{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import numpy as np" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "%load_ext autoreload\n", "%autoreload 2" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "from matplotlib import pylab as pl\n", "from matplotlib import animation\n", "from matplotlib.collections import PatchCollection\n", "#pl.switch_backend('qt5agg')\n", "#%matplotlib qt" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "import IsingLattice\n", "from IsingLattice import *" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Traceback (most recent call last):\n", " File \"c:\\Anaconda3\\lib\\site-packages\\matplotlib\\cbook\\__init__.py\", line 388, in process\n", " proxy(*args, **kwargs)\n", " File \"c:\\Anaconda3\\lib\\site-packages\\matplotlib\\cbook\\__init__.py\", line 228, in __call__\n", " return mtd(*args, **kwargs)\n", " File \"c:\\Anaconda3\\lib\\site-packages\\matplotlib\\animation.py\", line 1026, in _start\n", " self._init_draw()\n", " File \"c:\\Anaconda3\\lib\\site-packages\\matplotlib\\animation.py\", line 1750, in _init_draw\n", " self._draw_frame(next(self.new_frame_seq()))\n", "TypeError: 'NoneType' object is not an iterator\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Averaged quantities:\n", "E = -0.9112318840579711\n", "E*E = 1.2264492753623188\n", "M = -0.4963768115942029\n", "M*M = 0.3135473278985507\n" ] } ], "source": [ "%run ILanim.py" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "pl.show()" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "9" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "np.sum([np.array([[1,1,1],[1,1,1],[1,1,1]])])" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "2.2479234399999983" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "np.average([2.2465504000000003,2.2551448,2.2456268999999978,2.2509048000000007,2.241390299999992])" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.004709093347389065" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "np.std([2.2465504000000003,2.2551448,2.2456268999999978,2.2509048000000007,2.241390299999992])" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [], "source": [ "aa = np.array([[1,2,3],[4,5,6],[7,8,9]])" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([[7, 8, 9],\n", " [1, 2, 3],\n", " [4, 5, 6]])" ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ "np.roll(aa,1,0)" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.21756048000015654" ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ "np.average([0.2150575000000572,0.21588909999991301,0.221953200000371,0.2193971000001511,0.21550550000029034])" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.002681437107620675" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "np.std([0.2150575000000572,0.21588909999991301,0.221953200000371,0.2193971000001511,0.21550550000029034])" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.1350813799999969" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "np.average([0.13431200000002264,0.1349497999999585,0.13549130000001242,0.1350567999999157,0.13559700000007524])" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.0004568941776972011" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "np.std([0.13431200000002264,0.1349497999999585,0.13549130000001242,0.1350567999999157,0.13559700000007524])" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "16.666666666666664" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "2.25 / 0.135" ] }, { "cell_type": "code", "execution_count": 174, "metadata": {}, "outputs": [], "source": [ "from matplotlib.colors import ListedColormap" ] }, { "cell_type": "code", "execution_count": 175, "metadata": {}, "outputs": [], "source": [ "ListedColormap?" ] }, { "cell_type": "code", "execution_count": 44, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 44, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig = pl.figure()\n", "matax = fig.add_subplot(3,1,1)\n", "matax.matshow(np.array([[-1,-1],[-1,-1]]), cmap = ListedColormap([\"navy\", \"darkorange\"]))" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.05 0\n", "0.05 10000\n", "0.05 20000\n", "0.05 30000\n", "0.05 40000\n", "0.05 50000\n", "0.05 60000\n", "0.05 70000\n", "0.05 80000\n", "0.05 90000\n", "0.1 0\n", "0.1 10000\n", "0.1 20000\n", "0.1 30000\n", "0.1 40000\n", "0.1 50000\n", "0.1 60000\n", "0.1 70000\n", "0.1 80000\n", "0.1 90000\n", "0.15000000000000002 0\n", "0.15000000000000002 10000\n", "0.15000000000000002 20000\n", "0.15000000000000002 30000\n", "0.15000000000000002 40000\n", "0.15000000000000002 50000\n", "0.15000000000000002 60000\n", "0.15000000000000002 70000\n", "0.15000000000000002 