Performance optimization
This commit is contained in:
parent
47f333769a
commit
38eb54873f
22
build.gradle
22
build.gradle
@ -1,5 +1,5 @@
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plugins {
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id "org.jetbrains.kotlin.jvm" version "1.2.30"
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id "org.jetbrains.kotlin.jvm" version "1.3.10"
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id "java"
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id "application"
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}
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@ -18,6 +18,10 @@ repositories {
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dependencies {
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compile group: 'org.apache.commons', name: 'commons-math3', version: '3.6.1'
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compile "org.jetbrains.kotlin:kotlin-stdlib-jdk8"
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// https://mvnrepository.com/artifact/org.apache.commons/commons-rng-simple
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compile group: 'org.apache.commons', name: 'commons-rng-simple', version: '1.1'
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testCompile group: 'junit', name: 'junit', version: '4.12'
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}
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@ -25,12 +29,12 @@ compileKotlin {
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kotlinOptions.jvmTarget = "1.8"
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}
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task runTrap(type: JavaExec) {
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classpath = sourceSets.main.runtimeClasspath
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main = mainClassName
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// arguments to pass to the application
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args 'D:\\Work\\Numass\\trapping\\trap.out'
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}
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//task runTrap(type: JavaExec) {
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// classpath = sourceSets.main.runtimeClasspath
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//
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// main = mainClassName
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//
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// // arguments to pass to the application
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// args 'D:\\Work\\Numass\\trapping\\trap.out'
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//}
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@ -11,33 +11,21 @@
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Added jar: [commons-math3-3.6.1.jar]\n",
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"Added jar: [trapping-dev.jar]\n"
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]
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}
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],
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"source": [
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"%classpath add jar ../build/install/trapping/lib/commons-math3-3.6.1.jar\n",
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"%classpath add jar ../build/install/trapping/lib/trapping-dev.jar"
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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": 17,
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"metadata": {
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"ExecuteTime": {
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"end_time": "2018-04-08T18:58+0000",
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"start_time": "2018-04-08T18:58+0000"
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}
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},
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"outputs": [
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "3161978b-3c71-4d18-a97e-f972beece3ff",
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"version_major": 2,
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"version_minor": 0
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},
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"method": "display_data"
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "30d035de-65b2-4c03-96c6-25b897f10de4",
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"model_id": "6884d267-e5ee-4841-8c60-9c66eea437c5",
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"version_major": 2,
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"version_minor": 0
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},
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@ -48,11 +36,39 @@
