Adding comparison notebook and updating pyproject.toml.

docs/notebooks/mbls-comparison.ipynb

@@ -0,0 +1,111 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Create some artificial data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "t = []\n",
+    "y = []\n",
+    "bands = []\n",
+    "dy = []\n",
+    "N = 60\n",
+    "for i, band in enumerate([\"u\", \"g\", \"r\", \"i\", \"z\"]):\n",
+    "    rng = np.random.default_rng(i)\n",
+    "    t_band = 300 * rng.random(N)\n",
+    "    y_band = 3 + 2 * np.sin(2 * np.pi * t_band)\n",
+    "    dy_band = 0.01 * (0.5 + rng.random(N))  # uncertainties\n",
+    "    y_band += dy_band * rng.standard_normal(N)\n",
+    "    t += list(t_band)\n",
+    "    y += list(y_band)\n",
+    "    dy += list(dy_band)\n",
+    "    bands += [band] * N"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Example using astropy.timeseries"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from astropy.timeseries import LombScargleMultiband"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model = LombScargleMultiband(t, y, bands, dy, nterms_base=1, nterms_band=1)\n",
+    "frequency, power = model.autopower(method=\"flexible\")\n",
+    "freq_maxpower = frequency[np.argmax(power)]\n",
+    "t_phase = np.linspace(0, 1 / freq_maxpower, 100)\n",
+    "y_fit = model.model(t_phase, freq_maxpower)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "plt.plot(frequency, power)\n",
+    "print(f\"Frequency with peak power: {frequency[np.argmax(power)]}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "mapals",
+   "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": "3.12.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

pyproject.toml

@@ -16,6 +16,7 @@ dynamic = ["version"]
 requires-python = ">=3.9"
 dependencies = [
     "cuda-python",
+    "numpy",
 ]
 
 [project.urls]
@@ -28,8 +29,10 @@ dev = [
     "black", # Used for static linting of files
     "jupyter", # Clears output from Jupyter notebooks
     "pre-commit", # Used to run checks before finalizing a git commit
-    "pytest",
+    "pytest", # Used to run tests
     "pytest-cov", # Used to report total code coverage
+    "matplotlib", # Used to plot data
+    "astropy", # Used as the LS baseline for comparison
 ]
 
 [build-system]