from tdastro.astro_utils import interpolation - logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s") @@ -83,7 +81,11 @@ def set_transmission_table_grids(self, wave_grid: float | int | None) -> None: passband.set_transmission_table_grid(wave_grid) def fluxes_to_bandfluxes( - self, flux_density_matrix: np.ndarray, flux_wavelengths: np.ndarray + self, + flux_density_matrix: np.ndarray, + flux_wavelengths: np.ndarray, + extrapolate_mode: str = "raise", + spline_degree: int = 1, ) -> np.ndarray: """Calculate bandfluxes for all passbands in the group. @@ -93,9 +95,13 @@ def fluxes_to_bandfluxes( A 2D array of flux densities where rows are times and columns are wavelengths. flux_wavelengths : np.ndarray An array of wavelengths in Angstroms corresponding to the columns of flux_density_matrix. - target_grid_step : float, optional - The unit of the grid (in Angstrom) to which the flux density matrix and normalized transmission - table should be interpolated. + extrapolate_mode : str, optional + The mode of extrapolation to use, passed to scipy.interpolate.InterpolatedUnivariateSpline. + Default is "raise", which will raise a ValueError if the interpolation goes out of bounds. Other + options are "const" (pads with boundary value) and "zeros" (pads with 0). + spline_degree : int, optional + The degree of the spline to use for interpolation; must be 1 <= spline_degree <= 5. Default is 1, + which is linear interpolation. Returns ------- @@ -104,7 +110,12 @@ def fluxes_to_bandfluxes( """ bandfluxes = {} for full_name, passband in self.passbands.items(): - bandfluxes[full_name] = passband.fluxes_to_bandflux(flux_density_matrix, flux_wavelengths) + bandfluxes[full_name] = passband.fluxes_to_bandflux( + flux_density_matrix, + flux_wavelengths, + extrapolate_mode=extrapolate_mode, + spline_degree=spline_degree, + ) return bandfluxes @@ -115,8 +126,8 @@ class Passband: ---------- survey : str The survey to which the passband belongs: eg, "LSST". - filter : str - The filter of the passband. This is the filter name: eg, "u". + filter_name : str + The name of the passband's filter: eg, "u". full_name : str The full name of the passband. This is the survey and filter concatenated: eg, "LSST_u". _wave_grid : np.ndarray | float | None @@ -137,7 +148,7 @@ class Passband: def __init__( self, survey: str, - filter: str, + filter_name: str, wave_grid: float = 5.0, table_path: str | None = None, table_url: str | None = None, @@ -148,8 +159,8 @@ def __init__( ---------- survey : str The survey to which the passband belongs: eg, "LSST". - filter : str - The filter of the passband. This is the filter name: eg, "u". + filter_name : str + The filter_name of the passband: eg, "u". wave_grid : np.ndarray | float | int | None, optional The grid of wavelengths (Angstrom) to which the flux density matrix and transmission table should be interpolated. A float or int will be converted to a numpy array with a grid step matching the @@ -161,11 +172,11 @@ def __init__( if no file exists at this location, the file will be downloaded from table_url. table_url : str, optional The URL to download the transmission table file. If None, the table URL will be set to - a default URL based on the survey and filter. Default is None. + a default URL based on the survey and filter_name. Default is None. """ self.survey = survey - self.filter = filter - self.full_name = f"{survey}_{filter}" + self.filter_name = filter_name + self.full_name = f"{survey}_{filter_name}" self.table_path = table_path self.table_url = table_url @@ -190,7 +201,7 @@ def _load_transmission_table(self) -> None: # Check if the table file exists locally, and download it if it does not if self.table_path is None: self.table_path = os.path.join( - os.path.dirname(__file__), f"passbands/{self.survey}/{self.filter}.dat" + os.path.dirname(__file__), f"passbands/{self.survey}/{self.filter_name}.dat" ) os.makedirs(os.path.dirname(self.table_path), exist_ok=True) if not os.path.exists(self.table_path): @@ -203,7 +214,7 @@ def _load_transmission_table(self) -> None: raise OSError(f"Error reading transmission table from file: {e}") from e # Check that the table has the correct shape - if loaded_table.shape[1] != 2: + if loaded_table.size == 0 or loaded_table.shape[1] != 2: raise ValueError("Transmission table must have exactly 2 columns.") # Check that wavelengths are strictly increasing @@ -227,11 +238,11 @@ def _download_transmission_table(self) -> bool: """ if self.table_url is None: if self.survey == "LSST": - # TODO consider: https://github.com/lsst/throughputs/blob/main/baseline/filter_g.dat + # Consider: https://github.com/lsst/throughputs/blob/main/baseline/filter_g.dat # Or check with Mi's link (unless that was above) self.table_url = ( f"http://svo2.cab.inta-csic.es/svo/theory/fps3/getdata.php" - f"?format=ascii&id=LSST/LSST.{self.filter}" + f"?format=ascii&id=LSST/LSST.{self.filter_name}" ) else: raise NotImplementedError( @@ -254,9 +265,10 @@ def _download_transmission_table(self) -> bool: return False def _set_wave_grid_attr(self, wave_grid: np.ndarray | float | int | None) -> None: - """Set the wave grid attribute. Note: only sets the attribute; does NOT process transmission table. + """Set the wave grid attribute. Keeps _wave_grid as None or array-type, even when set with a float. - Used to keep the type of _wave_grid attribute as an array, even when set with a float. TODO reword + Note: this only sets the attribute; it does NOT process transmission table. Use + set_transmission_table_grid to set the attribute and process the transmission table in one step. Parameters ---------- @@ -266,15 +278,51 @@ def _set_wave_grid_attr(self, wave_grid: np.ndarray | float | int | None) -> Non boundaries of the transmission table. If None, the transmission table will later be interpolated to a grid maintaining the same boundaries, but matching the step of the flux density matrix. """ - if isinstance(wave_grid, (float, int)): + if wave_grid is None: + self._wave_grid = wave_grid + + elif isinstance(wave_grid, np.ndarray): + # Check that the wave grid is valid + if wave_grid.size <= 1: + raise ValueError("Wave grid must have at least two values.") + elif wave_grid.ndim != 1: + raise ValueError("Wave grid must be a 1D array.") + elif not np.all(np.diff(wave_grid) > 0): + raise ValueError("Wave grid must have strictly increasing values.") + + # Truncate the wave grid to fit the transmission table boundaries if self._loaded_table is None: + raise ValueError("Transmission table must be loaded before setting wave grid.") + lower_bound, upper_bound = self._loaded_table[0, 0], self._loaded_table[-1, 0] + lower_index = np.searchsorted(wave_grid, lower_bound, side="left") + upper_index = np.searchsorted(wave_grid, upper_bound, side="right") + wave_grid = wave_grid[lower_index:upper_index] + if wave_grid.size <= 1: raise ValueError( - "Transmission table must be loaded before setting wave grid with an integer or float." + "Wave grid has fewer than two values after truncation to fit within the transmission " + "table's boundaries." ) - self._wave_grid = interpolation.create_grid(self._loaded_table[:, 0], wave_grid) - else: + # TODO If I'm truncating here, should I also interpolate? at that point, why let them give + # an array at all? ask about this in the morning. + self._wave_grid = wave_grid + elif isinstance(wave_grid, (float, int)): + # Get the bounds of our new grid from the transmission table + if self._loaded_table is None: + raise ValueError("Transmission table must be loaded before setting wave grid.") + lower_bound, upper_bound = self._loaded_table[0, 0], self._loaded_table[-1, 0] + + # Generate new grid; include the original upper bound if step size is divisor of target interval. + # We use linspace instead of arange, as numpy recommends this for non-integer step sizes; plus, + # arange generates values within a half-open interval, and we usually want the upper bound. + self._wave_grid = np.linspace( + lower_bound, upper_bound, int((upper_bound - lower_bound) / wave_grid) + 1 + ) + + else: + raise ValueError("Wave grid must be a 1D numpy array, float, int, or None.") + def set_transmission_table_grid(self, new_wave_grid: np.ndarray | float | int | None) -> None: """Updates _wave_grid attr and sets the transmission table to the new grid. @@ -318,6 +366,7 @@ def _interpolate_or_downsample_transmission_table(self, transmission_table: np.n """ if self._wave_grid is None: return transmission_table + if isinstance(self._wave_grid, (float, int)): self._set_wave_grid_attr(self._wave_grid) @@ -354,9 +403,11 @@ def _normalize_interpolated_transmission_table(self, transmission_table: np.ndar If the transmission table is the wrong size or the calculated denominator is zero. """ if transmission_table.size == 0: - raise ValueError("Transmission table is empty, cannot normalize.") - elif transmission_table.shape[1] != 2: - raise ValueError("Transmission table must have exactly 2 columns.") + raise ValueError("Transmission table is empty; cannot normalize.") + elif transmission_table.shape[0] == 1: + raise ValueError(f"Cannot normalize transmission table with only one row: {transmission_table}.") + elif transmission_table.ndim != 2 or transmission_table.shape[1] != 2: + raise ValueError("Transmission table must be 2D array with exactly 2 columns.") wavelengths_angstrom = transmission_table[:, 0] transmissions = transmission_table[:, 1] @@ -365,7 +416,12 @@ def _normalize_interpolated_transmission_table(self, transmission_table: np.ndar denominator = scipy.integrate.trapezoid(numerators, x=wavelengths_angstrom) if denominator == 0: - raise ValueError("Denominator is zero, cannot normalize.") + raise ValueError( + "Denominator is zero; cannot normalize transmission table. " + f"Consider checking the transmission table for band {self.full_name}. " + f"With wave grid set to: {self._wave_grid}, transmission table wavelengths are: " + f"{transmission_table[:, 0]}." + ) # Calculate phi_b for each wavelength normalized_transmissions = numerators / denominator @@ -419,18 +475,19 @@ def _interpolate_flux_densities( "density matrix or reduce the spline_degree parameter." ) - # Make sure grid is an array if not None + # Make sure the wave grid we're interpolating to is an array (if not None) if isinstance(self._wave_grid, (float, int)): self._set_wave_grid_attr(self._wave_grid) - # If grid is None, we use the flux density matrix grid step to interpolate the transmission table - if self._wave_grid is None: + # If wave grid is None, use the flux density matrix's grid step to interpolate the transmission table + elif self._wave_grid is None: if not np.allclose(np.diff(_flux_wavelengths), np.diff(_flux_wavelengths)[0]): raise ValueError( "Flux density wavelengths must have a uniform step to interpolate transmission to match. " "Alternatively, provide a target grid step with the set_transmission_table_grid method." ) - # Update transmission table step to match the flux density matrix step (preserving boundaries) + # Update transmission table step to match the flux density matrix step + # (but keep the same transmission table boundaries) flux_grid_step = np.diff(_flux_wavelengths)[0] self.set_transmission_table_grid(flux_grid_step) diff --git a/tests/tdastro/astro_utils/test_passband_groups.py b/tests/tdastro/astro_utils/test_passband_groups.py new file mode 100644 index 00000000..0837f51c --- /dev/null +++ b/tests/tdastro/astro_utils/test_passband_groups.py @@ -0,0 +1,153 @@ +from unittest.mock import patch + +import numpy as np +from tdastro.astro_utils.passbands import Passband, PassbandGroup + + +def create_passband_group(path): + """Helper function to create a PassbandGroup object for testing.""" + # Initialize requirements for PassbandGroup object + survey = "TEST" + band_labels = ["a", "b", "c"] + table_dir = path / survey + table_dir.mkdir() + + transmission_tables = { + "a": "100 0.5\n200 0.75\n300 0.25\n", + "b": "100 0.25\n200 0.5\n300 0.75\n", + "c": "100 0.75\n200 0.25\n300 0.5\n", + } + for band_label in band_labels: + with open(table_dir / f"{band_label}.dat", "w") as f: + f.write(transmission_tables[band_label]) + + # Load the PassbandGroup object + passbands = [] + for band_label in band_labels: + passbands.append( + Passband(survey, band_label, table_path=table_dir / f"{band_label}.dat", wave_grid=100.0) + ) + return PassbandGroup(passbands=passbands) + + +def test_passband_group_init(): + """Test the initialization of the Passband class, and implicitly, _load_preset.""" + # Test that we can create an empty PassbandGroup object + empty_passband = PassbandGroup() + assert len(empty_passband.passbands) == 0 + + # Test that the PassbandGroup class can be initialized with a preset + # Mock the transmission table files at passbands/LSST/.dat using patch + transmission_table_array = np.array([[100, 0.5], [200, 0.75], [300, 0.25]]) + + def mock_load_transmission_table(self): + self._loaded_table = transmission_table_array + + with patch.object(Passband, "_load_transmission_table", new=mock_load_transmission_table): + lsst_passband_group = PassbandGroup(preset="LSST") + assert len(lsst_passband_group.passbands) == 6 + assert "LSST_u" in lsst_passband_group.passbands + assert "LSST_g" in lsst_passband_group.passbands + assert "LSST_r" in lsst_passband_group.passbands + assert "LSST_i" in lsst_passband_group.passbands + assert "LSST_z" in lsst_passband_group.passbands + assert "LSST_y" in lsst_passband_group.passbands + + # Test that the PassbandGroup class can be initialized with a list of Passband objects + with patch.object(Passband, "_load_transmission_table", new=mock_load_transmission_table): + lsst_gri_passbands = [ + Passband("LSST", "g"), + Passband("LSST", "r"), + Passband("LSST", "i"), + ] + lsst_gri_passband_group = PassbandGroup(passbands=lsst_gri_passbands) + assert len(lsst_gri_passband_group.passbands) == 3 + assert "LSST_g" in lsst_gri_passband_group.passbands + assert "LSST_r" in lsst_gri_passband_group.passbands + assert "LSST_i" in lsst_gri_passband_group.passbands + + # Test that the PassbandGroup class raises an error for an unknown preset + try: + _ = PassbandGroup(preset="Unknown") + except ValueError as e: + assert str(e) == "Unknown passband preset: Unknown" + else: + raise AssertionError("PassbandGroup should raise an error for an unknown preset") + + +def test_passband_group_str(tmp_path): + """Test the __str__ method of the PassbandGroup class.""" + empty_passband_group = PassbandGroup() + assert str(empty_passband_group) == "PassbandGroup containing 0 passbands: " + + # Test that the __str__ method returns the expected string with preset passbands + lsst_passband_group = PassbandGroup(preset="LSST") + assert ( + str(lsst_passband_group) + == "PassbandGroup containing 6 passbands: LSST_u, LSST_g, LSST_r, LSST_i, LSST_z, LSST_y" + ) + + # Test that the __str__ method returns the expected string with custom passbands + test_passband_group = create_passband_group(tmp_path) + assert str(test_passband_group) == "PassbandGroup containing 3 passbands: TEST_a, TEST_b, TEST_c" + + +def test_passband_group_set_transmission_table_grid(tmp_path): + """Test the set_transmission_table_to_new_grid method of the PassbandGroup class.""" + test_passband_group = create_passband_group(tmp_path) + + # Test that grid is reset successfully AND we have called interpolation methods the transmission table + with patch.object(Passband, "set_transmission_table_grid") as mock_set_grid: + # Call the method with a float + test_passband_group.set_transmission_table_grids(50.0) + + # Check that the method was called for each Passband object + assert mock_set_grid.call_count == len(test_passband_group.passbands) + for _ in test_passband_group.passbands: + mock_set_grid.assert_any_call(50.0) + + # Call the method with None + test_passband_group.set_transmission_table_grids(None) + + # Check that the method was called for each Passband object + assert mock_set_grid.call_count == 2 * len(test_passband_group.passbands) + for _ in test_passband_group.passbands: + mock_set_grid.assert_any_call(None) + + +def test_passband_group_fluxes_to_bandfluxes(tmp_path): + """Test the fluxes_to_bandfluxes method of the PassbandGroup class.""" + # Test with empty passband group + empty_passband_group = PassbandGroup() + flux = np.array([[1.0, 1.0, 1.0], [2.0, 1.0, 1.0], [3.0, 1.0, 1.0]]) + flux_wavelengths = np.array([100, 200, 300]) + bandfluxes = empty_passband_group.fluxes_to_bandfluxes(flux, flux_wavelengths) + assert len(bandfluxes) == 0 + + # Test with simple passband group + test_passband_group = create_passband_group(tmp_path) + flux = np.array( + [ + [1.0, 1.0, 1.0], + [2.0, 1.0, 1.0], + [3.0, 1.0, 1.0], + [2.0, 1.0, 1.0], + [1.0, 1.0, 1.0], + ] + ) + flux_wavelengths = np.array([100, 200, 300]) + bandfluxes = test_passband_group.fluxes_to_bandfluxes(flux, flux_wavelengths) + + # Check values are as expected + assert len(bandfluxes) == 3 + for band_name in test_passband_group.passbands: + assert band_name in bandfluxes + assert bandfluxes[band_name].shape == (5,) + assert np.allclose( + bandfluxes[band_name], + np.trapz( + flux * test_passband_group.passbands[band_name].processed_transmission_table[:, 1], + x=flux_wavelengths, + axis=1, + ), + ) diff --git a/tests/tdastro/astro_utils/test_passbands.py b/tests/tdastro/astro_utils/test_passbands.py index 9199833b..4e90233e 100644 --- a/tests/tdastro/astro_utils/test_passbands.py +++ b/tests/tdastro/astro_utils/test_passbands.py @@ -2,86 +2,98 @@ import numpy as np import pytest -from tdastro.astro_utils.passbands import Passband, PassbandGroup +from tdastro.astro_utils.passbands import Passband def test_passband_init(): """Test the initialization of the Passband class.""" - # Test that we can create an empty PassbandGroup object - empty_passband = PassbandGroup() - assert len(empty_passband.passbands) == 0 - - # Test that the PassbandGroup class can be initialized with a preset - lsst_passband_group = PassbandGroup(preset="LSST") - assert len(lsst_passband_group.passbands) == 6 - assert "LSST_u" in lsst_passband_group.passbands - assert "LSST_g" in lsst_passband_group.passbands - assert "LSST_r" in lsst_passband_group.passbands - assert "LSST_i" in lsst_passband_group.passbands - assert "LSST_z" in lsst_passband_group.passbands - assert "LSST_y" in lsst_passband_group.passbands - - # Test that the PassbandGroup class can be initialized with a list of Passband objects - lsst_gri_passbands = [ - Passband("LSST", "g"), - Passband("LSST", "r"), - Passband("LSST", "i"), - ] - lsst_gri_passband_group = PassbandGroup(passbands=lsst_gri_passbands) - assert len(lsst_gri_passband_group.passbands) == 3 - assert "LSST_g" in lsst_gri_passband_group.passbands - assert "LSST_r" in lsst_gri_passband_group.passbands - assert "LSST_i" in lsst_gri_passband_group.passbands - - # Test that the PassbandGroup class raises an error for an unknown preset - try: - _ = PassbandGroup(preset="Unknown") - except ValueError as e: - assert str(e) == "Unknown passband preset: Unknown" - else: - raise AssertionError("PassbandGroup should raise an error for an unknown preset") - - -def test_passband_str(): - """Test the __str__ method of the PassbandGroup class.""" - empty_passband_group = PassbandGroup() - assert str(empty_passband_group) == "PassbandGroup containing 0 passbands: " - - lsst_passband_group = PassbandGroup(preset="LSST") - assert ( - str(lsst_passband_group) - == "PassbandGroup containing 6 passbands: LSST_u, LSST_g, LSST_r, LSST_i, LSST_z, LSST_y" - ) + # Test we get a TypeError if we don't provide a survey and filter_name + with pytest.raises(TypeError): + a_band = Passband() + + # Test we get an NotImplementedError if we don't have a local transmission table or provided URL, and the + # survey has no default URL + with pytest.raises(NotImplementedError): + a_band = Passband("TEST", "a") + + # Test that the Passband class can be initialized with a survey and filter_name + # Mock a transmission table file that we'll "find" at passbands/TEST/a.dat + transmission_table_array = np.array([[100, 0.5], [200, 0.75], [300, 0.25]]) + + def mock_load_transmission_table(self): + self._loaded_table = transmission_table_array + + with patch.object(Passband, "_load_transmission_table", new=mock_load_transmission_table): + a_band = Passband("TEST", "a") + assert a_band.survey == "TEST" + assert a_band.filter_name == "a" + assert a_band.full_name == "TEST_a" + # Cannot check table_path as we have mocked the method that sets it; see unit test for loading tables + assert a_band.table_url is None + np.testing.assert_allclose(a_band._loaded_table, transmission_table_array) + assert isinstance(a_band._wave_grid, np.ndarray) + assert a_band.processed_transmission_table is not None + + +def create_test_passband(path, transmission_table, filter_name="a", **kwargs): + """Helper function to create a Passband object for testing.""" + survey = "TEST" + table_path = path / f"{survey}_{filter_name}.dat" + + # Create a transmission table file + with open(table_path, "w") as f: + f.write(transmission_table) + + # Create a Passband object + return Passband(survey, filter_name, table_path=table_path, **kwargs) + + +def test_passband_str(tmp_path): + """Test the __str__ method of the Passband class.""" + transmission_table = "1000 0.5\n1005 0.6\n1010 0.7\n" + + # Check that the __str__ method returns the expected string + a_band = create_test_passband(tmp_path, transmission_table) + assert str(a_band) == "Passband: TEST_a" def test_passband_load_transmission_table(tmp_path): """Test the _load_transmission_table method of the Passband class.""" - survey = "TEST" - band_label = "a" - table_path = tmp_path / f"{survey}_{band_label}.dat" - # Create a transmission table file + # Test a toy transmission table was loaded correctly transmission_table = "1000 0.5\n1005 0.6\n1010 0.7\n" - with open(table_path, "w") as f: + a_band = create_test_passband(tmp_path, transmission_table) + np.testing.assert_allclose(a_band._loaded_table, np.array([[1000, 0.5], [1005, 0.6], [1010, 0.7]])) + + # Test that we raise an error if the transmission table is blank + transmission_table = "" + with open(a_band.table_path, "w") as f: f.write(transmission_table) + with pytest.raises(ValueError): + a_band._load_transmission_table() - # Initialization of the Passband object automatically loads the transmission table - a_band = Passband(survey, band_label, table_path=table_path) + # Test that we raise an error if the transmission table is not formatted correctly + transmission_table = "1000\n1005 0.6\n1010 0.7" + with open(a_band.table_path, "w") as f: + f.write(transmission_table) + with pytest.raises(ValueError): + a_band._load_transmission_table() - # Check that the transmission table was loaded correctly - assert a_band.processed_transmission_table.shape == (3, 2) - assert np.allclose(a_band.processed_transmission_table[:, 0], np.array([1000, 1005, 1010])) - assert a_band.processed_transmission_table[0, 1] < a_band.processed_transmission_table[1, 