Sorry, last post.  Here's a slightly more complete version for sake of archiving:

On Mon, Nov 25, 2013 at 9:45 PM, Adam Hughes <hughes...@gmail.com> wrote:

I made a couple basic utilties:

  zoom, crop, and zoomplot

They're very straightforward, but there was just enough nuance involved that working directly with numpy and matplotlib would become a pain.

See the attached notebook and/or pdf.  The PDF was generaged with nbconvert, and the image quality is poor.  Feel free to use and distribute this; please the ignore the content claim on the title page; it defaults to all of our pdfs that we generate with nbconvert.

On Friday, November 22, 2013 2:03:04 PM UTC-5, Adam Hughes wrote:

Hi everyone,

I'm used to working with big images of lots of particles.  In the notebook, I'd like to be able to look at a full image, and then at a zoomed in region of interest.  A few basic questions come to mind:

    

 Is there a zoom/crop function or preffered approach to basic manipulations of zooming and cropping, or would I have to do this at the numpy or matplotlib level?  I saw that there's a rectangle function that probably would be useful here.  Does anyone have any examples or personal code built for doing some of these common manipulations?   Ideally, I want to take the fastest approach to:

1.  Selecting a rectangular region of interest (ROI).

2.  Cropping or zooming in on this region, and storing the ROI as its own array/image.

3.  If possible, removing the ROI from the original image, and splicing the original image back together.  If this is possible, that would be amazing.  This would allow us to effectively cut out regions of our images that are obviously contaminates. 

Thanks.

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