{ "cells": [ { "cell_type": "markdown", "id": "b0dd5244", "metadata": {}, "source": [ "## Installing and so on" ] }, { "cell_type": "code", "execution_count": 1, "id": "5927c847", "metadata": {}, "outputs": [], "source": [ "%load_ext autoreload\n", "%autoreload 2" ] }, { "cell_type": "markdown", "id": "199a4ab6", "metadata": {}, "source": [ "Do a `uv sync --extra examples` to install the required dependencies\n" ] }, { "cell_type": "code", "execution_count": 10, "id": "8cb57f96", "metadata": {}, "outputs": [], "source": [ "import sys\n", "import os\n", "sys.path.append(os.path.abspath('..'))\n", "\n", "from yanat import generative_game_theoric as gen\n", "from yanat import utils as ut\n", "from vizman import viz\n", "import seaborn as sns\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import netneurotools.datasets as nntd\n", "from scipy.spatial.distance import pdist, squareform" ] }, { "cell_type": "markdown", "id": "f51c7762", "metadata": {}, "source": [ "For better plots" ] }, { "cell_type": "code", "execution_count": 3, "id": "c9709674", "metadata": {}, "outputs": [], "source": [ "viz.set_visual_style()" ] }, { "cell_type": "markdown", "id": "fb77b013", "metadata": {}, "source": [ "## Fetching a human connectome from netneurotools" ] }, { "cell_type": "code", "execution_count": 4, "id": "d8a9ac78", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Please cite the following papers if you are using this function:\n", " [primary]:\n", " \n", " [celegans]:\n", " Lav R Varshney, Beth L Chen, Eric Paniagua, David H Hall, and Dmitri B Chklovskii. Structural properties of the caenorhabditis elegans neuronal network. PLoS computational biology, 7(2):e1001066, 2011.\n", " [drosophila]:\n", " Ann-Shyn Chiang, Chih-Yung Lin, Chao-Chun Chuang, Hsiu-Ming Chang, Chang-Huain Hsieh, Chang-Wei Yeh, Chi-Tin Shih, Jian-Jheng Wu, Guo-Tzau Wang, Yung-Chang Chen, and others. Three-dimensional reconstruction of brain-wide wiring networks in drosophila at single-cell resolution. Current biology, 21(1):1–11, 2011.\n", " [human]:\n", " Alessandra Griffa, Yasser Alemán-Gómez, and Patric Hagmann. Structural and functional connectome from 70 young healthy adults [data set]. Zenodo, 2019.\n", " [macaque_markov]:\n", " Nikola T Markov, Maria Ercsey-Ravasz, Camille Lamy, Ana Rita Ribeiro Gomes, Loïc Magrou, Pierre Misery, Pascale Giroud, Pascal Barone, Colette Dehay, Zoltán Toroczkai, and others. The role of long-range connections on the specificity of the macaque interareal cortical network. Proceedings of the National Academy of Sciences, 110(13):5187–5192, 2013.\n", " [macaque_modha]:\n", " Dharmendra S Modha and Raghavendra Singh. Network architecture of the long-distance pathways in the macaque brain. Proceedings of the National Academy of Sciences, 107(30):13485–13490, 2010.\n", " [mouse]:\n", " Mikail Rubinov, Rolf JF Ypma, Charles Watson, and Edward T Bullmore. Wiring cost and topological participation of the mouse brain connectome. Proceedings of the National Academy of Sciences, 112(32):10032–10037, 2015.\n", " [rat]:\n", " Mihail Bota, Olaf Sporns, and Larry W Swanson. Architecture of the cerebral cortical association connectome underlying cognition. Proceedings of the National Academy of Sciences, 112(16):E2093–E2101, 2015.\n", "Dataset ds-famous_gmat already exists. Skipping download.\n" ] } ], "source": [ "human_struct = nntd.fetch_famous_gmat(\"human_struct_scale033\")" ] }, { "cell_type": "code", "execution_count": 5, "id": "3de24d9a", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "dict_keys(['labels', 'conn', 'coords', 'dist'])" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "human_struct.keys()" ] }, { "cell_type": "code", "execution_count": 6, "id": "b6f16412", "metadata": {}, "outputs": [], "source": [ "connectivity = ut.minmax_normalize(human_struct[\"conn\"])\n", "coordinates = human_struct[\"coords\"]" ] }, { "cell_type": "code", "execution_count": 