mirror of
https://github.com/ImperialCollegeLondon/ReCoDE_MCMCFF.git
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450 lines
220 KiB
Plaintext
450 lines
220 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "5ac56056-ca33-4f13-8e36-564b94144c1e",
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"metadata": {
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"tags": []
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},
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"source": [
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"<h1 align=\"center\">Markov Chain Monte Carlo for fun and profit</h1>\n",
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"<h1 align=\"center\"> 🎲 ⛓️ 👉 🧪 </h1>"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 30,
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"id": "eb5d773e-4cc0-48ae-bb71-7ece7ab5f936",
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"import matplotlib.pyplot as plt\n",
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"from numba import jit\n",
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"\n",
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"# This loads some custom styles for matplotlib\n",
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"import json, matplotlib\n",
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"\n",
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"with open(\"assets/matplotlibrc.json\") as f:\n",
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" matplotlib.rcParams.update(json.load(f))\n",
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"\n",
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"np.random.seed(\n",
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" 42\n",
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") # This makes our random numbers reproducable when the notebook is rerun in order\n",
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"\n",
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"\n",
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"def show_state(state, ax=None):\n",
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" if ax is None:\n",
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" f, ax = plt.subplots()\n",
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" ax.matshow(state, cmap=\"Greys\", vmin=-1, vmax=1)\n",
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" ax.set(xticks=[], yticks=[])"
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]
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},
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{
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"cell_type": "markdown",
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"id": "337f1de8-d743-441f-bc15-387bcfff558d",
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"metadata": {
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"tags": []
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},
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"source": [
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"# Doing Monte Carlo!\n",
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"\n",
