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For plotting points with matplotlib, we use the s argument of scatter(). The square root of s specifies the width and height of the markers in points.
In the datashader approach, we use ds.tf.spread(agg, px=px) to regulate the size of the markers. Here, px is calculated like this: px = int(np.round(np.sqrt(render_params.size))), to make the behavior agree to the matplotlib approach.
Problem: If you alter the dpi in pl.show(), the point size of the datashader points remains the same, whileit changes for matplotlib, leading to different sizes:
Now it looks like this, for dpi [50, 100, 200, 300] using blob.pl.render_points(element="blobs_points", size=400, color="blue").pl.render_points(element="blobs_points", size=400, color="yellow", method="datashader", alpha=1).pl.show(dpi=100)
Should be correct imo
For plotting points with matplotlib, we use the
s
argument ofscatter()
. The square root ofs
specifies the width and height of the markers in points.In the datashader approach, we use
ds.tf.spread(agg, px=px)
to regulate the size of the markers. Here,px
is calculated like this:px = int(np.round(np.sqrt(render_params.size)))
, to make the behavior agree to the matplotlib approach.Problem: If you alter the
dpi
inpl.show()
, the point size of the datashader points remains the same, whileit changes for matplotlib, leading to different sizes:dpi=100
, mpl=blue, ds=whitedpi=200
, mpl=blue, ds=whitedpi=50
, ds=blue, mpl=white (note: colors and order swapped!)The text was updated successfully, but these errors were encountered: