Metadata-Version: 1.2
Name: psf
Version: 2019.2.20
Summary: Point Spread Function calculations for fluorescence microscopy
Home-page: https://www.lfd.uci.edu/~gohlke/
Author: Christoph Gohlke
Author-email: cgohlke@uci.edu
License: BSD
Description: Point Spread Function calculations for fluorescence microscopy
        ==============================================================
        
        Psf is a Python library to calculate Point Spread Functions (PSF) for
        fluorescence microscopy.
        
        This library is no longer actively developed.
        
        :Authors:
          `Christoph Gohlke <https://www.lfd.uci.edu/~gohlke/>`_,
          Oliver Holub
        
        :Organization:
          Laboratory for Fluorescence Dynamics. University of California, Irvine
        
        :License: 3-clause BSD
        
        :Version: 2019.2.20
        
        Requirements
        ------------
        * `CPython 2.7 or 3.5+ <https://www.python.org>`_
        * `Numpy 1.14 <https://www.numpy.org>`_
        * `Matplotlib 2.2 <https://www.matplotlib.org>`_  (optional for plotting)
        * A Python distutils compatible C compiler  (build)
        
        Revisions
        ---------
        2019.1.1
            Update copyright year.
        
        References
        ----------
        (1) Electromagnetic diffraction in optical systems. II. Structure of the
            image field in an aplanatic system.
            B Richards and E Wolf. Proc R Soc Lond A, 253 (1274), 358-379, 1959.
        (2) Focal volume optics and experimental artifacts in confocal fluorescence
            correlation spectroscopy.
            S T Hess, W W Webb. Biophys J (83) 2300-17, 2002.
        (3) Electromagnetic description of image formation in confocal fluorescence
            microscopy.
            T D Viser, S H Wiersma. J Opt Soc Am A (11) 599-608, 1994.
        (4) Photon counting histogram: one-photon excitation.
            B Huang, T D Perroud, R N Zare. Chem Phys Chem (5), 1523-31, 2004.
            Supporting information: Calculation of the observation volume profile.
        (5) Gaussian approximations of fluorescence microscope point-spread function
            models.
            B Zhang, J Zerubia, J C Olivo-Marin. Appl. Optics (46) 1819-29, 2007.
        (6) The SVI-wiki on 3D microscopy, deconvolution, visualization and analysis.
            https://svi.nl/NyquistRate
        (7) Theory of Confocal Microscopy: Resolution and Contrast in Confocal
            Microscopy. http://www.olympusfluoview.com/theory/resolutionintro.html
        
        Examples
        --------
        >>> import psf
        >>> args = dict(shape=(32, 32), dims=(4, 4), ex_wavelen=488, em_wavelen=520,
        ...             num_aperture=1.2, refr_index=1.333,
        ...             pinhole_radius=0.55, pinhole_shape='round')
        >>> obsvol = psf.PSF(psf.GAUSSIAN | psf.CONFOCAL, **args)
        >>> print('%.5f, %.5f' % obsvol.sigma.ou)
        2.58832, 1.37059
        >>> obsvol = psf.PSF(psf.ISOTROPIC | psf.CONFOCAL, **args)
        >>> obsvol[0, :3]
        array([ 1.     ,  0.51071,  0.04397])
        >>> # save the image plane to file
        >>> obsvol.slice(0).tofile('_test_slice.bin')
        >>> # save a full 3D PSF volume to file
        >>> obsvol.volume().tofile('_test_volume.bin')
        
        Refer to the psf_example.py file in the source distribution for more.
        
Platform: any
Classifier: Development Status :: 7 - Inactive
Classifier: License :: OSI Approved :: BSD License
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: C
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Requires-Python: >=2.7
