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Merge pull request #52 from lincc-frameworks/issue/6/bandpass
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Passband integration
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@OliviaLynn
OliviaLynn authored Aug 8, 2024
2 parents 8145ab9 + dc69168 commit 6b3eee6
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278 changes: 278 additions & 0 deletions docs/notebooks/bandpass-demo.ipynb
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Passband Demo"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"A demonstartion of using the `Passbands` class to calculate normalized in-band flux densities.\n",
"\n",
"This code and notebook reference equations in *\"On the Choice of LSST Flux Units\"* by Željko Ivezić and the LSST Project Science Team, which may be found [here](https://docushare.lsst.org/docushare/dsweb/Get/Document-27758)."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"from tdastro.astro_utils.passbands import Passbands\n",
"from tdastro.sources.spline_model import SplineModel"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Set up LSST passbands\n",
"\n",
"These values are unnormalized; we'll need to apply phi from eq 8 of the LSST Flux paper."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"passbands = Passbands()\n",
"passbands.load_all_transmission_tables()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"def plot_single_transmission_table(band_name: str) -> None:\n",
" \"\"\"Plot a single transmission table.\"\"\"\n",
" plt.title(f\"{band_name}-band Transmission Table\")\n",
" plt.xlabel(\"Wavelength (Angstrom)\")\n",
" plt.ylabel(\"Transmission\")\n",
" plt.plot(passbands.transmission_tables[band_name][:, 0], passbands.transmission_tables[band_name][:, 1])\n",
" plt.show()\n",
"\n",
"\n",
"plot_single_transmission_table(\"u\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"def plot_transmission_tables() -> None:\n",
" \"\"\"Plot all transmission tables.\"\"\"\n",
" plt.title(\"Transmission Tables\")\n",
" plt.xlabel(\"Wavelength (Angstrom)\")\n",
" plt.ylabel(\"Transmission\")\n",
" plt.legend(passbands.bands)\n",
" for band_id in passbands.bands:\n",
" plt.plot(passbands.transmission_tables[band_id][:, 0], passbands.transmission_tables[band_id][:, 1])\n",
" plt.show()\n",
"\n",
"\n",
"plot_transmission_tables()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Get normalized passband"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"passbands.calculate_normalized_system_response_tables()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"def plot_single_normalized_system_response_table(band_name: str) -> None:\n",
" \"\"\"Plot a single normalized system response table.\"\"\"\n",
" plt.title(f\"{band_name}-band Normalized System Response Table\")\n",
" plt.xlabel(\"Wavelength (Angstrom)\")\n",
" plt.ylabel(\"Normalized System Response (Angstrom⁻¹)\")\n",
" plt.plot(\n",
" passbands.normalized_system_response_tables[band_name][:, 0],\n",
" passbands.normalized_system_response_tables[band_name][:, 1],\n",
" )\n",
" plt.show()\n",
"\n",
"\n",
"plot_single_normalized_system_response_table(\"u\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"def plot_normalized_system_response_tables() -> None:\n",
" \"\"\"Plot all normalized system response tables.\"\"\"\n",
" plt.title(\"Normalized System Response Tables\")\n",
" plt.xlabel(\"Wavelength (Angstrom)\")\n",
" plt.ylabel(\"Normalized System Response (Angstrom⁻¹)\")\n",
" plt.legend(passbands.bands)\n",
" for band_id in passbands.bands:\n",
" plt.plot(\n",
" passbands.normalized_system_response_tables[band_id][:, 0],\n",
" passbands.normalized_system_response_tables[band_id][:, 1],\n",
" )\n",
" plt.show()\n",
"\n",
"\n",
"plot_normalized_system_response_tables()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Set up a source\n",
"\n",
"Note that our transmission tables are to the closest integer; eg, in 'u', all integers in [3200, 4085].\n",
"\n",
"Models that follow a different grid might need to be put through a SplineModel to match this grid."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"input_times = np.array([1001.0, 1002.0, 1003.0])\n",
"input_wavelengths = np.linspace(2000.0, 6000.0, 3)\n",
"input_fluxes = np.array([[1.0, 5.0, 1.0], [5.0, 10.0, 5.0], [1.0, 5.0, 1.0]])\n",
"\n",
"spline_model = SplineModel(input_times, input_wavelengths, input_fluxes, time_degree=2, wave_degree=2)\n",
"\n",
"times = np.linspace(1000.0, 1006.0, 48)\n",
"wavelengths = np.linspace(2000.0, 8000.0, 16)\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.figure(figsize=(12, 3))\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": [
"## Calculate in-band flux densities"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"per_passband_normalized_fluxes = passbands.get_all_in_band_fluxes(spline_model, times)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Print in-band normalized fluxes (abridged--we only print every 4th value, for space)\n",
"np.set_printoptions(precision=2)\n",
"print(per_passband_normalized_fluxes[::4])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"def plot_passband_normalized_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",
" offset = 0.015 # Optionally add a small offset for the overlapping bandss\n",
" for i, band in enumerate(passbands.bands):\n",
" ax.plot(times + offset * i, per_passband_normalized_fluxes[:, i] + offset * i, marker=\"o\", label=band)\n",
"\n",
" ax.legend()\n",
" plt.show()\n",
"\n",
"\n",
"plot_passband_normalized_lightcurve()"
]
}
],
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},
"nbformat": 4,
"nbformat_minor": 2
}
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