1] - assert a_band.processed_transmission_table[1, 1] < a_band.processed_transmission_table[2, 1] + # Test that we raise an error if the transmission table wavelengths are not sorted + transmission_table = "1000 0.5\n900 0.6\n1010 0.7" + with open(a_band.table_path, "w") as f: + f.write(transmission_table) + with pytest.raises(ValueError): + a_band._load_transmission_table() def test_passband_download_transmission_table(tmp_path): """Test the _download_transmission_table method of the Passband class.""" # Initialize a Passband object survey = "TEST" - band_label = "a" - table_path = tmp_path / f"{survey}_{band_label}.dat" - table_url = f"http://example.com/{survey}/{band_label}.dat" + filter_name = "a" + table_path = tmp_path / f"{survey}_{filter_name}.dat" + table_url = f"http://example.com/{survey}/{filter_name}.dat" transmission_table = "1000 0.5\n1005 0.6\n1010 0.7\n" def mock_urlretrieve(url, filename, *args, **kwargs): # Urlretrieve saves contents directly to filename @@ -91,113 +103,168 @@ def mock_urlretrieve(url, filename, *args, **kwargs): # Urlretrieve saves conte # Mock the urlretrieve portion of the download method with patch("urllib.request.urlretrieve", side_effect=mock_urlretrieve) as mocked_urlretrieve: - a_band = Passband(survey, band_label, table_path=table_path, table_url=table_url) + a_band = Passband(survey, filter_name, table_path=table_path, table_url=table_url) # Check that the transmission table was downloaded mocked_urlretrieve.assert_called_once_with(table_url, table_path) # Check that the transmission table was loaded correctly - assert a_band.processed_transmission_table.shape == (3, 2) - assert a_band.processed_transmission_table[0, 0] == 1000 - assert a_band.processed_transmission_table[1, 0] == 1005 - assert a_band.processed_transmission_table[2, 0] == 1010 + np.testing.assert_allclose(a_band._loaded_table, np.array([[1000, 0.5], [1005, 0.6], [1010, 0.7]])) -def test_passband_interpolate_or_downsample_transmission_table(tmp_path): - """Test down-sampling and interpolation of the transmission table.""" - # Initialize a Passband object - survey = "TEST" - band_label = "a" - table_path = tmp_path / f"{survey}_{band_label}.dat" +def test_passband_set_wave_grid_attr(tmp_path): + """Test the _set_wave_grid_attr method of the Passband class.""" + transmission_table = "100 0.5\n200 0.75\n300 0.25\n" + a_band = create_test_passband(tmp_path, transmission_table, wave_grid=100) + + # Test that the wave grid is set correctly + a_band._set_wave_grid_attr(50.0) + np.testing.assert_allclose(a_band._wave_grid, np.arange(100.0, 301.0, 50.0)) + + # Test that the wave grid is reset correctly + a_band._set_wave_grid_attr(100.0) + np.testing.assert_allclose(a_band._wave_grid, np.array([100.0, 200.0, 300.0])) + + # Test that we can set the wave grid with None + a_band._set_wave_grid_attr(None) + assert a_band._wave_grid is None + + # Test we can be lazy and set the wave grid with just an integer + a_band._set_wave_grid_attr(100) + np.testing.assert_allclose(a_band._wave_grid, np.array([100.0, 200.0, 300.0])) + + # Test that we can set the wave grid with a numpy array + # Note, we truncate given grid to fit transmission table bounds + a_band._set_wave_grid_attr(np.array([100.0, 150.0, 200.0, 250.0, 300.0, 350.0, 400.0])) + np.testing.assert_allclose(a_band._wave_grid, np.array([100.0, 150.0, 200.0, 250.0, 300.0])) + + # Test that we raise an error if the wave grid is not sorted + with pytest.raises(ValueError): + a_band._set_wave_grid_attr(np.array([100.0, 300.0, 200.0])) + + # Test that we raise an error if the wave grid is not 1D + with pytest.raises(ValueError): + a_band._set_wave_grid_attr(np.array([[100.0, 200.0], [300.0, 400.0]])) + + # Test we raise an error if wave grid is only one value + with pytest.raises(ValueError): + a_band._set_wave_grid_attr(np.array([100.0])) + + # Test we raise an error if wave grid is empty + with pytest.raises(ValueError): + a_band._set_wave_grid_attr(np.array([])) + + +def test_passband_set_transmission_table_grid(tmp_path): + """Test the set_transmission_table_to_new_grid method of the PassbandGroup class.""" + transmission_table = "100 0.5\n200 0.75\n300 0.25\n400 0.5\n500 0.25\n600 0.5" + + # Test case where interpolation is not needed + a_band = create_test_passband(tmp_path, transmission_table, wave_grid=100) + np.testing.assert_allclose(a_band._wave_grid, np.array([100.0, 200.0, 300.0, 400.0, 500.0, 600.0])) + np.testing.assert_allclose( + a_band.processed_transmission_table[:, 0], + np.array([100.0, 200.0, 300.0, 400.0, 500.0, 600.0]), + ) + + # Test that grid is reset successfully AND we have interpolated the transmission table as well + a_band.set_transmission_table_grid(50.0) + np.testing.assert_allclose(a_band._wave_grid, np.arange(100.0, 601.0, 50.0)) + np.testing.assert_allclose( + a_band.processed_transmission_table[:, 0], + np.array([100.0, 150.0, 200.0, 250.0, 300.0, 350.0, 400.0, 450.0, 500.0, 550.0, 600.0]), + ) + +def test_passband_process_transmission_table(tmp_path): + """Test the _process_transmission_table method of the Passband class: correct methods are called.""" transmission_table = "100 0.5\n200 0.75\n300 0.25\n" - with open(table_path, "w") as f: - f.write(transmission_table) + a_band = create_test_passband(tmp_path, transmission_table, wave_grid=100) + + # Mock the methods that _process_transmission_table wraps + with ( + patch.object(a_band, "_interpolate_or_downsample_transmission_table") as mock_interp_table, + patch.object(a_band, "_normalize_interpolated_transmission_table") as mock_norm_table, + ): + # Call the _process_transmission_table method + a_band._process_transmission_table() - a_band = Passband(survey, band_label, table_path=table_path, wave_grid=100) + # Check that each method is called once + mock_interp_table.assert_called_once_with(a_band._loaded_table) + mock_norm_table.assert_called_once() + + +def test_passband_interpolate_or_downsample_transmission_table(tmp_path): + """Test down-sampling and interpolation of the transmission table.""" + transmission_table = "100 0.5\n200 0.75\n300 0.25\n" + a_band = create_test_passband(tmp_path, transmission_table) # Downsample the transmission table a_band._set_wave_grid_attr(200) table = a_band._interpolate_or_downsample_transmission_table(a_band._loaded_table) np.testing.assert_allclose(table[:, 0], [100, 300]) - # Interpolate the transmission table + # Downsample the transmission table to a very large step size + a_band._set_wave_grid_attr(500) + table = a_band._interpolate_or_downsample_transmission_table(a_band._loaded_table) + np.testing.assert_allclose(table[:, 0], [100]) + + # Interpolate the transmission table (note for comparison below: np.arange is exclusive of stop value) a_band._set_wave_grid_attr(50) table = a_band._interpolate_or_downsample_transmission_table(a_band._loaded_table) np.testing.assert_allclose(table[:, 0], np.arange(100, 301, 50)) + # Interpolate the transmission table to a somewhat small step size (1 Angstrom) + a_band._set_wave_grid_attr(1) + table = a_band._interpolate_or_downsample_transmission_table(a_band._loaded_table) + np.testing.assert_allclose(table[:, 0], np.arange(100, 301, 1)) + + # Interpolate the transmission table to an even smaller step size (0.1 Angstrom) + a_band._set_wave_grid_attr(0.1) + table = a_band._interpolate_or_downsample_transmission_table(a_band._loaded_table) + np.testing.assert_allclose(table[:, 0], np.arange(100, 300.01, 0.1)) + def test_passband_normalize_interpolated_transmission_table(tmp_path): """Test the _normalize_interpolated_transmission_table method of the Passband class.""" - # Initialize a Passband object - survey = "TEST" - band_label = "a" - table_path = tmp_path / f"{survey}_{band_label}.dat" - transmission_table = "100 0.5\n200 0.75\n300 0.25\n" - with open(table_path, "w") as f: - f.write(transmission_table) + a_band = create_test_passband(tmp_path, transmission_table, wave_grid=100) - a_band = Passband(survey, band_label, table_path=table_path, wave_grid=100) - - # Normalize the transmission table (skipping interpolation as grid already matches) + # Normalize the transmission table (we skip interpolation as grid already matches) a_band._normalize_interpolated_transmission_table(a_band._loaded_table) # Compare results expected_result = np.array([[100.0, 0.0075], [200.0, 0.005625], [300.0, 0.00125]]) assert np.allclose(a_band.processed_transmission_table, expected_result) - -def test_passband_process_transmission_table(tmp_path): - """Test the _process_transmission_table method of the Passband class: correct methods are called.""" - - # Initialize a Passband object - survey = "TEST" - band_label = "a" - table_path = tmp_path / f"{survey}_{band_label}.dat" - - transmission_table = "100 0.5\n200 0.75\n300 0.25\n" - with open(table_path, "w") as f: - f.write(transmission_table) - - a_band = Passband(survey, band_label, table_path=table_path, wave_grid=100) - - # Mock the methods that _process_transmission_table wraps - with patch.object( - a_band, "_interpolate_or_downsample_transmission_table" - ) as mock_interp_table, patch.object( - a_band, "_normalize_interpolated_transmission_table" - ) as mock_norm_table: - # Call the _process_transmission_table method - a_band._process_transmission_table() - - # Check that each method is called once with the correct arguments - mock_interp_table.assert_called_once_with(a_band._loaded_table) - mock_norm_table.assert_called_once() + # Test that we raise an error if the transmission table is the wrong size or shape + with pytest.raises(ValueError): + a_band._normalize_interpolated_transmission_table(np.array([[]])) + with pytest.raises(ValueError): + a_band._normalize_interpolated_transmission_table(np.array([[100, 0.5]])) + with pytest.raises(ValueError): + a_band._normalize_interpolated_transmission_table(np.array([100, 0.5])) + with pytest.raises(ValueError): + a_band._normalize_interpolated_transmission_table(np.array([[100, 0.5, 105, 0.6]])) def test_passband_interpolate_flux_densities_basic(tmp_path): - """Test the _interpolate_flux_densities method of the Passband class. Make sure values are interpolated as - expected.""" - # Initialize a Passband object - survey = "TEST" - band_label = "a" - table_path = tmp_path / f"{survey}_{band_label}.dat" - + """Test basic functionality of the _interpolate_flux_densities method of the Passband class.""" transmission_table = "100 0.5\n200 0.75\n300 0.25\n400 0.5\n500 0.25\n600 0.5" - with open(table_path, "w") as f: - f.write(transmission_table) - # Test interpolation is skipped when not needed - a_band = Passband(survey, band_label, table_path=table_path, wave_grid=100.0) + # Test: no interpolation needed + a_band = create_test_passband(tmp_path, transmission_table, wave_grid=100) fluxes = np.array([[0.25, 0.5, 1.0, 1.0, 0.5, 0.25]]) flux_wavelengths = np.array([100.0, 200.0, 300.0, 400.0, 500.0, 600.0]) - (result_fluxes, result_wavelengths) = a_band._interpolate_flux_densities(fluxes, flux_wavelengths) - np.testing.assert_allclose(result_fluxes, fluxes) - np.testing.assert_allclose(result_wavelengths, flux_wavelengths) - # Test interpolation when fluxes span entire band - b_band = Passband(survey, band_label, table_path=table_path, wave_grid=50.0) + with patch("scipy.interpolate.InterpolatedUnivariateSpline") as mock_spline: + (result_fluxes, result_wavelengths) = a_band._interpolate_flux_densities(fluxes, flux_wavelengths) + np.testing.assert_allclose(result_fluxes, fluxes) + np.testing.assert_allclose(result_wavelengths, flux_wavelengths) + mock_spline.assert_not_called() + + # Test: interpolation when fluxes span entire band + b_band = create_test_passband(tmp_path, transmission_table, wave_grid=50, filter_name="b") fluxes = np.array([[0.25, 0.5, 1.0, 1.0, 0.5, 0.25], [0.25, 0.5, 1.0, 1.0, 0.5, 0.25]]) flux_wavelengths = np.array([100.0, 200.0, 300.0, 400.0, 500.0, 600.0]) (result_fluxes, result_wavelengths) = b_band._interpolate_flux_densities(fluxes, flux_wavelengths) @@ -211,34 +278,26 @@ def test_passband_interpolate_flux_densities_basic(tmp_path): # Ends should be 0.25 assert result_fluxes[0, 0] == 0.25 assert result_fluxes[0, 10] == 0.25 - # Beginning should be increasing + # Beginning should be increasing. We don't go all the way to the middle, as the spline may wiggle a bit + # approximating the flat top between 300 and 400 Angstroms. assert np.all(np.diff(result_fluxes[0, :5]) > 0) - # End should be decreasing + # End should be decreasing. Similarly, not starting exactly at the middle. assert np.all(np.diff(result_fluxes[0, 7:]) < 0) -def test_passband_interpolate_flux_densities_degrees(tmp_path): - """Test the _interpolate_flux_densities method of the Passband class. Make sure values are interpolated as - expected.""" - # Initialize a Passband object - survey = "TEST" - band_label = "a" - table_path = tmp_path / f"{survey}_{band_label}.dat" - +def test_passband_interpolate_flux_densities_spline_degrees(tmp_path): + """Test spline degree settings in the _interpolate_flux_densities method of the Passband class.""" transmission_table = "100 0.5\n200 0.75\n300 0.25\n400 0.5\n500 0.25\n600 0.5" - with open(table_path, "w") as f: - f.write(transmission_table) - - a_band = Passband(survey, band_label, table_path=table_path, wave_grid=50.0) + a_band = create_test_passband(tmp_path, transmission_table, wave_grid=50) fluxes = np.array([[0.25, 0.5, 1.0, 1.0, 0.5, 0.25], [0.25, 0.5, 1.0, 1.0, 0.5, 0.25]]) flux_wavelengths = np.array([100.0, 200.0, 300.0, 400.0, 500.0, 600.0]) - # Test we can run with default degrees + # Test we can run interpolation with spline_degree at default (3) (result_fluxes, result_wavelengths) = a_band._interpolate_flux_densities(fluxes, flux_wavelengths) assert result_fluxes.shape == (2, 11) assert result_wavelengths.shape == (11,) - # Test we can run with degrees 1-5 + # Test we can run with spline_degree at values 1-5 for degree in range(1, 6): (result_fluxes, result_wavelengths) = a_band._interpolate_flux_densities( fluxes, flux_wavelengths, spline_degree=degree @@ -260,35 +319,43 @@ def test_passband_interpolate_flux_densities_degrees(tmp_path): a_band._interpolate_flux_densities(fluxes, flux_wavelengths, spline_degree=3) -def test_passband_interpolate_flux_densities_mismatched_bounds( - tmp_path, -): - """Test the _interpolate_flux_densities method of the Passband class. Make sure values are interpolated as - expected, out-of-bounds values are handled correctly, and padding is creating when needed.""" - # Initialize a Passband object - survey = "TEST" - band_label = "a" - table_path = tmp_path / f"{survey}_{band_label}.dat" - +def test_passband_interpolate_flux_densities_truncation_needed(tmp_path): + """Test truncation in the _interpolate_flux_densities method of the Passband class.""" transmission_table = "100 0.5\n200 0.75\n300 0.25\n400 0.5\n500 0.25\n600 0.5" - with open(table_path, "w") as f: - f.write(transmission_table) - # Test interpolation when fluxes are out of bounds - a_band = Passband(survey, band_label, table_path=table_path, wave_grid=100.0) - fluxes = np.array([[0.25, 0.5, 1.0, 1.0, 0.5, 0.25]]) + # Test truncation when fluxes are out of bounds + a_band = create_test_passband(tmp_path, transmission_table, wave_grid=100) + fluxes = np.array([[0.25, 0.5, 1.0, 1.0, 0.5, 0.25, 0.0, 0.5]]) flux_wavelengths = np.array([50.0, 100.0, 200.0, 300.0, 400.0, 500.0, 600.0, 650.0]) + (result_fluxes, result_wavelengths) = a_band._interpolate_flux_densities(fluxes, flux_wavelengths) + assert result_fluxes.shape == (1, 6) + assert result_wavelengths.shape == (6,) + np.testing.assert_allclose(result_wavelengths, np.array([100.0, 200.0, 300.0, 400.0, 500.0, 600.0])) + np.testing.assert_allclose(result_fluxes, fluxes[:, 1:7]) + + # Test truncation and interpolation when fluxes are out of bounds + a_band.set_transmission_table_grid(50) + (result_fluxes, result_wavelengths) = a_band._interpolate_flux_densities(fluxes, flux_wavelengths) + assert result_fluxes.shape == (1, 11) + assert result_wavelengths.shape == (11,) + np.testing.assert_allclose(result_wavelengths, np.arange(100, 601, 50)) + np.testing.assert_allclose(result_fluxes[:, ::2], fluxes[:, 1:7]) - # Test padding (with no interpolation) when fluxes do not span the entire band - a_band = Passband(survey, band_label, table_path=table_path, wave_grid=100.0) + +def test_passband_interpolate_flux_densities_padding_needed(tmp_path): + """Test padding in the _interpolate_flux_densities method of the Passband class.""" + transmission_table = "100 0.5\n200 0.75\n300 0.25\n400 0.5\n500 0.25\n600 0.5" + + # Test padding (with NO interpolation) when fluxes do not span the entire band + a_band = create_test_passband(tmp_path, transmission_table, wave_grid=100, filter_name="b") fluxes = np.array([[0.5, 1.0, 0.5, 0.25], [0.5, 1.0, 0.5, 0.25]]) flux_wavelengths = np.array([200.0, 300.0, 400.0, 500.0]) - # Case 1: with extrapolation="raise" + # Case 1: padding needed with extrapolation="raise" with pytest.raises(ValueError): a_band._interpolate_flux_densities(fluxes, flux_wavelengths, "raise") - # Case 2: with extrapolation="zeros" + # Case 2: padding needed with extrapolation="zeros" (result_fluxes, result_wavelengths) = a_band._interpolate_flux_densities( fluxes, flux_wavelengths, "zeros" ) @@ -297,7 +364,7 @@ def test_passband_interpolate_flux_densities_mismatched_bounds( np.testing.assert_allclose(result_fluxes, expected_fluxes) np.testing.assert_allclose(result_wavelengths, expected_waves) - # Case 3: with extrapolation="constant" + # Case 3: padding needed with extrapolation="constant" (result_fluxes, result_wavelengths) = a_band._interpolate_flux_densities( fluxes, flux_wavelengths, "const" ) @@ -306,17 +373,18 @@ def test_passband_interpolate_flux_densities_mismatched_bounds( np.testing.assert_allclose(result_fluxes, expected_fluxes) np.testing.assert_allclose(result_wavelengths, expected_waves) - # Test interpolation and padding when fluxes do not span the entire band - d_band = Passband(survey, band_label, table_path=table_path, wave_grid=50.0) + # Test padding (this time WITH interpolation as well) when fluxes do not span the entire band + b_band = create_test_passband(tmp_path, transmission_table, wave_grid=50, filter_name="b") fluxes = np.array([[0.25, 0.75, 1.0, 0.25]]) flux_wavelengths = np.array([200.0, 300.0, 400.0, 500.0]) - (result_fluxes, result_wavelengths) = d_band._interpolate_flux_densities( + (result_fluxes, result_wavelengths) = b_band._interpolate_flux_densities( fluxes, flux_wavelengths, "zeros" ) + # Check waves generated as expected expected_waves = np.arange(100, 601, 50) np.testing.assert_allclose(result_wavelengths, expected_waves) assert result_fluxes.shape == (1, 11) - # Check zero-padding + # Check flux zero-padding on both ends assert np.isclose(result_fluxes[0, 0], 0.0) assert np.isclose(result_fluxes[0, 1], 0.0) assert np.isclose(result_fluxes[0, 9], 0.0) @@ -329,28 +397,11 @@ def test_passband_interpolate_flux_densities_mismatched_bounds( # Check the decreasing section (originally indices [2, 3]) is still decreasing (now indices [6, 8]) assert np.all(np.diff(result_fluxes[0, 6:8]) < 0) - # Test handling when fluxes are out of bounds - e_band = Passband(survey, band_label, table_path=table_path, wave_grid=100.0) - fluxes = np.array([[0.25, 0.5, 1.0, 1.5, 1.5, 1.0, 0.5, 0.25]]) - flux_wavelengths = np.array([50.0, 100.0, 200.0, 300.0, 400.0, 500.0, 600.0, 650.0]) - (result_fluxes, result_wavelengths) = e_band._interpolate_flux_densities(fluxes, flux_wavelengths) - expected_waves = np.arange(100, 601, 100) - np.testing.assert_allclose(result_wavelengths, expected_waves) - np.testing.assert_allclose(result_fluxes, fluxes[:, 1:7]) - def test_passband_fluxes_to_bandflux(tmp_path): """Test the fluxes_to_bandflux method of the Passband class.""" - # Initialize a Passband object - survey = "TEST" - band_label = "a" - table_path = tmp_path / f"{survey}_{band_label}.dat" - transmission_table = "100 0.5\n200 0.75\n300 0.25\n" - with open(table_path, "w") as f: - f.write(transmission_table) - - a_band = Passband(survey, band_label, table_path=table_path, wave_grid=100.0) + a_band = create_test_passband(tmp_path, transmission_table, wave_grid=100) # Define some mock flux values and calculate our expected bandflux flux = np.array( @@ -365,115 +416,35 @@ def test_passband_fluxes_to_bandflux(tmp_path): expected_in_band_flux = np.trapz( flux * a_band.processed_transmission_table[:, 1], x=a_band.processed_transmission_table[:, 0] ) - - # Compare results in_band_flux = a_band.fluxes_to_bandflux(flux, a_band.processed_transmission_table[:, 0]) - np.allclose(in_band_flux, expected_in_band_flux) - - -def make_passband_group(path): - """Helper function to create a PassbandGroup object for testing.""" - # Initialize requirements for PassbandGroup object - survey = "TEST" - band_labels = ["a", "b", "c"] - table_dir = path / survey - table_dir.mkdir() - - transmission_tables = { - "a": "100 0.5\n200 0.75\n300 0.25\n", - "b": "100 0.25\n200 0.5\n300 0.75\n", - "c": "100 0.75\n200 0.25\n300 0.5\n", - } - for band_label in band_labels: - with open(table_dir / f"{band_label}.dat", "w") as f: - f.write(transmission_tables[band_label]) - - # Load the PassbandGroup object - passbands = [] - for band_label in band_labels: - passbands.append( - Passband(survey, band_label, table_path=table_dir / f"{band_label}.dat", wave_grid=100.0) - ) - return PassbandGroup(passbands=passbands) - - -def test_passband_group_fluxes_to_bandfluxes(tmp_path): - """Test the fluxes_to_bandfluxes method of the PassbandGroup class.""" - test_passband_group = make_passband_group(tmp_path) + np.testing.assert_allclose(in_band_flux, expected_in_band_flux) - # Define some mock flux values and calculate our expected bandfluxes + # Test with a different set of fluxes flux = np.array( [ - [1.0, 1.0, 1.0], - [2.0, 1.0, 1.0], - [3.0, 1.0, 1.0], - [2.0, 1.0, 1.0], - [1.0, 1.0, 1.0], + [100.0, 12.0, 1.0, 0.5, 0.25], + [300.0, 200.0, 100.0, 50.0, 25.0], + [1.0, 500, 1000, 500, 250], + [2.0, 1.0, 1.0, 1.0, 1.0], + [3.0, 1.0, 1.0, 1.0, 1.0], + [200.0, 100.0, 50.0, 25.0, 12.5], + [100.0, 50.0, 25.0, 12.5, 6.25], ] ) - flux_wavelengths = np.array([100, 200, 300]) - - # Compare results - bandfluxes = test_passband_group.fluxes_to_bandfluxes(flux, flux_wavelengths) - for band_name in test_passband_group.passbands: - assert band_name in bandfluxes - assert bandfluxes[band_name].shape == (5,) - assert np.allclose( - bandfluxes[band_name], - np.trapz( - flux * test_passband_group.passbands[band_name].processed_transmission_table[:, 1], - x=flux_wavelengths, - axis=1, - ), - ) - - -def test_passband_set_transmission_table_grid(tmp_path): - """Test the set_transmission_table_to_new_grid method of the PassbandGroup class.""" - # Initialize a Passband object - survey = "TEST" - band_label = "a" - table_path = tmp_path / f"{survey}_{band_label}.dat" - - transmission_table = "100 0.5\n200 0.75\n300 0.25\n400 0.5\n500 0.25\n600 0.5" - with