7, "id": "35726909", "metadata": {}, "outputs": [], "source": [ "euclidean_distance = squareform(pdist(coordinates))" ] }, { "cell_type": "code", "execution_count": 11, "id": "929f7455", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" }, { "data": { 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sns.heatmap(connectivity)" ] }, { "cell_type": "markdown", "id": "984db128", "metadata": {}, "source": [ "Example of how nodes can have different resources based on empirical data. To be the most parsimonious, you can leave this out. To be more topographically accurate, you can include it. Of course you can define this based on anything else you want e.g., genetics or cytoarchitectonic features." ] }, { "cell_type": "code", "execution_count": 12, "id": "173bea48", "metadata": {}, "outputs": [], "source": [ "resource = connectivity.sum(0)/(connectivity.sum(0).max()) " ] }, { "cell_type": "markdown", "id": "81b23a4f", "metadata": {}, "source": [ "The model is fitted to the density of the empirical connectivity matrix:" ] }, { "cell_type": "code", "execution_count": 13, "id": "32d5ba44", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "np.float64(0.30976919727101176)" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ut.find_density(connectivity)" ] }, { "cell_type": "markdown", "id": "8f3d2887", "metadata": {}, "source": [ "## Fitting the trade-off parameter:" ] }, { "cell_type": "markdown", "id": "9fe22fdb", "metadata": {}, "source": [ "The model has a coefficient for 'wiring benefit' called `alpha` and one to scale wiring cost called `beta`. I usually set that to 1 but note that both (and pretty much all other) parameters can be time-varying. `Penalty` adds a penalty to the payoff for each node, encouraging them to connect to avoid fragmented graphs. This is usually not needed but it can be useful to prevent fragmentation given some metrics. `Batch size` is the number of nodes to be updated at once so higher means slower computation but faster convergence. `Payoff tolerance` is the threshold for the change in payoff to be considered worthy. Think of it as a learning rate. If set to zero, it will converge but will continue going through local updates that are driven by numerical noise (in symmetric networks). In directed graphs, and of course given the metric, it converges to a unique solution that is a Nash Equilibrium. To prevent that little fight after convergence in symmetric networks, you can slowly raise the tolerance to make insignificant payoff differences not worthy. `Weight` is the coefficient of the exponential decay on weights of the generated networks. If this is zero, the networks are evaluated as binary. Otherwise, they'll get weights based on the euclidean distance with longer connections having exponentially less weight. `Resource scaling` is the scaling of the resource available to the nodes. Things depend on the metric so you need to find the right balance for these, or leave them out and just go with `alpha` alone to be the most parsimonious (but also binary). Anyway, let's try this bad boy:" ] }, { "cell_type": "code", "execution_count": 14, "id": "fc3e51c6", "metadata": {}, "outputs": [], "source": [ "n_iterations = 3000 # this needs to be higher depending on the metric.\n", "beta_vec = np.ones(n_iterations)\n", "penalty_vec = np.zeros(n_iterations)\n", "batch_size_vec = np.full(n_iterations, 10)\n", "payoff_tolerance_vec = 10 * (1 - np.exp(-2 * np.linspace(0, 1, n_iterations)))\n", "weight = 0.1\n", "resource_scaling = 10" ] }, { "cell_type": "code", "execution_count": 15, "id": "2620a56f", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[]" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.plot(payoff_tolerance_vec)" ] }, { "cell_type": "markdown", "id": "7b4e2031", "metadata": {}, "source": [ "We'll be using propagation dynamics here with a spatial decay of 0.9. Read here if you want to know more about it: https://doi.org/10.7554/eLife.101780\n", "We