{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": { "tags": [ "hide-cell" ] }, "outputs": [], "source": [ "import jax.numpy as jnp\n", "import matplotlib.pyplot as plt\n", "plt.style.use(\"https://github.com/mlefkir/beauxgraphs/raw/main/beautifulgraphs_colblind.mplstyle\")" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "# Timmer and Koenig's method\n", "\n", "We follow the method described in [Timmer & Koenig (1995)](https://ui.adsabs.harvard.edu/abs/1995A%26A...300..707T). " ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## Description" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "### Main algorithm\n", "\n", "1. Evaluate the power spectral density at a set of frequencies $f_j$ to get a set of power values $P_j=\\mathcal{P}(f_j)$\n", "2. Draw two random numbers $N_{1,j}$ and $N_{2,j}$ from a standard normal distribution for each frequency $f_j$.\n", "3. Calculate the complex Fourier coefficients $A_j=\\sqrt{P_j/2} \\left (N_{1,j}+\\mathrm{i}N_{2,j} \\right)$. Where $A_0=0$ so that the mean of the time series is zero and the last value $A_j$ is a real number.\n", "4. Calculate the inverse Fourier transform of the coefficients $A_j$ to get a realisation of the time series $x(t)$.\n", "\n", "### Extending the frequency grid\n", "\n", "To reduce the effects of aliasing and leakage in the generated time series we extend the frequency grid with two factors: $S_\\mathrm{low}$ and $S_\\mathrm{high}$, for low and high frequencies, respectively. The grid of frequencies is then given by $f_0 = f_\\mathrm{min}/S_\\mathrm{low} = \\Delta f$ to $f_N = f_\\mathrm{max}S_\\mathrm{high}$.\n", "\n", "```{eval-rst}\n", ".. tikz:: \n", " :xscale: 90\n", "\n", " [thick]\n", "\n", " \\draw (0,2pt) -- + (0,-2pt) node[below=1mm] {0};\n", " \\draw (.5,2pt) -- + (0,-2pt) node[below=1mm] {$f_0$};\n", " \\draw (3.5,5pt) -- + (0,-5pt) node[below=1mm] {$f_\\mathrm{min}$};\n", " \\draw (10.,5pt) -- + (0,-5pt) node[below=1mm] {$f_\\mathrm{max}$};\n", " \\draw (14,5pt) -- + (0,-5pt) node[below=1mm] {$f_\\mathrm{N}$};\n", " \\draw[thick] (0,0) -- node[below=7mm] {Frequency $f$} + (15,0);\n", " \\foreach \\x in {0,0.5,...,14.}\n", " \\draw (\\x cm,3pt) -- (\\x cm,-3pt) node[anchor=north] {};\n", "```\n", "\n", "The generated time series will be longer than the desired time series, to obtain a time series of duration $T$ with sampling period $\\Delta T$, a random subset of the long time is selected. The subset is then resampled to the desired sampling period $\\Delta T$.\n", "\n", "The true variance of the process is given by $\\int_{-\\infty}^{+\\infty} \\mathcal{P}(f) \\mathrm{d}f$. To correct for the variance of the generated time series, we multiply the time series by a factor $2\\sqrt{f_0}N$. More details about the sample variance of time series are given in the notebook [on the sample variance](../references/On_the_sample_variance.ipynb).\n", "### Implementation in `pioran`\n", "\n", "The main method is implemented in the {meth}`~pioran.simulate.Simulations.timmer_Koenig_method` method of the class {class}`~pioran.simulate.Simulations`. This method is used to generate the long-term time series. Then a random subset is selected and resampled to the desired sampling period using the {meth}`~pioran.simulate.Simulations.extract_subset_timeseries` and {meth}`~pioran.simulate.Simulations.sample_timeseries` methods. This is done under the hood by the {meth}`~pioran.simulate.Simulations.simulate` method, which we detail in the next section." ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## Usage in `pioran`" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "The first thing to do is to define the parameters of the time series, duration, sampling and PSD model and the parameters of the method which are scaling factors for the frequency grid.\n", "All of these are given to the initialisation of a {class}`~pioran.simulate.Simulations` object." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "No GPU/TPU found, falling back to CPU. (Set TF_CPP_MIN_LOG_LEVEL=0 and rerun for more info.)\n" ] } ], "source": [ "from pioran import Simulations\n", "from pioran.psd import Lorentzian\n", "\n", "psd_model = Lorentzian([0.0,1,1e-2])\n", "\n", "duration = 500\n", "dt = 1\n", "S_low = 20 # scale of the lowest frequency\n", "S_high = 20 # scale of the highest frequency\n", "Sim = Simulations(T=duration,dt=dt,model=psd_model,S_low=S_low,S_high=S_high)" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "We can plot the PSD model to see what it looks like:" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "tags": [ "hide-input" ] }, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig,ax = Sim.plot_psd(figsize=(8,4))" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "To generate a random time series we use the {meth}`~pioran.simulate.Simulations.simulate` method. We specify the method to use with `method='TK'`. By default, the values of the time series are randomised with a normal distribution. This can be changed with the `randomise_fluxes` argument. The errors are assumed to be Gaussian.\n", "\n", "By default, the mean of the time series is shifted to twice the minimum of the time series to get a positive-valued time series. This can be changed with the `mean` argument. \n", "\n", "The sampling can be selected as irregular with the `irregular_sampling` argument. The seed of the random number generator must be set with the `seed` argument." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "t, ts, ts_err = Sim.simulate(method='TK',seed=1423,irregular_sampling=True)" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "tags": [ "hide-input" ] }, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots(figsize=(8,4))\n", "ax.errorbar(t,ts,yerr=ts_err,fmt='o')\n", "ax.set_xlabel('Time (d)')\n", "ax.set_ylabel('Simulated time series')\n", "fig.tight_layout()" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## References\n", "\n", "Timmer J. & Koenig M. On generating power law noise. Astronomy and Astrophysics, [300](https://ui.adsabs.harvard.edu/abs/1995A%26A...300..707T), 707 (1995). " ] } ], "metadata": { "kernelspec": { "display_name": "pioran", "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": "3.10.9" }, "orig_nbformat": 4 }, "nbformat": 4, "nbformat_minor": 2 }