S82 RRLyr notebook

docs/tutorials/rrlyr-period.ipynb

@@ -0,0 +1,136 @@
+{
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+   "cell_type": "markdown",
+   "id": "7bc777c97b317198",
+   "metadata": {
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+   },
+   "source": [
+    "# Explore SDSS Stripe 82 RR Lyrae catalog with period-folding\n",
+    "\n",
+    "This short example notebook demonstrates how to use TAPE to explore the SDSS Stripe 82 RR Lyrae catalog. We will use a Lomb–Scargle periodogram to extract periods from r-band light curves and select the RR Lyrae star with the most confident period determination. Then, we will plot the period-folded light curve for this RR Lyrae star."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "initial_id",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2023-09-20T13:16:49.339804Z",
+     "start_time": "2023-09-20T13:16:48.655140Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "from light_curve import Periodogram\n",
+    "from tape import Ensemble"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "fecf2313f49ad1ac",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2023-09-20T13:16:53.703300Z",
+     "start_time": "2023-09-20T13:16:49.340873Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "# Load SDSS Stripe 82 RR Lyrae catalog\n",
+    "ens = Ensemble(client=False).from_dataset('s82_rrlyrae')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5c2dd5a5fd58ce00",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2023-09-20T13:17:00.548389Z",
+     "start_time": "2023-09-20T13:16:53.706738Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "%%time\n",
+    "\n",
+    "# Filter out invalid detections, \"flux\" denotes magnitude column\n",
+    "ens = ens.query(\"10 < flux < 25\", table=\"source\")\n",
+    "\n",
+    "# Find periods using Lomb-Scargle periodogram\n",
+    "periodogram = Periodogram(peaks=1, nyquist=0.1, max_freq_factor=10, fast=False)\n",
+    "\n",
+    "# Use r band only\n",
+    "df = ens.batch(periodogram, band_to_calc='r')\n",
+    "display(df)\n",
+    "\n",
+    "# Find RR Lyr with the most confient period\n",
+    "id = df.index[df['period_s_to_n_0'].argmax()]\n",
+    "period = df['period_0'].loc[id]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f79ad1eb83d0d125",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2023-09-20T13:17:00.655691Z",
+     "start_time": "2023-09-20T13:17:00.548017Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "# Plot folded light curve\n",
+    "ts = ens.to_timeseries(id)\n",
+    "COLORS = {'u': 'blue', 'g': 'green', 'r': 'orange', 'i': 'red', 'z': 'purple'}\n",
+    "color = [COLORS[band] for band in ts.band]\n",
+    "plt.title(f'{id} P={period:.3f} d')\n",
+    "plt.gca().invert_yaxis()\n",
+    "plt.scatter(ts.time % period / period, ts.flux, c=color, s=7)\n",
+    "plt.xlim([0, 1])\n",
+    "plt.xlabel('Phase')\n",
+    "plt.ylabel('Magnitude')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "cf157e25e291651a",
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+     "start_time": "2023-09-20T13:17:00.647036Z"
+    }
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
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+  "kernelspec": {
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+   "language": "python",
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