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Add doctests for trapezoidal_rule.py #11491

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Describe your change:

Contributes to #9943

  • Add an algorithm?
  • Fix a bug or typo in an existing algorithm?
  • Add or change doctests? -- Note: Please avoid changing both code and tests in a single pull request.
  • Documentation change?

Checklist:

  • I have read CONTRIBUTING.md.
  • This pull request is all my own work -- I have not plagiarized.
  • I know that pull requests will not be merged if they fail the automated tests.
  • This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
  • All new Python files are placed inside an existing directory.
  • All filenames are in all lowercase characters with no spaces or dashes.
  • All functions and variable names follow Python naming conventions.
  • All function parameters and return values are annotated with Python type hints.
  • All functions have doctests that pass the automated testing.
  • All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
  • If this pull request resolves one or more open issues then the description above includes the issue number(s) with a closing keyword: "Fixes #ISSUE-NUMBER".

@algorithms-keeper algorithms-keeper bot added the awaiting reviews This PR is ready to be reviewed label Jul 17, 2024
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@tianyizheng02 tianyizheng02 left a comment

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Thanks for your improvements! I left a few comments on some minor issues left over from the original code.

while x < (b - h):
yield x
x = x + h
def make_points(a: float, b: float, h: float) -> Iterator[float]:
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Could we rename these variables for clarity? Rather than single-letter variable names, we could have something like lower_bound, upper_bound, and step_size.

Comment on lines 52 to 54
h = (boundary[1] - boundary[0]) / steps
a = boundary[0]
b = boundary[1]
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Same as my other comment: let's rename these variables to be more descriptive.

Comment on lines 56 to 60
y = 0.0
y += (h / 2.0) * f(a)
for i in x_i:
# print(i)
y += h * f(i)
y += (h / 2.0) * f(b)
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Minor nitpick: we can change 0.0 and 2.0 to just 0 and 2. Python will appropriately cast values to float anyway, so I don't see a need to specify the decimal points.

@tianyizheng02 tianyizheng02 added awaiting changes A maintainer has requested changes to this PR and removed awaiting reviews This PR is ready to be reviewed labels Aug 6, 2024
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3 participants