{ "cells": [ { "cell_type": "markdown", "metadata": { "id": "-a3a8SMUfffw" }, "source": [ "## Supervised learning and decoding with manifold GPLVMs\n", "_Kristopher T. Jensen (February, 2022); ktj21@cam.ac.uk_\n", "\n", "In this short example notebook, we fit mGPLVM as a _supervised_ learning model (based on Jensen, Kao, Tripodi & Hennequin, NeurIPS 2020).\n", "\n", "The general specification of mGPLVM is a latent variable model where the objective is to maximize the marginal likelihood:\n", "$$p(Y) = \\int p_{\\theta}(Y|Z) p(Z) dZ,$$\n", "where $p(Y|Z)$ is a Gaussian processes, $Y \\in \\mathbb{R}^{N \\times T}$ are neural recordings, and $Z \\in T^1$ are some latent variables on a circle (note that everything readily generalizes to higher-dimensional Euclidean and non-Euclidean manifolds).\n", "\n", "However, in the supervised setting, $p(Z)$ is a _delta function_ during training, and we can simply optimize the parameters $\\theta$ of the generative model $p_{\\theta}(Y_{train}|Z_{train})$ without worrying about inferring $Z$:\\\n", "$$\\theta^* = \\text{argmax}_\\theta \\left [ \\log p_{\\theta}(Y_{train}|Z_{train}) \\right ].$$\n", "\n", "After training, we need to perform inference on the _test data_ $Y^*$ to find the latent variables $Z^*$ given the training data $\\{ Y_{train}, Z_{train} \\}$.\n", "This takes the form\\\n", "$$p(Z^*|Y^*, \\{Y_{train}, Z_{train}\\}) \\propto p_{\\theta}(Y^* | Z^*, \\{Y_{train}, Z_{train}\\}) p(Z^*),$$\n", "where $p_{\\theta}(Y^* | Z^*, \\{Y_{train}, Z_{train}\\})$ is given by the standard predictive GP equations.\n", "This is of course difficult, and we resort to variational inference using the mGPLVM machinery, but now with frozen generative parameters $\\theta^*$.\n", "\n", "For the prior $p(Z^*)$ we have two main options:\\\n", "(i) we can assume a uniform, uninformative prior.\\\n", "(ii) we can fit the prior to the training data.\n", "The simplest approach here is to define an autoregressive prior that matches the distribution over displacements in the training data. For continuous processes with high temporal resolution, this can be a very strong and useful prior!\n", "\n", "See Jensen et al. (2020) for further details about the generative model and inference procedure. Further developments on auto-regressive priors and non-Gaussian noise models were presented at Cosyne 2021 but have not been published." ] }, { "cell_type": "markdown", "metadata": { "id": "6xTt6Pydj7dW" }, "source": [ "We start by installing the mGPLVM implementation used in Jensen et al. This is freely available, but the codebase is still under active development with ongoing work on various latent variable models (here we use the 'bGPFA' branch which is most up-to-date)." ] }, { "cell_type": "markdown", "metadata": { "id": "vXnQlLvokQXx" }, "source": [ "We proceed to load a few packages and set our random seed." ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "cellView": "form", "colab": { "base_uri": "https://localhost:8080/" }, "id": "JKaph-Wg0O08", "outputId": "31a100e2-236c-44ba-b28b-f70e63f2cb3f" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "loading\n" ] } ], "source": [ "#@title Load packages\n", "import time\n", "tic = time.time()\n", "import torch\n", "import mgplvm as mgp\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import pickle\n", "from sklearn.decomposition import FactorAnalysis\n", "from sklearn.linear_model import LinearRegression, Ridge, RidgeCV\n", "from scipy.interpolate import CubicSpline\n", "from scipy.ndimage import gaussian_filter1d\n", "from scipy.stats import binned_statistic, pearsonr, ttest_1samp\n", "plt.rcParams['font.size'] = 20\n", "plt.rcParams['axes.spines.right'] = False\n", "plt.rcParams['axes.spines.top'] = False\n", "device = mgp.utils.get_device() # use GPU if available, otherwise CPU" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "8zyPallQ-j6W", "outputId": "b01d0969-41f0-4bb2-de86-39b8ac216732" }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "seed = 0 #set the seed\n", "np.random.seed(seed)\n", "torch.manual_seed(seed)" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "cellView": "form", "id": "67KxbXh6doRm" }, "outputs": [], "source": [ "#@title Define plot functions\n", "\n", "def plot_activity_heatmap(Y):\n", " ### plot the activity of our neurons ###\n", " plt.figure(figsize = (12, 6))\n", " plt.imshow(Y[0, ...], cmap = 'Greys', aspect = 'auto', vmin = np.quantile(Y, 0.01), vmax = np.quantile(Y, 0.99))\n", " plt.xlabel('time')\n", " plt.ylabel('neuron')\n", " plt.title('Raw activity', fontsize = 25)\n", " plt.xticks([])\n", " plt.yticks([])\n", " plt.show()\n", "\n", "def plot_tuning_curves(fit_thetas, ys_noise, plot_thetas, ys, ys_lin, ys_bins, ys_gp, xs_bins):\n", " plt.figure(figsize = (5,3.0))\n", " plt.scatter(fit_thetas, ys_noise, color = \"k\", alpha = 0.2)\n", " plt.plot(plot_thetas, ys, 'k-')\n", " plt.plot(plot_thetas, ys_lin, 'b-')\n", " plt.plot(xs_bins, ys_bins, 'g-')\n", " plt.plot(plot_thetas, ys_gp, 'm-')\n", " plt.legend(['true', 'linear', 'binned', 'GP'], frameon = False, ncol = 2, loc = 'upper center', bbox_to_anchor = [0.5, 1.4])\n", " plt.xlim(-np.pi, np.pi)\n", " plt.xlabel('theta')\n", " plt.ylabel('activity')\n", " plt.yticks([])\n", " plt.xticks([-np.pi, 0, np.pi], [r'$-\\pi$', r'$0$', r'$\\pi$'])\n", " plt.show()\n", "\n", "def cb(mod, i, loss):\n", " \"\"\"here we construct an (optional) function that helps us keep track of the training\"\"\"\n", " if i in [0, 50, 100, 150, 300, 500, 1000, 1500, 1999]: #iterations to plot\n", " X = mod.lat_dist.prms[0].detach().cpu().numpy()[0, ...]\n", " X = X % (2*np.pi)\n", " plt.figure(figsize = (4,4))\n", " plt.xlim(0, 2*np.pi); plt.ylim(0, 2*np.pi)\n", " plt.xlabel(\"true latents\"); plt.ylabel(\"model latents\")\n", " plt.scatter(thetas_plot, X[:, 0], color = 'k')\n", " plt.title('iter = '+str(i))\n", " plt.show()\n", " print(mod.lat_dist.msg(Y, None, None) + mod.svgp.msg + mod.lprior.msg, loss/n_ts1)\n", "\n", "def plot_final_thetas(thetas2, thetas2_lin, thetas2_mgplvm):\n", " plt.figure()\n", " plt.scatter(thetas2, thetas2_lin, color = \"b\")\n", " plt.scatter(thetas2, thetas2_mgplvm, color = \"k\")\n", " plt.legend(['linear', 'mgplvm'], frameon = False, ncol = 2, loc = 'upper center', bbox_to_anchor = (0.5, 1.25))\n", " plt.xlabel('true theta')\n", " plt.ylabel('predicted theta')\n", " plt.show()\n", "\n", "def plot_final_errors(errs_lin, errs_mgplvm, bins):\n", " plt.figure()\n", " plt.hist(errs_lin, bins = bins, color = 'b', alpha = 0.2)\n", " plt.hist(errs_mgplvm, bins = bins, color = 'k', alpha = 0.2)\n", " plt.axvline(np.mean(errs_lin), color = 'b', lw = 3)\n", " plt.axvline(np.mean(errs_mgplvm), color = 'k', lw = 3)\n", " plt.xlabel('error')\n", " plt.ylabel('frequency')\n", " plt.legend(['linear', 'mgplvm'], frameon = False)\n", " plt.show()\n", "\n", "def plot_uncertainty_estimates(xs, errs_by_uncertainty):\n", " #xs, errs_by_uncertainty = xs**2, errs_by_uncertainty**2 #variances instead of stds\n", " plt.figure(figsize = (5,5))\n", " plt.scatter(xs, errs_by_uncertainty, color = \"k\")\n", " plt.plot([xs[0], xs[-1]], [xs[0], xs[-1]], \"k-\")\n", " plt.xlabel(\"uncertainty\")\n", " plt.ylabel(\"RMSE\")\n", " plt.xticks([0.15, 0.20, 0.25])\n", " plt.yticks([0.15, 0.20, 0.25])\n", " plt.show()" ] }, { "cell_type": "markdown", "metadata": { "id": "lPJDeNPFk2sr" }, "source": [ "In order to validate the method, we generate synthetic data from 40 neurons and 100 time points, assuming 'Gaussian bump'-like tuning curves and Gaussian noise.\n", "We use this fairly sparse dataset to illustrate the data efficiency of this approach, but it would of course also work with more data.\n", "We also note that the codebase readily allows for Poisson or negative binomial noise models." ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "AS020KtW0YIE", "outputId": "6837968f-1729-41a3-cf21-b3ab784ca744" }, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "### generate some synthetic data ###\n", "\n", "n_ts = 600 #total time points\n", "n_ts1 = 100 #training time points\n", "n_neurons = 40 #number of neurons\n", "\n", "thetas = np.zeros(n_ts) #generate a sequence of angles as an autoregressive process\n", "for i in range(1, n_ts):\n", " thetas[i] = (thetas[i-1] + np.random.normal()) % (2*np.pi)\n", "\n", "prefs = np.sort(np.random.uniform(0, 2*np.pi, n_neurons)) #preferred orientations\n", "deltas = prefs[:, None] - thetas[None, :] #difference from head direction\n", "gs = np.random.uniform(0.5, 1.5, n_neurons) #scale variables\n", "kappas = np.random.uniform(2, 4, n_neurons) #concentration parameters\n", "#generate activity\n", "Y = gs[:, None] * np.exp( kappas[:, None]*( np.cos(deltas) - 1 ) ) + np.random.normal(0, 0.5, (n_neurons, n_ts))\n", "Y = Y[None, ...]\n", "\n", "#split into train and test\n", "Y1 = Y[:, :, :n_ts1] #train\n", "thetas1 = thetas[:n_ts1]\n", "Y2 = Y[:, :, n_ts1:] #test\n", "\n", "### plot the training data we just generated ###\n", "plot_activity_heatmap(Y1)" ] }, { "cell_type": "markdown", "metadata": { "id": "_sZcDIaBizY7" }, "source": [ "In this next code snippet, we consider why fitting this GPLVM-based model might be a good idea.\n", "To do this, we consider an example neuron from above and try to approximate its tuning using three different approached.\n", "\n", "The first is by assuming linearity in $[\\cos\\theta, \\sin \\theta]$ which is what many linear decoders of angles do.\n", "However, this enforces a sinusoidal tuning curve which does not fit the data well.\n", "\n", "The second is to bin the data and construct an empirical tuning curve as the average activity in each bin (note that this corresponds to a Gaussian noise model, and we could equally well use non-Gaussian noise models).\n", "However, this requires us to specify _a priori_ what the resolution is, and it leads to non-intuitive discontinuities.\n", "This is the approach taken by many standard Bayesian decoders.\n", "In fact, this is equivalent to fitting a Gaussian Process with a kernel that is constant within each bin and discontinuous between bins.\n", "\n", "Alternatively, we can posit that the expected similarity of neural activity is not discrete but rather a function of distance on the circle.\n", "We do this by fitting a Gaussian process to the data with a kernel that ensures smoothness/continuity on the circle.\n", "Importantly, the length scale can now be learned directly from the data and there are no discontinuities.\n", "This is particularly important in the limited-data regime, and we see that this model fits the data better." ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "fTsiORPTMzDg", "outputId": "0f001aef-89d5-4b5b-a33c-03e85b3169de" }, "outputs": [ { "data": { "image/png": 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\n", 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plot_thetas = np.linspace(-np.pi, np.pi, 101) #values to use for plotting\n", "inds = np.arange(0, len(plot_thetas), 4) #only record a subset of angles\n", "\n", "for example in range(2):\n", " if example == 0: #single neuron\n", " ys = 1.4 * np.exp( 2.3*( np.cos(plot_thetas) - 1 ) ) #tuning curve\n", " ell = 1/np.sqrt(2.3)\n", " else:\n", " ys1 = 1.4 * np.exp( 4*( np.cos(plot_thetas + 0.5*np.pi) - 1 ) ) #tuning curve\n", " ys2 = 1.4 * np.exp( 4*( np.cos(plot_thetas - 0.5*np.pi) - 1 ) ) #tuning curve\n", " ys = ys1+ys2\n", " ell = 1/np.sqrt(4)\n", "\n", " ys_noise = (ys + np.random.normal(0, 0.3, len(plot_thetas)))[inds] #noisy data\n", " fit_thetas = plot_thetas[inds] #supervised angles for our noisy data\n", "\n", " ### fit the linear model ###\n", " cs_plot = np.array([np.cos(plot_thetas), np.sin(plot_thetas)]).T #cos/sin\n", " cs_fit = cs_plot[inds, :] #for our noisy data data\n", " clf_single = RidgeCV(alphas=10**np.linspace(-5,5,51)).fit(cs_fit, ys_noise[:, None]) #crossvalidated ridge regression\n", " ys_lin = clf_single.predict(cs_plot) #fitted tuning curve\n", "\n", " ### binned decoder ###\n", " bins = np.linspace(-np.pi, np.pi, 11) #assume 11 bins for now\n", " ys_bins = binned_statistic(fit_thetas, ys_noise, bins = bins)[0] #activity in each bin\n", " ys_bins = np.repeat(ys_bins, 2) #expand for plotting\n", " xs_bins = np.repeat(bins, 2)[1:-1] #expand for plotting\n", "\n", " ### fit out GP-based model ###\n", " def K(x1, x2, ell = 0.75, sig = 0.3):\n", " '''for illustration purposes, we pick some reasonable parameters but these could be learned from data'''\n", " Kmat = np.exp( (np.cos(x1[:, None] - x2[None, :]) - 1) / (2*ell**2) )\n", " if (sig > 0) and (x1.shape == x2.shape): Kmat += sig*np.eye(len(fit_thetas))\n", " return Kmat\n", " #GP inference\n", " ys_gp = K(plot_thetas, fit_thetas, sig = 0, ell = ell) @ np.linalg.inv(K(fit_thetas, fit_thetas, ell = ell)) @ ys_noise\n", " ys_gp = ys_gp.flatten()\n", "\n", " ### plot result ###\n", " plot_tuning_curves(fit_thetas, ys_noise, plot_thetas, ys, ys_lin, ys_bins, ys_gp, xs_bins)\n" ] }, { "cell_type": "markdown", "metadata": { "id": "v1D9DB7EmLrd" }, "source": [ "Having gained some intuition for the benefits of Gaussian process-based models, we are ready to construct our full mGPLVM for decoding. In the following code snippet, we set a couple of model parameters relating to the optimization process and initialization. Most of the initialization is done directly from the data, but it can be useful to include if we have prior knowledge about e.g. the timescale of the behavior we care about." ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "id": "FYvLxtgB4yM8" }, "outputs": [], "source": [ "### set some parameters for fitting ###\n", "max_steps = 1001 # number of training iterations\n", "n_mc = 1 # number of monte carlo samples per iteration (since the latents are a delta function, we only need 1)\n", "print_every = 100 # how often we print training progress\n", "d_latent = 1 # specify the dimensionality of the space\n", "n_z = 10 #number of inducing points; performance increases with more inducing points" ] }, { "cell_type": "markdown", "metadata": { "id": "fuqWNwvcmcVD" }, "source": [ "Having specified our parameters, we can construct the mGPLVM model.\n", "In this particular library, we need to separately specify (i) the noise model, (ii) the latent manifold (see Jensen et al. 2020 for various manifolds), (iii) the prior and variational distribution, and (iv) the GP kernel.\n", "\n", "For this dataset we use a Gaussian noise model, but we can easily swap in a count-based model.\n", "Note how we set the latent distribution to be centered at the ground truth thetas and have a very small standard deviation (1e-5; effectively a delta function)." ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "id": "xMuXfgUA5I2Y" }, "outputs": [], "source": [ "### construct the actual model ###\n", "n_trials, n_neurons, n_ts1 = Y1.shape\n", "data1 = torch.Tensor(Y1).to(device)\n", "\n", "manif = mgp.manifolds.Torus(n_ts1, d_latent) # our latent variables live on a ring (see Jensen et al. 2020 for alternatives)\n", "likelihood = mgp.likelihoods.Gaussian(n_neurons, Y = Y1, d = d_latent) #Gaussian noise\n", "mu = thetas1[None, :, None] #ground truth thetas for training\n", "lat_dist = mgp.rdist.ReLie(manif, n_ts1, n_trials, sigma = 1e-5, diagonal = True, mu = mu) #latent distribution\n", "\n", "lprior = mgp.lpriors.Uniform(manif) #note that we could also learn the generative parameters of a parametric prior\n", "kernel = mgp.kernels.QuadExp(n_neurons, manif.distance, Y = Y1, ell = np.ones(n_neurons)*1, scale = 0.7*np.ones(n_neurons)) #squared exponential kernel\n", "z = manif.inducing_points(n_neurons, n_z) #inducing points\n", "mod = mgp.models.SvgpLvm(n_neurons, n_ts1, n_trials, z, kernel, likelihood, lat_dist, lprior).to(device) #construct model" ] }, { "cell_type": "markdown", "metadata": { "id": "2i0UrqCRGZ_k" }, "source": [ "We are now ready to actually learn the generative parameters!" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 1000 }, "id": "hjdmKtGy5c-Z", "outputId": "898e6e73-47b8-494d-8ed7-ef7c35b784c8" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "fitting 40 neurons and 100 time bins for 1001 iterations\n", "iter 0 | elbo -3.913 | kl 0.298 | loss 3.913 | |mu| 3.944 | sig 0.000 | scale 0.700 | ell 1.000 | lik_sig 0.836 |\n" ] }, { "data": { "image/png": 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\n", 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\n", 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\n", 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y27dv3ytNf38/S5cu9TqXCpIEmCMblgvnUqBUa9GmTZuYNGkS/f39bN68mYGBAZYsWeKBpUpVBxgzK11OdK4DlJtuYceOHUydOpWNGze2IGftzcciua6Xy+WYO3du2YmiKlX2utIST5kp6V2SviHpXkm/LTh+jKRLJb1iopmSNEeSRdsHJno95+LkF0QrF1zAW4tqlWQskggz3M2ODj0HvKggyZOERdcEfKnWDEk6Aria0LFvaq3Xca6SXC5XcXJu8NaiiUhSghkizLl7DXAw8OXCk2b2OHAH8M5aMxMFsWsIs+OtqPU6zlWSy+WYPXt2xXT9/f3eQ3cCktTBXATcC3zQzExSqcVefgO8fQL5uQQ4E5ge7Z2ru1wux5w5c8qmyWQyHbUIfaskKcG8FrjNyq81+wRwaC0ZkXQM8EVgqZn9pJZrOFeNiy++OHYxtDwPLvWRJMDsBPavkOYVhLqTRCT1AmsI88x8IsH75ktaJ2ndhg0bkn6s6zL5KS6ffbb80l1Tp0714FInSR6R7gemS1KpUoyk/QmPNb+sIR+fAt4AvMXMnqv2TWa2ClgFMG3atPJ/klxXq2ZZkbwVK7z6r16SlGDWAEcDV0ra632SMsAVwOGElqaqSTqJUGr5BzO7M8l7natWNcuKACxcuNBLL3WUJMCsBH5EqIh9BHgfgKTrgDFgAfA9M8tVe8GCR6NfA59MkBfnqpJ/LIobsFhoxowZXTv7f8OYWdUb4ZFqMbABGC/YNhNGWfcmvN6BhMGR1WxXlbvWCSecYM4VGhkZsb6+vorfrUwmYwsXLmx1dttZ7O9loqECZrYTWCzpM8BrgH5gK/CAmZXvClnaC8D/ijn3RkK9zE8JE4z745OrWjXd//v6+ryPS4Ml6ck7AGwxs6fMzAi/9MVpDgAOMrOqBm5YqNAtORRA0mJCgFltZv9cbT6dGxoaYsWKFWWborPZrI+KboIkJZiHCY9HnyuT5hLgs4SlTZxrulwuV1VwGR0dbV6muliSSl5Fm3OpNTw8XDa4+Lii5ko8mrqClwLlezFVycwWm5n88chVY2hoiN7e3rKtRZlMxutcmqzsI5KkC4oOHV/iGIRHogHCYMj/qFPenKvK0NBQxVHRkrz7fwuoXHFS0jihKa/idaL9NuA8a8HibNOmTbN169Y1+2NdCvT29pZtLZLEggULvI9L48RWnVSq5H1/wQW+Slib+rsl0u0iTLFwp5ltSZ4/55KbOXMma9euLZvGW4taq2yAMbPV+X9LmgvcYGZfa3iunKugmuCSyWS8tajFkkz6fUYjM+JcEpWCC8D8+fObkBNXTr1bkZxrqPzYonIymQwLFy70OpcUSDRUQNIUwtSZbyfM/bJfiWRmZkfVIW/O7aWaHroAO3fubFKOXCVJhgocSBgX9DrgKeDFhHFIk9kz+fdjwI76ZtG56nroQhgR7dIjySPS5YTgchFwUHTsSsLM/6cCvwAeAo6pZwadg8o9dCEEl1tuuaVJOXLVSBJgzgV+YmbXWMH/dDRc+2fAOYQJqYbrnEfnyi58ls1mMTMPLimUJMAcQSil5I1TUAdjZk8APwD+sj5Zc26PuIXPJPnYohRLEmC2ETrU5W0FXlaU5o+Eyl/nJiTfWtTT08Pg4CDnnHMOfX19e6XJ99D1TnTplSTAPEIoxeTdD7w1mo837y3A4/XImOte+Qm6x8bGMDPGxsZYvXo1c+fOJZvNIolsNsuaNWu8KTrlkjRT/xj4rwWrCnwT+Efg+5JuJCyWdjJQeS1O58ooNUH3tm3buOmmm7xnbptJEmBWE5qkX0kozawgLFPyHuCsKM0dhNYm52oWV6FbrqLXpVPVj0hm9gszW2hmj0Svd5rZecCJhBUGTgFO98GOrhaFdS49PaW/lnEVvS69EvXkLcXM7gburkNeXJcqXhSt1NQLPhNde/KxSK6l8rP/l1oULZPJ7K7Q9Zno2lNsCUbSp2q8pplZuYnBnQP2lFziJosaHx9nfHy8ybly9RQ7o100m10tzMyavqqAz2jXfiqtuOiz/7eNmma08/lfXN3lcjmGh4dZv369z/7fBWIDjJn9uJkZcZ2vuDI3js/+3zm8ktc1TakOdMX6+vp89v8O4gHGNU25jnLeWtSZJtwPxrlK8vUucXUuXpnbuTzAuIaqVO/ilbmdzR+RXEOVq3fxR6LO5yUY11Bx9S6S/LGoC3gJxjVU3ABFH7jYHTzAuIZasmTJPjPReb1L9yg3FumrNV7TzOyiGt/r2lRhD92BgYHd60Hn61dKnXOdz8ciuQkr1VLU19fnFbjdI3YsUrkAk63108wsfgRbg3iAaZ24QYvev6VrJB/s2Iog4dpLLpdj0aJFbNq0qeR5n+LSeTO1q0kul2PevHls3749No23FLnErUiS3iXpG5LulfTbguPHSLpUkq+L1AWGh4fLBhdvKXKQIMAoWA3cAJwPHAUcWZDkSeALwOx6ZtClS35y7nITRQFeweuAZCWYIWAOcA1wMPDlwpNm9jhh2ZJ31i13LlWGhoaYM2dOxeCSzWY9uDggWYC5CLgX+KCZbQVKNT/9hr1LNa5D5HI5li9fXnYWOoBJkyb5o5HbLUmAeS1wm5X/hj0BHDqxLLm0yeVyXHDBBRXT9ff3c80113jpxe2WpBVpJ7B/hTSvAJ6pPTsubfKd6MrN7u/9XVycJCWY+4Hpkkp2qpG0P2Ep2V/WI2MuHaqZ5tIfiVycJAFmDXA0cKWkvd4nKQNcARwOXFu33LmWq9RZbsqUKf5I5GIlCTArgR8BlwCPENajRtJ1wBiwAPiemeXqnUnXOuU6y02aNImVK1c2MTeu3VQdYMxsF/DnwGeBycBrCGMQzgP6gM8R+se4DlJqugXwCl1XnUQ9ec1sp5ktBg4DjgHeAhwHHGpmnzaznfXPomulWbNmsWrVKrLZ7O6Z/0dGRti4caMHF1dR7GjqduOjqZ1rmdjR1D6jnXOuYcrNaHdrjdc0M5tR43udcx2kXEe76THHjdJFovzxznjmcs5NWOwjkpn1FG6EXrzfAx4G3k8Yc/SiaD8P+B3wXSr39nXOdYkkdTCfBKYB08xstZmNmdkL0f5a4E3ASVE6l2L5KRd6enoYHBwkl/OuS64xkgSYWcD1Zral1Ekz2wxch88Hk2r5sUVjY2OYGWNjY8yfP9+DjGuIJAHmcCB+CrNgB/Dy2rPjGq3U2KJt27YxPDzcohy5TpYkwPweeLekyaVOStoPeDfwaJIMSOqX9AFJ35H0W0nPSdoq6aeSLioe9+QmJm5skU/Q7RohyS/vauDVwK2S3hoNcERSRtLpwFrgVSQf7Hg+8E+EOpyfA1cB1wPHAv8MfCtuBLerTmGdS09P6f9yn6DbNUKS+WC+CJwAnAvcBoxL2kyYPrOH0ET9vShdEr+Orvl9M9s96YikTwB3AX9BGO90fcLrOvZdFG3Xrl37pPEJul2jJBnsuMPM3kOoxL0V2EoILlsJpZdZZvaepOORzOxWM7uxMLhExx8HVkQvpye5ptsjbj6XTCaze2yRT9DtGiXxukhm9nXg6w3ISyk7or0PoqxRXN3K+Ph42VnqnKuH1FagSuoF8hPB/rCVeWlncXUrXufimqGWhdcGJF0u6XpJayX9a/S65rWsY3yRUNF7k5ndHJOX+ZLWSVq3YcOGOn98Zyg1n4vXubimMbOqN+CDwHPALmC8aHseuDjJ9cp8ziWEMU3/CRxczXtOOOEEc6WNjIxYNps1SZbNZm1kZKTVWXKdJfb3sur5YCTNIEyZ+TTwj4SK3j8QOtadGQWFqcDbzWxtrQFP0oeArxAmGZ9hobK3Ip8PxrmWie1GkqSS96OE4HKCmT1UcPxB4PZoWdm7o3Q1BRhJHwauBO4jBJcnarmOcy4dktTBnAR8qyi47BYd/3aULjFJlxGCyz3AGR5cquMDF12aJSnBvAjYWCHNhihdIpI+SZhM/G7gLAsDJ10FQ0NDrFixYvdyrvmBi4D3a3GpkKQO5gFgi5mdXCbNnYRK2ddWnQFpLmF4wS7gakLHvWKjFqaEiNVtdTC5XI45c+aUXCvaV1p0TVaXOpjvAJdKWgZ8wgqmbZD0EkIJ5CTg7xNm7shonwE+HJPmx/iCbnsZHh6OXYjeBy66tEhSgnkxcCdhuZKngXsJrUgvA44HDgAeAE42s6cakdlyuq0E09PTExtgvATjmmziqwpEQeNUwsjnDGFNpPOB06LX/wS8uRXBpRvF9cSV5J3oXGokXXhtq5ldDBwI/CkhuPwpcJCZXWxmT9Y/i65US1GpHrqSWLBggVfwutSoaSyShRUe7zOzO6L9jsrvcrWIm+IS2GfFxTVr1rBs2bIW59i5PXxlx5QbHBxkbGxsn+Nez+JSpC6tSEh6JfA3hErdVwKTSiQzMzsqyXVdPJ/i0rWzqgOMpOnATYR1j3YCf6T0PC0+vWUdDQwMlCzB+HQLrh0kqYP5e0Jr0QXA/mZ2hJkdWWprTFa7k0+34NpZkgBzHPAvZjZiRdNbusaZNWvWPpW5PsWlaxdJAsyTgI8RapBygxZnzZrF6Ogo4+PjjI6OenBxbSNJJe+/Aac3KiPdrHjmfx+06DpFkqEChwA/A24GLjWzZxuZsaTauZnam6Jdm5t4M7WZbZR0NmFxtAsk/ZrSI5/NzGYkz2P38qZo16mSNFO/nrDg2kHRoTfEJO2MnntN5E3RrlMlqeS9AugHPgVkgUlm1lNiyzQkpx2i2nFF3hTtOkGSAHMK8K9m9nkze8TM9l2D1JWVy+WYN2/eXuOK5s2bB+w7rsibol0nSFLJuxG4xsw+2tgs1aYdKnmnTp3Ks8/uWzfe39/Pxo2VZiN1LrUmPh8McDs1TujtQumlVHAB2LRpU5Nz41xzJAkwlwKvk/QxST7eKKHh4eFWZ8G5pkvS0e5ywnpFS4APSrqH+Gbqi+qQt45Srsm5v7+/iTlxrnmSBJgLC/59JHsm6y5mgAcYwmPR8PAw69evp6enh127SteLL126tMk5c645kgQYHyWdQHH3/1LBxae4dJ0uSU/efXuCuX3kSy2lOs4BZDIZxsfHGRgYYMmSJR5cXEdLNKOdK6+41FLK+Pg44+M+24XrDh5g6iSXyzF37tzYepY87/7vuklNqwq4vQ0NDTF79uyKwcW7/7tu4wFmgnK5HMuXL6+Yzrv/u27kj0gTVKkDXV9fnwcW17W8BDMBuVwutrUoz4OL62YeYGqUbzEqp7+/34OL62oeYBLK5XIccsghzJ49u2xzdG9vr/fQdV3P62ASyOVyzJ49u2K6/v5+li5d6qUX1/U8wFSp2uDiE3U7t4c/IlUhPxNdJd7Pxbm9eQmmglwuxwUXXFCxe38mk/EWI+eKeAmmjHxLUTVjh1avXu3BxbkiXoKJUe3YIoAZM2Z4cHGuBC/BlDBz5syqxhYBLFy4kFtuuaUJuXKu/XgJpsjQ0BBr166tmG7SpElcc801XnJxrgwvwRRZtWpVxTT9/f0eXJyrgpdgipR7LMpkMl6Z61wCXoIpksnEr3zrwcW5ZDzAFIkbwOgtRc4l5wGmyLJly1i4cOHukkwmk/GWIudqVPXa1GnXDmtTO9eh6rI2dcfI5XIMDg7S09PD4OAguVyu1VlyriN1XStS8dIiY2Nju+tdvI7FufrqukekwcHBktNc+jQLztXMH5Hy4hahL7c4vXOuNl0XYOIWPvMF0Zyrv44PMENDQ/T29iKJ3t5eXv3qV9PX17dXGp8oyrnG6OgAM3PmTJYvX767+/+uXbtYu3Ytp5xyCtlsFkm+IJpzDdSxrUi5XC52VPTtt9/Ozp07m5wj57pPx5Zgyq24WM08L865ievYAFOuVajcgEbnXP2kJsBIeqWkr0p6TNILkkYlXSXpoFquV65VqNKKjM65+khFgJF0FHA38H7gLuBK4HfAIuBOSf1Jr7lkyZJ9WosgjIpetmzZxDLsnKtKKgIMsAw4DLjEzN5jZh8zszMJgea1QOI25FmzZrFq1aq9WotGRkZ8VLRzTdTyoQKSXgU8BIwCR5nZeMG5A4A/ELoiH2Zmz5a5jmWzWZYsWeJNzs41V6qHCpwZ7X9UGFwAzOxp4A6gDzi50oXyAxd9dLRz6ZCGAPPaaP/rmPO/ifavqeZi27ZtK9tE7ZxrnjR0tHtJtN8acz5//MDiE5LmA/s0CY2NjSHp7rrkzhU6BNjY6kx0uHa8xz80s7NLnUhDgKkk/3y3T2WRma0CVgFIWmdm05qZsW7j97jxOu0ep+ERKV9CeUnM+RcXpXPOtYk0BJgHo31cHcufRPu4OhrnXEqlIcDcFu3PkrRXfqJm6jcDzwE/q3Cdyksyuonye9x4HXWPWx5gzOwh4EfAIPChotOfAaYAXyvXBya6Tkf9x6SR3+PG67R73PKOdrB7qMC/E3rzfhf4T+BNwBmER6NTzWxT63LonKtFKgIMgKQjgM8CZwP9hB68NwCfMbPNLcyac65GqQkwzrnO0/I6mFLqNXVDvaeA6ASS+iV9QNJ3JP1W0nOStkr6qaSLiivaK1xrVJLFbI838udIu3rem3b+Hqeuo12J+pgHgJMIUzecLenN1dTH1Os6Heh8YDnhEfQ2YD3wUuA84J+Bd0g636ov2m4Fripx/JmJZ7XtTfjetP332MxStQE3E3rt/nXR8Sui4yuaeZ1O2wiDS98F9BQdfxkh2BjwF1VeaxQYbfXPlMatXvem3b/HqaqDqePUDXW5TreR9AnC3DtfMbO/riL9KICZDTY2Z+2nHvemE77HaauDqdfUDXWbAqLL7Ij2SZZc2E/SbEmfkLRI0hmSfNLjYKL3pu2/x2kLMPWauqGuU0B0A0m9wAXRyx8meOvLgDWEks9VwK3AbySdXtcMtqeJ3pu2/x6nLcDUPHVDg67TTb4IHAvcZGY3V/mea4AZhF+kKcBxwEpCr+wfSPqzBuSzXdTj3rT99zh1rUgVxE7d0KLrdARJlwB/S2ihmFPt+8zsM0WH7gMWSHomut5i4L11ymZbadK9Sf33OG0lmHpN3eBTQFRJ0oeApcD9wBlWn17TK6L9W+twrU6T5N60/fc4bQGmXlM3+BQQVZD0YeArhL+uZ5hZvTrHPRHtp9Tpep0kyb1p++9x2gJMvaZuqNd1OpakywjLwtxDCC5PlH9HIqdE+9/V8ZqdIsm9afvvcaoCjCWcukHSJElHR70da75Ot5H0SUKl7t3ADDOLnQM27h5Ler2kg0ukzxJKRQAjdcx220h6bzr5e5yqjnaQbOoGSYPAw8BYcYcmnwKiNElzgWuBXcDVlH5+HzWza6P0g5S4x5IWAx8j/JV9GHgaOAp4J7A/cBPwXjPb3pAfJMWS3puO/h63uitxTPfoIwjNfH8AtgNjhIrIg4vSDRJq0Et2ya72Ot20EVovrMJ2e6V7DJwO/Auh5WkLoZPeBuB/E/rTqNU/awvvcaJ708nf49SVYJxznSNVdTDOuc7iAcY51zAeYJxzDeMBxjnXMB5gnHMN4wHGOdcwHmCccw3jAcY1lKQLo5n0L2x1XlzzeYBJOUmD0S/ota3OSytJWhzdh+ndnId24wHGOdcwHmCccw3jASbFolG5D0cv5xatDnhhlGZ69HqxpJMkfV/S5ujYYJTGJN0e8xnXFqYtOvcmSddJelzSdkmPSFop6fA6/GxnSFol6X5JTymsMHmfpE9L2r8o7Sjw6ejlbYX3oShdn6SPS7pH0rOSnpF0p6T3lfj8wvt2fHTftkjaJunHkk5NmgdJL5X0ZUkPRp+/Jfr3tQpLkHSddpuTt9vcTpjQeRFwL3BDwbl7itKeAnwc+CnwVeAQwsjbmkh6P/BPwAvA94BHCDOofQB4l6STzWx9rdcHLgOOJkxF8H3CNAZvJoz2ni5pppntitJeBbyHMEp5NWGdoOL8HkiYtf8NwC8I96AHeDvwdUmvN7PLS+RjGnApcCdhZcsB4C+AtZKON7P8rHJl8yCpj7CMyFGEUdM3EubMzQLvBq6jGyfgavVwbt/Kb+wZyn9tzPnp7Jlm4eKYNHtNwVB07tro/GDBsdcQgtNvgVcUpT+TMJfMd6rM/4XR9S8sOv4qSkzpAHwuSv/fio4vjo5Pr/BzXFp0fH/CMizjwPEx9604bxdHx5dVmwfCapkGXFni3GTggFZ/l1qx+SNS57jHzFbW6VoLgUnAIjN7tPCEmd1KKNG8K5q2sSZm9juLfvuKXBXt317ttST1A7OBdWb290Wf8zyhtCTgr0q8/Q6LJtcq8FXC4nMnVZuHAs8VHzCz7RYWSus6/ojUOe6q47Xy88aeLunEEucPAzKEks7dtXyApCmER7/3Rtc5gD3LcAC8IsHlTozyY1G9VbFJ0f6YEufWFR8wsx2S/ggclCAPPwYeBT4m6Y2EWevuIAT+XWXf2cE8wHSOeq0IANAf7T9aId3UWi4uaRKhvuQkwooG3yTM+JZfuvbTwH4JLpnP74nRFqdUfrfEpN1JCFpVMbOnJJ1MmCv3XPaUwDZKWgZ83sx2xF6gQ3mA6RzlpiY04v+vDyxxbPd6PGb21EQyFePdhOCy2swuLDwh6eXsaa2pVj6/V5rZRyaevdqY2e+BiyQJeB2hvupDwKcIFc6fbFXeWsXrYNIvX7yeyILyTxLmdd2LwkLsx5dIn18G47QJfGY5r47215c4F7duc7n7cBehErdR+a0mD7tZ8Cszuxp4W3T4PY3MWFp5gEm/JwklkIEJXOMuYEDSWUXHLyc0oxb7CuFx5UpJ+yz6JWmypIn8Mo9G++lF130V8KWY9+Rnzt/nPlhY0ykHTJP0SUn7lNYkHSXpyFozXCkPko4t1ZcIeGm03zbBz25L/oiUcmb2jKSfA6dJyhGWqtgFfM/M/l+Vl/kyoU7gu5K+CWwGTgWOJPS1mV70mQ9ImkdoTfmVpB9GnzuJ8Mt1GqHO5Ogaf6wbCU3gH5F0HPDL6Lp/TugTUyqY3kYopfydpGMJgRcz+3x0/r8T+ul8Fpgj6afAH4HDCZW7JwLvY0/HxVqUy8NM4ApJ/05YTeAJ4JWEx8Fx4H9O4HPbV6vbyX2rvBEeKW4k/AUdp6DvBnv6cyyucI1zCS0mz0fX+Qah9HItRf1gCt5zXHR+jNDhbjOhUnYlcGaVeb+Q0n1NjiCUOh4lNO3+itDhrZeYfjuEpuh7ovQWvr57nZ9MCDT/TqiXeQFYD6wFPgz0F6Qte98IpazRavNACGJXRPd4Q/TZo4QOdqe2+jvUqs2XLXHONYzXwTjnGsYDjHOuYTzAOOcaxgOMc65hPMA45xrGA4xzrmE8wDjnGsYDjHOuYTzAOOca5v8D9dG9vzhw5QEAAAAASUVORK5CYII=\n", 