Comments (2)
Hi @alpha-1-centauri ,
It depends on which plot. Many of the plotting functions accept an ax
argument so you can use them like this:
import decoupler as dc
import matplotlib.pyplot as plt
# Read
mat, net = dc.get_toy_data()
# Cerate a new figure
fig, ax = plt.subplots(1, 2)
ax = ax.ravel()
# Add plot in first subplot
dc.plot_filter_by_expr(mat, ax=ax[0])
In case the function does not have an ax
argument (you can check that with ?name_of_the_function
, for example ?plot_filter_by_expr
), you can always return the figure with return_fig=True
:
fig = dc.plot_filter_by_expr(mat, retrun_fig=True)
And then you can modify the figure directly like for example change the background color or change its size:
fig.set_facecolor('black')
fig.set_figwidth(6)
fig.set_figheight(3)
Alternatively, you can save the plot with save=plot.pdf
and then manually modify them with Affinity/Inkscape or any other vector based editing software.
Hope this is helpful!
from decoupler-py.
Worked great - thank you for the quick reply!
from decoupler-py.
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