Metadata-Version: 2.1
Name: hydroinform
Version: 0.1.15
Summary: A steady-state stream model and python access to DFS-files
Home-page: http://hydroinform.dk
Author: Jan Gregersen and Jacob Gudbjerg
Author-email: jacobgudbjerg@gmail.com
License: UNKNOWN
Description: # hydroinform
        This package contains a steady-state stream model and some tools to access .dfs-files from DHI
        
        # Usage
        Convert .dfs, res1d and res11-files to netCDF:
        ```sh
        #Import NetCDF and DFS from hydroinform
        from hydroinform import NetCDF, DFS
        
        #Saves "omr4_jag_3DSZ.dfs3 as "omr4_jag_3DSZ.nc"
        NetCDF.save_as_NetCDF('omr4_jag_3DSZ.dfs3')
        
        #Saves "omr4_jag_3DSZ.dfs3 as "newname.nc"
        NetCDF.save_as_NetCDF('omr4_jag_3DSZ.dfs3','newname.nc')
        
        #Saves only the first item and the second and fourth time step from "omr4_jag_3DSZ.dfs3""
        d= DFS.DFSBase.open_file('omr4_jag_3DSZ.dfs3')
        NetCDF.save_dfs_as_NetCDF(d, [0], [1,3], 'omr4_jag_3DSZ_one_time.nc')
        
        #Saves the discharge data from "Storaa_HD_quasiStationary_20090701.res1d" as 'Storaa_HD_quasiStationary_20090701.nc'
        NetCDF.save_as_NetCDF('Storaa_HD_quasiStationary_20090701.res1d')
        
        ```
        
        Write a pump extraction file to be used with MikeZero:
        ```sh
        #Import DFS from HydroInform
        from hydroinform import DFS
        
        #The number of Items (In this case number of pumping wells)
        numberofitems = 5;
        
        #Now create the file.
        _tso = DFS.DFS0.new_file(r'c:\temp\extraction.dfs0'), numberofitems);
        
        #Loop the items and set the units etc.
        for itemCount in range (0, numberofitems):
            _tso.items[itemCount].value_type = DFS.DataValueType.MeanStepBackward
            _tso.items[itemCount].eum_item = DFS.EumItem.eumIPumpingRate
            _tso.items[itemCount].eum_unit = DFS.EumUnit.eumUm3PerYear
            _tso.items[itemCount].name = "Item number: " + str(itemCount)
              
        #Loop the years where you have pumping data
        tscount = 0;
        for year in range(2010, 2016):
            #For every year append a new timestep
            _tso.append_time_step(datetime.datetime(year, 12, 31, 12))
            #Loop the items and set a value for this timestep
            for itemCount in range (0, numberofitems):
                #Sets the data. Note that timesteps count from 0 and Items count from 1
                _tso.set_data(tscount, itemCount+1, year * itemCount)
            tscount+=1
        #Call dispose which will save and close the file.
        _tso.dispose()
        ```
Platform: UNKNOWN
Classifier: Programming Language :: Python
Classifier: License :: OSI Approved :: GNU General Public License (GPL)
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
