Marker Size Control

Control the size of plot markers either uniformly across all points or individually based on your data. This is useful for creating bubble charts where marker size represents a third dimension of data.

Static Marker Sizes

Set a uniform marker size for all points in a plot using the mark_size parameter on AddPlot:

from texer import PGFPlot, Axis, AddPlot, Coordinates, evaluate

plot = PGFPlot(
    Axis(
        xlabel="X",
        ylabel="Y",
        title="Static Marker Size (5pt)",
        grid=True,
        plots=[
            AddPlot(
                color="blue",
                mark="*",
                mark_size=5,  # All markers will be 5pt
                only_marks=True,
                coords=Coordinates(x=[1, 2, 3, 4, 5], y=[2, 4, 3, 5, 4]),
            )
        ],
    )
)

print(evaluate(plot, {}))

Output:

The mark_size parameter accepts:

• Numeric values (automatically converted to pt units): mark_size=5 becomes 5pt
• String values with units: mark_size="3mm" or mark_size="0.5cm"

---

Multiple Series with Different Sizes

Create plots with multiple series, each having different marker sizes:

from texer import PGFPlot, Axis, AddPlot, Coordinates, evaluate

plot = PGFPlot(
    Axis(
        xlabel="X",
        ylabel="Y",
        title="Multiple Series with Different Sizes",
        legend_pos="north west",
        grid=True,
        plots=[
            AddPlot(
                color="blue",
                mark="*",
                mark_size=3,
                only_marks=True,
                coords=Coordinates(x=[1, 2, 3, 4, 5], y=[2, 4, 3, 5, 4]),
            ),
            AddPlot(
                color="red",
                mark="square*",
                mark_size=6,
                only_marks=True,
                coords=Coordinates(x=[1, 2, 3, 4, 5], y=[3, 2, 4, 3, 5]),
            ),
            AddPlot(
                color="green!70!black",
                mark="triangle*",
                mark_size=9,
                only_marks=True,
                coords=Coordinates(x=[1, 2, 3, 4, 5], y=[4, 5, 2, 4, 3]),
            ),
        ],
        legend=["Small (3pt)", "Medium (6pt)", "Large (9pt)"],
    )
)

print(evaluate(plot, {}))

Output:

---

Data-Driven Marker Sizes (Bubble Charts)

For bubble charts, control each marker's size individually based on your data. This requires enabling scatter=True mode:

from texer import PGFPlot, Axis, AddPlot, Coordinates, evaluate

plot = PGFPlot(
    Axis(
        xlabel="X Position",
        ylabel="Y Position",
        title="Bubble Chart (Data-Driven Sizes)",
        grid=True,
        plots=[
            AddPlot(
                color="red",
                mark="*",
                only_marks=True,
                scatter=True,  # Enable scatter mode for per-point sizes
                coords=Coordinates(
                    x=[1, 2, 3, 4, 5],
                    y=[2, 4, 3, 5, 4],
                    marker_size=[5, 10, 15, 20, 25]  # Different size for each point
                ),
            )
        ],
    )
)

print(evaluate(plot, {}))

Output:

This generates coordinates with bracket notation for the marker size metadata:

\addplot[..., scatter, point meta=explicit,
  visualization depends on={\pgfplotspointmeta \as \perpointmarksize},
  scatter/@pre marker code/.append style={/tikz/mark size=\perpointmarksize}
] coordinates {(1, 2) [5] (2, 4) [10] (3, 3) [15] (4, 5) [20] (5, 4) [25]};

Requirements for Data-Driven Sizes

• You must set scatter=True on the AddPlot
• Provide marker_size as a list in Coordinates alongside x and y
• The marker_size list must have the same length as x and y

---

Quick Bubble Charts with scatter_plot()

Use the convenience function for creating bubble charts with minimal code:

from texer import scatter_plot, evaluate

plot = scatter_plot(
    x=[1, 2, 3, 4, 5],
    y=[2, 4, 3, 5, 4],
    marker_size=[5, 10, 15, 20, 25],
    xlabel="X Value",
    ylabel="Y Value",
    title="Easy Bubble Chart",
    color="green!70!black",
    mark="o"
)

print(evaluate(plot, {}))

Output:

The scatter_plot() helper automatically:

• Enables scatter mode
• Sets only_marks=True
• Configures the marker size visualization

---

Dynamic Marker Sizes from Data

Marker sizes can be data-driven using Ref and Iter:

from texer import PGFPlot, Axis, AddPlot, Coordinates, Ref, Iter, evaluate

plot = PGFPlot(
    Axis(
        xlabel="Time (s)",
        ylabel="Performance",
        title=Ref("plot_title"),
        grid=True,
        plots=[
            AddPlot(
                color="blue",
                mark="*",
                only_marks=True,
                scatter=True,
                coords=Coordinates(
                    Iter(
                        Ref("measurements"),
                        x=Ref("time"),
                        y=Ref("perf"),
                        marker_size=Ref("importance")
                    )
                ),
            )
        ],
    )
)

data = {
    "plot_title": "Performance Over Time (size = importance)",
    "measurements": [
        {"time": 0, "perf": 50, "importance": 5},
        {"time": 1, "perf": 60, "importance": 8},
        {"time": 2, "perf": 55, "importance": 12},
        {"time": 3, "perf": 70, "importance": 15},
        {"time": 4, "perf": 65, "importance": 20},
    ],
}

print(evaluate(plot, data))

Output:

This pattern is powerful for:

• Visualizing uncertainty or confidence intervals
• Showing importance/weight of data points
• Creating bubble charts from database queries
• Any scenario where a third variable should control point size

---

API Reference

AddPlot Parameters

Parameter	Type	Description
mark_size	float, int, or str	Static marker size for all points (e.g., 5 or "3mm")
scatter	bool	Enable scatter mode for data-driven marker sizes
scatter_src	str	Control how marker size data is interpreted (default: "explicit")

Coordinates Parameters

Parameter	Type	Description
marker_size	list or Ref	Individual marker size for each point (requires scatter=True on AddPlot)

Iter Parameters for Coordinates

When using Iter inside Coordinates, you can specify:

Parameter	Type	Description
x	Ref	Path to x values in each item
y	Ref	Path to y values in each item
z	Ref	Path to z values (for 3D plots)
marker_size	Ref	Path to marker size values in each item

---

Notes

• Static vs Data-Driven: mark_size on AddPlot sets a uniform size; marker_size in Coordinates allows per-point sizes
• Units: Marker sizes are specified in LaTeX pt units by default
• 3D Support: Data-driven marker sizes also work with 3D scatter plots
• Cannot Combine: Static mark_size and data-driven marker_size cannot be used together in the same plot