{ "cells": [ { "cell_type": "markdown", "id": "a9b5c578-2027-49c7-aca0-945d95b707f4", "metadata": {}, "source": [ "# BDA (mean-centred PLS)\n", "\n", "Barycentric discriminant analysis (BDA; [Abdi and Williams, 2018](https://doi.org/10.1007/978-1-4614-7163-9_110192-2)), also known as mean-centred partial least squares (mean-centred PLS; [Krishnan et al., 2011](https://doi.org/10.1016/j.neuroimage.2010.07.034)) is a tool for identifying multivariate patterns that differentiate between multiple conditions. The basic idea is to perform singular value decomposition on a matrix of condition-wise averages (barycentres) whose columns have been mean-centred." ] }, { "cell_type": "markdown", "id": "1943dda1-b350-46f3-9219-d8171fd0e330", "metadata": {}, "source": [ "## Setting up simulated data\n", "\n", "We will simulate a dataset with a between-participants condition and a within-participants condition. There will be a main effect of between-participants condition, a main effect of within-participants condition, and an interaction (all orthogonal to each other). The pattern of the between-participants main effect will be linear over the observed variables and the pattern of both the within-participants main effect and the interaction will be sinusoidal over the observed variables" ] }, { "cell_type": "code", "execution_count": 1, "id": "aef18dba-df70-4cf1-8d3e-78017fc85bf5", "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import pandas as pd\n", "from pyplsc import BDA\n", "from matplotlib import pyplot as plt\n", "\n", "np.random.seed(123)\n", "\n", "n_var = 50\n", "n_subj = 30\n", "data = np.random.normal(size=(n_subj*2, n_var))\n", "design = pd.DataFrame({\n", " 'group': ['g-a']*n_subj + ['g-b']*n_subj,\n", " 'cond': ['c-a', 'c-b']*n_subj,\n", " 'subj': np.cumsum([1, 0]*n_subj)\n", "})\n", "between_effect = np.arange(n_var)/n_var - 0.5 # Linear pattern over observed variables\n", "within_effect = np.sin(0.2*np.arange(n_var)) # Sinusoidal pattern over observed variables\n", "interaction = np.cos(0.2*np.arange(n_var)) # Ditto\n", "data[design['group'] == 'g-b'] += between_effect\n", "data[design['cond'] == 'c-b'] += within_effect\n", "data[(design['group'] == 'g-b') & (design['cond'] == 'c-b')] += interaction\n", "data[(design['group'] == 'g-a') & (design['cond'] == 'c-a')] += interaction\n", "data[(design['group'] == 'g-a') & (design['cond'] == 'c-b')] -= interaction\n", "data[(design['group'] == 'g-b') & (design['cond'] == 'c-a')] -= interaction" ] }, { "cell_type": "markdown", "id": "1530c33b-836e-42d8-8674-ca369e65522c", "metadata": {}, "source": [ "We can visualize each of these patterns as follows:" ] }, { "cell_type": "code", "execution_count": 2, "id": "5f60a731-ff9c-44ec-880f-573b22a6d464", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "f, ax = plt.subplots(3, 1, sharex=True)\n", "ax[0].plot(between_effect)\n", "ax[0].set_title('Main effect of group')\n", "ax[1].plot(within_effect)\n", "ax[1].set_title('Main effect of condition')\n", "ax[2].plot(interaction)\n", "ax[2].set_title('Interaction')\n", "f.supxlabel('Observed variable')\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "65c31170-5895-4e9b-8e1c-5842f5d55fad", "metadata": {}, "source": [ "## Fitting and evaluating model\n", "\n", "Next, we can fit the BDA model to this data. We'll provide the design matrix and specify which columns correspond to the between- and within-participants factors, as well as which column differentiates participants (which is necessary when there is a within-participants factor):" ] }, { "cell_type": "code", "execution_count": 3, "id": "8795176f-0e6f-44f7-a094-77a7cb733ae9", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "mod = BDA(random_state=123)\n", "mod.fit(data,\n", " design,\n", " between='group',\n", " within='cond',\n", " participant='subj')" ] }, { "cell_type": "markdown", "id": "a31959d8-88f7-4170-a5d1-203e891b219c", "metadata": {}, "source": [ "We can assess the significance of each latent variable using permutation testing as follows:" ] }, { "cell_type": "code", "execution_count": 4, "id": "621ac9b1-8cc8-4113-8957-9b9293ac2009", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Getting permutations: 