From c0744af05bd11e5c79e154720c464310b7a5f0d2 Mon Sep 17 00:00:00 2001 From: Jeremy Kubica <104161096+jeremykubica@users.noreply.github.com> Date: Thu, 21 Nov 2024 12:45:34 -0500 Subject: [PATCH] Initial Implementation of a JAX Salt2 model --- src/tdastro/astro_utils/salt2_color_law.py | 134 + src/tdastro/sources/salt2_jax.py | 121 + src/tdastro/utils/__init__.py | 0 src/tdastro/utils/bicubic_interp.py | 364 + src/tdastro/utils/io_utils.py | 4 + .../astro_utils/test_salt_color_law.py | 52 + .../data/truncated-salt2-h17/SALT2.INFO | 19 + .../salt2_color_correction.dat | 8 + .../salt2_color_dispersion.dat | 636 + .../salt2_lc_dispersion_scaling.dat | 1000 ++ .../salt2_lc_relative_covariance_01.dat | 500 + .../salt2_lc_relative_variance_0.dat | 500 + .../salt2_lc_relative_variance_1.dat | 500 + .../salt2_spec_covariance_01.dat | 10000 +++++++++++++++ .../salt2_spec_variance_0.dat | 10000 +++++++++++++++ .../salt2_spec_variance_1.dat | 10000 +++++++++++++++ .../truncated-salt2-h17/salt2_template_0.dat | 10426 ++++++++++++++++ .../truncated-salt2-h17/salt2_template_1.dat | 10426 ++++++++++++++++ tests/tdastro/sources/test_salt2.py | 50 + .../make_truncated_salt2_table.py | 57 + tests/tdastro/utils/test_bicubic_interp.py | 230 + 21 files changed, 55027 insertions(+) create mode 100644 src/tdastro/astro_utils/salt2_color_law.py create mode 100644 src/tdastro/sources/salt2_jax.py create mode 100644 src/tdastro/utils/__init__.py create mode 100644 src/tdastro/utils/bicubic_interp.py create mode 100644 tests/tdastro/astro_utils/test_salt_color_law.py create mode 100755 tests/tdastro/data/truncated-salt2-h17/SALT2.INFO create mode 100755 tests/tdastro/data/truncated-salt2-h17/salt2_color_correction.dat create mode 100755 tests/tdastro/data/truncated-salt2-h17/salt2_color_dispersion.dat create mode 100644 tests/tdastro/data/truncated-salt2-h17/salt2_lc_dispersion_scaling.dat create mode 100644 tests/tdastro/data/truncated-salt2-h17/salt2_lc_relative_covariance_01.dat create mode 100644 tests/tdastro/data/truncated-salt2-h17/salt2_lc_relative_variance_0.dat create mode 100644 tests/tdastro/data/truncated-salt2-h17/salt2_lc_relative_variance_1.dat create mode 100644 tests/tdastro/data/truncated-salt2-h17/salt2_spec_covariance_01.dat create mode 100644 tests/tdastro/data/truncated-salt2-h17/salt2_spec_variance_0.dat create mode 100644 tests/tdastro/data/truncated-salt2-h17/salt2_spec_variance_1.dat create mode 100644 tests/tdastro/data/truncated-salt2-h17/salt2_template_0.dat create mode 100644 tests/tdastro/data/truncated-salt2-h17/salt2_template_1.dat create mode 100644 tests/tdastro/sources/test_salt2.py create mode 100755 tests/tdastro/testing_utils/make_truncated_salt2_table.py create mode 100644 tests/tdastro/utils/test_bicubic_interp.py diff --git a/src/tdastro/astro_utils/salt2_color_law.py b/src/tdastro/astro_utils/salt2_color_law.py new file mode 100644 index 00000000..ace90476 --- /dev/null +++ b/src/tdastro/astro_utils/salt2_color_law.py @@ -0,0 +1,134 @@ +"""The ColorLaw used by SALT models as defined by in (Guy J., 2007) + +It is adapted from sncosmo's SALT2ColorLaw class (but implemented in JAX): +https://github.com/sncosmo/sncosmo/blob/v2.10.1/sncosmo/salt2utils.pyx +""" + +import jax.numpy as jnp +import numpy as np + +# Constants used in SALT2ColorLaw computations (from: +# https://github.com/sncosmo/sncosmo/blob/v2.10.1/sncosmo/salt2utils.pyx) +_SALT2CL_B = 4302.57 # B-band-ish wavelength +_SALT2CL_V = 5428.55 # V-band-ish wavelength +_WAVESCALE = 1.0 / (_SALT2CL_V - _SALT2CL_B) + + +class SALT2ColorLaw: + """An object that applies the color law to the given wavelengths. + + Parameters + ---------- + wave_min : float + The minimum wavelength (in angstroms) + wave_max : float + The maximum wavelength (in angstroms) + coeffs : list, numpy array, or jax array + The <= 6 coefficients of the polynomial to use. + + Attributes + ---------- + coeffs : JAX array + The final 7 coefficients to use (based on the <= 6 provided in the parameters). + scaled_wave_min : float + The minimum wavelength shifted and scaled. + scaled_wave_max : float + The maximum wavelength shifted and scaled. + value_at_min : float + The value of the polynomial at wave_min. + value_at_max : float + The value of the polynomial at wave_max. + _exponents : JAX array + A precomputed array of the exponents to use. + """ + + def __init__(self, wave_min, wave_max, coeffs): + # Create the internal coefficient array. The new first entry is 1.0 minus the + # sum of the given entries. The first six given entries are then listed. + coeffs = np.array(coeffs) + num_coeffs = min(len(coeffs), 6) + + padded_coeffs = np.zeros(7) + padded_coeffs[1 : (num_coeffs + 1)] = np.array(coeffs)[0:num_coeffs] + padded_coeffs[0] = 1.0 - np.sum(padded_coeffs) + self.coeffs = jnp.asarray(padded_coeffs) + + # Compute the bounds for the wavelengths and the value of the polynomial at both bounds. + self.scaled_wave_min = (wave_min - _SALT2CL_B) * _WAVESCALE + self.scaled_wave_max = (wave_max - _SALT2CL_B) * _WAVESCALE + + self.exponents = jnp.arange(1, 8, 1) + self.value_at_min = jnp.sum(self.coeffs * jnp.power(self.scaled_wave_min, self.exponents)) + self.value_at_max = jnp.sum(self.coeffs * jnp.power(self.scaled_wave_max, self.exponents)) + + # Precompute the polynomials derivative at the min and max wavelength. + dcoeffs = jnp.arange(2, 8, 1) * self.coeffs[1:7] + dexponents = jnp.arange(1, 7, 1) + self.deriv_at_min = jnp.sum(dcoeffs * jnp.power(self.scaled_wave_min, dexponents)) + self.coeffs[0] + self.deriv_at_max = jnp.sum(dcoeffs * jnp.power(self.scaled_wave_max, dexponents)) + self.coeffs[0] + + @classmethod + def from_file(cls, filename): + """Create the SALT2ColorLaw object from data in a file. + + Parameters + ---------- + filename : str + The name of the file to load. + """ + with open(filename, mode="r") as f: + data = f.read().split() + + # The first line holds the number of coefficients N and the next N lines + # each hold a single coefficient. + num_coeff = int(data[0]) + coeffs = np.array(data[1 : (1 + num_coeff)], dtype=float) + + # The rest of the lines (if any) are meta-data with a label and value on each line. + wave_min = 3000.0 + wave_max = 7000.0 + for i in range(1 + num_coeff, len(data), 2): + if "min_lambda" in data[i]: + wave_min = float(data[i + 1]) + elif "max_lambda" in data[i]: + wave_max = float(data[i + 1]) + elif "version" in data[i]: + version = int(data[i + 1]) + if version != 1: + raise RuntimeError(f"Unsupported version {version}.") + + return SALT2ColorLaw(wave_min, wave_max, coeffs) + + def apply(self, wavelengths): + """Apply the color law to the given wavelengths. + + Parameters + ---------- + wavelengths : array + The wavelengths in angstroms. + """ + num_waves = len(wavelengths) + shifted_wave = (jnp.asarray(wavelengths) - _SALT2CL_B) * _WAVESCALE + + # Compute the three cases of interest. + # 1) If the shifted wave is past the lower bound, extrapolate a value based on + # the value and derivative at that bound. + below = self.value_at_min + self.deriv_at_min * (shifted_wave - self.scaled_wave_min) + # 2) If the shifted wave is past the upper bound, extrapolate a value based on + # the value and derivative at that bound. + above = self.value_at_max + self.deriv_at_max * (shifted_wave - self.scaled_wave_max) + # 3) If the shifted value is in the middle, use the polynomial. + wave_T = jnp.reshape(shifted_wave, (num_waves, 1)) + coeffs_all = jnp.tile(self.coeffs, (num_waves, 1)) + middle = jnp.sum((coeffs_all * jnp.power(wave_T, self.exponents)).T, axis=0) + + result = -jnp.where( + shifted_wave < self.scaled_wave_min, + below, + jnp.where( + shifted_wave > self.scaled_wave_max, + above, + middle, + ), + ) + return result diff --git a/src/tdastro/sources/salt2_jax.py b/src/tdastro/sources/salt2_jax.py new file mode 100644 index 00000000..985c320c --- /dev/null +++ b/src/tdastro/sources/salt2_jax.py @@ -0,0 +1,121 @@ +from pathlib import Path + +from tdastro.astro_utils.salt2_color_law import SALT2ColorLaw +from tdastro.sources.physical_model import PhysicalModel +from tdastro.utils.bicubic_interp import BicubicInterpolator + + +class SALT2JaxModel(PhysicalModel): + """A SALT2 model implemented with JAX for it can use auto-differentiation. + + The model is defined in (Guy J., 2007) as: + + flux(time, wave) = x0 * [M0(time, wave) + x1 * M1(time, wave)] * exp(c * CL(wave)) + + where x0, x1, and c are given parameters, M0 is the average spectral sequence, + M1 is the first compoment to describe variability, and CL is the average color + correction law. + + We use the formulation in sncosmo where CL is defined such that: + + flux(time, wave) = x0 * [M0(time, wave) + x1 * M1(time, wave)] * 10 ** (-0.4 * c * CL(wave)) + + This class is based on the sncosmo implementation at: + https://github.com/sncosmo/sncosmo/blob/v2.10.1/sncosmo/models.py + The wrapped sncosmo version in sncosmo_models.py is faster and should be used + when auto-differentiation is not needed. + + Attributes + ---------- + _m0_model : BicubicInterpolator + The interpolator for the m0 parameter. + _m1_model : BicubicInterpolator + The interpolator for the m1 parameter. + _colorlaw : SALT2ColorLaw + The data to apply the color law. + + Parameters + ---------- + x0 : parameter + The SALT2 x0 parameter. + x1 : parameter + The SALT2 x1 parameter. + c : parameter + The SALT2 c parameter. + model_dir : `str` + The path for the model file directory. + Default: "" + m0_filename : `str` + The file name for the m0 model component. + Default: "salt2_template_0.dat" + m1_filename : `str` + The file name for the m1 model component. + Default: "salt2_template_1.dat" + cl_filename : `str` + The file name of the color law correction coefficients. + Default: "salt2_color_correction.dat", + **kwargs : `dict`, optional + Any additional keyword arguments. + """ + + def __init__( + self, + x0=None, + x1=None, + c=None, + model_dir="", + m0_filename="salt2_template_0.dat", + m1_filename="salt2_template_1.dat", + cl_filename="salt2_color_correction.dat", + **kwargs, + ): + super().