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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# GolemFlavor Inference"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"In this example, we will take the fake data generated in the `tutorial.ipynb` example and use it to make an inference the source flavour composition using Bayesian techniques."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"from __future__ import absolute_import, division, print_function\n",
"\n",
"from functools import partial\n",
"\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Define Fake Data"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We will generate some fake data using a multivariate Gaussian likelihood, as described in the `tutorial.ipynb` notebook. We set our injected source composition to the pion decay model $(1:2:0)_S$ and use the global neutrino data fit mixing matrix values to calculate the expected measured composition."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"from golemflavor.fr import NUFIT_U\n",
"from golemflavor.fr import normalize_fr, u_to_fr\n",
"\n",
"source_composition = normalize_fr((1, 0, 0))\n",
"measured_composition = u_to_fr(source_composition, NUFIT_U)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We also set the smearing, which represents detector related imperfections in our Gaussian likelihood:"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"smearing = 0.02"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Then we define the `asimov_paramset` which contains `Params` objects for each of our measured quantities:"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"from golemflavor.fr import fr_to_angles\n",
"from golemflavor.enums import ParamTag\n",
"from golemflavor.param import Param, ParamSet\n",
"\n",
"# Convert from flavor composition to flavor angles\n",
"measured_flavor_angles = fr_to_angles(measured_composition)\n",
"\n",
"# Parameters can be tagged for later convenience\n",
"tag = ParamTag.BESTFIT\n",
"\n",
"# Define the asimov `ParamSet`, with `Param` objects containing information such as name, value and ranges.\n",
"asimov_paramset = [\n",
" Param(name='measured_angle1', value=measured_flavor_angles[0], ranges=[ 0., 1.], std=smearing, tag=tag, tex=r'\\sin^4\\phi_\\oplus'),\n",
" Param(name='measured_angle2', value=measured_flavor_angles[1], ranges=[-1., 1.], std=smearing, tag=tag, tex=r'\\cos(2\\psi_\\oplus)')\n",
"]\n",
"asimov_paramset = ParamSet(asimov_paramset)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Physics Model"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The goal here is to make an inference of the source flavor composition from our fake data measurement. In order to do this, we need a model that links the two. Of course, in this case we will use the neutrino mixing model that we generated the fake data with, but it is worth mentioning that with real data we sometimes do not have this luxury. Model dependence is a heavily debated topic in physics. That isn't to say that having model dependence is a bad thing, indeed the best physicists are ones which do make model assumptions but can however justify their simplifications to the wider community.\n",
"\n",
"As a reminder from `tutorial.ipynb`, the measured flavor composition can be written as a function of the source flavor composition and mixing matrix:\n",
"\n",
"$$ \\phi_{\\alpha,\\oplus}=\\sum_{i,\\beta} \\mid{U_{\\alpha i}}\\mid^2\\mid{U_{\\beta i}}\\mid^2\\phi_{\\beta,\\text{S}} $$\n",
"\n",
"So here we must sample over the source flavor compositions to see which agrees best with the data. However, we must also take into account that the values of the mixing matrix are perfect and have uncertainties of their own."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Nuisance Parameters"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Not all parameters of a model are of direct inferential interest, however they still need to be included as they may reduce the effect of systematic bias. These are called *nuisance parameters*. Here the mixing matrix parameters are examples of such nuisance parameters and we must include the effect of their uncertainties in our inference of the source flavor composition."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Anarchic Sampling\n",
"\n",