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}
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],
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"source": [
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"def scatter = inr.numass.trapping.Scatter.INSTANCE\n",
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"%classpath add jar ../build/install/trapping/lib/commons-math3-3.6.1.jar\n",
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"%classpath add jar ../build/install/trapping/lib/trapping-dev.jar"
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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": 11,
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"metadata": {
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"ExecuteTime": {
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"end_time": "2018-04-08T18:58+0000",
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"start_time": "2018-04-08T18:58+0000"
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}
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},
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"outputs": [
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "582da53b-a518-4a8a-b7ce-84d38c580cf3",
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"version_major": 2,
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"version_minor": 0
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},
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"method": "display_data"
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"scatter = inr.numass.trapping.Scatter.INSTANCE\n",
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"\n",
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"def e = (1..20) // energy in keV\n",
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"\n",
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"def factor = 1e-22\n",
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"factor = 1e-22\n",
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"def sigmaEl = e.collect{scatter.sigmael(it*1000)/factor}\n",
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"def sigmaIon = e.collect{scatter.sigmaion(it*1000)/factor}\n",
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"def sigmaExc = e.collect{scatter.sigmaexc(it*1000)/factor}\n",
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@ -63,6 +79,112 @@
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"plot << new Line(x: e, y: sigmaExc, displayName: \"Excitation\")\n"
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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": 15,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"E(keV)\telastic\tion\texc\n",
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"12.0\t0.43948540252301355\t2.7362696996880764\t2.2754271467658227\n",
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"12.1\t0.4360219815420227\t2.716347129996631\t2.259247553470829\n",
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"12.2\t0.4326153394877464\t2.6967291910800784\t2.2433117665045716\n",
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"12.3\t0.42926409223681455\t2.6774088086825643\t2.227614186457129\n",
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"12.4\t0.42596690029168804\t2.6583791281775273\t2.212149386181278\n",
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"12.5\t0.4227224669965498\t2.639633506055748\t2.1969121041685504\n",
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"12.6\t0.41952953683810995\t2.621165501807934\t2.1818972382301722\n",
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"12.7\t0.4163868938266485\t2.602968870180603\t2.1670998394665926\n",
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"12.8\t0.4132933599529065\t2.585037553785318\t2.1525151065102723\n",
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"12.9\t0.4102477937167139\t2.567365676042546\t2.138138380027344\n",
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"13.0\t0.4072490887234942\t2.5499475344425586\t2.123965137464613\n",
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"13.1\t0.4042961723450181\t2.532777594106803\t2.1099909880291814\n",
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"13.2\t0.40138800444100226\t2.515850481634202\t2.096211667888705\n",
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"13.3\t0.3985235761383543\t2.4991609792177183\t2.082623035581028\n",
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"13.4\t0.3957019086650494\t2.4827040190174023\t2.069221067622563\n",
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"13.5\t0.39292205223581\t2.466474677776929\t2.0560018543054204\n",
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"13.6\t0.39018308498692494\t2.4504681716713828\t2.042961595673853\n",
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"13.7\t0.3874841119576961\t2.434679851374739\t2.0300965976711156\n",