100%|██████████████████████████████████████████████████████| 1000/1000 [00:00<00:00, 1957.92it/s]\n", "Permuting: 100%|██████████████████████████████████████████████████████████████████| 1000/1000 [00:01<00:00, 918.24it/s]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "[0.000999 0.000999 0.000999 nan]\n", "[0 1 2]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\n" ] } ], "source": [ "mod.permute(1000)\n", "print(mod.pvals_)\n", "is_sig = mod.pvals_ < 0.05\n", "sig_lvs = np.where(is_sig)[0]\n", "print(sig_lvs)" ] }, { "cell_type": "markdown", "id": "94736f18-2332-4fb2-8d01-692b13648a4f", "metadata": {}, "source": [ "There are 3 significant latent variables (one for each effect we simulated). Note that mean-centering reduces the rank of the decomposed matrix by 1, such that the final singular value is always 0 and the final $p$ value is not meaningful. Next, we can perform bootstrap resampling to assess the reliability of the data saliences and to evaluate how reliably each latent variable is differentially expressed in each condition. Afterward, we will see how to visualize the results of this resampling." ] }, { "cell_type": "code", "execution_count": 5, "id": "8d07a243-564c-43c0-ba48-b13829d230d0", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Getting resamples: 100%|█████████████████████████████████████████████████████████| 1000/1000 [00:00<00:00, 2736.78it/s]\n", "Resampling: 100%|█████████████████████████████████████████████████████████████████| 1000/1000 [00:01<00:00, 819.77it/s]\n" ] } ], "source": [ "mod.bootstrap(1000, return_boot_stat_dist=False)" ] }, { "cell_type": "markdown", "id": "0e340e57-e645-42bb-a5a9-a20cd956bcb3", "metadata": {}, "source": [ "## Visualizing the model\n", "\n", "Bootstrap resampling yields two things: first, it estimates the standard deviation of the data saliences and thus allows us to estimate a z score or \"bootstrap ratio\" for each salience. Second, it allows us to estimate the variability of the average scores in each condition. These values are available in the `data_sals_z_` and `boot_stat_ci_` attributes, respectively. For plotting `boot_stat_ci_` in a `matplotlib` bar plot, the `get_boot_stat_yerr` method is useful:" ] }, { "cell_type": "code", "execution_count": 6, "id": "8c37e800-2b54-49be-8b41-827d4b7d41a7", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "labels = mod.design_sal_labels_\n", "labels = labels['between'].astype(str) + '_' + labels['within'].astype(str)\n", "n_sig = len(sig_lvs)\n", "\n", "fig = plt.figure(constrained_layout=True)\n", "subfigs = fig.subfigures(nrows=n_sig)\n", "\n", "for lv_idx in range(n_sig):\n", " subfig = subfigs[lv_idx]\n", " subfig.suptitle('LV %s (%.2f%% variance explained, p = %.3f)' % (\n", " lv_idx,\n", " 100*mod.variance_explained_[lv_idx],\n", " mod.pvals_[lv_idx]))\n", " ax = subfig.subplots(ncols=2)\n", " ax[0].bar(x=labels,\n", " height=mod.boot_stat_val_[:, lv_idx],\n", " yerr=mod.get_boot_stat_yerr(lv_idx))\n", " ax[0].set_ylabel('Data score')\n", " ax[1].plot(mod.data_sals_z_[:, lv_idx])\n", " ax[1].set_ylabel('Bootstrap ratio')" ] }, { "cell_type": "markdown", "id": "6f41f237-a168-47dd-a818-b751ef47718b", "metadata": {}, "source": [ "As we can see, the model approximately identifies both patterns and their differential expression as a function of between-participants group and within-participants condition. Note that because of the inherent sign ambiguity of SVD, the absolute signs of the data scores and bootstrap ratios for a given latent variable pair are arbitrary, and could both be flipped for interpretability with `.flip_signs(lv_idx)`." ] }, { "cell_type": "markdown", "id": "8202f870-f5a3-4543-8ef6-6a1fbda492d8", "metadata": {}, "source": [ "## Main effects and interactions\n", "\n", "When there are both within- and between-participants conditions, it is possible to selectively examine any combination of the main effects and the interaction. In the original Matlab PLS, the defualt behaviour (controlled in `plscmd` by `cfg.meancentering_mode = 0`) when there are both within- and between-participants conditions is to subtract any between-participants main effect in the mean-centering step, thereby examining only the within-participants main effect and the interaction. Matlab PLS also gives the option to subtract the within-participants main effect (`cfg.meancentering_mode = 1`) and to subtract both the within- and between-participants main effects, and thereby evaluate only the interaction (`cfg.meancentering_mode = 3`).