"In the same way that flavor compositions cannot directly be sampled over, the mixing matrix values also cannot directly be sampled (it's also **extremely** inefficient to brute force sample values in a matrix such that the resulting matrix is unitary). As with any Bayesian inference, the prior distribution needs to be chosen carefully. Firstly we can rewrite the $3\\times3$ unitary mixing matrix in terms of *mixing angles*. The following is the standard representation most commonly used:\n",
"\n",
"$$\n",
"\\begin{align}\n",
" U=\n",
" \\begin{pmatrix}\n",
" 1 & 0 & 0 \\\\\n",
" 0 & c_{23} & s_{23} \\\\\n",
" 0 & -s_{23} & c_{23} \\\\\n",
" \\end{pmatrix}\n",
" \\begin{pmatrix}\n",
" c_{13} & 0 & s_{13}e^{-i\\delta} \\\\\n",
" 0 & 1 & 0 \\\\\n",
" -s_{13}e^{i\\delta} & 0 &c_{13} \\\\\n",
" \\end{pmatrix}\n",
" \\begin{pmatrix}\n",
" c_{12} & s_{12} & 0 \\\\\n",
" -s_{12} & c_{12} & 0 \\\\\n",
" 0 & 0 & 1 \\\\\n",
" \\end{pmatrix}\n",
"\\end{align}\n",
"$$\n",
"\n",
"where $s_{ij}\\equiv\\sin\\theta_{ij}$, $c_{ij}\\equiv\\cos\\theta_{ij}$, $\\theta_{ij}$ are the three mixing angles and $\\delta$ is the CP violating phase. Overall phases in the mixing matrix do not affect neutrino oscillations, which only depend on quartic products, and so they have been omitted.\n",
"\n",
"Now we have an efficient way of generating $3\\times3$ unitary matrices we can focus on how to define the prior space which we sample from. As we did for the flavor angles, we must do so under the integration invariant [*Haar measure*](https://doi.org/10.1016/j.physletb.2003.08.045). For the group $U(3)$, the Haar measure is given by the volume element $\\text{d}U$, which can be written in terms of the above mixing angles:\n",
"\n",
"$$\n",
"\\begin{align}\n",
" \\text{d} U=\\text{d}\\left(\\sin^2\\theta_{12}\\right)\\wedge\\,\n",
" \\text{d}\\left(\\cos^4\\theta_{13}\\right)\\wedge\\,\n",
" \\text{d}\\left(\\sin^2\\theta_{23}\\right)\\wedge\\,\\text{d}\\delta\n",
"\\end{align}\n",
"$$\n",
"\n",
"which says that the Haar measure for the group $U(3)$ is flat in $\\sin^2\\theta_{12}$, $\\cos^4\\theta_{13}$, $\\sin^2\\theta_{23}$ and $\\delta$. Therefore, in order to ensure the distribution over the mixing matrix $U$ is unbiased, the prior space of the mixing angles must be chosen according to this Haar measure, i.e. in $\\sin^2\\theta_{12}$, $\\cos^4\\theta_{13}$, $\\sin^2\\theta_{23}$ and $\\delta$.\n",
"\n",
"Of course, GolemFlavor provides the handy function to be able to do this conversion `angles_to_u`."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Help on function angles_to_u in module golemflavor.fr:\n",
"\n",
"angles_to_u(bsm_angles)\n",
" Convert angular projection of the mixing matrix elements back into the\n",
" mixing matrix elements.\n",
" \n",
" Parameters\n",
" ----------\n",
" bsm_angles : list, length = 4\n",
" sin(12)^2, cos(13)^4, sin(23)^2 and deltacp\n",
" \n",
" Returns\n",
" ----------\n",
" unitary numpy ndarray of shape (3, 3)\n",
" \n",
" Examples\n",
" ----------\n",
" >>> from fr import angles_to_u\n",
" >>> print(angles_to_u((0.2, 0.3, 0.5, 1.5)))\n",
" array([[ 0.66195018+0.j , 0.33097509+0.j , 0.04757188-0.6708311j ],\n",
" [-0.34631487-0.42427084j, 0.61741198-0.21213542j, 0.52331757+0.j ],\n",
" [ 0.28614067-0.42427084j, -0.64749908-0.21213542j, 0.52331757+0.j ]])\n",
"\n"
]
}
],
"source": [
"from golemflavor.fr import angles_to_u\n",
"help(angles_to_u)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Gaussian Priors\n",
"\n",
"The [global fit to world neutrino data](<https://doi.org/10.1007/JHEP01(2017)087>) includes estimates of the uncertainty of each mixing angle. These uncertainties can be included as an extra Gaussian prior in our likelihood by specifying the `prior` keyword when defining the `Param`, with the `std` keyword being the one standard deviation from the central value."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"from golemflavor.enums import PriorsCateg\n",
"\n",
"# Params can be tagged for later convenience\n",
"tag = ParamTag.SM_ANGLES\n",
"\n",
"# Include with a Limited Gaussian prior, which is a Gaussian adjusted for boundaries defined by `ranges`\n",
"lg_prior = PriorsCateg.LIMITEDGAUSS\n",
"\n",
"# Define the nuisance `Param` objects containing information such as name, value, ranges, prior and std.\n",
"nuisance = [\n",
" Param(name='s_12_2', value=0.307, seed=[0.26, 0.35], ranges=[0., 1.], std=0.013, tex=r's_{12}^2', prior=lg_prior, tag=tag),\n",
" Param(name='c_13_4', value=(1-(0.02206))**2, seed=[0.950, 0.961], ranges=[0., 1.], std=0.00147, tex=r'c_{13}^4', prior=lg_prior, tag=tag),\n",
" Param(name='s_23_2', value=0.538, seed=[0.31, 0.75], ranges=[0., 1.], std=0.069, tex=r's_{23}^2', prior=lg_prior, tag=tag),\n",
" Param(name='dcp', value=4.08404, seed=[0, 2*np.pi], ranges=[0., 2*np.pi], std=2.0, tex=r'\\delta_{CP}', tag=tag),\n",
