Cleopatra

Cleopatra is a matplotlib utility package for visualizing 2D/3D numpy arrays, unstructured meshes, point clouds, vector fields, polygons, lines, and statistical distributions. It targets scientific and research users working with geospatial and raster data, providing a high-level API over matplotlib with sensible defaults and rich customization.

For the package's boundaries — what belongs here and what does not — see SCOPE.md.

Package Layout

graph TD
    subgraph core["Core"]
        glyph["<b>glyph</b><br/>Glyph — base class<br/>figure/axes · color norms · classification<br/>colorbars · ticks · point overlays · animation"]
    end

    subgraph visualizers["Visualizers — subclass Glyph"]
        array_glyph["<b>array_glyph</b><br/>ArrayGlyph · FacetGrid<br/>2D/3D rasters, facets, animation"]
        mesh_glyph["<b>mesh_glyph</b><br/>MeshGlyph<br/>unstructured meshes"]
        scatter_glyph["<b>scatter_glyph</b><br/>ScatterGlyph<br/>point clouds"]
        vector_glyph["<b>vector_glyph</b><br/>VectorGlyph<br/>vector fields"]
        flow_glyph["<b>flow_glyph</b><br/>FlowGlyph<br/>flow paths"]
        line_glyph["<b>line_glyph</b><br/>LineGlyph<br/>line / bar / band"]
        polygon_glyph["<b>polygon_glyph</b><br/>PolygonGlyph<br/>polygon collections"]
        kde_glyph["<b>kde_glyph</b><br/>KDEGlyph<br/>2D kernel density"]
    end

    subgraph standalone["Standalone"]
        statistical_glyph["<b>statistical_glyph</b><br/>StatisticalGlyph<br/>histogram · boxplot · multiboxplot · stripes"]
    end

    subgraph support["Supporting utilities"]
        styles["<b>styles</b><br/>Styles · Scale · ColorScale<br/>MidpointNormalize · classify · resolve_sizes · legends"]
        colors["<b>colors</b><br/>Colors<br/>hex/RGB conversion · colormaps"]
        animation["<b>animation</b><br/>save_animation · to_gif · embed_gif"]
        projection["<b>projection</b><br/>apply_projection_frame"]
        config["<b>config</b><br/>Config — matplotlib backend helper"]
    end

    subgraph optional["Optional — cleopatra[tiles]"]
        tiles["<b>tiles</b><br/>add_tiles · fetch / stitch helpers<br/>XYZ web-tile basemaps"]
    end

    array_glyph & mesh_glyph & scatter_glyph & vector_glyph & flow_glyph & line_glyph & polygon_glyph & kde_glyph ==>|extends| glyph
    glyph -->|color scales · classification| styles
    glyph -->|save / embed| animation
    array_glyph -.->|optional basemap| tiles

Loading

• glyph provides the shared Glyph base class (figure/axes lifecycle, colorbars, color norms, ticks, classification, animation).
• The user-facing visualizers all subclass Glyph and share its colour-mapping/colorbar pipeline — array_glyph (ArrayGlyph, FacetGrid), mesh_glyph (MeshGlyph), scatter_glyph (ScatterGlyph), vector_glyph (VectorGlyph), flow_glyph (FlowGlyph), line_glyph (LineGlyph), polygon_glyph (PolygonGlyph), and kde_glyph (KDEGlyph). statistical_glyph (StatisticalGlyph) stands alone.
• tiles adds the optional web-tile basemap helper (cleopatra.tiles.add_tiles), behind the cleopatra[tiles] extra.
• colors, styles, animation, projection, and config are supporting utilities (colour conversions; predefined styles, MidpointNormalize, ColorScale, value→size mapping, classify classification schemes and legend builders; glyph-independent animation save/embed helpers; static projected map frames; and the matplotlib-backend helper).

Main Features

ArrayGlyph -- Raster / Array Visualization

• Plot 2D numpy arrays with automatic colorbar and customizable color scales (linear, power, symmetric log-norm, boundary-norm, midpoint).
• Display cell values and overlay point markers on the plot.
• Animate 3D arrays over time and export to GIF, MP4, MOV, or AVI (via ffmpeg).