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"13.8\t0.3848242641161482\t2.419105197336177\t2.0174032684483527\n",
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"13.9\t0.3822026974267757\t2.403739815254919\t2.00487811482759\n",
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"14.0\t0.3796185919582249\t2.3885794317439313\t1.9925177389113418\n",
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"14.1\t0.3770711510289289\t2.373619890173301\t1.9803188348317768\n",
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"14.2\t0.3745596003888268\t2.358857146684646\t1.9682781856327505\n",
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"14.3\t0.3720831874354002\t2.3442872663683785\t1.9563926602783916\n",
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"14.4\t0.36964118046236066\t2.32990641959609\t1.9446592107822769\n",
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"14.5\t0.36723286793941123\t2.315710878500726\t1.9330748694515214\n",
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"14.6\t0.3648575578215951\t2.3016970135976464\t1.9216367462404509\n",
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"14.7\t0.36251457688682004\t2.287861290540006\t1.910342026208781\n",
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"14.8\t0.3602032701002296\t2.274200267002247\t1.8991879670794969\n",
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"14.9\t0.357923000004158\t2.26071058968582\t1.8881718968918926\n",
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"15.0\t0.3556731461324769\t2.2473889914415754\t1.8772912117454528\n",
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"15.1\t0.353453104448203\t2.234232288503513\t1.8665433736304802\n",
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"15.2\t0.35126228680329497\t2.221237377828907\t1.8559259083415982\n",
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"15.3\t0.3491001204196282\t2.2084012345400286\t1.845436403470438\n",
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"15.4\t0.3469660473901797\t2.1957209094629615\t1.835072506474014\n",
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"15.5\t0.3448595241995173\t2.1831935267592297\t1.824831922815469\n",
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"15.6\t0.3427800212627204\t2.170816281646157\t1.8147124141740314\n",
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"15.7\t0.34072702248191666\t2.158586438202101\t1.8047117967211865\n",
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"15.8\t0.33870002481965195\t2.1465013272528792\t1.7948279394602165\n",
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"15.9\t0.3366985378883526\t2.134558344335901\t1.7850587626263867\n",
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"16.0\t0.33472208355517563\t2.122754947738674\t1.7754022361452126\n",
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"16.1\t0.33277019556158083\t2.111088656608532\t1.7658563781463463\n",
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"16.2\t0.33084241915698676\t2.0995570491305764\t1.7564192535307461\n",
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"16.3\t0.32893831074590485\t2.0881577607709536\t1.7470889725889123\n",
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"16.4\t0.3270574375479805\t2.0768884825827687\t1.7378636896680617\n",
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"16.5\t0.3251993772703896\t2.0657469595720115\t1.7287416018862318\n",
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"16.6\t0.32336371779207285\t2.054730989121034\t1.7197209478913829\n",
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"16.7\t0.3215500568593091\t2.043838419467228\t1.7108000066636726\n",
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"16.8\t0.31975800179215863\t2.0330671482346325\t1.7019770963591483\n",
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"16.9\t0.3179871692013229\t2.022415121016355\t1.693250573193194\n",
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"17.0\t0.3162371847149949\t2.011880330005736\t1.684618830362136\n",
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"17.1\t0.3145076827152896\t2.0014608126743285\t1.6760802970014965\n",
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"17.2\t0.31279830608386505\t1.991154650494809\t1.6676334371794341\n",
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"17.3\t0.31110870595636253\t1.9809599677070577\t1.6592767489239986\n",
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"17.4\t0.3094385414853119\t1.9708749301257074\t1.6510087632828718\n",
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"17.5\t0.3077874796111622\t1.9608977439875288\t1.6428280434143254\n",
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"17.6\t0.30615519484111486\t1.9510266548371218\t1.6347331837082066\n",
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"17.7\t0.3045413690354524\t1.9412599464494087\t1.6267228089357717\n",
