{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Rapid prototyping of fMRI models with `brainiak.matnormal`\n", "\n", "Michael Shvartsman [m.shvartsman.work@gmail.com](mailto://m.shvartsman.work@gmail.com)\n", "\n", "# Annotated Bibliography \n", "\n", "Shvartsman, M., Sundaram, N., Aoi, M., Charles, A., Willke, T. L., & Cohen, J. D. (2018). Matrix-normal models for fMRI analysis. *International Conference on Artificial Intelligence and Statistics, AISTATS 2018*, 1914–1923. Extended version available at [`link`](https://arxiv.org/abs/1711.03058) *Describes how to formulate a number of common fMRI analysis methods available in `BrainIAK` as matrix-normal models, and shows some benefits of this formulation.*\n", "\n", "Cai, M. B., Shvartsman, M., Wu, A., Zhang, H., & Zhu, X. (2020). Incorporating structured assumptions with probabilistic graphical models in fMRI data analysis. *Neuropsychologia*, 144, 1–23. [`link`](https://doi.org/10.1016/j.neuropsychologia.2020.107500) *Provides an alternate framing of the matrix normal model focusing on the modeling of structured residuals.*\n", "\n", "\n", "Magnus, J. R., & Neudecker, H. (1988). Matrix differential calculus with applications in statistics and econometrics. *This is the standard reference for matrix calculus. A summary of some important identities may also be found on Wikipedia at [`link`](https://en.wikipedia.org/wiki/Matrix_calculus#Identities_in_differential_form).*\n", "\n", "\n", "Katanoda, K., Matsuda, Y., & Sugishita, M. (2002). A spatio-temporal regression model for the analysis of functional MRI data. *NeuroImage*, 17(3), 1415–1428. [`link`](https://doi.org/10.1006/nimg.2002.1209) *Example of a regression model for fMRI with separable residuals.*\n", "\n", "Hartvig, N. V. (2002). A stochastic geometry model for functional magnetic resonance images. *Scandinavian Journal of Statistics*, 29(3), 333–353. [`link`](https://doi.org/10.1111/1467-9469.00294) *Example of a separable residual covariance to a spatial activation model for fMRI data.*\n", "\n", "Kia, S. M., Beckmann, C. F., & Marquand, A. F. (2018). Scalable multi-task gaussian process tensor regression for normative modeling of structured variation in neuroimaging data. Retrieved from [`link`](http://arxiv.org/abs/1808.00036) *Example of using tensor regression models for analyzing fMRI data.*\n", "\n", "\n", "## Table of contents\n", "- [](#overview-understanding-kronecker-separability)\n", "- [](#example-1-matrix-normal-separable-covariance-regression)\n", "- [](#example-2-priors-and-marginalization-with-mn-rsa)\n", "- [](#example-3-latent-design-matrices-with-pca-and-fa)\n", "- [](#summary)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Overview: Understanding kronecker-separability\n", "\n", "Unlike many of the other tools in `brainiak`, the `brainiak.matnormal` package is only a little bit about specific methods and a lot about letting you try new ideas and method variants quickly. If the variants are useful, they can be sped up and made neater for broader consumption. To understand the idea behind matrix-normal or kronecker-separable models, consider the following figure: \n", "\n", "\n", "\n", "**Matrix normal models simultaneously model spatial and temporal residuals.** \\[A\\]: a schematic view of a vectorized data matrix, where each voxel's time series is vertically concatenated (in orange), and the covariance of every voxel at every timepoint with every other voxel at every other timepoint is modeled. Modeling all of these elements independently is intractable, and some structure needs to be imposed -- in this case, kronecker-separable structure. \\[B\\]: the un-vectorized data matrix (orange rectangle), and its spatial and temporal covariances on the right and bottom. \\[C\\]: A matrix-normal distribution with the mean M and row/column covariances R, C is equivalent to the large structure in \\[A\\], but can be much more tractable to estimate. Figure and caption reused under CC-BY-NC-ND from doi:[10.1016/j.neuropsychologia.2020.107500](https://doi.org/10.1016/j.neuropsychologia.2020.107500). \n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Example 1: Matrix-normal (separable-covariance) regression\n", "To understand how simple it is to prototype new matrix-normal models, consider first simple linear regression: \n", "\n", "$$\n", "Y \\sim \\mathcal{MN}(XB, I, I), \n", "$$\n", "\n", "where $Y$ is a centered TRs by voxels matrix of brain data, $X$ is a TRs by conditions design matrix, and $B$ is a conditions by voxels coefficients matrix. Notated this way, the model is the conventional massively-univariate GLM: the activation at every voxel and every timepoint is a linear combination (aka weighted sum) of the condition coding, weighted by the coefficients -- or equivalently a weighted sum of the coefficients, with the condition codes as weights. We can generate a simple dataset and show how simple it is to fit such a model by maximum likelihood using automatically computed gradients. " ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "# General imports and setup\n", "import numpy as np\n", "import scipy.linalg\n", "from numpy.linalg import cholesky\n", "import seaborn as sns\n", "import tensorflow as tf\n", "import matplotlib.pyplot as plt\n", "\n", "from scipy.optimize import minimize\n", "from scipy.special import expit as inv_logit\n", "from scipy.stats import norm, pearsonr\n", "\n", "from sklearn.datasets import make_friedman1\n", "from sklearn.base import BaseEstimator, TransformerMixin\n", "from sklearn.linear_model import LinearRegression\n", "\n", "np.random.seed(1)\n", "tf.random.set_seed(1)\n", "sns.set_theme()\n", "\n", "# brainiak.matnormal.covs provides implementations of various\n", "# structured covariances. We will discuss this shortly.