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axis_scale='unit' centres on the mean, so skewed data sit off-centre

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#287 0 comentarios 0 reacciones 0 asignados Ver en GitHub

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Evaluación

Dificultad
4/5
Tiempo estimado
3-5 días
Aptitud para principiantes
22/100
Tipo de issue
Error
Claridad
Bastante claro
Estado de actividad
Activo
Stack tecnológico
matplotlib, plotly, python
Área
data-visualization

Línea de trabajo

The centring logic for axis_scale='unit' is the starting point, and the issue traces it to the mean rather than the midrange. Run tests/test_gh141_marker_line_smoothing.py and tests/test_plot_audit_b1.py::TestStaticLineDataFidelity first, since these five tests encode the current placement and will fail under the change. The issue defers this to 1.2 and it touches every 2-D and 3-D figure, so confirm scope with maintainers before editing.

Escrito por el modelo de indexación a partir del texto del issue.

Descripción

enhancement

With the default axis_scale='unit', each axis is centred on the data's mean, not its midrange. Skewed data therefore sit off-centre in the plot box.

Measured during the 1.1 release review (candidate c433b8f0):

  • hyp.plot(...) 2-D on a random-walk fixture (feature tour PLOT-basic-*): the trajectory fills the top two-thirds of the box and the bottom third is empty. Matplotlib and plotly behave the same.
  • weights_sample: every axis mean maps to about +0.13. Per axis, 72–76% of points sit above the centre, and 41% fall in the upper octant.
  • A lognormal array: means map to about −0.85, and 0.7% of points per axis sit above the centre. The data fill the lower corner.

Centring each axis on its midrange (min + max) / 2 would fill the box. It changes how every 2-D and 3-D figure looks. On a patched copy, 5 tests that encode the current placement fail: 3 in tests/test_gh141_marker_line_smoothing.py and 2 in tests/test_plot_audit_b1.py::TestStaticLineDataFidelity. Every gallery image, tutorial output and screenshot would need regenerating, so this is deferred from 1.1 to 1.2.

Lenguaje dominante
Python
Estrellas
1.9k
Forks
164
Merge medio
2 h 46 min
PR fusionados (30 d)
2

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