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"Now that we can evaluate the energy of a state there isn't that much more work to do Markov Chain Monte Carlo on it. I won't go into the details of how MCMC works but put very simply:\n",
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"\n",
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"We want to calculate thermal averages about a physical system. For example, is this bag of H20 molecules solid or liquid at T = -20C? Our Ising model is much simpler so the equivalent question would be what's the average color of this system at some T?\n",
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"\n",
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"It turns out that this question is pretty hard to answer using maths, it can be done for the 2D Ising model but for anything more complicated it's pretty much impossible. This is where MCMC comes in. MCMC is a numerical method that gives us a rule to probalistically jump from one state of the system to another. \n",
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"\n",
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"If we perform many such jumps many times we get a (Markov) chain of states. The great thing about this chain is that if we average a measurement over it, such as looking at the average proportion of white pixels, the answer we get will be close to the real answer for this system and will converge closer and closer to the true answer as we extend the chain. \n",
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"\n",
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"I've written a very basic MCMC sampler for the 2D Ising model below. It needs:\n",
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"- an initial start to start the chain\n",
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"- to know how many steps to take\n",
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"- the temperature we want to simulate at\n",
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"- a way to measure the energy of a state, which we wrote in a previous chapter\n",
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"\n",
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"It then loops over:\n",
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"- modify the state a little, here we just flip one bond\n",
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"- accepting $p = \\exp(-\\Delta_E / T)$ based on how the energy changed\n",
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"- if we rejected, change the state back to how it was"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "2586a542-35f2-419e-9aa2-2bb9e9ab74b9",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"image/png": 