Generate figures for quick reference tables

This final section contains the code for figures used in the line properties table in the Matplotlib page.

import numpy as np
import matplotlib.pyplot as plt

# Machinery to store outputs for later use.
# This is for rendering in the Jupyter Book version of these pages.
from myst_nb import glue

Line property figures

This example demonstrates using alpha for transparency:

size = 256, 16
dpi = 72.0
figsize = size[0] / float(dpi), size[1] / float(dpi)
fig = plt.figure(figsize=figsize, dpi=dpi)
fig.patch.set_alpha(0)
plt.axes((0, 0.1, 1, 0.8), frameon=False)

for i in range(1, 11):
    plt.axvline(i, linewidth=1, color="blue", alpha=0.25 + 0.75 * i / 10.0)

plt.xlim(0, 11)
plt.xticks([])
plt.yticks([])

# Store figure for use in reference table.
glue("plot_alpha", fig, display=False)

This example demonstrates aliased versus anti-aliased text.

First, aliased text (antialiased=False):

size = 128, 16
dpi = 72.0
figsize = size[0] / float(dpi), size[1] / float(dpi)
fig = plt.figure(figsize=figsize, dpi=dpi)
fig.patch.set_alpha(0)

plt.axes((0, 0, 1, 1), frameon=False)

plt.rcParams["text.antialiased"] = False
plt.text(0.5, 0.5, "Aliased", ha="center", va="center")

plt.xlim(0, 1)
plt.ylim(0, 1)
plt.xticks([])
plt.yticks([])

# Reset rcParams back to defaults
plt.rcdefaults()

# Store figure for use in reference table.
glue("plot_aliased", fig, display=False)

Next, antialiased=True.

fig = plt.figure(figsize=figsize, dpi=dpi)
fig.patch.set_alpha(0)
plt.axes((0, 0, 1, 1), frameon=False)

plt.rcParams["text.antialiased"] = True
plt.text(0.5, 0.5, "Anti-aliased", ha="center", va="center")

plt.xlim(0, 1)
plt.ylim(0, 1)
plt.xticks([])
plt.yticks([])

# Reset rcParams back to defaults
plt.rcdefaults()

# Store figure for use in reference table.
glue("plot_antialiased", fig, display=False)

An example demoing the various colors taken by Matplotlib’s plot.

size = 256, 16
dpi = 72.0
figsize = size[0] / float(dpi), size[1] / float(dpi)
fig = plt.figure(figsize=figsize, dpi=dpi)
fig.patch.set_alpha(0)
plt.axes((0, 0.1, 1, 0.8), frameon=False)

for i in range(1, 11):
    plt.plot([i, i], [0, 1], lw=1.5)

plt.xlim(0, 11)
plt.xticks([])
plt.yticks([]);

# Store figure for use in reference table.
glue("plot_color", fig, display=False)

Plot various linewidths with Matplotlib.

size = 256, 16
dpi = 72.0
figsize = size[0] / float(dpi), size[1] / float(dpi)
fig = plt.figure(figsize=figsize, dpi=dpi)
fig.patch.set_alpha(0)
plt.axes((0, 0.1, 1, 0.8), frameon=False)

for i in range(1, 11):
    plt.plot([i, i], [0, 1], color="b", lw=i / 2.0)

plt.xlim(0, 11)
plt.ylim(0, 1)
plt.xticks([])
plt.yticks([]);

# Store figure for use in reference table.
glue("plot_linewidth", fig, display=False)

An example demoing the solid cap style in Matplotlib.

size = 256, 16
dpi = 72.0
figsize = size[0] / float(dpi), size[1] / float(dpi)
fig = plt.figure(figsize=figsize, dpi=dpi)
fig.patch.set_alpha(0)
plt.axes((0, 0, 1, 1), frameon=False)

plt.plot(np.arange(4), np.ones(4), color="blue", linewidth=8, solid_capstyle="butt")

plt.plot(
    5 + np.arange(4), np.ones(4), color="blue", linewidth=8, solid_capstyle="round"
)

plt.plot(
    10 + np.arange(4),
    np.ones(4),
    color="blue",
    linewidth=8,
    solid_capstyle="projecting",
)

plt.xlim(0, 14)
plt.xticks([])
plt.yticks([]);

# Store figure for use in reference table.
glue("plot_solid_capstyle", fig, display=False)

An example showing the different solid joint styles in Matplotlib.

size = 256, 16
dpi = 72.0
figsize = size[0] / float(dpi), size[1] / float(dpi)
fig = plt.figure(figsize=figsize, dpi=dpi)
fig.patch.set_alpha(0)
plt.axes((0, 0, 1, 1), frameon=False)

plt.plot(np.arange(3), [0, 1, 0], color="blue", linewidth=8, solid_joinstyle="miter")
plt.plot(
    4 + np.arange(3), [0, 1, 0], color="blue", linewidth=8, solid_joinstyle="bevel"
)
plt.plot(
    8 + np.arange(3), [0, 1, 0], color="blue", linewidth=8, solid_joinstyle="round"
)

plt.xlim(0, 12)
plt.ylim(-1, 2)
plt.xticks([])
plt.yticks([])

# Store figure for use in reference table.
glue("plot_solid_joinstyle", fig, display=False)

An example demoing the dash capstyle.

size = 256, 16
dpi = 72.0
figsize = size[0] / float(dpi), size[1] / float(dpi)
fig = plt.figure(figsize=figsize, dpi=dpi)
fig.patch.set_alpha(0)
plt.axes((0, 0, 1, 1), frameon=False)

plt.plot(
    np.arange(4),
    np.ones(4),
    color="blue",
    dashes=[15, 15],
    linewidth=8,
    dash_capstyle="butt",
)

plt.plot(
    5 + np.arange(4),
    np.ones(4),
    color="blue",
    dashes=[15, 15],
    linewidth=8,
    dash_capstyle="round",
)

plt.plot(
    10 + np.arange(4),
    np.ones(4),
    color="blue",
    dashes=[15, 15],
    linewidth=8,
    dash_capstyle="projecting",
)

plt.xlim(0, 14)
plt.xticks([])
plt.yticks([])

# Store figure for use in reference table.
glue("plot_dash_capstyle", fig, display=False)

Example demoing the dash join style.

size = 256, 16
dpi = 72.0
figsize = size[0] / float(dpi), size[1] / float(dpi)
fig = plt.figure(figsize=figsize, dpi=dpi)
fig.patch.set_alpha(0)
plt.axes((0, 0, 1, 1), frameon=False)

plt.plot(
    np.arange(3),
    [0, 1, 0],
    color="blue",
    dashes=[12, 5],
    linewidth=8,
    dash_joinstyle="miter",
)
plt.plot(
    4 + np.arange(3),
    [0, 1, 0],
    color="blue",
    dashes=[12, 5],
    linewidth=8,
    dash_joinstyle="bevel",
)
plt.plot(
    8 + np.arange(3),
    [0, 1, 0],
    color="blue",
    dashes=[12, 5],
    linewidth=8,
    dash_joinstyle="round",
)

plt.xlim(0, 12)
plt.ylim(-1, 2)
plt.xticks([])
plt.yticks([]);

# Store figure for use in reference table.
glue("plot_dash_joinstyle", fig, display=False)

Demo the marker edge widths of Matplotlib’s markers.

size = 256, 16
dpi = 72.0
figsize = size[0] / float(dpi), size[1] / float(dpi)
fig = plt.figure(figsize=figsize, dpi=dpi)
fig.patch.set_alpha(0)
plt.axes((0, 0, 1, 1), frameon=False)

for i in range(1, 11):
    plt.plot(
        [
            i,
        ],
        [
            1,
        ],
        "s",
        markersize=5,
        markeredgewidth=1 + i / 10.0,
        markeredgecolor="k",
        markerfacecolor="w",
    )
plt.xlim(0, 11)
plt.xticks([])
plt.yticks([])

# Store figure for use in reference table.
glue("plot_mew", fig, display=False)

Demo the marker edge color of Matplotlib’s markers.

size = 256, 16
dpi = 72.0
figsize = size[0] / float(dpi), size[1] / float(dpi)
fig = plt.figure(figsize=figsize, dpi=dpi)
fig.patch.set_alpha(0)
plt.axes((0, 0, 1, 1), frameon=False)

rng = np.random.default_rng()

for i in range(1, 11):
    r, g, b = np.random.uniform(0, 1, 3)
    plt.plot(
        [
            i,
        ],
        [
            1,
        ],
        "s",
        markersize=5,
        markerfacecolor="w",
        markeredgewidth=1.5,
        markeredgecolor=(r, g, b, 1),
    )

plt.xlim(0, 11)
plt.xticks([])
plt.yticks([])

# Store figure for use in reference table.
glue("plot_mec", fig, display=False)

Demo the marker face color of Matplotlib’s markers.

size = 256, 16
dpi = 72.0
figsize = size[0] / float(dpi), size[1] / float(dpi)
fig = plt.figure(figsize=figsize, dpi=dpi)
fig.patch.set_alpha(0)
plt.axes((0, 0, 1, 1), frameon=False)

rng = np.random.default_rng()

for i in range(1, 11):
    r, g, b = np.random.uniform(0, 1, 3)
    plt.plot(
        [
            i,
        ],
        [
            1,
        ],
        "s",
        markersize=8,
        markerfacecolor=(r, g, b, 1),
        markeredgewidth=0.1,
        markeredgecolor=(0, 0, 0, 0.5),
    )
plt.xlim(0, 11)
plt.xticks([])
plt.yticks([])

# Store figure for use in reference table.
glue("plot_mfc", fig, display=False)

Demo the marker size control in Matplotlib.

size = 256, 16
dpi = 72.0
figsize = size[0] / float(dpi), size[1] / float(dpi)
fig = plt.figure(figsize=figsize, dpi=dpi)
fig.patch.set_alpha(0)
plt.axes((0, 0, 1, 1), frameon=False)

for i in range(1, 11):
    plt.plot(
        [
            i,
        ],
        [
            1,
        ],
        "s",
        markersize=i,
        markerfacecolor="w",
        markeredgewidth=0.5,
        markeredgecolor="k",
    )

plt.xlim(0, 11)
plt.xticks([])
plt.yticks([])

# Store figure for use in reference table.
glue("plot_ms", fig, display=False)

Line styles figure

def linestyle(ls, i):
    X = i * 0.5 * np.ones(11)
    Y = np.arange(11)
    plt.plot(
        X,
        Y,
        ls,
        color=(0.0, 0.0, 1, 1),
        lw=3,
        ms=8,
        mfc=(0.75, 0.75, 1, 1),
        mec=(0, 0, 1, 1),
    )
    plt.text(0.5 * i, 10.25, ls, rotation=90, fontsize=15, va="bottom")

linestyles = [
    "-",
    "--",
    ":",
    "-.",
    ".",
    ",",
    "o",
    "^",
    "v",
    "<",
    ">",
    "s",
    "+",
    "x",
    "d",
    "1",
    "2",
    "3",
    "4",
    "h",
    "p",
    "|",
    "_",
    "D",
    "H",
]
n_lines = len(linestyles)

size = 20 * n_lines, 300
dpi = 72.0
figsize = size[0] / float(dpi), size[1] / float(dpi)
fig = plt.figure(figsize=figsize, dpi=dpi)
plt.axes((0, 0.01, 1, 0.9), frameon=False)

for i, ls in enumerate(linestyles):
    linestyle(ls, i)

plt.xlim(-0.2, 0.2 + 0.5 * n_lines)
plt.xticks([])
plt.yticks([])

# Store figure for use in reference sections.
glue("line_styles_fig", fig, display=False)

Marker style figure

def marker(m, i):
    X = i * 0.5 * np.ones(11)
    Y = np.arange(11)

    plt.plot(X, Y, lw=1, marker=m, ms=10, mfc=(0.75, 0.75, 1, 1), mec=(0, 0, 1, 1))
    plt.text(0.5 * i, 10.25, repr(m), rotation=90, fontsize=15, va="bottom")

markers = [
    0,
    1,
    2,
    3,
    4,
    5,
    6,
    7,
    "o",
    "h",
    "_",
    "1",
    "2",
    "3",
    "4",
    "8",
    "p",
    "^",
    "v",
    "<",
    ">",
    "|",
    "d",
    ",",
    "+",
    "s",
    "*",
    "|",
    "x",
    "D",
    "H",
    ".",
]

n_markers = len(markers)

size = 20 * n_markers, 300
dpi = 72.0
figsize = size[0] / float(dpi), size[1] / float(dpi)
fig = plt.figure(figsize=figsize, dpi=dpi)
plt.axes((0, 0.01, 1, 0.9), frameon=False)

for i, m in enumerate(markers):
    marker(m, i)

plt.xlim(-0.2, 0.2 + 0.5 * n_markers)
plt.xticks([])
plt.yticks([])

# Store figure for use in reference sections.
glue("marker_styles_fig", fig, display=False)

Colormap figure

plt.rc("text", usetex=False)
a = np.outer(np.arange(0, 1, 0.01), np.ones(10))

fig = plt.figure(figsize=(10, 5))
plt.subplots_adjust(top=0.8, bottom=0.05, left=0.01, right=0.99)
maps = [m for m in plt.colormaps if not m.endswith("_r")]
maps.sort()
l = len(maps) + 1

for i, m in enumerate(maps):
    plt.subplot(1, l, i + 1)
    plt.axis("off")
    plt.imshow(a, aspect="auto", cmap=plt.get_cmap(m), origin="lower")
    plt.title(m, rotation=90, fontsize=10, va="bottom")

# Restore Matplotlib defaults.
plt.rcdefaults()

# Store figure for use in reference sections.
glue("colormap_fig", fig, display=False)