open(table_path, "w") as f: - f.write(transmission_table) - - # Test interpolation is skipped when not needed - a_band = Passband(survey, band_label, table_path=table_path, wave_grid=100.0) - np.testing.assert_allclose(a_band._wave_grid, np.array([100.0, 200.0, 300.0, 400.0, 500.0, 600.0])) - np.testing.assert_allclose( - a_band.processed_transmission_table[:, 0], - np.array([100.0, 200.0, 300.0, 400.0, 500.0, 600.0]), - ) - - # Test that grid is reset successfully AND we have interpolated the transmission table as well - a_band.set_transmission_table_grid(50.0) - np.testing.assert_allclose(a_band._wave_grid, np.arange(100.0, 601.0, 50.0)) - np.testing.assert_allclose( - a_band.processed_transmission_table[:, 0], - np.array([100.0, 150.0, 200.0, 250.0, 300.0, 350.0, 400.0, 450.0, 500.0, 550.0, 600.0]), + flux_wave_grid = np.array([100.0, 150.0, 200.0, 250.0, 300.0]) + a_band.set_transmission_table_grid(flux_wave_grid) + in_band_flux = a_band.fluxes_to_bandflux(flux, flux_wave_grid) + expected_in_band_flux = np.trapz( + flux * a_band.processed_transmission_table[:, 1], x=a_band.processed_transmission_table[:, 0] ) + np.testing.assert_allclose(in_band_flux, expected_in_band_flux) + # Test we raise an error if the fluxes are not the right shape + with pytest.raises(ValueError): + a_band.fluxes_to_bandflux( + np.array([[1.0, 2.0], [3.0, 4.0]]), a_band.processed_transmission_table[:, 0] + ) -def test_passband_group_set_transmission_table_grid(tmp_path): - """Test the set_transmission_table_to_new_grid method of the PassbandGroup class.""" - test_passband_group = make_passband_group(tmp_path) - - # Test that grid is reset successfully AND we have interpolated the transmission table as well - with patch.object(Passband, "set_transmission_table_grid") as mock_set_grid: - # Call the method with a float - test_passband_group.set_transmission_table_grids(50.0) - - # Check that the method was called for each Passband object - assert mock_set_grid.call_count == len(test_passband_group.passbands) - for _ in test_passband_group.passbands: - mock_set_grid.assert_any_call(50.0) - - # Call the method with None - test_passband_group.set_transmission_table_grids(None) - - # Check that the method was called for each Passband object - assert mock_set_grid.call_count == 2 * len(test_passband_group.passbands) - for _ in test_passband_group.passbands: - mock_set_grid.assert_any_call(None) + # Test we raise an error if the fluxes are empty + with pytest.raises(ValueError): + a_band.fluxes_to_bandflux(np.array([]), a_band.processed_transmission_table[:, 0]) From dcd110caeca024508e5a2bf9dfcd834fad4e987b Mon Sep 17 00:00:00 2001 From: Olivia Lynn Date: Mon, 9 Sep 2024 23:25:07 -0400 Subject: [PATCH 21/38] Simplify type-checking logic; revise some docstrings --- src/tdastro/astro_utils/passbands.py | 36 +++++++++++++++------------- 1 file changed, 20 insertions(+), 16 deletions(-) diff --git a/src/tdastro/astro_utils/passbands.py b/src/tdastro/astro_utils/passbands.py index 45155dd5..8b41bcfb 100644 --- a/src/tdastro/astro_utils/passbands.py +++ b/src/tdastro/astro_utils/passbands.py @@ -15,18 +15,18 @@ class PassbandGroup: Attributes ---------- - passbands : dict - A dictionary of Passband objects. Note the keys are the full names of the passbands (eg, "LSST_u"). + passbands : dict of Passband + A dictionary of Passband objects, where the keys are the full_names of the passbands (eg, "LSST_u"). """ - def __init__(self, preset=None, passbands=None): + def __init__(self, preset: str = None, passbands_list: list = None): """Initialize a PassbandGroup object. Parameters ---------- preset : str, optional A pre-defined set of passbands to load. - passbands : list, optional + passbands_list : list, optional A list of Passband objects assigned to the group. """ self.passbands = {} @@ -34,8 +34,8 @@ def __init__(self, preset=None, passbands=None): if preset is not None: self._load_preset(preset) - if passbands is not None: - for passband in passbands: + if passbands_list is not None: + for passband in passbands_list: self.passbands[passband.full_name] = passband def __str__(self) -> str: @@ -105,8 +105,8 @@ def fluxes_to_bandfluxes( Returns ------- - dict - A dictionary of bandfluxes with passband names as keys. + dict of np.ndarray + A dictionary of bandfluxes with passband names as keys and np.ndarrays of bandfluxes as values. """ bandfluxes = {} for full_name, passband in self.passbands.items(): @@ -280,8 +280,12 @@ def _set_wave_grid_attr(self, wave_grid: np.ndarray | float | int | None) -> Non """ if wave_grid is None: self._wave_grid = wave_grid + return - elif isinstance(wave_grid, np.ndarray): + if self._loaded_table is None: + raise ValueError("Transmission table must be loaded before setting wave grid.") + + if isinstance(wave_grid, np.ndarray): # Check that the wave grid is valid if wave_grid.size <= 1: raise ValueError("Wave grid must have at least two values.") @@ -291,8 +295,6 @@ def _set_wave_grid_attr(self, wave_grid: np.ndarray | float | int | None) -> Non raise ValueError("Wave grid must have strictly increasing values.") # Truncate the wave grid to fit the transmission table boundaries - if self._loaded_table is None: - raise ValueError("Transmission table must be loaded before setting wave grid.") lower_bound, upper_bound = self._loaded_table[0, 0], self._loaded_table[-1, 0] lower_index = np.searchsorted(wave_grid, lower_bound, side="left") upper_index = np.searchsorted(wave_grid, upper_bound, side="right") @@ -309,8 +311,6 @@ def _set_wave_grid_attr(self, wave_grid: np.ndarray | float | int | None) -> Non elif isinstance(wave_grid, (float, int)): # Get the bounds of our new grid from the transmission table - if self._loaded_table is None: - raise ValueError("Transmission table must be loaded before setting wave grid.") lower_bound, upper_bound = self._loaded_table[0, 0], self._loaded_table[-1, 0] # Generate new grid; include the original upper bound if step size is divisor of target interval. @@ -512,7 +512,11 @@ def _interpolate_flux_densities( return (flux_density_matrix, flux_wavelengths) def fluxes_to_bandflux( - self, _flux_density_matrix, _flux_wavelengths, extrapolate_mode="raise", spline_degree=1 + self, + _flux_density_matrix: np.ndarray, + _flux_wavelengths: np.ndarray, + extrapolate_mode="raise", + spline_degree=1, ) -> np.ndarray: """Calculate the bandflux for a given set of flux densities. @@ -525,9 +529,9 @@ def fluxes_to_bandflux( Parameters ---------- - flux_density_matrix : np.ndarray + _flux_density_matrix : np.ndarray A 2D array of flux densities where rows are times and columns are wavelengths. - flux_wavelengths : np.ndarray + _flux_wavelengths : np.ndarray An array of wavelengths in Angstroms corresponding to the columns of flux_density_matrix. extrapolate_mode : str, optional The mode of extrapolation to use, passed to scipy.interpolate.InterpolatedUnivariateSpline. From fb4d4d1baff977f86019dd97e906fcc58781ebf8 Mon Sep 17 00:00:00 2001 From: Olivia Lynn Date: Mon, 16 Sep 2024 00:48:21 -0400 Subject: [PATCH 22/38] Update Passband, PassbandGroup to new interface --- src/tdastro/astro_utils/passbands.py | 469 ++++++++---------- .../astro_utils/test_passband_groups.py | 120 ++--- tests/tdastro/astro_utils/test_passbands.py | 374 +++++--------- tests/tdastro/sources/test_snia.py | 198 ++++++++ 4 files changed, 580 insertions(+), 581 deletions(-) create mode 100644 tests/tdastro/sources/test_snia.py diff --git a/src/tdastro/astro_utils/passbands.py b/src/tdastro/astro_utils/passbands.py index 8b41bcfb..1bb9baf9 100644 --- a/src/tdastro/astro_utils/passbands.py +++ b/src/tdastro/astro_utils/passbands.py @@ -1,7 +1,9 @@ import logging import os import socket +import urllib.parse import urllib.request +from typing import Literal, Optional from urllib.error import HTTPError, URLError import numpy as np @@ -17,105 +19,155 @@ class PassbandGroup: ---------- passbands : dict of Passband A dictionary of Passband objects, where the keys are the full_names of the passbands (eg, "LSST_u"). + waves : np.ndarray + The union of all wavelengths in the passbands. """ - def __init__(self, preset: str = None, passbands_list: list = None): + def __init__( + self, + preset: str = None, + passband_parameters: list = None, + delta_wave: float | None = 5.0, + trim_percentile: float | None = 0.1, + ): """Initialize a PassbandGroup object. Parameters ---------- preset : str, optional A pre-defined set of passbands to load. - passbands_list : list, optional - A list of Passband objects assigned to the group. + passband_parameters : list of dict, optional + A list of dictionaries of passband parameters used to create Passband objects. + Each dictionary must contain the following: + - survey : str + - filter_name : str + Dictionaries may also contain the following optional parameters: + - table_path : str + - table_url : str + - delta_wave : float + - trim_percentile : float + - units : str (either 'nm' or 'A') + If survey is not LSST (or other survey with defined defaults), either a table_path or table_url + must be provided. + delta_wave : float | None, optional + The grid step of the wave grid. Default is 5.0. + trim_percentile : float | None, optional + The percentile to trim the transmission table by. For example, if trim_percentile is 0.1, the + transmission table will be trimmed to include only the central 80% of rows. """ self.passbands = {} if preset is not None: - self._load_preset(preset) + self._load_preset(preset, delta_wave, trim_percentile) - if passbands_list is not None: - for passband in passbands_list: + if passband_parameters is not None: + for parameters in passband_parameters: + # TODO maybe check mismatched keys in parameters and group (specifically delta_wave, + # trim_percentile, units.) + passband = Passband(**parameters, delta_wave=delta_wave, trim_percentile=trim_percentile) self.passbands[passband.full_name] = passband + self._update_waves() + def __str__(self) -> str: """Return a string representation of the PassbandGroup.""" return ( f"PassbandGroup containing {len(self.passbands)} passbands: " - f"{', '.join([passband.full_name for passband in self.passbands.values()])}" + f"{', '.join(self.passbands.keys())}" ) - def _load_preset(self, preset: str) -> None: + def _load_preset(self, preset: str, delta_wave: float | None, trim_percentile: float | None) -> None: """Load a pre-defined set of passbands. Parameters ---------- preset : str The name of the pre-defined set of passbands to load. + delta_wave : float | None + The grid step of the wave grid. + trim_percentile : float | None + The percentile to trim the transmission table by. """ if preset == "LSST": self.passbands = { - "LSST_u": Passband("LSST", "u"), - "LSST_g": Passband("LSST", "g"), - "LSST_r": Passband("LSST", "r"), - "LSST_i": Passband("LSST", "i"), - "LSST_z": Passband("LSST", "z"), - "LSST_y": Passband("LSST", "y"), + "LSST_u": Passband("LSST", "u", delta_wave=delta_wave, trim_percentile=trim_percentile), + "LSST_g": Passband("LSST", "g", delta_wave=delta_wave, trim_percentile=trim_percentile), + "LSST_r": Passband("LSST", "r", delta_wave=delta_wave, trim_percentile=trim_percentile), + "LSST_i": Passband("LSST", "i", delta_wave=delta_wave, trim_percentile=trim_percentile), + "LSST_z": Passband("LSST", "z", delta_wave=delta_wave, trim_percentile=trim_percentile), + "LSST_y": Passband("LSST", "y", delta_wave=delta_wave, trim_percentile=trim_percentile), } else: raise ValueError(f"Unknown passband preset: {preset}") - def set_transmission_table_grids(self, wave_grid: float | int | None) -> None: - """Set the wave grid attribute for all passbands in the group. + def _update_waves(self) -> None: + """Update the group's wave attribute to be the union of all wavelengths in the passbands.""" + if len(self.passbands) == 0: + self.waves = np.array([]) + else: + self.waves = np.unique(np.concatenate([passband.waves for passband in self.passbands.values()])) + + def process_transmission_tables( + self, delta_wave: float | None = 5.0, trim_percentile: float | None = 0.1 + ): + """Process the transmission tables for all passbands in the group; recalculate group's wave attribute. Parameters ---------- - wave_grid : float | int | None - The grid of wavelengths (Angstrom) to which the flux density matrix and transmission table should - be interpolated. If a float or int is given, wave_grid will be converted to a numpy array with a - wave_grid step matching the boundaries of the transmission table. If None, the transmission table - will later be interpolated to a grid with the same boundaries, but matching the step of the flux - density matrix. + delta_wave : float | None, optional + The grid step of the wave grid. Default is 5.0. + trim_percentile : float | None, optional + The percentile to trim the transmission table by. For example, if trim_percentile is 0.1, the + transmission table will be trimmed to include only the central 80% of rows. """ - for _, passband in self.passbands.items(): - passband.set_transmission_table_grid(wave_grid) + for passband in self.passbands.values(): + passband.process_transmission_table(delta_wave, trim_percentile) - def fluxes_to_bandfluxes( - self, - flux_density_matrix: np.ndarray, - flux_wavelengths: np.ndarray, - extrapolate_mode: str = "raise", - spline_degree: int = 1, - ) -> np.ndarray: + self._update_waves() + + def fluxes_to_bandfluxes(self, flux_density_matrix: np.ndarray) -> np.ndarray: """Calculate bandfluxes for all passbands in the group. Parameters ---------- flux_density_matrix : np.ndarray A 2D array of flux densities where rows are times and columns are wavelengths. - flux_wavelengths : np.ndarray - An array of wavelengths in Angstroms corresponding to the columns of flux_density_matrix. - extrapolate_mode : str, optional - The mode of extrapolation to use, passed to scipy.interpolate.InterpolatedUnivariateSpline. - Default is "raise", which will raise a ValueError if the interpolation goes out of bounds. Other - options are "const" (pads with boundary value) and "zeros" (pads with 0). - spline_degree : int, optional - The degree of the spline to use for interpolation; must be 1 <= spline_degree <= 5. Default is 1, - which is linear interpolation. Returns ------- dict of np.ndarray A dictionary of bandfluxes with passband names as keys and np.ndarrays of bandfluxes as values. """ + if flux_density_matrix.size == 0 or len(self.waves) != len(flux_density_matrix[0]): + raise ValueError( + f"PassbandGroup mismatched grids: Flux density matrix has {len(flux_density_matrix[0])} " + f"columns, which does not match transmission table's {len(self.waves)} rows. Check that the " + f"flux density matrix was calculated on the same grid as the transmission tables, which can " + f"be accessed via the Passband's or PassbandGroup's waves attribute." + ) + bandfluxes = {} + group_has_regular_grid_step = np.allclose(np.diff(self.waves), np.diff(self.waves)[0]) + # TODO this will never work, because the wavelengths are not the same for all passbands--so there will + # always be a big jump between passbands + # TODO in general there's a better algorithm to find the indices of the wavelengths in the passband + # where we first figure out which passbands the wavelengths are in, and then find the indices in the + # target passbands. we shouldn't blindly search through the whole group's waves like this. + for full_name, passband in self.passbands.items(): - bandfluxes[full_name] = passband.fluxes_to_bandflux( - flux_density_matrix, - flux_wavelengths, - extrapolate_mode=extrapolate_mode, - spline_degree=spline_degree, - ) + # We only want the fluxes that are in the passband's wavelength range + if group_has_regular_grid_step: + lower, upper = passband.waves[0], passband.waves[-1] + lower_index, upper_index = np.searchsorted(self.waves, [lower, upper]) + in_band_fluxes = flux_density_matrix[:, lower_index:upper_index] + else: + indices = np.unique(np.searchsorted(passband.waves, self.waves)) + if indices[-1] == len(passband.waves): + indices = indices[:-1] + in_band_fluxes = flux_density_matrix[:, indices] + + bandfluxes[full_name] = passband.fluxes_to_bandflux(in_band_fluxes) + print() return bandfluxes @@ -130,13 +182,12 @@ class Passband: The name of the passband's filter: eg, "u". full_name : str The full name of the passband. This is the survey and filter concatenated: eg, "LSST_u". - _wave_grid : np.ndarray | float | None - The grid of wavelengths (Angstrom) to which the flux density matrix and transmission table should be - interpolated. Use the _set_wave_grid_attr method to set this value. Default step is 5.0. table_path : str The path to the transmission table file. table_url : str The URL to download the transmission table file. + waves : np.ndarray + The wavelengths of the transmission table. _loaded_table : np.ndarray A 2D array of wavelengths and transmissions. This is the table loaded from the file, and is neither interpolated nor normalized. @@ -149,9 +200,11 @@ def __init__( self, survey: str, filter_name: str, - wave_grid: float = 5.0, + delta_wave: float | None = 5.0, + trim_percentile: float | None = 0.1, table_path: str | None = None, table_url: str | None = None, + units: Optional[Literal["nm", "A"]] = "A", ): """Initialize a Passband object. @@ -161,18 +214,25 @@ def __init__( The survey to which the passband belongs: eg, "LSST". filter_name : str The filter_name of the passband: eg, "u". - wave_grid : np.ndarray | float | int | None, optional - The grid of wavelengths (Angstrom) to which the flux density matrix and transmission table should - be interpolated. A float or int will be converted to a numpy array with a grid step matching the - boundaries of the transmission table. If None, the transmission table will later be interpolated - to a grid maintaining the same boundaries, but matching the step of the flux density matrix. - Default is 5.0. + delta_wave : float | None, optional + The grid step of the wave grid. Default is 5.0. + trim_percentile : float | None, optional + The percentile to trim the transmission table by. For example, if trim_percentile is 0.1, the + transmission table will be trimmed to include only the central 80% of the area under the + transmission curve. + waves : np.ndarray + The wavelengths of the transmission table. To be used when evaluating models to generate fluxes + that will be passed to fluxes_to_bandflux. table_path : str, optional The path to the transmission table file. If None, the table path will be set to a default path; if no file exists at this location, the file will be downloaded from table_url. table_url : str, optional The URL to download the transmission table file. If None, the table URL will be set to a default URL based on the survey and filter_name. Default is None. + units : Literal['nm','A'], optional + Denotes whether the wavelength units of the table are nanometers ('nm') or Angstroms ('A'). + By default 'A'. Does not affect the output units of the class, only the interpretation of the + provided passband table. """ self.survey = survey self.filter_name = filter_name @@ -180,10 +240,17 @@ def __init__( self.table_path = table_path self.table_url = table_url + self.units = units self._load_transmission_table() - self._set_wave_grid_attr(wave_grid) - self._process_transmission_table() + self.process_transmission_table(delta_wave, trim_percentile) + # interpolated_table = self._interpolate_transmission_table(self._loaded_table, delta_wave) + # trimmed_table = self._trim_transmission_by_percentile(interpolated_table, trim_percentile) + # self._normalize_transmission_table(trimmed_table) + + # previous implementation: + # self._set_wave_grid_attr(wave_grid) + # self._process_transmission_table() def __str__(self) -> str: """Return a string representation of the Passband.""" @@ -221,6 +288,12 @@ def _load_transmission_table(self) -> None: if not np.all(np.diff(loaded_table[:, 0]) > 0): raise ValueError("Wavelengths in transmission table must be strictly increasing.") + # Correct for units + if self.units == "nm": + loaded_table[ + :, 0 + ] *= 10.0 # Multiply the first column (wavelength) by 10.0 to convert to Angstroms + self._loaded_table = loaded_table def _download_transmission_table(self) -> bool: @@ -238,8 +311,7 @@ def _download_transmission_table(self) -> bool: """ if self.table_url is None: if self.survey == "LSST": - # Consider: https://github.com/lsst/throughputs/blob/main/baseline/filter_g.dat - # Or check with Mi's link (unless that was above) + # TODO switch to files at: https://github.com/lsst/throughputs/blob/main/baseline/total_g.dat self.table_url = ( f"http://svo2.cab.inta-csic.es/svo/theory/fps3/getdata.php" f"?format=ascii&id=LSST/LSST.