__init__(**kwargs) + + # Add the model specific parameters. + self.add_parameter("x0", x0, **kwargs) + self.add_parameter("x1", x1, **kwargs) + self.add_parameter("c", c, **kwargs) + + # Load the data files. + model_path = Path(model_dir) + self._m0_model = BicubicInterpolator.from_grid_file( + model_path / m0_filename, + scale_factor=1e-12, + ) + self._m1_model = BicubicInterpolator.from_grid_file( + model_path / m1_filename, + scale_factor=1e-12, + ) + + # Use the default color correction values. + self._colorlaw = SALT2ColorLaw.from_file(model_path / cl_filename) + + def compute_flux(self, phase, wavelengths, graph_state, **kwargs): + """Draw effect-free observations for this object. + + Parameters + ---------- + phase : `numpy.ndarray` + A length T array of rest frame timestamps. + wavelengths : `numpy.ndarray`, optional + A length N array of wavelengths (in angstroms). + graph_state : `GraphState` + An object mapping graph parameters to their values. + **kwargs : `dict`, optional + Any additional keyword arguments. + + Returns + ------- + flux_density : `numpy.ndarray` + A length T x N matrix of SED values (in nJy). + """ + m0_vals = self._m0_model(phase, wavelengths) + m1_vals = self._m1_model(phase, wavelengths) + params = self.get_local_params(graph_state) + + flux_density = ( + params["x0"] + * (m0_vals + params["x1"] * m1_vals) + * 10.0 ** (-0.4 * self._colorlaw.apply(wavelengths) * params["c"]) + ) + return flux_density diff --git a/src/tdastro/utils/__init__.py b/src/tdastro/utils/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/src/tdastro/utils/bicubic_interp.py b/src/tdastro/utils/bicubic_interp.py new file mode 100644 index 00000000..6c8afce0 --- /dev/null +++ b/src/tdastro/utils/bicubic_interp.py @@ -0,0 +1,364 @@ +"""The BicubicInterpolator is used by SALT models. + +It is adapted from sncosmo's BicubicInterpolator class (but implemented in JAX): +https://github.com/sncosmo/sncosmo/blob/v2.10.1/sncosmo/salt2utils.pyx +""" + +import jax.numpy as jnp +from jax import jit, vmap + +from tdastro.utils.io_utils import read_grid_data + + +@jit +def _kernel_value(input_vals): + """A vectorized (JAX-ized) form of the kernval method from: + https://github.com/sncosmo/sncosmo/blob/v2.10.1/sncosmo/salt2utils.pyx + + Uses: + A = -0.5 + B = A + 2.0 = 1.5 + C = A + 3.0 = 2.5 + """ + x = jnp.abs(input_vals) + + # Start with the case of 1.0 <= x <= 2.0. + result = -0.5 * (-4.0 + x * (8.0 + x * (-5.0 + x))) + + # Override cases where x < 1.0 + result = jnp.where(x < 1.0, x * x * (1.5 * x - 2.5) + 1.0, result) + + # Override cases where x > 2.0 + result = jnp.where(x > 2.0, 0.0, result) + return result + + +def _compute_linear(ix, iy, ax, ay, z_vals): + """Computes the linear interpolation (used for the edges). This operation is + broken out into a function so it can be jit compiled and vmapped. + + Parameters + ---------- + ix, iy : int + The location of the current point in the array of z values. + ax, ay : float + The current point distance relative to the respective nodes in the z array. + z_vals : JAX Array + An 2d matrix of z values. + + Returns + ------- + float + The result of the linear interpolation at this point. + """ + return (1.0 - ax) * ((1.0 - ay) * z_vals[ix][iy] + ay * z_vals[ix][iy + 1]) + ax * ( + (1.0 - ay) * z_vals[ix + 1][iy] + ay * z_vals[ix + 1][iy + 1] + ) + + +def _compute_cubic(ix, iy, dx, dy, z_vals): + """Computes the bicubic interpolation (used for the center). This operation is + broken out into a function so it can be jit compiled and vmapped. + + Parameters + ---------- + ix, iy : int + The location of the current point in the array of z values. + dx, dy : float + The current point distance relative to the respective nodes in the z array. + z_vals : JAX Array + An 2d matrix of z values. + + Returns + ------- + float + The result of the bicubic interpolation at this point. + """ + wx = _kernel_value(jnp.asarray([dx - 1.0, dx, dx + 1.0, dx + 2.0])) + wy = _kernel_value(jnp.asarray([dy - 1.0, dy, dy + 1.0, dy + 2.0])) + + return ( + wx[0] + * ( + wy[0] * z_vals[ix - 1][iy - 1] + + wy[1] * z_vals[ix - 1][iy] + + wy[2] * z_vals[ix - 1][iy + 1] + + wy[3] * z_vals[ix - 1][iy + 2] + ) + + wx[1] + * ( + wy[0] * z_vals[ix][iy - 1] + + wy[1] * z_vals[ix][iy] + + wy[2] * z_vals[ix][iy + 1] + + wy[3] * z_vals[ix][iy + 2] + ) + + wx[2] + * ( + wy[0] * z_vals[ix + 1][iy - 1] + + wy[1] * z_vals[ix + 1][iy] + + wy[2] * z_vals[ix + 1][iy + 1] + + wy[3] * z_vals[ix + 1][iy + 2] + ) + + wx[3] + * ( + wy[0] * z_vals[ix + 2][iy - 1] + + wy[1] * z_vals[ix + 2][iy] + + wy[2] * z_vals[ix + 2][iy + 1] + + wy[3] * z_vals[ix + 2][iy + 2] + ) + ) + + +@jit +def expand_to_cross_products(x_vals, y_vals): + """Create the unraveled arrays representing the grid of points from each access. + + Parameters + ---------- + x_vals : array-like + A length N array of the x values. + y_vals : array-like + A length M array of the y values. + + Returns + ------- + all_x : JAX array + A length N * M array of the