\n", "from brainiak.matnormal.covs import (\n", " CovAR1,\n", " CovDiagonal,\n", " CovDiagonalGammaPrior,\n", " CovIdentity,\n", " CovUnconstrainedCholesky,\n", ")\n", "\n", "# brainiak.matnormal.matnormal_likelihoods provides efficient implementations\n", "# of matrix-normal likelihoods, including marginals and conditionals\n", "from brainiak.matnormal.matnormal_likelihoods import (\n", " matnorm_logp,\n", " matnorm_logp_marginal_row,\n", " matnorm_logp_marginal_col,\n", ")\n", "\n", "# brainiak.matnormal provides implementations of MN variants of some existing analyses\n", "from brainiak.matnormal.mnrsa import MNRSA\n", "from brainiak.matnormal.regression import MatnormalRegression\n", "\n", "# brainiak.matnormal.utils provides helpers that (mostly) make it easy\n", "# to interface between tensorflow and scipy optimizers\n", "from brainiak.matnormal.utils import (\n", " make_val_and_grad,\n", " pack_trainable_vars,\n", " rmn,\n", " unpack_trainable_vars,\n", ")\n", "\n", "# this is used in the MNRSA example\n", "from brainiak.utils.utils import cov2corr" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "# Generate data\n", "conditions = 5\n", "voxels = 100\n", "TRs = 50\n", "\n", "X, _ = make_friedman1(n_samples=TRs, n_features=conditions, random_state=None)\n", "B = 2 * np.random.random(size=(conditions, voxels)) # pretty generous SNR of 2\n", "Y = X @ B + np.random.normal(size=(TRs, voxels))" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "b'CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH'\n", "True and estimated B correlation: 0.78999786325132\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Now we create the tensorflow objects we need. The covariances are independent\n", "# since this is the univariate GLM.\n", "space_cov = CovIdentity(size=voxels)\n", "time_cov = CovIdentity(size=TRs)\n", "\n", "# this is our estimate of B, and the wrappers for X and Y.\n", "B_hat = tf.Variable(np.random.normal(size=(conditions, voxels)), name=\"beta\")\n", "Y_tf = tf.constant(Y)\n", "X_tf = tf.constant(X)\n", "# construct loss (negative log likelihood)\n", "# note that params are ignored by this function but implicitly\n", "# tracked by tensorflow to compute gradients\n", "def loss(params):\n", " return -matnorm_logp(Y_tf - X_tf @ B_hat, time_cov, space_cov)\n", "\n", "\n", "val_and_grad = make_val_and_grad(lossfn=loss, train_vars=[B_hat])\n", "initial_guess = pack_trainable_vars([B_hat])\n", "opt_results = minimize(fun=val_and_grad, x0=initial_guess, jac=True, method=\"L-BFGS-B\")\n", "print(opt_results.message) # check that we converged\n", "\n", "_ = B_hat.assign(unpack_trainable_vars(opt_results.x, trainable_vars=[B_hat])[0])\n", "\n", "plt.plot(B.flatten(), B_hat.numpy().flatten(), \"bo\")\n", "plt.xlabel(\"True B\")\n", "plt.ylabel(\"Estimated B\")\n", "plt.title(\"True vs estimated B\")\n", "print(\n", " f\"True and estimated B correlation: {pearsonr(B_hat.numpy().flatten(), B.flatten())[0]}\"\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In practice, a simple model like this could just as easily be fit using more standard tools. More interesting is if we (reasonably) assume that the noise in our data is structured, and we want to model that structure rather than try to prewhiten it, for example:\n", "\n", "$$\n", "\\sigma_v^{-1} \\sim \\mathcal{InvGamma}(\\alpha, \\beta)\\\\\n", "Y \\sim \\mathcal{MN}(XB, \\Sigma_{AR1},\\mathrm{diag}(\\sigma_v)), \n", "$$\n", "\n", "where $\\Sigma_{AR1}$ is a structured covariance matrix with AR(1) structure, and the spatial covariance is diagonal (independent) but with varying scales for each voxel and we use an inverse-gamma prior to regularize them. Estimating this model is very similar: " ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "b'CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH'\n", "True and estimated B correlation: 0.7891954003335606\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# generate AR(1) temporal noise that is independent in space\n", "true_time_cov = CovAR1(size=TRs)\n", "true_space_cov = CovDiagonalGammaPrior(size=voxels)\n", "noise = rmn(rowcov=true_time_cov._cov, colcov=true_space_cov._cov)\n", "Y = X @ B + noise\n", "\n", "# This time space_cov is AR(1)\n", "space_cov = CovDiagonalGammaPrior(size=voxels)\n", "time_cov = CovAR1(size=TRs)\n", "\n", "# Reset B_hat\n", "B_hat = tf.Variable(np.random.normal(size=(conditions, voxels)), name=\"beta\")\n", "\n", "# Now we estimate B_hat, but also the AR parameters and the\n", "# voxelwise residual variances (which the relevant\n", "# cov objects know about and expose to us)\n", "train_vars = [B_hat] + time_cov.get_optimize_vars() + space_cov.get_optimize_vars()\n", "\n", "# now this loss incorporates the log-likelihood of our covariance parameters\n", "def loss(params):\n", " return (\n", " -matnorm_logp(Y_tf - X_tf @ B_hat, time_cov, space_cov)\n", " - space_cov.logp\n", " - time_cov.logp\n", " )\n", "\n", "\n", "val_and_grad = make_val_and_grad(lossfn=loss, train_vars=train_vars)\n", "initial_guess = pack_trainable_vars(train_vars)\n", "opt_results = minimize(fun=val_and_grad, x0=initial_guess, jac=True, method=\"L-BFGS-B\")\n", "print(opt_results.message) # check that we