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Some simple examples of extracting uncertainties from astropy.modeling
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| { | |
| "cells": [ | |
| { | |
| "cell_type": "code", | |
| "execution_count": 1, | |
| "metadata": { | |
| "collapsed": true | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "from collections import defaultdict\n", | |
| "\n", | |
| "import numpy as np\n", | |
| "\n", | |
| "%matplotlib inline\n", | |
| "from matplotlib import pyplot as plt\n", | |
| "\n", | |
| "from astropy.modeling import models" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 2, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "# makes the \"random\" numbers reproducible\n", | |
| "np.random.seed(12345)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "# Testing fit uncertainties " | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 3, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "[<matplotlib.lines.Line2D at 0x11234e7b8>]" | |
| ] | |
| }, | |
| "execution_count": 3, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| }, | |
| { | |
| "data": { | |
| "image/png": 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iW76N8oJyTEZTRGfg/g/u5/rXr2dz22b/tmxyBmLlDDT1NDG5cLK/k2A49Peh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\nfI59jfvQaBYULeCCC2D3bmMU8i035kDjArYfrA54XFtvGxo9ajFgT7Z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9xvSc6RGNq/fF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\ncEQMCIIgCMIE5/8HlbHkDGVN/1EAAAAASUVORK5CYII=\n", | |
| "text/plain": [ | |
| "<matplotlib.figure.Figure at 0x10d22e4e0>" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "gauss = models.Gaussian1D(amplitude=5.3, mean=1.4, stddev=1.1)\n", | |
| "x = np.linspace(-2, 5, 100)\n", | |
| "\n", | |
| "base_data = gauss(x)\n", | |
| "data_random = np.random.normal(0, 1, x.shape)\n", | |
| "data = base_data + data_random\n", | |
| "plt.plot(x, base_data)\n", | |
| "plt.plot(x, data)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 4, | |
| "metadata": { | |
| "collapsed": true | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "from astropy.modeling import fitting" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 5, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "fitter = fitting.LevMarLSQFitter()\n", | |
| "model = fitter(gauss, x, data)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "## Covariance in the LevMarLSQFitter" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "The below is the parameter covariance matrix that `LevMarLSQFitter` generates. Most of the other fitters don't report uncertainties, but the Levenberg-Marquardt algorithms is such that it's relatively straightforward to have it come out without additional computational expense." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 6, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "array([[ 5.68024914e-02, 1.11636496e-06, -8.64051873e-03],\n", | |
| " [ 1.11636496e-06, 3.93137225e-03, -5.70164087e-07],\n", | |
| " [ -8.64051873e-03, -5.70164087e-07, 3.93869884e-03]])" | |
| ] | |
| }, | |
| "execution_count": 6, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "cov = fitter.fit_info['param_cov']\n", | |
| "cov" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "So then $\\sqrt{{\\rm diag}(cov)}$ is the uncertainties on the parameters:" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 7, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "{'amplitude': 0.2383327325763821,\n", | |
| " 'mean': 0.062700655905525871,\n", | |
| " 'stddev': 0.062759053809748763}" | |
| ] | |
| }, | |
| "execution_count": 7, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "dict(zip(model.param_names, np.diag(cov)**0.5))" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "Now lets just try making two models like the original model, but with the parameters for the + and - sides of the uncertainties, and show those models over the original data:" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 8, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "modelup = model.copy()\n", | |
| "modeldown = model.copy()\n", | |
| "\n", | |
| "for i, nm in enumerate(model.param_names):\n", | |
| " setattr(modelup, nm, getattr(model, nm) + fitter.fit_info['param_cov'][i, i]**0.5)\n", | |
| " setattr(modeldown, nm, getattr(model, nm) - fitter.fit_info['param_cov'][i, i]**0.5)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 9, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "<matplotlib.legend.Legend at 0x11290ba58>" | |
| ] | |
| }, | |
| "execution_count": 9, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| }, | |
| { | |
| "data": { | |
| "image/png": 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dl8iALYznMjMrdwoUZxaTODyRk2EtWBQRg+fpEwx6chj+nCLpje8qz90FQvxC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\n2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| |
| "text/plain": [ | |
| "<matplotlib.figure.Figure at 0x11238b4e0>" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "plt.plot(x, data, label='data')\n", | |
| "plt.plot(x, model(x), 'r', label='model')\n", | |
| "plt.plot(x, modelup(x), 'm', ls='--', label='model + unc')\n", | |
| "plt.plot(x, modeldown(x), 'g', ls='--', label='model - unc')\n", | |
