Computers and Technology, 03.12.2021 09:50, kaylastronaut
I have a problem with a task using scipy. optimize. minimize execution through the following methods: CG, BFG, Newton-CG, L-BFGS-B
Consider the following area: D = [-5.10]x[0.15]. This task, given below, must be performed in this domain. And executed in Jupyter notebook
Draw N = 100 random points uniformly distributed over D. For each point, run a local minimization of f using scipy. optimize. minimize with the following methods: CG, BFGS, Newton-CG, L-BFGS-B. For this task, you will have to write two other functions, one that returns the Jacobian matrix of f and one that returns the Hessian matrix of f . Store the answers in an array with shape N x 6, each row of which has the following data:
(x1, y1,x2, y2,v, c),
where (x1, y1) and (x2, y2) are respectively the starting and the final point of the optimization, while v is the final value of f . The final element of the row c is code of the used method, according to this correspondence: CG:1, BFGS:2, Newton-CG:3, L-BFGS-B:4
Answers: 2
Computers and Technology, 22.06.2019 03:10, victoriadorvilu
This program reads a file called 'test. txt'. you are required to write two functions that build a wordlist out of all of the words found in the file and print all of the unique words found in the file. remove punctuations using 'string. punctuation' and 'strip()' before adding words to the wordlist. write a function build_wordlist() that takes a 'file pointer' as an argument and reads the contents, builds the wordlist after removing punctuations, and then returns the wordlist. another function find_unique() will take this wordlist as a parameter and return another wordlist comprising of all unique words found in the wordlist. example: contents of 'test. txt': test file another line in the test file output: ['another', 'file', 'in', 'line', 'test', 'the']
Answers: 1
I have a problem with a task using scipy. optimize. minimize execution through the following methods...
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