[SciPy-Dev] GSoC'15 Idea: Approximation with Parametric Splines

[Anastasiia Tsyplia]

Hello,

My name is Anastasiia Tsyplia. I am a 5th-yaer student of National Mining
University of Ukraine.

I am keen on interpolation/approximation with splines and it was a nice
surprise to find out that there is a demand in interpolation improvements
amongst the Scipy's ideas for GSoC'15. However, I've spend some time on
working out the idea
<https://drive.google.com/file/d/0BzveGSDwNVtBanU1THpFTXNKZHc/view?usp=sharing>
of my own.

Recently I've made a post <http://tsplb.blogspot.com/> dedicated to
description of the parametric spline curves construction process and
approaches to approximate engineering data by spline functions and
parametric spline curves with SciPy.

It seems that using parametric spline curves in approximation can be
extremely useful and time-saving approach. That's why I would like to share
my project idea and hope to hear some feedback as I am about to make a
proposal for the Google Summer of Code.

I have a 2-year experience in programming with Python, PyOpengl, PyQt,
Matplotlib, Numpy & SciPy. Some time I spent to dive into ctypes and
scratched the surface of C. Now my priority is Cython. I've read the book
on the spline methods recommended on SciPy's idea page, so I feel myself
competent in spline methods. I feel free with recursions: the last
challenge I faced was implementation of binary space partitioning algorithm
in python as I was writing my own ray-tracer.

I would like to contribute to SciPy by any means, so I'm ready to receive
instructions on my next move. And, certainly I'm looking forward to start
dealing with B-Splines in Cython as it is also a part of my project idea.


 Thanks in advance,

Looking forward to receive the feedback,

Anastasiia Tsyplia
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