converged\n", "\n", "# assign the AR parameters as well as B\n", "unpacked_theta = unpack_trainable_vars(opt_results.x, trainable_vars=train_vars)\n", "for var, val in zip(train_vars, unpacked_theta):\n", " var.assign(val)\n", "\n", "\n", "plt.plot(B.flatten(), B_hat.numpy().flatten(), \"bo\")\n", "plt.xlabel(\"True B\")\n", "plt.ylabel(\"Estimated B\")\n", "plt.title(\"True vs estimated B\")\n", "print(\n", " f\"True and estimated B correlation: {pearsonr(B_hat.numpy().flatten(), B.flatten())[0]}\"\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "`brainiak.matnormal` provides a convenience wrapper for such regression models (as `MatnormalRegression`). " ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "True an estimated B correlation (MN): 0.6194865860962584\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "model = MatnormalRegression(time_cov=time_cov, space_cov=space_cov)\n", "model.fit(X, Y, naive_init=False)\n", "plt.plot(B.flatten(), model.beta_.flatten(), \"bo\")\n", "plt.xlabel(\"True B\")\n", "plt.ylabel(\"Estimated B\")\n", "plt.title(\"True vs estimated B\")\n", "print(\n", " f\"True an estimated B correlation (MN): {pearsonr(model.beta_.flatten(), B.flatten())[0]}\"\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The covariance-modeling approach should work better than either ignoring covariance structure in the data, or pre-whitening by dividing out the correlations. So we now compare to both of those approaches on the same synthetic dataset. " ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "True and estimated B correlation (MN): 0.6194865860962584\n", "True and estimated B correlation (GLM, ignore cov): 0.38985685962097216\n", "True and estimated B correlation (GLM, prewhiten cov): 0.5315137290009893\n" ] }, { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "glm_ignore_cov = LinearRegression()\n", "glm_ignore_cov.fit(X, Y)\n", "\n", "# prewhiten\n", "W = np.linalg.cholesky(np.cov(Y))\n", "Y_whitened = np.linalg.solve(W, Y)\n", "X_whitened = np.linalg.solve(W, X)\n", "coef_whitened = np.linalg.solve(X_whitened.T @ X_whitened, X_whitened.T @ Y_whitened)\n", "glm_whitened = LinearRegression()\n", "glm_whitened.fit(X_whitened, Y_whitened)\n", "\n", "fig, axes = plt.subplots(1, 3, sharex=False, sharey=True, figsize=(18, 6))\n", "\n", "axes[0].plot(B.flatten(), model.beta_.flatten(), \"bo\", label=\"MN\")\n", "axes[0].set_title(\"True vs estimated B (MN)\")\n", "axes[1].plot(\n", " B.flatten(),\n", " glm_ignore_cov.coef_.T.flatten(),\n", " \"go\",\n", " label=\"GLM (ignore cov)\",\n", ")\n", "axes[1].set_title(\"True vs estimated B (GLM, ignore cov)\")\n", "axes[2].plot(\n", " B.flatten(),\n", " glm_whitened.coef_.T.flatten(),\n", " \"ro\",\n", " label=\"GLM (pre-whiten)\",\n", ")\n", "axes[2].set_title(\"True vs estimated B (GLM, prewhiten cov)\")\n", "for ax in axes: \n", " ax.set_xlabel(\"True B\")\n", " ax.set_ylabel(\"Estimated B\") \n", "plt.xlim(0, 2)\n", "plt.ylim(-5, 5)\n", "print(\n", " f\"True and estimated B correlation (MN): {pearsonr(B.flatten(), model.beta_.flatten())[0]}\"\n", ")\n", "print(\n", " f\"True and estimated B correlation (GLM, ignore cov): {pearsonr(B.flatten(),glm_ignore_cov.coef_.T.flatten())[0]}\"\n", ")\n", "print(\n", " f\"True and estimated B correlation (GLM, prewhiten cov): {pearsonr(B.flatten(), glm_whitened.coef_.T.flatten())[0]}\"\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Example 2: Priors and marginalization, with MN-RSA\n", "We have already introduced the idea of priors in the previous example, though in that case we were using them purely as regularization. But we can sometimes set priors in a way that lets us integrate over some nuisance parameter entirely. This marginalization is used, for example, in deriving BRSA from beta-series RSA (also available in `brainiak`). We notate the same marginalization in the matrix-normal setting next. If: \n", "\n", "$$\n", "B \\sim \\mathcal{MN}(0, U, I)\\\\\n", "Y \\mid B \\sim \\mathcal{MN}(XB, \\Sigma_{AR1},I), \n", "$$\n", "then:\n", "$$\n", "Y \\sim \\mathcal{MN}(0, XUX^{T} + \\Sigma_{AR1},I), \n", "$$\n", "\n", "and the RSA correlation is given by dividing the RSA covariance $U$ by the featurewise variances. BRSA relies on a number of linear algebra tricks to speed up estimation, and similar tricks for the matrix-normal setting are availble in generalized form to enable MN-RSA. A more extended example is available at the [MN-RSA example notebook](https://github.com/brainiak/brainiak/blob/master/examples/reprsimil/bayesian_rsa_example.ipynb) shipped with `brainiak`: " ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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338ft27dhaWmJefPmYcCAAQboZb2MyJdffqleVH7zzTcRHh4uuZ2lS5ciIyMDt27dQocOHeDo6Ig9e/bo/RkKtbt69WqDfIZifX4UQ36OYlRfPwnUVeuuaGkDmycCjdYPU9GsnAxBtAaqs48BtQxOxsoGNt36GL9DRqbZRJcIotXAcWzhaTP5+09OhiBMDeuirpks/JKTIQhTw7rRjjbjEQTRKFrZSKbZhLCB+gQ9a9euFUzS01zbbmntGrPtltausdsWhVOB45Q6L3MZyTQ7J7Nu3TqjfZmM0XZLa9eYbbe0do3dtjita8cvTZcIwtQolQBD0iooGc43tQDIyRCEqVEp2Q5IstRpAZCTIQhTQ9GlpsPCwgKenp7qVAEtoe2W1q4x225p7Rq7bVE4xuiSmTgZOlZAECam+tROcNW602vIbNrApmekCXpkXJp8JFNbnq8x97Tq2AW1pbl6tXkzLlHQ7rFzCwojJ/LsHV55irntS+tKeLbAzC9wstf/8Owp1ux/HXvVWvFs0cc/RWrvuTz7821uM7ebUyGccDrsxFocDOJLarQBw4LkX3i53OHb0r5H/jB+bhZbR/b1hVNXXXi2QSfWIkOgv8q/DnqyEtyDryXk9O8fUfbqOJ79xEVXne3Zujuh/65FkvrQ2vbJ6O1krl+/jsTERNy+fRuOjo5YsWIFunbtyt6ASgmoHvtiP/5YIkpFsaQyroI9FUF13k1me6kNu5O5XyucvuB+/i2erdaBPZ1l5R3xg3iVAn22lOBklMpyYbvAe6yqZm+3Mk94Z0VlHv+9qJPoZFSdhAXLVCV8e2WekaZQRnIyLL/