plot#

Hist2d.plot(ax=None, fname=None, xlabel='__auto__', ylabel='__auto__', zlabel='__auto__', title='__auto__', logscale=False, xlim=None, ylim=None, colorbar_kwargs={}, savefig_kwargs={}, use_fixed_layout=None, fixed_layout_kwargs=None, make_me_nice=None, make_me_nice_kwargs=None, **pcolormesh_kwargs)[source]#

Plot the 2D histogram using matplotlib.pyplot.pcolormesh.

Parameters:

fnamestr, optional

If provided, the plot will be saved to this file.

xlabelstr, default “__auto__”

Label for the x-axis.

If “__auto__”, use Hist2d.xlabel.

ylabelstr, default “__auto__”

Label for the y-axis.

If “__auto__”, use Hist2d.ylabel.

zlabelstr, default “__auto__”

Label for the colorbar (z-axis).

If “__auto__”, use Hist2d.zlabel.

titlestr, default “__auto__”

Title of the plot.

If “__auto__”, use Hist2d.title.

logscalebool, optional

If True, use a logarithmic color scale.

xlimtuple[float, float], optional

Limits for the x-axis.

ylimtuple[float, float], optional

Limits for the y-axis.

colorbar_kwargs: dict, optional

Additional keyword arguments passed to add_colorbar().

savefig_kwargsdict, optional

Additional keyword arguments passed to savefig().

Returns:

tuple of Figure, Axes, Colorbar: A tuple containing the matplotlib Figure, Axes, and Colorbar objects.

Other Parameters:

pcolormesh_kwargsdict, optional: Additional keyword arguments passed to pcolormesh.
use_fixed_layout: Deprecated since version 5.5.0: Does nothing.
fixed_layout_kwargs: Deprecated since version 5.5.0: Does nothing.
make_me_nice: Deprecated since version 5.5.0: Does nothing.
make_me_nice_kwargs: Deprecated since version 5.5.0: Does nothing.

Examples

import matplotlib.pyplot as plt
import numpy as np

import atompy as ap

plt.style.use("atom")

rng = np.random.default_rng(42)
lim = (-2, 2)
size = 1_000

hist = ap.Hist2d(
    *np.histogram2d(*rng.normal(size=(2, size)), range=(lim, lim)),
    title="A 2D Histogram",
    xlabel="X Label",
    ylabel="Y Label",
    zlabel="Intensity",
)

fig, ax, cb = hist.plot()

plt.show()

(Source code, png, hires.png, pdf)

import matplotlib.pyplot as plt
import numpy as np

import atompy as ap

plt.style.use("atom")

rng = np.random.default_rng(42)
lim = (-2, 2)
size = 1_000

hist = ap.Hist2d(
    *np.histogram2d(*rng.normal(size=(2, size)), range=(lim, lim)),
    xlabel="X Label",
    ylabel="Y Label",
    zlabel="Intensity",
)

fig, axs = plt.subplots(ncols=2, layout="compressed", figsize=(6.0, 3.0))

cmaps = "viridis", "cividis"

for ax, cmap in zip(axs, cmaps):
    ax.set_box_aspect(1)
    hist.plot(ax=ax, title=cmap, cmap=cmap)

(Source code, png, hires.png, pdf)