MeshGlyph -- Unstructured Mesh Visualization

• Visualize UGRID-style unstructured mesh data using triangulation (tripcolor, tricontourf).
• Render wireframe outlines via LineCollection.
• Accepts raw numpy arrays of node coordinates and face-node connectivity.
• Animate time-varying mesh data.

StatisticalGlyph -- Distribution Plots

• Create histograms for 1D and 2D datasets with customizable bins, colors, and transparency.
• Draw boxplots, multi-boxplots, and strip plots.

ScatterGlyph -- Point Clouds

• Plot 2D point clouds, colour-mapped by a per-point values array with a matching colorbar.
• Encode a second quantity through per-point marker sizes (with an optional size legend), so colour and size carry two variables at once.

VectorGlyph -- Vector Fields

• Render 2D (u, v) vector fields as arrows (quiver), wind barbs, or streamlines.
• Colour the artist by vector magnitude hypot(u, v) through the shared scalar-mapping pipeline.

FlowGlyph -- Flow Paths

• Draw a sequence of polylines as a LineCollection, colour-mapped by a per-path values array.
• Scale per-path line widths by magnitude, with an optional width legend.

LineGlyph -- Line / Bar / Band Plots

• Line, bar, and fill_between (band) plots from 1D or 2D y (one series per column).

PolygonGlyph -- Polygon Collections

• Fill and colour-map collections of polygons by a per-polygon values array, or draw outlines only.

KDEGlyph -- Kernel Density

• Estimate a 2D Gaussian kernel density of an (x, y) point cloud (NumPy only, no scipy) and draw it as filled or line density contours.

Colors -- Color Utilities

• Convert between hex, RGB (0-255), and normalized RGB (0-1) formats.
• Extract color ramps from images and create custom matplotlib colormaps.

Installation

pip

pip install cleopatra

# with the optional web-tile basemap support (cleopatra.tiles.add_tiles)
pip install "cleopatra[tiles]"

conda

conda install -c conda-forge cleopatra

# with the optional web-tile basemap support
conda install -c conda-forge cleopatra-tiles

The conda packages are built from the cleopatra-feedstock (the cleopatra-tiles output bundles mercantile, pillow, pyproj, and xyzservices).

From source (latest development version)

pip install git+https://github.com/serapeum-org/cleopatra

Quick Start

Plot a 2D array

import numpy as np
from cleopatra.array_glyph import ArrayGlyph

arr = np.random.rand(10, 10)
glyph = ArrayGlyph(arr)
fig, ax = glyph.plot(title="Random Array")

Create a histogram

import numpy as np
from cleopatra.statistical_glyph import StatisticalGlyph

data = np.random.normal(0, 1, 1000)
stat = StatisticalGlyph(data)
fig, ax = stat.histogram(bins=30)

Plot an unstructured mesh

import numpy as np
from cleopatra.mesh_glyph import MeshGlyph

node_x = np.array([0.0, 1.0, 0.5, 1.5])
node_y = np.array([0.0, 0.0, 1.0, 1.0])
face_nodes = np.array([[0, 1, 2], [1, 3, 2]])
face_data = np.array([10.0, 20.0])

mg = MeshGlyph(node_x, node_y, face_nodes)
fig, ax = mg.plot(face_data, location="face", title="Mesh Data")

Plot a value-coloured point cloud

import numpy as np
from cleopatra.scatter_glyph import ScatterGlyph

x = np.random.rand(100)
y = np.random.rand(100)
values = np.random.rand(100)
sg = ScatterGlyph(x, y, values=values)
fig, ax, sc = sg.plot(title="Scatter")

Plot a vector field

import numpy as np
from cleopatra.vector_glyph import VectorGlyph

x, y = np.meshgrid(np.linspace(0, 1, 8), np.linspace(0, 1, 8))
u, v = np.cos(x), np.sin(y)
vg = VectorGlyph(x, y, u, v)
fig, ax, artist = vg.plot(kind="quiver", title="Vector Field")

Requirements

• Python >= 3.11
• numpy >= 2.0.0
• matplotlib >= 3.9

Documentation

Full documentation is available at serapeum-org.github.io/cleopatra.

License

Cleopatra is licensed under the GNU General Public License v3.