"]\n",
"\n",
"# Define the source flavor angles `Param` objects\n",
"tag = ParamTag.SRCANGLES\n",
"src_compositions = [\n",
" Param(name='source_angle1', value=0, ranges=[ 0., 1.], tag=tag, tex=r'\\sin^4\\phi_S'),\n",
" Param(name='source_angle2', value=0, ranges=[-1., 1.], tag=tag, tex=r'\\cos(2\\psi_S)')\n",
"]\n",
"\n",
"# Define the llh `ParamSet`, containing the nuisance parameters plus our parameter of interest\n",
"llh_paramset = ParamSet(nuisance + src_compositions)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"As a reminder, we have 2 `ParamSet` objects:\n",
"* `asimov_paramset` contains the measured parameters\n",
"* `llh_paramset` contains the model parameter values"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Markov Chain Monte Carlo"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now, we wrap our physics model along with the `multi_gaussian` likelihood into a function that accepts input parameters `theta` from the MCMC:"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Running without GolemFit\n"
]
}
],
"source": [
"from golemflavor.fr import angles_to_fr\n",
"from golemflavor.llh import multi_gaussian\n",
"\n",
"def triangle_llh(theta, asimov_paramset, llh_paramset):\n",
" \"\"\"Log likelihood function for a given theta.\"\"\"\n",
" if len(theta) != len(llh_paramset):\n",
" raise AssertionError(\n",
" 'Length of MCMC scan is not the same as the input '\n",
" 'params\\ntheta={0}\\nparamset]{1}'.format(theta, llh_paramset)\n",
" )\n",
"\n",
" # Set llh_parameters values to the sampled parameters\n",
" for idx, param in enumerate(llh_paramset):\n",
" param.value = theta[idx]\n",
"\n",
" # Convert sampled mixing angles to a mixing matrix\n",
" sm_angles = llh_paramset.from_tag(ParamTag.SM_ANGLES, values=True)\n",
" sm_u = angles_to_u(sm_angles)\n",
"\n",
" # Convert flavor angles to flavor compositions for the model parameters\n",
" source_angles = llh_paramset.from_tag(ParamTag.SRCANGLES, values=True)\n",
" source_composition = angles_to_fr(source_angles)\n",
"\n",
" # Calculate the expected measured flavour composition for our sampled values\n",
" measured_composition = u_to_fr(source_composition, sm_u)\n",
"\n",
" # Convert flavor angles to flavor compositions for the injected parameters\n",
" bestfit_measured_comp = angles_to_fr(asimov_paramset.from_tag(ParamTag.BESTFIT, values=True))\n",
"\n",
" # Get the value of `smearing`\n",
" smearing = asimov_paramset['measured_angle1'].std\n",
"\n",
" # Calculate the log likelihood using `multi_gaussian`\n",
" llh = multi_gaussian(measured_composition, bestfit_measured_comp, smearing)\n",
" return llh"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Last thing we need to setup is our prior distribution, which in this case includes both the bounds on our model parameters, as well as the extra priors for the mixing angle parameters. As we have defined this already in the `ParamSet` object using the `prior`, `std` and `ranges` keyword, we can use the GolemFlavor function `lnprior` to do the work for us:"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"from golemflavor.llh import lnprior\n",
"\n",
"def ln_prob(theta, asimov_paramset, llh_paramset):\n",
" \"\"\"Posterior function for a given theta.\"\"\"\n",
" # Get the value of the log prior (prior from mixing matrix Params is calculated here)\n",
" lp = lnprior(theta, paramset=llh_paramset)\n",
" if not np.isfinite(lp):\n",
" return -np.inf\n",
" \n",
" # Return the log prior + log likelihood\n",
" return lp + triangle_llh(theta, asimov_paramset, llh_paramset)\n",
"\n",
"# Evalaute the posterior using the defined `asimov_paramset` and `llh_paramset`\n",
"ln_prob_eval = partial(\n",
" ln_prob,\n",
" asimov_paramset=asimov_paramset,\n",
" llh_paramset=llh_paramset\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Running burn-in\n"
]
},
{
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"application/vnd.jupyter.widget-view+json": {
"model_id": "e1d59d638e5f4fa483057effebec7889",
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},
"text/plain": [
"HBox(children=(FloatProgress(value=0.0, max=1000.0), HTML(value='')))"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Finished burn-in\n",
"Running\n"
]
},
{
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"application/vnd.jupyter.widget-view+json": {
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{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Finished\n",
"acceptance fraction [0.4288 0.4305 0.4342 0.4181 0.4278 0.4304 0.4294 0.4315 0.4169 0.4133\n",
