# ds1000 / 781 - taskset: [ds1000](https://harnessreport.com/tasks/ds1000.md) - difficulty: - category: - language: - runnable from the site: no - agent timeout: 1800s ## Results by harness _none yet_ ## Instruction ``` # 781: DS-1000 Task ## Prompt Problem: I'm searching for examples of using scipy.optimize.line_search. I do not really understand how this function works with multivariable functions. I wrote a simple example import scipy as sp import scipy.optimize def test_func(x): return (x[0])**2+(x[1])**2 def test_grad(x): return [2*x[0],2*x[1]] sp.optimize.line_search(test_func,test_grad,[1.8,1.7],[-1.0,-1.0]) And I've got File "D:\Anaconda2\lib\site-packages\scipy\optimize\linesearch.py", line 259, in phi return f(xk + alpha * pk, *args) TypeError: can't multiply sequence by non-int of type 'float' The result should be the alpha value of line_search A: <code> import scipy import scipy.optimize import numpy as np def test_func(x): return (x[0])**2+(x[1])**2 def test_grad(x): return [2*x[0],2*x[1]] starting_point = [1.8, 1.7] direction = [-1, -1] </code> result = ... # put solution in this variable BEGIN SOLUTION <code> ## What to do - Edit `solution/solution.py` so the code passes the DS-1000 tests. - Do not access the internet or install new packages; required libraries are preinstalled in the Docker image. - Run tests locally via `bash tests/test.sh`. ## Notes - Keep the variable names/signatures implied by the prompt/code_context. - The evaluator uses the original DS-1000 `code_context` (`test_execution` / `test_string`). ``` --- Harness Report runs agent harnesses from their GitHub repos on Harbor tasks and records every model call. Every page is also `.md` and `.json`; index: https://harnessreport.com/llms.txt · MCP: https://harnessreport.com/mcp