{
“cells”: [
{

“cell_type”: “markdown”, “id”: “405a87b6”, “metadata”: {}, “source”: [

“# Using MonoTools.lightcurven”, “n”, “The fit and search modules take in, as default, lightcurve.lc objects. Here we’ll give a very quick overview of how to use them.”

]

}, {

“cell_type”: “markdown”, “id”: “ea3b8f87”, “metadata”: {}, “source”: [

“The simplest way to use a lightcurve object, is simply to load externally your data, and make a lightcurve object from them, by passing time, flux and flux_err arrays.n”, “n”, “First let’s import the module and other useful stuff:”

]

}, {

“cell_type”: “code”, “execution_count”: 13, “id”: “1529fd6d”, “metadata”: {}, “outputs”: [

{

“name”: “stdout”, “output_type”: “stream”, “text”: [

“The autoreload extension is already loaded. To reload it, use:n”, ” %reload_ext autoreloadn”

]

}

], “source”: [

“%load_ext autoreloadn”, “%autoreload 2n”, “from MonoTools.MonoTools import lightcurve as lcn”, “import numpy as npn”, “import matplotlib.pyplot as pltn”, “%matplotlib inline”

]

}, {

“cell_type”: “markdown”, “id”: “ab74ca30”, “metadata”: {}, “source”: [

“## Loading a TESS, K2 or Kepler lightcurven”, “n”, “The easiest way to use MonoTools.lightcurve is to not bother with the load_lc function defined below, but instead to jump straight to extracting a multilc class from a search of Kepler, K2 and TESS data.n”, “n”, “This is possible simply by passing an id and mission argument to the multilc class.n”, “n”, “It will search the given mission, but if do_search is True, it will also search other missions for corresponding data using the multilc.get_all_lightcurves() function. This function is assisted by including a radec in astropy.coordinates.SkyCoord format as an argument when initialising the multilc class (as otherwise, we have to access the input catalogue and then use the ra & dec to search for extra data).n”, “n”, “Set load=False if you do not want to load from file.”

]

}, {

“cell_type”: “code”, “execution_count”: 10, “id”: “375b7d18”, “metadata”: {}, “outputs”: [

{

“name”: “stdout”, “output_type”: “stream”, “text”: [

“Getting all IDsn”, “Accessing online catalogues to match ID to RA/Dec (may be slow) mission= tessn”, “Empty TableListn”, “Sector 44 not (yet) found on MAST | RESPONCE:404n”, “Sector 45 not (yet) found on MAST | RESPONCE:404n”, “Sector 46 not (yet) found on MAST | RESPONCE:404n”

]

}

], “source”: [

“tesslc=lc.multilc(441420236, ‘tess’)”

]

}, {

“cell_type”: “markdown”, “id”: “f9855110”, “metadata”: {}, “source”: [

“If other missions have been searched, the info should end up in multilc.all_ids.n”, “n”, “You can see that the TESS input catalog has been searched and stored at tesslc.all_ids[‘tess’][‘data’], which is useful.”

]

}, {

“cell_type”: “code”, “execution_count”: 72, “id”: “b23cb23f”, “metadata”: {}, “outputs”: [

{
“data”: {
“text/plain”: [

“{‘tess’: {‘id’: 441420236,n”, ” ‘data’: ID ra dec pmRA pmDEC Tmag objType typeSrc \n”, ” 0 441420236 311.289718 -31.3409 281.424 -359.895 6.755 STAR tmgaia2 n”, ” n”, ” version HIP … splists e_RA e_Dec RA_orig \n”, ” 0 20190415 102409 … cooldwarfs_v8 1.20885 0.836737 311.291137 n”, ” n”, ” Dec_orig e_RA_orig e_Dec_orig raddflag wdflag dstArcSec n”, ” 0 -31.34245 0.038006 0.02705 1 0 0.0 n”, ” n”, ” [1 rows x 125 columns],n”, ” ‘search’: [1, 27]},n”, ” ‘k2’: {},n”, ” ‘kepler’: {},n”, ” ‘corot’: {}}”

]

}, “execution_count”: 72, “metadata”: {}, “output_type”: “execute_result”

}

], “source”: [

“#In this case there are no extra lightcurves from e.g. Kepler, K2 or CoRoT:n”, “tesslc.all_ids”

]

}, {

“cell_type”: “markdown”, “id”: “bced90db”, “metadata”: {}, “source”: [

“## Plottingn”, “n”, “Now you have a lightcurve, then you can plot using lc.plot(). For high-cadence data (<30 minutes), it will perform binning and plot these are stronger points. n”, “n”, “Useful arguments include:n”, “* plot_rows How many rows would you like to split the data over?n”, “* timeseries: If you want to plot more than just flux, then include those timeseries here (e.g. bg_flux, raw_flux, flux_flat etc). These other timeseries can be offset using the y_offset argumentn”, “* ylim and xlim: If you don’t want to plot the whole x or y span, then cut them here.n”

]

}, {

“cell_type”: “code”, “execution_count”: 12, “id”: “e19a1b68”, “metadata”: {}, “outputs”: [

{
“data”: {

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”, “text/plain”: [

“<Figure size 841.68x595.44 with 2 Axes>”

]

}, “metadata”: {

“needs_background”: “light”

}, “output_type”: “display_data”

}

], “source”: [

“tesslc.plot(plot_rows=2)”

]