use a bisection method to find the optimal alpha with a tolerance of 0.01 difference between the empirical and synthetic density. The maximum number of iterations is 10 and I never exceeded it so far." ] }, { "cell_type": "code", "execution_count": 16, "id": "7cfe67fb", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Simulating network evolution: 3%|▎ | 85/2999 [00:06<00:47, 61.28it/s] /Users/kf02/Library/Mobile Documents/com~apple~CloudDocs/Work/Projects/YANAT/YANAT/yanat/utils.py:49: RuntimeWarning: divide by zero encountered in log\n", " return np.nan_to_num(np.log(adjacency_matrix), neginf=0, posinf=0)\n", "/Users/kf02/Library/Mobile Documents/com~apple~CloudDocs/Work/Projects/YANAT/YANAT/yanat/utils.py:49: RuntimeWarning: divide by zero encountered in log\n", " return np.nan_to_num(np.log(adjacency_matrix), neginf=0, posinf=0)\n", "/Users/kf02/Library/Mobile Documents/com~apple~CloudDocs/Work/Projects/YANAT/YANAT/yanat/utils.py:49: RuntimeWarning: divide by zero encountered in log\n", " return np.nan_to_num(np.log(adjacency_matrix), neginf=0, posinf=0)\n", "/Users/kf02/Library/Mobile Documents/com~apple~CloudDocs/Work/Projects/YANAT/YANAT/yanat/utils.py:49: RuntimeWarning: divide by zero encountered in log\n", " return np.nan_to_num(np.log(adjacency_matrix), neginf=0, posinf=0)\n", "/Users/kf02/Library/Mobile Documents/com~apple~CloudDocs/Work/Projects/YANAT/YANAT/yanat/utils.py:49: RuntimeWarning: divide by zero encountered in log\n", " return np.nan_to_num(np.log(adjacency_matrix), neginf=0, posinf=0)\n", "/Users/kf02/Library/Mobile Documents/com~apple~CloudDocs/Work/Projects/YANAT/YANAT/yanat/utils.py:49: RuntimeWarning: divide by zero encountered in log\n", " return np.nan_to_num(np.log(adjacency_matrix), neginf=0, posinf=0)\n", "/Users/kf02/Library/Mobile Documents/com~apple~CloudDocs/Work/Projects/YANAT/YANAT/yanat/utils.py:49: RuntimeWarning: divide by zero encountered in log\n", " return np.nan_to_num(np.log(adjacency_matrix), neginf=0, posinf=0)\n", "/Users/kf02/Library/Mobile Documents/com~apple~CloudDocs/Work/Projects/YANAT/YANAT/yanat/utils.py:49: RuntimeWarning: divide by zero encountered in log\n", " return np.nan_to_num(np.log(adjacency_matrix), neginf=0, posinf=0)\n", "/Users/kf02/Library/Mobile Documents/com~apple~CloudDocs/Work/Projects/YANAT/YANAT/yanat/utils.py:49: RuntimeWarning: divide by zero encountered in log\n", " return np.nan_to_num(np.log(adjacency_matrix), neginf=0, posinf=0)\n", "/Users/kf02/Library/Mobile Documents/com~apple~CloudDocs/Work/Projects/YANAT/YANAT/yanat/utils.py:49: RuntimeWarning: divide by zero encountered in log\n", " return np.nan_to_num(np.log(adjacency_matrix), neginf=0, posinf=0)\n", "Simulating network evolution: 3%|▎ | 94/2999 [00:06<00:43, 67.11it/s]/Users/kf02/Library/Mobile Documents/com~apple~CloudDocs/Work/Projects/YANAT/YANAT/yanat/utils.py:49: RuntimeWarning: divide by zero encountered in log\n", " return np.nan_to_num(np.log(adjacency_matrix), neginf=0, posinf=0)\n", "/Users/kf02/Library/Mobile Documents/com~apple~CloudDocs/Work/Projects/YANAT/YANAT/yanat/utils.py:49: RuntimeWarning: divide by zero encountered in log\n", " return np.nan_to_num(np.log(adjacency_matrix), neginf=0, posinf=0)\n", "/Users/kf02/Library/Mobile Documents/com~apple~CloudDocs/Work/Projects/YANAT/YANAT/yanat/utils.py:49: RuntimeWarning: divide by zero encountered in log\n", " return np.nan_to_num(np.log(adjacency_matrix), neginf=0, posinf=0)\n", "/Users/kf02/Library/Mobile Documents/com~apple~CloudDocs/Work/Projects/YANAT/YANAT/yanat/utils.py:49: RuntimeWarning: divide by zero encountered in log\n", " return np.nan_to_num(np.log(adjacency_matrix), neginf=0, posinf=0)\n", "/Users/kf02/Library/Mobile Documents/com~apple~CloudDocs/Work/Projects/YANAT/YANAT/yanat/utils.py:49: RuntimeWarning: divide by zero encountered in log\n", " return np.nan_to_num(np.log(adjacency_matrix), neginf=0, posinf=0)\n", "/Users/kf02/Library/Mobile