Fd999F1euXFE/vnLlCpKSkhAWFoa1a9fi+++/h4tLvZPv2bMnFixYIKkPQujtZBYsWIBJkyYhKioKO3bswPz587Fp0ya9O0YQ5gqnqgOnrNVdUeIfW5bf4sqVK9X/zsrKwquvvoqQkBC1LTo6GgkJCZLuqwu9NuMZK/k3QZg1EhOJKxQK5Ofna1yPbx5szG/xv//9L0aOHGnQJGBC6DWSMUXiaIIwOyROl2JiYlBQUKBR9LhMrdTfYk1NDXbt2oVvv/1Ww75nzx4cOXIEzs7OmDNnDgICAiS+OD5NvvBr1ZGfVtLKuZtebXpnHmpUGQt9Z4vYi1L4Nr3uVE9M4Wa9nv+MlrIRxT/o1bYYXU4f1Ov5UWL24i16tauNTum/MPdDbyTmk9m8ebNBZGof5cCBA/Dw8ED37t3VtgkTJmDmzJmwsrLC0aNH8cYbbyAtLQ0dOnTQ6156OZlHE0dbWFg0KnF0bWmuxtzTyrkbam/ql9i6aNgMQbt35iHk9eJLaXR8tbtAbWHOLFXwbH2LUvCr22iefZOEhd8QgYXfmMLN2OwRw7MHSlj4/eNOe0H7iOIfsNt1As/eVsLCb1cP/sJvl9MHkRsQxrPbObG3+9sFvgZzVPEW7HDlRwalLvwOCMjn2Tql/4JbQ/vz7EdPeepsz867EwadWCupD1JHMiy/J6m/xeTkZLzyyisaNmdnZ/W/+/XrB3d3d1y7dg29e/fW3Vct6LUmY8zE0QRhthhB3E3Kb7GoqAgnT57EyJEjNezFxQ+jgpcvX0ZBQQGeeOKJRr7Ih+g9XVq4cCESExPx2WefqRNHEwShBaUSqDP8AUmx3+KMGTPw5ptv4vnnnwcAbN++HQMHDkT79pqj3FWrVuHixYuQy+WwsrLCypUrNUY3jUVvJ9OtWzds27ZN7440KRI+zPZthPedCNlr6myZ27VRCW+8FrLX1LBPw1QQn04IlSm11Oc9Xyk8EBazs2IB4fdCyK7t9QlR90C4vpBdxTAV4yRO1+qfZJyzS2K/xS+//FLj8euvvy74fGMNEJp84ZcgWh2045cgCKNCp7AJgjAqHMd4Cts8zi6TkyEIU0MjGYIgjAqtyRAEYVSUSraIJuX4JQiiUdCaDEEQRoWmSwRBGBVa+CUIwqjQSMa03IxL1EjX6J15SPQUNStuaV9KKqs9zJ5O4e4Dfo7fersNzzYEfJsYViLzbzE7K2WW4kcQhMpKwH5k4cRtfi7edwFsE7Dfv8P+Op6yEN6qXy6gKGAnchxDjMI/+afS3UTsL/oW8GyPY+HWiMVZDmzrLeaxJNP0ToYgWh2tTBKFnAxBmBplHaNMrX4J9ZsL5GQIwsRwKg4cyzRP4lSwuaKXkykvL8e7776LGzduwNraGl26dMHixYspaRVBaKOV7ZPRK/GHTCbD9OnTsW/fPuzatQve3t74+OOPDdU3gjBPjJAZrzmjl5NxdHREcHCw+rG/vz8KCwv17hRBmDUqjv0yAwymha1SqTB16lSEhoZiypQphmiSIMySym8/AFehOxm8rK0T7F5baoIeGReDLfwuWbIE9vb2iI2NlfS8wsiJvH0yQooCUhDbJyOmhCBln8zZuWd4thcVKfjNna9WkAf90m+KZeh/wq6Cud1TtY6C9tcK/oNvPfmflZR4RpkFv8/v3tiMlZ35Cgv3ZRL2ydTy98lMLtyM7wSUG6Tuk3nS6h7P1jNvJ05584XtPZ7ka30/joWbG5y3bpXUh/pRCstmPPMYyRjEyaxYsQK5ublYv3495HL98rsShNmjYjyFrZK20Y9FC1ub3nVlZSXee+89XLx4ERYWFkhISMDAgQMl9UEIvZ3MqlWrcOHCBWzYsMHocpcEYRawrrdIHMmw6tKL6V1v3LgRDg4O2L9/P3JychATE4OMjAy0adNGUj8eR69hx7Vr1/DFF1+gpKQEEyZMQFRUFGbNmqVXhwjC7GkmWtiPk56ejvHjxwMAunbtiueeew6//MJX1pSKXiOZp59+GleuXNGrAx1eeQpchea+GkFFRwkJfMTWWKzGzRcssxrIn+uLUaq6JGLnj+L+tGGXy4jrJnxOpk8PfrTu3i32M1GeJbXiZXX8MlsZ+/vcxY2vIAkAE5yLeLb8AmElSyGOWtsL2oss+e+nt/jLE6RbRCWzPe8nB53tWansIVmZSOJIxtBa2GJ614WFhfD0fKia6e7ujqIi/mcpFdrxSxAmhuM4cBI24xlSC9tYetfaICdDEKZG4kjGkFrY2vSuPTw8UFBQoB75KBQKjX1wjYVCQQRhappQC1ub3vWQIUOw9a9wfE5ODs6fP4+QkBB9Xy2NZAjC5CiVQJ3hE4mzaGFr07ueNm0aEhMTERERAblcjsWLF8PBQfe6lC7IyRCEqVGBcbokrVkWLWxtetf29vZYs2aNtJsyQE6GIEwN5fglCMKoGGkzXnOFnAxBmBhOpWILYVMicYIgGgXHOJIxk6RV5GQIwtQoVYwytTSSMQiX1pWgOu+m+nHf2cCZpQpevfZtqpnbFJMteXGccKoGsaMCQgy+8CGz/UzQfOZ2HQY/wWzflsSekMEX0vbdF8jYjyzcy+dvqO8M4KKQ3YE9PcV4R+EUC+Od+d+Lmip2CRcAWHawE8+2QsQ+rEr3e2dTyZ7OQw2tyRAEYUzqjxXQdIkgCGPRykYyBjtWsG7dOvj6+uLq1auGapIgzJMGmVqWywwwyEjm4sWLOHPmjMYxcYIgRKCRjDRqamqwePFiLFy40ADdIYhWAAc2pQLz8DH6qxV89NFH8PDwQExMDEJDQ7F+/Xr4+PgYqn8EYXZUJE4GV1qss56soyvaLv/OBD0yLnpNl06fPo0LFy7gnXfeaXQbJ3v9j2YIuygFv7rxM/9LC2ELh2HFVAWEstqJIRSqFlNBWCEhhP3W61Y8W5vEb3F/+Ws8+zdSQtg1wmHYiOKt2O86nmcvlbN/JdoLJLoeWvwD0l0n8OxSQthtHav4zz95EDcCw3h2qSHsL+915NlW5G5BQhe+KgRTCNvbGX1OfC6pDzRdkkBmZiays7MRFhaG0NBQFBUVYdq0aThy5Iih+kcQZkeDFjbLZQ7oNZKJj49HfHy8+jFNlwiCATpWQBCEUVGBLVeMeUSwDetkDh06JPk5KdYWKLV5OK/uC2CTDX+eXVPHvn17CETWZCCs6ihFVUDoqMAHuZsF118STixmbrd8wlSerU0icH//dZ493E44m78QTj4PRMteeI6fid7Oj11VoDrrtqC9V0++wkLuefZE1V7PCtvbC9ir8tjX6gBgThvhBdc5rnz7+VwXne1xjfkJMU6FZDRdIgiiUbSyhV9yMgRhYjglwNXpdiCctBS/zRZyMgRhaoy0JsOihZ2UlIS0tDR1IvG33npLrUiQmJiIX3/9Va3BNGTIELz++uvSOiEAORmCMDGs4WmpIWwWLWw/Pz9MnToVdnZ2yMrKQmxsLI4cOQJb2/q1yvj4eMTGxkq6ry5Id4kgTA2Hh6MZbddfPsaQWtghISGws7MDAPj6+oLjONy+fdtIL7QeGskQhImRKlZgaC3sBlJTU9G5c2e4ubmpbd988w22bt0Kb29v/O1vf0O3bt0kvjo+5GQIwtRIXJMxpBZ2A8ePH8enn36Kr7/+Wm1766234OzsDLlcjtTUVEyfPh0HDhxQO67GQtMlgjAxUlVq3d3d4eXlpXE97mQe1cIGIKqFDdSfOfz73/+OpKQkPPnkk2q7q6sr5PJ6lxAdHY0HDx6gqIi/l0oq5GQIwsTUh7AZLgkhbFYt7HPnzuGtt97CmjVr8OyzmrsbH9XJ/r//+z/I5XK4uro2/oX+BU2XCMLEGEtAkkULe9GiRaiqqsL8+Q93qK9cuRK+vr5ISEhAaWkpZDIZHBwc8Pnnn8PSUn8X0eROpletFe7XaqZaCKnlp16wkRDOs9JysEyonbhuBQI1hRFTFRBK1SB0VECMDj98zWzf4b+Aud0BBcLvhQuA2wV2PHtl2X3mtjsECh/1sPbk250KxI83PM6DP/l/wtuL2GUSlwvKSvhHMrxE7CzfuMbsyTWWk2HRwk5OThZ9/rfffivthow0uZMhiNaHDOBYzsuxn6lrzpCTIQhTwziSoVPYf1FdXY1ly5bht99+g42NDfz9/bFkyRJD9I0gzJL66ZLuUYrU6VJzRW8n89FHH8HGxgb79u2DTCbDrVu3DNEvgjBbjLUm01zRy8ncv38fqamp+PnnnyGT1XvmTp34cp8EQTxEpZJBpdQ9kpExjHZaAnqpFWRlZWH27NmIiIjA77//jjZt2mDu3LkICgoyZB8JwqwojJwEpUK3WoGFuys8dn5vgh4ZF71GMkqlEnl5eejRowcSEhJw9uxZzJw5E/v374eDgwNTG6m95+J+/sMpVkzhZmz2iOHVM0QIO6p4C3a48rPS9+nBz+QmhlAIW0xVQCirnRhCoWoxFYRvpYSw2wpPX32y9uLqM0N4dhs73Rn6G+gQyI8ft/sqA3enD+LZS4+zf3627fh9cD/yExQvvcyzyyyk/Y0syW3Ls/nl7Ma5riN49vxK3d9hO29nDDyxVlIfOI4tfa+ZpPjVb8evu7s7LC0t1Sc/X3jhBXTo0AHXr7P/uAiitcGpZMyXOaCXk3FyckJwcDCOHj0KoD5pTmlpKbp06WKQzhGEWcIxOhimvTTNH72jS4sWLcL777+PFStWwNLSEitXrtT7hChBmDOtbbqkt5Px9vbGd981Xkrz+Ta3UeugmVgn8LHHAFBTo99x8waesOMrGd67JaxuIMQ2AfXG2YnCqo5SVAWEjgrMKPiP4PrLa2cWMbeb+7J4+kS5BT9Gau/CviZTfpJvaweg/CR/+3/FXf4RBjHeuc2vmwxg9g3+H6/4avZ2AeDFkeWC9q7hNTzbnd26lTptZOxqng2olHKolLonESx1WgK045cgTAztkyEIwqioOBlUDOstLHVaAuRkCMLEcAA4BgdiJksy5GQIwuSwhqfNJIRNToYgTAxFlwiCMCqsG+3MZTMeORmCMDFKlRxKle7wtJyhTkuAnAxBmJj6hV+2euaAebhKgmhBcH+FsHVdLBGoR7l+/TrGjx+PwYMHY/z48cjJyeHVUSqVWLRoEcLDwxEREaGRE1hbmT7QSIYgTAzH6ECkOhkWLexdu3bhxo0byMjIwO3btxEdHY0XX3wRXl5eWsv0ocmdTE5FO1TeqVY/fgbAH3fa8+qpJCRVLrMUPoLgB+BUrSPP7lnCvpXeF8J1fWv4dicf9gz9YqoCQqkatB0VeJwuP30uqazuym/Mbbe1bSNod/1yNt/G3Crw6vAfhe3V/Ps5W7OrKwDA0V18ydahInYni2qe7XGsZBLEkf5CanRJoVAIKkg+ekawQQv7m2++AVCvhb1kyRKUlZVpaC+lpaVh7NixkMvlcHJyQnh4OPbu3Yvp06drLdOHJncyBNHakLrj15Ba2AqFAh4eHurH7u7uapVIbWX6QE6GIExM/UiGZbpU/39jaGGbEnIyBGFiVJwMSgkjGSE968d