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Simplify parsing of errorbar input. #13124

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Merged
merged 1 commit into from
Jan 17, 2019
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anntzer
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@anntzer anntzer commented Jan 6, 2019

PR Summary

PR Checklist

  • Has Pytest style unit tests
  • Code is Flake 8 compliant
  • New features are documented, with examples if plot related
  • Documentation is sphinx and numpydoc compliant
  • Added an entry to doc/users/next_whats_new/ if major new feature (follow instructions in README.rst there)
  • Documented in doc/api/api_changes.rst if API changed in a backward-incompatible way

# special case for empty lists
if len(err) > 1:
fe = cbook.safe_first_element(err)
if len(err) != len(data) or np.size(fe) > 1:
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the check that len(err) == len(data) is taken care of by safezip, so can be dropped.

# for the (undocumented, but tested) support for (n, 1) arrays.
ash, bsh = map(np.shape, [a, b])
if (len(ash) > 2 and not (len(ash) == 2 and ash[1] == 1)
or len(bsh) > 2 and not (len(bsh) == 2 and bsh[1] == 1)):
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I think the expression is wrong. The first part is already False for len(ashape) == 2 so the rhs of the and is never evaluated in that case. Should be

if (len(ashape) > 2 or (len(ashape) == 2 and ashape[1] != 1)

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duh, indeed

or len(bsh) > 2 and not (len(bsh) == 2 and bsh[1] == 1)):
raise ValueError(
"err must be a scalar or a 1D or (2, n) array-like")
# Using list comprehensions rather than arrays to preserve units.
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Would it be worth it to special-case if v and e are arrays to speed up the calculation? Probably not.

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anntzer commented Jan 7, 2019

thanks, handled

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Seems fine, but blocking on a discussion w/ homogenizing with #12903, which is the same problem for bar.

raise ValueError(
"err must be a scalar or a 1D or (2, n) array-like")
# Using list comprehensions rather than arrays to preserve units.
low = [v - e for v, e in cbook.safezip(data, a)]
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What units has this been tested with? This is basically the same issue as bar in #12903 so we should make sure unit handling is the same. In particular if v is a datetime, and e a timedelta, I assume this works? What about for pint units? And are we sure this works w/ pandas? Not that I think #12903 checked all those boxes, but I think we should be thinking about how to uniformly handle this case and bar. ie. we now have _convert_dx, and maybe errorbar should use it as well.

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@anntzer anntzer Jan 16, 2019

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Do you want to first make a PR letting errorbar use _convert_dx? I can rebase this one onto yours after it's merged.

However it's not actually clear to me it's the "same" issue as #12903; in bar() you need to be able to support deunitized widths (because the default, 0.8, is deunitized...) whereas here we can just always assume that the error has the same unit (or a compatible one) as the value.

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I agree they are different and maybe using the same helper doesn't make sense. (I actually think defaulting width=0.8 in bar is ambiguous and a mistake, but...).

Tests with datetime-like obects would be helpful. Not sure categoricals need to be tested (when would the error be a +/- f? )

And we should decide if we should add pint to the tests.

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@anntzer anntzer Jan 17, 2019

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tbh I don't particularly care about adding tests for units for this PR specifically.

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actually I guess thats fair since you didn't change the algorithm...

raise ValueError(
"err must be a scalar or a 1D or (2, n) array-like")
# Using list comprehensions rather than arrays to preserve units.
low = [v - e for v, e in cbook.safezip(data, a)]
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actually I guess thats fair since you didn't change the algorithm...

@jklymak jklymak merged commit 7f4b044 into matplotlib:master Jan 17, 2019
@anntzer anntzer deleted the errorbar branch January 17, 2019 19:57
@QuLogic QuLogic added this to the v3.1 milestone Jan 18, 2019
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4 participants