Programmatically configuring plots

Plots in Glue are designed to be easily configured with Python. As much as possible, plot settings are controlled by simple properties on data viewer objects. For example:

from glue.core import Data, DataCollection
from import GlueApplication
from glue.viewers.scatter.qt import ScatterWidget
import numpy as np

# create some data
d = Data(x=np.random.random(100), y=np.random.random(100))
dc = DataCollection([d])

# create a GUI session
ga = GlueApplication(dc)

# plot x vs y, flip the x axis, log-scale y axis
scatter = ga.new_data_viewer(ScatterWidget)
scatter.xatt =['x']
scatter.yatt =['y']
scatter.xflip = True
scatter.ylog = True

# show the GUI

Plot Options

Here are the settings associated with each data viewer:

Scatter Plots

xlog log scaling on x axis?
ylog log scaling on y axis?
xflip invert the x axis?
yflip invert the y axis?
xmin Lower x limit of plot
xmax Upper x limit of plot
ymin Lower y limit of plot
ymax Upper y limit of plot
hidden Show hidden attributes
xatt Attribute to plot on x axis
yatt Attribute to plot on y axis

Image Viewer

data Current data
attribute Current attribute
rgb_mode RGB Mode?

Histogram Viewer

xmin Minimum value
xmax Maximum value
normed Normalized?
autoscale Autoscale view to histogram?
cumulative Cumulative?
nbins Number of bins
xlog Log-scale the x axis?
ylog Log-scale the y axis?

Customizing Plots with Matplotlib

If you want, you can directly manipulate the Matplotlib plot objects that underly Glue plots. This can be useful if you want to create static plots with custom annotation, styles, etc.

From the GUI

Open the IPython terminal window. The application.viewers variable is a list of lists of all the open plot windows. Each inner list contains the data viewers open on a single tab. Every viewer has an axes attribute, which points to a Matplotlib Axes object:

plot = application.viewers[0][0]
ax = plot.axes
ax.set_title('Custom title')
ax.figure.canvas.draw()  # update the plot

From a script

Save the current glue session via File->Save Session. You can reload this session programmatically as follows:

from import GlueApplication
app = GlueApplication.restore('output.glu', show=False)
plot = app.viewers[0][0]
ax = plot.axes