}, {

“cell_type”: “markdown”, “id”: “416eb950”, “metadata”: {}, “source”: [

“## Initialising a simple lightcurve from pre-loaded datan”, “n”, “The above lightcurve methods create a MonoTools.lightcurve.multilc method. But this inherits the base MonoTools.lightcurve.lc class and is built from combinations of individual lc objects.n”, “n”, “The base class MonoTools.lightcurve.lc can also be simply loaded using time/flux/flux_err arrays.n”, “n”, “Here’s some important info for calling lc.load_lc().n”, “n”, “##### The flx_system argumentn”, “You must specify the "flux system" underlying the lightcurve fluxn”, “- ppm: normalised lightcurve with median at 0.0 with units in parts per millionn”, “- ppt: normalised lightcurve with median at 0.0 with units in parts per thousand (this is the default)n”, “- norm0: normalised lightcurve with median at 0.0 with units as a ratio (0->1)n”, “- norm1: normalised lightcurve with median at 1.0 with units as a ratio (0->1)n”, “- elec: un-normalised lightcurve with units of pure electrons where the median is proportional to stellar magnituden”, “n”, “The flux system can be changed using lc.change_flux_system(new_flx_system) (and is automatically made uniform when stacking lc objects).n”, “n”, “##### The jd_base argumentn”, “As with flx_system, we need to know the base system used for the lightcurve time. The default is the TESS system using jd_base=2457000n”, “n”, “##### The mission, sect and src argumentsn”, “The arguments identify the source of the lightcurve, and are necessary if you plan to stack multiple lightcurves together.n”, “- mission: the photometric mission providing the lightcurve in lowercase (e.g. k2, tess, kepler, etc)n”, “- sect: the sector, campaign or quarter within that mission the data comes fromn”, “- src: a identifier for the source of the lightcurve detrending. e.g. pdc (most kepler quarters), vand, ev or pdc (for k2 campaigns), pdc, qlp or el (for tess sectors) n”, “n”, “n”, “Here is a simple example of loading data:”

]

}, {

“cell_type”: “code”, “execution_count”: 94, “id”: “9b743bc5”, “metadata”: {}, “outputs”: [

{
“data”: {

“image/png”: 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”, “text/plain”: [

“<Figure size 841.68x595.44 with 1 Axes>”

]

}, “metadata”: {

“needs_background”: “light”

}, “output_type”: “display_data”

}

], “source”: [

“fakeflux=np.random.normal(7*np.sin(np.linspace(-4,5,500)),5,500)n”, “fakeflux[np.random.choice(500,5)]*=5n”, “n”, “simplelc1 = lc.lc()n”, “simplelc1.load_lc(time=np.arange(2000,2050,0.1), n”, ” fluxes=fakeflux, n”, ” flux_errs=np.random.normal(0.01,0.0005,500),n”, ” flx_system=’ppt’,jd_base=2457000,n”, ” mission=’tess’,sect=’99’,src=’test’)n”, “simplelc1.plot()”

]

}, {

“cell_type”: “markdown”, “id”: “d00f1538”, “metadata”: {}, “source”: [

“If we have multiple types of flux (for example, ‘raw’ and ‘detrended’ fluxes, background flux, etc) then we can make our input flux and flux_err arguments dictionaries:”

]

}, {

“cell_type”: “code”, “execution_count”: 79, “id”: “421f76e6”, “metadata”: {}, “outputs”: [

{
“data”: {

“image/png”: 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”, “text/plain”: [

“<Figure size 841.68x595.44 with 1 Axes>”

]

}, “metadata”: {

“needs_background”: “light”

}, “output_type”: “display_data”

}

], “source”: [

“fakeflux2=np.random.normal(7*np.sin(np.linspace(5,20,500)),5,500)n”, “fakeflux2[np.random.choice(500,5)]*=5n”, “n”, “simplelc2 = lc.lc()n”, “simplelc2.load_lc(time=np.arange(2050,2100,0.1),n”, ” fluxes={‘flux’:fakeflux2,’bg_flux’:np.random.normal(40,2.5,500)},n”, ” flux_errs={‘flux_err’:np.random.normal(0.01,0.0005,500),’bg_flux_err’:np.random.normal(2.5,0.01,500)},n”, ” flx_system=’ppt’,jd_base=2457000,n”, ” mission=’tess’,sect=’100’,src=’test’)n”, “n”, “#Plotting both of our flux arrays:n”, “simplelc2.plot(timeseries=[‘flux’,’bg_flux’],ylim=(-20,60))”

]

}, {

“cell_type”: “markdown”, “id”: “ae97d7bd”, “metadata”: {}, “source”: [

“One thing to note is the cadence array that is created for these times. This is effectively the unique identifier for the data when stacking lightcurves with the format:n”, “n”, “[telescope ID k1/k2/co/te/ch]_[cadence in secs]_[pipeline source]_[Sector/Q/camp]

]

}, {

“cell_type”: “code”, “execution_count”: 8, “id”: “97bc729f”, “metadata”: {}, “outputs”: [

{
“data”: {
“text/plain”: [

“‘ts_8600_test_99’”

]

}, “execution_count”: 8, “metadata”: {}, “output_type”: “execute_result”

}

], “source”: [

“print(simplelc1.cadence[0])”

]

}, {

“cell_type”: “markdown”, “id”: “b4904ca7”, “metadata”: {}, “source”: [

“### Masking, binning & flattening”

]

}, {

“cell_type”: “markdown”, “id”: “20668765”, “metadata”: {}, “source”: [

“The lightcurve.lc class is built to allow quick masking, binning & flattening of the data.n”, “n”, “n”, “##### Using lc.make_mask()n”, “This function calls the make_fluxmask function to mask anomalous points.n”, “n”, “Some useful arguments when making a mask:n”, “* flux_arr_name: Which timeseries of maskn”, “* cut_all_anom_lim: The limit in sigma above which we cut all anomalies (default is 5)n”, “* end_of_orbit: Whether to mask end-of-orbit flux jumps (often seen in TESS). Default is Truen”, “* use_flat: Whether to use the flattened flux array to perform masking. Default is Falsen”, “* mask_islands: Whether to mask small "islands" of flux (defined as <0.5d long segments >0.5d from other data). Default is Falsen”, “* input_mask & in_transit: Two already-determined masks which allow inclusion of custom masks and make sure in-transit points are not cut.n”, “* extreme_anom_limit: An extreme flux limit above/below which we cut points (default:0.25 meaning flux must be >25% median flux & <400%)n”, “n”, “In the case of a multilc (i.e. a lightcurve stacked from multiple sectors/sources), make_cadmask is also called, which masks cadences in the lc.mask_cadences list. This is useful when there are multiple lightcurve sources for the same data (i.e. qlp & pdc), but we only want to consider one as part of the defauly lightcurve as it is higher-quality.n”, “n”, “(Note that this is performed by default when accessing a mission lightcurve from lc.multilc)”

]

}, {

“cell_type”: “code”, “execution_count”: 37, “id”: “6529739e”, “metadata”: {}, “outputs”: [

{
“data”: {
“text/plain”: [

“[<matplotlib.lines.Line2D at 0x7fd97dd45e20>]”