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"17.8\t0.3029456912010658\t1.9315959397875393\t1.6187955734272899\n",
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"17.9\t0.3013678572919011\t1.9220329919948316\t1.6109501602763423\n",
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"18.0\t0.29980757001605496\t1.9125694954194674\t1.603185280569817\n",
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"18.1\t0.29826453864926233\t1.9032038766707016\t1.5954996726426307\n",
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"18.2\t0.29673847885453164\t1.8939345957053948\t1.5878921013562524\n",
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"18.3\t0.29522911250768985\t1.8847601449437406\t1.5803613574001418\n",
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"18.4\t0.2937361675286164\t1.8756790484131034\t1.5729062566152603\n",
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"18.5\t0.2922593777179467\t1.866689860918917\t1.565525639338836\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"null"
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]
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},
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"execution_count": 15,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"println \"E(keV)\\telastic\\tion\\texc\"\n",
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"for(d = 12.0; d < 18.6; d += 0.1){\n",
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" def sigmaEl = scatter.sigmael(d*1000)/factor\n",
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" def sigmaIon = scatter.sigmaion(d*1000)/factor\n",
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" def sigmaExc = scatter.sigmaexc(d*1000)/factor\n",
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" println \"$d\\t$sigmaEl\\t$sigmaIon\\t$sigmaExc\"\n",
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"}"
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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": null,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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23
src/main/kotlin/inr/numass/trapping/FunctionCache.kt
Normal file
23
src/main/kotlin/inr/numass/trapping/FunctionCache.kt
Normal file
@ -0,0 +1,23 @@
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package inr.numass.trapping
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import java.util.*
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class FunctionCache(val xPrecision: Double, val function: (Double) -> Double) {
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private val values = TreeMap<Double, Double>()
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operator fun invoke(x: Double): Double {
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val floor: MutableMap.MutableEntry<Double, Double>? = values.floorEntry(x)
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val ceil: MutableMap.MutableEntry<Double, Double>? = values.ceilingEntry(x)
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if (floor == null || ceil == null || ceil.key - floor.key <= xPrecision) {
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val newValue = function(x)
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values[x] = newValue
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return newValue
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} else {
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val x0 = floor.key
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val x1 = ceil.key
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val y0 = floor.value
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val y1 = ceil.value
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return y0 + (x - x0) * (y1 - y0) / (x1 - x0)
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}
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}
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}
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28
src/main/kotlin/inr/numass/trapping/RandomGeneratorBridge.kt
Normal file
28
src/main/kotlin/inr/numass/trapping/RandomGeneratorBridge.kt
Normal file
@ -0,0 +1,28 @@
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package inr.numass.trapping
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import org.apache.commons.math3.random.RandomGenerator
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import org.apache.commons.rng.UniformRandomProvider
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class RandomGeneratorBridge(val provider: UniformRandomProvider) : RandomGenerator {
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override fun nextBoolean(): Boolean = provider.nextBoolean()
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override fun nextFloat(): Float = provider.nextFloat()
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override fun setSeed(seed: Int) = error("Not supported")