x values. + all_y : JAX array + A length N * M array of the y values. + """ + grids = jnp.meshgrid(x_vals, y_vals, indexing="ij") + x_all = jnp.ravel(grids[0]) + y_all = jnp.ravel(grids[1]) + return x_all, y_all + + +class BicubicInterpolator: + """An object that performs bicubic interpolation over a 2-d grid. + + Parameters + ---------- + x_vals : array-like + The values along the x-axis of the grid. The values must be sorted + and at regular step sizes. + y_vals : array-like + The values along the y-axis of the grid. The values must be sorted + and at regular step sizes. + z_vals : array-like + The values along the z-axis of the grid. + + Attributes + ---------- + x_vals : BicubicAxis + The values along the x-axis of the grid stored with precomputed information. + y_vals : BicubicAxis + The values along the y-axis of the grid stored with precomputed information. + z_vals : JAX array + The values along the z-axis of the grid. + """ + + def __init__(self, x_vals, y_vals, z_vals): + # Load and validate the x and y values. + self.x_vals = BicubicAxis(jnp.asarray(x_vals)) + self.y_vals = BicubicAxis(jnp.asarray(y_vals)) + + # Load an validate the z values. + self.z_vals = jnp.asarray(z_vals) + if len(self.z_vals.shape) != 2: + raise ValueError(f"z values should be a 2-d array. Found shape={self.z_vals.shape}") + if self.z_vals.shape[0] != len(self.x_vals) or self.z_vals.shape[1] != len(self.y_vals): + raise ValueError( + f"z values wrong shape. Expected shape=({len(self.x_vals)}, {len(self.y_vals)})." + f" Found shape={self.z_vals.shape}." + ) + self._compute_linear = vmap(jit(_compute_linear), in_axes=(0, 0, 0, 0, None)) + self._compute_cubic = vmap(jit(_compute_cubic), in_axes=(0, 0, 0, 0, None)) + + @classmethod + def from_grid_file(cls, filename, scale_factor=1.0): + """Load the grid data from an ASCII file and create a BicubicInterpolator. + + Parameters + ---------- + filename : str + The name of the grid file. + scale_factor : float + A multiplicative scale factor for the z values. + Default: 1.0 + """ + x_vals, y_vals, z_vals = read_grid_data(filename) + z_vals *= scale_factor + return BicubicInterpolator(x_vals, y_vals, z_vals) + + def __call__(self, x_q, y_q): + """Evaluate the bicubic interpolation at a grid of points. + + Parameters + ---------- + x_q : array-like + The N-length array of x values. + y_q : array-like + The M-length array of y values. + + Returns + ------- + results : `jaxlib.xla_extension.ArrayImpl` + An N x M array of interpolated values for each (x, y) pair. + """ + x_q = jnp.asarray(x_q) + y_q = jnp.asarray(y_q) + n_xq = len(x_q) + n_yq = len(y_q) + + # Find the first index *before* each of the query values with + # the n-1 index in each dimension mapped to n-2. + ix = self.x_vals.find_indices(x_q) + iy = self.y_vals.find_indices(y_q) + ix_all, iy_all = expand_to_cross_products(ix, iy) + + # Compute the weights to use for linear interpolation and perform the linear interpolation. + wx, wy = expand_to_cross_products( + (x_q - self.x_vals.values[ix]) / (self.x_vals.values[ix + 1] - self.x_vals.values[ix]), + (y_q - self.y_vals.values[iy]) / (self.y_vals.values[iy + 1] - self.y_vals.values[iy]), + ) + lin_res = self._compute_linear(ix_all, iy_all, wx, wy, self.z_vals) + + # Compute the cubic kernel weights for each point and the resulting + # cubic interpolated values. + dx, dy = expand_to_cross_products( + (self.x_vals.values[ix] - x_q) / (self.x_vals.values[ix + 1] - self.x_vals.values[ix]), + (self.y_vals.values[iy] - y_q) / (self.y_vals.values[iy + 1] - self.y_vals.values[iy]), + ) + quad_res = self._compute_cubic(ix_all, iy_all, dx, dy, self.z_vals) + + # Fill in the values from the different interpolations. Use 0.0 for anything out of + # bounds. Use linear interpolation for anything along the edges. And use cubic + # interpolation for the points in the middle. + x_out, y_out = expand_to_cross_products( + self.x_vals.out_of_bounds(x_q), + self.y_vals.out_of_bounds(y_q), + ) + out_of_bounds = x_out | y_out + + x_edge, y_edge = expand_to_cross_products( + (ix == 0) | (ix > self.x_vals.num_vals - 3), + (iy == 0) | (iy > self.y_vals.num_vals - 3), + ) + on_edge = x_edge | y_edge + + results = jnp.where(out_of_bounds, 0.0, jnp.where(on_edge, lin_res, quad_res)) + results = results.reshape(n_xq, n_yq) + return results + + +class BicubicAxis: + """A helper class that represents values for an axis of bicubic interpolation + with restrictions on acceptable data to match the SALT2 and SALT3 models. + + Restrictions include: + - Data must contain at least 3 values. + - Data must be sorted. + - Data must be spaced at regular steps. + + Attributes + ---------- + values : JAX Array + The values of the range. + min_val : float + The starting value of the range. + max_val : float + The maximum value of the range. + num_vals : int + The number of values in the range. + regular_steps : bool + Indicates whether the axis uses regularly sized steps. + step_size : float + The step size of the range. + """ + + def __init__(self, values): + # Load and validate the y values. + self.values = jnp.asarray(values) + if len(self.values.shape) != 1: + raise ValueError( + f"The RegularRange values should be a 1-d array. Found shape={self.values.shape}." + ) + if len(self.values) < 3: + raise ValueError( + f"Insufficient points for RegularRange. Required >= 3. Found {len(self.values)}." + ) + if jnp.any(self.values[:-1] >= self.values[1:]): + raise ValueError("The RegularRange values must be in sorted order.") + self.num_vals = len(self.values) + self.min_val = self.values[0] + self.max_val = self.values[-1] + + # Check the step sizes are regular (allowing for inprecision when things are written as + # floats). If it is regular we can use a faster algorithm to find the indices. + # We pick and save a single core search function, so JAX does not encounter an "if" during + # tracing (at the cost of another function call during find_indices). + step_sizes = self.values[1:] - self.values[:-1] + min_step = jnp.min(step_sizes) + max_step = jnp.max(step_sizes) + if max_step - min_step > 1e-6: + self.regular_steps = False + self.step_size = None + self._initial_search = self._search_nonregular + else: + self.regular_steps = True + self.step_size = 0.5 * min_step + 0.5 * max_step + self._initial_search = self._search_regular + + def __len__(self): + return self.num_vals + + def __str__(self): + return f"BicubicAxis [{self.min_val},{self.max_val}]. step={self.step_size}. size={self.num_vals}" + + def _search_regular(self, query_pts): + """Do an initial search for the query points indices given regular steps.""" + return jnp.floor((query_pts - self.min_val) / self.step_size).astype(int) + + def _search_nonregular(self, query_pts): + """Do an initial search for the query points indices given non-regular steps.""" + return jnp.searchsorted(self.values, query_pts, side="right") - 1 + + def find_indices(self, query_pts): + """Finds the first index *before* each of the query values with + the n - 1 index in each dimension mapped to n - 2. + + values[idx[i]] <= query_pts[i] < values[idx[i] + 1] + for all i where idx[i] > 0 and idx[i] < n - 2. + + Parameters + ---------- + query_pts : array-like + The values of the query points. + + Returns + ------- + idx : JAX Array + A pair of arrays with the indices. + """ + query_pts = jnp.asarray(query_pts) + idx = self._initial_search(query_pts) + idx = jnp.where(idx < 0, 0, idx) + idx = jnp.where(idx >= self.num_vals - 1, self.num_vals - 2, idx) + + return idx + + def out_of_bounds(self, values): + """Compute a Boolean array of the values that are out of bounds. + + Parameters + ---------- + values : array-like + The N values to test + + Returns + ------- + results : JAX array + A length N array indicating whether each element is out of bounds. + """ + values = jnp.asarray(values) + return (values < self.min_val) | (values > self.max_val) diff --git a/src/tdastro/utils/io_utils.py b/src/tdastro/utils/io_utils.py index 926c2c15..c8b98457 100644 --- a/src/tdastro/utils/io_utils.py +++ b/src/tdastro/utils/io_utils.py @@ -1,3 +1,5 @@ +import logging + import numpy as np from astropy.table import Table @@ -35,6 +37,8 @@ def read_grid_data(input_file, format="ascii", validate=False): ------ ``ValueError`` if any data validation fails. """ + logging.debug(f"Loading file {input_file} (format={format})") + data = Table.read(input_file, format=format, comment=r"\s*#") if len(data.colnames) != 3: raise ValueError( diff --git a/tests/tdastro/astro_utils/test_salt_color_law.py b/tests/tdastro/astro_utils/test_salt_color_law.py new file mode 100644 index 00000000..20f8187d --- /dev/null +++ b/tests/tdastro/astro_utils/test_salt_color_law.py @@ -0,0 +1,52 @@ +import os + +import jax.numpy as jnp +import pytest +from tdastro.astro_utils.salt2_color_law import ( + _SALT2CL_B, + _SALT2CL_V, + _WAVESCALE, + SALT2ColorLaw, +) + + +def test_salt2_color_law(): + """Test that we can create and query a simple SALT2ColorLaw object.""" + test_cl = SALT2ColorLaw(_SALT2CL_B, _SALT2CL_V, [0.5, 0.25, 0.1]) + + # The coefficients are shifted (with 1 - sum(others) prepended) and zero padded. + assert jnp.allclose(test_cl.coeffs, jnp.asarray([0.15, 0.5, 0.25, 0.1, 0.0, 0.0, 0.0])) + assert test_cl.scaled_wave_min == pytest.approx(0.0) + assert test_cl.scaled_wave_max == pytest.approx(1.0) + assert test_cl.value_at_min == pytest.approx(0.0) + assert test_cl.value_at_max == pytest.approx(1.0) + assert test_cl.deriv_at_min == pytest.approx(0.15) + assert test_cl.deriv_at_max == pytest.approx(2.3) + + # Test that we can compute the results for some manually specified points. + half_step = (_SALT2CL_V - _SALT2CL_B) / 2.0 + test_wavelengths = [ + _SALT2CL_B - half_step, # Shifted and scaled -> -0.5 + _SALT2CL_B, # Shifted and scaled -> 0.0 + _SALT2CL_B + half_step, # Shifted and scaled -> 0.5 + _SALT2CL_V, # Shifted and scaled -> 1.0 + _SALT2CL_V + half_step, # Shifted and scaled -> 1.5 + ] + results = test_cl.apply(test_wavelengths) + + assert results[0] == pytest.approx(0.0 + 