{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Exercise 10.1\n", "## Signal Classification using Dynamic Graph Convolutional Neural Networks\n", "After a long journey through the universe before reaching the earth, the cosmic particles interact with the galactic magnetic field $B$.\n", "As these particles carry a charge $q$ they are deflected in the field by the Lorentz force $F = q \\cdot v × B$.\n", "Sources of cosmic particles are located all over the sky, thus arrival distributions of the cosmic particles are isotropic in general. However, particles originating from the same source generate on top of the isotropic\n", "arrival directions, street-like patterns from galactic magnetic field deflections.\n", "\n", "In this tasks we want to classify whether a simulated set of $500$ arriving cosmic particles contains street-like patterns (signal), or originates from an isotropic background.\n", "\n", "Training graph networks can be computationally demanding, thus, we recommend to use a GPU for this task." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "keras 2.4.0\n" ] } ], "source": [ "from tensorflow import keras\n", "import numpy as np\n", "from matplotlib import pyplot as plt\n", "\n", "layers = keras.layers\n", "\n", "print(\"keras\", keras.__version__)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Download EdgeConv Layer" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "import gdown\n", "import os\n", "\n", "url = \"https://raw.githubusercontent.com/DeepLearningForPhysicsResearchBook/deep-learning-physics/main/edgeconv.py\"\n", "output = 'edgeconv.py'\n", "\n", "if os.path.exists(output) == False:\n", " gdown.download(url, output, quiet=False)\n", "\n", "from edgeconv import EdgeConv" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Download Data" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "url = \"https://drive.google.com/u/0/uc?export=download&confirm=HgGH&id=1XKN-Ik7BDyMWdQ230zWS2bNxXL3_9jZq\"\n", "output = 'cr_sphere.npz'\n", "\n", "if os.path.exists(output) == False:\n", " gdown.download(url, output, quiet=True)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "f = np.load(output)\n", "n_train = 10000\n", "x_train, x_test = f['data'][:-n_train], f['data'][-n_train:]\n", "labels = keras.utils.to_categorical(f['label'], num_classes=2)\n", "y_train, y_test = labels[:-n_train], labels[-n_train:]" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "x_train.shape (40000, 500, 4)\n", "y_train.shape (40000, 2)\n" ] } ], "source": [ "print(\"x_train.shape\", x_train.shape)\n", "print(\"y_train.shape\", y_train.shape)" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "# define coordinates for very first EdgeConv\n", "train_points, test_points = x_train[..., :3], x_test[..., :3]\n", "\n", "# Use normalized Energy as features for convolutional layers\n", "train_features, test_features = x_train[..., -1, np.newaxis], x_test[..., -1, np.newaxis]\n", "train_features = np.concatenate([train_features, train_points], axis=-1)\n", "\n", "train_input_data = [train_points, train_features]\n", "test_input_data = [test_points, test_features]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Plot an example sky map" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "def scatter(v, c=None, zlabel=\"\", title=\"\", **kwargs):\n", "\n", " def vec2ang(v):\n", " x, y, z = np.asarray(v)\n", " phi = np.arctan2(y, x)\n", " theta = np.arctan2(z, (x * x + y * y) ** .5)\n", " return phi, theta\n", "\n", " lons, lats = vec2ang(v)\n", " lons = -lons\n", " fig = plt.figure(figsize=kwargs.pop('figsize', [12, 6]))\n", " ax = fig.add_axes([0.1, 0.1, 0.85, 0.9], projection=\"hammer\")\n", " events = ax.scatter(lons, lats, c=c, s=12, lw=2)\n", "\n", " cbar = plt.colorbar(events, orientation='horizontal', shrink=0.85, pad=0.05, aspect=30, label=zlabel)\n", " plt.xticks(fontsize=16)\n", " plt.yticks(fontsize=16)\n", " return fig\n", "\n", "\n", "test_id = 0\n", "example_map = x_test[test_id]\n", "fig = scatter(example_map[:, 0:3].T, c=example_map[:, 3], zlabel=\"Energy (normed)\", title = \"Event %i\" % test_id)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Design DGCNN" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Start with defining a kernel network\n", "Design a kernel network. The input to the kernel network is the central pixel coordinate and the neighborhood pixel coordinates.