A clean, expressive wrapper around Matplotlib, Plotly, plotext, and tikzfigure for producing publication-quality figures with minimal boilerplate. Swap backends without rewriting your data — render the same canvas as a crisp PNG, an interactive Plotly chart, a terminal-native plotext figure, or camera-ready TikZ code for LaTeX.
pip install maxplotlibximport numpy as np
from maxplotlib import Canvas
x = np.linspace(0, 2 * np.pi, 200)
y = np.sin(x)
canvas, ax = Canvas.subplots()
ax.plot(x, y)Figure 1
Plot the figure with the default (matplotlib) backend:
canvas.show()
Use canvas.plot(x, y) to add data directly to a canvas. When you want
to explicitly render an already-built canvas, use canvas.render(...).
The older canvas.plot(backend=...) spelling is still supported for
compatibility, but emits a FutureWarning.
Add several lines at once with shared styling:
canvas.plot_many(
[(x, np.sin(x)), (x, np.cos(x))],
labels=["sin(x)", "cos(x)"],
linewidth=2,
)Common figure and axis settings can be grouped with configure():
canvas.configure(
title="Trigonometry",
xlabel="Angle",
ylabel="Value",
grid=True,
facecolor="whitesmoke",
)For Matplotlib-specific customization, pass method calls declaratively. Figure methods run once and axes methods run for every subplot, providing access to any Matplotlib API without requiring a maxplotlib wrapper:
canvas.plot(matplotlib_customizations={
"figure": {
"suptitle": "My figure",
},
"axes": {
"tick_params": {
"axis": "both",
"which": "major",
"length": 6,
},
},
})For dynamic customization, the same option also accepts a function:
def customize(fig, axes):
fig.suptitle("My figure")
for ax in axes.flat:
ax.tick_params(axis="both", which="major", length=6)
canvas.plot(matplotlib_customizations=customize)Axis labels, titles, and tick appearance accept Matplotlib-style keyword arguments:
canvas.set_xlabel("Time", fontsize=12, fontweight="bold", labelpad=10)
canvas.set_ylabel("Duration", color="darkblue")
canvas.set_title("Runtime", fontsize=14, color="navy")
canvas.tick_params(
axis="both",
which="major",
labelsize=10,
colors="darkgreen",
length=6,
)Common axis controls and figure-level layout settings are also available:
canvas.set_facecolor("whitesmoke")
canvas.set_axisbelow(True)
canvas.margins(x=0.05, y=0.1)
canvas.minorticks_on()
canvas.invert_yaxis()
canvas.supxlabel("Shared x label")
canvas.supylabel("Shared y label")
canvas.subplots_adjust(left=0.15, bottom=0.15)
canvas.tight_layout()Use Canvas.twinx() to add a second y-axis that shares the primary
x-axis:
twin_canvas, primary = Canvas.subplots()
secondary = twin_canvas.twinx()
primary.plot(x, np.sin(x), color="tab:blue")
secondary.plot(x, 100 * np.cos(x), color="tab:red")
primary.set_ylabel("sin(x)", color="tab:blue")
secondary.set_ylabel("100 cos(x)", color="tab:red")
twin_canvas.show()Secondary y-axes are currently supported by the Matplotlib and Plotly backends.
Several Matplotlib field and annotation APIs map directly to interactive Plotly traces, including pseudocolor plots, sparsity patterns, triangular grids, and tables:
plotly_canvas, plotly_ax = Canvas.subplots()
plotly_ax.pcolor(x, x, np.outer(np.sin(x), np.cos(x)))
plotly_ax.spy([[1, 0, 1], [0, 1, 0], [1, 0, 1]])
plotly_ax.table(cellText=[["A", "B"], ["1", "2"]])
plotly_canvas.show(backend="plotly")Plotly raises NotImplementedError for primitives without a faithful
equivalent instead of silently dropping them. To render the supported
parts of a mixed canvas, explicitly opt into skipping unsupported
primitives:
plotly_canvas.render(backend="plotly", allow_unsupported=True)Render the same line graph directly in the terminal with the plotext