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override fun setSeed(seed: IntArray?) = error("Not supported")
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override fun setSeed(seed: Long) = error("Not supported")
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override fun nextBytes(bytes: ByteArray) = provider.nextBytes(bytes)
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override fun nextInt(): Int = provider.nextInt()
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override fun nextInt(n: Int): Int = provider.nextInt(n)
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override fun nextGaussian(): Double = error("Not supported")
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override fun nextDouble(): Double = provider.nextDouble()
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override fun nextLong(): Long = provider.nextLong()
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}
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@ -407,7 +407,7 @@ object Scatter {
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while (i <= 30) {
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G = 1.0 / 2.0 + (y + sin(2.0 * y) / 2.0) / Math.PI
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Gp = (1.0 + cos(2.0 * y)) / Math.PI
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y = y - (G - F) / Gp
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y -= (G - F) / Gp
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if (abs(G - F) < 1e-8) {
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break
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}
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@ -666,16 +666,23 @@ object Scatter {
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return Dinelreturn
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}
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private fun sumexc(K: Double): Double {
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private fun _sumexc(K: Double): Double {
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val Kvec = doubleArrayOf(0.0, 0.1, 0.2, 0.4, 0.6, 0.8, 1.0, 1.2, 1.5, 1.8, 2.0, 2.5, 3.0, 4.0, 5.0)
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val fvec = arrayOf(doubleArrayOf(2.907e-1, 2.845e-1, 2.665e-1, 2.072e-1, 1.389e-1, // B
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8.238e-2, 4.454e-2, 2.269e-2, 7.789e-3, 2.619e-3, 1.273e-3, 2.218e-4, 4.372e-5, 2.889e-6, 4.247e-7), doubleArrayOf(3.492e-1, 3.367e-1, 3.124e-1, 2.351e-1, 1.507e-1, // C
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8.406e-2, 4.214e-2, 1.966e-2, 5.799e-3, 1.632e-3, 6.929e-4, 8.082e-5, 9.574e-6, 1.526e-7, 7.058e-9), doubleArrayOf(6.112e-2, 5.945e-2, 5.830e-2, 5.072e-2, 3.821e-2, // Bp
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2.579e-2, 1.567e-2, 8.737e-3, 3.305e-3, 1.191e-3, 6.011e-4, 1.132e-4, 2.362e-5, 1.603e-6, 2.215e-7), doubleArrayOf(2.066e-2, 2.127e-2, 2.137e-2, 1.928e-2, 1.552e-2, // Bpp
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1.108e-2, 7.058e-3, 4.069e-3, 1.590e-3, 5.900e-4, 3.046e-4, 6.142e-5, 1.369e-5, 9.650e-7, 1.244e-7), doubleArrayOf(9.405e-2, 9.049e-2, 8.613e-2, 7.301e-2, 5.144e-2, // D
|
||||
3.201e-2, 1.775e-2, 8.952e-3, 2.855e-3, 8.429e-4, 3.655e-4, 4.389e-5, 5.252e-6, 9.010e-8, 7.130e-9), doubleArrayOf(4.273e-2, 3.862e-2, 3.985e-2, 3.362e-2, 2.486e-2, // Dp
|
||||
1.612e-2, 9.309e-3, 4.856e-3, 1.602e-3, 4.811e-4, 2.096e-4, 2.498e-5, 2.905e-6, 5.077e-8, 6.583e-9), doubleArrayOf(0.000e-3, 2.042e-3, 7.439e-3, 2.200e-2, 3.164e-2, // EF
|
||||
3.161e-2, 2.486e-2, 1.664e-2, 7.562e-3, 3.044e-3, 1.608e-3, 3.225e-4, 7.120e-5, 6.290e-6, 1.066e-6))
|
||||
val fvec = arrayOf(
|
||||
doubleArrayOf(2.907e-1, 2.845e-1, 2.665e-1, 2.072e-1, 1.389e-1,
|
||||
8.238e-2, 4.454e-2, 2.269e-2, 7.789e-3, 2.619e-3, 1.273e-3, 2.218e-4, 4.372e-5, 2.889e-6, 4.247e-7), // B
|
||||
doubleArrayOf(3.492e-1, 3.367e-1, 3.124e-1, 2.351e-1, 1.507e-1,
|
||||
8.406e-2, 4.214e-2, 1.966e-2, 5.799e-3, 1.632e-3, 6.929e-4, 8.082e-5, 9.574e-6, 1.526e-7, 7.058e-9), // C
|
||||
doubleArrayOf(6.112e-2, 5.945e-2, 5.830e-2, 5.072e-2, 3.821e-2,
|
||||
2.579e-2, 1.567e-2, 8.737e-3, 3.305e-3, 1.191e-3, 6.011e-4, 1.132e-4, 2.362e-5, 1.603e-6, 2.215e-7), // Bp
|
||||
doubleArrayOf(2.066e-2, 2.127e-2, 2.137e-2, 1.928e-2, 1.552e-2,
|
||||
1.108e-2, 7.058e-3, 4.069e-3, 1.590e-3, 5.900e-4, 3.046e-4, 6.142e-5, 1.369e-5, 9.650e-7, 1.244e-7), // Bpp
|
||||
doubleArrayOf(9.405e-2, 9.049e-2, 8.613e-2, 7.301e-2, 5.144e-2,
|
||||
3.201e-2, 1.775e-2, 8.952e-3, 2.855e-3, 8.429e-4, 3.655e-4, 4.389e-5, 5.252e-6, 9.010e-8, 7.130e-9), // D
|
||||
doubleArrayOf(4.273e-2, 3.862e-2, 3.985e-2, 3.362e-2, 2.486e-2,
|
||||
1.612e-2, 9.309e-3, 4.856e-3, 1.602e-3, 4.811e-4, 2.096e-4, 2.498e-5, 2.905e-6, 5.077e-8, 6.583e-9), // Dp
|
||||
doubleArrayOf(0.000e-3, 2.042e-3, 7.439e-3, 2.200e-2, 3.164e-2,