| "plt.legend(loc=0)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "## Monte Carlo Uncertainties " | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "A completely different way to do uncertainties is to do Monte Carlo realizations of the spectrum and fit a bunch of those. The below does exactly this, and then plot the distributions. The width of those distributions then encode the uncertainties in the fit." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 10, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "dists = defaultdict(list)\n", | |
| "for i in range(1000):\n", | |
| " # create a data set that is the base data, but with a random offset that's scaled\n", | |
| " # to match the uncertainties we used to create the data in the first place\n", | |
| " unc = np.std(data_random)\n", | |
| " yoff = data + np.random.randn(len(data)) * unc\n", | |
| " \n", | |
| " # make a temporary fit that we just discard at the end of this loop,\n", | |
| " # having extracted the parameter values\n", | |
| " modeli = fitter(gauss, x, yoff)\n", | |
| " for nm in modeli.param_names:\n", | |
| " dists[nm].append(getattr(modeli, nm).value)\n", | |
| " \n", | |
| "dists = {k: np.array(v) for k,v in dists.items()}" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 11, | |
| "metadata": { | |
| "collapsed": false, | |
| "scrolled": false | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "LevMar fitter uncertainties:\n", | |
| " [[ 0.23833273 0.00105658 -0.09295439]\n", | |
| " [ 0.00105658 0.06270066 -0.00075509]\n", | |
| " [-0.09295439 -0.00075509 0.06275905]]\n" | |
| ] | |
| }, | |
| { | |
| "data": { | |
| "image/png": 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HgrKIiIiIiA8FZRERERERHwrKIiIiIiI+FJRFRERERHwoKIuIiIiI+FBQFhERERHxoaAs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\nQ/369bnqqqsCul+4/Pjjj2zYsIFHHnkk0qEIIYQQohSC7aMc7fZgzCR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UBBW+9MKR9I5Q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\nAAAASUVORK5CYII=\n", | |
| "text/plain": [ | |
| "<matplotlib.figure.Figure at 0x10ca6eeb8>" | |
| ] | |
| }, | |
| "metadata": {}, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "# you'll need to \"pip install corner\" to get the plot below\n", | |
| "import corner\n", | |
| "\n", | |
| "distarr = np.array([dists[nm] for nm in model.param_names]).T\n", | |
| "\n", | |
| "corner.corner(distarr, labels=model.param_names, show_titles=True, title_fmt='.3f', truths=model.parameters)\n", | |
| "print('LevMar fitter uncertainties:\\n', np.sign(cov)*np.abs(cov)**0.5)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "Comparing the diagonals of the covariance matrix to the uncertainties the corner plot shows demonstrates that they are quite consistent: the `mean` is very close, while for `amplitude` and `stddev` they are fairly close, but not quite the same, primarily due to a larger covariance between the parameters." | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "# Chi-squared" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "To compute the chi-squared we can just do so directly, using:\n", | |
| "\n", | |
| "$ \\chi^2 = \\sum_{i}\\frac{(O_i-E_i)^2}{\\sigma^2}$\n", | |
| "\n", | |
| "In this case, $O_i$ is the actual data, and $E_i$ are the model's outputs, and \\sigma^2 is the variance (could be per-pixel but in this case we assumed uniform)." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 12, | |
| "metadata": { | |
| "collapsed": true | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "dof = len(data) - len(model.parameters)\n", | |
| "unc = 1 # this is the amplitude of data_random, so we know the *true* uncertainty in each pixel" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "Below we show the *reduced* chi-squared, as that's what we can use to actually compare fits." | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 13, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "1.0717686317063173" | |
| ] | |
| }, | |
| "execution_count": 13, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "Oi = data\n", | |
| "Ei = model(x)\n", | |
| "chisq = np.sum((Oi - Ei)**2 / unc)\n", | |
| "chisq / dof" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "Seems promising... Now lets make sure the one-sigma-up and one-sigma-down are worse fits:" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 14, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "1.1350310771395113" | |
| ] | |
| }, | |
| "execution_count": 14, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "Oi = data\n", | |
| "Ei = modelup(x)\n", | |
| "chisq = np.sum((Oi - Ei)**2 / unc)\n", | |
| "chisq / dof" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 15, | |
| "metadata": { | |
| "collapsed": false | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "1.132821998907509" | |
| ] | |
| }, | |
| "execution_count": 15, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "Oi = data\n", | |
| "Ei = modeldown(x)\n", | |
| "chisq = np.sum((Oi - Ei)**2 / unc)\n", | |
| "chisq / dof" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "Hooray! Statistics kind of makes sense after all!" | |
| ] | |
| } | |
| ], | |
| "metadata": { | |
| "anaconda-cloud": {}, | |
| "kernelspec": { | |
| "display_name": "Python [conda env:aas229-workshop]", | |
| "language": "python", | |
| "name": "conda-env-aas229-workshop-py" | |
| }, | |
| "language_info": { | |
| "codemirror_mode": { | |
| "name": "ipython", | |
| "version": 3 | |
| }, | |
| "file_extension": ".py", | |
| "mimetype": "text/x-python", | |
| "name": "python", | |
| "nbconvert_exporter": "python", | |
| "pygments_lexer": "ipython3", | |
| "version": "3.5.2" | |
| } | |
| }, | |
| "nbformat": 4, | |
| "nbformat_minor": 0 | |
| } |
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