matplotview 0.1.0

A library for creating lightweight views of matplotlib axes.

matplotview

A library for creating lightweight views of matplotlib axes.

matplotview provides a simple interface for creating "views" of matplotlib axes, providing a simple way of displaying overviews and zoomed views of data without plotting data twice.

Installation

You can install matplotview using pip:

pip install matplotview

Usage

matplotview provides two methods, view, and inset_zoom_axes. The view method accepts two Axes, and makes the first axes a view of the second. The inset_zoom_axes method provides the same functionality as Axes.inset_axes, but the returned inset axes is configured to be a view of the parent axes.

Examples

An example of two axes showing the same plot.

from matplotview import view
import matplotlib.pyplot as plt
import numpy as np

fig, (ax1, ax2) = plt.subplots(1, 2)

# Plot a line, circle patch, some text, and an image...
ax1.plot([i for i in range(10)], "r")
ax1.add_patch(plt.Circle((3, 3), 1, ec="black", fc="blue"))
ax1.text(10, 10, "Hello World!", size=20)
ax1.imshow(np.random.rand(30, 30), origin="lower", cmap="Blues", alpha=0.5,
           interpolation="nearest")

# Turn axes 2 into a view of axes 1.
view(ax2, ax1)
# Modify the second axes data limits to match the first axes...
ax2.set_aspect(ax1.get_aspect())
ax2.set_xlim(ax1.get_xlim())
ax2.set_ylim(ax1.get_ylim())

fig.tight_layout()
fig.show()

An inset axes example.

from matplotlib import cbook
import matplotlib.pyplot as plt
import numpy as np
from matplotview import inset_zoom_axes

def get_demo_image():
    z = cbook.get_sample_data("axes_grid/bivariate_normal.npy", np_load=True)
    # z is a numpy array of 15x15
    return z, (-3, 4, -4, 3)

fig, ax = plt.subplots(figsize=[5, 4])

# Make the data...
Z, extent = get_demo_image()
Z2 = np.zeros((150, 150))
ny, nx = Z.shape
Z2[30:30+ny, 30:30+nx] = Z

ax.imshow(Z2, extent=extent, interpolation='nearest', origin="lower")

# Creates an inset axes with automatic view of the parent axes...
axins = inset_zoom_axes(ax, [0.5, 0.5, 0.47, 0.47])
# Set limits to sub region of the original image
x1, x2, y1, y2 = -1.5, -0.9, -2.5, -1.9
axins.set_xlim(x1, x2)
axins.set_ylim(y1, y2)
axins.set_xticklabels([])
axins.set_yticklabels([])

ax.indicate_inset_zoom(axins, edgecolor="black")

fig.show()

Because views support recursive drawing, they can be used to create fractals also.

import matplotlib.pyplot as plt
import matplotview as mpv
from matplotlib.patches import PathPatch
from matplotlib.path import Path
from matplotlib.transforms import Affine2D

outside_color = "black"
inner_color = "white"

t = Affine2D().scale(-0.5)

outer_triangle = Path.unit_regular_polygon(3)
inner_triangle = t.transform_path(outer_triangle)
b = outer_triangle.get_extents()

fig, ax = plt.subplots(1)
ax.set_aspect(1)

ax.add_patch(PathPatch(outer_triangle, fc=outside_color, ec=[0] * 4))
ax.add_patch(PathPatch(inner_triangle, fc=inner_color, ec=[0] * 4))
ax.set_xlim(b.x0, b.x1)
ax.set_ylim(b.y0, b.y1)

ax_locs = [
    [0, 0, 0.5, 0.5],
    [0.5, 0, 0.5, 0.5],
    [0.25, 0.5, 0.5, 0.5]
]

for loc in ax_locs:
    inax = mpv.inset_zoom_axes(ax, loc, render_depth=6)
    inax.set_xlim(b.x0, b.x1)
    inax.set_ylim(b.y0, b.y1)
    inax.axis("off")
    inax.patch.set_visible(False)

fig.show()