Documents/com~apple~CloudDocs/Work/Projects/YANAT/YANAT/yanat/utils.py:49: RuntimeWarning: divide by zero encountered in log\n", " return np.nan_to_num(np.log(adjacency_matrix), neginf=0, posinf=0)\n", "Simulating network evolution: 100%|██████████| 2999/2999 [00:42<00:00, 70.80it/s]\n", "Simulating network evolution: 100%|██████████| 2999/2999 [00:37<00:00, 79.87it/s]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Initial range: alpha=[0.1, 200], density=[0.0005877167205406994, 0.39288862768145755]\n", "Target density: 0.31354687040846313\n", "Iteration 1: Testing alpha=159.57078651685393\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Simulating network evolution: 100%|██████████| 2999/2999 [00:37<00:00, 79.87it/s]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Alpha=159.57078651685393 → density=0.3643843667352336, diff from target=0.05083749632677048\n", "Iteration 2: Testing alpha=137.28609664010457\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Simulating network evolution: 100%|██████████| 2999/2999 [00:38<00:00, 78.71it/s]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Alpha=137.28609664010457 → density=0.35027916544225685, diff from target=0.036732295033793716\n", "Iteration 3: Testing alpha=122.87579237118602\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Simulating network evolution: 100%|██████████| 2999/2999 [00:39<00:00, 75.24it/s]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Alpha=122.87579237118602 → density=0.3379371143109021, diff from target=0.02439024390243899\n", "Iteration 4: Testing alpha=113.99914536177101\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Simulating network evolution: 100%|██████████| 2999/2999 [00:42<00:00, 70.43it/s]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Alpha=113.99914536177101 → density=0.3253012048192771, diff from target=0.011754334410813971\n", "Iteration 5: Testing alpha=109.87609937582457\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Simulating network evolution: 100%|██████████| 2999/2999 [00:40<00:00, 74.62it/s]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Alpha=109.87609937582457 → density=0.3241257713781957, diff from target=0.010578900969732574\n", "Iteration 6: Testing alpha=106.28669013192841\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Simulating network evolution: 100%|██████████| 2999/2999 [00:37<00:00, 78.97it/s]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Alpha=106.28669013192841 → density=0.3182486041727887, diff from target=0.0047017337643255885\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\n" ] } ], "source": [ "result=gen.find_optimal_alpha(\n", " distance_matrix=euclidean_distance,\n", " empirical_connectivity=connectivity,\n", " distance_fn=gen.propagation_distance,\n", " n_iterations=n_iterations, \n", " alpha_range=(0.1, 200), \n", " max_search_iterations=10,\n", " tolerance=0.01,\n", " payoff_tolerance=payoff_tolerance_vec,\n", " batch_size=batch_size_vec,\n", " node_resources=resource*resource_scaling,\n", " weight_coefficient=weight,\n", " spatial_decay = 0.9)" ] }, { "cell_type": "code", "execution_count": 17, "id": "41f7bfb7", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "dict_keys(['alpha', 'density', 'evolution'])" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "result.keys()" ] }, { "cell_type": "code", "execution_count": 18, "id": "c6e23e96", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(83, 83, 3000)" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "result[\"evolution\"].shape" ] }, { "cell_type": "code", "execution_count": 19, "id": "14d3476e", "metadata": {}, "outputs": [], "source": [ "from scipy.stats import spearmanr" ] }, { "cell_type": "code", "execution_count": 24, "id": "37cb496c", "metadata": {}, "outputs": [], "source": [ "weighted_adj = np.zeros_like(result[\"evolution\"])\n", "for network in