|
||||
3.161e-2, 2.486e-2, 1.664e-2, 7.562e-3, 3.044e-3, 1.608e-3, 3.225e-4, 7.120e-5, 6.290e-6, 1.066e-6))// EF
|
||||
val EeV = doubleArrayOf(12.73, 13.20, 14.77, 15.3, 14.93, 15.4, 13.06)
|
||||
var n: Int = 0
|
||||
var j: Int
|
||||
@ -690,33 +697,32 @@ object Scatter {
|
||||
//
|
||||
while (n <= nmax) {
|
||||
En = EeV[n] / 27.21 // En is the excitation energy in Hartree atomic units
|
||||
if (K >= 5.0) {
|
||||
f[n] = 0.0
|
||||
} else if (K >= 3.0 && K <= 4.0) {
|
||||
f[n] = fvec[n][12] + (K - 3.0) * (fvec[n][13] - fvec[n][12])
|
||||
} else if (K >= 4.0 && K <= 5.0) {
|
||||
f[n] = fvec[n][13] + (K - 4.0) * (fvec[n][14] - fvec[n][13])
|
||||
} else {
|
||||
j = 0
|
||||
while (j < 14) {
|
||||
if (K >= Kvec[j] && K <= Kvec[j + 1]) {
|
||||
jmin = j - 1
|
||||
when {
|
||||
K >= 5.0 -> f[n] = 0.0
|
||||
K in 3.0..4.0 -> f[n] = fvec[n][12] + (K - 3.0) * (fvec[n][13] - fvec[n][12])
|
||||
K in 4.0..5.0 -> f[n] = fvec[n][13] + (K - 4.0) * (fvec[n][14] - fvec[n][13])
|
||||
else -> {
|
||||
j = 0
|
||||
while (j < 14) {
|
||||
if (K >= Kvec[j] && K <= Kvec[j + 1]) {
|
||||
jmin = j - 1
|
||||
}
|
||||
j++
|
||||
}
|
||||
j++
|
||||
if (jmin < 0) {
|
||||
jmin = 0
|
||||
}
|
||||
if (jmin > 11) {
|
||||
jmin = 11
|
||||
}
|
||||
j = 0
|
||||
while (j <= 3) {
|
||||
x4[j] = Kvec[jmin + j]
|
||||
f4[j] = fvec[n][jmin + j]
|
||||
j++
|
||||
}
|
||||
f[n] = lagrange(4, x4, f4, K)
|
||||
}
|
||||
if (jmin < 0) {
|
||||
jmin = 0
|
||||
}
|
||||
if (jmin > 11) {
|
||||
jmin = 11
|
||||
}
|
||||
j = 0
|
||||
while (j <= 3) {
|
||||
x4[j] = Kvec[jmin + j]
|
||||
f4[j] = fvec[n][jmin + j]
|
||||
j++
|
||||
}
|
||||
f[n] = lagrange(4, x4, f4, K)
|
||||
}
|
||||
sum += f[n] / En
|
||||
n++
|
||||
@ -724,15 +730,18 @@ object Scatter {
|
||||
return sum
|
||||
}
|
||||
|
||||
//Caching function for precision
|
||||
private val sumexcCache = FunctionCache(0.01, this::_sumexc)
|
||||
private fun sumexc(K: Double): Double = sumexcCache(K)
|
||||
|
||||
fun lagrange(n: Int, xn: DoubleArray, fn: DoubleArray, x: Double): Double {
|
||||
var i: Int
|
||||
var j: Int
|
||||
var j: Int = 0
|
||||
var f: Double = 0.0
|
||||
var aa: Double
|
||||
var bb: Double
|
||||
val a = DoubleArray(100)
|
||||
val b = DoubleArray(100)
|
||||
j = 0
|
||||
while (j < n) {
|
||||
i = 0
|
||||
while (i < n) {
|
||||
|
||||
@ -4,6 +4,8 @@ import org.apache.commons.math3.analysis.UnivariateFunction
|
||||
import org.apache.commons.math3.analysis.interpolation.LinearInterpolator
|
||||
import org.apache.commons.math3.random.JDKRandomGenerator
|
||||
import org.apache.commons.math3.random.RandomGenerator
|
||||
import org.apache.commons.rng.UniformRandomProvider
|
||||
import org.apache.commons.rng.simple.RandomSource
|
||||
|
||||
import java.io.*
|
||||
import java.util.stream.Stream
|
||||
@ -13,7 +15,7 @@ import java.util.stream.Stream
|
||||
*/
|
||||
class SimulationManager {
|
||||
|
||||
var generator: RandomGenerator = JDKRandomGenerator()
|
||||
var generator: UniformRandomProvider = RandomSource.create(RandomSource.SPLIT_MIX_64)
|
||||
|
||||
/**
|
||||
* output for accepted events
|
||||
@ -88,11 +90,11 @@ class SimulationManager {
|
||||
* @return
|
||||
*/
|
||||
@Synchronized
|
||||
fun simulateAll(num: Int): Counter {
|
||||
fun simulateAll(num: Number): Counter {
|
||||
val counter = Counter()
|
||||
val simulator = Simulator(eLow, thetaTransport, thetaPinch, gasDensity, bSource, magneticField, generator)
|
||||
val simulator = Simulator(eLow, thetaTransport, thetaPinch, gasDensity, bSource, magneticField, RandomGeneratorBridge(generator))
|
||||
|
||||
System.out.printf("%nStarting sumulation with initial energy %g and %d electrons.%n%n", initialE, num)
|
||||
System.out.printf("%nStarting sumulation with initial energy %g and %d electrons.%n%n", initialE, num.toLong())
|
||||
output.printf("%s\t%s\t%s\t%s\t%s\t%s%n", "E", "theta", "theta_start", "colNum", "L", "state")
|
||||
Stream.generate { getRandomTheta() }.limit(num.toLong()).parallel()
|
||||
.forEach { theta ->
|
||||
|
||||
@ -1,5 +1,6 @@
|
||||
package inr.numass.trapping
|
||||
|
||||
import org.apache.commons.rng.simple.RandomSource
|
||||
import java.time.Duration
|
||||
import java.time.Instant
|
||||
|
||||
@ -13,11 +14,13 @@ fun main(args: Array<String>) {
|
||||
|
||||
System.out.printf("Starting at %s%n%n", startTime.toString())
|
||||
SimulationManager().apply {
|
||||
generator = RandomSource.create(RandomSource.SPLIT_MIX_64)
|
||||
setOutputFile("D:\\Work\\Numass\\trapping\\test1.out")
|
||||
setFields(0.6, 3.7, 7.2)
|
||||
gasDensity = 1e19
|
||||
reportFilter = {true}
|
||||
}.simulateAll(1e5.toInt())
|
||||
initialE = 14000.0
|
||||
range = 4000.0
|
||||
}.simulateAll(1e6)
|
||||
|
||||
val finishTime = Instant.now()
|
||||
System.out.printf("%nFinished at %s%n", finishTime.toString())
|
||||
|
||||
Loading…
Reference in New Issue
Block a user