Metadata-Version: 1.0
Name: sciproc
Version: 0.3.1
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