range(result[\"evolution\"].shape[-1]):\n", " weighted_adj[...,network] = gen._apply_weighting(result[\"evolution\"][...,network],euclidean_distance,weight)\n" ] }, { "cell_type": "code", "execution_count": 25, "id": "5cc346e6", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[]" ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.plot(weighted_adj.mean((0,1)))" ] }, { "cell_type": "code", "execution_count": 27, "id": "a1813d9f", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/Users/kf02/Library/Mobile Documents/com~apple~CloudDocs/Work/Projects/YANAT/YANAT/yanat/utils.py:49: RuntimeWarning: divide by zero encountered in log\n", " return np.nan_to_num(np.log(adjacency_matrix), neginf=0, posinf=0)\n" ] }, { "data": { "text/plain": [ "" ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sns.scatterplot(x=ut.log_normalize(weighted_adj[...,-1]).flatten(),\n", " y=ut.log_normalize(connectivity).flatten())" ] }, { "cell_type": "code", "execution_count": 42, "id": "b037cf63", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "SignificanceResult(statistic=np.float64(0.44798373001772485), pvalue=np.float64(0.0))" ] }, "execution_count": 42, "metadata": {}, "output_type": "execute_result" } ], "source": [ "spearmanr(weighted_adj[...,-1].flatten(),connectivity.flatten())" ] }, { "cell_type": "markdown", "id": "58f7a012", "metadata": {}, "source": [ "This might seem good but I usually test against the value we get just from the euclidean distance." ] }, { "cell_type": "code", "execution_count": 43, "id": "c65121fe", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "SignificanceResult(statistic=np.float64(-0.4061853909430151), pvalue=np.float64(5.312447132311121e-272))" ] }, "execution_count": 43, "metadata": {}, "output_type": "execute_result" } ], "source": [ "spearmanr(euclidean_distance.flatten(),connectivity.flatten())" ] }, { "cell_type": "markdown", "id": "50a3f086", "metadata": {}, "source": [ "So, a bit better!" ] }, { "cell_type": "code", "execution_count": 30, "id": "be435e1d", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 30, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sns.heatmap(weighted_adj[...,-1])" ] }, { "cell_type": "code", "execution_count": 31, "id": "781f7ed8", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/Users/kf02/Library/Mobile Documents/com~apple~CloudDocs/Work/Projects/YANAT/YANAT/yanat/utils.py:49: RuntimeWarning: divide by zero encountered in log\n", " return np.nan_to_num(np.log(adjacency_matrix), neginf=0, posinf=0)\n" ] }, { "data": { "text/plain": [ "" ] }, "execution_count": 31, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "viz.plot_matrix(ut.log_minmax_normalize(weighted_adj[...,-1]))" ] }, { "cell_type": "code", "execution_count": 32, "id": "b6b21e23", "metadata": {}, "outputs": [], "source": [ "densities = [ut.find_density(result[\"evolution\"][...,i]) for i in range(result[\"evolution\"].shape[-1])]" ] }, { "cell_type": "code", "execution_count": 33, "id": "0086a7d4", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.plot(densities);" ] }, { "cell_type": "markdown", "id": "00ecac35", "metadata": {}, "source": [ "If you have a bunch of empirical networks with the same density, then all you have to do is to use the same parameters to generate synthetic ones. That optimization function is just calling this one under the hood. Here's how to make one:" ] }, { "cell_type": "code", "execution_count": 34, "id": "930f14c6", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Simulating network evolution: 100%|██████████| 2999/2999 [00:41<00:00, 71.60it/s]\n" ] } ], "source": [ "nets = gen.simulate_network_evolution(\n", " distance_matrix=euclidean_distance,\n", " n_iterations=n_iterations,\n", " distance_fn=gen.propagation_distance,\n", " alpha=result[\"alpha\"],\n", " beta=beta_vec,\n", " connectivity_penalty=penalty_vec,\n", " n_jobs=-1,\n", " random_seed=11,\n", " batch_size=batch_size_vec,\n", " payoff_tolerance=payoff_tolerance_vec,\n", " weight_coefficient=weight,\n", " node_resources=resource*resource_scaling,\n", " spatial_decay = 0.9\n", " )" ] }, { "cell_type": "code", "execution_count": 35, "id": "42c91425", "metadata": {}, "outputs": [], "source": [ "densities = [ut.find_density(nets[...,i]) for i in range(nets.shape[-1])]" ] }, { "cell_type": "code", "execution_count": 36, "id": "5760c9b3", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.plot(densities);" ] }, { "cell_type": "markdown", "id": "f5f44536", "metadata": {}, "source": [ "By default, synthetic networks are binary:" ] }, { "cell_type": "code", "execution_count": 37, "id": "3b84972c", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 37, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sns.heatmap(nets[...,-1])" ] }, { "cell_type": "markdown", "id": "fcbc3f77", "metadata": {}, "source": [ "We can check how well the degree distributions match." ] }, { "cell_type": "code", "execution_count": 38, "id": "97717068", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 38, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sns.scatterplot(x=nets[..., -1].sum(axis=1), \n", "y=connectivity.astype(bool).astype(int).sum(axis=1))" ] }, { "cell_type": "markdown", "id": "cf9a3bcd", "metadata": {}, "source": [ "And what stuff is missed" ] }, { "cell_type": "code", "execution_count": 39, "id": "726b831e", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 39, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sns.heatmap(connectivity.astype(bool)-nets[...,-1])" ] }, { "cell_type": "markdown", "id": "23d7cd2e", "metadata": {}, "source": [ "we can also look at the cosine similarity between the two networks to see how similar they are." ] }, { "cell_type": "code", "execution_count": 40, "id": "f685e2f1", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "np.float64(0.570789557808441)" ] }, "execution_count": 40, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from yanat.utils import calculate_endpoint_similarity\n", "calculate_endpoint_similarity(connectivity.astype(bool).astype(int), nets[...,-1]).mean()" ] }, { "cell_type": "markdown", "id": "ce46d397", "metadata": {}, "source": [ "Not bad actually. But what about the topography, i.e., the spatial distribution of edges" ] }, { "cell_type": "code", "execution_count": 41, "id": "609bab5d", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "SignificanceResult(statistic=np.float64(0.2150308148390282), pvalue=np.float64(0.05091255014113673))" ] }, "execution_count": 41, "metadata": {}, "output_type": "execute_result" } ], "source": [ "spearmanr(nets[..., -1].sum(axis=1), connectivity.astype(bool).astype(int).sum(axis=1))" ] }, { "cell_type": "markdown", "id": "89cc19e2", "metadata": {}, "source": [ "Also not bad but remember the resources have a role here. Anyway, here's an animation showing the whole wiring battle:" ] }, { "cell_type": "code", "execution_count": 50, "id": "ba2a03af", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Animation size has reached 20983227 bytes, exceeding the limit of 20971520.0. If you're sure you want a larger animation embedded, set the animation.embed_limit rc parameter to a larger value (in MB). This and further frames will be dropped.\n" ] }, { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "\n", "
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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from matplotlib import animation\n", "fig = plt.figure()\n", "\n", "ims = []\n", "for i in range(nets.shape[-1]):\n", " im = plt.imshow(nets[...,i], animated=True)\n", " ims.append([im])\n", "\n", "ani = animation.ArtistAnimation(fig, ims, interval=200, blit=True,\n", " repeat_delay=100)\n", "from IPython.display import HTML\n", "HTML(ani.to_jshtml())" ] }, { "cell_type": "code", "execution_count": null, "id": "05eda2c2", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": ".venv", "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": "3.11.13" } }, "nbformat": 4, "nbformat_minor": 5 }