setup.py

# -*- coding: utf-8 -*-

from setuptools import setup

setup(
  
  name='superpose3d',

  packages=['superpose3d'],

  description='Diamond\'s 1988 rotational superposition algorithm (+scale tranforms)',
  long_description='''Register 3-D point clouds using rotation, translation, and scale transformations.

##  Usage

```
def Superpose3D(X,    # <-- Nx3 array of coords for the "frozen" point cloud
                x,    # <-- Nx3 array of coords for the "mobile" point cloud
                w=None, #<- optional weights for the calculation of RMSD
                        #   (default w[n] = 1 for all n)
                allow_rescale=False)  #<--attempt to rescale mobile point cloud?
```

Superpose3D() takes two ordered lists (or numpy arrays) of xyz coordinates
(*of the same length*, **N**) representing points in a point cloud
(**X** and **x**). Treating them as rigid objects,
"Superpose3D()" attempts to superimpose them using **rotations**,
**translations**, and (optionally) **scale** transformations in order
to minimize the root-mean-squared-distance (RMSD) between corresponding
points from either point cloud, where RMSD is defined as:
```
   RMSD = sqrt( (Σ_n w[n] * Σ_i |X[n][i] - (Σ_j c*R[i][j]*x[n][j] + T[i])|^2) / (Σ_n w[n]) )
```
If *w=None*, equal weights are used.  In that case:
```
   RMSD = sqrt( (Σ_n Σ_i |X[n][i] - (Σ_j c*R[i][j]*x[n][j] + T[i])|^2) / N )
```
...where:
```
    T  = a translation vector (a 1-D numpy array containing x,y,z displacements),
    R  = a rotation matrix    (a 3x3 numpy array whose determinant = 1),
    c  = a scalar             (a number, 1 by default)
```
This function returns a 4-tuple containing the optimal values of:
```
   (RMSD, T, R, c)
```
This function implements a more general variant of the method from this paper:
R. Diamond, (1988)
"A Note on the Rotational Superposition Problem",
 Acta Cryst. A44, pp. 211-216.

This version has been augmented slightly to support scale transformations.  (I.E. multiplication by scalars.  This can be useful for the registration of two different annotated volumetric 3-D images of the same object taken at different magnifications.)

Note that if you enable scale transformations (i.e. if *allow_rescale=True*), you should be wary if the function returns a negative **c** value.  Negative **c** values correspond to inversions (reflections).  For this reason, if you are using this function to compare the conformations of molecules, you should probably set *allow_rescale=False*.  This will prevent matching a molecule with its stereoisomer.

Note: A C++ version of this repository is available at
https://github.com/jewettaij/superpose3d_cpp
''',

  long_description_content_type='text/markdown',

  author='Andrew Jewett',

  author_email='jewett.aij@gmail.com',

  url='https://github.com/jewettaij/superpose3d',

  download_url='https://github.com/jewettaij/superpose3d/archive/v0.2.11.zip',

  version='0.2.11',

  install_requires=[
      'numpy',
  ],
    
  keywords=['registration', '3d', 'structure-comparison', 'molecular-structure',
            'clem'],

  license='MIT',

  classifiers=['Development Status :: 4 - Beta',
               'License :: OSI Approved :: MIT License',
               'Environment :: Console',
               'Operating System :: MacOS :: MacOS X',
               'Operating System :: POSIX :: Linux',
               'Operating System :: Microsoft :: Windows',
               'Programming Language :: Python',
               'Topic :: Scientific/Engineering'],

  zip_safe=True,
  include_package_data=True
)