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1x6yZ3+cIHW4Zdlw7tkscc4kA57nH9KQNAAAAQEKKNgAAAAAJKdoAAAAAJKRoAwAAAJCQIGKAFekdHpk5iBLWam2hr6ey9D/LmM0JzsxyDplDjVsGgvYOF81is9k861xr52Tv8R7rx9T5cY77Z4lw9pp+1I7jnPux5fxY4t5rvRb1DtEea//q6mp0f0/aAAAAACSkaAMAAACQkKINAAAAQEKKNgAAAAAJCSIGWJG1hV0uofd4GG+oD2Nc+71xjhDL2zxGvdurbeu68M81mxOYPWWbc2jdj96hw7X7tgy8HdM7ILp1P3qbM7a9w4l3u93otp60AQAAAEhI0QYAAAAgIUUbAAAAgIQUbQAAAAASEkQMsHJrD7Fsrfd4GO9pTgP37t69u1BP2tlsNs86ryXCHWtlCRNtqXWw5dRg0iWCPrOEerK8/X4f2+32kdu1nDMtg45r1fZ1znlODWZuHTxes91Sa3rv404d36WC489xrTxpAwAAAJCQog0AAABAQoo2AAAAAAkp2gAAAAAkpGgDwI0Nw/CsF8vLfF1KKQ+89vv90l2i0um1u8mrpTnze2zfqe3V7tf7fuw93ktpeV1aXvfM7oWi95rfY6/a+Td1rRjbpvUaUNPf1uc+tW9T+99jXZjafu01nXrts9zbPfqhaAMAAACQkKINAAAAQEKKNgAAAAAJKdoAAAAAJKRoA5BUlkC1MZcagAk3sd/vV3UfZAgTXsqlnldvS7wPtbxWt2WOj61FLQOAx7QOBW4ZOjxH76DjllrP5anB3UvdZ0vcx1PHY8xNxkjRBgAAACAhRRsAAACAhBRtAAAAABJ63tIdAMjmus+nntslfM6e8zJnWFLLtXOpDK/T/tb241LvvTWd15r6upSa+dx6HKeuC2PbzFkXatubev5LtD/mHGM09RjXZShNddqP3tegth89eNIGAAAAICFFGwAAAICEFG0AAAAAElK0AQAAAEhIEDHAimQJSYaHuc3z9DYH17Y8p6XGZ2qg5CXM+annULvfJYxRVpvNZnLI8Ol+c67nUgHip1qHGNdoHQDc+5hZ7seW41bb1jnCmmv2uwlP2gAAAAAkpGgDAAAAkJCiDQAAAEBCijYAAAAACQkiBjhxCcGIWQLmuJ3MNbJZIiB1iWDSOWqPWXNelxCQuib7/T622+0DX+sdit46bLr3PbpE2G/Lc69t6xwhzDUBwEuEQY+Zcw163xtjdrvd6Nc9aQMAAACQkKINAAAAQEKKNgAAAAAJKdoAAAAAJCSIGOACCW2E/jabzSLBimuyRKisa9JO77F0rc5rauBt6+vUsr05IbhTz7V1uG2Wn9mmXpfW471EAPAcNf2d2zdP2gAAAAAkpGgDAAAAkJCiDQAAAEBCijYAAAAACQkiBliRLGF1rNsS4bA8qGXYZW+t54v5x5LG5t9ut1ugJ+fX8j5rHcbbOyR5agju2DatjzlV7TVoPW5T25pz7lOv1RJ69MOTNgAAAAAJKdoAAAAAJKRoAwAAAJCQog0AAABAQoKIAeCWEfraxn6/j+1226StSw1QnDrX5oSX9g7/bC3z/dgyhHQO4dX9tAxFn3Odpl7POfOgZt/W86zlmphF67W55f2e+f1grG9XV1ej23rSBgAAACAhRRsAAACAhBRtAAAAABJStAEAAABISBAxANDdafDf3bt3F+pJO5vNplmIZ5ZQ1Tn96B0Wu0R45JwA1sx69/dSwj/XrHcAcK2WYeGt+zp1Ts6Z33NCe6fuN6dvtcdt2Y+peodSR7Q997Gv7Xa70TY9aQMAAACQkKINAAAAQEKKNgAAAAAJybQBAJhgv9/HdrtduhsXKUsmSm1mxBLZN61zKlqO+Tmu1ekxsuRCrc3UcVwqT6W3llkycyxx7/XO+Om9Tra+LkvkMV2Xr+VJGwAAAICEFG0AAAAAElK0AQAAAEhI0QYAAAAgIUHEADzUOQL3gLamhn+2DpBdIjy4tyxrYm0gZu01WOJa9R63LNcqi5bXeE7ocM11yRJ0PKcfc+ba1EDk2rZaBgW3Xjta9rflnKzdrse640kbAAAAgIQUbQAAAAASUrQBAAAASEjRBgAAACAhQcQAcCa3ORTz9Dzv3LkTjz/++EK9aWOz2Tzrmi5xPeeEQNb0v/W8nRrk2LL9OcfoHS56m/QOeb0t4z22Fq1NTf9bhufeZN+peh/zHGHkY8doGQDc0py1o3Wo89R+XMeTNgAAAAAJKdoAAAAAJKRoAwAAAJCQog0AAABAQoKIAXio2xLkuJTbHE7Mzc0Jd5waoNgyxPc6Lds7Rxjl1PZ7a32tegeO1o6RNfHh9vt9bLfbSftODVEds8S9V6tlwPUS59QyJPgm7U19j6g9Zm17va/LEgHzY/3Y7Xaj23rSBgAAACAhRRsAAACAhBRtAAAAABJStAEAAABISBAxAJzJnKC708A6wZzLmxP+OVXr6551HmUJP24dlJs5sHhN7UdYEx9lTuhry/1aXpclgrZbH7N235ah6HPUnH/roOqp5szJcwSq1+x3dXU1uq0nbQAAAAASUrQBAAAASEjRBgAAACAhRRsAAACAhAQRAwDdnYb83b17d6Ge9JUlaLa33kGOrcM0a445pnU4ZZa5sET4J+dVe4/WBDqfIxi85phztptqzppeO2412y1xzNZavz9mWcemhtqP7bfb7Ub396QNAAAAQEKKNgAAAAAJKdoAAAAAJKRoAwAAAJCQIGIAWIG1h32e9v/OnTvx+OOPL9SbNjabTVUA4dSwxNbXvHdIcstgy95Bx621Dv9c+/1ee63mnOfax6il2rWoRusw2trrdHrcc4TntgwAHlPbt5pzXSoQeUyW97TeAfaZ1mZP2gAAAAAkpGgDAAAAkJCiDQAAAEBCijYAAAAACQkiBuBpmULXWIepwX93795t3JMcWgdlTjUnAPNU7/DIOfu1DPpsrXf7WdbrJeY3j9Y79LrlGjOnH7Wmrh9ZgplrtQ4Yrtm39fve1BDqpd5/ewciR3jSBgAAACAlRRsAAACAhBRtAAAAABKSaQOszmazqfocKzdnHLmpLBkuS9jv97Hdbpu0tVRuTMtMgLF9s6wpLXN0WsvctxpL9WPq3M0ybr21zpzJoHVOSku18692Tk7NSamd30u8d0899+vUjNGc61LrHNlInrQBAAAASEjRBgAAACAhRRsAAACAhBRtAAAAABJStAFWZ7/fRynlgRfAmg3D8KzXGo9xG4yN45yxdV0eVDseU38OMN43dzrWN3nVqrmn5vRjTt9qxuMc+9Y4x/w+7X/ttZpzDlPX3CXu99pzv8kYKdoAAAAAJKRoAwAAAJCQog0AAABAQoo2AAAAAAkp2gAATLDZbCaHI/YMybxOzTHmhH8uIUs/5hg7h5bhmb2DWlsHfbYcj8xzt6WxX9Aw9Txbz8epoaxztOxvbftzgnGXCMttGeTbI3i3Zt+WbbXub42bXHdFGwAAAICEFG0AAAAAElK0AQAAAEhI0QYAAAAgIUUbAKCpmsDA/X6/dDcXVRtGuabAyjntnfucamXu2zn0DDCe24+pbvs1fZRz3O8113OpwOhWQfKt7405AdG129X2t/f8mLpv62PWvgefY54q2gAAAAAkpGgDAAAAkJCiDQAAAEBCijYAAAAACT1v6Q4AnNNp2Ni5gu2Ay7Pf72O73T7wtSVCTceOmXlty9y3U637Wnutao5b21btnKzdN8v1EyD8jM1mUzUeU69d7Vi33G7OXM5izj069VznhnS3am/OWrfEdW7Zjx7996QNAAAAQEKKNgAAAAAJKdoAAAAAJKRoAwAAAJCQIGJgdcYC92qD0noHKGYObVwT4wj15twb7qvzah0SOvWYc4JPBfqvV8uA1DkB170tsSa2Dmvu3Y/a9lsGXC/xs92c9W/qec0Jdb+6uho9hidtAAAAABJStAEAAABISNEGAAAAICFFGwAAAICEBBEDNCSQsQ3jyBqMhaL3dgn3xtTAx3OEWArZzenc99na7Pf72G63D3ytZSBt63svS6j2VHPGNvNcntrf2vnRetyyvG+cgydtAAAAABJStAEAAABISNEGAAAAICGZNsDqjH12m/Oa85nsNX6WGGgn8xqQuW8t1Z5nTR7EOTIjWmaDjLV1dXU1qa3M5lzjmrZaX/fe+SQt+3uOrJqW7S1xXWq1vqY1bWWZRzfhSRsAAACAhBRtAAAAABJStAEAAABISNEGAAAAICFBxAALOA0yu4TwyznBfL3HY6ngOFjKEnO+5TFb9792LVpijLK0PzWI01q6vM1m0+y6ZAkdrpUlVPYc4cRTLbH+tT73ln2bc61q9p0z/3a73ei2nrQBAAAASEjRBgAAACAhRRsAAACAhBRtAAAAABISRAywgKzBjbWhfK37n3U84GH2+31st9sHvjY1fLF1iOUS91SWEN/aNStLSGjLAOA55zR136VCo2nj9Fq1DvZt2Y+a/eZu19KcUOfe90Hvvl1CcHytluHVV1dXo9t60gYAAAAgIUUbAAAAgIQUbQAAAAASUrQBAAAASEgQMQBPu9SA4Sz94PLNCXdcQu9AyanHPIep5zUnrHPOWNbsOycw9hxhsz3b4kFTw1zPMYdq26tpf6n7sUbvYOZzhP1OPW6W970soca1c3K3243u70kbAAAAgIQUbQAAAAASUrQBAAAASEjRBgAAACAhQcQAnFWWcLpLZGzX4/RaLRX+OfWYY1r2I3PgaG1bWe69tc0Z4cQ3t9/vY7vdPnK7qWN7jhDcqeG2c7QMP27dj5YB0bVanmvr0PWxfkx9H239fttyjK6urka39aQNAAAAQEKKNgAAAAAJKdoAAAAAJKRoAwAAAJCQIGIAzipLOOfaTA3cY70yX+PWIZMttQxIbd3XLGHKcywRGMuylpijc+ZQy/vsHMG+S9xTrcPea/ar1TIw+xxq5szce8OTNgAAAAAJKdoAAAAAJKRoAwAAAJCQog0AAABAQoKIATrrHdjG8mrD73qHt5pHOU0NcsxiiUDJOe33DkNdKoS5JiQ5y7xaom+Zx2MJtefe8meU1uHBNf2Yc4+2fF8d68eca3B63HNcgyVCh1v2Y4458+gcvyjCkzYAAAAACSnaAAAAACSkaAMAAACQkEwb4FbrnYdwXXu3+XP2l+g2Zcmc47Pbt8HUceudsXLb16YlxqN3JtYS9+gSuRrneD/ParPZpL13W2ax1F7jc+TMtWx/ifld217NMbLce62P2fKemjtGnrQBAAAASEjRBgAAACAhRRsAAACAhBRtAAAAABISRAzcallCCucElGUJ3COn1oGgU9s3/9rIEpw5pncQ6iUEWy51DC7bfr+P7Xb7yO1q7tHWwb5T14WWAes36Ufv/i7RjzkBzkuE5k/tb+vz7P3zzVj7u91udFtP2gAAAAAkpGgDAAAAkJCiDQAAAEBCijYAAAAACQkiBoALNif4r3ew7G2ROaC3dzBpbXst2+d2OJ1Ht3nObDabZ53/2H2WJSi4ZXtLXPcsvyhizrm3DB2ec8ze+/Z+rxo7Ro97z5M2AAAAAAkp2gAAAAAkpGgDAAAAkJCiDQAAAEBC5SYBOLvd7qMR8aF+3QHO4CVPPPHEC5fuxBzWIrgI1iIgi1WvR9YiuBija9GNijYAAAAAnIePRwEAAAAkpGgDAAAAkJCiDQAAAEBCijYAAAAACSnaAAAAACSkaAMAAACQkKINAAAAQEKKNgAAAAAJKdoAAAAAJPT/AZ1J3/L5foCiAAAAAElFTkSuQmCC\n",
|
|
"text/plain": [
|
|
"<Figure size 1440x360 with 4 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"@jit(nopython=True, nogil=True)\n",
|
|
"def energy(state):\n",
|
|
" E = 0\n",
|
|
" N, M = state.shape\n",
|
|
" for i in range(N):\n",
|
|
" for j in range(M):\n",
|
|
" # handle the north and south neighbours\n",
|
|
" if 0 <= (i + 1) < N:\n",
|
|
" E -= state[i, j] * state[i + 1, j]\n",
|
|
"\n",
|
|
" # handle the east and west neighbours\n",
|
|
" if 0 <= (j + 1) < M:\n",
|
|
" E -= state[i, j] * state[i, j + 1]\n",
|
|
"\n",
|
|
" return 2 * E / (N * M)\n",
|
|
"\n",
|
|
"\n",
|
|
"# While writing numba it's useful to keep the list of supported numpy functions open:\n",
|
|
"# https://numba.pydata.org/numba-doc/dev/reference/numpysupported.html\n",
|
|
"@jit(nopython=True, nogil=True)\n",
|
|
"def mcmc(initial_state, steps, T, energy=energy):\n",
|
|
" N, M = initial_state.shape\n",
|
|
