%matplotlib inlineimport numpy as npfrom matplotlib import pyplot as pltimport math Problem 3Notice that tan(1) = π/4, this means we can calculate π by using 4 × arctan(1)So this means that if we find Taylor series expansion of arctan(x) around x = 0, then we can calculate π to any accuracy we want.3.1) Find taylor expansion of arctan for 3 non-zero terms. If you forgot,13.2) Guess the rest of the terms1༤༤1arctan(2)=1 + x²3.3) Calculate π using taylor approximation for 200 non-zero terms. (you must write some sort of for loop to do it).1PythonPythonPython

3.1) Find Taylor Expansion of arctan(x) for 3 Non-Zero Termsimport numpy as npfrom matplotlib…

Answered: Problem 3 Notice that tan(1) = π/4,…

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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in java Revers an Array of n integers Reversing an Array1. Describe the definition of recursive function.oBase case(s)oRecursive case(s)2. Write the code.
ANSWER MUST BE IN PYTHON3. METHOD HEADER BELOW. #!/bin/python3 import math import os import random import re import sys import numpy as np import pandas as pd from sklearn.linear_model import LinearRegression def read_dataframe(): # Return a pandas dataframe from stdin return pd.read_csv(sys.stdin) def read_matrix(): # Return column names and data as a matrix df = read_dataframe() return list(df.columns), df.values def read_list(): # Return column names and data as a list of lists # Each element in the list corresponds to columns in the data col_names, val = read_matrix() return col_names, val.T.tolist() # # Complete the 'main' function below. # # The function is expected to return a STRING. # def main(): # Write your code here if __name__ == '__main__': fptr = open(os.environ['OUTPUT_PATH'], 'w') result = main() fptr.write(result + '\n') fptr.close()
Longest Common Subsequence:ExampleLCS for input Sequences “ABCDGH” and “AEDFHR” is “ADH” of length 3.LCS for input Sequences “AGGTAB” and “GXTXAYB” is “GTAB” of length 4.Implementation in Java.
%matplotlib inline import math import numpy as np from matplotlib import pyplot as plt def f(x): return math.sqrt(-x/(x+1)) def g(x): return math.tan(math.sqrt(2*(x + 1))) xs = np.linspace(-0.999,-0.1, 100) fx = [f(x) for x in xs] gx = [g(x) for x in xs] plt.plot(xs,fx) plt.plot(xs,gx) plt.grid
In java, the Arrays class contains a static binarySearch() method that returns …… if element is found. false true (-k–1) where k is the position before which the element should be inserted The index of the element
%matplotlib inlineimport mathimport numpy as npfrom matplotlib import pyplot as pltdef bad_poisson(lmd, k): return pow(lmd,k)*math.exp(-lmd)/math.factorial(k)# bad_poisson(1000,1000) # uncomment to see it breaks
6. Code for implement insertion sort in java.
import numpy as np%matplotlib inlinefrom matplotlib import pyplot as pltimport mathfrom math import exp np.random.seed(9999)def is_good_peak(mu, min_dist=0.8): if mu is None: return False smu = np.sort(mu) if smu[0] < 0.5: return False if smu[-1] > 2.5: return False for p, n in zip(smu, smu[1:]): #print(abs(p-n)) if abs(p-n) < min_dist: return False return True maxx = 3ndata = 500nset = 10l = []answers = []for iset in range(1, nset): npeak = np.random.randint(2,4) xs = np.linspace(0,maxx,ndata) ys = np.zeros(ndata) mu = None while not is_good_peak(mu): mu = np.random.random(npeak)*maxx for ipeak in range(npeak): m = mu[ipeak] sigma = np.random.random()*0.3 + 0.2 height = np.random.random()*0.5 + 1 ys += height*np.exp(-(xs-m)**2/sigma**2) ys += np.random.randn(ndata)*0.07 l.append(ys) answers.append(mu) p6_ys = lp6_xs =…
def findOccurrences(s, ch): lst = [] for i in range(0, len(s)): if a==s[i]: lst.append(i) return lst Use the code above instead of enumerate in the code posted below. n=int(input("Number of rounds of Hangman to be played:")) for i in range(0,n): word = input("welcome!") guesses = '' turns = int(input("Enter the number of failed attempts allowed:")) def hangman(word): secrete_word = "-" * len(word) print(" the secrete word " + secrete_word) user_input = input("Guess a letter: ") if user_input in word: occurences = findOccurrences(word, user_input) for index in occurences: secrete_word = secrete_word[:index] + user_input + secrete_word[index + 1:] print(secrete_word) else: user_input = input("Sorry that letter was not found, please try again: ") def findOccurrences(s, ch): return [i for i, letter in enumerate(s) if letter == ch] *** enumerate not discussed in…
IN JAVA Write recursive code and iterative code for binary search.
JAVA Language: Transpose Rotate. Question: Modify Transpose.encode() so that it uses a rotation instead of a reversal. That is, a word like “hello” should be encoded as “ohell” with a rotation of one character. (Hint: use a loop to append the letters into a new string) import java.util.*; public class TestTranspose { public static void main(String[] args) { String plain = "this is the secret message"; // Here's the message Transpose transpose = new Transpose(); String secret = transpose.encrypt(plain); System.out.println("\n ********* Transpose Cipher Encryption *********"); System.out.println("PlainText: " + plain); // Display the results System.out.println("Encrypted: " + secret); System.out.println("Decrypted: " + transpose.decrypt(secret));// Decrypt } } abstract class Cipher { public String encrypt(String s) { StringBuffer result = new…
2. Problem 2: In this problem you will test our "in class" version of Gaussian elimination against the version in numpy. Use both codes to solve some randomly chosen linear systems of size N 10, 20, 40, 80, 160, 320, 640, 1280, 2560, and 5120. Depending on your computer, the last two may or may not work. If they don't, just say so in your report. If you computer can do N- 10240 then try this as well. Note that in cach case N 10 * 2k for k = 1,..., 10. That is, each time we are doubling the size of the matrix. abone Plot the results as two curves. Our code in red and numPy in bluc. (Or whatever colors you prefer). Can you guess the function which governs the runtime? Based on this guess, how long would it take to do N 40960 using numPy? N=81920?

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