On Monday, February 17, 2014 8:14:10 PM UTC-5, Juan Nunez-Iglesias wrote:

Your first error is the circularity of a square of side 1, which according to your formula should be 4 * pi * 1 / (4^2) = pi / 4 ≈ 0.785.

Doh! Duh, right.

I don't know anything about the Canvas object so I'll let others comment on the rest, but clearly this is very dependent on how perimeter is computed: are we computing the perimeter of a polygon with the boundary vertices of the rasterization, or the perimeter along the (square) pixel boundaries, or the *convex* polygon enveloping the rasterized circle? Based on your numbers, I'd bet on one of the first two. Again, I'll let someone else deal with the correctness of the approach. =)

Canvas is actually just wrapping skimage.draw and region_props, so it uses the same rasterization that scikit image uses when a user draws a circle. Here's an example that uses pure scikit: http://nbviewer.ipython.org/github/hugadams/pyparty/blob/digitiaztion_help/e... I'm pretty sure that the results in the canvas are correct for the plotted circularity. Assuming that the calls to skimage.draw() are correct, would you know which *perimeter* of the methods you listed would be returned by region_props? Thanks Juan

Juan.

On Tue, Feb 18, 2014 at 11:35 AM, Adam Hughes <hughes...@gmail.com<javascript:>

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wrote:

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Hi,

I was trying to measure the circularity as a function of circle radius using the underlying circle object from skimage.draw(). I got some strange results, and tried to outline the exercise as well as the confusing outcome in a notebook. Essentially, the circularity as a function of particle radius does not seem to converge to 1.0, and in addition, at very small radii, the circularity does not agree with what one would expect from the circularity of a pixel (ie rectangle).

I was hoping that an expert could have a glance at the notebook and offer some feedback? Hoping that I made an obvious mistake or assertion somewhere.

The notebook actually uses my "pyparty" library that I posted a while back for drawing and storing the descriptors; however, I verified that these are the same descriptors that one gets using skimage.labels() directly (this is not show in the notebook).

Here's the static view:

http://nbviewer.ipython.org/github/hugadams/pyparty/blob/master/examples/Not...

Thanks.

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