Comments (2)
Hi @XuanZhoudiffer,
The figure that comes out of visualize_plot()
is a matplotlib.axes.Axes. You can therefore update its values by changing the axis attributes!
- For the background for example you can change the facecolor attribute:
ax = plotter_object.visualize_plot()
ax.set_facecolor('white') # Add your desired color here
ax.figure.savefig(fname='plot.png')
- For the dot sizes you can modify the collection of the plot size:
ax = plotter_object.visualize_plot()
ax.collections[0].set_sizes([300]) # Add your size here instead of 300
ax.figure.savefig(fname='plot.png')
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These manipulations require some knowledge of the Axis attributes of matplotlib
. I am leaving the issue open as to make it easier we will add the possibility to pass kwargs
used by matplotlib.axes.Axes.scatter(), over which the scatter version of visualize_plot()
is built on top, directly to visualize_plot()
. This way you won't have to manipulate the figure after it is created.
from chemplot.
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