80000\n", "0.15000000000000002 90000\n", "0.2 0\n", "0.2 10000\n", "0.2 20000\n", "0.2 30000\n", "0.2 40000\n", "0.2 50000\n", "0.2 60000\n", "0.2 70000\n", "0.2 80000\n", "0.2 90000\n", "0.25 0\n", "0.25 10000\n", "0.25 20000\n", "0.25 30000\n", "0.25 40000\n", "0.25 50000\n", "0.25 60000\n", "0.25 70000\n", "0.25 80000\n", "0.25 90000\n", "0.3 0\n", "0.3 10000\n", "0.3 20000\n", "0.3 30000\n", "0.3 40000\n", "0.3 50000\n", "0.3 60000\n", "0.3 70000\n", "0.3 80000\n", "0.3 90000\n", "0.35000000000000003 0\n", "0.35000000000000003 10000\n", "0.35000000000000003 20000\n", "0.35000000000000003 30000\n", "0.35000000000000003 40000\n", "0.35000000000000003 50000\n", "0.35000000000000003 60000\n", "0.35000000000000003 70000\n", "0.35000000000000003 80000\n", "0.35000000000000003 90000\n", "0.4 0\n", "0.4 10000\n", "0.4 20000\n", "0.4 30000\n", "0.4 40000\n", "0.4 50000\n", "0.4 60000\n", "0.4 70000\n", "0.4 80000\n", "0.4 90000\n", "0.45 0\n", "0.45 10000\n", "0.45 20000\n", "0.45 30000\n", "0.45 40000\n", "0.45 50000\n", "0.45 60000\n", "0.45 70000\n", "0.45 80000\n", "0.45 90000\n", "0.5 0\n", "0.5 10000\n", "0.5 20000\n", "0.5 30000\n", "0.5 40000\n", "0.5 50000\n", "0.5 60000\n", "0.5 70000\n", "0.5 80000\n", "0.5 90000\n", "0.55 0\n", "0.55 10000\n", "0.55 20000\n", "0.55 30000\n", "0.55 40000\n", "0.55 50000\n", "0.55 60000\n", "0.55 70000\n", "0.55 80000\n", "0.55 90000\n", "0.6000000000000001 0\n", "0.6000000000000001 10000\n", "0.6000000000000001 20000\n", "0.6000000000000001 30000\n", "0.6000000000000001 40000\n", "0.6000000000000001 50000\n", "0.6000000000000001 60000\n", "0.6000000000000001 70000\n", "0.6000000000000001 80000\n", "0.6000000000000001 90000\n", "0.6500000000000001 0\n", "0.6500000000000001 10000\n", "0.6500000000000001 20000\n", "0.6500000000000001 30000\n", "0.6500000000000001 40000\n", "0.6500000000000001 50000\n", "0.6500000000000001 60000\n", "0.6500000000000001 70000\n", "0.6500000000000001 80000\n", "0.6500000000000001 90000\n", "0.7000000000000001 0\n", "0.7000000000000001 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"0.9000000000000001 0\n", "0.9000000000000001 10000\n", "0.9000000000000001 20000\n", "0.9000000000000001 30000\n", "0.9000000000000001 40000\n", "0.9000000000000001 50000\n", "0.9000000000000001 60000\n", "0.9000000000000001 70000\n", "0.9000000000000001 80000\n", "0.9000000000000001 90000\n", "0.9500000000000001 0\n", "0.9500000000000001 10000\n", "0.9500000000000001 20000\n", "0.9500000000000001 30000\n", "0.9500000000000001 40000\n", "0.9500000000000001 50000\n", "0.9500000000000001 60000\n", "0.9500000000000001 70000\n", "0.9500000000000001 80000\n", "0.9500000000000001 90000\n", "1.0 0\n", "1.0 10000\n", "1.0 20000\n", "1.0 30000\n", "1.0 40000\n", "1.0 50000\n", "1.0 60000\n", "1.0 70000\n", "1.0 80000\n", "1.0 90000\n", "1.05 0\n", "1.05 10000\n", "1.05 20000\n", "1.05 30000\n", "1.05 40000\n", "1.05 50000\n", "1.05 60000\n", "1.05 70000\n", "1.05 80000\n", "1.05 90000\n", "1.1 0\n", "1.1 10000\n", "1.1 20000\n", "1.1 30000\n", "1.1 40000\n", "1.1 50000\n", "1.1 60000\n", "1.1 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "n_rows = 2\n", "n_cols = 2\n", "il = IsingLattice(n_rows, n_cols)\n", "il.lattice = np.ones((n_rows, n_cols))\n", "spins = n_rows*n_cols\n", "runtime = 100000\n", "times = range(runtime)\n", "temps = np.arange(0.05, 5.05, 0.05)\n", "energies = []\n", "magnetisations = []\n", "energysq = []\n", "magnetisationsq = []\n", "energystds = []\n", "magnetisationstds = []\n", "for t in temps:\n", " for i in times:\n", " if i % 10000 == 0:\n", " print(t, i)\n", " energy, magnetisation = il.montecarlostep(t)\n", " aveE, aveE2, aveM, aveM2, n_cycles = il.statistics()\n", " stdE = np.std(il.E[il.cutoff:])\n", " stdM = np.std(il.M[il.cutoff:])\n", " energies.append(aveE)\n", " energysq.append(aveE2)\n", " energystds.append(stdE)\n", " magnetisations.append(aveM)\n", " magnetisationsq.append(aveM2)\n", " magnetisationstds.append(stdM)\n", " #reset the IL object for the next cycle\n", " il.E = []\n", " il.M = []\n", "fig = pl.figure()\n", "enerax = fig.add_subplot(2,1,1)\n", "enerax.set_ylabel(\"Energy per spin\")\n", "enerax.set_xlabel(\"Temperature\")\n", "enerax.set_ylim([-2.2, 0.2])\n", "magax = fig.add_subplot(2,1,2)\n", "magax.set_ylabel(\"Magnetisation per spin\")\n", "magax.set_xlabel(\"Temperature\")\n", "magax.set_ylim([-1.2, 1.2])\n", "enerax.errorbar(temps, np.array(energies)/spins, yerr = np.array(energystds)/spins)\n", "magax.errorbar(temps, np.array(magnetisations)/spins, yerr = np.array(magnetisationstds)/spins)\n", "pl.show()\n", "pl.savefig(\"2x2_2.svg\")\n", "pl.savefig(\"2x2_2.png\")\n", "\n", "final_data = np.column_stack((temps, energies, energysq, energystds, magnetisations, magnetisationsq, magnetisationstds))\n", "np.savetxt(\"2x2_2.dat\", final_data)" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.05 0\n", "0.05 10000\n", "0.05 20000\n", "0.05 30000\n", "0.05 40000\n", "0.05 50000\n", 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"text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "n_rows = 4\n", "n_cols = 4\n", "il = IsingLattice(n_rows, n_cols)\n", "il.lattice = np.ones((n_rows, n_cols))\n", "spins = n_rows*n_cols\n", "runtime = 100000\n", "times = range(runtime)\n", "temps = np.arange(0.05, 5.05, 0.05)\n", "energies = []\n", "magnetisations = []\n", "energysq = []\n", "magnetisationsq = []\n", "energystds = []\n", "magnetisationstds = []\n", "for t in temps:\n", " for i in times:\n", " if i % 10000 == 0:\n", " print(t, i)\n", " energy, magnetisation = il.montecarlostep(t)\n", " aveE, aveE2, aveM, aveM2, n_cycles = il.statistics()\n", " stdE = np.std(il.E[il.cutoff:])\n", " stdM = np.std(il.M[il.cutoff:])\n", " energies.append(aveE)\n", " energysq.append(aveE2)\n", " energystds.append(stdE)\n", " magnetisations.append(aveM)\n", " magnetisationsq.append(aveM2)\n", " magnetisationstds.append(stdM)\n", " #reset the IL object for the next cycle\n", " il.E = []\n", " il.M = []\n", "fig = pl.figure()\n", "enerax = fig.add_subplot(2,1,1)\n", "enerax.set_ylabel(\"Energy per spin\")\n", "enerax.set_xlabel(\"Temperature\")\n", "enerax.set_ylim([-2.2, 0.2])\n", "magax = fig.add_subplot(2,1,2)\n", "magax.set_ylabel(\"Magnetisation per spin\")\n", "magax.set_xlabel(\"Temperature\")\n", "magax.set_ylim([-1.2, 1.2])\n", "enerax.errorbar(temps, np.array(energies)/spins, yerr = np.array(energystds)/spins)\n", "magax.errorbar(temps, np.array(magnetisations)/spins, yerr = np.array(magnetisationstds)/spins)\n", "pl.show()\n", "pl.savefig(\"4x4_2.svg\")\n", "pl.savefig(\"4x4_2.png\")\n", "\n", "final_data = np.column_stack((temps, energies, energysq, energystds, magnetisations, magnetisationsq, magnetisationstds))\n", "np.savetxt(\"4x4_2.dat\", final_data)" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.05 0\n", "0.05 10000\n", "0.05 20000\n", "0.05 30000\n", "0.05 40000\n", "0.05 50000\n", 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "n_rows = 8\n", "n_cols = 8\n", "il = IsingLattice(n_rows, n_cols)\n", "il.lattice = np.ones((n_rows, n_cols))\n", "spins = n_rows*n_cols\n", "runtime = 100000\n", "times = range(runtime)\n", "temps = np.arange(0.05, 5.05, 0.05)\n", "energies = []\n", "magnetisations = []\n", "energysq = []\n", "magnetisationsq = []\n", "energystds = []\n", "magnetisationstds = []\n", "for t in temps:\n", " for i in times:\n", " if i % 10000 == 0:\n", " print(t, i)\n", " energy, magnetisation = il.montecarlostep(t)\n", " aveE, aveE2, aveM, aveM2, n_cycles = il.statistics()\n", " stdE = np.std(il.E[il.cutoff:])\n", " stdM = np.std(il.M[il.cutoff:])\n", " energies.append(aveE)\n", " energysq.append(aveE2)\n", " energystds.append(stdE)\n", " magnetisations.append(aveM)\n", " magnetisationsq.append(aveM2)\n", " magnetisationstds.append(stdM)\n", " #reset the IL object for the next cycle\n", " il.E = []\n", " il.M = []\n", "fig = pl.figure()\n", "enerax = fig.add_subplot(2,1,1)\n", "enerax.set_ylabel(\"Energy per spin\")\n", "enerax.set_xlabel(\"Temperature\")\n", "enerax.set_ylim([-2.2, 0.2])\n", "magax = fig.add_subplot(2,1,2)\n", "magax.set_ylabel(\"Magnetisation per spin\")\n", "magax.set_xlabel(\"Temperature\")\n", "magax.set_ylim([-1.2, 1.2])\n", "enerax.errorbar(temps, np.array(energies)/spins, yerr = np.array(energystds)/spins)\n", "magax.errorbar(temps, np.array(magnetisations)/spins, yerr = np.array(magnetisationstds)/spins)\n", "pl.show()\n", "pl.savefig(\"8x8_2.svg\")\n", "pl.savefig(\"8x8_2.png\")\n", "\n", "final_data = np.column_stack((temps, energies, energysq, energystds, magnetisations, magnetisationsq, magnetisationstds))\n", "np.savetxt(\"8x8_2.dat\", final_data)" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.05 0\n", "0.05 10000\n", "0.05 20000\n", "0.05 30000\n", "0.05 40000\n", "0.05 50000\n", 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "n_rows = 16\n", "n_cols = 16\n", "il = IsingLattice(n_rows, n_cols)\n", "il.lattice = np.ones((n_rows, n_cols))\n", "spins = n_rows*n_cols\n", "runtime = 200000\n", "times = range(runtime)\n", "temps = np.arange(0.05, 5.05, 0.05)\n", "energies = []\n", "magnetisations = []\n", "energysq = []\n", "magnetisationsq = []\n", "energystds = []\n", "magnetisationstds = []\n", "for t in temps:\n", " for i in times:\n", " if i % 10000 == 0:\n", " print(t, i)\n", " energy, magnetisation = il.montecarlostep(t)\n", " aveE, aveE2, aveM, aveM2, n_cycles = il.statistics()\n", " stdE = np.std(il.E[il.cutoff:])\n", " stdM = np.std(il.M[il.cutoff:])\n", " energies.append(aveE)\n", " energysq.append(aveE2)\n", " energystds.append(stdE)\n", " magnetisations.append(aveM)\n", " magnetisationsq.append(aveM2)\n", " magnetisationstds.append(stdM)\n", " #reset the IL object for the next cycle\n", " il.E = []\n", " il.M = []\n", "fig = pl.figure()\n", "enerax = fig.add_subplot(2,1,1)\n", "enerax.set_ylabel(\"Energy per spin\")\n", "enerax.set_xlabel(\"Temperature\")\n", "enerax.set_ylim([-2.2, 0.2])\n", "magax = fig.add_subplot(2,1,2)\n", "magax.set_ylabel(\"Magnetisation per spin\")\n", "magax.set_xlabel(\"Temperature\")\n", "magax.set_ylim([-1.2, 1.2])\n", "enerax.errorbar(temps, np.array(energies)/spins, yerr = np.array(energystds)/spins)\n", "magax.errorbar(temps, np.array(magnetisations)/spins, yerr = np.array(magnetisationstds)/spins)\n", "pl.show()\n", "pl.savefig(\"16x16_2.svg\")\n", "pl.savefig(\"16x16_2.png\")\n", "\n", "final_data = np.column_stack((temps, energies, energysq, energystds, magnetisations, magnetisationsq, magnetisationstds))\n", "np.savetxt(\"16x16_2.dat\", final_data)" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.05 0\n", "0.05 10000\n", "0.05 20000\n", "0.05 30000\n", "0.05 40000\n", "0.05 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170000\n", "5.0 180000\n", "5.0 190000\n", "5.0 200000\n", "5.0 210000\n", "5.0 220000\n", "5.0 230000\n", "5.0 240000\n", "5.0 250000\n", "5.0 260000\n", "5.0 270000\n", "5.0 280000\n", "5.0 290000\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "n_rows = 32\n", "n_cols = 32\n", "il = IsingLattice(n_rows, n_cols)\n", "#updates the lattice without updating the energy\n", "#this will cause the beginning of the simulation to produce erroneous but will be covered up by the cutoff point\n", "il.lattice = np.ones((n_rows, n_cols))\n", "spins = n_rows*n_cols\n", "runtime = 300000\n", "times = range(runtime)\n", "temps = np.arange(0.05, 5.05, 0.05)\n", "energies = []\n", "magnetisations = []\n", "energysq = []\n", "magnetisationsq = []\n", "#lists are created to keep track of the standard deviations to use for error bars\n", "energystds = []\n", "magnetisationstds = []\n", "for t in temps:\n", " for i in times:\n", " if i % 10000 == 0:\n", " print(t, i)\n", " energy, magnetisation = il.montecarlostep(t)\n", " aveE, aveE2, aveM, aveM2, n_cycles = il.statistics()\n", " stdE = np.std(il.E[il.cutoff:])\n", " stdM = np.std(il.M[il.cutoff:])\n", " energies.append(aveE)\n", " energysq.append(aveE2)\n", " energystds.append(stdE)\n", " magnetisations.append(aveM)\n", " magnetisationsq.append(aveM2)\n", " magnetisationstds.append(stdM)\n", " #reset the IL object for the next cycle\n", " il.E = []\n", " il.M = []\n", "fig = pl.figure()\n", "enerax = fig.add_subplot(2,1,1)\n", "enerax.set_ylabel(\"Energy per spin\")\n", "enerax.set_xlabel(\"Temperature\")\n", "enerax.set_ylim([-2.2, 0.2])\n", "magax = fig.add_subplot(2,1,2)\n", "magax.set_ylabel(\"Magnetisation per spin\")\n", "magax.set_xlabel(\"Temperature\")\n", "magax.set_ylim([-1.2, 1.2])\n", "#plots including error bars\n", "enerax.errorbar(temps, np.array(energies)/spins, yerr = np.array(energystds)/spins)\n", "magax.errorbar(temps, np.array(magnetisations)/spins, yerr = np.array(magnetisationstds)/spins)\n", "pl.show()\n", "pl.savefig(\"32x32_2.svg\")\n", "pl.savefig(\"32x32_2.png\")\n", "\n", "#final data saved with extra columns for standard deviations\n", "final_data = np.column_stack((temps, energies, energysq, energystds, magnetisations, magnetisationsq, magnetisationstds))\n", "np.savetxt(\"32x32_2.dat\", final_data)" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "%matplotlib qt" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "c:\\Anaconda3\\lib\\site-packages\\numpy\\core\\fromnumeric.py:2920: RuntimeWarning: Mean of empty slice.