\n", "Hint: using `layers.BatchNormalization` can help to stabilize the training process of a DGCNN.\n", "\n", "You can make use of the code snippet below.\n", "\n", "Note that the output of the DNN should be `(None, nodes)`, where `None` is a placeholder for the batch size." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "def kernel_nn(data, nodes=16):\n", " d1, d2 = data # get xi (\"central\" pixel) and xj (\"neighborhood\" pixels)\n", "\n", " return x" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Build complete graph network model\n", "In the first layer, it might be advantageous to choose the next neighbors using the coordinates of the cosmic ray but perform the convolution using their energies also.\n", "Thus, we input `y = EdgeConv(...)[points_input, feats_input]` into the first EdgeConv layer. \n", "If we later want to perform a dynamic EdgeConv (we want to update the graph), we simply input `z = EdgeConv(...)([y, y])`.\n", "\n", "To specify the size of the \"convolutional filter\", make use of the `next_neighbors` argument (searches for $k$ next neighbors for each cosmic ray). " ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "points_input = layers.Input((500, 3))\n", "feats_input = layers.Input((500, 4))\n", "\n", "x = EdgeConv(lambda a: kernel_nn(a, nodes=8), next_neighbors=5)([points_input, feats_input]) # conv with fixed graph\n", "x = layers.Activation(\"relu\")(x)\n", "...\n", "out = layers.Dense(2, name=\"classification\", activation=\"softmax\")(x)\n", "\n", "model = keras.models.Model([points_input, feats_input], out)\n", "print(model.summary())" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "You can inspect the kernel network using:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "model.layers[2].kernel_func.summary()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Train the model" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "model.compile(...)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "history = model.fit(train_input_data, y_train, batch_size=64, epochs=10)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Visualization of the underlying graph\n", "To inspect the changing neighborhood relation (we used a DGCNN) of the nodes, we visualize the underlying graph structure.\n", "\n", "Note that plotting may take some time, so be a bit patient." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To perform the relative complex plotting, we make use of networkx and sklearn. \n", "If you don't have installed the packages yet, run the cell below." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "import sys\n", "!{sys.executable} -m pip install sklearn\n", "!{sys.executable} -m pip install networkx" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "import tensorflow.keras.backend as K\n", "from sklearn.neighbors import kneighbors_graph\n", "import networkx as nx\n", "\n", "edge_layers = [l for l in model.layers if \"edge_conv\" in l.name]\n", "coord_mask = [np.sum(np.linalg.norm(inp_d[test_id], axis=-1)) == 500 for inp_d in train_input_data]\n", "assert True in coord_mask, \"For plotting the spherical graph at least one input has to have 3 dimensions XYZ\"\n", "fig, axes = plt.subplots(ncols=len(edge_layers), figsize=(5 * len(edge_layers), 5))\n", "\n", "for i, e_layer in enumerate(edge_layers):\n", " points_in, feats_in = model.inputs\n", " coordinates = e_layer.get_input_at(0)\n", " functor = K.function(model.inputs, coordinates)\n", " sample_input = [inp[np.newaxis, test_id] for inp in train_input_data]\n", "\n", " if type(e_layer.input) == list:\n", " layer_points, layer_features = functor(sample_input)\n", " else:\n", " layer_points = functor(sample_input)\n", "\n", " layer_points = np.squeeze(layer_points)\n", " adj = kneighbors_graph(layer_points, e_layer.next_neighbors)\n", " g = nx.DiGraph(adj)\n", "\n", " for c, s in zip(coord_mask, sample_input):\n", " if c == True:\n", " pos = s\n", " break\n", "\n", " axes[i].set_title(\"Graph in %s\" % e_layer.name)\n", " nx.draw(g, cmap=plt.get_cmap('viridis'), pos=pos.squeeze()[:, :-1],\n", " node_size=10, width=0.5, arrowsize=5, ax=axes[i])\n", " axes[i].axis('equal')" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.9" } }, "nbformat": 4, "nbformat_minor": 4 }