" assert N == M\n",
|
|
"\n",
|
|
" current_state = initial_state.copy()\n",
|
|
" E = N**2 * energy(current_state)\n",
|
|
" for i in range(steps):\n",
|
|
" i, j = np.random.randint(N), np.random.randint(N)\n",
|
|
"\n",
|
|
" # modify the state a little, here we just flip a random pixel\n",
|
|
" current_state[i, j] *= -1\n",
|
|
" new_E = N**2 * energy(current_state)\n",
|
|
"\n",
|
|
" if (new_E < E) or np.exp(-(new_E - E) / T) > np.random.random():\n",
|
|
" E = new_E\n",
|
|
" else:\n",
|
|
" current_state[i, j] *= -1 # reject the change we made\n",
|
|
"\n",
|
|
" return current_state\n",
|
|
"\n",
|
|
"\n",
|
|
"Ts = [4, 5, 50]\n",
|
|
"\n",
|
|
"ncols = 1 + len(Ts)\n",
|
|
"f, axes = plt.subplots(ncols=ncols, figsize=(5 * ncols, 5))\n",
|
|
"\n",
|
|
"initial_state = np.ones(shape=(50, 50))\n",
|
|
"axes[0].set(title=\"Initial state\")\n",
|
|
"show_state(initial_state, ax=axes[0])\n",
|
|
"\n",
|
|
"for T, ax in zip(Ts, axes[1:]):\n",
|
|
" # initial_state = rng.choice([1,-1], size = (50,50))\n",
|
|
"\n",
|
|
" final_state = mcmc(initial_state, steps=100_000, T=T)\n",
|
|
" show_state(final_state, ax=ax)\n",
|
|
" ax.set(title=f\"T = {T}\")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "5d1874d4-4585-49ed-bc6f-b11c22231669",
|
|
"metadata": {},
|
|
"source": [
|
|
"These images give a flavour of why physicists find this model useful, it gives window into how thermal noise and spontaneous order interact. At low temperatures the energy cost of being different from your neighbours is the most important thing, while at high temperatures, it doesn't matter and you really just do your own thing.\n",
|
|
"\n",
|
|
"There's a special point somewhere in the middle called the critical point $T_c$ where all sorts of cool things happen, but my favourite is that for large system sizes you get a kind of fractal behaviour which I will demonstrate more once we've sped this code up and can simulate larger systems in a reasonable time. You can kinda see it for 50x50 systesm at T = 5 but not really clearly."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "5f728039-a975-4083-b68e-a13b4f2d1f87",
|
|
"metadata": {},
|
|
"source": [
|
|
"The code we have so far is really just a sketch of a solution. So this is a good time to step back and think about what are aims are and how this software will fulfil them. I see three broad areas on which it needs improvement:\n",
|
|
"\n",
|
|
"**Functionality**\n",
|
|
"Right now we can't really do much except print nice pictures of states, but (within the fiction of this project) we really want to be able to do science! So we need to think about what measurements and observations we might want to make and how that might affect the structure of our code.\n",
|
|
"\n",
|
|
"**Testing**\n",
|
|
"I've already missed at least one devastating bug in this code, and there are almost certainly more! Before we start adding too much new code we should think about how to increase our confidence that the individual components are working correctly. It's very easy to build a huge project out of hundreds of functions, realise there's a bug and then struggle to find the source of that bug. If we test our components individually and thoroughly, we can avoid some of that pain.\n",