\n", " out=out, **kwargs)\n", "c:\\Anaconda3\\lib\\site-packages\\numpy\\core\\_methods.py:85: RuntimeWarning: invalid value encountered in double_scalars\n", " ret = ret.dtype.type(ret / rcount)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Averaged quantities:\n", "E = nan\n", "E*E = nan\n", "M = nan\n", "M*M = nan\n", "\n" ] } ], "source": [ "%run ILanim" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([[ 1.50000000e+00, -1.23891266e+02, 1.53852763e+04,\n", " 6.01918608e+00, 6.28677585e+01, 3.95537946e+03,\n", " 1.73908069e+00],\n", " [ 1.75000000e+00, -1.21409759e+02, 1.48039296e+04,\n", " 7.97495596e+00, 6.20691845e+01, 3.85982019e+03,\n", " 2.69007875e+00],\n", " [ 2.00000000e+00, -1.14912433e+02, 1.33171898e+04,\n", " 1.05982332e+01, 5.98978387e+01, 3.60470967e+03,\n", " 4.11808106e+00],\n", " [ 2.25000000e+00, -9.93614082e+01, 1.02510410e+04,\n", " 1.94512611e+01, -5.12711676e+01, 2.85274777e+03,\n", " 1.49671356e+01],\n", " [ 2.50000000e+00, -7.80987077e+01, 6.48883690e+03,\n", " 1.97339494e+01, 3.10762032e+00, 1.80513280e+03,\n", " 4.23730515e+01],\n", " [ 2.75000000e+00, -6.18353387e+01, 4.11945900e+03,\n", " 1.72002876e+01, -5.18081551e+00, 9.38623663e+02,\n", " 3.01957416e+01]])" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "final_data" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "#files loaded in\n", "d2x2 = np.loadtxt(\"2x2_2.dat\")\n", "d4x4 = np.loadtxt(\"4x4_2.dat\")\n", "d8x8 = np.loadtxt(\"8x8_2.dat\")\n", "d16x16 = np.loadtxt(\"16x16_2.dat\")\n", "d32x32 = np.loadtxt(\"32x32_2.dat\")\n", "\n", "#creates plot areas\n", "fig = pl.figure()\n", "enerax = fig.add_subplot(2,1,1)\n", "enerax.set_ylabel(\"Energy per spin\")\n", "enerax.set_xlabel(\"Temperature\")\n", "enerax.set_ylim([-2.2, 0.2])\n", "magax = fig.add_subplot(2,1,2)\n", "magax.set_ylabel(\"Magnetisation per spin\")\n", "magax.set_xlabel(\"Temperature\")\n", "magax.set_ylim([-1.2, 1.2])\n", "\n", "#plots energies\n", "enerax.plot(d2x2[:,0], d2x2[:,1] / 4, label = \"2x2\")\n", "enerax.plot(d4x4[:,0], d4x4[:,1] / 16, label = \"4x4\")\n", "enerax.plot(d8x8[:,0], d8x8[:,1] / 64, label = \"8x8\")\n", "enerax.plot(d16x16[:,0], d16x16[:,1] / 256, label = \"16x16\")\n", "enerax.plot(d32x32[:,0], d32x32[:,1] / 1024, label = \"32x32\")\n", "\n", "#plots magnetisations\n", "magax.plot(d2x2[:,0], d2x2[:,4] / 4, label = \"2x2\")\n", "magax.plot(d4x4[:,0], d4x4[:,4] / 16, label = \"4x4\")\n", "magax.plot(d8x8[:,0], d8x8[:,4] / 64, label = \"8x8\")\n", "magax.plot(d16x16[:,0], d16x16[:,4] / 256, label = \"16x16\")\n", "magax.plot(d32x32[:,0], d32x32[:,4] / 1024, label = \"32x32\")\n", "\n", "enerax.legend()\n", "magax.legend()\n", "pl.show()" ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "#function defined to make plotting easier\n", "def var_by_T2(E, E2, T):\n", " return (E2 - E ** 2) / (T ** 2)\n", "\n", "pl.figure()\n", "pl.plot(d2x2[:,0], var_by_T2(d2x2[:,1], d2x2[:,2], d2x2[:,0])/4, label = \"2x2\")\n", "pl.plot(d4x4[:,0], var_by_T2(d4x4[:,1], d4x4[:,2], d4x4[:,0])/16, label = \"4x4\")\n", "pl.plot(d8x8[:,0], var_by_T2(d8x8[:,1], d8x8[:,2], d8x8[:,0])/64, label = \"8x8\")\n", "pl.plot(d16x16[:,0], var_by_T2(d16x16[:,1], d16x16[:,2], d16x16[:,0])/256, label = \"16x16\")\n", "pl.plot(d32x32[:,0], var_by_T2(d32x32[:,1], d32x32[:,2], d32x32[:,0])/1024, label = \"32x32\")\n", "pl.xlabel(\"Temperature\")\n", "pl.ylabel(\"Specific Heat Capacity\")\n", "pl.legend()\n", "pl.savefig(\"C against T.png\", dpi = 300)\n", "pl.show()" ] }, { "cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [], "source": [ "#provided files loaded in\n", "c2x2 = np.loadtxt(\"C++_data/2x2.dat\")\n", "c4x4 = np.loadtxt(\"C++_data/4x4.dat\")\n", "c8x8 = np.loadtxt(\"C++_data/8x8.dat\")\n", "c16x16 = np.loadtxt(\"C++_data/16x16.dat\")\n", "c32x32 = np.loadtxt(\"C++_data/32x32.dat\")" ] }, { "cell_type": "code", "execution_count": 37, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "pl.figure()\n", "pl.plot(d2x2[:,0], var_by_T2(d2x2[:,1], d2x2[:,2], d2x2[:,0])/4, label = \"Simulated 2x2\")\n", "pl.plot(c2x2[:,0], c2x2[:,5], label = \"Provided 2x2\")\n", "pl.xlabel(\"Temperature\")\n", "pl.ylabel(\"Specific Heat Capacity\")\n", "pl.legend()\n", "pl.show()" ] }, { "cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "pl.figure()\n", "pl.plot(d4x4[:,0], var_by_T2(d4x4[:,1], d4x4[:,2], d4x4[:,0])/16, label = \"Simulated 4x4\")\n", "pl.plot(c4x4[:,0], c4x4[:,5], label = \"Provided 4x4\")\n", "pl.xlabel(\"Temperature\")\n", "pl.ylabel(\"Specific Heat Capacity\")\n", "pl.legend()\n", "pl.show()" ] }, { "cell_type": "code", "execution_count": 40, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "pl.figure()\n", "pl.plot(d8x8[:,0], var_by_T2(d8x8[:,1], d8x8[:,2], d8x8[:,0])/64, label = \"Simulated 8x8\")\n", "pl.plot(c8x8[:,0], c8x8[:,5], label = \"Provided 8x8\")\n", "pl.xlabel(\"Temperature\")\n", "pl.ylabel(\"Specific Heat Capacity\")\n", "pl.legend()\n", "pl.show()" ] }, { "cell_type": "code", "execution_count": 41, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "pl.figure()\n", "pl.plot(d16x16[:,0], var_by_T2(d16x16[:,1], d16x16[:,2], d16x16[:,0])/256, label = \"Simulated 16x16\")\n", "pl.plot(c16x16[:,0], c16x16[:,5], label = \"Provided 16x16\")\n", "pl.xlabel(\"Temperature\")\n", "pl.ylabel(\"Specific Heat