{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# TTV model evaluation example\n", "\n", "*Author: Hannu Parviainen*
\n", "*Last modified: 20.10.2020*\n", "\n", "Evaluating the transit model for a planet whose transit center times deviate from a linear ephemeris is extremely simple in PyTransit. Each light curve (indexed by an array of light curve indices, `lcids`) can be given its own zero epoch by giving the model a set of per-light-curve epoch indices (`epids`), and then giving the zero epoch (`t0`) as an array rather than as a single float. Here is an example using the `RoadRunner` model, but the same approach will work with the `QuadraticModel` as well (and with the rest of the transit models a bit later).\n", "\n", "**Note:** The first evaluation of the transit model takes a bit of time because numba compiles the code behind the scenes only when needed (and calling `TransitModel.evaluate` with different types of parameters calls actually a different numba routines). The model evaluation is extremely fast after all the required code has been compiled." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Populating the interactive namespace from numpy and matplotlib\n" ] } ], "source": [ "%pylab inline" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "from pytransit import RoadRunnerModel" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "rc('figure', figsize=(13,4))" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "tm = RoadRunnerModel()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Set up the model\n", "\n", "First, we create the time, light curve index, and epoch index arrays. We model `ntr` consecutive transits, each with `npt` points." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "ntr = 3\n", "npt = 200" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "times = concatenate(linspace(-0.2, 0.2, npt)[newaxis,:] + arange(ntr)[:,newaxis])\n", "lcids = repeat(arange(ntr), npt)\n", "epids = arange(ntr)" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, axs = subplots(3, 1, figsize=(13,6), sharex='all')\n", "axs[0].plot(times)\n", "axs[1].plot(lcids)\n", "axs[2].plot(epids[lcids])\n", "setp(axs[0], ylabel='Time [d]')\n", "setp(axs[1], ylabel='Light curve index')\n", "setp(axs[2], ylabel='Epoch index', xlabel='Point')\n", "fig.tight_layout()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Model evaluation for a linear ephemeris\n", "\n", "First, we check that everything works as it should when we assume that the orbit does not evolve over time." ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "tm.set_data(times, lcids=lcids)" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "flux = tm.evaluate(k=0.11, ldc=[0.23, 0.1], t0=1.0, p=1.0, a=4.0, i=0.5*pi)" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, ax = subplots()\n", "ax.plot(times, flux, 'k.-')\n", "fig.tight_layout()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## TTV model evaluation\n", "\n", "Next, we give the `TransitModel.set_data` method the per-light-curve *epoch indices* (`epids`), and then a separate transit centre time in the model evaluation, one per light curve." ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "scrolled": false }, "outputs": [], "source": [ "tm.set_data(times, lcids=lcids, epids=epids)" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "flux = tm.evaluate(k=0.11, ldc=[0.23, 0.1], t0=[0.0, 1.1, 1.9], p=1.0, a=4.0, i=0.5*pi)" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, ax = subplots()\n", "ax.plot(times, flux, 'k.-')\n", "fig.tight_layout()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As with all the PyTransit models, the TTV model can be evaluated for a set of parameter vectors in a single call." ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "npv = 10\n", "ks = normal(0.1, 0.01, npv)\n", "ldcs = tile([0.23, 0.1], [npv,1,1])\n", "t0s = tile([0.0, 1.1, 1.9], [npv, 1])\n", "t0s[:,1] += normal(0.0, 0.02, npv)\n", "ps = full(npv, 1.0)\n", "smas = full(npv, 4.0)\n", "incs = full(npv, 0.5*pi)" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [], "source": [ "flux = tm.evaluate(k=ks, ldc=ldcs, t0=t0s, p=ps, a=smas, i=incs)" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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© 2020 Hannu Parviainen
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