]

}, “execution_count”: 37, “metadata”: {}, “output_type”: “execute_result”

}, {

“data”: {

“image/png”: 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1XrhOIJdKXsNkvm2VbVRnE9VOzAnhPHeUUhPfZmh0HpPOLpPwvU6hRN62M06YJWXmrnGJOHDB1TJOa0Hn7V7J0sBdksG1AteOLuyl1r9r3k+bpR6X52iocrAeVVKt1vCN9Vswsv8wFi6e3TAfcODFN/Ddv/8RquO1plFDGtGKCu+1xauDalh+zYfqicv0+zg6Oo6dWwad55yiVuvaJnOTokfqqInvrAsOw4y7ok/qFkbkbS+0zZICmgU270bqahmnsaDzdK9kcf24RmC04oVx7ehskTWurgmF/nmY9T1QXgDP8+qRWLUqY+sjFZxySh/WrF2Okf2HsWPzPjzzf/dPzAdYRg2uKJHd/the6wK/KOvdnAQ1I4YWLp5tdUfp1zYXdX32v65IvYDNdt+Hhw5hx6Z92twJYdnK8+sdStoFh2a7mT5jWqq0FL1GYUTe9kIDCI01NwU2L+vYNprI27LNy72SxfXjGoHRihfGtaOzRdbYwiZd/eBhW/r1D8zFbeuuwjfWb6mLLuDfixPvnMRZs96H6nitYcJ36pS+UP9+FLb0w0BjeK85D6Vb76alf9FHzq13PuPj1foWgWHuDNuirhPvnHTKzBm1uEx/HuY1mCdCMc25syTtzdZhJ0lL0asURuTDXmiXWHPb5FEaTMtizdrlufhdW0UW10+SCIxWYBNm2wIeM7ImSwcUdb9WXFvGyP7D2PpIpX5MF169beo7MakyqzrFoY9OFaVS47yRWc6ovDKlklcPLSZMbBEY5s5Ys3a5NUWz/jxsFvarI282uJb0xWXmKMscGYFhfV5pom7MDts1LUUvUxiRD3uhk8SaJ11NaNuMpD70G6ti95PDXR3fG2cRJ82TDtgjMNqBrYNVVvL1N1/WEFmTtgOKu18qqkRN2P/BH324/t2wVaVJ3VumMWPbui+unGGWft0dZaQEMSee41I020bVP3js+YaV4wAiR1m3rbuqYVRhe179A80JCV2jbsyOsKgCDxRI5AF7qJzrC5106Gd7QafPmFYfWtZqjA8umoUX9r3W1THoYa6KNHnSo86XlKRuroZJxLHxBoFQgp/GPWISVb84/70ZlZPGXWYT8OGhQ7j7K5sBoB7qG3Xvoix927aA5ugl7hmb5wfQEJJM3oSPfeeWQYzsP4yXh/8VzP6z++59u/DpW5fia39/c2wbsCUkdJ0P68XQ4TQUSuQV5svmMhxO6roI80kToT4EfO+p7+nZhpRXqGaaOYmkFq6Z60d3O+iCXyr5lm+eZTWJ89/rpHWX6SK7bWOlYS7gB48/D8+jyJQNUQJnCngaMTT/BkDDCEe5lpQx9utfj9f/lmvA88/+3HmLwiwux7wMkm6nkCIPTAi6q1gkbczmsPnokePWFZG92pDyCNVMG72TpIOxrWiuL3AarzYIfq1WxbaNFas7zjyPzQ0Sdn1bm7FFcpihly5tLqrjMVdmA/BTDASGhm0NSNikaBQu8x9xfxOWV2h0dELg4SetTLwBS7caUt0Sf19YkQfCre0oP7Prw9Ana1WCpqgVkb1GHi9P2tGArYMJi1oy48DPmvU+rLi2XE/L+/Zb7+K5p1+p56vRxU8vi17WqM5AJ6oTi3Pd6N9Lc35V5oYU2vCjyTyP6jmazDUgaYIBbPc+rFxhwmarpznBSkAQVsqJdprS3bRR+z60k25KqlYYkbc1AJs1lXdKgKHKRIKmsBWRvUqSTs/l/idxR5jD/TChMuPA9WuoifRSycOHP7oYzz39SlOCOkU9UqOeKtfeGejEdWJJXDdpzj9QnliZTSBcetkiXHfDkvrf2iZOkwYDRK0/Mc+RVPz7B+Y2TLCWSh4u+si51iydcaLZTaIKdFdStUKIfNTKxrhFT1lufLvzvncrrvc/yb3WOxhTJHWhCosDNyNIFp03B9fdsCQ2Wqiehtjhebp2Ymk6O5e2FedbV+jXXnJ5fz0YwNzz2IbtnQmrj4v4m64wfdS1Y/M+7HnqQMNOU1HlCBuJ5S2qadwuebg786LlIk9EVwL4GwAlAN9i5vV5XyPqAZvWaJ6LnpLkfW+lf67Tvr8k9z8N5gvzwUWzMFg5WM9HZLvvtpcsrizqc3NlZdT3W5HCIknbcqlT2A5Tys0Y5ZayjYaHKgetbkkX8be5wmwjYtuoJWqOY6C8AKWSB2a/89Lf7aypO9KMEMKeeSfe1ZaKPBGVAPwtgP8A4HUAzxHRJmYezvM6rr1m/0Dzfq4uN93mk9SXQ8fF4rskRgJg/TmuIcRtT5h3bhobLj70LNj823Hpcl2FNU0mSPPvXNxzSTo7cxSSdU8B89ouoqp/V93HX777q8i2FnbPXVxhtkAGtQ+EOl/UHAcA36mv/4/sbhwzh06SEYJ+31UkUdxmNa2g1Zb8xQBGmPnnAEBEDwFYBSBXkU/yQuv7uQKInYQyG8mq6y/BIw8+U9/GzWU5dEMMd5AICpjwMxMRGAyuAX19HkBwaggquiJse8K8c9O4Wqp63bI2ZlNM9ZWKej6iqL/Jo455/J0reQ31ozpal+gfhfp97X+6P3YrTFtnZnOFqYRtd39lc32UYgYy7Ni0r+ld0NuAGVChUkfoOezj3DhRaUgANOTQKZXSjRBsqSja6advtcjPAXBI+/11AJfoXyCi1QBWA8C8efNSX8jFUkozCdUg0GPj+P7/fLq+rRlR43LoqHA6MxEUMJHnBWjMd1L/2WHiz1xkojfCKB9pXONM6uPU7//dX9mc2vrRUcmwxser6Osr4bO3r4j1UycR4LR+3FZPqmWZy1DE3Qfb6CjqnsW1tbiyDFUONiyA+sHjz+PpH+0H4L8Pd913U9MIg9l/F8x2VB8ZaOkM5i+c6bSpiSnSUZFHy1aePxH5Q8AVV1+QyoBS7cXcrKZdfvqOT7wy8wYAGwCgXC5zzNczYT5wfRIqLH2p3qDAVF/RCvjhXksu78dQ5SBeHXkzMkxO32NWNRx9CGvDtBxs9YnKex/mRnFpnK7WpM0SirJ+kqCiYwC/87v7K1sA+KOdMD91EgFOazG3Y1It61yGy31Q13BduJVmjwVbeztr1vtQ0/ZOHhut1le5mm4bEKxbdprpDNasXV6frDXbRdjxOKMPaJzD0yeDXe6vejf0rSTDUlG0klaL/BsA9JqcHRzrCGGTUHExwKpBKRcNEeB5fm6SsF2FzLS2el4TAmHh4tn1Yzs27/Oz7jEB4LpAnnPuLLw68mZsREiSz12tbBdrMiy8Lsz6yYrqYKvVcD91EgFOazHnYWm3miT3weW7aescFp2jJzkDGle5mq4/2zX1dAZmGgslxmb7NCN24ow+W3pj13sWlUup3e2l1SL/HIBziWgBfHG/HsAftviakdgmocJ6d5VHY9ac0yZcNB5w4cUfxKdvXdo4QQaGVyIQKDStrWl9rL/3Rnz+y1fXG9Iv3/0VHnnwGdSqvm/xwItv4MCLb4CIrBNdtvJH1de0sgHUM/eFTQIrn7bNxeMSXue6baKNZSvPx47N+zA2Wm04HuUqcO2c9M/TvHRZLe1Wk0SUbXMqNv98mjqHRTmpJGd63hrVhsy9HJTxZUbTqPPasme6+ONdjD71vaT317x2J9fPtFTkmXmciG4D8EP4IZT3M/OLrbxmVnT3jMqj0dfXuOBGz1infO2Av7nBlasuBABrWlvT+lBDVHWudWu+HQxjCUQTFn2aDQ3CRLmqDZNVZwOgnlubiOB5/qhEj1xw3XQ8Tyu3f2Au7rrvpobRjukq2LaxUo+WUhutR4mRPgmmb9WXhk6HrsaRRJTVd7NMRtvuRVh7aLpexCgirExNcwoJ/fG2yfk098xGO1x6rrTcJ8/M2wBsa/V18kI1nu/etwvPP/tzMDOqNfuCG9PXzsz179iyYNo6EDVE1SdnyGN4nodarQau2SN44nKaRImyOcu/+8lhLbyNg5FJY+6TsPQQtmFoWis3KpzRNmzetrGCv7nTz764d8/PANizKOoMVRq36rvnq1tTbQrdbSss8yLJnIbuc46auDXbg/mc44yCsDLp5w2zwPNK8ZyUbnLpdXzitRvpH5iLT9+6tMk/Z3tQtp3po6wXswMJc3Mo8Zw+YxpG9h9uuGZc3L2ez8V8KdasXY4fPPY8fnbgMGpBjpAll/dj8LlGK9+MAGhlegizTrYEYbaOY/eTjZG4P3jsebw68mZkuQbKjflSuMapomNaHWHTKZJMuOshwK771Uatjg5j+oxpII/qi9/C5gzC3CpxrpRWPbtucemJyAfY/LRZVjNGNboll/djsHIQXENsx6DH9u/YtK+eKtdmWYft66lHDek5X5avurBBSM2UvPpneaSHiBp96Od0TRC25PL+ugUPAO8/8zfwykv/GluuS37vt7DnxwcARuiGFFHx02GuqiLg2u7155Vkv9qkbUct9lO7vIUtfjNJskagE8+una4+EXlEWxcuDyBJj62E1rZiM87qUOLX11dqEvGGSWBjtx/dvRK2klLlEImK1NGPpcnFEmX9K2sNgavIJcZe+dKVT37+wpnY+8yIU8RDVDrhuPhp0yfc6eF43ri057CRZ9y9SCKw5mI/ZvviN9vf3X7rP2J8rIq+KSXcdd9NABqjdLI+O9tckCvtdvWJyKO9Q2/d9x62YlPH9KMzI3SOwBbVYopV1AuWpFNL+pJE3WPV8akQVYVLjP2Ka8sNL5lrxENUuoC4+GmbT7iouYlcJlSnz5gWKvCuI+SwQIGoBVhhZdu5ZbAekTU2WsX3H9jtd/4JXET6fINZN9tcUBKhb7erT0QerRu+5ZF+V70UZnZEl309zUUuI/sPhy4MSUpSf2NUvVWj14mKsY8SvahyhZUhzhWj4qfDNoxupWXWyQlel1WzQHgKC9cRclSgQNgCrCT35a1jv4g0MEwxV3VShhURoa9vYuRnzgXtfnI4kci3210kIo9mq0S5N7K8THmm31V/F5cd0Xx59MZkxu5niV9X9Utah7B6m1FHnkehZcwierYyxIXn6WUN2zC6lZZZJyd4Xa4d9R3XskdFz4S1mahzL1t5PnZs2ldPh3HlNRf6E/KWzt0U86lT/XanpyFgZoyNTcwTrbr+koa5oFPeMyUyXbNJu119IvIB6kabvry0DyCqESa1gvUyJvk7vTEdPXLcGrufhizpV8M6J9ehv579M009zDK4hOcB0RtGt9Iya7fVZ0vpEXXtqO+4lj3qe2FtJu5v7tpwU4OIqvTKOrrrFJhYjwKgwehQ+zareaL3nvoefOGOq+tRanueOoC9z4wkNjja1VlPapE3rVHTl7dzy2DTsNK199WtU9sQvxWodKbAhDtG/VOf5SEWaWKp4+6Zbv1Fxf4rq8sl+6cLeQlRqyyzdlp9ts477tpR5XMte9rRbVxKD/OYyoWkorasI0gjnYEKYTY3kukf8Bc3ukRzdZpJK/K2Bp30+3GiZaYxiFp0k3VyTWVsVL5tPbOfKo/NVZHmmmliqV3SJsftZzqxWKwx+2cW8hKiVlpm7bL6bJ23mWIgaflcy+76vbQpKcLqFjWC1M9tc5V2QyimC5NW5G0P3fTl6T5hc/MAMwGZjbg0Boo8JteGKgf9JGcB42Phe45mvaarMLpY/HELuBTmC5WHwOv1iTpX0g1CepVuF60sKSnC6hb27G2dia1jdx2BdDJCatKKvO2h23x5QHNiLyJy2uHFHA7qaQxcJ5GS1EfP7NcXssjH9ZpxjdLl5YgTDTNuPe1+pq2kqOkLbHTqHrsyVEmekkJvj0kEOcmGObpO2M7f6TY0aUU+rEHbxGuo0pg+d+Gi2U6+OHUNWxqDKCvVJs4uoqsy+wHxIZJR4YS2bcrUfYh6QZL6dM24dVvsv1nHdgtPJ6NbOkE77nEWN2GSlBS29ugyEktjAEUJeafb0KQVecC9QZuCGBaSFXYNMw9OmJVqzv4rXC2BJC9omI/etk3Zzi2D9UmrqOvb9sOM8uma97WdGym40u0ujF4jq5vwtnVXNeSOj9q2MK24Rj3zsPJHXcsl904rmdQi74pNEOOyHYb9fVQcvjn7H2cJZPXzmZ2CGVIGwN+dB825cmy+dZcdocwIoCzugXb4ObvdhdFrZLVq9fQbYdkvbTsyJRHXqGduKz+Ahm0pzY3IXTaebyUi8o6Ygph0WKu+m2ZIN1D294hl9hc1DZTdt/ELI2o1rppDAAAQsHDx7NiXxXRp2VarhkUApZnMbIWfM2oJv4h7PuQxMlLPI2xD7zx2ZAp75mb5p8+YVl9b45U8nDcwDy8O/Qu2bdyLnVsGGxZWuaQxaQUi8m0kTsjNxqOGoQAAQsP/WWLV41bjNuTSr9Zw4p2TsSMRm+vFVv+4CKA87qXLPbB9PlkmWDtJniMjW4dhtos8d2RSbUjvOPS1NdXxGl4YfG3C1RkYM51294nIt5GoBVKmS6dp1/hxf0vA8cCds2zl+alj1aMEMmwOIW4k4vLyhkUApXG7JLEIXQS805Njk4m8RkZhbc5lN6g0rkFbGzLn0XRXJ3kUuU9suyi0yHcqNjVq2B+1QCpsGApMbDPI7Ls5XPzZZhoAFau/5PL+2GyU+rkBf8/PuFh2Vf7hoUOhe4SaEUBAeMcRRRKL0EXAZYK1N7G5UVuxG1RYG9LX1nieB69E1m0qO2kwFFbkOzX8jrtuVA4URZjrQ20zWK3WYiNXmpMvoSFWf83a5U07Tunogu2yGYneISTZ4cnmV00SbZE1WkI/l0ywFgNbu8g6UotaTKWvrVHX6qY2VFiR79TwO+66SQVH+cAXLp6NqVP7nC1NPVKGPGD2nNNx+PW3653LyP7DTdE86u/0BhoXy252amqiyXWHp3ZY0K4CLhOsxSVrO4tqQ7bRRDdRWJHv1PA77rphrhBbwwHSRwqY5bjuMx9p2NEeaAyLDIuFj4tlNzs1AE2bnLgsGAtbI5AXIuDFxmWxYNaRWto2FLUBiWv5s1BYke/U8NvlujZXSFRSrjSRArZy6LH9ABqyUgIToj86Ol7PwBlXH1snoDY3V5n79LjhsOcQtkYgK53MGSK0h1YsFnS9rusqcH2BoecRLr1sEa67YYmTDmSlsCIPdM56c71uHq6dJOUwfzdHFDs27Wua3FV/EzahGtYJqEkpJfbbH/Xjhm2jkVa51iQscnKQdzitC7Z9gG1Wum2BYa3GePpH+/Hs7pdx5aoL8fZb7zatFBeRLwhJXTt5N1xT9K/4+AVNk7u26ARzQjWsU+sf8Jd7V8dr/ghhbLxhSXqYSygv15qERU4O8g6ndUFvW2HtGphIaUDMDUIP+HH1Wx+pNBxz2dc4KSLyOZFWZF1dO3HXzqPhKss7ah9W1wlVhf4CEgi1anNkUdx9aHXee6G3SWIMpen44/Zq1tu1nlIcaExp8NErzsOPdryAWpWt14na1zgLmUSeiK4D8N8A/DsAFzNzRfvsSwBuAVAF8Hlm/mGWa3UzWZMuZX2oaXLdh5Uldh9WxwlV2znri7wct3kLy4iZZycqFIM8w2l1XPZqVu3aTClupjT4zXPOwl9/6xZ8/4HdeOap/ROpQxC9r3FWslryLwC4FsB9+kEi6gdwPYDzAHwAwE4i+i1mrjafovfppFsgba77MKJcLyoKxtwKzeWcAJqWhMe5n2wZMZPeW4mqEXSSdvxxq8PVz/MXzmxKKQ40r77tH5iLRefNwZ6nDoDBIAI+/NHFWHTenJYZIplEnplfAnxhMVgF4CFm/jWAg0Q0AuBiAM9kuV43EDd0a7dbwEwM5prrPg2qUSddpp1mpDNUOdgg8ESdSdMq9BYurr2wjt8W6uj6bvcPNKcDCUtp0BTeHETZtIpW+eTnANij/f56cKwJIloNYDUAzJs3r0XFyQeXoVu73QJmg0mS6z4t5ksS92Lpgj06Nl7veKL+bvqMaQ0TVR/+6GLnl0HCJicnWdymzSvECVOnum1mroiKNHP5XquIFXki2glgluWjO5j58awFYOYNADYAQLlcts9IdAmuQ7d2o/x4KtolSa77LMT5zJXY/vLdX9UFm2u+gLukfyAiMDM8j7DovDktGzUIxSCL29QMddSDA1w2M1e46kA79SJW5Jl5WYrzvgFAr8HZwbGeptuiNWwpBYBGH7j+eyuuHeYz18tGRH7uHPYnmE68c9JpjcDUqcnvtYRN9j4uaaGjggPSvJ/1wIJg8tTzqCve8TxolbtmE4DvEdHX4U+8ngvgn1t0rbbRDdEaut9w95PD9QyTYQKbZI/WuGvaFjCF+cx1sSWP4ZU8MHPDd/JaI6DTbR2xkIxtGyv1LK3KXWK6BrOku7Zh5omPSj/Qi2QNofwEgG8AOBPAViIaZObfZ+YXiehhAMMAxgF8riiRNZ10y9isZ6DZ6jCt2e8/sBvP7n459MVxuWZUTpuS15xt0hRbW1RNHmsEbH/Tjlw4Qv4MDx3CPeu31gMJxiybysSN1JK2mcng3ssaXfMogEdDPrsTwJ1Zzi80YlsiTR5wwcXn4NO3LrUKbMnzsOfHB+oLMGwvjss19URmSpijRNrFqmplh9mqXDhC6xiqHEStNhE8Th41jcTyGqkp6922R4IqS1Eselnx2kNY/YZTSg0CDzQK7NEjx7Ft48TSaduL43JN1WGYk6xRCdM6NeoRv3xv4s/D9GF0bLxp0w1FHi7TqD0Sps+YFhpl06q5LX0Tna6Lkxfai7nKLsrKUAKrGlHUi+N6zaNHjmP7o3u7XjzFL9+buAp4VuMhao+EqCibpG4glwyVto3t836nROR7jKQNPA/Lx+wwul08u2GCXEhHO0Z/cXskZI2ycfXzD1Xy29g+ChH5HiRpiFleL04viWcnJ8iF7iaqHScZLYfh6i4cKNs3ts8bEfkeI85KaHW0QKfFU1azCnlga8d623LdnMdGklQI5sb24pMXYq2EIk86ToZwN6Ez5Nm2kox422E0eS09uwAA9R2VhocOZT6XshK8kt1XGPd5N5D2ftg6MEHIA5e2laTd9g/MTZQOoZWIJd9i8rY+46yEbvebZ7kfEjUjpCXOzRfXtlzarX4NIP0K87wRkW8xrXCfxA3xOu03jyLL/ej2DkzoTlwEOq5tNWz3p210b7tGqeQBhNg9Hdo1vyQi32LE+mwk6/3o5g5M6E5cDYuotjVQXoBSybNudG9eQ2Vwido9rZ3zSyLyLUasz0bkfgjtJg9Dq39gbuRG9+bKcBAid09rZ4CEiHwbEOuzEbkfQjvJy7CI2ujevAYQ7ZNv5wifmLtnn45yucyVSiX+i4IgCCG00ted57nzPBcR7WXmsvUzEXlBEIrCZF1LESXyEicvCEJhkLUUzYjId5g8F0oJwmSnFxYDthuZeO0gk3VoKQitQqK3mhGR7yBFzjMjCJ0iLnprsiW5E5HvILJQShDay2QcPYvIdxAZWgpCe5mMo2cR+Q4zWRcGTbYhs9AdZB0992K7FZEX2s5kHDIL3UGW0XOvtlsReaHtTMYhs9A9pB0992q7lTh5oe1ILLPQi/Rqu5W0BkJH6EXfpiB0a7ttWe4aIvorAFcDGAXwMwA3MfM7wWdfAnALgCqAzzPzD+POJyIvCIKQnFbmrnkCwG8z8wCAlwF8KbhgP4DrAZwH4EoAf0dEpYzXEgRBEBKSSeSZeQczjwe/7gFwdvDzKgAPMfOvmfkggBEAF2e5liAIgpCcPCdebwawPfh5DgA949brwbEmiGg1EVWIqHLs2LEciyMIgiDEhlAS0U4Asywf3cHMjwffuQPAOIAHkxaAmTcA2AD4Pvmkfy8IgiCEEyvyzLws6nMiuhHASgCX88Qs7hsA9Knns4NjgiAIQhvJ5K4hoisB3A7g48x8UvtoE4DriegUIloA4FwA/5zlWoIgCEJysq54vQfAKQCeICIA2MPMa5j5RSJ6GMAwfDfO55i5mvFagiAIQkIyiTwzL4z47E4Ad2Y5vyAIgpANSWsgCIJQYETkBUEQCoyIvCAIQoERkRcEQSgwIvKCIAgFRkReEAShwIjIC4IgFBgReUEQhAIjIi8IglBgROQFQRAKjIi8IAhCgRGRFwRBKDAi8oIgCAVGRF4QBKHAiMgLgiAUGBF5QRCEAiMiLwiCUGBE5AVBEAqMiLwgCEKBEZEXBEEoMCLygiAIBUZEXhAEocCIyAuCIBQYEXlBEIQCIyIvCIJQYDKJPBH9BRENEdEgEe0gog8Ex4mI7iaikeDzC/MpriAIgpCErJb8XzHzADOfD2ALgD8Lji8HcG7wbzWAb2a8jiAIgpCCTCLPzCe0X98LgIOfVwH4DvvsATCDiGZnuZYgCIKQnL6sJyCiOwF8BsBxAEuDw3MAHNK+9npw7LDl71fDt/Yxb968rMURBEEQNGIteSLaSUQvWP6tAgBmvoOZ5wJ4EMBtSQvAzBuYuczM5TPPPDN5DQRBEIRQYi15Zl7meK4HAWwD8OcA3gAwV/vs7OCYIAiC0EayRtecq/26CsD+4OdNAD4TRNlcCuA4Mze5agRBEITWktUnv56IFgGoAXgNwJrg+DYAKwCMADgJ4KaM1xEEQRBSkEnkmfkPQo4zgM9lObcgCIKQHVnxKgiCUGBE5AVBEAqMiLwgCEKBEZEXBEEoMCLygiAIBUZEXhAEocCIyAuCIBQYEXlBEIQCIyIvCIJQYETkBUEQCoyIvCAIQoERkRcEQSgwIvKCIAgFRkReEAShwIjIC4IgFBgReSEbd90F7NrVeGzXLv+4IAgdJ+vOUMJk56KLgE99Cq/+5T3Y483GpbXDmP+l24CHH+50yQRBgIi8kJWlS/HqX96D0/7zzaidWcZpxyp49Zv3Y/7SpZ0umSAIEJEXcmCPNxu1M8v4w8NP4XsfuAyeNxvzO10oQRAAiMgLOXBp7TBOO1bB9z5wGa46WsHbtcOdLpIgCAEi8kI2du3C/C/dhle/eT88bzbeVj75D54FiMtGEDqOiLyQjeeeAx5+GPOXLp1w0XzwLP+4iLwgdBxi5k6XoU65XOZKpdLpYgiAHwJ50UWNQr1rly/et9/euXIJgtAEEe1l5rLtM7HkBTsSGikIhUBEXrAjoZGCUAhyWfFKRH9KRExEZwS/ExHdTUQjRDRERBfmcR2hvezxZmNrEBq59awy9nizO10kQRASktmSJ6K5AK4A8C/a4eUAzg3+XQLgm8H/Qg8hoZGC0Pvk4a757wBuB/C4dmwVgO+wP6u7h4hmENFsZhaV6BUkNFIQCkEmkSeiVQDeYOafEJH+0RwAh7TfXw+Oicj3ChIaKQiFIFbkiWgngFmWj+4A8GX4rprUENFqAKsBYN68eVlOJeSJLUxy6VIReEHoMWJFnpmX2Y4T0b8HsACAsuLPBvA8EV0M4A0Ac7Wvnx0cs51/A4ANgB8nn6TwgiAIQjSpo2uY+afMfBYzz2fm+fBdMhcy8xEAmwB8JoiyuRTAcfHHC4IgtJ9WxclvA7ACwAiAkwBuatF1BEEQhAhyE/nAmlc/M4DP5XVuQRAEIR2y/Z8gCEKB6aoEZUR0DMBrKf/8DAD/lmNxegGp8+RA6jw5yFLn32TmM20fdJXIZ4GIKmFZ2IqK1HlyIHWeHLSqzuKuEQRBKDAi8oIgCAWmSCK/odMF6ABS58mB1Hly0JI6F8YnLwiCIDRTJEteEARBMBCRFwRBKDBdLfJENJeIdhHRMBG9SERfCI6fTkRPENErwf+nBcdDd6QiohuC779CRDd0qk5xpKjzYiJ6hoh+TURrjXNdSUQHgvuxrhP1cSFFnf8oeL4/JaKnieh3tHMVtc6rgjoPElGFiJZo5ypk29b+7iIiGieiT2rHCllnIvoYER0PnvMgEf2Zdq50bZuZu/YfgNnwk54BwG8AeBlAP4C7AKwLjq8D8NXg5xUAtgMgAJcCeDY4fjqAnwf/nxb8fFqn65dTnc8CcBGAOwGs1c5TAvAzAOcAmArgJwD6O12/nOr8u+r5wd+FTD3nItf5VEzMoQ0A2F/0tq0903+Cnw/rk0WvM4CPAdhiOU/qtt3VljwzH2bm54OffwHgJfibj6wC8EDwtQcAXBP8XN+Ripn3AJhBRLMB/D6AJ5j5/zHz2wCeAHBl+2riTtI6M/NRZn4OwJhxqosBjDDzz5l5FMBDwTm6jhR1fjp4jgCwB34qa6DYdX6Xg7cdwHsBqJ8L27YD/guARwAc1Y4Vvc42UrftrhZ5HSKaD+ACAM8CmMkTqYuPAJgZ/By2I1XY8a7Gsc5hTJY63wJ/9AYUvM5E9Aki2g9gK4Cbg8OFrTMRzQHwCfh7ROsUts4BHyainxDRdiI6LziWus49IfJEdCr83vxPmPmE/llg3RQuDlTqHF9nIloKX+S/2LZC5kySOjPzo8y8GL7V9xftLGeeJKjz/wDwRWautbeE+ZOgzs/Dz0PzOwC+AeCxrNfuepEnoinwb86DzLwxOPxm4IZB8L8ayoXtSOW8U1U3kLDOYRS6zkQ0AOBbAFYx81vB4ULXWcHMTwE4h4jOQLHrXAbwEBG9CuCTAP6OiK5BgevMzCeY+d3g520ApmR9zl0t8kREAP4BwEvM/HXto00A1Iz6DQAe147bdqT6IYAriOi0YBb7iuBY15GizmE8B+BcIlpARFMBXB+co+tIWmcimgdgI4A/ZuaXte8Xuc4Lg78B+VFjpwB4CwVu28y8gCd2nvs/AD7LzI+hwHUmolnac74Yvka/hSxtO+vscSv/AVgCfxgzBGAw+LcCwPsBPAngFQA7AZwefJ8A/C38WeifAihr57oZ/k5VIwBu6nTdcqzzLPj+uRMA3gl+nh58tgL+bP7PANzR6brlWOdvAXhb+25FO1dR6/xFAC8G33sGwJKit23jb7+NILqmyHUGcFvwnH8CP6jgd7O2bUlrIAiCUGC62l0jCIIgZENEXhAEocCIyAuCIBQYEXlBEIQCIyIvCIJQYETkBUEQCoyIvCAIQoH5/7XqRRdptm8lAAAAAElFTkSuQmCCn”, “text/plain”: [