Capacity\")\n", "pl.legend()\n", "pl.show()" ] }, { "cell_type": "code", "execution_count": 43, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "pl.figure()\n", "pl.plot(d32x32[:,0], var_by_T2(d32x32[:,1], d32x32[:,2], d32x32[:,0])/1024, label = \"Simulated 32x32\")\n", "pl.plot(c32x32[:,0], c32x32[:,5], label = \"Provided 32x32\")\n", "pl.xlabel(\"Temperature\")\n", "pl.ylabel(\"Specific Heat Capacity\")\n", "pl.legend()\n", "pl.savefig(\"Comparison 32.png\", dpi = 300)\n", "pl.show()" ] }, { "cell_type": "code", "execution_count": 66, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "#creates all the polynomial fits\n", "fit2 = np.polyfit(c32x32[:,0],c32x32[:,5],2)\n", "fit3 = np.polyfit(c32x32[:,0],c32x32[:,5],3)\n", "fit4 = np.polyfit(c32x32[:,0],c32x32[:,5],4)\n", "fit5 = np.polyfit(c32x32[:,0],c32x32[:,5],5)\n", "fit6 = np.polyfit(c32x32[:,0],c32x32[:,5],6)\n", "\n", "#all polynomial fits plotted at once\n", "pl.figure()\n", "pl.plot(c32x32[:,0], c32x32[:,5], ls = \"\", marker = \"x\", ms = 1, mew = 0.5, label = \"Data\")\n", "pl.plot(c32x32[:,0], np.polyval(fit2, c32x32[:,0]), lw = 1, label = \"Order 2 fit\")\n", "pl.plot(c32x32[:,0], np.polyval(fit3, c32x32[:,0]), lw = 1, label = \"Order 3 fit\")\n", "pl.plot(c32x32[:,0], np.polyval(fit4, c32x32[:,0]), lw = 1, label = \"Order 4 fit\")\n", "pl.plot(c32x32[:,0], np.polyval(fit5, c32x32[:,0]), lw = 1, label = \"Order 5 fit\")\n", "pl.plot(c32x32[:,0], np.polyval(fit6, c32x32[:,0]), lw = 1, label = \"Order 6 fit\")\n", "pl.xlabel(\"Temperature\")\n", "pl.ylabel(\"Specific Heat Capacity\")\n", "pl.legend()\n", "pl.savefig(\"Whole fit.png\", dpi = 300)\n", "pl.show()" ] }, { "cell_type": "code", "execution_count": 95, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "T = c32x32[:,0]\n", "#selects values of temperature only near the peak (manually chosen)\n", "selection = np.logical_and(T > 2.2, T < 2.4)\n", "\n", "#creates all the polynomial fits\n", "fit232 = np.polyfit(T[selection], c32x32[:,5][selection], 2)\n", "fit3 = np.polyfit(T[selection], c32x32[:,5][selection], 3)\n", "fit4 = np.polyfit(T[selection], c32x32[:,5][selection], 4)\n", "\n", "#all polynomial fits plotted at once\n", "pl.figure()\n", "pl.plot(T, c32x32[:,5], ls = \"\", marker = \"x\", ms = 1, mew = 0.5, label = \"Data\")\n", "pl.plot(T[selection], np.polyval(fit232, T[selection]), lw = 1, label = \"Order 2 fit\")\n", "pl.plot(T[selection], np.polyval(fit3, T[selection]), lw = 1, label = \"Order 3 fit\")\n", "pl.plot(T[selection], np.polyval(fit4, T[selection]), lw = 1, label = \"Order 4 fit\")\n", "pl.xlabel(\"Temperature\")\n", "pl.ylabel(\"Specific Heat Capacity\")\n", "pl.legend()\n", "pl.savefig(\"Cut fit.png\", dpi = 300)\n", "pl.show()" ] }, { "cell_type": "code", "execution_count": 106, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[]" ] }, "execution_count": 106, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "T = c16x16[:,0]\n", "selection = np.logical_and(T > 2.2, T < 2.4)\n", "\n", "fit216 = np.polyfit(T[selection], c16x16[:,5][selection], 2)\n", "\n", "pl.figure()\n", "pl.plot(T, c16x16[:,5], ls = \"\", marker = \"x\", ms = 1, mew = 0.5, label = \"Data\")\n", "pl.plot(T[selection], np.polyval(fit216, T[selection]), lw = 1, label = \"Order 2 fit\")" ] }, { "cell_type": "code", "execution_count": 107, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[]" ] }, "execution_count": 107, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "T = c8x8[:,0]\n", "selection = np.logical_and(T > 2.2, T < 2.5)\n", "\n", "fit28 = np.polyfit(T[selection], c8x8[:,5][selection], 2)\n", "\n", "pl.figure()\n", "pl.plot(T, c8x8[:,5], ls = \"\", marker = \"x\", ms = 1, mew = 0.5, label = \"Data\")\n", "pl.plot(T[selection], np.polyval(fit28, T[selection]), lw = 1, label = \"Order 2 fit\")" ] }, { "cell_type": "code", "execution_count": 117, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[]" ] }, "execution_count": 117, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "T = c4x4[:,0]\n", "selection = np.logical_and(T > 2.2, T < 2.7)\n", "\n", "fit24 = np.polyfit(T[selection], c4x4[:,5][selection], 2)\n", "\n", "pl.figure()\n", "pl.plot(T, c4x4[:,5], ls = \"\", marker = \"x\", ms = 1, mew = 0.5, label = \"Data\")\n", "pl.plot(T[selection], np.polyval(fit24, T[selection]), lw = 1, label = \"Order 2 fit\")" ] }, { "cell_type": "code", "execution_count": 124, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[]" ] }, "execution_count": 124, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "T = c2x2[:,0]\n", "selection = np.logical_and(T > 2.2, T < 2.9)\n", "\n", "fit22 = np.polyfit(T[selection], c2x2[:,5][selection], 2)\n", "\n", "pl.figure()\n", "pl.plot(T, c2x2[:,5], ls = \"\", marker = \"x\", ms = 1, mew = 0.5, label = \"Data\")\n", "pl.plot(T[selection], np.polyval(fit22, T[selection]), lw = 1, label = \"Order 2 fit\")" ] }, { "cell_type": "code", "execution_count": 127, "metadata": {}, "outputs": [], "source": [ "#creates a file containing the curie temperatures for the five lattice sizes\n", "np.savetxt(\"Curie.dat\", np.column_stack(np.array([[2, 4, 8, 16, 32], [-fit22[1] / (2 * fit22[0]), -fit24[1] / (2 * fit24[0]), -fit28[1] / (2 * fit28[0]), -fit216[1] / (2 * fit216[0]), -fit232[1] / (2 * fit232[0])]])))" ] }, { "cell_type": "code", "execution_count": 152, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "#loads curie temperatures\n", "curiedata = np.loadtxt(\"Curie.dat\")\n", "\n", "#creates the straight line fit\n", "fitcurie = np.polyfit(1 / curiedata[:,0], curiedata[:,1], 1, cov = True)\n", "\n", "pl.figure()\n", "pl.plot(1 / curiedata[:,0], curiedata[:,1], ls = \"\", marker = \"x\", ms = 4, mew = 0.5, label = \"Data\")\n", "pl.plot([-0.2,0.7], np.polyval(fitcurie[0], [-0.2,0.7]), lw = 1, label = \"Linear fit\")\n", "#plots the y axis\n", "pl.plot([0,0],[2,3], ls = \"--\")\n", "#plots a horizontal line at the y-intercept\n", "pl.plot([-1,1],2 * [fitcurie[0][1]], ls = \"--\" , label = \"T = 2.29\")\n", "pl.xlim([-0.1,0.6])\n", "pl.ylim([2.25,2.6])\n", "pl.xlabel(\"1 / Lattice Length\")\n", "pl.ylabel(\"Curie temperature\")\n", "pl.legend()\n", "pl.savefig(\"Curie.png\", dpi = 300)\n", "pl.show()" ] }, { "cell_type": "code", "execution_count": 148, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(array([0.52854139, 2.2868124 ]), array([[ 0.00970613, -0.00188056],\n", " [-0.00188056, 0.00064644]]))" ] }, "execution_count": 148, "metadata": {}, "output_type": "execute_result" } ], "source": [ "fitcurie" ] }, { "cell_type": "code", "execution_count": 156, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([[-0.04758923, -0.94361596, -0.2975907 , 0.76386894, -0.83569791],\n", " [-0.0748526 , 0.43133863, -0.99525877, -0.08666995, -0.69842653],\n", " [ 0.55411962, 0.59286319, 0.826757 , 0.0695626 , 0.98744436],\n", " [ 0.9425918 , -0.00547443, -0.90875198, -0.97940631, 0.44680952],\n", " [-0.97555721, -0.68183658, -0.99070604, -0.04453518, 0.59921396]])" ] }, "execution_count": 156, "metadata": {}, "output_type": "execute_result" } ], "source": [ "np.cos(np.random.random(size = (5, 5)) * 2 * np.pi)" ] }, { "cell_type": "code", "execution_count": 164, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "13.0" ] }, "execution_count": 164, "metadata": {}, "output_type": "execute_result" } ], "source": [ "np.sqrt(np.sum(np.array([-12,5]) ** 2))" ] }, { "cell_type": "code", "execution_count": 172, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "11.0" ] }, "execution_count": 172, "metadata": {}, "output_type": "execute_result" } ], "source": [ "np.absolute((5+6) * 1j)" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "from matplotlib import cm" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "hsv = cm.get_cmap('hsv',256)" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(0.0, 1.0, 0.9647031631761764, 1.0)" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "hsv(0.5)" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "1" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "5 % 2" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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"text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "pl.matshow(np.array(4 * [[0.1,0.2,0.3,0.7]]), cmap = hsv)" ] }, { "cell_type": "code", "execution_count": 197, "metadata": {}, "outputs": [], "source": [ "pl.matshow?" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "import matplotlib.animation as animation" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "Writer = animation.writers['ffmpeg']\n", "writer = Writer(fps=15, metadata=dict(artist='Me'), bitrate=1800)" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "def update_line(num, data, line):\n", " line.set_data(data[..., :num])\n", " return line,\n", "\n", "fig1 = pl.figure()\n", "\n", "data = np.random.rand(2, 250)\n", "l, = pl.plot([], [], 'r-')\n", "pl.xlim(0, 1)\n", "pl.ylim(0, 1)\n", "pl.xlabel('x')\n", "pl.title('test')\n", "line_ani = animation.FuncAnimation(fig1, update_line, 250, fargs=(data, l),\n", " interval=50, blit=True)\n", "line_ani.save('lines.mp4', writer=writer)" ] }, { "cell_type": "code", "execution_count": 45, "metadata": {}, "outputs": [ { "data": { "image/png": 