|
|
"\n",
|
|
"**Performance**\n",
|
|
"Performance only matters in so far as it limits what we can do. And there is a real danger that trying to optimise for performance too early or in the wrong places will just lead to complexity that makes the code harder to read, harder to write and more likely to contain bugs. However I do want to show you the fractal states at the critical point, and I can't currently generate those images in a reasonable time, so some optimisation will happen!"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "486f066c-f027-44e8-8937-8636a52f32fb",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Functionality\n",
|
|
"\n",
|
|
"The main thing we want to be able to do is to take measurements, the code as I have writting it doesn't really allow that because it only returns the final state in the chain. Let's say we have a measurement called `average_color(state)` that we want to average over the whole chain. We could just stick that inside our definition of `mcmc` but we know that we will likely make other measurements too and we don't want to keep writing new versions of our core functionality!\n",
|
|
"\n",
|
|
"## Exercise 1\n",
|
|
"Have a think about how you would implement this and what options you have."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "c28b0a86-28f8-426f-9013-70e962f02256",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Solution 1\n",
|
|
"So I chatted with my mentors on this project on how to best do this and we came up with a few ideas:\n",
|
|
"\n",
|
|
"### Just save all the states and return them\n",
|
|
"\n",
|
|
"The problem with this is the states are very big and we don't want to waste all that memory. For an NxN state that uses 8 bit integers (the smallest we can use in numpy) 1000 samples would already use 2.5Gb of memory! We will see later that we'd really like to be able to go a bit bigger than 50x50 and 1000 samples!\n",
|
|
"\n",
|
|
"### Pass in a function to make measurements\n",
|
|
"```python\n",
|
|
"\n",
|
|
"def mcmc(initial_state, steps, T, measurement, energy=energy):\n",
|
|
" ...\n",
|
|
"\n",
|
|
" current_state = initial_state.copy()\n",
|
|
" E = N**2 * energy(current_state)\n",
|
|
" for i in range(steps):\n",
|
|
" measurements[i] = measurement(state)\n",
|
|
" ...\n",
|
|
"\n",
|
|
" return measurements\n",
|
|
"```\n",
|
|
"\n",
|
|
"This could work but it limits how we can store measurements and what shape and type they can be. What if we want to store our measurements in a numpy array? Or what if your measurement itself is a vector or and object that can't easily be stored in a numpy array? We would have to think carefully about what functionality we want."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "c7c9575f-2450-4298-a507-90f0c1b9b284",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"### Use Inheritance\n",
|
|
"```python\n",
|
|
"# This class would define the basic functionality of performing MCMC\n",
|
|
"class MCMCSampler(object):\n",
|
|
" def run(self, initial_state, steps, T):\n",
|
|
" ...\n",
|
|
" for i in range(steps):\n",
|
|