{self.filter_name}" @@ -250,6 +322,7 @@ def _download_transmission_table(self) -> bool: ) try: socket.setdefaulttimeout(10) + logging.info(f"Retrieving {self.table_url}", flush=True) urllib.request.urlretrieve(self.table_url, self.table_path) if os.path.getsize(self.table_path) == 0: logging.error(f"Transmission table downloaded for {self.full_name} is empty.") @@ -264,122 +337,103 @@ def _download_transmission_table(self) -> bool: logging.error(f"URL error occurred when downloading table for {self.full_name}: {e}") return False - def _set_wave_grid_attr(self, wave_grid: np.ndarray | float | int | None) -> None: - """Set the wave grid attribute. Keeps _wave_grid as None or array-type, even when set with a float. - - Note: this only sets the attribute; it does NOT process transmission table. Use - set_transmission_table_grid to set the attribute and process the transmission table in one step. + def process_transmission_table(self, delta_wave: float | None = 5.0, trim_percentile: float | None = 0.1): + """Process the transmission table. Parameters ---------- - wave_grid : np.ndarray | float | int | None - The grid of wavelengths (Angstrom) to which the flux density matrix and transmission table should - be interpolated. A float or int will be converted to a numpy array with a grid step matching the - boundaries of the transmission table. If None, the transmission table will later be interpolated - to a grid maintaining the same boundaries, but matching the step of the flux density matrix. + delta_wave : float | None, optional + The grid step of the wave grid. Default is 5.0 Angstroms. + trim_percentile : float | None, optional + The percentile to trim the transmission table by. For example, if trim_percentile is 0.1, the + transmission table will be trimmed to include only the central 80% of rows. """ - if wave_grid is None: - self._wave_grid = wave_grid - return - - if self._loaded_table is None: - raise ValueError("Transmission table must be loaded before setting wave grid.") - - if isinstance(wave_grid, np.ndarray): - # Check that the wave grid is valid - if wave_grid.size <= 1: - raise ValueError("Wave grid must have at least two values.") - elif wave_grid.ndim != 1: - raise ValueError("Wave grid must be a 1D array.") - elif not np.all(np.diff(wave_grid) > 0): - raise ValueError("Wave grid must have strictly increasing values.") - - # Truncate the wave grid to fit the transmission table boundaries - lower_bound, upper_bound = self._loaded_table[0, 0], self._loaded_table[-1, 0] - lower_index = np.searchsorted(wave_grid, lower_bound, side="left") - upper_index = np.searchsorted(wave_grid, upper_bound, side="right") - wave_grid = wave_grid[lower_index:upper_index] - if wave_grid.size <= 1: - raise ValueError( - "Wave grid has fewer than two values after truncation to fit within the transmission " - "table's boundaries." - ) - # TODO If I'm truncating here, should I also interpolate? at that point, why let them give - # an array at all? ask about this in the morning. + # TODO do we want to store delta_wave and trim_percentile as attributes? + interpolated_table = self._interpolate_transmission_table(self._loaded_table, delta_wave) + trimmed_table = self._trim_transmission_by_percentile(interpolated_table, trim_percentile) + self.processed_transmission_table = self._normalize_transmission_table(trimmed_table) - self._wave_grid = wave_grid + self.waves = self.processed_transmission_table[:, 0] - elif isinstance(wave_grid, (float, int)): - # Get the bounds of our new grid from the transmission table - lower_bound, upper_bound = self._loaded_table[0, 0], self._loaded_table[-1, 0] - - # Generate new grid; include the original upper bound if step size is divisor of target interval. - # We use linspace instead of arange, as numpy recommends this for non-integer step sizes; plus, - # arange generates values within a half-open interval, and we usually want the upper bound. - self._wave_grid = np.linspace( - lower_bound, upper_bound, int((upper_bound - lower_bound) / wave_grid) + 1 - ) - - else: - raise ValueError("Wave grid must be a 1D numpy array, float, int, or None.") - - def set_transmission_table_grid(self, new_wave_grid: np.ndarray | float | int | None) -> None: - """Updates _wave_grid attr and sets the transmission table to the new grid. + def _interpolate_transmission_table(self, table: np.ndarray, delta_wave: float | None) -> np.ndarray: + """Interpolate the transmission table to a new wave grid. Parameters ---------- - new_wave_grid : np.ndarray | float | int | None - The grid of wavelengths (Angstrom) to which the flux density matrix and transmission table should - be interpolated. A float or int will be converted to a numpy array with a grid step matching the - boundaries of the transmission table. If None, the transmission table will later be interpolated - to a grid maintaining the same boundaries, but matching the step of the flux density matrix. + table : np.ndarray + A 2D array of wavelengths and transmissions. + delta_wave : float | None + The grid step of the wave grid. Default is 5.0 Angstroms. + + Returns + ------- + np.ndarray + A 2D array of wavelengths and transmissions. """ - self._set_wave_grid_attr(new_wave_grid) - self._process_transmission_table() + # Don't interpolate if delta_wave is None or the table is already on the desired grid + if delta_wave is None: + return table + if np.allclose(np.diff(table[:, 0]), delta_wave): + return table + + # Regrid wavelengths to the new wave grid + wavelengths = table[:, 0] + lower_bound, upper_bound = wavelengths[0], wavelengths[-1] + new_wavelengths = np.linspace( + lower_bound, upper_bound, int((upper_bound - lower_bound) / delta_wave) + 1 + ) - def _process_transmission_table(self) -> None: - """Process the transmission table: downsample or interpolate, then normalize.""" - interpolated_transmissions = self._interpolate_or_downsample_transmission_table(self._loaded_table) - normalized_transmissions = self._normalize_interpolated_transmission_table(interpolated_transmissions) - self.processed_transmission_table = normalized_transmissions + # Interpolate the transmission table to the new wave grid + spline = scipy.interpolate.InterpolatedUnivariateSpline(table[:, 0], table[:, 1], ext="raise", k=1) + interpolated_transmissions = spline(new_wavelengths) + return np.column_stack((new_wavelengths, interpolated_transmissions)) - def _interpolate_or_downsample_transmission_table(self, transmission_table: np.ndarray) -> np.ndarray: - """Interpolate or downsample a transmission table to a desired grid. + def _trim_transmission_by_percentile( + self, table: np.ndarray, trim_percentile: float | None + ) -> np.ndarray: + """Trim the transmission table such that it only includes the central (1 - 2*trim_percentile) of rows. - Note that if self._wave_grid is None, this method will return the original transmission table, as - we will later interpolate the transmission table to match the flux density matrix. + E.g., if trim_percentile is 0.1, the transmission table will be trimmed to include only the central + 80% of rows. Parameters ---------- - transmission_table : np.ndarray + table : np.ndarray A 2D array of wavelengths and transmissions. + trim_percentile : float + The percentile to trim the transmission table by. For example, if trim_percentile is 0.1, the + transmission table will be trimmed to include only the central 80% of rows. Returns ------- np.ndarray A 2D array of wavelengths and transmissions. - - Raises - ------ - ValueError - If the transmission table does not have exactly 2 columns. """ - if self._wave_grid is None: - return transmission_table + if trim_percentile is None: + return table + if trim_percentile < 0 or trim_percentile > 0.5: + raise ValueError("Trim percentile must be between 0 and 0.5.") - if isinstance(self._wave_grid, (float, int)): - self._set_wave_grid_attr(self._wave_grid) + # Separate wavelengths and transmissions + wavelengths = table[:, 0] + transmissions = table[:, 1] - if transmission_table.shape[1] != 2: - raise ValueError("Transmission table must have exactly 2 columns.") + # Calculate the cumulative sum of the transmission values (area under the curve) + cumulative_area = scipy.integrate.cumulative_trapezoid(transmissions, x=wavelengths) - spline = scipy.interpolate.InterpolatedUnivariateSpline( - transmission_table[:, 0], transmission_table[:, 1], ext="raise", k=1 - ) - interpolated_transmissions = spline(self._wave_grid) - return np.column_stack((self._wave_grid, interpolated_transmissions)) + # Normalize cumulative area to range from 0 to 1 + cumulative_area /= cumulative_area[-1] - def _normalize_interpolated_transmission_table(self, transmission_table: np.ndarray) -> np.ndarray: + # Find indices where the cumulative area exceeds the trim percentiles + lower_bound = np.searchsorted(cumulative_area, trim_percentile) + upper_bound = np.searchsorted(cumulative_area, 1 - trim_percentile) + + # Trim the table to the desired range + trimmed_table = table[lower_bound : upper_bound + 1] + + return trimmed_table + + def _normalize_transmission_table(self, transmission_table: np.ndarray) -> np.ndarray: """Calculate the value of phi_b for all wavelengths in a transmission table. This is eq. 8 from "On the Choice of LSST Flux Units" (Ivezić et al.): @@ -427,96 +481,9 @@ def _normalize_interpolated_transmission_table(self, transmission_table: np.ndar normalized_transmissions = numerators / denominator return np.column_stack((wavelengths_angstrom, normalized_transmissions)) - def _interpolate_flux_densities( - self, - _flux_density_matrix: np.ndarray, - _flux_wavelengths: np.ndarray, - extrapolate_mode: str = "raise", - spline_degree: int = 1, - ) -> tuple: - """Interpolate the flux density matrix to match the transmission table, which matches self._wave_grid. - - Parameters - ---------- - _flux_density_matrix : np.ndarray - A 2D array of flux densities where rows are times and columns are wavelengths. - _flux_wavelengths : np.ndarray - An array of wavelengths in Angstroms corresponding to the columns of _flux_density_matrix. - extrapolate_mode : str, optional - The mode of extrapolation to use, passed to scipy.interpolate.InterpolatedUnivariateSpline. - Default is "raise", which will raise a ValueError if the interpolation goes out of bounds. Other - options are "const" (pads with boundary value) and "zeros" (pads with 0). - spline_degree : int, optional - The degree of the spline to use for interpolation; must be 1 <= spline_degree <= 5. Default is 1, - which is linear interpolation. - - Returns - ------- - tuple - A tuple containing the interpolated flux density matrix and interpolated wavelengths. - - Raises - ------ - ValueError - If the wavelengths in the flux density matrix are not strictly increasing, if the spline degree is - invalid, or if the _wave_grid attribute is not set and the flux density matrix wavelengths (which - would then be used to determine the grid step) do not have a uniform step. - """ - # Make sure all given wavelengths are strictly increasing - if not np.all(np.diff(_flux_wavelengths) > 0): - raise ValueError("Wavelengths corresponding to flux density matrix must be strictly increasing.") - - # Make sure the degree of the spline is valid - if (spline_degree < 1) or (spline_degree > 5): - raise ValueError("Spline degree must be between 0 and 5.") - elif spline_degree > len(_flux_wavelengths): - raise ValueError( - "Spline degree is greater than the number of wavelengths. Add more wavelengths to the flux " - "density matrix or reduce the spline_degree parameter." - ) - - # Make sure the wave grid we're interpolating to is an array (if not None) - if isinstance(self._wave_grid, (float, int)): - self._set_wave_grid_attr(self._wave_grid) - - # If wave grid is None, use the flux density matrix's grid step to interpolate the transmission table - elif self._wave_grid is None: - if not np.allclose(np.diff(_flux_wavelengths), np.diff(_flux_wavelengths)[0]): - raise ValueError( - "Flux density wavelengths must have a uniform step to interpolate transmission to match. " - "Alternatively, provide a target grid step with the set_transmission_table_grid method." - ) - # Update transmission table step to match the flux density matrix step - # (but keep the same transmission table boundaries) - flux_grid_step = np.diff(_flux_wavelengths)[0] - self.set_transmission_table_grid(flux_grid_step) - - # Interpolate the flux density matrix - if not np.array_equal(_flux_wavelengths, self._wave_grid): - # Initialize an array to store interpolated flux densities - interpolated_flux_density_matrix = np.empty((len(_flux_density_matrix), len(self._wave_grid))) - - # Interpolate each row individually - for i, row in enumerate(_flux_density_matrix): - spline = scipy.interpolate.InterpolatedUnivariateSpline( - _flux_wavelengths, row, ext=extrapolate_mode, k=spline_degree - ) - interpolated_flux_density_matrix[i, :] = spline(self._wave_grid) - - flux_density_matrix = interpolated_flux_density_matrix - flux_wavelengths = self._wave_grid - else: - flux_density_matrix = _flux_density_matrix - flux_wavelengths = _flux_wavelengths - - return (flux_density_matrix, flux_wavelengths) - def fluxes_to_bandflux( self, - _flux_density_matrix: np.ndarray, - _flux_wavelengths: np.ndarray, - extrapolate_mode="raise", - spline_degree=1, + flux_density_matrix: np.ndarray, ) -> np.ndarray: """Calculate the bandflux for a given set of flux densities. @@ -529,31 +496,27 @@ def fluxes_to_bandflux( Parameters ---------- - _flux_density_matrix : np.ndarray + flux_density_matrix : np.ndarray A 2D array of flux densities where rows are times and columns are wavelengths. - _flux_wavelengths : np.ndarray - An array of wavelengths in Angstroms corresponding to the columns of flux_density_matrix. - extrapolate_mode : str, optional - The mode of extrapolation to use, passed to scipy.interpolate.InterpolatedUnivariateSpline. - Default is "raise", which will raise a ValueError if the interpolation goes out of bounds. Other - options are "const" (pads with boundary value) and "zeros" (pads with 0). - spline_degree : int, optional - The degree of the spline to use for interpolation; must be 1 <= spline_degree <= 5. Default is 1, - which is linear interpolation. Returns ------- np.ndarray - An array of bandfluxes. + An array of bandfluxes with length flux_density_matrix, where each element is the bandflux + at the corresponding time. """ - # Interpolate flux density matrix to match the transmission table, which matches self._wave_grid - flux_density_matrix, flux_wavelengths = self._interpolate_flux_densities( - _flux_density_matrix, _flux_wavelengths, extrapolate_mode, spline_degree - ) + if flux_density_matrix.size == 0 or len(self.waves) != len(flux_density_matrix[0]): + raise ValueError( + f"Passband mismatched grids: Flux density matrix has {len(flux_density_matrix[0])} " + f"columns, which does not match the {len(self.waves)} rows in band {self.full_name}'s " + f"transmission table. Check that the flux density matrix was calculated on the same grid as " + f"the transmission tables, which can be accessed via the Passband's or PassbandGroup's waves " + f"attribute." + ) # Calculate the bandflux as ∫ f(λ)φ_b(λ) dλ, # where f(λ) is the in-band flux density and φ_b(λ) is the normalized system response integrand = flux_density_matrix * self.processed_transmission_table[:, 1] - bandfluxes = scipy.integrate.trapezoid(integrand, x=flux_wavelengths) + bandfluxes = scipy.integrate.trapezoid(integrand, x=self.waves) return bandfluxes diff --git a/tests/tdastro/astro_utils/test_passband_groups.py b/tests/tdastro/astro_utils/test_passband_groups.py index 0837f51c..7e700636 100644 --- a/tests/tdastro/astro_utils/test_passband_groups.py +++ b/tests/tdastro/astro_utils/test_passband_groups.py @@ -4,11 +4,11 @@ from tdastro.astro_utils.passbands import Passband, PassbandGroup -def create_passband_group(path): +def create_passband_group(path, delta_wave=5.0, trim_percentile=None): """Helper function to create a PassbandGroup object for testing.""" # Initialize requirements for PassbandGroup object survey = "TEST" - band_labels = ["a", "b", "c"] + filter_names = ["a", "b", "c"] table_dir = path / survey table_dir.mkdir() @@ -17,17 +17,23 @@ def create_passband_group(path): "b": "100 0.25\n200 0.5\n300 0.75\n", "c": "100 0.75\n200 0.25\n300 0.5\n", } - for band_label in band_labels: - with open(table_dir / f"{band_label}.dat", "w") as f: - f.write(transmission_tables[band_label]) + for filter_name in filter_names: + with open(table_dir / f"{filter_name}.dat", "w") as f: + f.write(transmission_tables[filter_name]) # Load the PassbandGroup object passbands = [] - for band_label in band_labels: + for filter_name in filter_names: passbands.append( - Passband(survey, band_label, table_path=table_dir / f"{band_label}.dat", wave_grid=100.0) + { + "survey": survey, + "filter_name": filter_name, + "table_path": table_dir / f"{filter_name}.dat", + "delta_wave": delta_wave, + "trim_percentile": trim_percentile, + } ) - return PassbandGroup(passbands=passbands) + return PassbandGroup(passband_parameters=passbands) def test_passband_group_init(): @@ -56,11 +62,11 @@ def mock_load_transmission_table(self): # Test that the PassbandGroup class can be initialized with a list of Passband objects with patch.object(Passband, "_load_transmission_table", new=mock_load_transmission_table): lsst_gri_passbands = [ - Passband("LSST", "g"), - Passband("LSST", "r"), - Passband("LSST", "i"), + {"survey": "LSST", "filter_name": "g"}, + {"survey": "LSST", "filter_name": "r"}, + {"survey": "LSST", "filter_name": "i"}, ] - lsst_gri_passband_group = PassbandGroup(passbands=lsst_gri_passbands) + lsst_gri_passband_group = PassbandGroup(passband_parameters=lsst_gri_passbands) assert len(lsst_gri_passband_group.passbands) == 3 assert "LSST_g" in lsst_gri_passband_group.passbands assert "LSST_r" in lsst_gri_passband_group.passbands @@ -92,62 +98,44 @@ def test_passband_group_str(tmp_path): assert str(test_passband_group) == "PassbandGroup containing 3 passbands: TEST_a, TEST_b, TEST_c" -def test_passband_group_set_transmission_table_grid(tmp_path): - """Test the set_transmission_table_to_new_grid method of the PassbandGroup class.""" - test_passband_group = create_passband_group(tmp_path) - - # Test that grid is reset successfully AND we have called interpolation methods the transmission table - with patch.object(Passband, "set_transmission_table_grid") as mock_set_grid: - # Call the method with a float - test_passband_group.set_transmission_table_grids(50.0) - - # Check that the method was called for each Passband object - assert mock_set_grid.call_count == len(test_passband_group.passbands) - for _ in test_passband_group.passbands: - mock_set_grid.assert_any_call(50.0) - - # Call the method with None - test_passband_group.set_transmission_table_grids(None) - - # Check that the method was called for each Passband object - assert mock_set_grid.call_count == 2 * len(test_passband_group.passbands) - for _ in test_passband_group.passbands: - mock_set_grid.assert_any_call(None) - - def test_passband_group_fluxes_to_bandfluxes(tmp_path): """Test the fluxes_to_bandfluxes method of the PassbandGroup class.""" # Test with empty passband group - empty_passband_group = PassbandGroup() - flux = np.array([[1.0, 1.0, 1.0], [2.0, 1.0, 1.0], [3.0, 1.0, 1.0]]) - flux_wavelengths = np.array([100, 200, 300]) - bandfluxes = empty_passband_group.fluxes_to_bandfluxes(flux, flux_wavelengths) - assert len(bandfluxes) == 0 + # empty_passband_group = PassbandGroup() + # flux = np.array([[1.0, 1.0, 1.0], [2.0, 1.0, 1.0], [3.0, 1.0, 1.0]]) + # flux_wavelengths = np.array([100, 200, 300]) + # bandfluxes = empty_passband_group.fluxes_to_bandfluxes(flux) + # assert len(bandfluxes) == 0 # Test with simple passband group - test_passband_group = create_passband_group(tmp_path) - flux = np.array( - [ - [1.0, 1.0, 1.0], - [2.0, 1.0, 1.0], - [3.0, 1.0, 1.0], - [2.0, 1.0, 1.0], - [1.0, 1.0, 1.0], - ] - ) - flux_wavelengths = np.array([100, 200, 300]) - bandfluxes = test_passband_group.fluxes_to_bandfluxes(flux, flux_wavelengths) - - # Check values are as expected - assert len(bandfluxes) == 3 - for band_name in test_passband_group.passbands: - assert band_name in bandfluxes - assert bandfluxes[band_name].shape == (5,) - assert np.allclose( - bandfluxes[band_name], - np.trapz( - flux * test_passband_group.passbands[band_name].processed_transmission_table[:, 1], - x=flux_wavelengths, - axis=1, - ), - ) + test_passband_group = create_passband_group(tmp_path, delta_wave=20, trim_percentile=None) + print(test_passband_group) + print(test_passband_group.waves) + for band in test_passband_group.passbands: + print(band) + print(test_passband_group.passbands[band].waves) + # flux = np.array( + # [ + # [1.0, 1.0, 1.0], + # [2.0, 1.0, 1.0], + # [3.0, 1.0, 1.0], + # [2.0, 1.0, 1.0], + # [1.0, 1.0, 1.0], + # ] + # ) + # flux_wavelengths = np.array([100, 200, 300]) + # bandfluxes = test_passband_group.fluxes_to_bandfluxes(flux, flux_wavelengths) + + # # Check values are as expected + # assert len(bandfluxes) == 3 + # for band_name in test_passband_group.passbands: + # assert band_name in bandfluxes + # assert bandfluxes[band_name].shape == (5,) + # assert np.allclose( + # bandfluxes[band_name], + # np.trapz( + # flux * test_passband_group.passbands[band_name].processed_transmission_table[:, 1], + # x=flux_wavelengths, + # axis=1, + # ), + # ) diff --git a/tests/tdastro/astro_utils/test_passbands.py b/tests/tdastro/astro_utils/test_passbands.py index 4e90233e..88c3d055 100644 --- a/tests/tdastro/astro_utils/test_passbands.py +++ b/tests/tdastro/astro_utils/test_passbands.py @@ -31,8 +31,7 @@ def mock_load_transmission_table(self): # Cannot check table_path as we have mocked the method that sets it; see unit test for loading tables assert a_band.table_url is None np.testing.assert_allclose(a_band._loaded_table, transmission_table_array) - assert isinstance(a_band._wave_grid, np.ndarray) - assert a_band.processed_transmission_table is not None + assert a_band.waves is not None def create_test_passband(path, transmission_table, filter_name="a", **kwargs): @@ -112,126 +111,132 @@ def mock_urlretrieve(url, filename, *args, **kwargs): # Urlretrieve saves conte np.testing.assert_allclose(a_band._loaded_table, np.array([[1000, 0.5], [1005, 0.6], [1010, 0.7]])) -def test_passband_set_wave_grid_attr(tmp_path): - """Test the _set_wave_grid_attr method of the Passband class.""" +def test_process_transmission_table(tmp_path): + """Test the process_transmission_table method of the Passband class; check correct methods are called.""" transmission_table = "100 0.5\n200 0.75\n300 0.25\n" - a_band = create_test_passband(tmp_path, transmission_table, wave_grid=100) - - # Test that the wave grid is set correctly - a_band._set_wave_grid_attr(50.0) - np.testing.assert_allclose(a_band._wave_grid, np.arange(100.0, 301.0, 50.0)) - - # Test that the wave grid is reset correctly - a_band._set_wave_grid_attr(100.0) - np.testing.assert_allclose(a_band._wave_grid, np.array([100.0, 200.0, 300.0])) + a_band = create_test_passband(tmp_path, transmission_table) - # Test that we can set the wave grid with None - a_band._set_wave_grid_attr(None) - assert a_band._wave_grid is None + # Mock the methods that _process_transmission_table wraps, to check each is called once + with ( + patch.object(a_band, "_interpolate_transmission_table") as mock_interp_table, + patch.object(a_band, "_trim_transmission_by_percentile") as mock_trim_table, + patch.object(a_band, "_normalize_transmission_table") as mock_norm_table, + ): + # Call the _process_transmission_table method + delta_wave, trim_percentile = 1.0, 0.05 + a_band.process_transmission_table(delta_wave, trim_percentile) - # Test we can be lazy and set the wave grid with just an integer - a_band._set_wave_grid_attr(100) - np.testing.assert_allclose(a_band._wave_grid, np.array([100.0, 200.0, 300.0])) + # Check that each method is called once + mock_interp_table.assert_called_once_with(a_band._loaded_table, delta_wave) + mock_trim_table.assert_called_once() + mock_norm_table.assert_called_once() - # Test that we can set the wave grid with a numpy array - # Note, we truncate given grid to fit transmission table bounds - a_band._set_wave_grid_attr(np.array([100.0, 150.0, 200.0, 250.0, 300.0, 350.0, 400.0])) - np.testing.assert_allclose(a_band._wave_grid, np.array([100.0, 150.0, 200.0, 250.0, 300.0])) + # Now call without mocking, to check waves set correctly (other values checked in method-specific tests) + delta_wave, trim_percentile = 5.0, None + a_band.process_transmission_table(delta_wave, trim_percentile) + np.testing.assert_allclose(a_band.waves, np.arange(100, 301, delta_wave)) - # Test that we raise an error if the wave grid is not sorted - with pytest.raises(ValueError): - a_band._set_wave_grid_attr(np.array([100.0, 300.0, 200.0])) - # Test that we raise an error if the wave grid is not 1D - with pytest.raises(ValueError): - a_band._set_wave_grid_attr(np.array([[100.0, 200.0], [300.0, 400.0]])) +def test_interpolate_transmission_table(tmp_path): + """Test the _interpolate_transmission_table method of the Passband class.""" + transmission_table = "100 0.5\n200 0.75\n300 0.25\n" + a_band = create_test_passband(tmp_path, transmission_table) - # Test we raise an error if wave grid is only one value - with pytest.raises(ValueError): - a_band._set_wave_grid_attr(np.array([100.0])) + # Interpolate the transmission table to a large step size (50 Angstrom) + table = a_band._interpolate_transmission_table(a_band._loaded_table, delta_wave=50) + np.testing.assert_allclose(table[:, 0], np.arange(100, 301, 50)) - # Test we raise an error if wave grid is empty - with pytest.raises(ValueError): - a_band._set_wave_grid_attr(np.array([])) + # Interpolate the transmission table to a somewhat small step size (1 Angstrom) + table = a_band._interpolate_transmission_table(a_band._loaded_table, delta_wave=1) + np.testing.assert_allclose(table[:, 0], np.arange(100, 301, 1)) + # Interpolate the transmission table to an even smaller step size (0.1 Angstrom) + table = a_band._interpolate_transmission_table(a_band._loaded_table, delta_wave=0.1) + np.testing.assert_allclose(table[:, 0], np.arange(100, 300.01, 0.1)) -def test_passband_set_transmission_table_grid(tmp_path): - """Test the set_transmission_table_to_new_grid method of the PassbandGroup class.""" - transmission_table = "100 0.5\n200 0.75\n300 0.25\n400 0.5\n500 0.25\n600 0.5" - # Test case where interpolation is not needed - a_band = create_test_passband(tmp_path, transmission_table, wave_grid=100) - np.testing.assert_allclose(a_band._wave_grid, np.array([100.0, 200.0, 300.0, 400.0, 500.0, 600.0])) - np.testing.assert_allclose( - a_band.processed_transmission_table[:, 0], - np.array([100.0, 200.0, 300.0, 400.0, 500.0, 600.0]), - ) +def test_trim_transmission_table(tmp_path): + """Test the _trim_transmission_by_percentile method of the Passband class.""" - # Test that grid is reset successfully AND we have interpolated the transmission table as well - a_band.set_transmission_table_grid(50.0) - np.testing.assert_allclose(a_band._wave_grid, np.arange(100.0, 601.0, 50.0)) - np.testing.assert_allclose( - a_band.processed_transmission_table[:, 0], - np.array([100.0, 150.0, 200.0, 250.0, 300.0, 350.0, 400.0, 450.0, 500.0, 550.0, 600.0]), - ) + # Test: transmission table with only 3 points + transmission_table = "100 0.5\n200 0.75\n300 0.25\n" + a_band = create_test_passband(tmp_path, transmission_table) + # Trim the transmission table by 5% (should remove the last point) + table = a_band._trim_transmission_by_percentile(a_band._loaded_table, trim_percentile=0.05) + np.testing.assert_allclose(table, np.array([[100, 0.5], [200, 0.75]])) -def test_passband_process_transmission_table(tmp_path): - """Test the _process_transmission_table method of the Passband class: correct methods are called.""" - transmission_table = "100 0.5\n200 0.75\n300 0.25\n" - a_band = create_test_passband(tmp_path, transmission_table, wave_grid=100) + # Trim the transmission table by 40% (should still preserve the first point, as table is skewed) + table = a_band._trim_transmission_by_percentile(a_band._loaded_table, trim_percentile=0.4) + np.testing.assert_allclose(table, np.array([[100, 0.5], [200, 0.75]])) - # Mock the methods that _process_transmission_table wraps - with ( - patch.object(a_band, "_interpolate_or_downsample_transmission_table") as mock_interp_table, - patch.object(a_band, "_normalize_interpolated_transmission_table") as mock_norm_table, - ): - # Call the _process_transmission_table method - a_band._process_transmission_table() + # Check no trimming if percentile is 0 + table = a_band._trim_transmission_by_percentile(a_band._loaded_table, trim_percentile=None) + np.testing.assert_allclose(table, np.array([[100, 0.5], [200, 0.75], [300, 0.25]])) - # Check that each method is called once - mock_interp_table.assert_called_once_with(a_band._loaded_table) - mock_norm_table.assert_called_once() + # Check we raise an error if the percentile is not between 0 and 0.5 + with pytest.raises(ValueError): + a_band._trim_transmission_by_percentile(a_band._loaded_table, trim_percentile=0.6) + with pytest.raises(ValueError): + a_band._trim_transmission_by_percentile(a_band._loaded_table, trim_percentile=-0.1) + # Test 2: larger, more normal transmission table + transmission_table = "100 0.05\n200 0.1\n300 0.25\n400 0.5\n500 0.8\n600 0.6\n700 0.4\n800 0.2\n900 0.1\n" + b_band = create_test_passband(tmp_path, transmission_table, filter_name="b") -def test_passband_interpolate_or_downsample_transmission_table(tmp_path): - """Test down-sampling and interpolation of the transmission table.""" - transmission_table = "100 0.5\n200 0.75\n300 0.25\n" - a_band = create_test_passband(tmp_path, transmission_table) + # Trim the transmission table by 5% (should remove the first and last points) + table = b_band._trim_transmission_by_percentile(b_band._loaded_table, trim_percentile=0.05) + np.testing.assert_allclose( + table, np.array([[200, 0.1], [300, 0.25], [400, 0.5], [500, 0.8], [600, 0.6], [700, 0.4], [800, 0.2]]) + ) - # Downsample the transmission table - a_band._set_wave_grid_attr(200) - table = a_band._interpolate_or_downsample_transmission_table(a_band._loaded_table) - np.testing.assert_allclose(table[:, 0], [100, 300]) + # Trim the transmission table by 40% (should remove most points) + table = b_band._trim_transmission_by_percentile(b_band._loaded_table, trim_percentile=0.4) + np.testing.assert_allclose(table, np.array([[400, 0.5], [500, 0.8]])) - # Downsample the transmission table to a very large step size - a_band._set_wave_grid_attr(500) - table = a_band._interpolate_or_downsample_transmission_table(a_band._loaded_table) - np.testing.assert_allclose(table[:, 0], [100]) + # Check no trimming if percentile is 0 + table = b_band._trim_transmission_by_percentile(b_band._loaded_table, trim_percentile=None) + np.testing.assert_allclose( + table, + np.array( + [ + [100, 0.05], + [200, 0.1], + [300, 0.25], + [400, 0.5], + [500, 0.8], + [600, 0.6], + [700, 0.4], + [800, 0.2], + [900, 0.1], + ] + ), + ) - # Interpolate the transmission table (note for comparison below: np.arange is exclusive of stop value) - a_band._set_wave_grid_attr(50) - table = a_band._interpolate_or_downsample_transmission_table(a_band._loaded_table) - np.testing.assert_allclose(table[:, 0], np.arange(100, 301, 50)) + # Test 3: much larger transmission table + transmissions = np.random.normal(0.5, 0.1, 1000) + wavelengths = np.arange(100, 1100, 1) + transmission_table = "\n".join( + [f"{wavelength} {transmission}" for wavelength, transmission in zip(wavelengths, transmissions)] + ) + c_band = create_test_passband(tmp_path, transmission_table, filter_name="c") - # Interpolate the transmission table to a somewhat small step size (1 Angstrom) - a_band._set_wave_grid_attr(1) - table = a_band._interpolate_or_downsample_transmission_table(a_band._loaded_table) - np.testing.assert_allclose(table[:, 0], np.arange(100, 301, 1)) + # Trim the transmission table by 5% on each side + table = c_band._trim_transmission_by_percentile(c_band._loaded_table, trim_percentile=0.05) + assert len(table) < len(c_band._loaded_table) - # Interpolate the transmission table to an even smaller step size (0.1 Angstrom) - a_band._set_wave_grid_attr(0.1) - table = a_band._interpolate_or_downsample_transmission_table(a_band._loaded_table) - np.testing.assert_allclose(table[:, 0], np.arange(100, 300.01, 0.1)) + original_area = np.trapz(c_band._loaded_table[:, 1], x=c_band._loaded_table[:, 0]) + trimmed_area = np.trapz(table[:, 1], x=table[:, 0]) + assert np.isclose(trimmed_area, original_area * 0.9, rtol=0.01) -def test_passband_normalize_interpolated_transmission_table(tmp_path): - """Test the _normalize_interpolated_transmission_table method of the Passband class.""" +def test_passband_normalize_transmission_table(tmp_path): # TODO check this still works + """Test the _normalize_transmission_table method of the Passband class.""" transmission_table = "100 0.5\n200 0.75\n300 0.25\n" - a_band = create_test_passband(tmp_path, transmission_table, wave_grid=100) + a_band = create_test_passband(tmp_path, transmission_table, delta_wave=100, trim_percentile=None) # Normalize the transmission table (we skip interpolation as grid already matches) - a_band._normalize_interpolated_transmission_table(a_band._loaded_table) + a_band._normalize_transmission_table(a_band._loaded_table) # Compare results expected_result = np.array([[100.0, 0.0075], [200.0, 0.005625], [300.0, 0.00125]]) @@ -239,169 +244,19 @@ def test_passband_normalize_interpolated_transmission_table(tmp_path): # Test that we raise an error if the transmission table is the wrong size or shape with pytest.raises(ValueError): - a_band._normalize_interpolated_transmission_table(np.array([[]])) - with pytest.raises(ValueError): - a_band._normalize_interpolated_transmission_table(np.array([[100, 0.5]])) + a_band._normalize_transmission_table(np.array([[]])) with pytest.raises(ValueError): - a_band._normalize_interpolated_transmission_table(np.array([100, 0.5])) + a_band._normalize_transmission_table(np.array([[100, 0.5]])) with pytest.raises(ValueError): - a_band._normalize_interpolated_transmission_table(np.array([[100, 0.5, 105, 0.6]])) - - -def test_passband_interpolate_flux_densities_basic(tmp_path): - """Test basic functionality of the _interpolate_flux_densities method of the Passband class.""" - transmission_table = "100 0.5\n200 0.75\n300 0.25\n400 0.5\n500 0.25\n600 0.5" - - # Test: no interpolation needed - a_band = create_test_passband(tmp_path, transmission_table, wave_grid=100) - fluxes = np.array([[0.25, 0.5, 1.0, 1.0, 0.5, 0.25]]) - flux_wavelengths = np.array([100.0, 200.0, 300.0, 400.0, 500.0, 600.0]) - - with patch("scipy.interpolate.InterpolatedUnivariateSpline") as mock_spline: - (result_fluxes, result_wavelengths) = a_band._interpolate_flux_densities(fluxes, flux_wavelengths) - np.testing.assert_allclose(result_fluxes, fluxes) - np.testing.assert_allclose(result_wavelengths, flux_wavelengths) - mock_spline.assert_not_called() - - # Test: interpolation when fluxes span entire band - b_band = create_test_passband(tmp_path, transmission_table, wave_grid=50, filter_name="b") - fluxes = np.array([[0.25, 0.5, 1.0, 1.0, 0.5, 0.25], [0.25, 0.5, 1.0, 1.0, 0.5, 0.25]]) - flux_wavelengths = np.array([100.0, 200.0, 300.0, 400.0, 500.0, 600.0]) - (result_fluxes, result_wavelengths) = b_band._interpolate_flux_densities(fluxes, flux_wavelengths) - - # Check wavelengths - expected_waves = np.arange(100, 601, 50) - np.testing.assert_allclose(result_wavelengths, expected_waves) - - # Check the interpolated fluxes, while being somewhat agnostic to the specific method of interpolation - assert result_fluxes.shape == (2, 11) - # Ends should be 0.25 - assert result_fluxes[0, 0] == 0.25 - assert result_fluxes[0, 10] == 0.25 - # Beginning should be increasing. We don't go all the way to the middle, as the spline may wiggle a bit - # approximating the flat top between 300 and 400 Angstroms. - assert np.all(np.diff(result_fluxes[0, :5]) > 0) - # End should be decreasing. Similarly, not starting exactly at the middle. - assert np.all(np.diff(result_fluxes[0, 7:]) < 0) - - -def test_passband_interpolate_flux_densities_spline_degrees(tmp_path): - """Test spline degree settings in the _interpolate_flux_densities method of the Passband class.""" - transmission_table = "100 0.5\n200 0.75\n300 0.25\n400 0.5\n500 0.25\n600 0.5" - a_band = create_test_passband(tmp_path, transmission_table, wave_grid=50) - fluxes = np.array([[0.25, 0.5, 1.0, 1.0, 0.5, 0.25], [0.25, 0.5, 1.0, 1.0, 0.5, 0.25]]) - flux_wavelengths = np.array([100.0, 200.0, 300.0, 400.0, 500.0, 600.0]) - - # Test we can run interpolation with spline_degree at default (3) - (result_fluxes, result_wavelengths) = a_band._interpolate_flux_densities(fluxes, flux_wavelengths) - assert result_fluxes.shape == (2, 11) - assert result_wavelengths.shape == (11,) - - # Test we can run with spline_degree at values 1-5 - for degree in range(1, 6): - (result_fluxes, result_wavelengths) = a_band._interpolate_flux_densities( - fluxes, flux_wavelengths, spline_degree=degree - ) - assert result_fluxes.shape == (2, 11) - assert result_wavelengths.shape == (11,) - - # Test we raise an error for invalid degrees + a_band._normalize_transmission_table(np.array([100, 0.5])) with pytest.raises(ValueError): - a_band._interpolate_flux_densities(fluxes, flux_wavelengths, spline_degree=0) + a_band._normalize_transmission_table(np.array([[100, 0.5, 105, 0.6]])) - with pytest.raises(ValueError): - a_band._interpolate_flux_densities(fluxes, flux_wavelengths, spline_degree=6) - - # Test we raise an error if number of degrees is greater than number of points - fluxes = np.array([[0.25, 0.5]]) - flux_wavelengths = np.array([100.0, 200.0]) - with pytest.raises(ValueError): - a_band._interpolate_flux_densities(fluxes, flux_wavelengths, spline_degree=3) - - -def test_passband_interpolate_flux_densities_truncation_needed(tmp_path): - """Test truncation in the _interpolate_flux_densities method of the Passband class.""" - transmission_table = "100 0.5\n200 0.75\n300 0.25\n400 0.5\n500 0.25\n600 0.5" - - # Test truncation when fluxes are out of bounds - a_band = create_test_passband(tmp_path, transmission_table, wave_grid=100) - fluxes = np.array([[0.25, 0.5, 1.0, 1.0, 0.5, 0.25, 0.0, 0.5]]) - flux_wavelengths = np.array([50.0, 100.0, 200.0, 300.0, 400.0, 500.0, 600.0, 650.0]) - (result_fluxes, result_wavelengths) = a_band._interpolate_flux_densities(fluxes, flux_wavelengths) - assert result_fluxes.shape == (1, 6) - assert result_wavelengths.shape == (6,) - np.testing.assert_allclose(result_wavelengths, np.array([100.0, 200.0, 300.0, 400.0, 500.0, 600.0])) - np.testing.assert_allclose(result_fluxes, fluxes[:, 1:7]) - - # Test truncation and interpolation when fluxes are out of bounds - a_band.set_transmission_table_grid(50) - (result_fluxes, result_wavelengths) = a_band._interpolate_flux_densities(fluxes, flux_wavelengths) - assert result_fluxes.shape == (1, 11) - assert result_wavelengths.shape == (11,) - np.testing.assert_allclose(result_wavelengths, np.arange(100, 601, 50)) - np.testing.assert_allclose(result_fluxes[:, ::2], fluxes[:, 1:7]) - - -def test_passband_interpolate_flux_densities_padding_needed(tmp_path): - """Test padding in the _interpolate_flux_densities method of the Passband class.""" - transmission_table = "100 0.5\n200 0.75\n300 0.25\n400 0.5\n500 0.25\n600 0.5" - - # Test padding (with NO interpolation) when fluxes do not span the entire band - a_band = create_test_passband(tmp_path, transmission_table, wave_grid=100, filter_name="b") - fluxes = np.array([[0.5, 1.0, 0.5, 0.25], [0.5, 1.0, 0.5, 0.25]]) - flux_wavelengths = np.array([200.0, 300.0, 400.0, 500.0]) - - # Case 1: padding needed with extrapolation="raise" - with pytest.raises(ValueError): - a_band._interpolate_flux_densities(fluxes, flux_wavelengths, "raise") - # Case 2: padding needed with extrapolation="zeros" - (result_fluxes, result_wavelengths) = a_band._interpolate_flux_densities( - fluxes, flux_wavelengths, "zeros" - ) - expected_fluxes = np.array([[0.0, 0.5, 1.0, 0.5, 0.25, 0.0], [0.0, 0.5, 1.0, 0.5, 0.25, 0.0]]) - expected_waves = np.array([100, 200, 300, 400, 500, 600]) - np.testing.assert_allclose(result_fluxes, expected_fluxes) - np.testing.assert_allclose(result_wavelengths, expected_waves) - - # Case 3: padding needed with extrapolation="constant" - (result_fluxes, result_wavelengths) = a_band._interpolate_flux_densities( - fluxes, flux_wavelengths, "const" - ) - expected_fluxes = np.array([[0.5, 0.5, 1.0, 0.5, 0.25, 0.25], [0.5, 0.5, 1.0, 0.5, 0.25, 0.25]]) - expected_waves = np.array([100, 200, 300, 400, 500, 600]) - np.testing.assert_allclose(result_fluxes, expected_fluxes) - np.testing.assert_allclose(result_wavelengths, expected_waves) - - # Test padding (this time WITH interpolation as well) when fluxes do not span the entire band - b_band = create_test_passband(tmp_path, transmission_table, wave_grid=50, filter_name="b") - fluxes = np.array([[0.25, 0.75, 1.0, 0.25]]) - flux_wavelengths = np.array([200.0, 300.0, 400.0, 500.0]) - (result_fluxes, result_wavelengths) = b_band._interpolate_flux_densities( - fluxes, flux_wavelengths, "zeros" - ) - # Check waves generated as expected - expected_waves = np.arange(100, 601, 50) - np.testing.assert_allclose(result_wavelengths, expected_waves) - assert result_fluxes.shape == (1, 11) - # Check flux zero-padding on both ends - assert np.isclose(result_fluxes[0, 0], 0.0) - assert np.isclose(result_fluxes[0, 1], 0.0) - assert np.isclose(result_fluxes[0, 9], 0.0) - assert np.isclose(result_fluxes[0, 10], 0.0) - # Check the ends of the given fluxes are preserved - assert np.isclose(result_fluxes[0, 2], 0.25) - assert np.isclose(result_fluxes[0, 8], 0.25) - # Check the increasing section (originally indices [0, 2]) is still increasing (now indices [2, 6]) - assert np.all(np.diff(result_fluxes[0, 2:6]) > 0) - # Check the decreasing section (originally indices [2, 3]) is still decreasing (now indices [6, 8]) - assert np.all(np.diff(result_fluxes[0, 6:8]) < 0) - - -def test_passband_fluxes_to_bandflux(tmp_path): +def test_passband_fluxes_to_bandflux(tmp_path): # TODO check this still works """Test the fluxes_to_bandflux method of the Passband class.""" transmission_table = "100 0.5\n200 0.75\n300 0.25\n" - a_band = create_test_passband(tmp_path, transmission_table, wave_grid=100) + a_band = create_test_passband(tmp_path, transmission_table, delta_wave=100, trim_percentile=None) # Define some mock flux values and calculate our expected bandflux flux = np.array( @@ -413,13 +268,12 @@ def test_passband_fluxes_to_bandflux(tmp_path): [1.0, 1.0, 1.0], ] ) - expected_in_band_flux = np.trapz( - flux * a_band.processed_transmission_table[:, 1], x=a_band.processed_transmission_table[:, 0] - ) - in_band_flux = a_band.fluxes_to_bandflux(flux, a_band.processed_transmission_table[:, 0]) + expected_in_band_flux = np.trapz(flux * a_band.processed_transmission_table[:, 1], x=a_band.waves) + in_band_flux = a_band.fluxes_to_bandflux(flux) np.testing.assert_allclose(in_band_flux, expected_in_band_flux) - # Test with a different set of fluxes + # Test with a different set of fluxes, regridding the transmission table + a_band.process_transmission_table(delta_wave=50, trim_percentile=None) flux = np.array( [ [100.0, 12.0, 1.0, 0.5, 0.25], @@ -431,9 +285,7 @@ def test_passband_fluxes_to_bandflux(tmp_path): [100.0, 50.0, 25.0, 12.5, 6.25], ] ) - flux_wave_grid = np.array([100.0, 150.0, 200.0, 250.0, 300.0]) - a_band.set_transmission_table_grid(flux_wave_grid) - in_band_flux = a_band.fluxes_to_bandflux(flux, flux_wave_grid) + in_band_flux = a_band.fluxes_to_bandflux(flux) expected_in_band_flux = np.trapz( flux * a_band.processed_transmission_table[:, 1], x=a_band.processed_transmission_table[:, 0] ) @@ -441,10 +293,8 @@ def test_passband_fluxes_to_bandflux(tmp_path): # Test we raise an error if the fluxes are not the right shape with pytest.raises(ValueError): - a_band.fluxes_to_bandflux( - np.array([[1.0, 2.0], [3.0, 4.0]]), a_band.processed_transmission_table[:, 0] - ) + a_band.fluxes_to_bandflux(np.array([[1.0, 2.0], [3.0, 4.0]])) # Test we raise an error if the fluxes are empty with pytest.raises(ValueError): - a_band.fluxes_to_bandflux(np.array([]), a_band.processed_transmission_table[:, 0]) + a_band.fluxes_to_bandflux(np.array([])) diff --git a/tests/tdastro/sources/test_snia.py b/tests/tdastro/sources/test_snia.py new file mode 100644 index 00000000..195c7ec6 --- /dev/null +++ b/tests/tdastro/sources/test_snia.py @@ -0,0 +1,198 @@ +import numpy as np +import sncosmo +from astropy import units as u +from tdastro.astro_utils.opsim import OpSim +from tdastro.astro_utils.passbands import PassbandGroup +from tdastro.astro_utils.snia_utils import DistModFromRedshift, HostmassX1Func, X0FromDistMod +from tdastro.astro_utils.unit_utils import flam_to_fnu +from tdastro.effects.redshift import Redshift +from tdastro.sources.sncomso_models import SncosmoWrapperModel +from tdastro.sources.snia_host import SNIaHost +from tdastro.util_nodes.np_random import NumpyRandomFunc + + +def draw_single_random_sn( + source, + wavelengths_rest=None, + phase_rest=None, + passbands=None, + opsim=False, + opsim_data=None, + randseed=None, +): + """ + Draw a single random SN realiztion + """ + + res = {"wavelengths_rest": wavelengths_rest, "phase_rest": phase_rest} + + state = source.sample_parameters() + + z = source.get_param(state, "redshift") + wave_obs = wavelengths_rest * (1.0 + z) + phase_obs = phase_rest * (1.0 + z) + + t0 = source.get_param(state, "t0") + times = t0 + phase_obs + + if opsim: + ra = source.get_param(state, "ra") + dec = source.get_param(state, "dec") + obs = opsim_data.get_observations(ra, dec, radius=1.75, cols=["time", "filter"]) + + times = obs["time"] + phase_obs = times - t0 + times = np.sort(times[(phase_obs > -20) & (phase_obs < 50)]) + # Note that we don't have filter info yet. + + if len(times) == 0: + print(f"No overlap time in opsim for (ra,dec)=({ra:.2f},{dec:.2f})") + return + + res["times"] = times + + flux_flam = source.evaluate(times, wave_obs, graph_state=state) + res["flux_flam"] = flux_flam + + # convert ergs/s/cm^2/AA to nJy + + flux_fnu = flam_to_fnu( + flux_flam, wave_obs, wave_unit=u.AA, flam_unit=u.erg / u.second / u.cm**2 / u.AA, fnu_unit=u.nJy + ) + + res["flux_fnu"] = flux_fnu + + bandfluxes = passbands.fluxes_to_bandfluxes(flux_fnu) + res["bandfluxes"] = bandfluxes + + res["state"] = state + + return res + + +def test_snia_end2end( + opsim_small, + opsim_db_file=None, + opsim=True, + nsample=1, + return_result=False, + phase_rest=None, + wavelengths_rest=None, +): + """Test that we can sample and create SN Ia simulation using the salt3 model.""" + + opsim_data = OpSim.from_db(opsim_db_file if opsim_db_file else opsim_small) if opsim else None + + ra_min = opsim_data["fieldRA"].min() if opsim_data else 0.0 + ra_max = opsim_data["fieldRA"].max() if opsim_data else 360.0 + dec_min = opsim_data["fieldDec"].min() if opsim_data else -90.0 + dec_max = opsim_data["fieldDec"].max() if opsim_data else 33.5 + t_min = opsim_data["observationStartMJD"].min() if opsim_data else 60796.0 + t_max = opsim_data["observationStartMJD"].max() if opsim_data else 64448.0 + + # Create a host galaxy anywhere on the sky. + host = SNIaHost( + ra=NumpyRandomFunc("uniform", low=ra_min, high=ra_max), + dec=NumpyRandomFunc("uniform", low=dec_min, high=dec_max), + hostmass=NumpyRandomFunc("uniform", low=7, high=12), + redshift=NumpyRandomFunc("uniform", low=0.01, high=0.02), + ) + + distmod_func = DistModFromRedshift(host.redshift, H0=73.0, Omega_m=0.3) + x1_func = HostmassX1Func(host.hostmass) + c_func = NumpyRandomFunc("normal", loc=0, scale=0.02) + m_abs_func = NumpyRandomFunc("normal", loc=-19.3, scale=0.1) + + x0_func = X0FromDistMod( + distmod=distmod_func, + x1=x1_func, + c=c_func, + alpha=0.14, + beta=3.1, + m_abs=m_abs_func, + ) + + sncosmo_modelname = "salt2-h17" + + source = SncosmoWrapperModel( + sncosmo_modelname, + t0=NumpyRandomFunc("uniform", low=t_min, high=t_max), + x0=x0_func, + x1=x1_func, + c=c_func, + ra=NumpyRandomFunc("normal", loc=host.ra, scale=0.01), + dec=NumpyRandomFunc("normal", loc=host.dec, scale=0.01), + redshift=host.redshift, + ) + + source.add_effect(Redshift(redshift=source.redshift, t0=source.t0)) + + url_base = "https://raw.githubusercontent.com/lsst/throughputs/e70d1daf069e606caa3feb43eccc62ec21e0baf5/" + passbands = PassbandGroup( + passband_parameters=[ + { + "survey": "LSST", + "filter_name": "u", + "table_url": f"{url_base}baseline/total_u.dat", + "units": "A", + }, + { + "survey": "LSST", + "filter_name": "r", + "table_url": f"{url_base}baseline/total_r.dat", + "units": "A", + }, + ], + delta_wave=1, + ) + wavelengths_rest = passbands.waves + + res_list = [] + + if phase_rest is None: + phase_rest = np.array([-5.0, 0.0, 10.0]) + if wavelengths_rest is None: + wavelengths_rest = np.linspace(3000, 8000, 200) + + for _n in range(0, nsample): + res = draw_single_random_sn( + source, + wavelengths_rest=wavelengths_rest, + phase_rest=phase_rest, + passbands=passbands, + opsim=opsim, + opsim_data=opsim_data, + ) + + state = res["state"] + p = {} + for parname in ["t0", "x0", "x1", "c", "redshift", "ra", "dec"]: + p[parname] = source.get_param(state, parname) + for parname in ["hostmass"]: + p[parname] = host.get_param(state, parname) + for parname in ["distmod"]: + p[parname] = x0_func.get_param(state, parname) + res["parameter_values"] = p + + saltpars = {"x0": p["x0"], "x1": p["x1"], "c": p["c"], "z": p["redshift"], "t0": p["t0"]} + model = sncosmo.Model(sncosmo_modelname) + model.update(saltpars) + z = p["redshift"] + wave = wavelengths_rest * (1 + z) + if opsim is None: + time = phase_rest * (1 + z) + p["t0"] + assert np.allclose(res["times"], time) + else: + time = res["times"] + + flux_sncosmo = model.flux(time, wave) + assert np.allclose(res["flux_flam"] * 1e10, flux_sncosmo * 1e10) + + for f in passbands.passbands: + bandflux_sncosmo = model.bandflux(f.replace("_", ""), time, zpsys="ab", zp=8.9 + 2.5 * 9) + assert np.allclose(res["bandfluxes"][f], bandflux_sncosmo, rtol=0.1) + + res_list.append(res) + + if return_result: + return res_list From a1f92fad6830032a52167b9b41db54859989ad3c Mon Sep 17 00:00:00 2001 From: Olivia Lynn Date: Mon, 16 Sep 2024 02:45:14 -0400 Subject: [PATCH 23/38] Update unit tests; fix merge errors; improve error logging output for mismatched flux/table --- src/tdastro/astro_utils/passbands.py | 35 ++++++++++++++++++++++------ tests/tdastro/sources/test_snia.py | 4 ++-- 2 files changed, 30 insertions(+), 9 deletions(-) diff --git a/src/tdastro/astro_utils/passbands.py b/src/tdastro/astro_utils/passbands.py index ae4c7e42..1fd7c62f 100644 --- a/src/tdastro/astro_utils/passbands.py +++ b/src/tdastro/astro_utils/passbands.py @@ -70,9 +70,9 @@ def __init__( if passband_parameters is not None: for parameters in passband_parameters: - # TODO maybe check mismatched keys in parameters and group (specifically delta_wave, - # trim_percentile, units.) - passband = Passband(**parameters, delta_wave=delta_wave, trim_percentile=trim_percentile) + parameters["delta_wave"] = delta_wave + parameters["trim_percentile"] = trim_percentile + passband = Passband(**parameters) self.passbands[passband.full_name] = passband self._update_waves() @@ -147,8 +147,9 @@ def fluxes_to_bandfluxes(self, flux_density_matrix: np.ndarray) -> np.ndarray: A dictionary of bandfluxes with passband names as keys and np.ndarrays of bandfluxes as values. """ if flux_density_matrix.size == 0 or len(self.waves) != len(flux_density_matrix[0]): + flux_density_matrix_num_cols = 0 if flux_density_matrix.size == 0 else len(flux_density_matrix[0]) raise ValueError( - f"PassbandGroup mismatched grids: Flux density matrix has {len(flux_density_matrix[0])} " + f"PassbandGroup mismatched grids: Flux density matrix has {flux_density_matrix_num_cols} " f"columns, which does not match transmission table's {len(self.waves)} rows. Check that the " f"flux density matrix was calculated on the same grid as the transmission tables, which can " f"be accessed via the Passband's or PassbandGroup's waves attribute." @@ -266,14 +267,33 @@ def _load_transmission_table(self) -> None: np.ndarray A 2D array of wavelengths and transmissions. """ + # Check if the table file exists locally, and download it if it does not if self.table_path is None: self.table_path = os.path.join( - os.path.dirname(__file__), f"passbands/{self.survey}/{self.label}.dat" + os.path.dirname(__file__), f"passbands/{self.survey}/{self.filter_name}.dat" ) os.makedirs(os.path.dirname(self.table_path), exist_ok=True) if not os.path.exists(self.table_path): self._download_transmission_table() - return np.loadtxt(self.table_path) + # Load the table file + try: + loaded_table = np.loadtxt(self.table_path) + except OSError as e: + raise OSError(f"Error reading transmission table from file: {e}") from e + # Check that the table has the correct shape + if loaded_table.size == 0 or loaded_table.shape[1] != 2: + raise ValueError("Transmission table must have exactly 2 columns.") + # Check that wavelengths are strictly increasing + if not np.all(np.diff(loaded_table[:, 0]) > 0): + raise ValueError("Wavelengths in transmission table must be strictly increasing.") + + # Correct for units + if self.units == "nm": + loaded_table[ + :, 0 + ] *= 10.0 # Multiply the first column (wavelength) by 10.0 to convert to Angstroms + + self._loaded_table = loaded_table def _download_transmission_table(self) -> bool: """Download a transmission table from a URL. @@ -485,8 +505,9 @@ def fluxes_to_bandflux( at the corresponding time. """ if flux_density_matrix.size == 0 or len(self.waves) != len(flux_density_matrix[0]): + flux_density_matrix_num_cols = 0 if flux_density_matrix.size == 0 else len(flux_density_matrix[0]) raise ValueError( - f"Passband mismatched grids: Flux density matrix has {len(flux_density_matrix[0])} " + f"Passband mismatched grids: Flux density matrix has {flux_density_matrix_num_cols} " f"columns, which does not match the {len(self.waves)} rows in band {self.full_name}'s " f"transmission table. Check that the flux density matrix was calculated on the same grid as " f"the transmission tables, which can be accessed via the Passband's or PassbandGroup's waves " diff --git a/tests/tdastro/sources/test_snia.py b/tests/tdastro/sources/test_snia.py index 195c7ec6..21745224 100644 --- a/tests/tdastro/sources/test_snia.py +++ b/tests/tdastro/sources/test_snia.py @@ -134,13 +134,13 @@ def test_snia_end2end( "survey": "LSST", "filter_name": "u", "table_url": f"{url_base}baseline/total_u.dat", - "units": "A", + "units": "nm", }, { "survey": "LSST", "filter_name": "r", "table_url": f"{url_base}baseline/total_r.dat", - "units": "A", + "units": "nm", }, ], delta_wave=1, From 63f8d7bdde8a92e7ac72ce6b69105af6b44449f1 Mon Sep 17 00:00:00 2001 From: Olivia Lynn Date: Mon, 16 Sep 2024 04:02:06 -0400 Subject: [PATCH 24/38] Improve algo for determining in-band flux wavelengths to use from PassbandGroup; unit tests --- src/tdastro/astro_utils/passbands.py | 26 ++++---- .../astro_utils/test_passband_groups.py | 65 +++++++------------ tests/tdastro/astro_utils/test_passbands.py | 4 +- 3 files changed, 38 insertions(+), 57 deletions(-) diff --git a/src/tdastro/astro_utils/passbands.py b/src/tdastro/astro_utils/passbands.py index 1fd7c62f..eecf91eb 100644 --- a/src/tdastro/astro_utils/passbands.py +++ b/src/tdastro/astro_utils/passbands.py @@ -70,8 +70,10 @@ def __init__( if passband_parameters is not None: for parameters in passband_parameters: - parameters["delta_wave"] = delta_wave - parameters["trim_percentile"] = trim_percentile + if "delta_wave" not in parameters: + parameters["delta_wave"] = delta_wave + if "trim_percentile" not in parameters: + parameters["trim_percentile"] = trim_percentile passband = Passband(**parameters) self.passbands[passband.full_name] = passband @@ -156,19 +158,15 @@ def fluxes_to_bandfluxes(self, flux_density_matrix: np.ndarray) -> np.ndarray: ) bandfluxes = {} - group_has_regular_grid_step = np.allclose(np.diff(self.waves), np.diff(self.waves)[0]) - # TODO this will never work, because the wavelengths are not the same for all passbands--so there will - # always be a big jump between passbands - # TODO in general there's a better algorithm to find the indices of the wavelengths in the passband - # where we first figure out which passbands the wavelengths are in, and then find the indices in the - # target passbands. we shouldn't blindly search through the whole group's waves like this. - for full_name, passband in self.passbands.items(): # We only want the fluxes that are in the passband's wavelength range - if group_has_regular_grid_step: - lower, upper = passband.waves[0], passband.waves[-1] - lower_index, upper_index = np.searchsorted(self.waves, [lower, upper]) - in_band_fluxes = flux_density_matrix[:, lower_index:upper_index] + # So, find the indices in the group's wave grid that are in the passband's wave grid + lower, upper = passband.waves[0], passband.waves[-1] + lower_index, upper_index = np.searchsorted(self.waves, [lower, upper]) + # Check that this is the right grid after all (check will fail if the grid is not regular, or + # passbands are overlapping) + if np.array_equal(self.waves[lower_index : upper_index + 1], passband.waves): + in_band_fluxes = flux_density_matrix[:, lower_index : upper_index + 1] else: indices = np.unique(np.searchsorted(passband.waves, self.waves)) if indices[-1] == len(passband.waves): @@ -176,7 +174,6 @@ def fluxes_to_bandfluxes(self, flux_density_matrix: np.ndarray) -> np.ndarray: in_band_fluxes = flux_density_matrix[:, indices] bandfluxes[full_name] = passband.fluxes_to_bandflux(in_band_fluxes) - print() return bandfluxes @@ -347,7 +344,6 @@ def process_transmission_table(self, delta_wave: float | None = 5.0, trim_percen The percentile to trim the transmission table by. For example, if trim_percentile is 0.1, the transmission table will be trimmed to include only the central 80% of rows. """ - # TODO do we want to store delta_wave and trim_percentile as attributes? interpolated_table = self._interpolate_transmission_table(self._loaded_table, delta_wave) trimmed_table = self._trim_transmission_by_percentile(interpolated_table, trim_percentile) self.processed_transmission_table = self._normalize_transmission_table(trimmed_table) diff --git a/tests/tdastro/astro_utils/test_passband_groups.py b/tests/tdastro/astro_utils/test_passband_groups.py index 7e700636..b2b60b37 100644 --- a/tests/tdastro/astro_utils/test_passband_groups.py +++ b/tests/tdastro/astro_utils/test_passband_groups.py @@ -14,8 +14,8 @@ def create_passband_group(path, delta_wave=5.0, trim_percentile=None): transmission_tables = { "a": "100 0.5\n200 0.75\n300 0.25\n", - "b": "100 0.25\n200 0.5\n300 0.75\n", - "c": "100 0.75\n200 0.25\n300 0.5\n", + "b": "250 0.25\n300 0.5\n350 0.75\n", + "c": "400 0.75\n500 0.25\n600 0.5\n", } for filter_name in filter_names: with open(table_dir / f"{filter_name}.dat", "w") as f: @@ -36,7 +36,7 @@ def create_passband_group(path, delta_wave=5.0, trim_percentile=None): return PassbandGroup(passband_parameters=passbands) -def test_passband_group_init(): +def test_passband_group_init(tmp_path): """Test the initialization of the Passband class, and implicitly, _load_preset.""" # Test that we can create an empty PassbandGroup object empty_passband = PassbandGroup() @@ -72,6 +72,17 @@ def mock_load_transmission_table(self): assert "LSST_r" in lsst_gri_passband_group.passbands assert "LSST_i" in lsst_gri_passband_group.passbands + # Test that our helper function creates a PassbandGroup object with the expected passbands + test_passband_group = create_passband_group(tmp_path) + assert len(test_passband_group.passbands) == 3 + assert "TEST_a" in test_passband_group.passbands + assert "TEST_b" in test_passband_group.passbands + assert "TEST_c" in test_passband_group.passbands + assert np.allclose( + test_passband_group.waves, + np.unique(np.concatenate([np.arange(100, 301, 5), np.arange(250, 351, 5), np.arange(400, 601, 5)])), + ) + # Test that the PassbandGroup class raises an error for an unknown preset try: _ = PassbandGroup(preset="Unknown") @@ -100,42 +111,16 @@ def test_passband_group_str(tmp_path): def test_passband_group_fluxes_to_bandfluxes(tmp_path): """Test the fluxes_to_bandfluxes method of the PassbandGroup class.""" - # Test with empty passband group - # empty_passband_group = PassbandGroup() - # flux = np.array([[1.0, 1.0, 1.0], [2.0, 1.0, 1.0], [3.0, 1.0, 1.0]]) - # flux_wavelengths = np.array([100, 200, 300]) - # bandfluxes = empty_passband_group.fluxes_to_bandfluxes(flux) - # assert len(bandfluxes) == 0 - # Test with simple passband group test_passband_group = create_passband_group(tmp_path, delta_wave=20, trim_percentile=None) - print(test_passband_group) - print(test_passband_group.waves) - for band in test_passband_group.passbands: - print(band) - print(test_passband_group.passbands[band].waves) - # flux = np.array( - # [ - # [1.0, 1.0, 1.0], - # [2.0, 1.0, 1.0], - # [3.0, 1.0, 1.0], - # [2.0, 1.0, 1.0], - # [1.0, 1.0, 1.0], - # ] - # ) - # flux_wavelengths = np.array([100, 200, 300]) - # bandfluxes = test_passband_group.fluxes_to_bandfluxes(flux, flux_wavelengths) - - # # Check values are as expected - # assert len(bandfluxes) == 3 - # for band_name in test_passband_group.passbands: - # assert band_name in bandfluxes - # assert bandfluxes[band_name].shape == (5,) - # assert np.allclose( - # bandfluxes[band_name], - # np.trapz( - # flux * test_passband_group.passbands[band_name].processed_transmission_table[:, 1], - # x=flux_wavelengths, - # axis=1, - # ), - # ) + + # Create some mock flux data with the same number of columns as wavelengths in our PassbandGroup + flux = np.linspace(test_passband_group.waves * 10, 100, 5) + + bandfluxes = test_passband_group.fluxes_to_bandfluxes(flux) + + # Check structure of result is as expected + assert len(bandfluxes) == 3 + for band_name in test_passband_group.passbands: + assert band_name in bandfluxes + assert bandfluxes[band_name].shape == (5,) diff --git a/tests/tdastro/astro_utils/test_passbands.py b/tests/tdastro/astro_utils/test_passbands.py index 88c3d055..9f896ede 100644 --- a/tests/tdastro/astro_utils/test_passbands.py +++ b/tests/tdastro/astro_utils/test_passbands.py @@ -230,7 +230,7 @@ def test_trim_transmission_table(tmp_path): assert np.isclose(trimmed_area, original_area * 0.9, rtol=0.01) -def test_passband_normalize_transmission_table(tmp_path): # TODO check this still works +def test_passband_normalize_transmission_table(tmp_path): """Test the _normalize_transmission_table method of the Passband class.""" transmission_table = "100 0.5\n200 0.75\n300 0.25\n" a_band = create_test_passband(tmp_path, transmission_table, delta_wave=100, trim_percentile=None) @@ -253,7 +253,7 @@ def test_passband_normalize_transmission_table(tmp_path): # TODO check this sti a_band._normalize_transmission_table(np.array([[100, 0.5, 105, 0.6]])) -def test_passband_fluxes_to_bandflux(tmp_path): # TODO check this still works +def test_passband_fluxes_to_bandflux(tmp_path): """Test the fluxes_to_bandflux method of the Passband class.""" transmission_table = "100 0.5\n200 0.75\n300 0.25\n" a_band = create_test_passband(tmp_path, transmission_table, delta_wave=100, trim_percentile=None) From 67c726cba55e2fd8cf275f47d6989745ce84443d Mon Sep 17 00:00:00 2001 From: Olivia Lynn Date: Mon, 16 Sep 2024 04:15:43 -0400 Subject: [PATCH 25/38] Update Passband demo notebook to match new interface; remove deprecated interpolation/extrapolation notebook --- .../interpolation-exterpolation-demo.ipynb | 177 ------------------ docs/notebooks/passband-demo.ipynb | 49 ++--- 2 files changed, 25 insertions(+), 201 deletions(-) delete mode 100644 docs/notebooks/interpolation-exterpolation-demo.ipynb diff --git a/docs/notebooks/interpolation-exterpolation-demo.ipynb b/docs/notebooks/interpolation-exterpolation-demo.ipynb deleted file mode 100644 index 5ab52125..00000000 --- a/docs/notebooks/interpolation-exterpolation-demo.ipynb +++ /dev/null @@ -1,177 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Interpolation/Exterpolation Demo" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "from tdastro.astro_utils.interpolation import (\n", - " create_grid,\n", - " get_grid_step,\n", - " interpolate_matrix_along_wavelengths,\n", - " interpolate_transmission_table,\n", - ")\n", - "from tdastro.astro_utils.passbands import PassbandGroup" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Set Up PassbandGroup" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "passband_group = PassbandGroup(preset=\"LSST\")\n", - "print(passband_group)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "passband_group.passbands[\"u\"].normalized_transmission_table" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Set Up Spline Model" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import matplotlib.pyplot as plt\n", - "import numpy as np\n", - "from tdastro.sources.spline_model import SplineModel\n", - "\n", - "# Load a model\n", - "input_times = np.array([1001.0, 1002.0, 1003.0, 1004.0, 1005.0])\n", - "input_wavelengths = np.linspace(2000.0, 10_000.0, 5)\n", - "input_fluxes = np.array(\n", - " [\n", - " [1.0, 5.0, 2.0, 3.0, 1.0],\n", - " [5.0, 10.0, 6.0, 7.0, 5.0],\n", - " [2.0, 6.0, 3.0, 4.0, 2.0],\n", - " [1.0, 5.0, 2.0, 3.0, 1.0],\n", - " [1.0, 5.0, 2.0, 3.0, 1.0],\n", - " ]\n", - ")\n", - "\n", - "spline_model = SplineModel(input_times, input_wavelengths, input_fluxes, time_degree=3, wave_degree=3)\n", - "\n", - "times = np.linspace(1000.0, 1006.0, 40)\n", - "wavelengths = np.linspace(2000.0, 11000.0, 30)\n", - "fluxes = spline_model.evaluate(times, wavelengths)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def plot_flux_spectrogram():\n", - " \"\"\"Plot a spectrogram to visualize the fluxes.\"\"\"\n", - " plt.imshow(fluxes.T, cmap=\"plasma\", interpolation=\"nearest\")\n", - "\n", - " # Add title, axis labels, and correct ticks\n", - " plt.title(\"Flux Spectrogram\")\n", - " plt.xlabel(\"Time (days)\")\n", - " plt.ylabel(\"Wavelength (Angstrom)\")\n", - " plt.xticks(np.arange(len(times))[::4], [f\"{round(time)}\" for time in times][::4])\n", - " plt.yticks(np.arange(len(wavelengths))[::2], [f\"{round(wave)}\" for wave in wavelengths][::2])\n", - "\n", - " # Add flux labels\n", - " for (j, i), label in np.ndenumerate(fluxes.T):\n", - " if i % 2 == 1:\n", - " plt.text(i, j, round(label, 1), ha=\"center\", va=\"center\", size=8)\n", - "\n", - " plt.show()\n", - "\n", - "\n", - "plot_flux_spectrogram()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Plot Lightcurve" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "bandfluxes = passband_group.fluxes_to_bandfluxes(fluxes, wavelengths)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def plot_lightcurve():\n", - " \"\"\"Plot the passband-normalized lightcurve.\"\"\"\n", - " fig, ax = plt.subplots()\n", - " ax.set_title(\"Passband-Normalized Lightcurve\")\n", - " ax.set_xlabel(\"Time (days)\")\n", - " ax.set_ylabel(\"Flux\")\n", - "\n", - " for i, label in enumerate(bandfluxes.keys()):\n", - " ax.plot(times, bandfluxes[label], marker=\"o\", label=label)\n", - "\n", - " ax.legend()\n", - " plt.show()\n", - "\n", - "\n", - "plot_lightcurve()" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "tda", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.9" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/docs/notebooks/passband-demo.ipynb b/docs/notebooks/passband-demo.ipynb index ea918f31..f99a2081 100644 --- a/docs/notebooks/passband-demo.ipynb +++ b/docs/notebooks/passband-demo.ipynb @@ -16,6 +16,23 @@ "from tdastro.astro_utils.passbands import PassbandGroup" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Set Up PassbandGroup" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "passband_group = PassbandGroup(preset=\"LSST\")\n", + "print(passband_group)" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -35,7 +52,7 @@ "\n", "# Load a model\n", "input_times = np.array([1001.0, 1002.0, 1003.0, 1004.0, 1005.0])\n", - "input_wavelengths = np.linspace(2000.0, 10_000.0, 5)\n", + "input_wavelengths = np.linspace(4000.0, 8000.0, 5)\n", "input_fluxes = np.array(\n", " [\n", " [1.0, 5.0, 2.0, 3.0, 1.0],\n", @@ -49,7 +66,7 @@ "spline_model = SplineModel(input_times, input_wavelengths, input_fluxes, time_degree=3, wave_degree=3)\n", "\n", "times = np.linspace(1000.0, 1006.0, 40)\n", - "wavelengths = np.linspace(2000.0, 11000.0, 30)\n", + "wavelengths = passband_group.waves\n", "fluxes = spline_model.evaluate(times, wavelengths)" ] }, @@ -61,18 +78,19 @@ "source": [ "def plot_flux_spectrogram():\n", " \"\"\"Plot a spectrogram to visualize the fluxes.\"\"\"\n", - " plt.imshow(fluxes.T, cmap=\"plasma\", interpolation=\"nearest\")\n", + " plt.figure(figsize=(12, 5))\n", + " plt.imshow(fluxes.T, cmap=\"plasma\", interpolation=\"nearest\", aspect=\"auto\")\n", "\n", " # Add title, axis labels, and correct ticks\n", " plt.title(\"Flux Spectrogram\")\n", " plt.xlabel(\"Time (days)\")\n", " plt.ylabel(\"Wavelength (Angstrom)\")\n", " plt.xticks(np.arange(len(times))[::4], [f\"{round(time)}\" for time in times][::4])\n", - " plt.yticks(np.arange(len(wavelengths))[::2], [f\"{round(wave)}\" for wave in wavelengths][::2])\n", + " plt.yticks(np.arange(len(wavelengths))[::50], [f\"{round(wave)}\" for wave in wavelengths][::50])\n", "\n", " # Add flux labels\n", " for (j, i), label in np.ndenumerate(fluxes.T):\n", - " if i % 2 == 1:\n", + " if i % 2 == 1 and j % 40 == 20:\n", " plt.text(i, j, round(label, 1), ha=\"center\", va=\"center\", size=8)\n", "\n", " plt.show()\n", @@ -85,17 +103,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### Set Up PassbandGroup" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "passband_group = PassbandGroup(preset=\"LSST\")\n", - "print(passband_group)" + "### Plot Lightcurve" ] }, { @@ -104,14 +112,7 @@ "metadata": {}, "outputs": [], "source": [ - "bandfluxes = passband_group.fluxes_to_bandfluxes(fluxes, wavelengths)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Plot Lightcurve" + "bandfluxes = passband_group.fluxes_to_bandfluxes(fluxes)" ] }, { From 1e71c783c831c5750854b64dd020a1c63f7f35a8 Mon Sep 17 00:00:00 2001 From: Olivia Lynn Date: Mon, 16 Sep 2024 04:36:36 -0400 Subject: [PATCH 26/38] Add process_transmission_tables example to demo --- docs/notebooks/passband-demo.ipynb | 30 +++++++++++++++++++++++++++--- 1 file changed, 27 insertions(+), 3 deletions(-) diff --git a/docs/notebooks/passband-demo.ipynb b/docs/notebooks/passband-demo.ipynb index f99a2081..5b05f19a 100644 --- a/docs/notebooks/passband-demo.ipynb +++ b/docs/notebooks/passband-demo.ipynb @@ -121,21 +121,45 @@ "metadata": {}, "outputs": [], "source": [ - "def plot_lightcurve():\n", + "def plot_lightcurve(bandfluxes):\n", " \"\"\"Plot the passband-normalized lightcurve.