5VAvbwsJCVAvb3d0dhYWF8PPzA6A5etFWpg96R5cOHz6M6OhoREVFITIyEhkZGXp3iiDMGZbIEuuUqgFWLewhQ4Zg27ZtUKlUKCsrw4EDBzB48GCdZfqg10iG4zi8++672Lx5M3x8fJCVlYWJEyciPDwccjlFxwlCCA6M0SWJCpIsWthRUVE4e/YsBg2qz8M8a9YseHt7A4DWMn3Qe7okl8tRUVGfCKqiogIuLi7kYAhCCyqwiUNKTSfDooVtYWGBRYuEk55pK9MHvSRRAOC3337DvHnzYG9vj/v372PDhg3w9/c3UPcIwvz4vdcbqM67qbOejbczgjM/M0GPjIteI5m6ujp88cUX+OyzzxAYGIiTJ09i3rx52LNnD9q0Ed5D8TgHg+ag8pE3fETxD9jtOoFXzxD7ZF4r+A++9Yzl2T3r2PfJCBFRvBX7Xcfz7C88xx7+u13ATyMpJlsilDZTDLF9MmJyK1L2ycgE9snYBo1C1YntzG0IkSGwTyayeAt2CsjZeEncJ1Ncw0+JOrT4B6QLfOdY9slYezkj4PgGSX3gOIBF4cdcTmHrNa+5fPkySkpKEBgYCAAIDAyEnZ0dsrP5X16CIOpRQcZ8mQN6ORk3NzcUFRXhzz//BABkZ2ejtLQUnTt3NkjnCMIcUULGfJkDek2XnJ2dsXDhQsydO1ethb1s2TI4Ojoaom8EYZZwkDFFjqRGl5orekeXIiMjERkZ2ejnt0EdLKEpK9EWfJkJKV69BOLyKUICFrYSzp8UyITlU0rl/LfSzo9/BkuMyjLhtQUh2VgpsiViayxWzt0Eyyx9X2RvO+uooJ2r5MvOoKaKud3uHfmSOGJ2ZZ20wfizLsILrs968e2n8110tmenYpfTaYADW+TITJZkaMcvQZgaY4WwmyvkZAjCxHBgmwrRSIYgiEahkrEJEZhJil9yMgRhaljD0+YSwiYnQxAmRgWAJdRAazIEQTQKFWRQyWgkQxCEkeDAtqhLC78EQTQKCmETBGFUOMbokkSxgmYLORmCMDEUXTIxXi53oFSWa9i6epTz6qmU7NvHT9wW3w5eZsGf6XZx499PjHv5zoL29ip+vKA66zZzux0CbUXs/CMS5SeZmxWVLQGEUzWIHRUQwvKZfsx2KSkkbpbx+/W0iN3dReAIgxbEjmQI2W3zdU9YbBqxcqKU1V8s9cyBJncyBNHaoLNLBEEYldYWXdI5B1mxYgVCQ0Ph6+uLq1evqu0sursEQfBpOFbAchmKyspKzJs3DxERERgyZAgOHz4sWO/AgQMYPXo0RowYgeHDh+Prr79Wl6WkpCAoKAhRUVGIiorCrFmzmO6tcyQTFhaGKVOmICYmRsPOortLEASfpghhb9y4EQ4ODti/fz9ycnIQExODjIwMXppcZ2dnfP7553B1dUVFRQVGjx4NPz8/BAUFAQD69u2LNWvWSLq3zpFMUFAQTyCqQXd3xIgRAOp1dy9duoSyMuE8IARBPEQl4QLqRdby8/M1rrt370q6Z3p6OsaPr89D3bVrVzz33HP45ZdfePVeeOEFuLrWK5e3bdsW3bp140nkSqVRazKsursseKV9z7N1OX2wMd1S8662shub9WpbLLHo0OIf9GpXjHZf8cXyDCVQahs0ykAtaWLl3I3JJkbfIn6y93p7SqP7pItO6fwfnP6yZiLIGPfA/FWHRQtbF4WFhfD09FQ/ZtG5zs7OxpkzZzRkUo4fP46oqCg4ODhgxowZePnll3Xeu8kXfvOHTYJSUax+3OX0QeQGhPHqSQlhbxMJYb97YzNWdo7h2Sc4s6sKXBQIYYtlu+/Vs5C5XWtPfgi73VcZuDt9EM9efpI9k5/rl7MF7WKqAoJZ7UQQClUbQgXh9Bi+M+lblIJf3Ubz7FJD2G09+QoEndJ/wa2h/Xn2k6d0y8PaejtjwIl1kvpQB+EMjUL1ADYt7FGjRqGwUPj79uuvv0rqHwCUlJTgjTfewIIFC9Qjm5dffhnDhg2Dra0tLl26hBkzZmDTpk3o1k37H5BGORlW3V2CIPhIjS6x/K62b9cuQ+Ph4YGCggL1TEOhUCA4OFiwbmlpKeLi4jB9+nQMHTpUbX90ltKjRw/07NkT586d0+lkGqVWwKq7SxAEn6aILg0ZMgRbt24FAOTk5OD8+fMICQnh1SsvL0dcXBxiYmIwduxYjbLi4oczjoKCApw5cwa+vr46761zJLN06VJkZGTg1q1biIuLg6OjI/bs2SOqu0sQhHaaYjPetGnTkJiYiIiICMjlcixevBgODg4AgE8//RQuLi6YOHEiNmzYgJycHGzdulXtlKZMmYJXXnkFmzdvxsGDB9VrsW+//TZ69Oih8946ncwHH3yADz74gGcX092Viq2jEqpqzRmqnRPLjFWc+3fEP577Mn5ZfgG7qkBnB+E1ACF77vkOzO06FTzg2doBKD3O72/FXb7apBiuzDX/QoKqgNA6iyFUELLl6TxbXwDZcv7r7urAfiQEANLO8gXkp4jY6yx1DyUcLKSvODRFCNve3l409Dx37lz1vxMSEpCQkCBY7+2338bbb78t+d5NvvBLEK2N1rbjl5wMQZgYSiROEIRRoRy/BEEYFRU4qBgmQyx1WgLkZAjCxFD6TYIgjAot/BIEYVQoaRVBEEaFoksEQRgVWvglCMKoKMEWwmY/a9+8aXInc+qqCyrzHp7TjALw2wUPXj0LCV79KQvxceZTtfyyo9b2zG2Pd7wjaG/ryN+O7/Usc7N48KfwV8q2HT+L/ju32Y8VvDr8R0F7ZPEoZAiUde/InnhMSD2gb1GsYKoGoaMCYkw4u5jZ/utzwlvgxRjilydsf5ZvP3GO/z18HDuldFfAMY5kOBrJEATRGCi6RBCEUWlt+2SY8skIKRaUl5djxowZGDx4MEaOHInZs2dTjl+CYKDeyXAMl3nA5GTCwsKwefNmjRyhMpkM06dPx759+7Br1y54e3vj448/NlpHCcJc4CRc5gCTkxFSLHB0dNRI3+fv7y+aY5QgiIc0bMbTdZmLk5FxHMf8WkJDQ7F+/Xr4+Pho2FUqFaZOnYrQ0FBMmTLF4J0kCHNi/kuzUZZ/U2c9Jy9nLD4iLUl5c8QgC79LliyBvb09YmOFpSy0kRE0B5V5t9SPo4q3YIfrRF49KSHscgu+SD0ATC7cjO88+GoFRQwZ0BoY76zg2TqfPIgbgXyFhfZ6hrDdj/wExUsv8+yzb7CLorxazQ8zA0Bk8RbsFHif9Q9hC6sKCGW1E0MoVC2mgiA1hN3dr4Rnc9n/C0oi+GoFTCFsb2cMPLFWUh9oM55EVqxYgdzcXKxfvx5yeaPykhNEq4JC2BJYtWoVLly4gA0bNsDa2tpQfSIIs6YpNuNVVlbivffew8WLF2FhYYGEhAQMHDiQV+/3339HfHw8unbtCgCwtrbWyOWdlJSkll8ZNWoUkx42k5MRUixYvXo1vvjiC3Tt2hUTJtQLm3l5eSEpKYmlSYJotTRnLWygXiQgJYW/azszMxN79+5VSyGNHTsWvXv3Rq9evbTem8nJiCkWXLlyheXpWlHKZKiTaa6JPP4YAFRgXzexU4n/BRAq8+bv3Belpkp4vUfIXpXHVysUQybcLGQW/P7GV7Ovbzhb3xct8xIoU9axT3nF1BuF7FJUBYTWWQYU/1fQ3veCNCmeq33e5NlcANz8sy3P7mHDV5B4HGvrSkn3B+pHKCyjlIY6CoVCUEHycRVJbaSnp2P58uUANLWwHxVv00VaWhqio6Nha1uvdhodHY20tDTDOBmCIAyHEhyUDE6moY6ptbBzcnIwatQoWFpaYtKkSRg1ql4zXaFQoHfv3hptZGZm6rw3ORmCMDFSk1aZUgv72Wefxc8//4y2bdsiLy8PcXFxcHV1Rd++fZnbeBxyMgRhYlQcBxXD9rSGOqbUwm5QlQQAb29vhIeH49SpU+jbty/c3d01HJlCoWDqG8WcCcLENMWxAlYt7JKSEjTsz719+zaOHj2KZ555Rt1GamoqqqqqUFVVhdTUVKY1HRrJEISJaYrNeKxa2BkZGdiyZQssLS2hVCoRHR2N8PBwAEBwcDAGDRqE4cOHA6hf+H10jUYMcjIEYWLqRyks0SXDwaqFHRsbq3Xn/pw5cyQtOAPkZAjC5JBaAUEQRkUJFZQMboalTkuAnAxBmJjWlhmPnAxBmBiO48CSYUVCFpZmDTkZgjAxpFZgYoJ7FEHVSXN784CAfF69ugfsZ5cK/2wvWvak1T2erVsE+/mTZQc78WwrAHx5ryPPPqdNMXO7ZSV8WRY3ACW5/DM1L45kPwd0dJeTaFlxDf+ez7roTqbUgL2L8KGvtp78M1tpZ72Z2xWTLRHKBSN0FkkbPseEIyxC9lMvvKOzPU7CWa8GaLpEEIRRkXpAsqVDToYgTExry4zXaEmUR1m3bp1oGUEQmqg4DkqGi+V8U0ug0ZIoDVy8eBFnzpwRLCMIgk/Djl/d/5kHjZZEAYCamhosXrwYCxcuNHS/CMJsYRN2Y5tStQT0kkT56KOP4OHhgZiYGFG5FIIgNJnUZzKK83VHHl29XPH9se9M0CPj0uiF39OnT+PChQt45x3dYT5tlL06DqqShyHsTum/4NZQvjyFIULYPfN24pR3JM+udwg7dwsSuvDlRea46hfC9svZjXNdR/DsXcNrmNsVC2EPLf4B6a4TePZnvfQLYYt9fpJC2M/yQ9hisiVCaTO1IRSqFpNbYQlhW3s5I+D4Bkl9oIVfRjIzM5GdnY2wsDCEhoaiqKgI06ZNw5EjRwzZP4IwQ1hXZMzDyTR6JBMfH4/4+Hj1Y5ouEQQbUjPjtXSYRjJLly5F//79UVRUhLi4OHXSGoIgpNOQSJzlMgf0kkR5lEOHDjWqAycuuqIy76EeSBSAo6f44XCVgEyKGC/6FoiWeTx5h2fL+8lBoKYww6qEt9IL2c/nujC3K/R18gOQX8nv253ddcztOlmIy7IIlZ3OZ++zbT5/4/tgACdP8SORdRKkgIXkYYeJ2FlkSx5FaJ0luHC7oL3n2Y91NyiXPhlobWsytOOXIEwNx3jC2jx8DDkZgjA1NJIhCMKoNMUBSVYt7E2bNiE5OVn9OC8vD2PHjsV7772nUydbDHIyBGFimiJpFasW9pQpUzBlyhQAQG1tLfr3748RIx7u1RLTydYG6S4RhImReqxAoVAgPz9f47p7966ke6anp2P8+PEANLWwtXH48GE4Ozvj+eefb9wL/QsayRCEiVFBBSWnOyWV6q+0VabWwm4gOTkZo0eP1rCJ6WRrg5wMQZgYqWsyptTCbqCkpATHjh3Dv/71L7WtsTrZ5GQIwsSoOLbdvKq/qphSC7uB1NRUDBgwQF0f0K6TrQ1akyEIE8N2csmwGWVYtbAbSE5OxiuvvKJh06aTrY0mH8nYuvNPCdt58086cxJ2/Fq4KbWUufFsVir+CWgxbCpthe3ezjwbJ+HtFfs62Qm0ayNj3/FrJRN/L6y9+G3bqWyY27YR6bWtQJ8dLNjfCzulcJ+F3gtra/YT9IB44m+h94JpN6/cQnedx2iKs0usWtgAcPLkSTx48AAvvfSSRhvadLK1ISmfDEEQ+hMWGImCPIXOep7e7jh4cqcJemRcmtV0SaFQIDQ0FAqF7g+gubTd0to1ZtstrV1jty1Gw0iG5TIHmny69ChKpRIFBQW8lfTm3HZLa9eYbbe0do3dtug9ObYQNkudlkCzcjIE0Rog3SWCIIxK/bEC3aMUc1kuJSdDECaGtLCbkHbt2mH27Nm83YzNue2W1q4x225p7Rq7bTGa4oBkU0IhbIIwMX1eGIT8POEjAI/i5e2BY2czTNAj49KsRjIE0RpQciooVRRdIgjCaLAeGTCPSQY5GYIwMRxjjl9zWcggJ0MQJoZy/BIEYVRaW3SJnAxBmJjWpiBJToYgTAyNZAiCMCoqxgOSKgphEwTRGGi6RBCEUeHAdi7JPFwMORmCMDk0kiEIwsiwLfyay1imWaXfJIjWQFOoFezYsQMjR45Ejx498J///Edr3R9//BEREREIDw/H4sWLoXrknJW2MjHIyRCEiWkIYbNchqJ79+745JNPNHSthcjLy8O6deuwdetWZGRkIDc3Fzt37tRZpg2aLhGEifHwcGNab/HwqJfvUSgUggqSUnLg+Pj4AADkcu3jin379iE8PFwt6jZ27FikpKQgOjpaa5k2yMkQhIn5+adU5rpVVVWIiorCnTt3NOxStbBZUSgU8PDwUD/28PBQKzloK9MGORmCaMbU1NQgJSWFZ5eqhW1hIV2EzlCQkyGIZgzrtEiXFjYr7u7uGs6qsLBQrcWtrUwbtPBLEISawYMH48CBAygrK4NKpcK2bdswdOhQnWXaoBy/BNEK2L17N1auXIm7d+/CysoKdnZ2+Prrr/HUU0/xtLB/+OEHfPXVVwCAfv36Yf78+erplrYyMcjJEARhVGi6RBCEUSEnQxCEUSEnQxCEUSEnQxCEUSEnQxCEUSEnQxCEUSEnQxCEUfl/nigT9+f8srMAAAAASUVORK5CYII=\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# make a fake RSA matrix\n", "conditions = 16\n", "groundtruth_U = np.zeros([conditions, conditions])\n", "groundtruth_U = np.eye(conditions) * 0.6\n", "groundtruth_U[8:12, 8:12] = 0.8\n", "for cond in range(8, 12):\n", " groundtruth_U[cond, cond] = 1\n", "groundtruth_C = cov2corr(groundtruth_U)\n", "plt.matshow(groundtruth_C, vmin=-1, vmax=1)\n", "plt.title(\"Ground truth RSA Matrix\")\n", "plt.colorbar()\n", "\n", "# synthetic data\n", "B = rmn(groundtruth_U, space_cov._cov) # now B is RSA-structured, rest is as above\n", "X, _ = make_friedman1(n_samples=TRs, n_features=conditions, random_state=None)\n", "noise = rmn(rowcov=true_time_cov._cov, colcov=true_space_cov._cov)\n", "Y = X @ B + noise\n", "\n", "rsa_cov = CovUnconstrainedCholesky(size=conditions)\n", "\n", "params = (\n", " rsa_cov.get_optimize_vars()\n", " + time_cov.get_optimize_vars()\n", " + space_cov.get_optimize_vars()\n", ")\n", "\n", "# note the loss now includes a marginal logp term, plus the likelihoods of the various covariances in question\n", "def loss(params):\n", " return -(\n", " time_cov.logp\n", " + space_cov.logp\n", " + rsa_cov.logp\n", " + matnorm_logp_marginal_row(\n", " Y, row_cov=time_cov, col_cov=space_cov, marg=X, marg_cov=rsa_cov\n", " )\n", " )\n", "\n", "val_and_grad = make_val_and_grad(lossfn=loss, train_vars=params)\n", "\n", "x0 = pack_trainable_vars(params)\n", "\n", "opt_results = minimize(fun=val_and_grad, x0=x0, jac=True, method=\"L-BFGS-B\")\n", "\n", "fit_params = unpack_trainable_vars(opt_results.x, params)\n", "\n", "for var, val in zip(params, fit_params):\n", " var.assign(val)\n", "\n", "U = rsa_cov._cov.numpy()\n", "C = cov2corr(U)\n", "plt.matshow(C, vmin=-1, vmax=1)\n", "plt.title(\"Estimated RSA Matrix\")\n", "plt.colorbar()\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As before, this model is available in `brainiak` directly as `MNRSA`, where it incorporates nuisance regressors as well: " ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "model_matnorm = MNRSA(time_cov=time_cov, space_cov=space_cov, n_nureg=3)\n", "\n", "model_matnorm.fit(Y, X)\n", "plt.matshow(model_matnorm.C_, vmin=-1, vmax=1)\n", "plt.title(\"Estimated RSA Matrix\")\n", "plt.colorbar()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Example 3: latent design matrices with PCA and FA\n", "The true benefit of a shared framework comes when starting to see the commonalities among methods. For example, consider what happens if the known design matrix $X$ is replaced with an unknown latent time series $S$, yielding the following model: \n", "\n", "$$\n", "Y \\sim \\mathcal{MN}(SB, I, I). \n", "$$\n", "\n", "In this model, we no longer know the design matrix, and the brain volume is now a weighted sum of unknown time series, with unknown weights. It turns out that this is precisely the model for probabilistic PCA, and there is nothing stopping us from implementing it in our framework. However, note that PCA has uniquely many solutions, so while doing naive gradient descent on this problem might work in toy examples, it isn't a particularly realistic example. To find a unique solution, we can integrate over either $S$ or $B$ using a matrix-normal prior. We choose to integrate over $S$, since it is a larger matrix in this case and this lets us estimate fewer parameters. " ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Generate data\n", "components = 5\n", "voxels = 100\n", "TRs = 50\n", "\n", "S = np.sin(\n", " np.arange(TRs)[:, None] @ np.random.randn(1, components)\n", " + np.random.randn(1, components)\n", ")\n", "plt.plot(S) # random sinewaves with noise\n", "plt.title(\"Simulated latent response\")\n", "plt.xlabel(\"TRs\")\n", "B = np.random.randn(components, voxels)\n", "Y = S @ B + np.random.randn(TRs, voxels)\n", "plt.figure()\n", "\n", "plt.plot(Y[:, :10])\n", "plt.xlabel(\"TRs\")\n", "_ = plt.title(\"Simulated voxel time series (first 10 voxels)\")" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "b'CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH'\n" ] }, { "data": { "image/png": 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\n", 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\n", 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# generate AR(1) temporal noise that is independent in space\n", "true_time_cov = CovIdentity(size=TRs)\n", "true_space_cov = CovIdentity(size=voxels)\n", "noise = rmn(rowcov=true_time_cov._cov, colcov=true_space_cov._cov)\n", "Y_tf = tf.constant(S @ B + noise)\n", "\n", "# This time space_cov is AR(1)\n", "space_cov = CovDiagonalGammaPrior(size=voxels)\n", "time_cov = CovAR1(size=TRs)\n", "marg_cov = CovIdentity(size=components)\n", "\n", "# B_hat\n", "B_hat = tf.Variable(np.random.normal(size=(components, voxels)), name=\"beta\")\n", "\n", "train_vars = [B_hat] + time_cov.get_optimize_vars() + space_cov.get_optimize_vars()\n", "\n", "# now this loss incorporates the log-likelihood of our covariance parameters\n", "def loss(params):\n", " return (\n", " -matnorm_logp_marginal_col(Y_tf, time_cov, space_cov, B_hat, marg_cov)\n", " - space_cov.logp\n", " - time_cov.logp\n", " )\n", "\n", "\n", "val_and_grad = make_val_and_grad(lossfn=loss, train_vars=train_vars)\n", "initial_guess = pack_trainable_vars(train_vars)\n", "opt_results = minimize(fun=val_and_grad, x0=initial_guess, jac=True, method=\"L-BFGS-B\")\n", "print(opt_results.message) # check that we converged\n", "\n", "# assign the parameters\n", "unpacked_theta = unpack_trainable_vars(opt_results.x, trainable_vars=train_vars)\n", "for var, val in zip(train_vars, unpacked_theta):\n", " var.assign(val)\n", "\n", "# now that we have B, solving for the MLE of S is just closed-form\n", "# linear regression\n", "Sigma_s_btrp = space_cov.solve(tf.transpose(a=B_hat))\n", "# Y Sigma_s^{-1} B'\n", "Y_Sigma_Btrp = tf.matmul(Y_tf, Sigma_s_btrp).numpy()\n", "# (B Sigma_s^{-1} B')^{-1}\n", "B_Sigma_Btrp = tf.matmul(B_hat, Sigma_s_btrp).numpy()\n", "S_hat = np.linalg.solve(B_Sigma_Btrp.T, Y_Sigma_Btrp.T).T\n", "\n", "# Since the PCA solution is not unique, we show reconstruction\n", "plt.plot((S @ B).flatten(), (S_hat @ B_hat).numpy().flatten(), \"bo\", alpha=0.5)\n", "plt.xlabel(\"True (noiseless) voxel time series\")\n", "plt.ylabel(\"Reconstructed noiseless voxel time series\")\n", "# Also show the inner products of S and B -- these won't be uniquely scaled \n", "plt.figure()\n", "plt.plot(\n", " (S @ S.T).flatten(),\n", " (S_hat @ tf.transpose(S_hat)).numpy().flatten(),\n", " \"bo\",\n", " alpha=0.5,\n", ")\n", "plt.xlabel(\"True latent response inner product\")\n", "plt.ylabel(\"Estimated latent response inner product\")\n", "plt.figure()\n", "\n", "plt.plot(\n", " (B.T @ B).flatten(),\n", " (tf.transpose(B_hat) @ B_hat).numpy().flatten(),\n", " \"bo\",\n", " alpha=0.5,\n", ")\n", "plt.xlabel(\"True weight matrix inner product\")\n", "_ = plt.ylabel(\"Estimated weight matrix inner product\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "If the code above looked very similar to the code earlier in the notebook, that's because it was: this is exactly as MN-RSA except for replacing the known design matrix $X$ with an estimated one $S$ and integrating in the other direction. If we replaced the `CovIdentity` with a `CovDiagonal` this model would be factor analysis, and other residual covariances may map to other models. `brainiak.matnormal` does not include a `MatnormalFactorAnalysis`, but we can easily sketch one here: " ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "class MNFactorAnalysis(BaseEstimator, TransformerMixin):\n", " \"\"\" Linear gaussian LVM with with structured residuals. \n", " If time_cov=space_cov=CovIdentity (the default), this is PCA\n", " If time_cov=CovIdentity and space_cov=CovDiagonal (or vice versa)\n", " this is factor analysis. \n", " ..math::\n", " Y \\\\sim \\\\mathcal{MN}(S\\beta, time_cov, space_cov)\n", "\n", " Parameters\n", " ----------\n", " time_cov : subclass of CovBase\n", " TR noise covariance class following CovBase interface.\n", " space_cov : subclass of CovBase\n", " Voxel noise covariance class following CovBase interface.\n", " n_features : int\n", " Number of latent dimensions\n", " dual : bool\n", " If false, use algorithm from \"regular\" probabilistic PCA (integrate over S),\n", " otherwise use \"dual\" probabilistic PCA algorithm (integrate over B)\n", " optimizer : string, default=\"L-BFGS-B\"\n", " Scipy optimizer to use. For other options, see \"method\" argument\n", " of scipy.optimize.minimize\n", " optCtrl: dict, default=None\n", " Additional arguments to pass to scipy.optimize.minimize.\n", "\n", " \"\"\"\n", "\n", " def __init__(\n", " self,\n", " time_cov,\n", " space_cov,\n", " n_features,\n", " dual=False,\n", " optimizer=\"L-BFGS-B\",\n", " optCtrl=None,\n", " ):\n", "\n", " self.optMethod = optimizer\n", " if optCtrl is None:\n", " self.optCtrl = {}\n", "\n", " self.time_cov = time_cov\n", " self.space_cov = space_cov\n", " self.n_features = n_features\n", "\n", " self.dual = dual\n", "\n", " self.n_t = time_cov.size\n", " self.n_v = space_cov.size\n", "\n", " def logp(self, Y):\n", " \"\"\" Log likelihood of model (internal)\n", " \"\"\"\n", " if self.dual:\n", " data_logp = matnorm_logp_marginal_row(\n", " Y, self.time_cov, self.space_cov, self.S, self.marg\n", " )\n", " else:\n", " data_logp = matnorm_logp_marginal_col(\n", " Y, self.time_cov, self.space_cov, self.B, self.marg\n", " )\n", "\n", " return time_cov.logp + space_cov.logp + data_logp\n", "\n", " def fit(self, X, y=None, naive_init=True):\n", " \"\"\" Compute the regression fit.\n", "\n", " Parameters\n", " ----------\n", " X : np.array, TRs by voxels.