0.15 * 0.5) + assert results[1] == pytest.approx(0.0) + assert results[2] == pytest.approx(-0.2375) + assert results[3] == pytest.approx(-1.0) + assert results[4] == pytest.approx(-1.0 - 2.3 * 0.5) + + +def test_salt2_color_law_load(test_data_dir): + """Test loading a Salt2ColorLaw object from a file.""" + filename = os.path.join(test_data_dir, "truncated-salt2-h17/salt2_color_correction.dat") + test_cl = SALT2ColorLaw.from_file(filename) + + expected_coeffs = [1.83205876, -1.33154627, 0.61225710, -0.12117791, 0.00840832, 0.0, 0.0] + assert jnp.allclose(test_cl.coeffs, jnp.asarray(expected_coeffs)) + assert test_cl.scaled_wave_min == pytest.approx((2800 - _SALT2CL_B) * _WAVESCALE) + assert test_cl.scaled_wave_max == pytest.approx((9500 - _SALT2CL_B) * _WAVESCALE) diff --git a/tests/tdastro/data/truncated-salt2-h17/SALT2.INFO b/tests/tdastro/data/truncated-salt2-h17/SALT2.INFO new file mode 100755 index 00000000..f91c628d --- /dev/null +++ b/tests/tdastro/data/truncated-salt2-h17/SALT2.INFO @@ -0,0 +1,19 @@ +# SALT2 extended to the IR by Steve Rodney +# Used in WFIRST Simulation paper: https://arxiv.org/abs/1702.01747 + +RESTLAMBDA_RANGE: 2000. 23000. + +COLORLAW_VERSION: 1 +COLORCOR_PARAMS: 2800 9500 4 -1.33154627 0.61225710 -0.12117791 0.00840832 +COLOR_OFFSET: 0.0 + +MAG_OFFSET: 0.27 +SEDFLUX_INTERP_OPT: 1 # 1=>linear, 2=>spline +ERRMAP_INTERP_OPT: 1 # 0=snake off; 1=>linear 2=>spline +ERRMAP_KCOR_OPT: 1 # 1/0 => on/off + +MAGERR_FLOOR: 0.005 # don;t allow smaller error than this +MAGERR_LAMOBS: 0.1 2000 4000 # magerr minlam maxlam +MAGERR_LAMREST: 0.1 100 200 # magerr minlam maxlam + +SIGMA_INT: 0.090 \ No newline at end of file diff --git a/tests/tdastro/data/truncated-salt2-h17/salt2_color_correction.dat b/tests/tdastro/data/truncated-salt2-h17/salt2_color_correction.dat new file mode 100755 index 00000000..70cc7c1e --- /dev/null +++ b/tests/tdastro/data/truncated-salt2-h17/salt2_color_correction.dat @@ -0,0 +1,8 @@ +4 +-1.33154627 +0.61225710 +-0.12117791 +0.00840832 +Salt2ExtinctionLaw.version 1 +Salt2ExtinctionLaw.min_lambda 2800 +Salt2ExtinctionLaw.max_lambda 9500 diff --git a/tests/tdastro/data/truncated-salt2-h17/salt2_color_dispersion.dat b/tests/tdastro/data/truncated-salt2-h17/salt2_color_dispersion.dat new file mode 100755 index 00000000..c1526e25 --- /dev/null +++ b/tests/tdastro/data/truncated-salt2-h17/salt2_color_dispersion.dat @@ -0,0 +1,636 @@ +# lam +# dispersion +2000 1.30891 +2010 1.27841 +2020 1.2487 +2030 1.21976 +2040 1.19156 +2050 1.1641 +2060 1.13733 +2070 1.11126 +2080 1.08585 +2090 1.06109 +2100 1.03696 +2110 1.01344 +2120 0.990522 +2130 0.968182 +2140 0.946407 +2150 0.925181 +2160 0.904488 +2170 0.884315 +2180 0.864646 +2190 0.84547 +2200 0.826771 +2210 0.808537 +2220 0.790756 +2230 0.773416 +2240 0.756504 +2250 0.740009 +2260 0.72392 +2270 0.708226 +2280 0.692916 +2290 0.677981 +2300 0.66341 +2310 0.649194 +2320 0.635322 +2330 0.621787 +2340 0.608579 +2350 0.59569 +2360 0.583111 +2370 0.570834 +2380 0.558851 +2390 0.547154 +2400 0.535737 +2410 0.524591 +2420 0.51371 +2430 0.503087 +2440 0.492715 +2450 0.482587 +2460 0.472698 +2470 0.463041 +2480 0.453611 +2490 0.444401 +2500 0.435405 +2510 0.426619 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+ 20.00 6980 1.5904363e-04 + 20.00 6990 1.6628986e-04 + 20.00 7000 1.7734701e-04 diff --git a/tests/tdastro/sources/test_salt2.py b/tests/tdastro/sources/test_salt2.py new file mode 100644 index 00000000..ca165377 --- /dev/null +++ b/tests/tdastro/sources/test_salt2.py @@ -0,0 +1,50 @@ +import numpy as np +from sncosmo.models import SALT2Source +from tdastro.sources.salt2_jax import SALT2JaxModel + + +def test_salt2_model(test_data_dir): + """Test loading a SALT2 object from a file and querying it.""" + dir_name = test_data_dir / "truncated-salt2-h17" + model = SALT2JaxModel(x0=0.5, x1=0.2, c=1.0, model_dir=dir_name) + + assert model._colorlaw is not None + assert model._m0_model is not None + assert model._m1_model is not None + + # Test compared to values computed via sncosmo's implementation that + # fall within the range of the truncated grid. We multiple by 1e12 + # for comparison precision purposes. + times = np.array([1.0, 2.1, 3.9, 4.0]) + waves = np.array([4000.0, 4102.0, 4200.0]) + expected_times_1e12 = np.array( + [ + [0.12842110, 0.17791164, 0.17462753], + [0.12287933, 0.17060205, 0.17152248], + [0.11121435, 0.15392100, 0.16234423], + [0.11051545, 0.15288580, 0.16170497], + ] + ) + + flux = model.evaluate(times, waves) + assert np.allclose(flux * 1e12, expected_times_1e12) + + +def test_salt2_model_parity(test_data_dir): + """Test loading a SALT2 object from a file and test we get the same + results as the sncosmo version. + """ + dir_name = test_data_dir / "truncated-salt2-h17" + td_model = SALT2JaxModel(x0=0.4, x1=0.3, c=1.1, model_dir=dir_name) + sn_model = SALT2Source(modeldir=dir_name) + sn_model.set(x0=0.4, x1=0.3, c=1.1) + + # Test compared to values computed via sncosmo's implementation that + # fall within the range of the truncated grid. We multiple by 1e12 + # for comparison precision purposes. + times = np.arange(-1.0, 15.0, 0.01) + waves = np.arange(3800.0, 4200.0, 0.5) + + flux_td = td_model.evaluate(times, waves) + flux_sn = sn_model._flux(times, waves) + assert np.allclose(flux_td * 1e12, flux_sn * 1e12) diff --git a/tests/tdastro/testing_utils/make_truncated_salt2_table.py b/tests/tdastro/testing_utils/make_truncated_salt2_table.py new file mode 100755 index 00000000..ccc391c8 --- /dev/null +++ b/tests/tdastro/testing_utils/make_truncated_salt2_table.py @@ -0,0 +1,57 @@ +#!