\"\"\"\n", " fig, ax = plt.subplots()\n", " ax.set_title(\"Passband-Normalized Lightcurve\")\n", " ax.set_xlabel(\"Time (days)\")\n", " ax.set_ylabel(\"Flux\")\n", "\n", - " for i, label in enumerate(bandfluxes.keys()):\n", + " for _, label in enumerate(bandfluxes.keys()):\n", " ax.plot(times, bandfluxes[label], marker=\"o\", label=label)\n", "\n", " ax.legend()\n", " plt.show()\n", "\n", "\n", - "plot_lightcurve()" + "plot_lightcurve(bandfluxes)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Update Wave Grid" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "passband_group.process_transmission_tables(delta_wavelength=20.0, trim_percentile=None)\n", + "\n", + "times = np.linspace(1000.0, 1006.0, 40)\n", + "wavelengths = passband_group.waves\n", + "fluxes = spline_model.evaluate(times, wavelengths)\n", + "\n", + "bandfluxes = passband_group.fluxes_to_bandfluxes(fluxes)\n", + "\n", + "plot_lightcurve(bandfluxes)" ] } ], From 15b01bce692b4f2f32ae5bc756b9eaeb04d56b40 Mon Sep 17 00:00:00 2001 From: Olivia Lynn Date: Mon, 16 Sep 2024 05:09:09 -0400 Subject: [PATCH 27/38] Update type hint format --- src/tdastro/astro_utils/passbands.py | 60 +++++++++++++--------------- 1 file changed, 28 insertions(+), 32 deletions(-) diff --git a/src/tdastro/astro_utils/passbands.py b/src/tdastro/astro_utils/passbands.py index eecf91eb..7a2338bc 100644 --- a/src/tdastro/astro_utils/passbands.py +++ b/src/tdastro/astro_utils/passbands.py @@ -27,18 +27,10 @@ def __init__( self, preset: str = None, passband_parameters: list = None, - delta_wave: float | None = 5.0, - trim_percentile: float | None = 0.1, + delta_wave: Optional[float] = 5.0, + trim_percentile: Optional[float] = 0.1, ): - """Initialize a PassbandGroup object. - - Attributes - ---------- - preset : str, optional - A pre-defined set of passbands to load. - passbands : dict - A dictionary of Passband objects assigned to the group. The keys are the passbands' full names: - eg, LSST_u, LSST_g, HSC_u, etc. + """Construct a PassbandGroup object. Parameters ---------- @@ -57,9 +49,9 @@ def __init__( - units : str (either 'nm' or 'A') If survey is not LSST (or other survey with defined defaults), either a table_path or table_url must be provided. - delta_wave : float | None, optional + delta_wave : float or None, optional The grid step of the wave grid. Default is 5.0. - trim_percentile : float | None, optional + trim_percentile : float or None, optional The percentile to trim the transmission table by. For example, if trim_percentile is 0.1, the transmission table will be trimmed to include only the central 80% of rows. """ @@ -86,16 +78,18 @@ def __str__(self) -> str: f"{', '.join(self.passbands.keys())}" ) - def _load_preset(self, preset: str, delta_wave: float | None, trim_percentile: float | None) -> None: + def _load_preset( + self, preset: str, delta_wave: Optional[float], trim_percentile: Optional[float] + ) -> None: """Load a pre-defined set of passbands. Parameters ---------- preset : str The name of the pre-defined set of passbands to load. - delta_wave : float | None + delta_wave : float or None The grid step of the wave grid. - trim_percentile : float | None + trim_percentile : float or None The percentile to trim the transmission table by. """ if preset == "LSST": @@ -118,15 +112,15 @@ def _update_waves(self) -> None: self.waves = np.unique(np.concatenate([passband.waves for passband in self.passbands.values()])) def process_transmission_tables( - self, delta_wave: float | None = 5.0, trim_percentile: float | None = 0.1 + self, delta_wave: Optional[float] = 5.0, trim_percentile: Optional[float] = 0.1 ): """Process the transmission tables for all passbands in the group; recalculate group's wave attribute. Parameters ---------- - delta_wave : float | None, optional + delta_wave : float or None, optional The grid step of the wave grid. Default is 5.0. - trim_percentile : float | None, optional + trim_percentile : float or None, optional The percentile to trim the transmission table by. For example, if trim_percentile is 0.1, the transmission table will be trimmed to include only the central 80% of rows. """ @@ -206,10 +200,10 @@ def __init__( self, survey: str, filter_name: str, - delta_wave: float | None = 5.0, - trim_percentile: float | None = 0.1, - table_path: str | None = None, - table_url: str | None = None, + delta_wave: Optional[float] = 5.0, + trim_percentile: Optional[float] = 0.1, + table_path: Optional[str] = None, + table_url: Optional[str] = None, units: Optional[Literal["nm", "A"]] = "A", ): """Initialize a Passband object. @@ -220,9 +214,9 @@ def __init__( The survey to which the passband belongs: eg, "LSST". filter_name : str The filter_name of the passband: eg, "u". - delta_wave : float | None, optional + delta_wave : float or None, optional The grid step of the wave grid. Default is 5.0. - trim_percentile : float | None, optional + trim_percentile : float or None, optional The percentile to trim the transmission table by. For example, if trim_percentile is 0.1, the transmission table will be trimmed to include only the central 80% of the area under the transmission curve. @@ -333,14 +327,16 @@ def _download_transmission_table(self) -> bool: logging.error(f"URL error occurred when downloading table for {self.full_name}: {e}") return False - def process_transmission_table(self, delta_wave: float | None = 5.0, trim_percentile: float | None = 0.1): + def process_transmission_table( + self, delta_wave: Optional[float] = 5.0, trim_percentile: Optional[float] = 0.1 + ): """Process the transmission table. Parameters ---------- - delta_wave : float | None, optional + delta_wave : Optional[float] = None The grid step of the wave grid. Default is 5.0 Angstroms. - trim_percentile : float | None, optional + trim_percentile : Optional[float] = None The percentile to trim the transmission table by. For example, if trim_percentile is 0.1, the transmission table will be trimmed to include only the central 80% of rows. """ @@ -350,15 +346,15 @@ def process_transmission_table(self, delta_wave: float | None = 5.0, trim_percen self.waves = self.processed_transmission_table[:, 0] - def _interpolate_transmission_table(self, table: np.ndarray, delta_wave: float | None) -> np.ndarray: + def _interpolate_transmission_table(self, table: np.ndarray, delta_wave: Optional[float]) -> np.ndarray: """Interpolate the transmission table to a new wave grid. Parameters ---------- table : np.ndarray A 2D array of wavelengths and transmissions. - delta_wave : float | None - The grid step of the wave grid. Default is 5.0 Angstroms. + delta_wave : float or None + The grid step of the wave grid. Returns ------- @@ -384,7 +380,7 @@ def _interpolate_transmission_table(self, table: np.ndarray, delta_wave: float | return np.column_stack((new_wavelengths, interpolated_transmissions)) def _trim_transmission_by_percentile( - self, table: np.ndarray, trim_percentile: float | None + self, table: np.ndarray, trim_percentile: Optional[float] ) -> np.ndarray: """Trim the transmission table such that it only includes the central (1 - 2*trim_percentile) of rows. From 4c03d1cf6377413aa590cbb548b42bdf04a012a1 Mon Sep 17 00:00:00 2001 From: Olivia Lynn Date: Mon, 16 Sep 2024 05:14:04 -0400 Subject: [PATCH 28/38] Temporarilly disable redshift in snia test --- tests/tdastro/sources/test_snia.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/tdastro/sources/test_snia.py b/tests/tdastro/sources/test_snia.py index 21745224..4e0245db 100644 --- a/tests/tdastro/sources/test_snia.py +++ b/tests/tdastro/sources/test_snia.py @@ -95,7 +95,7 @@ def test_snia_end2end( ra=NumpyRandomFunc("uniform", low=ra_min, high=ra_max), dec=NumpyRandomFunc("uniform", low=dec_min, high=dec_max), hostmass=NumpyRandomFunc("uniform", low=7, high=12), - redshift=NumpyRandomFunc("uniform", low=0.01, high=0.02), + redshift=0, ) distmod_func = DistModFromRedshift(host.redshift, H0=73.0, Omega_m=0.3) From a00a95c5aa6d9fd68761b6325c85ed7c865b7636 Mon Sep 17 00:00:00 2001 From: Olivia Lynn Date: Mon, 16 Sep 2024 05:51:40 -0400 Subject: [PATCH 29/38] Add force_download option for transmission tables; Switch to using **kwargs in PassbandGroup; Return redshift to snia test --- src/tdastro/astro_utils/passbands.py | 54 +++++++++---------- .../astro_utils/test_passband_groups.py | 2 +- tests/tdastro/astro_utils/test_passbands.py | 2 +- tests/tdastro/sources/test_snia.py | 4 +- 4 files changed, 30 insertions(+), 32 deletions(-) diff --git a/src/tdastro/astro_utils/passbands.py b/src/tdastro/astro_utils/passbands.py index 7a2338bc..f2353852 100644 --- a/src/tdastro/astro_utils/passbands.py +++ b/src/tdastro/astro_utils/passbands.py @@ -27,8 +27,7 @@ def __init__( self, preset: str = None, passband_parameters: list = None, - delta_wave: Optional[float] = 5.0, - trim_percentile: Optional[float] = 0.1, + **kwargs, ): """Construct a PassbandGroup object. @@ -49,23 +48,20 @@ def __init__( - units : str (either 'nm' or 'A') If survey is not LSST (or other survey with defined defaults), either a table_path or table_url must be provided. - delta_wave : float or None, optional - The grid step of the wave grid. Default is 5.0. - trim_percentile : float or None, optional - The percentile to trim the transmission table by. For example, if trim_percentile is 0.1, the - transmission table will be trimmed to include only the central 80% of rows. + **kwargs + Additional keyword arguments to pass to the Passband constructor. """ self.passbands = {} if preset is not None: - self._load_preset(preset, delta_wave, trim_percentile) + self._load_preset(preset, **kwargs) if passband_parameters is not None: for parameters in passband_parameters: - if "delta_wave" not in parameters: - parameters["delta_wave"] = delta_wave - if "trim_percentile" not in parameters: - parameters["trim_percentile"] = trim_percentile + # Add any missing parameters from kwargs + for key, value in kwargs.items(): + if key not in parameters: + parameters[key] = value passband = Passband(**parameters) self.passbands[passband.full_name] = passband @@ -78,28 +74,24 @@ def __str__(self) -> str: f"{', '.join(self.passbands.keys())}" ) - def _load_preset( - self, preset: str, delta_wave: Optional[float], trim_percentile: Optional[float] - ) -> None: + def _load_preset(self, preset: str, **kwargs) -> None: """Load a pre-defined set of passbands. Parameters ---------- preset : str The name of the pre-defined set of passbands to load. - delta_wave : float or None - The grid step of the wave grid. - trim_percentile : float or None - The percentile to trim the transmission table by. + **kwargs + Additional keyword arguments to pass to the Passband constructor. """ if preset == "LSST": self.passbands = { - "LSST_u": Passband("LSST", "u", delta_wave=delta_wave, trim_percentile=trim_percentile), - "LSST_g": Passband("LSST", "g", delta_wave=delta_wave, trim_percentile=trim_percentile), - "LSST_r": Passband("LSST", "r", delta_wave=delta_wave, trim_percentile=trim_percentile), - "LSST_i": Passband("LSST", "i", delta_wave=delta_wave, trim_percentile=trim_percentile), - "LSST_z": Passband("LSST", "z", delta_wave=delta_wave, trim_percentile=trim_percentile), - "LSST_y": Passband("LSST", "y", delta_wave=delta_wave, trim_percentile=trim_percentile), + "LSST_u": Passband("LSST", "u", **kwargs), + "LSST_g": Passband("LSST", "g", **kwargs), + "LSST_r": Passband("LSST", "r", **kwargs), + "LSST_i": Passband("LSST", "i", **kwargs), + "LSST_z": Passband("LSST", "z", **kwargs), + "LSST_y": Passband("LSST", "y", **kwargs), } else: raise ValueError(f"Unknown passband preset: {preset}") @@ -205,8 +197,9 @@ def __init__( table_path: Optional[str] = None, table_url: Optional[str] = None, units: Optional[Literal["nm", "A"]] = "A", + force_download: bool = False, ): - """Initialize a Passband object. + """Construct a Passband object. Parameters ---------- @@ -233,6 +226,9 @@ def __init__( Denotes whether the wavelength units of the table are nanometers ('nm') or Angstroms ('A'). By default 'A'. Does not affect the output units of the class, only the interpretation of the provided passband table. + force_download : bool, optional + If True, the transmission table will be downloaded even if it already exists locally. Default is + False. """ self.survey = survey self.filter_name = filter_name @@ -242,14 +238,14 @@ def __init__( self.table_url = table_url self.units = units - self._load_transmission_table() + self._load_transmission_table(force_download=force_download) self.process_transmission_table(delta_wave, trim_percentile) def __str__(self) -> str: """Return a string representation of the Passband.""" return f"Passband: {self.full_name}" - def _load_transmission_table(self) -> None: + def _load_transmission_table(self, force_download: bool = False) -> None: """Load a transmission table from a file (or download it if it doesn't exist). Table must have 2 columns: wavelengths and transmissions; wavelengths must be strictly increasing. @@ -264,7 +260,7 @@ def _load_transmission_table(self) -> None: os.path.dirname(__file__), f"passbands/{self.survey}/{self.filter_name}.dat" ) os.makedirs(os.path.dirname(self.table_path), exist_ok=True) - if not os.path.exists(self.table_path): + if force_download or not os.path.exists(self.table_path): self._download_transmission_table() # Load the table file try: diff --git a/tests/tdastro/astro_utils/test_passband_groups.py b/tests/tdastro/astro_utils/test_passband_groups.py index b2b60b37..8e130449 100644 --- a/tests/tdastro/astro_utils/test_passband_groups.py +++ b/tests/tdastro/astro_utils/test_passband_groups.py @@ -46,7 +46,7 @@ def test_passband_group_init(tmp_path): # Mock the transmission table files at passbands/LSST/.dat using patch transmission_table_array = np.array([[100, 0.5], [200, 0.75], [300, 0.25]]) - def mock_load_transmission_table(self): + def mock_load_transmission_table(self, **kwargs): self._loaded_table = transmission_table_array with patch.object(Passband, "_load_transmission_table", new=mock_load_transmission_table): diff --git a/tests/tdastro/astro_utils/test_passbands.py b/tests/tdastro/astro_utils/test_passbands.py index 9f896ede..6cfd5af2 100644 --- a/tests/tdastro/astro_utils/test_passbands.py +++ b/tests/tdastro/astro_utils/test_passbands.py @@ -20,7 +20,7 @@ def test_passband_init(): # Mock a transmission table file that we'll "find" at passbands/TEST/a.dat transmission_table_array = np.array([[100, 0.5], [200, 0.75], [300, 0.25]]) - def mock_load_transmission_table(self): + def mock_load_transmission_table(self, **kwargs): self._loaded_table = transmission_table_array with patch.object(Passband, "_load_transmission_table", new=mock_load_transmission_table): diff --git a/tests/tdastro/sources/test_snia.py b/tests/tdastro/sources/test_snia.py index 4e0245db..1d6cc94c 100644 --- a/tests/tdastro/sources/test_snia.py +++ b/tests/tdastro/sources/test_snia.py @@ -95,7 +95,7 @@ def test_snia_end2end( ra=NumpyRandomFunc("uniform", low=ra_min, high=ra_max), dec=NumpyRandomFunc("uniform", low=dec_min, high=dec_max), hostmass=NumpyRandomFunc("uniform", low=7, high=12), - redshift=0, + redshift=NumpyRandomFunc("uniform", low=0.01, high=0.02), ) distmod_func = DistModFromRedshift(host.redshift, H0=73.0, Omega_m=0.3) @@ -135,12 +135,14 @@ def test_snia_end2end( "filter_name": "u", "table_url": f"{url_base}baseline/total_u.dat", "units": "nm", + "force_download": True, }, { "survey": "LSST", "filter_name": "r", "table_url": f"{url_base}baseline/total_r.dat", "units": "nm", + "force_download": True, }, ], delta_wave=1, From 0f17c5a5435a14bec635bc2a1fb94230d70c9296 Mon Sep 17 00:00:00 2001 From: Olivia Lynn Date: Mon, 16 Sep 2024 05:55:15 -0400 Subject: [PATCH 30/38] Temporarily disable redshift in snia unit test --- tests/tdastro/sources/test_snia.py | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/tests/tdastro/sources/test_snia.py b/tests/tdastro/sources/test_snia.py index 1d6cc94c..4e0245db 100644 --- a/tests/tdastro/sources/test_snia.py +++ b/tests/tdastro/sources/test_snia.py @@ -95,7 +95,7 @@ def test_snia_end2end( ra=NumpyRandomFunc("uniform", low=ra_min, high=ra_max), dec=NumpyRandomFunc("uniform", low=dec_min, high=dec_max), hostmass=NumpyRandomFunc("uniform", low=7, high=12), - redshift=NumpyRandomFunc("uniform", low=0.01, high=0.02), + redshift=0, ) distmod_func = DistModFromRedshift(host.redshift, H0=73.0, Omega_m=0.3) @@ -135,14 +135,12 @@ def test_snia_end2end( "filter_name": "u", "table_url": f"{url_base}baseline/total_u.dat", "units": "nm", - "force_download": True, }, { "survey": "LSST", "filter_name": "r", "table_url": f"{url_base}baseline/total_r.dat", "units": "nm", - "force_download": True, }, ], delta_wave=1, From 805e8a7f68e6dee6b5043a9be3a5ab60197d48ff Mon Sep 17 00:00:00 2001 From: Olivia Lynn Date: Mon, 16 Sep 2024 06:01:50 -0400 Subject: [PATCH 31/38] Unit tests --- tests/tdastro/sources/test_snia.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/tests/tdastro/sources/test_snia.py b/tests/tdastro/sources/test_snia.py index 4e0245db..6903da4c 100644 --- a/tests/tdastro/sources/test_snia.py +++ b/tests/tdastro/sources/test_snia.py @@ -135,12 +135,14 @@ def test_snia_end2end( "filter_name": "u", "table_url": f"{url_base}baseline/total_u.dat", "units": "nm", + "force_download": True, }, { "survey": "LSST", "filter_name": "r", "table_url": f"{url_base}baseline/total_r.dat", "units": "nm", + "force_download": True, }, ], delta_wave=1, From 53aa789bc09f26af05e8733910a56ad674d0f415 Mon Sep 17 00:00:00 2001 From: Olivia Lynn Date: Mon, 16 Sep 2024 06:08:04 -0400 Subject: [PATCH 32/38] Return redshift to using NumpyRandomFunc --- tests/tdastro/sources/test_snia.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/tdastro/sources/test_snia.py b/tests/tdastro/sources/test_snia.py index 6903da4c..1d6cc94c 100644 --- a/tests/tdastro/sources/test_snia.py +++ b/tests/tdastro/sources/test_snia.py @@ -95,7 +95,7 @@ def test_snia_end2end( ra=NumpyRandomFunc("uniform", low=ra_min, high=ra_max), dec=NumpyRandomFunc("uniform", low=dec_min, high=dec_max), hostmass=NumpyRandomFunc("uniform", low=7, high=12), - redshift=0, + redshift=NumpyRandomFunc("uniform", low=0.01, high=0.02), ) distmod_func = DistModFromRedshift(host.redshift, H0=73.0, Omega_m=0.3) From e470a521f055ed3e4044251e45f0dd29a50af248 Mon Sep 17 00:00:00 2001 From: "Olivia R. Lynn" Date: Mon, 16 Sep 2024 23:45:10 -0400 Subject: [PATCH 33/38] Update src/tdastro/astro_utils/passbands.py Co-authored-by: Konstantin Malanchev --- src/tdastro/astro_utils/passbands.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/src/tdastro/astro_utils/passbands.py b/src/tdastro/astro_utils/passbands.py index f2353852..313db39f 100644 --- a/src/tdastro/astro_utils/passbands.py +++ b/src/tdastro/astro_utils/passbands.py @@ -208,7 +208,9 @@ def __init__( filter_name : str The filter_name of the passband: eg, "u". delta_wave : float or None, optional - The grid step of the wave grid. Default is 5.0. + The grid step of the wave grid, in angstroms. + It is typically used to downsample transmission using linear interpolation. + Default is 5 angstroms. If `None` the original grid is used. trim_percentile : float or None, optional The percentile to trim the transmission table by. For example, if trim_percentile is 0.1, the transmission table will be trimmed to include only the central 80% of the area under the From 9e35b10f3a05285cf254d486ca7f7eac508e10a1 Mon Sep 17 00:00:00 2001 From: "Olivia R. Lynn" Date: Mon, 16 Sep 2024 23:46:02 -0400 Subject: [PATCH 34/38] Update src/tdastro/astro_utils/passbands.py Co-authored-by: Konstantin Malanchev --- src/tdastro/astro_utils/passbands.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/tdastro/astro_utils/passbands.py b/src/tdastro/astro_utils/passbands.py index 313db39f..b1d3b143 100644 --- a/src/tdastro/astro_utils/passbands.py +++ b/src/tdastro/astro_utils/passbands.py @@ -398,7 +398,7 @@ def _trim_transmission_by_percentile( np.ndarray A 2D array of wavelengths and transmissions. """ - if trim_percentile is None: + if trim_percentile is None or trim_percentile == 0.0: return table if trim_percentile < 0 or trim_percentile > 0.5: raise ValueError("Trim percentile must be between 0 and 0.5.") From fa2a860a000a8e25f3c209838691160438b32898 Mon Sep 17 00:00:00 2001 From: Olivia Lynn Date: Mon, 16 Sep 2024 23:49:27 -0400 Subject: [PATCH 35/38] Remove "waves" from Passband constructor Paramters docstring --- src/tdastro/astro_utils/passbands.py | 6 ++---- 1 file changed, 2 insertions(+), 4 deletions(-) diff --git a/src/tdastro/astro_utils/passbands.py b/src/tdastro/astro_utils/passbands.py index b1d3b143..d75302db 100644 --- a/src/tdastro/astro_utils/passbands.py +++ b/src/tdastro/astro_utils/passbands.py @@ -179,7 +179,8 @@ class Passband: table_url : str The URL to download the transmission table file. waves : np.ndarray - The wavelengths of the transmission table. + The wavelengths of the transmission table. To be used when evaluating models to generate fluxes + that will be passed to fluxes_to_bandflux. _loaded_table : np.ndarray A 2D array of wavelengths and transmissions. This is the table loaded from the file, and is neither interpolated nor normalized. @@ -215,9 +216,6 @@ def __init__( The percentile to trim the transmission table by. For example, if trim_percentile is 0.1, the transmission table will be trimmed to include only the central 80% of the area under the transmission curve. - waves : np.ndarray - The wavelengths of the transmission table. To be used when evaluating models to generate fluxes - that will be passed to fluxes_to_bandflux. table_path : str, optional The path to the transmission table file. If None, the table path will be set to a default path; if no file exists at this location, the file will be downloaded from table_url. From acec858f15aadd919f93f39ab4372e2a2d8e2c8b Mon Sep 17 00:00:00 2001 From: Olivia Lynn Date: Tue, 17 Sep 2024 01:10:38 -0400 Subject: [PATCH 36/38] Change trim_percentile to trim_quantile; address related PR comments --- docs/notebooks/passband-demo.ipynb | 41 +++++++++++-- src/tdastro/astro_utils/passbands.py | 61 +++++++++---------- .../astro_utils/test_passband_groups.py | 6 +- tests/tdastro/astro_utils/test_passbands.py | 53 ++++++++-------- 4 files changed, 97 insertions(+), 64 deletions(-) diff --git a/docs/notebooks/passband-demo.ipynb b/docs/notebooks/passband-demo.ipynb index 5b05f19a..2b946a45 100644 --- a/docs/notebooks/passband-demo.ipynb +++ b/docs/notebooks/passband-demo.ipynb @@ -52,7 +52,7 @@ "\n", "# Load a model\n", "input_times = np.array([1001.0, 1002.0, 1003.0, 1004.0, 1005.0])\n", - "input_wavelengths = np.linspace(4000.0, 8000.0, 5)\n", + "input_wavelengths = np.linspace(4000.0, 10_000.0, 5)\n", "input_fluxes = np.array(\n", " [\n", " [1.0, 5.0, 2.0, 3.0, 1.0],\n", @@ -121,7 +121,7 @@ "metadata": {}, "outputs": [], "source": [ - "def plot_lightcurve(bandfluxes):\n", + "def plot_lightcurve():\n", " \"\"\"Plot the passband-normalized lightcurve.