“<Figure size 432x288 with 1 Axes>”

]

}, “metadata”: {

“needs_background”: “light”

}, “output_type”: “display_data”

}

], “source”: [

“simplelc1.make_mask()n”, “n”, “plt.plot(simplelc1.time,simplelc1.flux,’.’)n”, “plt.plot(simplelc1.time[~simplelc1.mask],simplelc1.flux[~simplelc1.mask],’xr’)”

]

}, {

“cell_type”: “markdown”, “id”: “e0e849f3”, “metadata”: {}, “source”: [

“##### Using lc.flatten()n”, “This is the in-built flattening function. It has two ways of peforming the flattening which can be selected with the flattype argument:n”, “- bspline (default): fits smooth splines while iterating away anomalies/transits/etcn”, “- polystep: uses out-of-box polynomial fits to smooth data without influencing transit depthn”, “n”, “To specify which timeseries to flatten, use the timeseries (default is only the flux array)n”, “n”, “To tweak the flattening function, the knot_dist,`maxiter`,`sigmaclip`,`stepsize`, reflect, & polydegree arguments can be usedn”, “n”, “transit_mask is a key input to the flattten function if transits have been identifed in the timeseries, as this masks the transits from being removed.n”, “n”, “lc.flatten() will add a new timeseries to the lc class with the suffix _flat, and in both cases, the best-fit splines are saved to _spline

]

}, {

“cell_type”: “code”, “execution_count”: 48, “id”: “317c463e”, “metadata”: {}, “outputs”: [

{
“data”: {

“image/png”: 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n”, “text/plain”: [

“<Figure size 841.68x595.44 with 1 Axes>”

]

}, “metadata”: {

“needs_background”: “light”

}, “output_type”: “display_data”

}

], “source”: [

“simplelc1.flatten()n”, “simplelc1.plot(timeseries=[‘flux’,’flux_spline’,’flux_flat’],yoffset=12.5,ylim=(-25,50))”

]

}, {

“cell_type”: “markdown”, “id”: “19260c2a”, “metadata”: {}, “source”: [

“##### Using lc.bin()n”, “This is the in-built binning function.n”, “n”, “Key arguments:n”, “* timeseries: As with plot() and flatten(), you can include the timeseries to be binnedn”, “* binsize, this determines the size of the bines and defaults to 30mins (e.g. 1/48)n”, “* use_masked and extramask affect the masks used when binning.”

]

}, {

“cell_type”: “code”, “execution_count”: 61, “id”: “87d597be”, “metadata”: {}, “outputs”: [], “source”: [

“simplelc1.bin(binsize=1.5)”

]

}, {

“cell_type”: “code”, “execution_count”: 63, “id”: “72947481”, “metadata”: {}, “outputs”: [

{
“data”: {
“text/plain”: [

“<ErrorbarContainer object of 3 artists>”

]

}, “execution_count”: 63, “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”: [

“#simplelc1.plot() won’t show the bins, as the cadence is too large, so let’s go back to a standard plotting:n”, “n”, “plt.plot(simplelc1.time[simplelc1.mask],simplelc1.flux[simplelc1.mask],’.’,markersize=2,alpha=0.5)n”, “plt.errorbar(simplelc1.bin_time,simplelc1.bin_flux,yerr=simplelc1.bin_flux_err,fmt=’o’)”

]

}, {

“cell_type”: “markdown”, “id”: “7c4a9b43”, “metadata”: {}, “source”: [

“## More useful functionsn”, “n”, “n”, “## Stacking lc objectsn”, “n”, “Under the hood of the multilc class is the ability to stack lc objects.n”, “n”, “This is done by making a new multilc object (which can be empty) and calling multilc.stack([newlcs]) with a list of lc objects as arguments. For example:”

]

}, {

“cell_type”: “code”, “execution_count”: 80, “id”: “2e3423ad”, “metadata”: {}, “outputs”: [

{
“data”: {

“image/png”: 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n”, “text/plain”: [

“<Figure size 841.68x595.44 with 2 Axes>”

]

}, “metadata”: {

“needs_background”: “light”

}, “output_type”: “display_data”

}

], “source”: [

“testlc = lc.multilc(123456789,’tess’,do_search=False) #we need do_search =False here, as we don’t actually want to search for other lightcurves for the star TIC123456789n”, “testlc.stack([simplelc1,simplelc2])n”, “testlc.plot(savepng=False)”

]

}, {

“cell_type”: “markdown”, “id”: “06f46c89”, “metadata”: {}, “source”: [

“## Savingn”, “n”, “Lightcurves are saved, by default, in the same ID-specific folder that other MonoTools modules access, and which can be modified using the $MONOTOOLSPATH system environment variable but is by default in the MonoTools/data path. So, in this case, it would be in the MonoTools/data/TIC00123456789/ folder.n”, “n”, “There are two ways to save the lightcurves found by lc and multilc:n”, “n”, “##### 1) As a pickled object.n”, “n”, “This retainins most metadata, although we delete binned and flattened arrays (which are re-derivable from the other timeseries).”

]

}, {

“cell_type”: “code”, “execution_count”: null, “id”: “507a17c7”, “metadata”: {}, “outputs”: [], “source”: [

“tools.MonoData_savepath”

]

}, {

“cell_type”: “code”, “execution_count”: 87, “id”: “a68e57fd”, “metadata”: {}, “outputs”: [], “source”: [

“testlc.save()”

]

}, {

“cell_type”: “markdown”, “id”: “7bf600f6”, “metadata”: {}, “source”: [

“##### 2) As a csv.n”, “n”, “This does not retain metadata and only stores those timeseries with the same length as the time array (i.e. time, fluxes, flux_errs, cadence, mask, etc):”

]

}, {

“cell_type”: “code”, “execution_count”: 88, “id”: “67db47d0”, “metadata”: {}, “outputs”: [], “source”: [

“testlc.save_csv()”

]

}, {

“cell_type”: “code”, “execution_count”: 93, “id”: “cad2af7e”, “metadata”: {}, “outputs”: [

{
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]

}, “execution_count”: 93, “metadata”: {}, “output_type”: “execute_result”

}

], “source”: [

“#Let’s see what got stored:n”, “import pandas as pdn”, “import osn”, “from MonoTools.MonoTools import toolsn”, “n”, “df=pd.read_csv(os.path.join(tools.MonoData_savepath,"TIC00123456789","TIC00123456789_lc.csv"),index_col=0)n”, “df”

]

}, {

“cell_type”: “markdown”, “id”: “46268c02”, “metadata”: {}, “source”: [

“## Loadingn”, “n”, “If you have already called multilc with a given id/mission pair, then the data is usually automatically stored in the MonoTools datapath. The next time you call multilc, it will check this path for existing data and load it using multilc.load_pickle(). This can occasionally cause bugs, so often it’s good to check if load=False fixes problems with initialising multilc objects.”

]

}

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