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@jradavenport
Created May 12, 2022 22:56
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TESS CVZ
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "efd2368f",
"metadata": {},
"outputs": [],
"source": [
"%matplotlib inline\n",
"import numpy as np\n",
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"import matplotlib.cm as cm\n",
"from glob import glob \n"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "726537f5",
"metadata": {},
"outputs": [],
"source": [
"import matplotlib\n",
"matplotlib.rcParams.update({'font.size':18})\n",
"matplotlib.rcParams.update({'font.family':'serif'})"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "a13a5de2",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'/Users/james/Dropbox/research_projects/TESS-Gaia/gaiatess12_xmatch_1arsec-result.csv'"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# my local copy of the TESS-Gaia cross match from Trevor\n",
"gdir = '/Users/james/Dropbox/research_projects/TESS-Gaia/'\n",
"\n",
"# make a list of all the result.csv files:\n",
"files = glob(gdir+'*result*')\n",
"\n",
"files[0]"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "bd941629",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"18497\n",
"37156\n",
"55771\n",
"74652\n",
"93330\n",
"111941\n",
"126743\n",
"145563\n",
"164172\n",
"182930\n",
"201700\n",
"220269\n",
"238879\n",
"257737\n",
"272553\n",
"291070\n",
"309694\n",
"328198\n",
"347142\n",
"365915\n",
"384323\n",
"403383\n",
"421936\n",
"440663\n",
"459435\n",
"474317\n",
"493161\n"
]
}
],
"source": [
"# read CSV file w/ Pandas into a dataframe\n",
"df = pd.read_csv(files[0])\n",
"print(len(df))\n",
"# brute force read them all in...\n",
"for k in range(1, len(files)):\n",
" df = pd.concat([df, pd.read_csv(files[k])], ignore_index=True, sort=False)\n",
" print(len(df))"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "7c68859f",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"227605"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# 493k star observations (rows)\n",
"\n",
"# the column \"ticid\" is the TESS Input Catalog ID, the unique ID we care about\n",
"df['ticid'].unique().size\n",
"# 227k unique stars"
]
},
{
"cell_type": "code",
"execution_count": 39,
"id": "b0b28509",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# heat map of entires across the sky\n",
"_ = plt.hist2d(df['ra'], df['dec'], bins=100, cmap=plt.cm.Spectral_r)"
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "35e389dc",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0, 0.5, '# of stars')"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"_ = plt.hist(df['ticid'].value_counts(), bins=30)\n",
"plt.yscale('log')\n",
"plt.xlabel('# of Data Sectors')\n",
"plt.ylabel('# of stars')\n",
"\n",
"# there must be some double-matching going on somewhere upstream, since there \n",
"# should only be a MAX of 13 Sectors of Data for any star"
]
},
{
"cell_type": "code",
"execution_count": 71,
"id": "49f8e748",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"11832"
]
},
"execution_count": 71,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# lets find stars w/ at least 10 Sectors of data, and drop the hand full of bad sources\n",
"sum((df['ticid'].value_counts() >= 10) & (df['ticid'].value_counts() <= 13))\n",
"# 11k stars to run, reasonable!"
]
},
{
"cell_type": "code",
"execution_count": 70,
"id": "f54fa377",
"metadata": {},
"outputs": [],
"source": [
"df_clean = df.drop_duplicates(subset='ticid').sort_values('ticid')\n",
"df_clean['Nsector'] = df.groupby('ticid').size().values\n"
]
},
{
"cell_type": "code",
"execution_count": 72,
"id": "45233ad1",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"11832"
]
},
"execution_count": 72,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"cvz = (df_clean['Nsector'] >=10) & (df_clean['Nsector'] <=13)\n",
"sum(cvz)"
]
},
{
"cell_type": "code",
"execution_count": 73,
"id": "32bcb40d",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.collections.PathCollection at 0x7fb821f2b4f0>"
]
},
"execution_count": 73,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# lets make sure they're located in the correct places on the sky\n",
"plt.scatter(df_clean['ra'][cvz], df_clean['dec'][cvz])\n",
"\n",
"# yep! "
]
},
{
"cell_type": "code",
"execution_count": 81,
"id": "b9927537",
"metadata": {
"scrolled": false
},
"outputs": [],
"source": [
"df_clean.loc[cvz].to_csv('TESS_CVZ.csv', index=False, index_label=False)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f05c9490",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"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": "3.8.5"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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