" 0.428 0.4408 0.4145 0.4163 0.4364 0.4226 0.4222 0.4071 0.4179 0.4299\n",
" 0.4419 0.4208 0.431 0.418 0.4301 0.4332 0.4291 0.415 0.4194 0.431\n",
" 0.4299 0.4429 0.4419 0.4216 0.4281 0.4245 0.4136 0.4278 0.4275 0.4275\n",
" 0.4167 0.4266 0.4308 0.4174 0.4339 0.4245 0.4331 0.4383 0.4129 0.4408\n",
" 0.4221 0.4331 0.4229 0.4316 0.428 0.4263 0.433 0.4309 0.4136 0.4331]\n",
"sum of acceptance fraction 25.601\n",
"np.unique(samples[:,0]).shape (256044,)\n",
"autocorrelation [ 84.76795567 90.34226183 101.72273776 124.98444783 103.45178419\n",
" 101.3873447 ]\n"
]
}
],
"source": [
"import golemflavor.mcmc as mcmc_utils\n",
"\n",
"# Reduce these values for a quicker runtime\n",
"nwalkers = 60\n",
"burnin = 1000\n",
"nsteps = 10000\n",
"\n",
"# Generate initial seed using a flat distribution\n",
"p0 = mcmc_utils.flat_seed(\n",
" llh_paramset, nwalkers=nwalkers\n",
")\n",
"\n",
"# Run the MCMC!\n",
"# Progress bar provided by tqdm (this took about 30mins on my laptop)\n",
"samples = mcmc_utils.mcmc(\n",
" p0 = p0,\n",
" ln_prob = ln_prob_eval,\n",
" ndim = len(llh_paramset),\n",
" nwalkers = nwalkers,\n",
" burnin = burnin,\n",
" nsteps = nsteps,\n",
" threads = 4\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Visualization"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"One of the great advantages of Bayesian inferences is the access we have to the full posterior distributions. We can visualize the relationships between our model parameters by plotting the joint posterior distributions, as is done here using the [`getdist` package](https://getdist.readthedocs.io/en/latest/)."
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Removed no burn in\n"
]
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 864x864 with 21 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"import golemflavor.plot as plot_utils\n",
"# getdist package requires `%matplotlib inline` to come after the import for inline notebook figures.\n",
"%matplotlib inline\n",
"\n",
"plot_utils.plot_Tchain(samples, llh_paramset.labels, llh_paramset.ranges, llh_paramset.names)\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Here, the non-diagonal plots show joint distributions between two parameters, labelled on the x- and y-axis and the diagonal plots show the marginalised distributions for each parameter, as labelled on the x-axis. The blue (light blue) shows the 90% (99%) credibility intervals.\n",
"\n",
"As we did in the previous example, we can also see how this looks in a ternary plot."
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"source_angles = samples[:,-2:]\n",
"source_compositions = np.array(\n",
" list(map(angles_to_fr, source_angles))\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 864x864 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"nbins = 25\n",
"fontsize = 23\n",
"\n",
"# Figure\n",
"fig = plt.figure(figsize=(12, 12))\n",
"\n",
"# Axis\n",
"ax = fig.add_subplot(111)\n",
"ax_labels = [\n",
" r'$\\nu_e\\:\\:{\\rm fraction}\\:\\left( f_{e,S}\\right)$',\n",
" r'$\\nu_\\mu\\:\\:{\\rm fraction}\\:\\left( f_{\\mu,S}\\right)$',\n",
" r'$\\nu_\\tau\\:\\:{\\rm fraction}\\:\\left( f_{\\tau,S}\\right)$'\n",
"]\n",
"tax = plot_utils.get_tax(ax, scale=nbins, ax_labels=ax_labels, rot_ax_labels=True)\n",
"\n",
"# Plot source composition posteriors\n",
"coverages = [(99, 'cornflowerblue'), (90, 'royalblue')]\n",
"for cov, color in coverages:\n",
" plot_utils.flavor_contour(\n",
" frs=source_compositions,\n",
" fill=True,\n",
" ax=ax,\n",
" nbins=nbins,\n",
" coverage=cov,\n",
" linewidth=2.5,\n",
" color=color,\n",
" alpha=0.7,\n",
" oversample=5\n",
" )\n",
"\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Great! Looks like our inference of the source flavour composition reflects the injected value $(1:0:0)_S$. Here, the credbility regions include the effect of smearing as well as our uncertainity about the values of the mixing matrix, which is why the values are not exactly at the injected $(1:0:0)_S$ value.\n",
"\n",
"In a real analysis, an ensemble of nuisance parameters is usually required, related to uncertainties arising from things such as the astrophysical flux, detector calibration and backgrounds from atmospherically produced neutrinos. All these effects come into play when making inferences and careful analysis must be done for each in order to minimize potential biases."
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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": "3.7.6"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
|