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\n", 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ " |mu| 3.944 | sig 0.000 | scale 0.517 | ell 1.287 | lik_sig 0.496 | 43.275065719273954\n", "iter 550 | elbo -0.784 | kl 0.295 | loss 1.079 | |mu| 3.944 | sig 0.000 | scale 0.511 | ell 1.277 | lik_sig 0.496 |\n", "iter 600 | elbo -0.784 | kl 0.302 | loss 1.085 | |mu| 3.944 | sig 0.000 | scale 0.506 | ell 1.267 | lik_sig 0.496 |\n", "iter 650 | elbo -0.783 | kl 0.300 | loss 1.083 | |mu| 3.944 | sig 0.000 | scale 0.501 | ell 1.258 | lik_sig 0.496 |\n", "iter 700 | elbo -0.783 | kl 0.296 | loss 1.079 | |mu| 3.944 | sig 0.000 | scale 0.496 | ell 1.248 | lik_sig 0.495 |\n", "iter 750 | elbo -0.783 | kl 0.297 | loss 1.080 | |mu| 3.944 | sig 0.000 | scale 0.492 | ell 1.237 | lik_sig 0.495 |\n", "iter 800 | elbo -0.783 | kl 0.300 | loss 1.083 | |mu| 3.944 | sig 0.000 | scale 0.488 | ell 1.225 | lik_sig 0.495 |\n", "iter 850 | elbo -0.783 | kl 0.297 | loss 1.080 | |mu| 3.944 | sig 0.000 | scale 0.484 | ell 1.212 | lik_sig 0.495 |\n", "iter 900 | elbo -0.783 | kl 0.298 | loss 1.081 | |mu| 3.944 | sig 0.000 | scale 0.480 | ell 1.201 | lik_sig 0.495 |\n", "iter 950 | elbo -0.782 | kl 0.298 | loss 1.080 | |mu| 3.944 | sig 0.000 | scale 0.476 | ell 1.189 | lik_sig 0.495 |\n", "iter 1000 | elbo -0.782 | kl 0.301 | loss 1.083 | |mu| 3.944 | sig 0.000 | scale 0.473 | ell 1.178 | lik_sig 0.495 |\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ " |mu| 3.944 | sig 0.000 | scale 0.473 | ell 1.178 | lik_sig 0.495 | 43.314183433002384\n" ] } ], "source": [ "t0 = time.time()\n", "thetas_plot = thetas1\n", "\n", "#note that the 'mask_Ts' function is a mask applied to the gradients for the variational distribution\n", "#by setting these gradients to zero, we are imposing the ground truth latents and doing supervised training\n", "train_params = mgp.crossval.training_params(max_steps = max_steps, n_mc = n_mc, lrate = 5e-2, callback = cb, burnin = 50, mask_Ts = (lambda x: x*0))\n", "print('fitting', n_neurons, 'neurons and', n_ts1, 'time bins for', max_steps, 'iterations')\n", "mod_train = mgp.crossval.train_model(mod, data1, train_params)" ] }, { "cell_type": "markdown", "metadata": { "id": "deiX8wX6G806" }, "source": [ "We proceed to train a simple linear model which we will use as a baseline.\n", "We also use the predictions of the linear model for initialization." ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "QKbTdsj19XxL", "outputId": "6efd945a-e5d7-4d51-fa33-4e28e8029a39" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(1, 40, 100) (100, 2)\n" ] } ], "source": [ "## first fit a linear model (we will use this for initialization and comparison) ##\n", "Y2 = Y[..., n_ts1:] #test data\n", "thetas2 = thetas[n_ts1:] #true test angles\n", "Z1 = np.array([np.cos(thetas1), np.sin(thetas1)]).T #true training cos/sin\n", "Z2 = np.array([np.cos(thetas2), np.sin(thetas2)]).T #true test cos/sin\n", "print(Y1.shape, Z1.shape)\n", "\n", "alphas = 10**(np.linspace(-4, 4, 51)) #possible regularization strengths\n", "clf = RidgeCV(alphas=alphas).fit(Y1[0, ...].T, Z1) #crossvalidated ridge regression\n", "Z2_pred = clf.predict(Y2[0, ...].T) #predict test data\n", "Z2_pred = Z2_pred / np.sqrt(np.sum(Z2_pred**2, axis = 1, keepdims = True)) #normalize\n", "thetas2_lin = (np.sign(Z2_pred[:, 1]) * np.arccos(Z2_pred[:, 0])) % (2*np.pi) #predicted angles" ] }, { "cell_type": "markdown", "metadata": { "id": "fvof3UXOsmdP" }, "source": [ "We're now ready for the prediction step.\n", "Here we copy over all parameters from our previous model apart from the variational distribution which we define anew." ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "DDKw4Dcl9AZo", "outputId": "50ace52f-3df3-4f87-f130-a6ac7369cdaa" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1.0123699125250345\n" ] } ], "source": [ "### now we want to do decoding ###\n", "_, _, n_ts2 = Y2.shape\n", "manif2 = mgp.manifolds.Torus(n_ts2, d_latent) # latent manifold is still a circle\n", "\n", "#compute displacements to use a better prior\n", "displacements = thetas1[1:] - thetas1[:-1]\n", "displacements[displacements < -np.pi] += 2*np.pi\n", "displacements[displacements > np.pi] -= 2*np.pi\n", "print(np.std(displacements)) #matches generative process\n", "\n", "mu2 = thetas2_lin[None, :, None] #initialize from linear prediction\n", "\n", "#lprior2 = mgp.lpriors.Uniform(manif2) #uniform prior\n", "#let's assume some degree of continuity in the data\n", "lprior2 = mgp.lpriors.Brownian(manif2, fixed_brownian_c = True, fixed_brownian_eta = True,\n", " brownian_eta = torch.ones(d_latent) * np.var(displacements))\n", "\n", "lat_dist2 = mgp.rdist.ReLie(manif2, n_ts2, n_trials, sigma = 0.5, diagonal = True, mu = mu2) #variational distribution\n" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "cellView": "form", "id": "NFvYWVIjf3Ta" }, "outputs": [], "source": [ "#@title Construct inference model\n", "data2 = torch.Tensor(Y2).to(device) #put data on device\n", "mod2 = mgp.models.SvgpLvm(n_neurons, n_ts2, n_trials, z.cpu(), kernel.cpu(), likelihood.cpu(), lat_dist2, lprior2).to(device) #use old generative model and new variational distribution\n", "for p in mod2.parameters(): #no gradients for generative parameters\n", " p.requires_grad = False\n", "for p in mod2.lat_dist.parameters(): #only inference\n", " p.requires_grad = True\n", "#copy over tuning curves (this summarizes p(Y*|Z*, {Y, Z}) from the training data in the SVGP framework)\n", "mod2.svgp.q_mu[...] = mod.svgp.q_mu[...].detach()\n", "mod2.svgp.q_sqrt[...] = mod.svgp.q_sqrt[...].detach()" ] }, { "cell_type": "markdown", "metadata": { "id": "oFBOXxO4ytlq" }, "source": [ "Finally we infer our new latents using the mGPLVM machinery!" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 1000 }, "id": "_KU1T_LpWP24", "outputId": "32ec4861-3df9-4515-eed5-6fc26113dd35" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "fitting 40 neurons and 500 time bins for 1001 iterations\n", "iter 0 | elbo -0.896 | kl 0.024 | loss 0.896 | |mu| 3.670 | sig 0.500 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ " |mu| 3.670 | sig 0.500 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 | 179.19064879098534\n", "iter 10 | elbo -0.871 | kl 0.025 | loss 0.896 | |mu| 3.669 | sig 0.445 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 20 | elbo -0.851 | kl 0.026 | loss 0.877 | |mu| 3.673 | sig 0.384 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 30 | elbo -0.839 | kl 0.028 | loss 0.867 | |mu| 3.679 | sig 0.335 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 40 | elbo -0.828 | kl 0.031 | loss 0.859 | |mu| 3.683 | sig 0.295 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 50 | elbo -0.820 | kl 0.034 | loss 0.854 | |mu| 3.686 | sig 0.265 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ " |mu| 3.686 | sig 0.265 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 | 170.80025111998782\n", "iter 60 | elbo -0.816 | kl 0.035 | loss 0.851 | |mu| 3.685 | sig 0.242 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 70 | elbo -0.812 | kl 0.037 | loss 0.849 | |mu| 3.684 | sig 0.225 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 80 | elbo -0.810 | kl 0.039 | loss 0.848 | |mu| 3.684 | sig 0.212 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 90 | elbo -0.807 | kl 0.040 | loss 0.847 | |mu| 3.687 | sig 0.202 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 100 | elbo -0.806 | kl 0.041 | loss 0.847 | |mu| 3.686 | sig 0.193 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ " |mu| 3.686 | sig 0.193 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 | 169.3359999584735\n", "iter 110 | elbo -0.804 | kl 0.042 | loss 0.846 | |mu| 3.687 | sig 0.186 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 120 | elbo -0.804 | kl 0.042 | loss 0.846 | |mu| 3.685 | sig 0.181 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 130 | elbo -0.803 | kl 0.043 | loss 0.846 | |mu| 3.685 | sig 0.177 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 140 | elbo -0.803 | kl 0.043 | loss 0.846 | |mu| 3.686 | sig 0.174 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 150 | elbo -0.802 | kl 0.044 | loss 0.846 | |mu| 3.686 | sig 0.171 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ " |mu| 3.686 | sig 0.171 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 | 169.16463894396955\n", "iter 160 | elbo -0.802 | kl 0.044 | loss 0.846 | |mu| 3.686 | sig 0.170 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 170 | elbo -0.802 | kl 0.044 | loss 0.846 | |mu| 3.686 | sig 0.168 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 180 | elbo -0.802 | kl 0.044 | loss 0.846 | |mu| 3.686 | sig 0.167 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 190 | elbo -0.802 | kl 0.044 | loss 0.846 | |mu| 3.686 | sig 0.166 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 200 | elbo -0.802 | kl 0.044 | loss 0.846 | |mu| 3.686 | sig 0.164 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 210 | elbo -0.801 | kl 0.044 | loss 0.846 | |mu| 3.685 | sig 0.164 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 220 | elbo -0.801 | kl 0.044 | loss 0.846 | |mu| 3.686 | sig 0.164 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 230 | elbo -0.802 | kl 0.044 | loss 0.846 | |mu| 3.688 | sig 0.163 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 240 | elbo -0.801 | kl 0.044 | loss 0.846 | |mu| 3.686 | sig 0.163 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 250 | elbo -0.801 | kl 0.044 | loss 0.846 | |mu| 3.686 | sig 0.163 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 260 | elbo -0.801 | kl 0.044 | loss 0.846 | |mu| 3.686 | sig 0.163 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 270 | elbo -0.801 | kl 0.044 | loss 0.846 | |mu| 3.685 | sig 0.163 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 280 | elbo -0.801 | kl 0.045 | loss 0.846 | |mu| 3.687 | sig 0.163 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 290 | elbo -0.801 | kl 0.045 | loss 0.846 | |mu| 3.687 | sig 0.162 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 300 | elbo -0.801 | kl 0.045 | loss 0.846 | |mu| 3.684 | sig 0.162 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ " |mu| 3.684 | sig 0.162 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 | 169.1358956642593\n", "iter 310 | elbo -0.801 | kl 0.044 | loss 0.846 | |mu| 3.686 | sig 0.162 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 320 | elbo -0.801 | kl 0.045 | loss 0.846 | |mu| 3.685 | sig 0.163 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 330 | elbo -0.801 | kl 0.045 | loss 0.846 | |mu| 3.687 | sig 0.162 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 340 | elbo -0.801 | kl 0.044 | loss 0.846 | |mu| 3.685 | sig 0.162 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 350 | elbo -0.801 | kl 0.045 | loss 0.846 | |mu| 3.686 | sig 0.164 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 360 | elbo -0.801 | kl 0.045 | loss 0.846 | |mu| 3.687 | sig 0.163 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 370 | elbo -0.801 | kl 0.044 | loss 0.846 | |mu| 3.685 | sig 0.163 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 380 | elbo -0.801 | kl 0.045 | loss 0.846 | |mu| 3.686 | sig 0.163 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 390 | elbo -0.801 | kl 0.045 | loss 0.846 | |mu| 3.687 | sig 0.162 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 400 | elbo -0.801 | kl 0.044 | loss 0.846 | |mu| 3.687 | sig 0.163 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 410 | elbo -0.801 | kl 0.045 | loss 0.846 | |mu| 3.687 | sig 0.163 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 420 | elbo -0.801 | kl 0.044 | loss 0.846 | |mu| 3.686 | sig 0.163 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 430 | elbo -0.801 | kl 0.045 | loss 0.846 | |mu| 3.685 | sig 0.163 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 440 | elbo -0.801 | kl 0.044 | loss 0.846 | |mu| 3.686 | sig 0.163 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 450 | elbo -0.801 | kl 0.044 | loss 0.846 | |mu| 3.686 | sig 0.162 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 460 | elbo -0.801 | kl 0.044 | loss 0.846 | |mu| 3.688 | sig 0.163 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 470 | elbo -0.801 | kl 0.045 | loss 0.846 | |mu| 3.687 | sig 0.163 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 480 | elbo -0.801 | kl 0.044 | loss 0.846 | |mu| 3.685 | sig 0.162 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 490 | elbo -0.801 | kl 0.045 | loss 0.846 | |mu| 3.687 | sig 0.162 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 500 | elbo -0.801 | kl 0.045 | loss 0.846 | |mu| 3.685 | sig 0.163 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n" ] }, { "data": { "image/png": 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\n", 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0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 560 | elbo -0.801 | kl 0.045 | loss 0.846 | |mu| 3.686 | sig 0.162 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 570 | elbo -0.801 | kl 0.045 | loss 0.846 | |mu| 3.687 | sig 0.162 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 580 | elbo -0.801 | kl 0.044 | loss 0.846 | |mu| 3.685 | sig 0.162 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 590 | elbo -0.801 | kl 0.045 | loss 0.846 | |mu| 3.686 | sig 0.163 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 600 | elbo -0.801 | kl 0.044 | loss 0.846 | |mu| 3.686 | sig 0.162 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 610 | elbo -0.801 | kl 0.045 | loss 0.846 | |mu| 3.686 | sig 0.163 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 620 | elbo -0.801 | kl 0.045 | loss 0.846 | |mu| 3.686 | sig 0.163 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 630 | elbo -0.801 | kl 0.045 | loss 0.846 | |mu| 3.687 | sig 0.163 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 640 | elbo -0.801 | kl 0.044 | loss 0.846 | |mu| 3.686 | sig 0.163 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 650 | elbo -0.801 | kl 0.045 | loss 0.846 | |mu| 3.686 | sig 0.161 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 660 | elbo -0.801 | kl 0.045 | loss 0.846 | |mu| 3.685 | sig 0.162 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 670 | elbo -0.801 | kl 0.044 | loss 0.846 | |mu| 3.685 | sig 0.162 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 680 | elbo -0.801 | kl 0.045 | loss 0.846 | |mu| 3.686 | sig 0.161 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 690 | elbo -0.802 | kl 0.044 | loss 0.846 | |mu| 3.686 | sig 0.162 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 700 | elbo -0.801 | kl 0.044 | loss 0.846 | |mu| 3.685 | sig 0.163 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 710 | elbo -0.801 | kl 0.045 | loss 0.846 | |mu| 3.687 | sig 0.162 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 720 | elbo -0.801 | kl 0.045 | loss 0.846 | |mu| 3.687 | sig 0.162 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 730 | elbo -0.801 | kl 0.044 | loss 0.846 | |mu| 3.685 | sig 0.162 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 740 | elbo -0.801 | kl 0.044 | loss 0.846 | |mu| 3.686 | sig 0.162 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 750 | elbo -0.801 | kl 0.045 | loss 0.846 | |mu| 3.685 | sig 0.162 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 760 | elbo -0.801 | kl 0.045 | loss 0.846 | |mu| 3.686 | sig 0.163 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 770 | elbo -0.801 | kl 0.044 | loss 0.846 | |mu| 3.686 | sig 0.163 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 780 | elbo -0.801 | kl 0.044 | loss 0.846 | |mu| 3.687 | sig 0.162 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 790 | elbo -0.801 | kl 0.044 | loss 0.846 | |mu| 3.686 | sig 0.163 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 800 | elbo -0.801 | kl 0.044 | loss 0.846 | |mu| 3.687 | sig 0.163 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 810 | elbo -0.801 | kl 0.044 | loss 0.846 | |mu| 3.687 | sig 0.163 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 820 | elbo -0.801 | kl 0.044 | loss 0.846 | |mu| 3.686 | sig 0.162 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 830 | elbo -0.801 | kl 0.045 | loss 0.846 | |mu| 3.687 | sig 0.162 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 840 | elbo -0.802 | kl 0.044 | loss 0.846 | |mu| 3.686 | sig 0.162 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 850 | elbo -0.801 | kl 0.045 | loss 0.846 | |mu| 3.686 | sig 0.162 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 860 | elbo -0.802 | kl 0.044 | loss 0.846 | |mu| 3.686 | sig 0.162 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 870 | elbo -0.801 | kl 0.044 | loss 0.846 | |mu| 3.686 | sig 0.162 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 880 | elbo -0.801 | kl 0.045 | loss 0.846 | |mu| 3.685 | sig 0.162 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 890 | elbo -0.801 | kl 0.044 | loss 0.846 | |mu| 3.687 | sig 0.163 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 900 | elbo -0.802 | kl 0.044 | loss 0.846 | |mu| 3.687 | sig 0.162 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 910 | elbo -0.801 | kl 0.045 | loss 0.846 | |mu| 3.686 | sig 0.162 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 920 | elbo -0.801 | kl 0.045 | loss 0.846 | |mu| 3.686 | sig 0.162 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 930 | elbo -0.801 | kl 0.044 | loss 0.846 | |mu| 3.687 | sig 0.162 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 940 | elbo -0.801 | kl 0.044 | loss 0.846 | |mu| 3.687 | sig 0.162 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 950 | elbo -0.801 | kl 0.044 | loss 0.846 | |mu| 3.687 | sig 0.163 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 960 | elbo -0.801 | kl 0.044 | loss 0.846 | |mu| 3.687 | sig 0.163 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 970 | elbo -0.801 | kl 0.045 | loss 0.846 | |mu| 3.687 | sig 0.163 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 980 | elbo -0.801 | kl 0.045 | loss 0.846 | |mu| 3.685 | sig 0.163 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 990 | elbo -0.801 | kl 0.045 | loss 0.846 | |mu| 3.685 | sig 0.162 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n", "iter 1000 | elbo -0.801 | kl 0.045 | loss 0.846 | |mu| 3.688 | sig 0.162 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 |\n" ] }, { "data": { "image/png": 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gNBE50bt0m6pW2yXvBV4L2D7F6BoqlQpr167N1H4lLnkIv5CU2AJGRIaAXar6i6B6VZ0SkR3A49KanGG0k0qlwurVq1tuIdvX1xfoU5SH8AtJSbJFugt4S502b/baGUbHk7VxXBADAwOhddPT0w0Z+bWTJAKmsVRyhtGhtGJbVCqVKJfLB4+gly5dGukRXZvtMe+k7U39BCA6J6VhGAeZmJiY57O0c+fOun3STE6fNZE6GBE5r+bSSQHXAArAEM4v6ecpzc0w2kqpVMp0FVMqleYZzFUqFfr6+mJtyzpF4VtPyXsVzloX7/XVXqnF3z7tBd6XyswMo81MTExw/vnnc+DAgdTHLhaLTExMHHzvx/GNq/PpFIVvPQFzvvcqwCbgq8DXAtrNAjuAm1R1V1qTM4x2EhTXZWZmpqlVTVj+56DE9377/v5+9u/ff/Babj2ng4hyVKouwPXAeXHbt7qYs6PRCiYnJ3VgYKAhJ8VCoRDqpCgigX1EJItMjGkT+ru0rAKGkZBmotKFRftPkokgh1hWAcNolFqP6Wa2SGEnQEni+HYUUcub2gK8GPg34D7gAE73UlseTTJmWsW2SEYWTE5Oan9/f6rxXEQk9F453wqF0fwWSUReiVPyFoBtwN3AoyFC68zYEi4lbItkpEErfI86ZNuThNAtUpKsAutwq5ZXqup3m52RYeSNSqWS6Fh6yZIlzMzMAM6mZWJigq1bt0YGmOqKbU8CkgiYE4HPmXAxupXx8fFENi+lUomHHnpowRhhlMvlBcfT3U4SJe8MUN+O2TDaSDPR/5NaxyZJBSsiTE1N9ZRwgWQC5lpcFDvDyCW+Nez09DSqGuoYGCaEklrHLlu2bMG1sDE6xfI2daI0wNUFKOPSklyKF8s3T8VOkYw40f/DUpCMjY1pqVRKdBo0ODi4YA5ppDjpQFI5RdoEDOOOqqeBW4BdwTJLL0gg41LBTpGMvr4+gr7PInIwBEKYQZuIBPatx+Tk5IJtT6VSWZA2tsu3RqGnSEkETHiQivmoqrY8C7cJGCOONWyYEGqULjxyboRULHmfErMc2/A0DaMJ4ljDpq0L6ZSwCe0itoBR1em4JcsJG0YYfvT/6ghxtX4/YSlIGqVnlbcxMWdHo+dIy1o3zHGxB0nP2VFEzhGRz4nIrSJyZ9X1E0Tk7SLypEZnWTXWKhFRr7yx2fEMo5qRkRGWLFnS1BilUsmESwySpC0RXIS7c71L+4DDq5o8APwzTpp9pNEJicgxwMdxhn3NfQsMI4QgZXAYpVKJJUuW9NKpUGokWcFcgou5uxlYBny0ulJV/wRsBV7Z6GQ8IbYZFx1vQ6PjGEYUlUoF91Wrjx/asjowtwmX+CQRMBfg0sVeqKq7ORSrt5rf4E6SGuXNwFm4UJ2WncBITBxXgfHx8cij6kKhEKokNpKRRMA8Dbheo7XC9wFHNjIRETkB+DAwoarfb2QMo7eJ6yoQtT0SEWZnZ20rlBJJBMyjwGF12jwJpztJhIgsAq7GxZl5V4J+oyJys4jcfP/99ye9rdFlBAXOro0gV2975P/97LQEZ3kliYC5DThDQv53ROQw3PbmZw3M4z3As4E1qrovbidV3aiqJ6vqyUce2dDCyegiwozepqenERFEhPPOOy+2JW8nJTjLK0kEzNXA8cDlIjKvn4gUgMuAo3EnTbERkVNwq5Z/UdWbkvQ1jGriGL1FpWUNwix1myOJgLkS+C5OEXs38AYAEfkSzvnxYuDrqhp7TVm1Nfo18O4EczF6nCBlbtpWumCWuk0T5WpdW3B2M+uA+4G5qrITl9FxUcLxjiC+e/zHosaycA29w9jY2II8Qo2GXIgqPRBmIS2aD9dQjaeHeSpQAnYDt6tqvJyX88c5HGdUF8RzcHqZG4E7gH9X1c+HjWWuAr1BpVJh1apVoWEZGvk+B+HH2LVTpFhEa83jFFxy+8fUabMUGIo7Zp2x1uH+krwxTntbwfQGYUGl0i4dmj6kXYT+LpPoYO4C1tZp82avnWFkQiuUriJS15bGiEcSASNELYUMowW0QumqNdssO65unLRTxz6BlEz8VXWdqoqqfjqN8YzuoF05hey4ujEivalF5LyaSycFXAOX7XEI5wz585TmZhgLYreUSiUGBwfZs6e1rmp2XN0Y9cI1XMUhp0YFXu2VWvyt017ccbVhNE1QpkVf0PT19SU2mmuUXsvGmCb1BMz53qsAm3C5qb8W0G4WF2LhJlXdldbkjN4mKtPi3NzcvNStaWLxX9IjUsCo6hb/3yKyGviqqn4m81kZBvX1HosXL6ZUKtUNHiUiFIvFg9sqf/UTtAry47+YQEmHJEG/zzThYmRNtQtAX1/013PHjh2xItMVi8V5J0Nzc3MUi0U+85nPMDk5GRkk3GgOC/pt5IK0AnEnwXIapUao+UrsmLwAIjKIC535Mlzsl8UBzVRVj0s0PaOn8QNF1cZyyRo7es6eJEG/j8D5BT0deBB4DM4PaYBDwb/vAYK1coYRQlCgqFZgR8/Zk8TQ7lKccLkAeJx37XJc5P9TgZ8CvwVOSHOCRvfTrpXEypUr23LfXiKJgHkV8H1V3axVihvP2emHwEpcQCqzqTYS0a6VxDXXXNOW+/YSSQTMMbhVis8cVToYVb0P+Bbw39KZmtErZBEoqr+/n4GBgcg2poPJniQCZi/OoM5nN3BUTZt7ccpfw4ik+jh6fHyc1atXUygUmhpzcHDw4HHz5s2b2bRpE6VSKbS96WBaQFQsB50fn+UW4HNV7/8DlwepUHVtK/C7uGOmWSweTH6ZnJycF19lbGxMi8Xighgsg4ODWigUmo7jUhu/JSwCnsV5SY1wuRFVOa8hTAB/5JDtzN/jtknfBt4EfBG3wvlE3DHTLCZg8snk5OQCYVL7Y0+7BAmPWiFnwiVVQn+XsQ3tROQ5wIXAP6vq3V7A7i8Ar6lqthU4R9vgj2SGdvlkeHg4UR7otDAjupYSamjXtCWviDwX+DNgCvhPVW2Ni2sNJmDySdwc0EkoFArMzkaHgBaRlnlbG+ECpumAU6r6E1X9vKr+qF3CxcgvzSpuq8fxFbhbtmw56EMUhilw80HaEe0MYx71VhpxGBgYYMuWLczNzTE1NcXIyAgjIyNMTU0xOTm54Ijb4rfkh1BXARF5T4Njqqp+oMG+RpdRLpcjdTClUinSwXHJkiVs2LAh1MPZvz4+Pm7xW/JImPaX+YnVkpTZKK1yVsVOkfKFf2pDxKmRf9oTlYqkXC63+6MY9Qn9XUY5O56ZqiQzeoZa72hVPZgUzVfQlsvleSuNc889N3Ass7btbEIFjKp+r5UTMbqHIO9oVQ08Oq5UKpEpQUxZ29kkigdjGHEIW3XUXq8XB8aUtZ2PnSIZqRO26li2bNlB/6Ph4WEuuOCCUOFi4Su7AwuZaaRO0MpkYGAAVQ3NElCNGcl1HNkZ2hm9Q7UH9PDw8Lx8zUHe0dXBtPv7+2MJFzC9S1cRdcTUScWOqbMlyGnRP2aOqvP7EuGcWFvMEbHjCDd3iarspGICJppmvYnDbFXK5XJoXaFQ0LGxsUQhGEQkoydgZIgJmF6m3gojDklWIM2UsbGxDJ+EkRGhv0vTwfQAQXYpe/fujbQ/qaZSqWTiFV1NoVBgbGyMK664ItP7GK0l9BRJRDY1OKaq6gWNT6kx7BQpnL6+PoL+n+Oe1mQd08VOjTqehhKvrWnwZopLbWLkhKGhoUABEfe0JmtzfTs16l6itkhPabAcm+F8jQYIitofx0rWP3oOW+WmgVnrdjlRCppOKqbkjSbpKVKQYjiNMjg4aLFxu4/Q36VZ8hqBZKV3MUVuV5KeJa+InCMinxORW0XkzqrrJ4jI20XE8iJ1AVnpXSybYm8R25ta3DnlVYAfuGMfh5LeAzwA/DNOmn0kpfkZbSJMMdwsFt+lt0iygrkEWAVsBpYBH62uVNU/4dKWvDK12RktodqPaPny5SxfvjyzY2k7MeotksSDuQC4FbhQVf0wiLX8BnhZKjMzWkKt53NUfNxmsROj3iPJCuZpwPUarRW+DziyuSkZrSTIyjdNSqXSQY9qi+/SeyQRMI8Ch9Vp8yRgpvHpGGkTFWIBstWJlEoltm/fPi/diNFbJBEwtwFnSIhTiogcBpwF/CyNiRnN429/pqenUVWmp6cZHR2dJ2Qa0Ykcdli9vzOOnTt3Jh7b6C6SCJirgeOBy0VkXj8RKQCXAUfjTpqMHFDPybFSqTAzk3zB+cgjjxw0pJqcnAzN3mgKXSO2pSxQAL6Ny330B+B2YBb4EvB77/pX4o6XdjFL3oWE5SMSkaYsdUulkk5OTmqpVAptkzQchNHRpGPJKyKLgEuBNwGlqqpdwMeBD6jqo7EHTBGz5F1ImDWun9O50aPovr4+Fi1axP79+wPrC4UCW7ZsMZ1L75COJa+qPqqq64DHAycALwSeCRypqu9tl3AxgolycmxGuTs3NxcqXPx6Ey4GNBj021sW3aGqP1DVX6pq8xnOjdQZGRlh48aN84Jv+0fFtYInTUz3YvhYRLsuIcgat6+vj7Vr1y5Q5F5yySXs2bMnk3mYMZ1RTVREu+saHFNVdUXjU2qMXtbB1MuQWE2xWGzasK6/vx8RWbBNKpVKTExM2Pao92goot0ZIdc1ZED/enfEf+ggkljjNitc/KT1/n23bdvGsmXLAGf34h+Bm5AxgETH1APAV4E7gdVAGVjsva7B+SF9BeiPO2aapZePqcOOo9Mu5XJ5wb3TyFhgdDzhciOqcl5D+ADO3uWIkPplOPuY98cdM83SywImLC9RmiVMaETlSzJ6htDfZRIl7wjwZVXdFVSpqjtxRnfnBtUb6VHrX7Ry5cpM04pEOSqGHXdb3BcDkoVrOBoIN35wHACe2Ph0jHrUKnSnp6f59Kc/7a8iAymVSg2HYSiXy0xNTYXWN5uxwOhukqxgfg+8WkQGgipFZDHwatw2KTYiUhKRN4rIV0TkThHZJyK7ReRGEbmg1u+p1wlS6EYllfc9mgcHBxPfyz9yjvLIbjRjgdEjRO2fqgvwbpy/0Y3Ai4CCd70AvNi7PgtcGndMr//FuH37PUAF+BCwCed+oLhtl9Qbp1d0MI0odBvR0fgR/+MocZvNe210PKG/y9i+SCLSD3wReJX3RZsDduKUu324I+qvA3+jCVwGROQsYBD4pqrOVV0/CvgxcIw35pejxukVO5issyzC/EyLUf5MUVsno6do3hdJVQ+o6mtwStzrgN044bIbuBYYUdXXJBEu3rjXqeo3qoWLd/1PwAbv7RlJxuxmWrH1qNafmBLXaIbE+g1V/ayqvkRVl6tqv/f6UlX91wzm5ysXzInSY2RkhFKpVL9hE1QLsTBlrSlxjTjkVoHqhYY4z3v77XbOJW+cdNJJTY/R1xf8X18qleYdR5sS12iGJMfUAIjIEO6H/2zgCNwW6afA1aqapnLgw8CJwDWq+p2QuYwCo9A7f1ErlQrXXRftJjY4OFjXmbFQKCyI6VIsFpmYmJjXzhc24+PjTE9PUygU5kXFM5cAI5IoDXBtAS7EJVybxSl5q8vDwEVJxou4z5txiuRfAcvi9OmVU6Q0rXZLpVLs0x9zCTAiSOUUaQXwXeAh4H/jFL1/xBnWneUJhSXAy1T12sSS7tB93gR8AhdkfIU6ZW9deuUUqa+vL9KoLgnVp0X1sNMkI4KGvKlreRtOuDxXVX9bdf0O4AYR2QL8xGvXkIARkbcAlwO/wAmX+xoZp5tZtmxZasnRkmwr7TTJaIQkSt5TgC/UCJeDeNe/6LVLjIi8AydcbgHONOFyiEqlwvLlyxGR1IRLUkWtnSYZjZBEwBwObK/T5n6vXSJE5N04pe5PcCuXevfpSoJM8iuVCueff37qKV2TZlm00ySjEZLoYG4Hdqnq8yPa3IRTyj4t9gREVuNyKc3iMhPsDmg2papXRY3TyTqYSqXC2rVrFwiRYrHI4YcfnrpwaVRvUqlUDgaZGhoaYv369XaKZECEDibJyc6HcELgCmpiwgCPBSa8+g/FHdPru476Jx431BunU0+RmslP1GgZGxtr98c2uotUTpEeA9yES1fyEHAr7hTpKOAkYCkuGdvzVfXBWIOmSKeuYFrhW1SLnfwYKZOKL9KDwKnAp3Ae1C8EXg+c7r3/FHBaO4RLJ1PvFGbx4sUtv6dhpEXSxGu7VfUinAXvX+CEy18Aj1PVi1T1gfSn2N3UO4V55JFHWn5Pw0iLRhOvPaqqv1DVrd5reMQjI5Kg05lm8Z0hg8Jo2smP0Upy6+zYK9RmX2w2tu7Y2Bjbt29HVZmbm2NycjIws6NhtILYSl4AEXky8D9wSt0nA/0BzVRVj0tldgnoVCVvLc0IGL+vHSEbLaZ5Ja+InAH8GidgTgeK3sC1xVZFMQlK99oM/tHg9PQ0o6Oj82LnGkY7SHJM/WPgWcAFwGe1JgJdu+m0FUySdK+NYsfRRosIXcEkETD7gM+r6pqUJpUqnSZgWh1b1zAypPktEvAALsi3kQKtsEWx42ij3SQRMP+GS09ipICfMD4r7DjayANJBMy7gMeKyP8RkeRZvIxMWbFihR1HG7kjdsApVd0uIi8HfgScJyK/JtjzWVV1RVoT7CaqvZGTmAeAi6E7OjrKhg0bAvveeeedptA1ckcSJe8zgOuBemepqqqFZieWlLwreZs9NfIVtmF2MqbQNdpIKkrey4AS8B6gDPSral9Aablw6QSCckonwVfYlsvlyHrDyBNJBMwLgP+rqh9U1btVdTarSXU6QZHpmjk1qlbYWmQ5o5NIEvR7PzCV0Ty6hrPPPptrrz0U83x6eppVq1ZRLBbr5ioK4/DDD0Uh9RW31RHwqusNI08kWcHcQIMBvXuFSy65ZJ5w8VFV9uzZQ39/kOtWfXbs2MGqVasQEYaHh9m6dSv79u2bV2+uAUYeSaLkPRZ3gvQvwEc06TFIxuRBybto0SJmZ6N3joVCoW6beohI4EmSuQYYbSKVvEiX4vIVrQcuFJFbCD+mviDR9LqEOIKjWeEChB5xW6Q6I28kETBrqv79FK8EoTiHyJ4jjdVJM9hJkpE3kgiYMIFieIyOjvLJT36yLfe2kyQjjyQKOJVn8qCDAVi6dCkzMzOJ+4XpVaIol8uWo8jIA6kY2hlVBNm6AGzYsKGh06KLL7440L7Fj69bi6/QnZubY2pqyoSLkUuSbJEMDz+d64EDLtb59PQ0559//sH6pGEvy+UyV1xxBaeddtqCzInAAhcD2w4ZHUNUVrZOKllmdpycnNRyuawiouVyWQcHB1uaabH2/pOTk5l9VsNogOYzO+adrHQwFtrSMOqSih1Mz1GpVFi9enXmR89mv2J0K6bkrcFX3ooIq1ataoldS19fn5n5G12JrWCqqN0OtWr7ODs7y+joKICdBhldhelgqmhFpP8oTBdjdChmBxOFvy3KUrgMDAzUtY8xXYzRbfS8gPG3RVmvXDZt2sTmzZtDI9KB+RIZ3UfPC5hmQ1nGoVwuMzIywsjICFNTU0xOTlpUOqMn6CkBE2Ten/XKpb+/f4HgGBkZYePGjZZmxOh6ekbJG2QwVywWefjhhzOLxl8qlZiYmDDBYXQ7ZmgXtBVKe2vU39/P5s2bTaAYhkfPbJFacfxswsUw5tMTAqZSqYR6OJdKpQUK1ygKheC0T74i1zCMQ/SEgBkfHw+0yhURJiYm2LhxY2jclVpmZ2cDBdLMzIyZ+xtGDT2h5O3r64s0+/dXN3GeRblcZv369fPyEvkUi0U7DTJ6kd625K1nwObHrqhHX1/fwdCUS5YsWVC/d+9exsfHG56nYXQbPSFggtKtNsLhhx/O+Pg4fX19oUpjM/c3jEN0/TH1JZdcwpVXXpmKrcuePXvqpn81c3/DOETXCphKpcJFF13UcD7oRjBzf8OYT1dukXyr3VYJFzP3N4xgumoFU6lUGB8fT92ozj/Crj01AovhYhhRdM0KZufOnZmEXSiXy2zfvp2JiQnzgDaMhHSNHczixYt1//79qY8rIgcVxP4KybIpGsY8Qu1gukbAiEgmH8S2QIax8I/rypUrueaaa9i2bRuqOq2qw0H9TMBEYJa5huFMPTZs2BBpjKqqgauYrtHBpE2pVDLhYvQ8lUqlrnCJwlYwNViQKMM4RNxg+GErmJ4XMCKCqh50YjTBYhiHqOco7BMmYLrKDqYRfOFiilzDWMjQ0FBTph+50cGIyJNFZJOI3CMij4jIlIh8TEQel/W9zUHRMIJZv349AwMDDffPxQpGRI4DfgA8HvgacDtwCrAWeLmInKaqC81oU8IcFA0jnGbUKHlZwVyBEy5vVtXXqOo7VfUs4HLgaUBm5rJmjWsYC/FT/Jx77rkcOHCg4XHaruQVkWOB3wJTwHGqOldVtxT4I85S8PGqGuq9mETJa4pdwwgnKMVPPfJsB3OW9/rdauECoKoPAVuBIvD8NG5WLpe5+uqrUVWmpqZMuBhGDWlmO82DDuZp3uuvQ+p/A7wUeCpwbTM3stMiw6hPmoceeRAwj/Ved4fU+9ePqK0QkVFgNO6Npqen7xKRnYlmZ1SzHNje7kl0OXl4xs8EGj86qiIPAqYe/t5ugY5FVTcCGwFE5GZVPbmVE+s17BlnT7c94zzoYPwVymND6h9T084wjA4hDwLmDu/1qSH1f+69huloDMPIKXkQMNd7ry8VkXnz8Y6pTwP2AT+sM87GDOZmzMeecfZ01TNuu4BR1d8C3wWGgTfVVL8PGAQ+E2UD443TVf8xecSecfZ02zNuu6EdBLoK/Ar4S+BM3Nbo1CxdBQzDyIZcCBgAETkGeD/wcqCEs+D9KvA+VbWjZcPoQHIjYAzD6D7aroMJIq3QDe0MAZFXRKQkIm8Uka+IyJ0isk9EdovIjSJyQa2ivc5YUyKiIeVPWX6OvJPms+nk73HuDO3SCt3Q7hAQOeb1wCdxW9DrgW3AE4DXAZ8GXiEir9f4S9vdwMcCrs80P9WOp+ln0/HfY1XNVQG+g7Pa/Yea65d51ze0cpxuKzjn0nOAvprrR+GEjQJ/HXOsKWCq3Z8pjyWtZ9Pp3+Nc6WBSDN2Qyji9hoi8Cxd75xOq+g8x2k8BaEhOnF4mjWfTDd/jvOlg0grd0NIQEF2EH1no0QR9FovIuSLyLhFZKyJnikghi8l1IM0+m47/HudNwMQJ3QDhbgVpj9MziMgi4Dzv7bcTdD0KuBq38vkYcB3wGxF5caoT7EyafTYd/z3Om4BpOHRDRuP0Eh8GTgSuUdXvxOyzGViB+yEN4tz8r8RZZX9LRJ6VwTw7hTSeTcd/j3N3ilSH0NANbRqnKxCRNwP/iDuhWBW3n6q+r+bSL4CLRWTGG28d8NqUptlRtOjZ5P57nLcVTFqhGywERExE5E3ABHAbcKamYzW9wXt9UQpjdRtJnk3Hf4/zJmDSCt1gISBiICJvAT6B++t6pqqmZRx3n/c6mNJ43USSZ9Px3+O8CZi0QjekNU7XIiLvwKWFuQUnXO6L7pGIF3ivv0txzG4hybPp+O9xrgSMJgzdICL9InK8Z+3Y8Di9hoi8G6fU/QmwQlVDY8CGPWMReYaILAtoX8atigAmU5x2x5D02XTz9zhXhnaQLHSDiAwDdwHTtQZNFgIiGBFZDVwFzAIfJ3j/PqWqV3nthwl4xiKyDngn7q/sXcBDwHHAK4HDgGuA16rq/kw+SI5J+my6+nvcblPiEPPoY3DHfH8E9gPTOEXkspp2wzgNeqBJdtxxeqngTi+0Trmh3jMGXgz8K+7kaRfOSO9+4N9x9jTS7s/axmec6Nl08/c4dysYwzC6h1zpYAzD6C5MwBiGkRkmYAzDyAwTMIZhZIYJGMMwMsMEjGEYmWECxjCMzDABY2SKiKzxIumvafdcjNZjAibniMiw9wO9qt1zaSciss57Dmf08hw6DRMwhmFkhgkYwzAywwRMjvG8cu/y3q6uyQ64xmtzhvd+nYicIiLfFJGd3rVhr42KyA0h97iqum1N3V+KyJdE5E8isl9E7haRK0Xk6BQ+25kislFEbhORB8VlmPyFiLxXRA6raTsFvNd7e331c6hpVxSRfxKRW0Rkj4jMiMhNIvKGgPtXP7eTvOe2S0T2isj3ROTUpHMQkSeIyEdF5A7v/ru8f18lLgVJz9FpMXl7jRtwAZ3XArcCX62qu6Wm7QuAfwJuBDYBy3Getw0hIucDnwIeAb4O3I2LoPZG4BwReb6qbmt0fOAdwPG4UATfxIUxOA3n7X2GiJytqrNe248Br8F5KW/B5Qmqne8RuKj9zwZ+insGfcDLgM+KyDNU9dKAeZwMvB24CZfZcgj4a+BaETlJVf2ocpFzEJEiLo3IcTiv6W/gYuaWgVcDX6IXA3C1253bSnThkCv/VSH1Z3AozMJFIW3mhWCoqbvKqx+uuvZUnHC6E3hSTfuzcLFkvhJz/mu88dfUXD+WgJAOwAe89n9bc32dd/2MOp/j7TXXD8OlYZkDTgp5brVzu8i7fkXcOeCyZSpweUDdALC03d+ldhTbInUPt6jqlSmNNQb0A2tV9Q/VFap6HW5Fc44XtrEhVPV36v36aviY9/qyuGOJSAk4F7hZVf9nzX0exq2WBPi7gO5b1QuuVcUmXPK5U+LOoYp9tRdUdb+6RGk9h22RuocfpziWHzf2xSLyvID6xwMF3ErnJ43cQEQGcVu/13rjLOVQGg6AJyUY7nnefNTTW9XS772eEFB3c+0FVT0gIvcCj0swh+8BfwDeKSLPwUWt24oT/LORPbsYEzDdQ1oZAQBK3uvb6rRb0sjgItKP05ecgsto8HlcxDc/de17gcUJhvTn+zyvhBE0310hbR/FCa1YqOqDIvJ8XKzcV3FoBbZdRK4APqiqB0IH6FJMwHQPUaEJlfD/6yMCrh3Mx6OqDzYzqRBejRMuW1R1TXWFiDyRQ6c1cfHne7mqvrX56TWGqv4euEBEBHg6Tl/1JuA9OIXzu9s1t3ZhOpj84y+vm0ko/wAurus8xCViPymgvZ8G4/Qm7hnFn3mvXw6oC8vbHPUcfoxT4mY13zhzOIg6fqmqHwde4l1+TZYTyysmYPLPA7gVyFATY/wYGBKRl9ZcvxR3jFrLJ3DblctFZEHSLxEZEJFmfsxT3usZNeMeC3wkpI8fOX/Bc1CX06kCnCwi7xaRBas1ETlORJ7S6ITrzUFETgyyJQKe4L3ubfLeHYltkXKOqs6IyI+A00WkgktVMQt8XVX/K+YwH8XpBL4mIp8HdgKnAk/B2dqcUXPP20Xkv+NOU34pIt/27tuP+3GdjtOZHN/gx/oG7gj8rSLyTOBn3rh/hbOJCRKm1+NWKR8SkRNxghdV/aBX//c4O533A6tE5EbgXuBonHL3ecAbOGS42AhRczgbuExEfoDLJnAf8GTcdnAO+F9N3Ldzafc5uZX6Bbel+AbuL+gcVbYbHLLnWFdnjFfhTkwe9sb5HG71chU1djBVfZ7p1U/jDO524pSyVwJnxZz7GoJtTY7BrTr+gDva/SXO4G0RIXY7uKPoW7z26r6+8+oHcILmBzi9zCPANuBa4C1Aqapt5HPDrbKm4s4BJ8Qu857x/d69p3AGdqe2+zvUrmJpSwzDyAzTwRiGkRkmYAzDyAwTMIZhZIYJGMMwMsMEjGEYmWECxjCMzDABYxhGZpiAMQwjM0zAGIaRGf8fgIJ8Yf/EU5QAAAAASUVORK5CYII=\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ " |mu| 3.688 | sig 0.162 | scale 0.473 | ell 1.178 | lik_sig 0.495 | brownian_c 0.000 | brownian_eta 1.025 | 169.15263993430926\n" ] } ], "source": [ "t0 = time.time()\n", "thetas_plot = thetas2\n", "\n", "# helper function to specify training parameters. We now do not mask the gradients.\n", "train_params2 = mgp.crossval.training_params(max_steps = max_steps, n_mc = 20, lrate = 2e-2, print_every = 10, callback = cb, burnin = 1, mask_Ts = (lambda x: x*1))\n", "print('fitting', n_neurons, 'neurons and', n_ts2, 'time bins for', max_steps, 'iterations')\n", "mod_train2 = mgp.crossval.train_model(mod2, data2, train_params2) #inference!" ] }, { "cell_type": "markdown", "metadata": { "id": "Os2U3ltny2jJ" }, "source": [ "We can then compare the performance of the simple linear decoder and our non-linear non-Euclidean mGPLVM-based decoder." ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 695 }, "id": "RcW2TUWIy6TC", "outputId": "f9817b32-14ac-42a9-a802-6529646dff96" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(500,) (500,) (500,)\n" ] }, { "data": { "image/png": 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\n", 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "average errors: 0.24719006903707 (linear), 0.1495513829871003 (mgplvm)\n", "\n", "Ttest_1sampResult(statistic=11.06075729330881, pvalue=1.3881822209953397e-25)\n" ] } ], "source": [ "#let's do some simple evaluation\n", "\n", "#plot inferred vs true angles\n", "thetas2_mgplvm = mod2.lat_dist.prms[0].detach().cpu().numpy()[0, :, 0] % (2*np.pi) #mgplvm prediction\n", "print(thetas2.shape, thetas2_lin.shape, thetas2_mgplvm.shape)\n", "plot_final_thetas(thetas2, thetas2_lin, thetas2_mgplvm)\n", "\n", "#compute errors in absolute distance\n", "errs_lin, errs_mgplvm = [np.arccos(np.cos(thetas2 - arr)) for arr in [thetas2_lin, thetas2_mgplvm]]\n", "bins = np.linspace(0, 0.6, 15)\n", "plot_final_errors(errs_lin, errs_mgplvm, bins)\n", "\n", "#print some summary statistics\n", "print('average errors:', np.mean(errs_lin), '(linear),', np.mean(errs_mgplvm), '(mgplvm)\\n') #print errors\n", "print(ttest_1samp(errs_lin-errs_mgplvm, 0)) #statistical test" ] }, { "cell_type": "markdown", "metadata": { "id": "uX_tQ5jyl_33" }, "source": [ "Finally, we note that the mGPLVM decoder also provides uncertainty estimates in the form of a full distribution over $p(Z^* | Y^*)$.\n", "Here, we shower that these uncertainty estimates are in fact well-calibrated, suggesting that they can be useful for uncertainty-sensitive downstream applications and analyses." ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 441 }, "id": "7oEGXD6DIBBJ", "outputId": "8fe8019a-7405-4680-f6cf-9b4230a131e2" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "68.3% ci: 63.800000000000004\n", "95.4% ci: 91.8\n", "[75 75 75 75 75 75 50]\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "correlation: (0.8755737655495163, 0.009798358756537113)\n", "total duration: 100.79450035095215\n" ] } ], "source": [ "## check whether our uncertainty estimates are well-calibrated##\n", "sigmas = mod2.lat_dist.prms[1].detach().cpu().numpy()[0, :, 0, 0] #model uncertainty\n", "print('68.3% ci:', 100*np.mean(errs_mgplvm < sigmas))\n", "print('95.4% ci:', 100*np.mean(errs_mgplvm < 2*sigmas))\n", "\n", "### now check whether the empirical std of of the residuals matches the model uncertainty###\n", "bins = np.concatenate([np.sort(sigmas)[::75], [np.inf]]) #construct some bins in which to compute errors\n", "print(np.histogram(sigmas, bins = bins)[0]) #how many observations in each bin\n", "\n", "def RMSE(residuals):\n", " '''compute RMSE for a set of residuals'''\n", " return np.sqrt(np.mean(residuals**2))\n", "\n", "#compute std of the residuals for each uncertainty bin\n", "errs_by_uncertainty = binned_statistic(sigmas, errs_mgplvm, statistic = RMSE, bins = bins)[0]\n", "#binned x-values taking the average within each bin\n", "xs = binned_statistic(sigmas, sigmas, statistic = RMSE, bins = bins)[0]\n", "\n", "### plot RMSE vs uncertainty ###\n", "plot_uncertainty_estimates(xs, errs_by_uncertainty)\n", "\n", "print('correlation:', pearsonr(xs, errs_by_uncertainty))\n", "print('total duration:', time.time() - tic)" ] }, { "cell_type": "markdown", "metadata": { "id": "_K0rfQHNxflJ" }, "source": [ "##SO(3)\n", "For those who have the courage, we now validate this approach on the group of 3D rotations (SO(3))." ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "cellView": "form", "id": "9pHbnk65-3wA" }, "outputs": [], "source": [ "#@title SO(3) helper functions\n", "\n", "def quaternion_multiply(quaternion1, quaternion2):\n", " #this is q1 \\times q2\n", " w1, x1, y1, z1 = quaternion1\n", " w2, x2, y2, z2 = quaternion2\n", " return np.array([-x1 * x2 - y1 * y2 - z1 * z2 + w1 * w2,\n", " x1 * w2 + y1 * z2 - z1 * y2 + w1 * x2,\n", " -x1 * z2 + y1 * w2 + z1 * x2 + w1 * y2,\n", " x1 * y2 - y1 * x2 + z1 * w2 + w1 * z2])\n", "\n", "def cb_so3(mod, i, loss):\n", " \"\"\"here we construct an (optional) function that helps us keep track of the training\"\"\"\n", " if i in [0, 50, 100, 150, 250, 350, 500, 750, 1000, 1250, 1500, 1999]: #iterations to plot\n", " print(i, mod.lat_dist.msg(Y, None, None) + mod.svgp.msg + mod.lprior.msg, loss/n_ts1)\n", "\n" ] }, { "cell_type": "markdown", "metadata": { "id": "KbZGNP82ALFi" }, "source": [ "We start by generating some data on SO(3) using an autoregressive process.\n", "We also construct a set of neurons with preferred firing fields on SO(3)." ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "_kLWsteXAb5z", "outputId": "ca10b74c-758c-47a1-88e0-ef399814e4e5" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "consecutive displacements: [0.35885536 0.76547395 1.34929525 2.14503775 2.91410946]\n", "baseline/random: [1.40482737 2.39040575 3.34394689 3.84129081 3.97570362]\n" ] } ], "source": [ "### Try SO(3) ###\n", "\n", "### generate some synthetic data ###\n", "\n", "tic = time.time()\n", "n_ts = 800 #total time points\n", "n_ts1 = 400 #training time points\n", "n_neurons = 100 #number of neurons\n", "\n", "#generate quaternions over time using an autoregressive process\n", "qs_t = np.random.normal(0, 1, (n_ts, 4)) #random points on sphere\n", "qs_t = qs_t / np.sqrt(np.sum(qs_t**2, axis = 1, keepdims = True)) #normalize\n", "for t in range(1, n_ts): #autoregressive process\n", " step = np.random.normal(0, 0.4, 3) #displacement in tangent space\n", " theta = np.sqrt(np.sum(step**2))\n", " v = step / theta\n", " qt = np.concatenate([np.ones(1)*np.cos(theta), np.sin(theta)*v]) #displacement in quaternion space\n", " qs_t[t, :] = quaternion_multiply(qt, qs_t[t-1, :])\n", " #print(qs_t[t, :], np.sum(qs_t[t, :]**2), theta)\n", "qs_t = np.sign(qs_t[:, :1]) * qs_t #consistent sign\n", "\n", "#generate preferred orientation for each neuron\n", "qs_n = np.random.normal(0, 1, (n_neurons, 4))\n", "qs_n = qs_n / np.sqrt(np.sum(qs_n**2, axis = 1, keepdims = True))\n", "qs_n = np.sign(qs_n[:, :1]) * qs_n #random quaternions\n", "qs_n = qs_n[np.argsort(qs_n[:, 0]), :] #sort by first element for visualization\n", "\n", "deltas = 4*( 1 - (qs_n @ qs_t.T)**2 ) #difference for each neuron/time (x^2 in small angle limit)\n", "\n", "dt_dists = 4*( 1 - np.sum(qs_t[:-1, :] * qs_t[1:, :], axis = 1)**2 )\n", "print('consecutive displacements:', np.quantile(dt_dists, [0.1, 0.25, 0.5, 0.75, 0.9]))\n", "print('baseline/random:', np.quantile(deltas.flatten(), [0.1, 0.25, 0.5, 0.75, 0.9]))" ] }, { "cell_type": "markdown", "metadata": { "id": "gH6AHDSqAUX7" }, "source": [ "We proceed to generate some synthetic neural activity and visualize it together with a couple of example tuning curves." ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "y5z-T44E3tQi", "outputId": "988df0d9-dafe-4ad6-9a21-7291827f6c06" }, "outputs": [ { "data": { "image/png": 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\n", 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#generate activity\n", "gs = np.random.uniform(0.5, 1.5, n_neurons) #scale variables\n", "ells = np.random.uniform(1.0, 2, n_neurons) #concentration parameters\n", "F = gs[:, None] * np.exp( - deltas / (2*ells[:, None]**2) )\n", "Y = F + np.random.normal(0, 0.4, (n_neurons, n_ts))\n", "Y = Y[None, ...]\n", "\n", "#split into train and test\n", "Y1 = Y[:, :, :n_ts1] #train\n", "thetas1 = qs_t[:n_ts1, :]\n", "Y2 = Y[:, :, n_ts1:] #test\n", "\n", "### plot the training data we just generated ###\n", "plot_activity_heatmap(Y1[:, :, np.argsort(qs_t[:n_ts1, 1])])\n", "\n", "### also plot some example tuning curves ###\n", "a = qs_t[..., :1]\n", "theta = 2 * np.arccos(a) #magnitude of rotation; ||x|| = theta/2\n", "u = qs_t[..., 1:] / np.sqrt(np.sum(qs_t[..., 1:]**2, axis = -1, keepdims=True))\n", "xs = 0.5 * theta * u\n", "\n", "print('\\n\\ntuning curves:')\n", "from mpl_toolkits import mplot3d\n", "plt.figure(figsize = (15,4.5))\n", "for i in range(3):\n", " ax = plt.subplot(1,3,i+1, projection='3d')\n", " n = np.random.choice(n_neurons)\n", " ax.scatter3D(xs[:, 0], xs[:, 1], xs[:,2], c = F[n, :], cmap = 'coolwarm', alpha = 0.8, s = 10)\n", " ax.set_xticks([]); ax.set_yticks([]); ax.set_zticks([])\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "id": "-eEwwfGNAaAS" }, "source": [ "We not construct our model.\n", "In this case, we learn the parameters of the prior directly during model training (note that we could also have done this for the circle; we just defined the prior separately for clarity of exposition)." ] }, { "cell_type": "code", "execution_count": 18, "metadata": { "id": "8JBJ3DQzFu18" }, "outputs": [], "source": [ "### set some parameters for fitting ###\n", "max_steps = 1501 # number of training iterations\n", "n_mc = 1 # number of monte carlo samples per iteration (since the latents are a delta function, we only need 1)\n", "print_every = 100 # how often we print training progress\n", "d_latent = 3 # specify the dimensionality of the space\n", "n_z = 15 #number of inducing points; performance increases with more inducing points\n", "\n", "### construct the actual model ###\n", "n_trials, n_neurons, n_ts1 = Y1.shape\n", "data1 = torch.Tensor(Y1).to(device)\n", "\n", "manif = mgp.manifolds.So3(n_ts1, d_latent) # our latent variables live on SO(3) (see Jensen et al. 2020 for alternatives)\n", "likelihood = mgp.likelihoods.Gaussian(n_neurons, Y = Y1, d = d_latent) #Gaussian noise\n", "mu = qs_t[None, :n_ts1, :] #ground truth thetas for training\n", "lat_dist = mgp.rdist.ReLie(manif, n_ts1, n_trials, sigma = 1e-5, diagonal = True, mu = mu) #latent distribution\n", "\n", "#learn the prior!\n", "lprior = mgp.lpriors.Brownian(manif, fixed_brownian_c = True, fixed_brownian_eta = False, brownian_eta = torch.ones(d_latent)*0.5**2)\n", "\n", "kernel = mgp.kernels.QuadExp(n_neurons, manif.distance, Y = Y1, ell = np.ones(n_neurons)*1.0, scale = 0.7*np.ones(n_neurons)) #squared exponential kernel\n", "z = manif.inducing_points(n_neurons, n_z) #inducing points\n", "mod = mgp.models.SvgpLvm(n_neurons, n_ts1, n_trials, z, kernel, likelihood, lat_dist, lprior).to(device) #construct model" ] }, { "cell_type": "markdown", "metadata": { "id": "odx3XMwDAlSX" }, "source": [ "No we're ready to train the model!\n", "This will take a bit longer since we're using more neurons and time points." ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "Fzz9AQeGG75m", "outputId": "37dd3d87-2fbd-4038-c64a-e48c773a6546" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "fitting 100 neurons and 400 time bins for 1501 iterations\n", "iter 0 | elbo -4.234 | kl 414.281 | loss 4.234 | |mu| 0.500 | sig 0.000 | scale 0.700 | ell 1.000 | lik_sig 0.615 | brownian_c 0.000 | brownian_eta 0.250 |\n", "0 |mu| 0.500 | sig 0.000 | scale 0.700 | ell 1.000 | lik_sig 0.615 | brownian_c 0.000 | brownian_eta 0.250 | 423.4367969499163\n", "iter 27 | elbo -1.188 | kl 414.324 | loss 174.066 | |mu| 0.500 | sig 0.000 | scale 0.678 | ell 0.996 | lik_sig 0.678 | brownian_c 0.000 | brownian_eta 0.147 |\n", "50 |mu| 0.500 | sig 0.000 | scale 0.645 | ell 1.048 | lik_sig 0.713 | brownian_c 0.000 | brownian_eta 0.156 | 26297.472139204503\n", "iter 54 | elbo -1.030 | kl 415.259 | loss 275.269 | |mu| 0.500 | sig 0.000 | scale 0.639 | ell 1.063 | lik_sig 0.713 | brownian_c 0.000 | brownian_eta 0.158 |\n", "iter 81 | elbo -0.915 | kl 414.933 | loss 333.734 | |mu| 0.500 | sig 0.000 | scale 0.594 | ell 1.196 | lik_sig 0.665 | brownian_c 0.000 | brownian_eta 0.161 |\n", "100 |mu| 0.500 | sig 0.000 | scale 0.560 | ell 1.327 | lik_sig 0.589 | brownian_c 0.000 | brownian_eta 0.161 | 35968.55832407983\n", "iter 108 | elbo -0.770 | kl 414.968 | loss 367.882 | |mu| 0.500 | sig 0.000 | scale 0.545 | ell 1.392 | lik_sig 0.552 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 135 | elbo -0.648 | kl 415.350 | loss 388.084 | |mu| 0.500 | sig 0.000 | scale 0.497 | ell 1.643 | lik_sig 0.454 | brownian_c 0.000 | brownian_eta 0.161 |\n", "150 |mu| 0.500 | sig 0.000 | scale 0.474 | ell 1.780 | lik_sig 0.434 | brownian_c 0.000 | brownian_eta 0.161 | 39517.59616520833\n", "iter 162 | elbo -0.587 | kl 414.338 | loss 398.698 | |mu| 0.500 | sig 0.000 | scale 0.460 | ell 1.876 | lik_sig 0.425 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 189 | elbo -0.563 | kl 415.042 | loss 406.132 | |mu| 0.500 | sig 0.000 | scale 0.435 | ell 2.046 | lik_sig 0.412 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 216 | elbo -0.551 | kl 414.446 | loss 409.485 | |mu| 0.500 | sig 0.000 | scale 0.418 | ell 2.169 | lik_sig 0.407 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 243 | elbo -0.545 | kl 414.953 | loss 412.283 | |mu| 0.500 | sig 0.000 | scale 0.405 | ell 2.265 | lik_sig 0.404 | brownian_c 0.000 | brownian_eta 0.161 |\n", "250 |mu| 0.500 | sig 0.000 | scale 0.402 | ell 2.286 | lik_sig 0.404 | brownian_c 0.000 | brownian_eta 0.161 | 41255.30519089216\n", "iter 270 | elbo -0.542 | kl 414.170 | loss 412.841 | |mu| 0.500 | sig 0.000 | scale 0.395 | ell 2.343 | lik_sig 0.402 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 297 | elbo -0.539 | kl 414.172 | loss 413.621 | |mu| 0.500 | sig 0.000 | scale 0.387 | ell 2.409 | lik_sig 0.401 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 324 | elbo -0.537 | kl 414.605 | loss 414.506 | |mu| 0.500 | sig 0.000 | scale 0.380 | ell 2.467 | lik_sig 0.401 | brownian_c 0.000 | brownian_eta 0.161 |\n", "350 |mu| 0.500 | sig 0.000 | scale 0.375 | ell 2.516 | lik_sig 0.400 | brownian_c 0.000 | brownian_eta 0.161 | 41519.8542502454\n", "iter 351 | elbo -0.536 | kl 414.804 | loss 414.969 | |mu| 0.500 | sig 0.000 | scale 0.375 | ell 2.518 | lik_sig 0.400 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 378 | elbo -0.535 | kl 415.226 | loss 415.545 | |mu| 0.500 | sig 0.000 | scale 0.370 | ell 2.565 | lik_sig 0.400 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 405 | elbo -0.534 | kl 414.598 | loss 415.006 | |mu| 0.500 | sig 0.000 | scale 0.366 | ell 2.607 | lik_sig 0.400 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 432 | elbo -0.534 | kl 414.101 | loss 414.561 | |mu| 0.500 | sig 0.000 | scale 0.363 | ell 2.647 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 459 | elbo -0.533 | kl 415.375 | loss 415.865 | |mu| 0.500 | sig 0.000 | scale 0.360 | ell 2.684 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 486 | elbo -0.533 | kl 415.280 | loss 415.787 | |mu| 0.500 | sig 0.000 | scale 0.358 | ell 2.719 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "500 |mu| 0.500 | sig 0.000 | scale 0.357 | ell 2.736 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 | 41430.51063560744\n", "iter 513 | elbo -0.532 | kl 414.655 | loss 415.173 | |mu| 0.500 | sig 0.000 | scale 0.356 | ell 2.752 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 540 | elbo -0.532 | kl 414.321 | loss 414.845 | |mu| 0.500 | sig 0.000 | scale 0.354 | ell 2.783 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 567 | elbo -0.532 | kl 414.058 | loss 414.585 | |mu| 0.500 | sig 0.000 | scale 0.353 | ell 2.813 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 594 | elbo -0.532 | kl 414.902 | loss 415.431 | |mu| 0.500 | sig 0.000 | scale 0.352 | ell 2.843 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 621 | elbo -0.531 | kl 415.630 | loss 416.160 | |mu| 0.500 | sig 0.000 | scale 0.352 | ell 2.871 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 648 | elbo -0.531 | kl 414.720 | loss 415.250 | |mu| 0.500 | sig 0.000 | scale 0.351 | ell 2.898 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 675 | elbo -0.531 | kl 414.549 | loss 415.079 | |mu| 0.500 | sig 0.000 | scale 0.351 | ell 2.924 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 702 | elbo -0.531 | kl 414.686 | loss 415.217 | |mu| 0.500 | sig 0.000 | scale 0.351 | ell 2.950 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 729 | elbo -0.531 | kl 414.893 | loss 415.424 | |mu| 0.500 | sig 0.000 | scale 0.351 | ell 2.975 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "750 |mu| 0.500 | sig 0.000 | scale 0.351 | ell 2.994 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 | 41595.048506881336\n", "iter 756 | elbo -0.531 | kl 415.057 | loss 415.587 | |mu| 0.500 | sig 0.000 | scale 0.351 | ell 2.999 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 783 | elbo -0.531 | kl 414.525 | loss 415.056 | |mu| 0.500 | sig 0.000 | scale 0.351 | ell 3.023 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 810 | elbo -0.530 | kl 415.801 | loss 416.331 | |mu| 0.500 | sig 0.000 | scale 0.352 | ell 3.046 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 837 | elbo -0.530 | kl 414.696 | loss 415.226 | |mu| 0.500 | sig 0.000 | scale 0.352 | ell 3.069 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 864 | elbo -0.530 | kl 414.470 | loss 415.001 | |mu| 0.500 | sig 0.000 | scale 0.353 | ell 3.091 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 891 | elbo -0.530 | kl 413.926 | loss 414.457 | |mu| 0.500 | sig 0.000 | scale 0.354 | ell 3.114 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 918 | elbo -0.530 | kl 414.147 | loss 414.677 | |mu| 0.500 | sig 0.000 | scale 0.355 | ell 3.135 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 945 | elbo -0.530 | kl 414.429 | loss 414.959 | |mu| 0.500 | sig 0.000 | scale 0.356 | ell 3.157 