Upload New File

ddb26a0a · cprutean · be822f80 · ddb26a0a
Commit ddb26a0a authored 1 year ago by cprutean
--- a/CodeExamples/OneWayConditional.ipynb
+++ b/CodeExamples/OneWayConditional.ipynb
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "781271bc",
+   "metadata": {},
+   "source": [
+    "# $\\Pi$ Example"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5417046e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\"\"\"     Example of estimating Pi by Monte Carlo Simulation.\n",
+    "\"\"\"\n",
+    "import math\n",
+    "import random\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "def main():\n",
+    "    maxPoint = int(input(\"Number of points : \"))\n",
+    "    plotInterval = maxPoint/100\n",
+    "    xData = []\n",
+    "    yData = []\n",
+    "\n",
+    "    point = 0\n",
+    "    inside = 0\n",
+    "    while point < maxPoint:\n",
+    "        point += 1\n",
+    "        x = random.uniform(-1.0,1.0)    # Random between -1 -> 1for both x and y\n",
+    "        y = random.uniform(-1.0,1.0)\n",
+    "\n",
+    "        if x*x + y*y <= 1.0:   # Test if inside unit circle\n",
+    "            inside += 1        \n",
+    "\n",
+    "        if point % plotInterval == 0:   # Calcualte estimate for plot\n",
+    "           estimate = 4.0*inside/point\n",
+    "           xData.append(point)\n",
+    "           yData.append(estimate)\n",
+    "\n",
+    "    print(\"Estimate for PI after \" + str(maxPoint) + \" is \" + str(estimate))   \n",
+    "    plt.plot(xData,yData)      # Plot the estimate\n",
+    "    plt.plot([0,maxPoint],[math.pi,math.pi]) # Plot Pi \n",
+    "    plt.ylim(3.0,3.3)          # Limit graph range\n",
+    "    plt.title(\"Plot of estimate of Pi again points\")\n",
+    "    plt.show()\n",
+    "\n",
+    "\n",
+    "main()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.9.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
+%% Cell type:markdown id:781271bc tags:
+# $\Pi$ Example
+%% Cell type:code id:5417046e tags:
+``` python
+"""     Example of estimating Pi by Monte Carlo Simulation.
+"""
+import math
+import random
+import matplotlib.pyplot as plt
+def main():
+    maxPoint = int(input("Number of points : "))
+    plotInterval = maxPoint/100
+    xData = []
+    yData = []
+    point = 0
+    inside = 0
+    while point < maxPoint:
+        point += 1
+        x = random.uniform(-1.0,1.0)    # Random between -1 -> 1for both x and y
+        y = random.uniform(-1.0,1.0)
+        if x*x + y*y <= 1.0:   # Test if inside unit circle
+            inside += 1
+        if point % plotInterval == 0:   # Calcualte estimate for plot
+           estimate = 4.0*inside/point
+           xData.append(point)
+           yData.append(estimate)
+    print("Estimate for PI after " + str(maxPoint) + " is " + str(estimate))
+    plt.plot(xData,yData)      # Plot the estimate
+    plt.plot([0,maxPoint],[math.pi,math.pi]) # Plot Pi
+    plt.ylim(3.0,3.3)          # Limit graph range
+    plt.title("Plot of estimate of Pi again points")
+    plt.show()
+main()
+```