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FEWdfBlyW5HZgK3B2Tb8VPcd9GjgQuG7y3yI3VNXfzGpYVW1L8j4mR1dzwGVVdces5j3DKcA7gNuS3DK97eKq+sZI8/elc4DLp99g7gbeNcbQmpw2XwHcxOSs5WYav5rCV1BI6sL+ehorSXvE2EnqgrGT1AVjJ6kLxk5SF4ydpC4YO0ldMHaSuvC/kBG4Wkx96B4AAAAASUVORK5CYII=\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig2 = pl.figure(figsize = [5, 5])\n", "\n", "x = np.arange(-9, 10)\n", "y = np.arange(-9, 10).reshape(-1, 1)\n", "base = 19 * [19 * [1]]\n", "ims = []\n", "for add in np.arange(15):\n", " ims.append((pl.pcolor(x, y, base + add, norm=pl.Normalize(0, 30)),))\n", "\n", "im_ani = animation.ArtistAnimation(fig2, ims, interval=50, repeat_delay=3000,\n", " blit=True)\n", "im_ani.save('im.mp4', writer=writer)" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [], "source": [ "animation.ArtistAnimation?" ] }, { "cell_type": "code", "execution_count": 47, "metadata": {}, "outputs": [], "source": [ "pl.pcolor?" ] }, { "cell_type": "code", "execution_count": 60, "metadata": {}, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig = pl.figure(figsize = [5, 5])\n", "\n", "huh = []\n", "\n", "for a in np.arange(100):\n", " huh.append((pl.pcolor(np.arange(0, 2), np.arange(0, 2), np.array(2 * [2 * [(a / 10) % (2 * np.pi)]]), cmap = \"hsv\", vmin = 0, vmax = 2 * np.pi),))\n", "\n", "#huh = [((pl.pcolor(np.arange(0, 2), np.arange(0, 2), 2 * [2 * [1]]),)), ((pl.pcolor(np.arange(0, 2), np.arange(0, 2), 2 * [2 * [2]],)))]\n", "\n", "testanim = animation.ArtistAnimation(fig, huh, repeat = False)\n", "\n", "testanim.save(\"test.mp4\", writer = writer)" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [], "source": [ "animation.FuncAnimation?" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "from IsingLatticecolor import *" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Step 0\n", "Step 10000\n", "Step 20000\n", "Step 30000\n", "Step 40000\n", "Step 50000\n", "Step 60000\n", "Step 70000\n", "Step 80000\n", "Step 90000\n", "Step 100000\n", "Step 110000\n", "Step 120000\n", "Step 130000\n", "Step 140000\n", "Step 150000\n", "Step 160000\n", "Step 170000\n", "Step 180000\n", "Step 190000\n", "Step 200000\n", "Step 210000\n", "Step 220000\n", "Step 230000\n", "Step 240000\n", "Step 250000\n", "Step 260000\n", "Step 270000\n", "Step 280000\n", "Step 290000\n", "Step 300000\n", "Step 310000\n", "Step 320000\n", "Step 330000\n", "Step 340000\n", "Step 350000\n", "Step 360000\n", "Step 370000\n", "Step 380000\n", "Step 390000\n", "Step 400000\n", "Step 410000\n", "Step 420000\n", "Step 430000\n", "Step 440000\n", "Step 450000\n", "Step 460000\n", "Step 470000\n", "Step 480000\n", "Step 490000\n", "Step 500000\n" ] }, { "data": { "image/png": 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\n", 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "n_rows = 32\n", "n_cols = 32\n", "temperature = 0.1\n", "runtime = 500001\n", "il = IsingLatticeColor(n_rows, n_cols)\n", "spins = n_rows*n_cols\n", "times = range(runtime)\n", "\n", "sfig = pl.figure(figsize = [10, 10])\n", "\n", "E = []\n", "M = []\n", "L = []\n", "for i in times:\n", " if i % 100 == 0:\n", " L.append((pl.pcolor(np.arange(0, n_rows + 1), np.arange(0, n_cols + 1), np.concatenate((np.concatenate((np.flipud(il.lattice), np.zeros((n_rows, 1))), axis = 1), np.zeros((1, n_cols + 1))), axis = 0), cmap = \"hsv\", vmin = 0, vmax = 2 * np.pi),))\n", " if i % 10000 == 0:\n", " print(\"Step\", i)\n", " energy, magnetisation = il.montecarlostep(temperature)\n", " E.append(energy)\n", " M.append(magnetisation)\n", "fig = pl.figure()\n", "matax = fig.add_subplot(3,1,1)\n", "matax.matshow(il.lattice, cmap = \"hsv\", vmin = 0, vmax = 2 * np.pi)\n", "enerax = fig.add_subplot(3,1,2)\n", "enerax.set_ylabel(\"Energy per spin\")\n", "enerax.set_xlabel(\"Monte Carlo Steps\")\n", "enerax.set_ylim([-2.1, 2.1])\n", "magax = fig.add_subplot(3,1,3)\n", "magax.set_ylabel(\"Magnetisation per spin\")\n", "magax.set_xlabel(\"Monte Carlo Steps\")\n", "magax.set_ylim([-0.1, 1.1])\n", "enerax.plot(times, np.array(E)/spins)\n", "magax.plot(times, np.array(M)/spins)\n", "fig.savefig(\"animlong2ff.png\", dpi = 300)\n", "\n", "\n", "Writer = animation.writers['ffmpeg']\n", "writer = Writer(fps=30, metadata=dict(artist='Me'), bitrate=1800)\n", "anim = animation.ArtistAnimation(sfig, L, repeat = False)\n", "anim.save(\"animlong2.mp4\", writer = writer)" ] }, { "cell_type": "code", "execution_count": 55, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[(,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,),\n", " (,)]" ] }, "execution_count": 55, "metadata": {}, "output_type": "execute_result" } ], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "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": "3.6.6" } }, "nbformat": 4, "nbformat_minor": 2 }