\"\"\"\n", " fig, ax = plt.subplots()\n", " ax.set_title(\"Passband-Normalized Lightcurve\")\n", @@ -135,7 +135,7 @@ " plt.show()\n", "\n", "\n", - "plot_lightcurve(bandfluxes)" + "plot_lightcurve()" ] }, { @@ -145,13 +145,44 @@ "### Update Wave Grid" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "By increasing our `delta_wave` parameter, we increase the grid step of our transmission table, and the fluxes caluculated from `passband_group.waves`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "passband_group.process_transmission_tables(delta_wave=30.0)\n", + "\n", + "times = np.linspace(1000.0, 1006.0, 40)\n", + "wavelengths = passband_group.waves\n", + "fluxes = spline_model.evaluate(times, wavelengths)\n", + "\n", + "bandfluxes = passband_group.fluxes_to_bandfluxes(fluxes)\n", + "\n", + "plot_lightcurve()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "By setting our `trim_quantile` parameter to None, we disable the automatic trimming performed on transmission table to remove the upper and lower tails." + ] + }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ - "passband_group.process_transmission_tables(delta_wavelength=20.0, trim_percentile=None)\n", + "passband_group.process_transmission_tables(delta_wave=30.0, trim_quantile=None)\n", "\n", "times = np.linspace(1000.0, 1006.0, 40)\n", "wavelengths = passband_group.waves\n", @@ -159,7 +190,7 @@ "\n", "bandfluxes = passband_group.fluxes_to_bandfluxes(fluxes)\n", "\n", - "plot_lightcurve(bandfluxes)" + "plot_lightcurve()" ] } ], diff --git a/src/tdastro/astro_utils/passbands.py b/src/tdastro/astro_utils/passbands.py index d75302db..10c8adff 100644 --- a/src/tdastro/astro_utils/passbands.py +++ b/src/tdastro/astro_utils/passbands.py @@ -44,7 +44,7 @@ def __init__( - table_path : str - table_url : str - delta_wave : float - - trim_percentile : float + - trim_quantile : float - units : str (either 'nm' or 'A') If survey is not LSST (or other survey with defined defaults), either a table_path or table_url must be provided. @@ -104,7 +104,7 @@ def _update_waves(self) -> None: self.waves = np.unique(np.concatenate([passband.waves for passband in self.passbands.values()])) def process_transmission_tables( - self, delta_wave: Optional[float] = 5.0, trim_percentile: Optional[float] = 0.1 + self, delta_wave: Optional[float] = 5.0, trim_quantile: Optional[float] = 1e-3 ): """Process the transmission tables for all passbands in the group; recalculate group's wave attribute. @@ -112,12 +112,12 @@ def process_transmission_tables( ---------- delta_wave : float or None, optional The grid step of the wave grid. Default is 5.0. - trim_percentile : float or None, optional - The percentile to trim the transmission table by. For example, if trim_percentile is 0.1, the - transmission table will be trimmed to include only the central 80% of rows. + trim_quantile : float or None, optional + The quantile to trim the transmission table by. For example, if trim_quantile is 1e-3, the + transmission table will be trimmed to include only the central 99.8% of rows. """ for passband in self.passbands.values(): - passband.process_transmission_table(delta_wave, trim_percentile) + passband.process_transmission_table(delta_wave, trim_quantile) self._update_waves() @@ -194,7 +194,7 @@ def __init__( survey: str, filter_name: str, delta_wave: Optional[float] = 5.0, - trim_percentile: Optional[float] = 0.1, + trim_quantile: Optional[float] = 1e-3, table_path: Optional[str] = None, table_url: Optional[str] = None, units: Optional[Literal["nm", "A"]] = "A", @@ -212,9 +212,9 @@ def __init__( The grid step of the wave grid, in angstroms. It is typically used to downsample transmission using linear interpolation. Default is 5 angstroms. If `None` the original grid is used. - trim_percentile : float or None, optional - The percentile to trim the transmission table by. For example, if trim_percentile is 0.1, the - transmission table will be trimmed to include only the central 80% of the area under the + trim_quantile : float or None, optional + The quantile to trim the transmission table by. For example, if trim_quantile is 1e-3, the + transmission table will be trimmed to include only the central 99.8% of the area under the transmission curve. table_path : str, optional The path to the transmission table file. If None, the table path will be set to a default path; @@ -239,7 +239,7 @@ def __init__( self.units = units self._load_transmission_table(force_download=force_download) - self.process_transmission_table(delta_wave, trim_percentile) + self.process_transmission_table(delta_wave, trim_quantile) def __str__(self) -> str: """Return a string representation of the Passband.""" @@ -324,7 +324,7 @@ def _download_transmission_table(self) -> bool: return False def process_transmission_table( - self, delta_wave: Optional[float] = 5.0, trim_percentile: Optional[float] = 0.1 + self, delta_wave: Optional[float] = 5.0, trim_quantile: Optional[float] = 1e-3 ): """Process the transmission table. @@ -332,12 +332,12 @@ def process_transmission_table( ---------- delta_wave : Optional[float] = None The grid step of the wave grid. Default is 5.0 Angstroms. - trim_percentile : Optional[float] = None - The percentile to trim the transmission table by. For example, if trim_percentile is 0.1, the - transmission table will be trimmed to include only the central 80% of rows. + trim_quantile : Optional[float] = None + The quantile to trim the transmission table by. For example, if trim_quantile is 1e-3, the + transmission table will be trimmed to include only the central 99.8% of rows. """ interpolated_table = self._interpolate_transmission_table(self._loaded_table, delta_wave) - trimmed_table = self._trim_transmission_by_percentile(interpolated_table, trim_percentile) + trimmed_table = self._trim_transmission_by_quantile(interpolated_table, trim_quantile) self.processed_transmission_table = self._normalize_transmission_table(trimmed_table) self.waves = self.processed_transmission_table[:, 0] @@ -375,31 +375,30 @@ def _interpolate_transmission_table(self, table: np.ndarray, delta_wave: Optiona interpolated_transmissions = spline(new_wavelengths) return np.column_stack((new_wavelengths, interpolated_transmissions)) - def _trim_transmission_by_percentile( - self, table: np.ndarray, trim_percentile: Optional[float] - ) -> np.ndarray: - """Trim the transmission table such that it only includes the central (1 - 2*trim_percentile) of rows. + def _trim_transmission_by_quantile(self, table: np.ndarray, trim_quantile: Optional[float]) -> np.ndarray: + """Trim the transmission table so that it only includes the central (100 - 2*trim_quartile)% of rows. - E.g., if trim_percentile is 0.1, the transmission table will be trimmed to include only the central - 80% of rows. + E.g., if trim_quantile is 1e-3, the transmission table will be trimmed to include only the central + 99.8% of rows. Parameters ---------- table : np.ndarray A 2D array of wavelengths and transmissions. - trim_percentile : float - The percentile to trim the transmission table by. For example, if trim_percentile is 0.1, the - transmission table will be trimmed to include only the central 80% of rows. + trim_quantile : float + The quantile to trim the transmission table by. For example, if trim_quantile is 1e-3, the + transmission table will be trimmed to include only the central 99.8% of rows. Must be greater than + or equal to 0 and less than 0.5. Returns ------- np.ndarray A 2D array of wavelengths and transmissions. """ - if trim_percentile is None or trim_percentile == 0.0: + if trim_quantile is None or trim_quantile == 0.0: return table - if trim_percentile < 0 or trim_percentile > 0.5: - raise ValueError("Trim percentile must be between 0 and 0.5.") + if trim_quantile < 0 or trim_quantile >= 0.5: + raise ValueError(f"Trim quantile must be between 0 and 0.5; got {trim_quantile}.") # Separate wavelengths and transmissions wavelengths = table[:, 0] @@ -411,9 +410,9 @@ def _trim_transmission_by_percentile( # Normalize cumulative area to range from 0 to 1 cumulative_area /= cumulative_area[-1] - # Find indices where the cumulative area exceeds the trim percentiles - lower_bound = np.searchsorted(cumulative_area, trim_percentile) - upper_bound = np.searchsorted(cumulative_area, 1 - trim_percentile) + # Find indices where the cumulative area exceeds the trim quantiles + lower_bound = max(np.searchsorted(cumulative_area, trim_quantile, side="right") - 1, 0) + upper_bound = np.searchsorted(cumulative_area, 1 - trim_quantile) # Trim the table to the desired range trimmed_table = table[lower_bound : upper_bound + 1] diff --git a/tests/tdastro/astro_utils/test_passband_groups.py b/tests/tdastro/astro_utils/test_passband_groups.py index 8e130449..6ce5ba8e 100644 --- a/tests/tdastro/astro_utils/test_passband_groups.py +++ b/tests/tdastro/astro_utils/test_passband_groups.py @@ -4,7 +4,7 @@ from tdastro.astro_utils.passbands import Passband, PassbandGroup -def create_passband_group(path, delta_wave=5.0, trim_percentile=None): +def create_passband_group(path, delta_wave=5.0, trim_quantile=None): """Helper function to create a PassbandGroup object for testing.""" # Initialize requirements for PassbandGroup object survey = "TEST" @@ -30,7 +30,7 @@ def create_passband_group(path, delta_wave=5.0, trim_percentile=None): "filter_name": filter_name, "table_path": table_dir / f"{filter_name}.dat", "delta_wave": delta_wave, - "trim_percentile": trim_percentile, + "trim_quantile": trim_quantile, } ) return PassbandGroup(passband_parameters=passbands) @@ -112,7 +112,7 @@ def test_passband_group_str(tmp_path): def test_passband_group_fluxes_to_bandfluxes(tmp_path): """Test the fluxes_to_bandfluxes method of the PassbandGroup class.""" # Test with simple passband group - test_passband_group = create_passband_group(tmp_path, delta_wave=20, trim_percentile=None) + test_passband_group = create_passband_group(tmp_path, delta_wave=20, trim_quantile=None) # Create some mock flux data with the same number of columns as wavelengths in our PassbandGroup flux = np.linspace(test_passband_group.waves * 10, 100, 5) diff --git a/tests/tdastro/astro_utils/test_passbands.py b/tests/tdastro/astro_utils/test_passbands.py index 6cfd5af2..ea5f36e3 100644 --- a/tests/tdastro/astro_utils/test_passbands.py +++ b/tests/tdastro/astro_utils/test_passbands.py @@ -119,12 +119,12 @@ def test_process_transmission_table(tmp_path): # Mock the methods that _process_transmission_table wraps, to check each is called once with ( patch.object(a_band, "_interpolate_transmission_table") as mock_interp_table, - patch.object(a_band, "_trim_transmission_by_percentile") as mock_trim_table, + patch.object(a_band, "_trim_transmission_by_quantile") as mock_trim_table, patch.object(a_band, "_normalize_transmission_table") as mock_norm_table, ): # Call the _process_transmission_table method - delta_wave, trim_percentile = 1.0, 0.05 - a_band.process_transmission_table(delta_wave, trim_percentile) + delta_wave, trim_quantile = 1.0, 0.05 + a_band.process_transmission_table(delta_wave, trim_quantile) # Check that each method is called once mock_interp_table.assert_called_once_with(a_band._loaded_table, delta_wave) @@ -132,8 +132,8 @@ def test_process_transmission_table(tmp_path): mock_norm_table.assert_called_once() # Now call without mocking, to check waves set correctly (other values checked in method-specific tests) - delta_wave, trim_percentile = 5.0, None - a_band.process_transmission_table(delta_wave, trim_percentile) + delta_wave, trim_quantile = 5.0, None + a_band.process_transmission_table(delta_wave, trim_quantile) np.testing.assert_allclose(a_band.waves, np.arange(100, 301, delta_wave)) @@ -156,46 +156,49 @@ def test_interpolate_transmission_table(tmp_path): def test_trim_transmission_table(tmp_path): - """Test the _trim_transmission_by_percentile method of the Passband class.""" + """Test the _trim_transmission_by_quantile method of the Passband class.""" # Test: transmission table with only 3 points transmission_table = "100 0.5\n200 0.75\n300 0.25\n" a_band = create_test_passband(tmp_path, transmission_table) # Trim the transmission table by 5% (should remove the last point) - table = a_band._trim_transmission_by_percentile(a_band._loaded_table, trim_percentile=0.05) + table = a_band._trim_transmission_by_quantile(a_band._loaded_table, trim_quantile=0.05) np.testing.assert_allclose(table, np.array([[100, 0.5], [200, 0.75]])) # Trim the transmission table by 40% (should still preserve the first point, as table is skewed) - table = a_band._trim_transmission_by_percentile(a_band._loaded_table, trim_percentile=0.4) + table = a_band._trim_transmission_by_quantile(a_band._loaded_table, trim_quantile=0.4) np.testing.assert_allclose(table, np.array([[100, 0.5], [200, 0.75]])) - # Check no trimming if percentile is 0 - table = a_band._trim_transmission_by_percentile(a_band._loaded_table, trim_percentile=None) + # Check no trimming if quantile is 0 + table = a_band._trim_transmission_by_quantile(a_band._loaded_table, trim_quantile=None) np.testing.assert_allclose(table, np.array([[100, 0.5], [200, 0.75], [300, 0.25]])) - # Check we raise an error if the percentile is not between 0 and 0.5 + # Check we raise an error if the quantile is not greater or equal to 0 and less than 0.5 with pytest.raises(ValueError): - a_band._trim_transmission_by_percentile(a_band._loaded_table, trim_percentile=0.6) + a_band._trim_transmission_by_quantile(a_band._loaded_table, trim_quantile=0.5) with pytest.raises(ValueError): - a_band._trim_transmission_by_percentile(a_band._loaded_table, trim_percentile=-0.1) + a_band._trim_transmission_by_quantile(a_band._loaded_table, trim_quantile=-0.1) # Test 2: larger, more normal transmission table transmission_table = "100 0.05\n200 0.1\n300 0.25\n400 0.5\n500 0.8\n600 0.6\n700 0.4\n800 0.2\n900 0.1\n" b_band = create_test_passband(tmp_path, transmission_table, filter_name="b") - # Trim the transmission table by 5% (should remove the first and last points) - table = b_band._trim_transmission_by_percentile(b_band._loaded_table, trim_percentile=0.05) + # Trim the transmission table by 5% (should remove the last point) + table = b_band._trim_transmission_by_quantile(b_band._loaded_table, trim_quantile=0.05) np.testing.assert_allclose( - table, np.array([[200, 0.1], [300, 0.25], [400, 0.5], [500, 0.8], [600, 0.6], [700, 0.4], [800, 0.2]]) + table, + np.array( + [[100, 0.05], [200, 0.1], [300, 0.25], [400, 0.5], [500, 0.8], [600, 0.6], [700, 0.4], [800, 0.2]] + ), ) # Trim the transmission table by 40% (should remove most points) - table = b_band._trim_transmission_by_percentile(b_band._loaded_table, trim_percentile=0.4) - np.testing.assert_allclose(table, np.array([[400, 0.5], [500, 0.8]])) + table = b_band._trim_transmission_by_quantile(b_band._loaded_table, trim_quantile=0.4) + np.testing.assert_allclose(table, np.array([[300, 0.25], [400, 0.5], [500, 0.8]])) - # Check no trimming if percentile is 0 - table = b_band._trim_transmission_by_percentile(b_band._loaded_table, trim_percentile=None) + # Check no trimming if quantile is 0 + table = b_band._trim_transmission_by_quantile(b_band._loaded_table, trim_quantile=None) np.testing.assert_allclose( table, np.array( @@ -222,18 +225,18 @@ def test_trim_transmission_table(tmp_path): c_band = create_test_passband(tmp_path, transmission_table, filter_name="c") # Trim the transmission table by 5% on each side - table = c_band._trim_transmission_by_percentile(c_band._loaded_table, trim_percentile=0.05) + table = c_band._trim_transmission_by_quantile(c_band._loaded_table, trim_quantile=0.05) assert len(table) < len(c_band._loaded_table) original_area = np.trapz(c_band._loaded_table[:, 1], x=c_band._loaded_table[:, 0]) trimmed_area = np.trapz(table[:, 1], x=table[:, 0]) - assert np.isclose(trimmed_area, original_area * 0.9, rtol=0.01) + assert trimmed_area >= (original_area * 0.9) def test_passband_normalize_transmission_table(tmp_path): """Test the _normalize_transmission_table method of the Passband class.""" transmission_table = "100 0.5\n200 0.75\n300 0.25\n" - a_band = create_test_passband(tmp_path, transmission_table, delta_wave=100, trim_percentile=None) + a_band = create_test_passband(tmp_path, transmission_table, delta_wave=100, trim_quantile=None) # Normalize the transmission table (we skip interpolation as grid already matches) a_band._normalize_transmission_table(a_band._loaded_table) @@ -256,7 +259,7 @@ def test_passband_normalize_transmission_table(tmp_path): def test_passband_fluxes_to_bandflux(tmp_path): """Test the fluxes_to_bandflux method of the Passband class.""" transmission_table = "100 0.5\n200 0.75\n300 0.25\n" - a_band = create_test_passband(tmp_path, transmission_table, delta_wave=100, trim_percentile=None) + a_band = create_test_passband(tmp_path, transmission_table, delta_wave=100, trim_quantile=None) # Define some mock flux values and calculate our expected bandflux flux = np.array( @@ -273,7 +276,7 @@ def test_passband_fluxes_to_bandflux(tmp_path): np.testing.assert_allclose(in_band_flux, expected_in_band_flux) # Test with a different set of fluxes, regridding the transmission table - a_band.process_transmission_table(delta_wave=50, trim_percentile=None) + a_band.process_transmission_table(delta_wave=50, trim_quantile=None) flux = np.array( [ [100.0, 12.0, 1.0, 0.5, 0.25], From 3e1998749118cf7ca4727dc3b1bcc2896b87969f Mon Sep 17 00:00:00 2001 From: Olivia Lynn Date: Wed, 18 Sep 2024 10:18:56 -0400 Subject: [PATCH 37/38] Add LSST transmission tables to unit test data directory (with README disclaimer) --- tests/tdastro/conftest.py | 6 + tests/tdastro/data/README.md | 4 + tests/tdastro/data/passbands/LSST/g.dat | 1813 +++++ tests/tdastro/data/passbands/LSST/i.dat | 8508 +++++++++++++++++++++++ tests/tdastro/data/passbands/LSST/r.dat | 8508 +++++++++++++++++++++++ tests/tdastro/data/passbands/LSST/u.dat | 8508 +++++++++++++++++++++++ tests/tdastro/data/passbands/LSST/y.dat | 8508 +++++++++++++++++++++++ tests/tdastro/data/passbands/LSST/z.dat | 8508 +++++++++++++++++++++++ tests/tdastro/sources/test_snia.py | 8 +- 9 files changed, 44366 insertions(+), 5 deletions(-) create mode 100644 tests/tdastro/data/README.md create mode 100644 tests/tdastro/data/passbands/LSST/g.dat create mode 100644 tests/tdastro/data/passbands/LSST/i.dat create mode 100644 tests/tdastro/data/passbands/LSST/r.dat create mode 100644 tests/tdastro/data/passbands/LSST/u.dat create mode 100644 tests/tdastro/data/passbands/LSST/y.dat create mode 100644 tests/tdastro/data/passbands/LSST/z.dat diff --git a/tests/tdastro/conftest.py b/tests/tdastro/conftest.py index 6311b9e2..1116e9ad 100644 --- a/tests/tdastro/conftest.py +++ b/tests/tdastro/conftest.py @@ -34,3 +34,9 @@ def opsim_small(test_data_dir): def opsim_shorten(test_data_dir): """Return the file path for the bad grid input file.""" return os.path.join(test_data_dir, "opsim_shorten.db") + + +@pytest.fixture +def passbands_dir(test_data_dir): + """Return the file path for passbands directory.""" + return os.path.join(test_data_dir, "passbands") diff --git a/tests/tdastro/data/README.md b/tests/tdastro/data/README.md new file mode 100644 index 00000000..3302068f --- /dev/null +++ b/tests/tdastro/data/README.md @@ -0,0 +1,4 @@ +# TDAstro Test Data + +- **passbands/:** + - Please note that the transmission tables included in this repository are for unit testing purposes only. We do not guarantee that they will be kept up to date, so users are encouraged to download and store their own files. \ No newline at end of file diff --git a/tests/tdastro/data/passbands/LSST/g.dat b/tests/tdastro/data/passbands/LSST/g.dat new file mode 100644 index 00000000..5fff70c5 --- /dev/null +++ b/tests/tdastro/data/passbands/LSST/g.dat @@ -0,0 +1,1813 @@ +# LSST Throughputs files created from syseng_throughputs repo +# Version 1.9 +# sha1 fcc05772f99427e4a45cd1b9da1628dded9a06d5 +# Aerosols added to atmosphere +# Wavelen_cutoff_BLUE 385.60 +# Wavelen_cutoff_RED 566.30 +# Wavelength(nm) Throughput(0-1) +3864 4.99572e-14 +3865 0.000254262 +3866 0.000509039 +3867 0.0010057 +3868 0.00150336 +3869 0.00201547 +3870 0.00252861 +3871 0.00303006 +3872 0.00353276 +3873 0.00405021 +3874 0.00456896 +3875 0.00508899 +3876 0.00560871 +3877 0.00611587 +3878 0.00662401 +3879 0.0071467 +3880 0.00767039 +3881 0.00818144 +3882 0.00869346 +3883 0.0092201 +3884 0.00974774 +3885 0.0102627 +3886 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b/tests/tdastro/data/passbands/LSST/i.dat @@ -0,0 +1,8508 @@ +# LSST Throughputs files created from syseng_throughputs repo +# Version 1.9 +# sha1 fcc05772f99427e4a45cd1b9da1628dded9a06d5 +# Aerosols added to atmosphere +# Wavelen_cutoff_BLUE 669.90 +# Wavelen_cutoff_RED 837.80 +# Wavelength(nm) Throughput(0-1) +300.0 0.0 +300.1 0.0 +300.20000000000005 0.0 +300.30000000000007 0.0 +300.4000000000001 0.0 +300.5000000000001 0.0 +300.60000000000014 0.0 +300.70000000000016 0.0 +300.8000000000002 0.0 +300.9000000000002 0.0 +301.0000000000002 0.0 +301.10000000000025 0.0 +301.2000000000003 0.0 +301.3000000000003 0.0 +301.4000000000003 0.0 +301.50000000000034 0.0 +301.60000000000036 0.0 +301.7000000000004 0.0 +301.8000000000004 0.0 +301.90000000000043 0.0 +302.00000000000045 0.0 +302.1000000000005 0.0 +302.2000000000005 0.0 +302.3000000000005 0.0 +302.40000000000055 0.0 +302.50000000000057 0.0 +302.6000000000006 0.0 +302.7000000000006 0.0 +302.80000000000064 0.0 +302.90000000000066 0.0 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"LSST", "filter_name": "r", - "table_url": f"{url_base}baseline/total_r.dat", + "table_path": f"{passbands_dir}/LSST/r.dat", "units": "nm", - "force_download": True, }, ], delta_wave=1, From 410712077b6da0de3a3490773dd4d54fbe17d805 Mon Sep 17 00:00:00 2001 From: Olivia Lynn Date: Wed, 18 Sep 2024 10:24:45 -0400 Subject: [PATCH 38/38] Raise error on both preset/params=None in PBG; PR formatting comments --- src/tdastro/astro_utils/passbands.py | 8 ++++++-- 1 file changed, 6 insertions(+), 2 deletions(-) diff --git a/src/tdastro/astro_utils/passbands.py b/src/tdastro/astro_utils/passbands.py index 10c8adff..28e1e60c 100644 --- a/src/tdastro/astro_utils/passbands.py +++ b/src/tdastro/astro_utils/passbands.py @@ -53,6 +53,9 @@ def __init__( """ self.passbands = {} + if preset is None and passband_parameters is None: + raise ValueError("PassbandGroup must be initialized with either a preset or passband_parameters.") + if preset is not None: self._load_preset(preset, **kwargs) @@ -330,9 +333,9 @@ def process_transmission_table( Parameters ---------- - delta_wave : Optional[float] = None + delta_wave : Optional[float] = 5.0 The grid step of the wave grid. Default is 5.0 Angstroms. - trim_quantile : Optional[float] = None + trim_quantile : Optional[float] = 1e-3 The quantile to trim the transmission table by. For example, if trim_quantile is 1e-3, the transmission table will be trimmed to include only the central 99.8% of rows. """ @@ -437,6 +440,7 @@ def _normalize_transmission_table(self, transmission_table: np.ndarray) -> np.nd ------- np.ndarray A 2D array of wavelengths and normalized transmissions. + Raises ------ ValueError