" self.measurement(state)\n",
|
|
"\n",
|
|
" \n",
|
|
"# This class would inherit from it and just implement the measurement\n",
|
|
"class AverageColorSampler(MCMCSampler):\n",
|
|
" measurements = np.zeros(10)\n",
|
|
" index = 0\n",
|
|
" \n",
|
|
" def measurement(self, state):\n",
|
|
" self.measurements[self.index] = some_function(state)\n",
|
|
" self.index += 1\n",
|
|
" \n",
|
|
"color_sampler = AverageColorSampler(...)\n",
|
|
"measurements = color_sampler.run(...)\n",
|
|
"```\n",
|
|
"\n",
|
|
"This would definitely work but I personally am not a huge fan of object oriented programming so I'm gonna skip this option!"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "7d05d25d-c9ba-406d-9977-0ca4aeb430a7",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Use a generator\n",
|
|
"This is the approach I ended up settling on, we will use [python generator function](https://peps.python.org/pep-0255/). While you may not have come across generator functions before, you almost certainly will have come across generators, `range(n)` is a generator, `(i for i in [1,2,3])` is a generator. Generator functions are a way to build your own generators, by way of example here is range implemented as a generator function:"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 3,
|
|
"id": "5b17c054-230f-4188-98a6-51fd8fe5b437",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"(<generator object my_range at 0x7f86c6d87040>, [0, 1, 2, 3, 4, 5, 6, 7, 8, 9])"
|
|
]
|
|
},
|
|
"execution_count": 3,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"def my_range(n):\n",
|
|
" \"Behaves like the builtin range function of one argument\"\n",
|
|
" i = 0\n",
|
|
" while i < n:\n",
|
|
" yield i # sends i out to whatever function called us\n",
|
|
" i += 1\n",
|
|
" return # let's python know that we have nothing else to give\n",
|
|
"\n",
|
|
"\n",
|
|
"my_range(10), list(my_range(10))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "b74fadbe-80c2-4a20-b651-0e47188b005a",
|
|
"metadata": {},
|
|
"source": [
|
|
"This requires only a very small change to our mcmc function and suddenly we can do whatever we like with the states! While we're at it I'm going to add an aditional argument `stepsize` that allows us to only sample the state every `stepsize` MCMC steps. You'll see why we would want to set this to value greater than 1 in a moment."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 4,
|
|
"id": "f73d6335-6514-45b1-9128-d72122d8b0b7",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"6.16 ms ± 16.3 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n",
|
|
"15.3 ms ± 406 µs per loop (mean ± std. dev. of 7 runs, 1 loop each)\n",
|
|
"2x slowdown!\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"@jit(nopython=True, nogil=True)\n",
|
|
"def mcmc_generator(initial_state, steps, T, stepsize=1000, energy=energy):\n",
|
|
" N, M = initial_state.shape\n",
|
|
" assert N == M\n",
|
|
"\n",
|
|
" current_state = initial_state.copy()\n",
|
|
" E = N**2 * energy(current_state)\n",
|
|
" for _ in range(steps):\n",
|
|
" for _ in range(stepsize):\n",
|
|
" i, j = np.random.randint(N), np.random.randint(N)\n",
|
|
"\n",
