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Tony S. Yu

Tony S. Yu

http://tonysyu.github.io/

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Tony S. Yu | tonysyu.github.io Reviews
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Tony S. Yu | tonysyu.github.io Reviews

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Tony S. Yu

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1

matplotlib - Tony S. Yu

http://tonysyu.github.io/tag/matplotlib.html

Tony S. Yu. This post is more than a year in the making (life got in the way), so this isn't exactly hot off the press. I added support for style-sheets back in Matplotlib 1.4. Based on my implementation in mpltools. And built a gallery page. To easily compare styles . IPython (Jupyter) widgets: An image convolution demo. Convolution is one of the fundamental concepts of image processing (and more generally, signal processing). For the scikit-image tutorial at Scipy 2014. Animating particles in a flow.

2

sympy - Tony S. Yu

http://tonysyu.github.io/tag/sympy.html

Tony S. Yu. Animating particles in a flow. This article demonstrates matplotlib's animation. Module by animating marker particles in a fluid flow around a cylinder. It's a bit long because it ties together a number of different ideas:. Before we really start, let's copy a function from a . Plotting streamlines with Matplotlib and SymPy. Fluid mechanics lends itself to some beautiful visualizations. I won't really cover the math or theory. Here; I'm .

3

IPython (Jupyter) widgets: An image convolution demo - Tony S. Yu

http://tonysyu.github.io/ipython-jupyter-widgets-an-image-convolution-demo.html

Tony S. Yu. IPython (Jupyter) widgets: An image convolution demo. Mon 01 September 2014. Convolution is one of the fundamental concepts of image processing (and more generally, signal processing). For the scikit-image tutorial at Scipy 2014. I created an IPython widget to help visualize convolution. This post explains that widget in more detail. Only a small portion of this post is actually about using the widget API. IPython notebook widgets. 13 (earlier versions probably work). That looks like this:.

4

python - Tony S. Yu

http://tonysyu.github.io/tag/python.html

Tony S. Yu. Readable regular expressions in Python. Awhile back, I needed to parse some strings that were created using Python's string formatter. There's actually a package called parse. That's intended to do just that: Reuse the string formatting syntax to extract data from a string. Unfortunately, there were a couple of reasons that prevented . Provides a simple interface for adding modules and packages to your Python path. An IPython magic for manipulating your Python path.

5

Tony S. Yu

http://tonysyu.github.io/index3.html

Tony S. Yu. Let's say you have some continuous data with a continuous error (or variance) measurement. Typically, you would just call matplotlib's. When plotting a series of lines, it's nice to pull a series of colors from a colormap (especially if there's some sequential relationship between lines). In fact, this has been asked (and answered) multiple times on the Matplotlib mailing list (e.g., [1]. And on StackOverflow . Software developer, engineer, and all-around good guy in Austin, TX, USA.

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Http:/ tonysysy.skyr ock.com/. Parfois le passé ne devrait pas être détéré . (8). 31/07/2011 at 2:52 PM. 04/08/2011 at 11:38 AM. Subscribe to my blog! Don't forget that insults, racism, etc. are forbidden by Skyrock's 'General Terms of Use' and that you can be identified by your IP address (66.160.134.2) if someone makes a complaint. Please enter the sequence of characters in the field below. Posted on Thursday, 04 August 2011 at 11:38 AM. Post to my blog. Here you are free.

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Tony S. Yu

Tony S. Yu. Readable regular expressions in Python. Awhile back, I needed to parse some strings that were created using Python's string formatter. There's actually a package called parse. That's intended to do just that: Reuse the string formatting syntax to extract data from a string. Unfortunately, there were a couple of reasons that prevented . Provides a simple interface for adding modules and packages to your Python path. IPython (Jupyter) widgets: An image convolution demo. If you're collaborating ...

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