def polar_map(hist: Histogram2D,
ax: Axes,
*,
show_zero: bool = True,
show_colorbar: bool = True,
**kwargs):
"""Polar map of polar histograms.
Similar to map, but supports less parameters."""
data = get_data(hist,
cumulative=False,
flatten=True,
density=kwargs.pop("density", False))
cmap = _get_cmap(kwargs)
norm, cmap_data = _get_cmap_data(data, kwargs)
colors = cmap(cmap_data)
rpos, phipos = (arr.flatten() for arr in hist.get_bin_left_edges())
dr, dphi = (arr.flatten() for arr in hist.get_bin_widths())
rmax, _ = (arr.flatten() for arr in hist.get_bin_right_edges())
bar_args = {}
if "zorder" in kwargs:
bar_args["zorder"] = kwargs.pop("zorder")
alphas = _get_alpha_data(cmap_data, kwargs)
if np.isscalar(alphas):
alphas = np.ones_like(data) * alphas
for i in range(len(rpos)):
if data[i] > 0 or show_zero:
bin_color = colors[i]
# TODO: align = "edge"
bars = ax.bar(phipos[i],
dr[i],
width=dphi[i],
bottom=rpos[i],
align='edge',
color=bin_color,
edgecolor=kwargs.get("grid_color", cmap(0.5)),
lw=kwargs.get("lw", 0.5),
alpha=alphas[i],
**bar_args)
ax.set_rmax(rmax.max())
if show_colorbar:
_add_colorbar(ax, cmap, cmap_data, norm)
def bar3d(h2: Histogram2D, ax: Axes3D, **kwargs):
"""Plot of 2D histograms as 3D boxes."""
density = kwargs.pop("density", False)
data = get_data(h2, cumulative=False, flatten=True, density=density)
if "cmap" in kwargs:
cmap = _get_cmap(kwargs)
_, cmap_data = _get_cmap_data(data, kwargs)
colors = cmap(cmap_data)
else:
colors = kwargs.pop("color", kwargs.pop("c", "blue"))
xpos, ypos = (arr.flatten() for arr in h2.get_bin_centers())
zpos = np.zeros_like(ypos)
dx, dy = (arr.flatten() for arr in h2.get_bin_widths())
_add_labels(ax, h2, kwargs)
ax.bar3d(xpos, ypos, zpos, dx, dy, data, color=colors, **kwargs)
ax.set_zlabel("density" if density else "frequency")
def map(h2: Histogram2D,
ax: Axes,
*,
show_zero: bool = True,
show_values: bool = False,
show_colorbar: bool = True,
x=None,
y=None,
**kwargs):
"""Coloured-rectangle plot of 2D histogram.
Parameters
----------
show_zero : Whether to show coloured box for bins with 0 frequency (otherwise background).
show_values : Whether to show labels with frequencies/densities in the middle of the bin
text_color : Optional
Colour of text descriptions
text_alpha : Optional[float]
Alpha for the text labels only
x : Optional[Callable]
Transformation of x bin coordinates
y : Optional[Callable]
Transformation of y bin coordinates
zorder : float
z-order in the axis (higher number above lower)
See Also
--------
image, polar_map, surface_map
Notes
-----
If you transform axes using x or y parameters, the deduction of axis limits
does not work well automatically. Please, make sure to attend to it yourself.
The densities in transformed maps are calculated from original bins.
"""
# Detect transformation
transformed = False
if x is not None or y is not None:
if not x:
x = lambda x, y: x
if not y:
y = lambda x, y: y
transformed = True
value_format = kwargs.pop("value_format", lambda x: str(x))
# TODO: Implement correctly the text_kwargs
if isinstance(value_format, str):
format_str = "{0:" + value_format + "}"
value_format = lambda x: format_str.format(x)
rect_args = {}
if "zorder" in kwargs:
rect_args["zorder"] = kwargs.pop("zorder")
data = get_data(h2,
cumulative=False,
flatten=True,
density=kwargs.pop("density", False))
cmap = _get_cmap(kwargs)
norm, cmap_data = _get_cmap_data(data, kwargs)
colors = cmap(cmap_data)
xpos, ypos = (arr.flatten() for arr in h2.get_bin_left_edges())
dx, dy = (arr.flatten() for arr in h2.get_bin_widths())
text_x, text_y = (arr.flatten() for arr in h2.get_bin_centers())
_apply_xy_lims(ax, h2, data=data, kwargs=kwargs)
_add_labels(ax, h2, kwargs)
ax.autoscale_view()
alphas = _get_alpha_data(cmap_data, kwargs)
if np.isscalar(alphas):
alphas = np.ones_like(data) * alphas
for i in range(len(xpos)):
bin_color = colors[i]
alpha = alphas[i]
if data[i] != 0 or show_zero:
if not transformed:
rect = plt.Rectangle([xpos[i], ypos[i]],
dx[i],
dy[i],
facecolor=bin_color,
edgecolor=kwargs.get(
"grid_color", cmap(0.5)),
lw=kwargs.get("lw", 0.5),
alpha=alpha,
**rect_args)
tx, ty = text_x[i], text_y[i]
else:
# See http://matplotlib.org/users/path_tutorial.html
points = ((xpos[i], ypos[i]), (xpos[i] + dx[i], ypos[i]),
(xpos[i] + dx[i], ypos[i] + dy[i]),
(xpos[i], ypos[i] + dy[i]), (xpos[i], ypos[i]))
verts = [(x(*p), y(*p)) for p in points]
codes = [
path.Path.MOVETO,
path.Path.LINETO,
path.Path.LINETO,
path.Path.LINETO,
path.Path.CLOSEPOLY,
]
rect_path = path.Path(verts, codes)
rect = patches.PathPatch(rect_path,
facecolor=bin_color,
edgecolor=kwargs.get(
"grid_color", cmap(0.5)),
lw=kwargs.get("lw", 0.5),
alpha=alpha,
**rect_args)
tx = x(text_x[i], text_y[i])
ty = y(text_x[i], text_y[i])
ax.add_patch(rect)
if show_values:
text = value_format(data[i])
yiq_y = np.dot(bin_color[:3], [0.299, 0.587, 0.114])
text_color = kwargs.get("text_color", None)
if not text_color:
if yiq_y > 0.5:
text_color = (0.0, 0.0, 0.0,
kwargs.get("text_alpha", alpha))
else:
text_color = (1.0, 1.0, 1.0,
kwargs.get("text_alpha", alpha))
ax.text(tx,
ty,
text,
horizontalalignment='center',
verticalalignment='center',
color=text_color,
clip_on=True,
**rect_args)
if show_colorbar:
_add_colorbar(ax, cmap, cmap_data, norm)