{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Testing out new kde-based method!\n", "> so many bins :)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "![](assets/kde_interesting.gif)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "import jax\n", "import neos.makers as makers\n", "import neos.cls as cls\n", "import numpy as np\n", "import jax.experimental.stax as stax\n", "import jax.experimental.optimizers as optimizers\n", "import jax.random\n", "import time\n", "\n", "import pyhf\n", "pyhf.set_backend(pyhf.tensor.jax_backend())" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# regression net\n", "init_random_params, predict = stax.serial(\n", " stax.Dense(1024),\n", " stax.Relu,\n", " stax.Dense(1024),\n", " stax.Relu,\n", " stax.Dense(1),\n", " stax.Sigmoid \n", ")" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.08" ] }, "execution_count": null, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bins = np.linspace(0,1,6)\n", "centers = bins[:-1] + np.diff(bins)/2.\n", "bandwidth = .4 * 1/(len(bins)-1)\n", "\n", "hmaker = makers.kde_bins_from_nn_three_blobs(predict,bins=bins,bandwidth=bandwidth)\n", "nnm = makers.nn_hepdata_like(hmaker)\n", "loss = cls.cls_maker(nnm, solver_kwargs=dict(pdf_transform=True))\n", "bandwidth" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Randomly initialise nn weights and check that we can get the gradient of the loss wrt nn params" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(DeviceArray(0.05880111, dtype=float64),\n", " [(DeviceArray([[-0.00179044, -0.00056627, 0.00202215, ..., -0.00396901,\n", " -0.00175673, -0.00723417],\n", " [-0.00017432, -0.00024473, -0.00143037, ..., -0.00237224,\n", " -0.00317624, -0.00390435]], dtype=float32),\n", " DeviceArray([ 0.00124554, -0.00019967, -0.00139115, ..., -0.00029852,\n", " -0.00180919, -0.00188678], dtype=float32)),\n", " (),\n", " (DeviceArray([[-2.70764849e-05, -6.28665646e-07, -1.20917028e-08, ...,\n", " 4.85653118e-06, -8.11458813e-05, 3.06508809e-05],\n", " [ 2.83182326e-05, 3.31130068e-05, 4.30183434e-07, ...,\n", " 0.00000000e+00, 1.55358535e-07, -2.02215233e-07],\n", " [-1.45628455e-05, -2.74914839e-07, -5.74184167e-09, ...,\n", " 2.39836436e-06, -6.88106229e-05, 3.14157187e-05],\n", " ...,\n", " [-3.00191073e-06, 7.77033274e-05, 9.19293257e-07, ...,\n", " 1.99842589e-06, -2.74845777e-04, 1.59332907e-04],\n", " [ 1.02543192e-04, 1.23361606e-04, 1.59768263e-06, ...,\n", " 3.53127803e-08, -5.06841570e-06, 4.16561761e-06],\n", " [ 5.91500029e-05, 8.81387532e-05, 1.13218164e-06, ...,\n", " 0.00000000e+00, -9.30895840e-06, 6.57422561e-06]], dtype=float32),\n", " DeviceArray([ 1.0152139e-03, 1.3619895e-03, 1.7323653e-05, ...,\n", " 4.6312110e-05, -1.7732537e-03, 8.8287907e-04], dtype=float32)),\n", " (),\n", " (DeviceArray([[-0.00040312],\n", " [-0.00372409],\n", " [-0.00373478],\n", " ...,\n", " [ 0.000288 ],\n", " [ 0.0022565 ],\n", " [ 0.00162871]], dtype=float32),\n", " DeviceArray([-0.0001226], dtype=float32)),\n", " ()])" ] }, "execution_count": null, "metadata": {}, "output_type": "execute_result" } ], "source": [ "gradd = jax.jit(jax.value_and_grad(loss))\n", "_, network = init_random_params(jax.random.PRNGKey(13), (-1, 2))\n", "gradd(network, 1.0)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Define training loop!" