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Coding workflows · Unweighted isotonic regression
03
A concrete starting point
Fit a nondecreasing sequence to at most 128 finite observations bounded by ±10^6 with equal least-squares weights. Test empty and descending inputs, rejecting Booleans and preserving the source list.
Define the change
Describe the input, expected output and boundaries that must stay intact.
Inspect the work
Review the proposed edits and any commands before relying on their result.
Check the outcome
Compare actual behavior with the expected result. If a check fails, investigate it before applying more changes.
Unweighted isotonic regression
A concrete starting point
from math import isfinite
def isotonic_fit(values):
if type(values) is not list or len(values) > 128:
raise ValueError("bounded list")
if any(type(x) not in (int, float) or abs(x) > 10**6 or
not isfinite(x) for x in values):
raise ValueError("bounded finite values")
blocks = []
for value in values:
blocks.append([float(value), 1])
while len(blocks) > 1 and (
blocks[-2][0] / blocks[-2][1] > blocks[-1][0] / blocks[-1][1]):
total, count = blocks.pop()
blocks[-1][0] += total; blocks[-1][1] += count
return [total / count for total, count in blocks for _ in range(count)]The example is a starting point for a real project, not a claim that generated code is already tested. Adjust paths, dependencies and expected behavior to match your application.