Metadata-Version: 1.0
Name: sciproc
Version: 0.2.16
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.
        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
        ncdfextra). It should be working with normal numpy data. However,
        if you want to process netcdf-files, we recommend to use the ncdfextra 
        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