|
|
" # modify the state a little, here we just flip a random pixel\n",
|
|
" current_state[i, j] *= -1\n",
|
|
" new_E = N**2 * energy(current_state)\n",
|
|
"\n",
|
|
" if (new_E < E) or np.exp(-(new_E - E) / T) > np.random.random():\n",
|
|
" E = new_E\n",
|
|
" else:\n",
|
|
" current_state[i, j] *= -1 # reject the change we made\n",
|
|
" yield current_state.copy()\n",
|
|
" return\n",
|
|
"\n",
|
|
"\n",
|
|
"N_steps = 1000\n",
|
|
"stepsize = 1\n",
|
|
"without_yield = %timeit -o mcmc(initial_state, steps = N_steps, T = 5)\n",
|
|
"with_yield = %timeit -o [np.mean(s) for s in mcmc_generator(initial_state, T = 5, steps = N_steps, stepsize = 1)]\n",
|
|
"print(f\"{with_yield.best / without_yield.best:.0f}x slowdown!\")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "132bf8d1-d341-494a-9881-689605a104b7",
|
|
"metadata": {},
|
|
"source": [
|
|
"Fun fact: if you replace `yield current_state.copy()` with `yield current_state` your python kernel will crash when you run the code. I believe this is a bug in Numba that related to how pointers to numpy arrays work but let's not worry too much about it. \n",
|
|
"\n",
|
|
"We take a factor of two slowdown but that doesn't seem so much to pay for the fact we can now sample the state at every single step rather than just the last."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 51,
|
|
"id": "1b027d64-fc6a-45c0-804d-9785b5f8258a",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<matplotlib.legend.Legend at 0x7f86b46aef40>"
|
|
]
|
|
},
|
|
"execution_count": 51,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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\n",
|
|
"text/plain": [
|
|
"<Figure size 1100x550 with 6 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"def average_color(state):\n",
|
|
" return np.mean(state)\n",
|
|
"\n",
|
|
"\n",
|
|
"initial_state = np.ones(shape=(20, 20))\n",
|
|
"\n",
|
|
"fig, axes = plt.subplots(\n",
|
|
" figsize=(10, 5),\n",
|
|
" nrows=3,\n",
|
|
" ncols=2,\n",
|
|
" sharey=\"all\",\n",
|
|
" sharex=\"col\",\n",
|
|
" gridspec_kw=dict(hspace=0, wspace=0, width_ratios=(4, 1)),\n",
|
|
")\n",
|
|
"\n",
|
|
"for T, ax, hist_ax in zip([10, 4.5, 3], axes[:, 0], axes[:, 1]):\n",
|
|
" m = np.array(\n",
|
|
" [\n",
|
|
" [\n",
|
|
" average_color(s)\n",
|
|
" for s in mcmc_generator(initial_state, steps=300, stepsize=200, T=T)\n",
|
|
" ]\n",
|
|
" for _ in range(10)\n",
|
|
" ]\n",
|
|
" ).T\n",
|
|
" indiv_line, *_ = ax.plot(m, alpha=0.4, color=\"k\", linewidth=0.9)\n",
|
|
" (mean_line,) = ax.plot(np.mean(m, axis=1))\n",
|
|
" hist_ax.hist(m.flatten(), orientation=\"horizontal\")\n",
|
|
"\n",
|
|
"\n",
|
|
"axes[-1, 0].set(xlabel=\"Monte Carlo step\", ylabel=\"Average Color\")\n",
|
|
"axes[-1, 0].legend([mean_line, indiv_line], [\"Mean\", \"Individual walker\"])"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "40f469e2-ce18-4fca-8630-2d245adf78b3",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "Python [conda env:recode]",
|
|
"language": "python",
|
|
"name": "conda-env-recode-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": "3.9.12"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 5
|
|
}
|