\n", " Brain data (note that this is Y in the math but we \n", " call it X in the interface to maintain scikit-learn \n", " API compatibility)\n", " y : None\n", " unused, here to maintain scikit-learn API compatibility\n", " \"\"\"\n", "\n", " if naive_init:\n", " # initialize to SVD (conventional PCA)\n", " u, _, v = np.linalg.svd(X)\n", " s_init, b_init = u[:, : self.n_features], v[: self.n_features, :]\n", " else:\n", " b_init = np.random.randn(self.n_features, self.n_v)\n", " s_init = np.random.randn(self.n_t, self.n_features)\n", "\n", " self.B = tf.Variable(b_init, name=\"B\")\n", " self.S = tf.Variable(s_init, name=\"S\")\n", "\n", " self.train_variables = [self.S] if self.dual else [self.B]\n", " self.train_variables.extend(self.time_cov.get_optimize_vars())\n", " self.train_variables.extend(self.space_cov.get_optimize_vars())\n", " self.marg = CovIdentity(self.n_features)\n", "\n", " def lossfn(theta):\n", " return -self.logp(X)\n", "\n", " val_and_grad = make_val_and_grad(lossfn, self.train_variables)\n", " x0 = pack_trainable_vars(self.train_variables)\n", "\n", " opt_results = minimize(\n", " fun=val_and_grad, x0=x0, jac=True, method=self.optMethod, **self.optCtrl\n", " )\n", "\n", " unpacked_theta = unpack_trainable_vars(opt_results.x, self.train_variables)\n", "\n", " for var, val in zip(self.train_variables, unpacked_theta):\n", " var.assign(val)\n", "\n", " if self.dual:\n", " self.B.assign(self.transform(X, direction=\"B\"))\n", " else:\n", " self.S.assign(self.transform(X, direction=\"S\"))\n", "\n", " self.B_ = self.B.numpy()\n", " self.S_ = self.S.numpy()\n", "\n", " def transform(self, X, direction=\"S\"):\n", " \"\"\"\n", " Transform input X using the fit model, returning \n", " the projected time series (if direction=\"S\")\n", " or inferred projection (if direction=\"B\"). \n", " \n", " Either simply requires solving a regression problem, \n", " which can be done in closed form. \n", " \n", " Again, this is Y in the math but X in the code becasue\n", " of scikit-learn\n", " \"\"\"\n", " if direction == \"S\":\n", " # Sigma_s^{-1} B'\n", " Sigma_s_btrp = self.space_cov.solve(tf.transpose(a=self.B))\n", " # Y Sigma_s^{-1} B'\n", " Y_Sigma_Btrp = tf.matmul(X, Sigma_s_btrp).numpy()\n", " # (B Sigma_s^{-1} B')^{-1}\n", " B_Sigma_Btrp = tf.matmul(self.B, Sigma_s_btrp).numpy()\n", "\n", " S_test = np.linalg.solve(B_Sigma_Btrp.T, Y_Sigma_Btrp.T).T\n", "\n", " return S_test\n", "\n", " elif direction == \"B\":\n", " # S' Sigma_t^{-1} S\n", " Strp_Sig_S = tf.transpose(self.S) @ self.time_cov.solve(self.S)\n", " # S' Sigma_t^{-1} X\n", " Strp_Sig_X = tf.transpose(self.S) @ self.time_cov.solve(X)\n", " B_test = np.linalg.solve(Strp_Sig_S, Strp_Sig_X)\n", " return B_test" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/plain": [ "Text(0, 0.5, 'Estimated weight matrix inner product')" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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\n", 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# regular\n", "mn_fa = MNFactorAnalysis(time_cov=time_cov, space_cov=space_cov, n_features=components, dual=False)\n", "\n", "mn_fa.fit(Y_tf, naive_init=False)\n", "\n", "plt.plot((S @ B).flatten(),(mn_fa.S_ @ mn_fa.B_).flatten(), 'bo')\n", "plt.xlabel(\"True (noiseless) voxel time series\")\n", "plt.ylabel(\"Reconstructed noiseless voxel time series\")\n", "\n", "plt.figure()\n", "plt.plot( (S @ S.T).flatten(),(mn_fa.S_ @ mn_fa.S_.T).flatten(), 'bo')\n", "plt.xlabel(\"True latent response inner product\")\n", "plt.ylabel(\"Estimated latent response inner product\")\n", "\n", "plt.figure()\n", "plt.plot( (B.T @ B).flatten(), (mn_fa.B_.T @ mn_fa.B_ ).flatten(),'bo')\n", "plt.xlabel(\"True weight matrix inner product\")\n", "plt.ylabel(\"Estimated weight matrix inner product\")\n" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0, 0.5, 'Estimated weight matrix inner product')" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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\n", 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Dual, integrating the other way\n", "mn_fa = MNFactorAnalysis(time_cov=time_cov, space_cov=space_cov, n_features=components, dual=True)\n", "\n", "mn_fa.fit(Y_tf, naive_init=False)\n", "\n", "plt.plot((S @ B).flatten(),(mn_fa.S_ @ mn_fa.B_).flatten(), 'bo')\n", "plt.xlabel(\"True (noiseless) voxel time series\")\n", "plt.ylabel(\"Reconstructed noiseless voxel time series\")\n", "\n", "plt.figure()\n", "plt.plot( (S @ S.T).flatten(),(mn_fa.S_ @ mn_fa.S_.T).flatten(), 'bo')\n", "plt.xlabel(\"True latent response inner product\")\n", "plt.ylabel(\"Estimated latent response inner product\")\n", "\n", "plt.figure()\n", "plt.plot( (B.T @ B).flatten(), (mn_fa.B_.T @ mn_fa.B_ ).flatten(),'bo')\n", "plt.xlabel(\"True weight matrix inner product\")\n", "plt.ylabel(\"Estimated weight matrix inner product\")\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Summary\n", "\n", "This demonstrates how `brainiak.matnormal` supports prototyping of models with kronecker-separable residuals. Again we highlight that while the specific model variants here can be implemented more efficiently, the shared and consistent framing provided by the matrix-normal framework can allow us to showcase the similarity across methods, as well as introduce a consistent idea (e.g. a particular residual structure) to different models in a consistent way. \n", "\n", "We invite further contributions and suggestions in helping us use `brainiak.matnormal` to blur the lines between methods-developer and methods-user. " ] } ], "metadata": { "kernelspec": { "display_name": "Python [conda env:brainiak] *", "language": "python", "name": "conda-env-brainiak-py" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.10" } }, "nbformat": 4, "nbformat_minor": 4 }