# ds1000 / 426

- 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

```
# 426: DS-1000 Task

## Prompt
Problem:
I have integers and I would like to convert them to binary numpy arrays of length m. For example, say m = 4. Now 15 = 1111 in binary and so the output should be (1,1,1,1).  2 = 10 in binary and so the output should be (0,0,1,0). If m were 3 then 2 should be converted to (0,1,0).
I tried np.unpackbits(np.uint8(num)) but that doesn't give an array of the right length. For example,
np.unpackbits(np.uint8(15))
Out[5]: array([0, 0, 0, 0, 1, 1, 1, 1], dtype=uint8)
Pay attention that the integers might overflow, and they might be negative. For m = 4:
63 = 0b00111111, output should be (1,1,1,1)
-2 = 0b11111110, output should be (1,1,1,0)
I would like a method that worked for whatever m I have in the code. Given an n-element integer array, I want to process it as above to generate a (n, m) matrix.
A:
<code>
import numpy as np
a = np.array([1, 2, 3, 4, 5])
m = 6
</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