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Peace-wise interpolation and lazy evaluation in cython

Project description

About

bpf4 is a library for curve fitting and break point functions in python. It is mainly programmed in Cython for efficiency. It has been used in itself for functional and numerical analysis.

Example

Find the intersection between two curves

>>> from bpf4 import bpf  # this imports the api
>>> import pylab
>>> a = bpf.spline((0, 0), (1, 5), (2, 3), (5, 10))  # each point (x, y)
>>> b = bpf.expon((0, -10), (2,15), (5, 3), exp=3)
>>> a.plot() # uses matplotlib
>>> b.plot()
>>> zeros = (a - b).zeros()
>>> pylab.plot(zeros, a.map(zeros), 'o')

![1](https://github.com/gesellkammer/bpf4/raw/master/pics/zeros.png)

Features

Many interpolation types besides linear:

  • spline
  • half-cosine
  • exponential
  • fibonacci
  • exponantial half-cosine
  • pchip
  • logarithmic
  • etc.

Interpolation types can be mixed, so that each segment has a different interpolation (with the exception of spline interpolation) Curves can be combined non-destructively. Following from the example above.

>>> c = (a + b).sin().abs()
>>> c[1.5:4].plot()  # plot only the range (1.5, 4)

![2](https://github.com/gesellkammer/bpf4/raw/master/pics/sinabs.png)

Syntax support for shifting, scaling and slicing a bpf

>>> a >> 2        # a shifted to the right
>>> (a * 5) ^ 2   # scale the x coord by 2, scale the y coord by 5
>>> a[2:2.5]      # slice only a portion of the bpf
>>> a[::0.01]     # sample the bpf with an interval of 0.01

Derivation and Integration: c.derivative().plot() or c.integrated().integrated().plot() Numerical integration: c.integrate_between(2, 4)

Dependencies

  • cython >= 0.19
  • numpy

Installation

To install the latest version (recommended)

$> git clone https://github.com/gesellkammer/bpf4.git $> cd bpf4 $> python setup.py install

Otherwise, via pip or easy_install

$> pip install bpf4

Project details


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