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 972 | elbo -0.530 | kl 415.509 | loss 416.039 | |mu| 0.500 | sig 0.000 | scale 0.357 | ell 3.178 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 999 | elbo -0.530 | kl 414.016 | loss 414.546 | |mu| 0.500 | sig 0.000 | scale 0.358 | ell 3.199 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "1000 |mu| 0.500 | sig 0.000 | scale 0.358 | ell 3.199 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 | 41541.80924897452\n", "iter 1026 | elbo -0.530 | kl 415.309 | loss 415.838 | |mu| 0.500 | sig 0.000 | scale 0.359 | ell 3.219 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1053 | elbo -0.530 | kl 415.001 | loss 415.530 | |mu| 0.500 | sig 0.000 | scale 0.360 | ell 3.239 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1080 | elbo -0.530 | kl 414.742 | loss 415.271 | |mu| 0.500 | sig 0.000 | scale 0.361 | ell 3.259 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1107 | elbo -0.530 | kl 414.342 | loss 414.871 | |mu| 0.500 | sig 0.000 | scale 0.362 | ell 3.279 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.162 |\n", "iter 1134 | elbo -0.530 | kl 415.311 | loss 415.840 | |mu| 0.500 | sig 0.000 | scale 0.364 | ell 3.299 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1161 | elbo -0.530 | kl 414.179 | loss 414.708 | |mu| 0.500 | sig 0.000 | scale 0.365 | ell 3.319 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.162 |\n", "iter 1188 | elbo -0.529 | kl 414.269 | loss 414.798 | |mu| 0.500 | sig 0.000 | scale 0.366 | ell 3.338 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.162 |\n", "iter 1215 | elbo -0.529 | kl 413.826 | loss 414.355 | |mu| 0.500 | sig 0.000 | scale 0.368 | ell 3.357 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1242 | elbo -0.529 | kl 414.570 | loss 415.100 | |mu| 0.500 | sig 0.000 | scale 0.369 | ell 3.376 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "1250 |mu| 0.500 | sig 0.000 | scale 0.370 | ell 3.382 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 | 41523.67677075849\n", "iter 1269 | elbo -0.529 | kl 414.489 | loss 415.019 | |mu| 0.500 | sig 0.000 | scale 0.371 | ell 3.395 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1296 | elbo -0.529 | kl 414.150 | loss 414.680 | |mu| 0.500 | sig 0.000 | scale 0.372 | ell 3.414 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.162 |\n", "iter 1323 | elbo -0.529 | kl 414.219 | loss 414.748 | |mu| 0.500 | sig 0.000 | scale 0.374 | ell 3.432 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.162 |\n", "iter 1350 | elbo -0.529 | kl 414.898 | loss 415.427 | |mu| 0.500 | sig 0.000 | scale 0.375 | ell 3.451 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1377 | elbo -0.529 | kl 414.898 | loss 415.427 | |mu| 0.500 | sig 0.000 | scale 0.377 | ell 3.469 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.162 |\n", "iter 1404 | elbo -0.529 | kl 414.542 | loss 415.071 | |mu| 0.500 | sig 0.000 | scale 0.378 | ell 3.488 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.162 |\n", "iter 1431 | elbo -0.529 | kl 415.669 | loss 416.198 | |mu| 0.500 | sig 0.000 | scale 0.380 | ell 3.506 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1458 | elbo -0.529 | kl 414.078 | loss 414.607 | |mu| 0.500 | sig 0.000 | scale 0.381 | ell 3.524 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.162 |\n", "iter 1485 | elbo -0.529 | kl 414.864 | loss 415.393 | |mu| 0.500 | sig 0.000 | scale 0.383 | ell 3.542 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "1500 |mu| 0.500 | sig 0.000 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 | 41478.34204845449\n" ] } ], "source": [ "t0 = time.time()\n", "\n", "train_params = mgp.crossval.training_params(max_steps = max_steps, n_mc = n_mc, lrate = 5e-2, callback = cb_so3, print_every = 27, burnin = 50, mask_Ts = (lambda x: x*0))\n", "print('fitting', n_neurons, 'neurons and', n_ts1, 'time bins for', max_steps, 'iterations')\n", "mod_train = mgp.crossval.train_model(mod, data1, train_params)" ] }, { "cell_type": "markdown", "metadata": { "id": "N2efA7T1Aq5t" }, "source": [ "For inference, we again initialize from a linear model - this time a linear model prediction orientations in quaternion space." ] }, { "cell_type": "code", "execution_count": 20, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "0atG26JFHw80", "outputId": "235cac95-df2e-4b20-969c-a2a647754163" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(1, 100, 400) (400, 4)\n", "linear error: [0.2881247 0.66655339 1.59165241 3.06419977 3.79916018]\n", "baseline/constant: [1.40482737 2.39040575 3.34394689 3.84129081 3.97570362]\n" ] } ], "source": [ "## first fit a linear model (we will use this for initialization and comparison) ##\n", "Y2 = Y[..., n_ts1:] #test data\n", "Z1, Z2 = qs_t[:n_ts1, :], qs_t[n_ts1:, :] #train/test quaternions\n", "print(Y1.shape, Z1.shape)\n", "\n", "alphas = 10**(np.linspace(-4, 4, 51)) #possible regularization strengths\n", "clf = RidgeCV(alphas=alphas).fit(Y1[0, ...].T, Z1) #crossvalidated ridge regression\n", "Z2_pred = clf.predict(Y2[0, ...].T) #predict test data\n", "Z2_pred = Z2_pred / np.sqrt(np.sum(Z2_pred**2, axis = 1, keepdims = True)) #normalize\n", "Z2_pred = np.sign(Z2_pred[:, :1]) * Z2_pred\n", "\n", "errs_lin = 4*( 1 - np.sum(Z2 * Z2_pred, axis = 1)**2 )\n", "errs_baseline = 4*( 1 - np.sum(np.array([1,0,0,0])[None, :] * Z2, axis = 1)**2 )\n", "errs_baseline = deltas.flatten()\n", "\n", "print('linear error:', np.quantile(errs_lin, [0.1, 0.25, 0.5, 0.75, 0.9]))\n", "print('baseline/constant:', np.quantile(errs_baseline, [0.1, 0.25, 0.5, 0.75, 0.9]))" ] }, { "cell_type": "markdown", "metadata": { "id": "xXNcJKaJA0M3" }, "source": [ "This sets us up to construct our inference model." ] }, { "cell_type": "code", "execution_count": 21, "metadata": { "id": "YGyQ6GRFJwIE" }, "outputs": [], "source": [ "### now we want to do decoding ###\n", "_, _, n_ts2 = Y2.shape\n", "manif2 = mgp.manifolds.So3(n_ts2, d_latent) # latent manifold is still So(3)\n", "mu2 = Z2_pred[None, ...] #initialize from linear prediction\n", "lat_dist2 = mgp.rdist.ReLie(manif2, n_ts2, n_trials, sigma = 0.4, diagonal = False, mu = mu2) #variational distribution\n", "#in this case we do not define a new prior" ] }, { "cell_type": "code", "execution_count": 22, "metadata": { "cellView": "form", "id": "-xjv24Et_exB" }, "outputs": [], "source": [ "#@title Construct SO(3) model\n", "\n", "data2 = torch.Tensor(Y2).to(device) #put data on device\n", "mod2 = mgp.models.SvgpLvm(n_neurons, n_ts2, n_trials, z.cpu(), kernel.cpu(), likelihood.cpu(), lat_dist2, lprior.cpu()).to(device) #use old generative model and new variational distribution\n", "for p in mod2.parameters(): #no gradients for generative parameters\n", " p.requires_grad = False\n", "for p in mod2.lat_dist.parameters(): #only inference\n", " p.requires_grad = True\n", "#copy over tuning curves (this summarizes p(Y*|Z*, {Y, Z}) from the training data in the SVGP framework)\n", "mod2.svgp.q_mu[...] = mod.svgp.q_mu[...].detach()\n", "mod2.svgp.q_sqrt[...] = mod.svgp.q_sqrt[...].detach()" ] }, { "cell_type": "markdown", "metadata": { "id": "9IRRag29A57T" }, "source": [ "Finally we are ready to do inference!" ] }, { "cell_type": "code", "execution_count": 23, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "5PvsCz0qKR1p", "outputId": "c7521f78-3edf-409b-904f-2e2e5e6a5431" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "fitting 100 neurons and 400 time bins for 1501 iterations\n", "iter 0 | elbo -0.623 | kl 0.018 | loss 0.623 | |mu| 0.500 | sig 0.400 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "0 |mu| 0.500 | sig 0.400 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 | 62.2546900889882\n", "iter 10 | elbo -0.599 | kl 0.018 | loss 0.617 | |mu| 0.500 | sig 0.336 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 20 | elbo -0.584 | kl 0.020 | loss 0.603 | |mu| 0.500 | sig 0.273 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 30 | elbo -0.574 | kl 0.021 | loss 0.595 | |mu| 0.500 | sig 0.230 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 40 | elbo -0.568 | kl 0.023 | loss 0.591 | |mu| 0.500 | sig 0.202 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 50 | elbo -0.564 | kl 0.024 | loss 0.588 | |mu| 0.500 | sig 0.185 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "50 |mu| 0.500 | sig 0.185 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 | 58.83990364661772\n", "iter 60 | elbo -0.562 | kl 0.025 | loss 0.587 | |mu| 0.500 | sig 0.175 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 70 | elbo -0.561 | kl 0.025 | loss 0.586 | |mu| 0.500 | sig 0.170 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 80 | elbo -0.560 | kl 0.026 | loss 0.586 | |mu| 0.500 | sig 0.168 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 90 | elbo -0.560 | kl 0.026 | loss 0.585 | |mu| 0.500 | sig 0.168 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 100 | elbo -0.559 | kl 0.026 | loss 0.585 | |mu| 0.500 | sig 0.168 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "100 |mu| 0.500 | sig 0.168 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 | 58.49902128107196\n", "iter 110 | elbo -0.559 | kl 0.026 | loss 0.585 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 120 | elbo -0.559 | kl 0.026 | loss 0.585 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 130 | elbo -0.559 | kl 0.026 | loss 0.585 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 140 | elbo -0.559 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 150 | elbo -0.559 | kl 0.026 | loss 0.585 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "150 |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 | 58.45806742648572\n", "iter 160 | elbo -0.559 | kl 0.026 | loss 0.585 | |mu| 0.500 | sig 0.168 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 170 | elbo -0.558 | kl 0.026 | loss 0.585 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 180 | elbo -0.559 | kl 0.026 | loss 0.585 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 190 | elbo -0.559 | kl 0.026 | loss 0.585 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 200 | elbo -0.559 | kl 0.026 | loss 0.585 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 210 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 220 | elbo -0.559 | kl 0.026 | loss 0.585 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 230 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 240 | elbo -0.559 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 250 | elbo -0.559 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "250 |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 | 58.41505519923592\n", "iter 260 | elbo -0.559 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 270 | elbo -0.559 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.168 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 280 | elbo -0.559 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.168 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 290 | elbo -0.559 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 300 | elbo -0.559 | kl 0.026 | loss 0.585 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 310 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 320 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 330 | elbo -0.559 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 340 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 350 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "350 |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 | 58.4201060165533\n", "iter 360 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.168 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 370 | elbo -0.559 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 380 | elbo -0.559 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 390 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 400 | elbo -0.559 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 410 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 420 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 430 | elbo -0.559 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 440 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.168 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 450 | elbo -0.559 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 460 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 470 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 