mb/data-accurate-pl-sex-chart
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improve formatting

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JOLIMAITRE Matthieu 2024-06-29 23:20:50 +02:00
parent 78dc4b8763
commit c64d06b205
1 changed files with 17 additions and 9 deletions
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26
src/main.py
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@ -1,6 +1,6 @@
#!/bin/env -S python
from matplotlib import pyplot
from matplotlib import pyplot, patheffects
from matplotlib.axes import Axes
from adjustText import adjust_text
@ -8,20 +8,19 @@ from adjustText import adjust_text
from data import (pay, release)
def center(data: list[tuple[str, list[float]]], padding: float = 0):
def center(data: list[tuple[str, list[float]]]):
for axis_index in range(len(data[0][1])):
min_ = min(data, key=lambda e: e[1][axis_index])[1][axis_index]
max_ = max(data, key=lambda e: e[1][axis_index])[1][axis_index]
delta = max_ - min_
desired_bias = (1 - padding)
desired_delta = 2 * desired_bias
for (_, values) in data:
original = values[axis_index]
value = (original - min_) / delta
value = (value * desired_delta) - desired_bias
value = (value * 2) - 1
values[axis_index] = value
# from some image, online
to_rank = {
'c#',
'assembly',
@ -76,7 +75,7 @@ ranked = list[tuple[str, list[float]]](
for label in to_rank
if label in pay and label in release
)
center(ranked, 0.1)
center(ranked)
print("\nunused", [l for l in pay.keys() if not l in map(lambda e: e[0], ranked)])
@ -87,10 +86,19 @@ print("\nranked", ranked)
(figure, axes) = pyplot.subplots()
assert type(axes) is Axes
axes.plot([-1, 1], [0, 0])
axes.plot([0, 0], [-1, 1])
texts = [axes.text(p, r, l) for (l, [r, p]) in ranked]
axes.axhline(y=0, color='k')
axes.axvline(x=0, color='k')
axes.set_xlim(-1, 1)
axes.set_ylim(-1, 1)
axes.axis("off")
drop_white = patheffects.withStroke(linewidth=3,foreground="white")
texts = [axes.text(p, r, l, path_effects=[drop_white]) for (l, [r, p]) in ranked]
adjust_text(texts, only_move={'points':'y', 'texts':'y'})
axes.text(1.1, 0, 'connait\nle sexe', path_effects=[drop_white])
axes.text(-1.3, 0, 'ne connait\npas le sexe', path_effects=[drop_white])
axes.text(0, 1.1, 'a le\nsexe', path_effects=[drop_white])
axes.text(0, -1.2, 'n\'a pas\nle sexe', path_effects=[drop_white])
pyplot.show()