backend:
terminal_fig = canvas.render(backend="plotext")
print(terminal_fig.build(keep_colors=False))Trigonometry
Runtime
┌┬─────────────────┬─────────────────┬─────────────────┬─────────────────┬┐
1.00┼ ▞▞ sin(x) ──▗▄▞▀▀▀▀▀▙▄▖────────────┼─────────────────┼─────────────▄▄▀▀▀┤
│ ▞▞ cos(x) ▄▀▘ │ ▝▀▄ │ │ ▄▞▀ ││
││ ▜▄▘ │ ▀▄ │ │ ▄▛ ││
0.67┼┼──────▟▀─▀▄──────┼─────────▀▄──────┼─────────────────┼──────▄▀─────────┼┤
││ ▄▛ ▝▚▖ │ ▚▖ │ │ ▗▞▘ ││
0.33┼┼──▗▞────────▀▖───┼────────────▝▄───┼─────────────────┼───▗▀────────────┼┤
││ ▄▀ ▝▚ │ ▚▖ │ │ ▞▘ ││
│▗▞▘ ▀▖│ ▀▄│ │▗▀ ││
0.00┼▞────────────────▝▙────────────────▝▚▖────────────────▟▘────────────────▄┤
││ │▜▖ │▀▄ ▗▛│ ▗▞▘│
││ │ ▝▙ │ ▝▚ ▟▘ │ ▄▀ ││
-0.33┼┼─────────────────┼───▚▖────────────┼───▀▖───────▗▞───┼─────────────▞▘──┼┤
││ │ ▝▄▖ │ ▝▚ ▗▄▘ │ ▟▀ ││
-0.67┼┼─────────────────┼──────▀▖─────────┼──────▀▄─▗▀──────┼─────────▄▛──────┼┤
││ │ ▝▜▄ │ ▄▛▘ │ ▗▞▘ ││
││ │ ▀▄▖ │ ▗▄▀ ▀▄▖ │ ▗▄▀▘ ││
-1.00┼┼─────────────────┼────────────▝▀▚▄▄▄▄▄▞▀▘───────▝▀▜▄▄▄▄▄▞▀▘────────────┼┤
└┼─────────────────┼─────────────────┼─────────────────┼─────────────────┼┘
0.0 1.6 3.1 4.7 6.3
Duration Time
Or plot with the TikZ backend:
canvas.show(backend="tikzfigure")
The tikzfigure backend supports creating side-by-side subplots (1×n layouts):
x = np.linspace(0, 2 * np.pi, 200)
canvas, (ax1, ax2) = Canvas.subplots(ncols=2, width="10cm", ratio=0.3)
ax1.plot(x, np.sin(x), color="royalblue")
ax1.set_title("sin(x)")
ax2.plot(x, np.cos(x), color="tomato")
ax2.set_title("cos(x)")
canvas.suptitle("Trigonometric Functions")
canvas.show(backend="tikzfigure") # Generates LaTeX subfigures
Figure 2
Note: Only horizontal layouts (1×n) are currently supported with the
tikzfigure backend. Vertical/grid layouts will raise
NotImplementedError. See the tutorials for more examples.
The plotext backend is designed for terminal-first workflows. It
currently supports line plots, scatter plots, bars, filled regions,
error bars, reference lines, text/annotations, labels/titles, log axes,
layers, matrix-style imshow() rendering, common patches, and
multi-subplot canvases.
x = np.linspace(1, 10, 40)
canvas, ax = Canvas.subplots()
ax.plot(x, np.sqrt(x), color="cyan", label="sqrt(x)")
ax.errorbar(x[::8], np.sqrt(x[::8]), yerr=0.15, color="yellow", label="samples")
ax.set_title("Terminal plot")
ax.set_xlabel("x")
ax.set_ylabel("y")
ax.set_xscale("log")
ax.set_legend(True)
canvas.show(backend="plotext") Terminal plot
┌──────────────────────────────────────────────────────────────────────────┐
3.16┤ ▞▞ sqrt(x) ▄▞│
│ │▗▄▞▀ │
│ ▄┼▘ │
2.79┤ ▄▀▀ │
│ ┼▀▀ │
2.42┤ ▗▞▀▀│ │
│ ▗▞▀▀▘ │
│ ▗▄┼▄▀▘ │
2.04┤ ▗▄▀▘ │ │
│ ▗▄▞▀▘ │
│ │ ▄▄▀▀▘ │
1.67┤ ▗▄▄┼▀▀ │
│ ▗▄▄▞▀▀▘ │
1.30┤ ▄▄▄▄▀▀▀▘ │
│ ▄▄▞▀▀ │
│┼ ▗▄▄▞▀▀▀▀▀ │
0.93┤│▀▀▘ │
└┬─────────────────┬──────────────────┬─────────────────┬─────────────────┬┘
1.0 1.8 3.2 5.6 10.0
y x
<maxplotlib.backends.plotext.figure.PlotextFigure at 0x1102a0690>
x = np.linspace(0, 2 * np.pi, 200)
canvas, ax = Canvas.subplots(width="10cm", ratio=0.55)
ax.plot(x, np.sin(x), color="steelblue", label=r"$\sin(x)$", layer=0)
ax.plot(x, np.cos(x), color="tomato", label=r"$\cos(x)$", layer=1)
ax.plot(
x,
np.sin(x) * np.cos(x),
color="seagreen",
label=r"$\sin(x)\cos(x)$",
linestyle="dashed",
layer=2,
)
ax.set_xlabel("x")
ax.set_legend(True)Figure 3
Show layer 0 only, then layers 0 and 1, then everything:
canvas.show(layers=[0])
(<Figure size 590.551x324.803 with 1 Axes>,
array([[<Axes: xlabel='x'>]], dtype=object))
Show all layers:
canvas.show()
(<Figure size 590.551x324.803 with 1 Axes>,
array([[<Axes: xlabel='x'>]], dtype=object))