\n", "\n", "In `pyplsc`, the effects modeled can be specified by the `effects` argument to `.fit()` as an iterable containing any combination of `'within'`, `'between'`, and `'interaction'`. For example, we can replicate the default behaviour of the original Matlab PLS for this simulated dataset as follows:" ] }, { "cell_type": "code", "execution_count": 7, "id": "696ace12-4f40-4aee-9de4-0aefd77a98dd", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "mod.fit(data,\n", " design,\n", " between='group',\n", " within='cond',\n", " participant='subj',\n", " effects=('within', 'interaction'))" ] }, { "cell_type": "markdown", "id": "3c4b9fb2-9834-46a7-b617-eb41740a8b65", "metadata": {}, "source": [ "Subtracting the between-participants main effect reduces the rank of the decomposed matrix by 1, so when we permute we can see that we have an additional null $p$ value:" ] }, { "cell_type": "code", "execution_count": 8, "id": "08be5ce6-81ac-4021-9e97-cea272d4400d", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Getting permutations: 100%|██████████████████████████████████████████████████████| 1000/1000 [00:00<00:00, 2226.63it/s]\n", "Permuting: 100%|██████████████████████████████████████████████████████████████████| 1000/1000 [00:01<00:00, 549.26it/s]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "[0.000999 0.000999 nan nan]\n", "[0 1]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\n" ] } ], "source": [ "mod.permute(1000)\n", "print(mod.pvals_)\n", "is_sig = mod.pvals_ < 0.05\n", "sig_lvs = np.where(is_sig)[0]\n", "print(sig_lvs)" ] }, { "cell_type": "markdown", "id": "7f46e409-0777-4e4f-9b69-98c4332cab99", "metadata": {}, "source": [ "As expected, the model now captures only the within-participants condition and the interaction:" ] }, { "cell_type": "code", "execution_count": 9, "id": "aca78555-3e64-454c-93e4-4c277af26d42", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Getting resamples: 100%|█████████████████████████████████████████████████████████| 1000/1000 [00:00<00:00, 3544.24it/s]\n", "Resampling: 100%|█████████████████████████████████████████████████████████████████| 1000/1000 [00:02<00:00, 485.28it/s]\n" ] }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "mod.bootstrap(1000, return_boot_stat_dist=False)\n", "labels = mod.design_sal_labels_\n", "labels = labels['between'].astype(str) + '_' + labels['within'].astype(str)\n", "n_sig = len(sig_lvs)\n", "\n", "fig = plt.figure(constrained_layout=True)\n", "subfigs = fig.subfigures(nrows=n_sig)\n", "\n", "for lv_idx in range(n_sig):\n", " subfig = subfigs[lv_idx]\n", " subfig.suptitle('LV %s (%.2f%% variance explained, p = %.3f)' % (\n", " lv_idx,\n", " 100*mod.variance_explained_[lv_idx],\n", " mod.pvals_[lv_idx]))\n", " ax = subfig.subplots(ncols=2)\n", " ax[0].bar(x=labels,\n", " height=mod.boot_stat_val_[:, lv_idx],\n", " yerr=mod.get_boot_stat_yerr(lv_idx))\n", " ax[0].set_ylabel('Data score')\n", " ax[1].plot(mod.data_sals_z_[:, lv_idx])\n", " ax[1].set_ylabel('Bootstrap ratio')" ] }, { "cell_type": "markdown", "id": "6e05defe-c7e2-465f-ba62-4ceb148d2c84", "metadata": {}, "source": [ "A natural next question is: can we also use specific pre-specified contrasts? We could, and the original Matlab PLS calls such an analysis \"non-rotated\" (in the sense of not involving SVD). However, the _raison d'etre_ of BDA is arguably that it identifies _data-driven_ contrasts in the form of the design saliences. This data was carefully simulated so that all the effects would be orthogonal, but real data is rarely so tidy and the design saliences are often a blend of multiple main effects and interactions. For examining structured effects, an approach like multivariate ANOVA or ANOVA-simultaneous component analysis is better suited." ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.13.2" } }, "nbformat": 4, "nbformat_minor": 5 }