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "#jit_loss = jax.jit(loss)\n", "\n", "opt_init, opt_update, opt_params = optimizers.adam(3e-3)\n", "\n", "#@jax.jit\n", "def update_and_value(i, opt_state, mu):\n", " net = opt_params(opt_state)\n", " value, grad = jax.value_and_grad(loss)(net, mu)\n", " return opt_update(i, grad, state), value, net\n", "\n", "def train_network(N):\n", " cls_vals = []\n", " _, network = init_random_params(jax.random.PRNGKey(1), (-1, 2))\n", " state = opt_init(network)\n", " losses = []\n", " \n", " # parameter update function\n", " #@jax.jit\n", " def update_and_value(i, opt_state, mu):\n", " net = opt_params(opt_state)\n", " value, grad = jax.value_and_grad(loss)(net, mu)\n", " return opt_update(i, grad, state), value, net\n", " \n", " for i in range(N):\n", " start_time = time.time()\n", " state, value, network = update_and_value(i,state,1.0)\n", " epoch_time = time.time() - start_time\n", " losses.append(value)\n", " metrics = {\"loss\": losses}\n", " yield network, metrics, epoch_time" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Plotting helper function for awesome animations :)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "def plot(axarr, network, metrics, hm, maxN):\n", " ax = axarr[0]\n", " g = np.mgrid[-5:5:101j, -5:5:101j]\n", " levels = bins\n", " ax.contourf(\n", " g[0],\n", " g[1],\n", " predict(network, np.moveaxis(g, 0, -1)).reshape(101, 101, 1)[:, :, 0],\n", " levels=levels,\n", " cmap=\"jet\",\n", " )\n", " ax.contour(\n", " g[0],\n", " g[1],\n", " predict(network, np.moveaxis(g, 0, -1)).reshape(101, 101, 1)[:, :, 0],\n", " colors=\"w\",\n", " levels=levels,\n", " )\n", " ax.scatter(hm.sig[:, 0], hm.sig[:, 1], alpha=0.25, c=\"C9\", label=\"sig\")\n", " ax.scatter(hm.bkg1[:, 0], hm.bkg1[:, 1], alpha=0.17, c=\"C1\", label=\"bkg1\")\n", " ax.scatter(hm.bkg2[:, 0], hm.bkg2[:, 1], alpha=0.17, c=\"C1\", label=\"bkg2\")\n", " ax.set_xlim(-5, 5)\n", " ax.set_ylim(-5, 5)\n", " ax.set_xlabel(\"x\")\n", " ax.set_ylabel(\"y\")\n", "\n", " ax = axarr[1]\n", " ax.axhline(0.05, c=\"slategray\", linestyle=\"--\")\n", " ax.plot(metrics[\"loss\"], c=\"steelblue\", linewidth=2.0)\n", "\n", " ax.set_ylim(0, 0.6)\n", " ax.set_xlim(0, maxN)\n", " ax.set_xlabel(\"epoch\")\n", " ax.set_ylabel(r\"$cl_s$\")\n", "\n", " ax = axarr[2]\n", " nn = s, b, db = hm(network)\n", " bin_width = 1/(len(bins)-1)\n", " ax.bar(centers, b, color=\"C1\", label=\"bkg\",width=bin_width)\n", " ax.bar(centers, s, bottom=b, color=\"C9\", label=\"sig\",width=bin_width)\n", " ax.bar(centers, db, bottom=b - db / 2.0, alpha=0.4, color=\"black\", label=\"bkg error\",width=bin_width)\n", " ax.set_ylim(0, 100)\n", " ax.set_ylabel(\"frequency\")\n", " ax.set_xlabel(\"nn output\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Install celluloid for animations!" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "!python -m pip install celluloid" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Let's run it!!" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "epoch 0: CLs = 0.061524204700417195, took 7.181300163269043s\n", "epoch 1: CLs = 0.038272014302923596, took 1.3694071769714355s\n", "epoch 2: CLs = 0.0038476321388671852, took 1.3954288959503174s\n", "epoch 3: CLs = 0.04351751517576652, took 1.365785837173462s\n", "epoch 4: CLs = 0.006314677268905777, took 1.3489091396331787s\n", "epoch 5: CLs = 0.0019261697248236231, took 1.3820810317993164s\n", "epoch 6: CLs = 0.0028004005358872597, took 1.3562629222869873s\n", "epoch 7: CLs = 0.002297108891974986, took 1.3525168895721436s\n", "epoch 8: CLs = 0.010675734361591749, took 1.348271131515503s\n", "epoch 9: CLs = 0.01199155502521454, took 1.3472709655761719s\n", "epoch 10: CLs = 0.00762593726609162, took 1.3535170555114746s\n", "epoch 11: CLs = 0.0032174685672372583, took 1.370344877243042s\n", "epoch 12: CLs = 0.001166807205252418, took 1.3701229095458984s\n", "epoch 13: CLs = 0.0004404550097800719, took 1.3815929889678955s\n", "epoch 14: CLs = 0.0004199528500352656, took 1.3516571521759033s\n", "epoch 15: CLs = 0.00043441462951632204, took 1.3560807704925537s\n", "epoch 16: CLs = 0.00042500279217305703, took 1.341277837753296s\n", "epoch 17: CLs = 0.00042511235116404755, took 1.361943006515503s\n", "epoch 18: CLs = 0.00043839415488466926, took 1.3481249809265137s\n", "epoch 19: CLs = 0.0004592491846160396, took 1.3479270935058594s\n", "epoch 20: CLs = 0.0004820709901054432, took 1.3617238998413086s\n", "epoch 21: CLs = 0.0005027081616038043, took 1.3702890872955322s\n", "epoch 22: CLs = 0.0005197880109817365, took 1.3762280941009521s\n", "epoch 23: CLs = 0.0005333018659892108, took 1.3563430309295654s\n", "epoch 24: CLs = 0.0005436285357709458, took 1.349862813949585s\n", "epoch 25: CLs = 0.000551007436950357, took 1.345383882522583s\n", "epoch 26: CLs = 0.000554992768869722, took 1.3663418292999268s\n", "epoch 27: CLs = 0.0005553554655504112, took 1.365978717803955s\n", "epoch 28: CLs = 0.0005524540322388027, took 1.3484511375427246s\n", "epoch 29: CLs = 0.0005461374322499601, took 1.3595550060272217s\n", "epoch 30: CLs = 0.000536697891139859, took 1.3438730239868164s\n", "epoch 31: CLs = 0.0005243710673876745, took 1.3666539192199707s\n", "epoch 32: CLs = 0.0005091909195142907, took 1.3533861637115479s\n", "epoch 33: CLs = 0.0004911840439387749, took 1.3540828227996826s\n", "epoch 34: CLs = 0.0004710972245902667, took 1.3600499629974365s\n", "epoch 35: CLs = 0.0004502861618211895, took 1.3401401042938232s\n", "epoch 36: CLs = 0.0004293846931564538, took 1.3844318389892578s\n", "epoch 37: CLs = 0.0004090827937917041, took 1.364354133605957s\n", "epoch 38: CLs = 0.000389510146778127, took 1.36216402053833s\n", "epoch 39: CLs = 0.00037028015231888034, took 1.349194049835205s\n", "epoch 40: CLs = 0.0003507029564255859, took 1.3452768325805664s\n", "epoch 41: CLs = 0.00032908757139238354, took 1.3685681819915771s\n", "epoch 42: CLs = 0.00030342042498654465, took 1.3600702285766602s\n", "epoch 43: CLs = 0.0002772329277664909, took 1.3491170406341553s\n", "epoch 44: CLs = 0.0002695513717874132, took 1.7477397918701172s\n", "epoch 45: CLs = 0.0002922674396699243, took 1.377424955368042s\n", "epoch 46: CLs = 0.00030858496496199983, took 1.3887889385223389s\n", "epoch 47: CLs = 0.00030070589406672177, took 1.358922004699707s\n", "epoch 48: CLs = 0.000279831606425196, took 1.3844869136810303s\n", "epoch 49: CLs = 0.0002677123425813832, took 1.4390051364898682s\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "#slow\n", "import numpy as np\n", "from matplotlib import pyplot as plt\n", "from IPython.display import HTML\n", "\n", "plt.rcParams.update(\n", " {\n", " \"axes.labelsize\": 13,\n", " \"axes.linewidth\": 1.2,\n", " \"xtick.labelsize\": 13,\n", " \"ytick.labelsize\": 13,\n", " \"figure.figsize\": [13., 4.0],\n", " \"font.size\": 13,\n", " \"xtick.major.size\": 3,\n", " \"ytick.major.size\": 3,\n", " \"legend.fontsize\": 11,\n", " }\n", ")\n", "\n", "\n", "fig, axarr = plt.subplots(1, 3, dpi=120)\n", "\n", "maxN = 50 # make me bigger for better results!\n", "\n", "animate = False # animations fail tests...\n", "\n", "if animate:\n", " from celluloid import Camera\n", " camera = Camera(fig)\n", "\n", "# Training\n", "for i, (network, metrics, epoch_time) in enumerate(train_network(maxN)):\n", " print(f\"epoch {i}:\", f'CLs = {metrics[\"loss\"][-1]}, took {epoch_time}s')\n", " if animate:\n", " plot(axarr, network, metrics, nnm.hm, maxN=maxN)\n", " plt.tight_layout()\n", " camera.snap()\n", " if i % 10 == 0:\n", " camera.animate().save(\"animation.gif\", writer=\"imagemagick\", fps=8)\n", " #HTML(camera.animate().to_html5_video())\n", "if animate:\n", " camera.animate().save(\"animation.gif\", writer=\"imagemagick\", fps=8)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" } }, "nbformat": 4, "nbformat_minor": 4 }