Pragalbh mm19 b012

Pragalbhv_MM19B012/Pragalbhv_assignment1.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Question1\n",
+    "Create two vectors 𝑦 and 𝑦̂ having the same dimensions, where 𝑦̂ should consist of random numbers between [0,1) and 𝑦 should contain 0𝑠 and1𝑠, for example, 𝑦=[0,1,1,0,1,0,0,1,...,1]. Compute the Cross-Entropy loss function\n",
+    "\n",
+    "n = 100, is the total number of elementsin y and 𝑦̂\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "import numpy as np\n",
+    "class q1():\n",
+    "    def __init__(self,n=100):\n",
+    "        self.n=n\n",
+    "        self.y_hat=np.random.random(self.n)\n",
+    "        self.y=np.random.randint(0,2,self.n)\n",
+    "    \n",
+    "    def check(self,a,b,c):# to test testcases\n",
+    "        self.n=a\n",
+    "        self.y_hat=b\n",
+    "        self.y=c\n",
+    "        \n",
+    "    def crossentropy(self):\n",
+    "        O=self.y*np.log2(self.y_hat)+(1-self.y)*np.log2(1-self.y_hat)\n",
+    "        O=-sum(O)/self.n\n",
+    "        return O\n",
+    "            \n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# b=q1(5)\n",
+    "# b.check(5,np.array([0.32, 0.56, 0.71, 0.14, 0.57]),np.array([1, 0, 1, 1, 0]))\n",
+    "# b.check(4,np.array([0.23, 0.54, 0.61, 0.89]),np.array([0, 0, 1, 1]))\n",
+    "# b.crossentropy()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "y:  [0 0 0 1 1 1 1 1 1 1 0 1 0 0 1 1 0 1 1 0 1 1 0 0 0 1 0 0 0 1 1 0 0 0 1 0 1\n",
+      " 0 0 0 1 0 0 1 1 0 1 1 1 1 1 1 0 0 1 1 0 0 1 0 1 1 1 1 0 1 1 1 1 0 1 0 0 0\n",
+      " 1 1 1 1 1 0 1 1 0 1 1 0 0 0 0 1 0 0 0 0 0 0 1 0 1 1]\n",
+      "y^:  [0.51021649 0.72948491 0.77934699 0.16864048 0.9810205  0.52897531\n",
+      " 0.42077713 0.24993429 0.29245122 0.47707456 0.68231908 0.24288666\n",
+      " 0.12652212 0.28854146 0.44658798 0.76661013 0.9325786  0.85773805\n",
+      " 0.94331178 0.06502094 0.42803983 0.98628899 0.62867782 0.82255184\n",
+      " 0.9620715  0.05291848 0.75515617 0.56735066 0.24574422 0.7224453\n",
+      " 0.6380315  0.01306936 0.77109653 0.48600201 0.36626264 0.29992089\n",
+      " 0.92651081 0.69393579 0.29673897 0.5465854  0.47831487 0.28070568\n",
+      " 0.14715873 0.81778697 0.66073728 0.46008507 0.9584546  0.32148232\n",
+      " 0.82442716 0.75120344 0.371478   0.09903866 0.63822627 0.98822728\n",
+      " 0.83935984 0.41268517 0.65951624 0.46678992 0.86718493 0.26555129\n",
+      " 0.22640279 0.40830547 0.01748741 0.9900541  0.35860553 0.82219612\n",
+      " 0.53973776 0.28845018 0.91035037 0.93150135 0.30976138 0.03925348\n",
+      " 0.35523396 0.18286391 0.65574514 0.90833396 0.26349271 0.53125752\n",
+      " 0.58091839 0.87783523 0.02759129 0.97593767 0.57664664 0.74691748\n",
+      " 0.49616255 0.71016896 0.58393564 0.13386478 0.51870505 0.74418914\n",
+      " 0.32108295 0.42511076 0.07943298 0.24763562 0.32567092 0.83955447\n",
+      " 0.04961893 0.28661403 0.01968282 0.99951812]\n",
+      "O:  1.307509498109142\n"
+     ]
+    }
+   ],
+   "source": [
+    "answer1=q1()\n",
+    "print('y: ',answer1.y)\n",
+    "print('y^: ',answer1.y_hat)\n",
+    "print('O: ',answer1.crossentropy())\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Question 2\n",
+    "Write a Python class to find a pair of elements (indices of the two numbers) from a given array whose sum equals a specific target number"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class findpair():\n",
+    "    def __init__(self,arr,target):\n",
+    "        self.dicta=dict()\n",
+    "        self.arr=arr\n",
+    "        self.target=target\n",
+    "    \n",
+    "    def find(self):\n",
+    "        N=len(self.arr)\n",
+    "        count=1\n",
+    "        for i in range(N):\n",
+    "            for j in range(N):\n",
+    "                if self.arr[i]+self.arr[j]==self.target:\n",
+    "                    self.dicta[count]=[i,j]\n",
+    "                    count+=1\n",
+    "        return self.dicta\n",
+    "        "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "10 20 10 40 50 60 70\n",
+      "50\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "{1: [0, 3], 2: [2, 3], 3: [3, 0], 4: [3, 2]}"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "\n",
+    "array=input() #assumed to be 1 23 45 66 and such...\n",
+    "target=int(input())\n",
+    "arr=list(map(int,array.strip(' ').split()))\n",
+    "#___\n",
+    "answer2=findpair(arr,target)\n",
+    "answer2.find()"
+   ]
+  }
+ ],
+ "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": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}