Metadata-Version: 1.0
Name: sciproc
Version: 0.7.6
Summary: Process scientific multidimensional data.
Home-page: http://www.nowebsite.com
Author: H. Wouters
Author-email: hendrikwout@gmail.com
License: LICENSE.txt
Description: ===========
        sciproc
        ===========
        
        
        Sciproc in experimental stage provides tools to select, edit, convert
        scientific (observed, model-generated) data. It needs Numpy. It's very
        experimental, as some functions aren't tested or only tested in 'idealised
        cases', so please be careful.  Please let me know if you would like to
        contribute. Currently selection from 1D data by coordinates or certain timestep
        and applying a function repeatedly on a multidimensional matrix is implemented.
        However selecting, interpolating and editing procedures for multidimensional
        data is planned in the near future.  You might want to use it if you have have
        any observational data and you want to select a period, make a selection with a
        certain timestep or make an interpolation. The aim is to make an addition to
        the cdo climate data operators with python power (see also pynacolada). It
        should be working with normal numpy data. However, if you want to process
        netcdf-files, we recommend to use the pynacolada interface which acutally uses
        sciproc. Typical usage
        often looks like this::
        
            #!/usr/bin/env python
        
            from numpy import *
            from sciproc import *
        
            # select data from a 1-D array:
            data = array([1.0,2.0,4.0,2.5])
            incoords = array([0.0,1.0,2.0,3.0])
            print(datatimeco(data,coords = incoords,outcoords = array([1.0,2.0]))
        
            a = array([[[1,3,2],[2,1,3],[4,1,3]],[[1,2,3],[4,1,2],[3,0,1]]])
            print('copy')
            print( multifunc(a,[False,False,True],lambda x: copyfunction(x)))
            print('take only elements 2 and 3 from third dimension')
            print(multifunc(a,[False,False,True],lambda x: secondandthirdelement(x)))
            print('take only elements 2 and 3 from second dimension')
            print(multifunc(a,[False,True,False],lambda x: secondandthirdelement(x)))
            print('reduce dimension')
        
        
        
        
        
        A Section
        =========
        
        
        A Sub-Section
        -------------
        
        
        
Platform: UNKNOWN