/usr/bin/env python + +import argparse + + +def parse_args(args): + """Parse the command line arguments. + + Parameters + ---------- + args : `list` of `str` + The command line arguments. + + Returns + ------- + `argparse.Namespace` + The parsed arguments. + """ + parser = argparse.ArgumentParser(description="Create a truncated version of a SALT2 table.") + parser.add_argument("--input", default="", help="The input SALT2 data file.") + parser.add_argument("--output", default="", help="The file name for the output data.") + parser.add_argument("--t_min", default=-100.0, help="The minimum time to include.") + parser.add_argument("--t_max", default=100.0, help="The maxmimum time to include.") + parser.add_argument("--w_min", default=0.0, help="The minimum wavelength to include.") + parser.add_argument("--w_max", default=25000.0, help="The maxmimum wavelength to include.") + return parser.parse_args(args) + + +def main(args=None): + """Subsample an OpSim file and save it to a new file. + + Parameters + ---------- + args : `list` of `str`, optional + The command line arguments. + """ + args = parse_args(args) + if args.input == args.output: + raise ValueError("Cannot overwrite file.") + times = (float(args.t_min), float(args.t_max)) + waves = (float(args.w_min), float(args.w_max)) + + print(f"Input file: {args.input}") + print(f"Output file: {args.output}") + print(f"Time range: {times}") + print(f"Wavelength range: {waves}") + + with open(args.input, "r") as input_file: + with open(args.output, "w") as output_file: + for line in input_file: + tokens = line.split() + if (times[0] <= float(tokens[0]) <= times[1]) and (waves[0] <= float(tokens[1]) <= waves[1]): + output_file.write(line) + + +if __name__ == "__main__": + main() diff --git a/tests/tdastro/utils/test_bicubic_interp.py b/tests/tdastro/utils/test_bicubic_interp.py new file mode 100644 index 00000000..9a200c99 --- /dev/null +++ b/tests/tdastro/utils/test_bicubic_interp.py @@ -0,0 +1,230 @@ +import os + +import jax.numpy as jnp +import numpy as np +import pytest +from tdastro.utils.bicubic_interp import ( + BicubicAxis, + BicubicInterpolator, + _kernel_value, + expand_to_cross_products, +) + + +def test_expand_to_cross_products(): + """Test that we can create cross product arrays.""" + x_vals = np.arange(5, 10) + y_vals = np.arange(-3, 3) + num_x = len(x_vals) + num_y = len(y_vals) + + # Manually fill in the expected results. + expected_x = np.zeros(num_x * num_y) + expected_y = np.zeros(num_x * num_y) + count = 0 + for row in range(num_x): + for col in range(num_y): + expected_x[count] = x_vals[row] + expected_y[count] = y_vals[col] + count += 1 + + all_x, all_y = expand_to_cross_products(x_vals, y_vals) + assert np.array_equal(all_x, expected_x) + assert np.array_equal(all_y, expected_y) + + +def test_bicubic_range(): + """Test that we can create and query a BicubicAxis object.""" + xvals = BicubicAxis([0.1 * i for i in range(100)]) + assert xvals.min_val == 0.0 + assert xvals.max_val == 9.9 + assert xvals.num_vals == 100 + assert xvals.step_size == pytest.approx(0.1) + + # Test that we can run out_of_bounds + values = [-1.0, 2.0, 11.0, 5.0, -0.1, 3.5, 4.0] + expected = [True, False, True, False, True, False, False] + is_out = xvals.out_of_bounds(values) + assert np.array_equal(is_out, expected) + + # Test that we can run find_indices + ix = xvals.find_indices(values) + assert np.array_equal(ix, [0, 20, 98, 50, 0, 35, 40]) + + # Run a larger find_indices search. + n_x = len(xvals) + x_q = jnp.asarray([0.04 * i - 0.1 for i in range(400)]) + ix = xvals.find_indices(x_q) + assert jnp.all(ix >= 0) + assert jnp.all(ix <= n_x - 2) + assert jnp.all((ix == n_x - 2) | (x_q < xvals.values[ix + 1])) + assert jnp.all((ix == 0) | (xvals.values[ix] <= x_q)) + + # Test that we fail for invalid BicubicAxis range objects. + with pytest.raises(ValueError): + _ = BicubicAxis([0.0, 0.1]) # Too few points + with pytest.raises(ValueError): + _ = BicubicAxis([0.0, 0.2, 0.1]) # Not sorted + + +def test_bicubic_range_non_regular(): + """Test that we can create and query a BicubicAxis object + without regular steps in the values.""" + xvals = BicubicAxis([0.1, 0.2, 0.4, 0.5, 0.6, 0.65, 0.7]) + assert xvals.min_val == 0.1 + assert xvals.max_val == 0.7 + assert xvals.num_vals == 7 + assert xvals.step_size is None + + # Test that we can run out_of_bounds + values = [0.05, 0.15, 0.25, 0.8, 0.5] + expected = [True, False, False, True, False] + is_out = xvals.out_of_bounds(values) + assert np.array_equal(is_out, expected) + + # Test that we can run find_indices + ix = xvals.find_indices(values) + assert np.array_equal(ix, [0, 0, 1, 5, 3]) + + +def test_bicubic_interpolator_simple(): + """Test that we can create and query a bicubic interpolator.""" + x_vals = np.arange(1.0, 5.0, 1.0) + y_vals = np.arange(0.0, 3.0, 0.5) + z_vals = np.full((len(x_vals), len(y_vals)), 1.0) + interp_obj = BicubicInterpolator(x_vals, y_vals, z_vals) + + x_queries = np.arange(0.5, 5.5, 0.5) + y_queries = np.arange(-0.5, 3.5, 0.5) + results = interp_obj(x_queries, y_queries) + + # Everything within the grid should be 1.0 and everything + # outside the grid should be 0.0. + for i, x_q in enumerate(x_queries): + for j, y_q in enumerate(y_queries): + if (x_q < 1.0) or (x_q > 4.0) or (y_q < 0.0) or (y_q > 2.5): + assert np.abs(results[i, j]) < 1e-8 + else: + assert np.abs(results[i, j] - 1.0) < 1e-8 + + +def test_bicubic_interpolator(): + """Test that we can create and query a bicubic interpolator.""" + x_vals = np.arange(1.0, 5.0, 1.0) + num_x = len(x_vals) + + y_vals = np.arange(-1.0, 2.0, 0.5) + num_y = len(y_vals) + + # Make a wavey plane of values. + z_vals = np.empty((num_x, num_y)) + for i in range(num_x): + for j in range(num_y): + if j % 2 == 0: + z_vals[i, j] = i + 0.2 * j + else: + z_vals[i, j] = i - 0.1 * j + + # Pick some query points. + x_q = jnp.asarray([-0.5, 1.0, 1.5, 2.0, 2.1, 3.4, 4.0, 5.5]) + y_q = jnp.asarray([-1.5, 0.0, 0.5, 1.1, 2.0, 3.5]) + + # Expected values (as computed by the sncosmo version) + expected = np.array( + [ + [0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + [0.0, 0.4, -0.3, 0.54, 0.0, 0.0], + [0.0, 0.9, 0.2, 1.04, 0.0, 0.0], + [0.0, 1.4, 0.7, 1.54, 0.0, 0.0], + [0.0, 1.5, 0.8, 1.64, 0.0, 0.0], + [0.0, 2.8, 2.1, 2.94, 0.0, 0.0], + [0.0, 3.4, 2.7, 3.54, 0.0, 0.0], + [0.0, 0.0, 0.0, 0.0, 0.0, 0.0], + ] + ) + + # Do the JAX interpolation. + interp_obj = BicubicInterpolator(x_vals, y_vals, z_vals) + res_jax = interp_obj(x_q, y_q) + + for i in range(len(x_q)): + for j in range(len(y_q)): + if jnp.abs(res_jax[i, j] - expected[i, j]) > 1e-5: + print(f"TEST {i}, {j} ({x_q[i]}, {y_q[j]}) = {res_jax[i, j]} vs {expected[i, j]}") + + assert jnp.allclose(expected, res_jax, rtol=1e-3, atol=1e-4) + + +def test_bicubic_interpolator2(): + """Test that we can create and query a bicubic interpolatorusing other values.""" + x_vals = [0.25 * i for i in range(100)] + y_vals = [j / 8.0 for j in range(320)] + z_vals = jnp.reshape(jnp.arange(len(x_vals) * len(y_vals)), (len(x_vals), len(y_vals))) + + x_q = jnp.asarray([-0.5, 0.0, 1.0, 22.2, 49.0, 50.5]) + y_q = jnp.asarray([-1.0, 5.0, 13.4, 21.5, 41.0]) + + # Expected values (as computed by the sncosmo version) + expected = np.array( + [ + [0.0, 0.0, 0.0, 0.0, 0.0], + [0.0, 40.0, 107.19999695, 172.0, 0.0], + [0.0, 1320.0, 1387.19999695, 1452.0, 0.0], + [0.0, 28456.00097656, 28523.20097351, 28588.00097656, 0.0], + [0.0, 0.0, 0.0, 0.0, 0.0], + [0.0, 0.0, 0.0, 0.0, 0.0], + ] + ) + + # Do the JAX interpolation. + interp_obj = BicubicInterpolator(x_vals, y_vals, z_vals) + res_jax = interp_obj(x_q, y_q) + + assert jnp.allclose(expected, res_jax, rtol=1e-5, atol=1e-5) + + +def test_kernel_values(): + """Test that we can evaluate the kernel with the JAX function + and get the same results as with the original function.""" + input = jnp.asarray([-1.5, -1.1, 0.0, 0.5, 1.0, 1.5, 2.0, 2.5]) + expected = jnp.asarray([-0.0625, -0.0405, 1.0, 0.5625, 0.0, -0.0625, 0.0, 0.0]) + all_results = _kernel_value(input) + assert jnp.allclose(expected, all_results) + + +def test_bad_bicubic_interpolator(): + """Test that we catch failure cases for creating a bicubic interpolator.""" + good_x = [1.0, 1.1, 1.2] + good_y = [1.0, 1.1, 1.2] + good_z = [[1.0, 1.1, 1.2], [1.0, 1.1, 1.2], [1.0, 1.1, 1.2]] + _ = BicubicInterpolator(good_x, good_y, good_z) + + # No too few x or y + with pytest.raises(ValueError): + _ = BicubicInterpolator([1.0], good_y, good_z) + with pytest.raises(ValueError): + _ = BicubicInterpolator(good_x, [1.0], good_z) + + # The x and y values must be in sorted order. + z = np.full((3, 4), 1.0) + _ = BicubicInterpolator([1.0, 2.0, 3.0], [0.0, 0.5, 1.0, 1.5], z) + with pytest.raises(ValueError): + _ = BicubicInterpolator([2.0, 1.0, 3.0], [0.0, 0.5, 1.0, 1.5], z) + with pytest.raises(ValueError): + _ = BicubicInterpolator([1.0, 2.0, 3.0], [0.0, 2.5, 1.0, 1.5], z) + + # Sizes must match z. + with pytest.raises(ValueError): + _ = BicubicInterpolator([1.0, 2.0, 3.0, 4.0], [0.0, 2.5, 1.0, 1.5], z) + with pytest.raises(ValueError): + _ = BicubicInterpolator([1.0, 2.0, 3.0], [0.0, 2.5, 1.0], z) + + +def test_load_bicubic_interp_from_file(test_data_dir): + """Test loading a bicubic interpolator object from a file.""" + filename = os.path.join(test_data_dir, "truncated-salt2-h17/salt2_template_0.dat") + test_obj = BicubicInterpolator.from_grid_file(filename) + + assert len(test_obj.x_vals) == 26 + assert len(test_obj.y_vals) == 401 + assert test_obj.z_vals.shape == (26, 401)