Add kde support for hist

ultraplot/axes/plot.py

@@ -7114,6 +7114,8 @@ def _apply_hist(
  filled=None,
  histtype=None,
  orientation="vertical",
+ kde=False,
+ kde_kw=None,
  **kwargs,
  ):
  """
@@ -7157,6 +7159,24 @@ def _apply_hist(
  if type(sub) is list:
  res[i] = cbook.silent_list("Polygon", sub)
  self._update_guide(res, **guide_kw)
+ # add kde line
+ if not kde:
+ return obj
+ from scipy.stats import gaussian_kde
+ edges = obj[1]
+ kde_kw = dict(kde_kw or {})
+ density = kw.get('density', False)
+ data2d = xs if xs.ndim > 1 else xs[:, None] # (M, N) data
+ stepsize = kde_kw.pop('stepsize', 300)
+ for i in range(data2d.shape[1]):
+ _x = data2d[:, i]
+ xa = np.linspace(_x.min(), _x.max(), stepsize)
+ ya = gaussian_kde(_x)(xa)
+ if not density:
+ idx = np.clip(np.digitize(xa, edges)-1, 0, len(edges)-2)
+ ya = ya * len(_x) * np.diff(edges)[idx]
+ x_line, y_line = (xa, ya) if orientation=="vertical" else (ya, xa)
+ self._call_native("plot", x_line, y_line, **kde_kw)
  return obj
 
  @inputs._preprocess_or_redirect("x", "bins", keywords="weights")

ultraplot/tests/test_1dplots.py

@@ -243,6 +243,42 @@ def test_histogram_types(rng):
  ax.hist(data, ec="k", **kw)
  return fig
 
+def test_hist_kde_lines(rng):
+ """
+ Test kde for hist.
+ """
+ data = rng.normal(size=200)
+ # No kde if no kde is not given
+ fig, ax = uplt.subplot()
+ ax.hist(data, bins=20)
+ assert len(ax.lines) == 0
+ # No kde if kde=False
+ ax.hist(data, bins=20, kde=False)
+ assert len(ax.lines) == 0
+ # One kde line with
+ ax.hist(data, bins=20, kde=True)
+ assert len(ax.lines) == 1
+ # test step size
+ line = ax.lines[-1]
+ # default stepsize is 300
+ assert line.get_xdata().size == 300
+ assert line.get_ydata().size == 300
+ assert line.get_xdata()[0] == pytest.approx(data.min())
+ assert line.get_xdata()[-1] == pytest.approx(data.max())
+ # use kde_kw to set stepsize=150
+ ax.hist(data, bins=20, kde=True, density=True, 
+ kde_kw={'stepsize': 150})
+ density_line = ax.lines[-1]
+ assert density_line.get_xdata().size == 150
+ assert density_line.get_ydata().size == 150
+ # test density, default is False, but to to test accurate? 
+ assert line.get_ydata().max() > 1.0
+ assert density_line.get_ydata().max() <= 1.0
+ # test area==1
+ area = np.trapezoid(density_line.get_ydata(), density_line.get_xdata())
+ assert area == pytest.approx(1.0, rel=1e-2)
+ uplt.close(fig)
+
 
 @pytest.mark.mpl_image_compare
 def test_invalid_plot(rng):