480 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.168 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 490 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 500 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.168 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "500 |mu| 0.500 | sig 0.168 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 | 58.41072910788002\n", "iter 510 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.168 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 520 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 530 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 540 | elbo -0.559 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 550 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 560 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 570 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.166 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 580 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 590 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 600 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.166 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 610 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 620 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.166 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 630 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.166 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 640 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 650 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 660 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 670 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 680 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 690 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 700 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 710 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 720 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 730 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 740 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 750 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "750 |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 | 58.39515554302095\n", "iter 760 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 770 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 780 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 790 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 800 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.168 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 810 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 820 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.166 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 830 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 840 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 850 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 860 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 870 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 880 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.166 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 890 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 900 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.166 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 910 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 920 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 930 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 940 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 950 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.166 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 960 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.166 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 970 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 980 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 990 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1000 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "1000 |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 | 58.38274132637594\n", "iter 1010 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1020 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1030 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1040 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1050 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1060 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.166 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1070 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.166 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1080 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.166 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1090 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1100 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1110 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1120 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1130 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.166 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1140 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1150 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1160 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.168 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1170 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1180 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.166 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1190 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1200 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.166 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1210 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1220 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1230 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1240 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1250 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "1250 |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 | 58.36953732996062\n", "iter 1260 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1270 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.166 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1280 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1290 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.166 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1300 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.166 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1310 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1320 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1330 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.166 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1340 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1350 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1360 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1370 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.166 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1380 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.166 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1390 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.166 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1400 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.166 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1410 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1420 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1430 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1440 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1450 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.166 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1460 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1470 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.166 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1480 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.166 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1490 | elbo -0.558 | kl 0.026 | loss 0.584 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "iter 1500 | elbo -0.558 | kl 0.026 | loss 0.583 | |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 |\n", "1500 |mu| 0.500 | sig 0.167 | scale 0.384 | ell 3.552 | lik_sig 0.399 | brownian_c 0.000 | brownian_eta 0.161 | 58.34791888432438\n" ] } ], "source": [ "t0 = time.time()\n", "\n", "# helper function to specify training parameters. We now do not mask the gradients.\n", "train_params2 = mgp.crossval.training_params(max_steps = max_steps, n_mc = 30, lrate = 2.5e-2, print_every = 10, callback = cb_so3, burnin = 1, mask_Ts = (lambda x: x*1))\n", "print('fitting', n_neurons, 'neurons and', n_ts2, 'time bins for', max_steps, 'iterations')\n", "mod_train2 = mgp.crossval.train_model(mod2, data2, train_params2) #inference!" ] }, { "cell_type": "markdown", "metadata": { "id": "CS5wvzPtA9pU" }, "source": [ "After performing inference, we compare our model to the linear and constant baselines and see that it vastly outperforms them." ] }, { "cell_type": "code", "execution_count": 24, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "5O7OL841K4Kv", "outputId": "9af011f2-da4e-4763-bc52-d53ad7dace3c" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(400, 4)\n", "constant mean error: 2.206467350300819\n", "linear mean error: 1.4969529603467293\n", "mgplvm mean error: 0.6597242035160659\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "total time for SO(3): 180.98119020462036\n" ] } ], "source": [ "Z2_mgplvm = mod2.lat_dist.prms[0].detach().cpu().numpy()[0, ...] #mgplvm prediction\n", "print(Z2_mgplvm.shape)\n", "\n", "errs_mgplvm = 4*( 1 - np.sum(Z2 * Z2_mgplvm, axis = 1)**2 )\n", "\n", "cols = ['g', 'b', 'k']\n", "bins = np.linspace(0, np.pi, 11)\n", "#bins = np.linspace(0, np.pi**2, 11)\n", "plt.figure()\n", "labels = ['constant', 'linear', 'mgplvm']\n", "for idat, dat in enumerate([errs_baseline, errs_lin, errs_mgplvm]):\n", " dat = np.arccos( 1 - 0.5*dat)\n", " #dat = dat**2\n", " plt.hist(dat, bins = bins, alpha = 0.3, color = cols[idat], density = True,\n", " histtype = ('step' if idat == 0 else 'bar'), lw = 5, label = labels[idat])\n", " plt.axvline(np.mean(dat), color = cols[idat], lw = 4)\n", " print(labels[idat]+' mean error:', np.mean(dat))\n", "plt.xlabel('geodesic error')\n", "plt.ylabel('frequency')\n", "plt.yticks([])\n", "plt.xticks([0, np.pi/2, np.pi], [r'$0$', r'$\\pi / 2$', r'$\\pi$'])\n", "plt.legend(frameon = False, loc = 'upper center', bbox_to_anchor = (0.5, 1.2), ncol = 3, fontsize = 16)\n", "plt.show()\n", "\n", "print('total time for SO(3):', time.time() - tic)" ] }, { "cell_type": "markdown", "metadata": { "id": "Q6XxbGjQBZ9N" }, "source": [ "-------------------------------------------------\n", "\n", "The rest is legacy code that I used for debugging" ] }, { "cell_type": "code", "execution_count": 25, "metadata": { "id": "HY1Fspl5n8xp" }, "outputs": [], "source": [ "# print(Y1 == Y2)\n", "# print(thetas[:n_ts1] == thetas2)\n", "# print(mod2, mod)\n", "\n", "# print('\\nkernel ell')\n", "# print(mod.svgp.kernel.ell)\n", "# print(mod2.svgp.kernel.ell)\n", "\n", "# print('\\nkernel scale')\n", "# print(mod.svgp.kernel.scale_sqr)\n", "# print(mod2.svgp.kernel.scale_sqr)\n", "\n", "# print('\\nlikelihood prms')\n", "# print(mod.svgp.likelihood.prms)\n", "# print(mod2.svgp.likelihood.prms)\n", "\n", "# print('\\ninducing points')\n", "# print(mod.svgp.z.z[:3, 0, 0])\n", "# print(mod2.svgp.z.z[:3, 0, 0])\n", "\n", "# print('\\nlat mu')\n", "# print(mod.lat_dist.lat_prms()[0][0, :10, 0])\n", "# print(mod2.lat_dist.lat_prms()[0][0, :10, 0])\n", "\n", "# print('\\nlat std')\n", "# print(mod.lat_dist.lat_prms()[1][0, :10, 0])\n", "# print(mod2.lat_dist.lat_prms()[1][0, :10, 0])\n", "\n", "# print('\\nqmu')\n", "# print(mod.svgp.q_mu.requires_grad)\n", "# print(mod2.svgp.q_mu.requires_grad)\n", "\n", "\n", "# print(mod(data1, 10))\n", "# print(mod2(data2, 10))\n", "\n", "# print(len([p for p in mod.parameters()]))\n", "\n", "# for p in mod2.parameters():\n", "# print(p.requires_grad)" ] } ], "metadata": { "accelerator": "GPU", "colab": { "collapsed_sections": [], "name": "mGPLVM_supervised.ipynb", "provenance": [] }, "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": "3.8.5" } }, "nbformat": 4, "nbformat_minor": 4 }