Skip to main content

A steady-state stream model and python access to DFS-files

Project description

hydroinform

This package contains a steady-state stream model and some tools to access .dfs-files from DHI

Usage

Write a pump extraction file to be used with MikeZero:

#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();

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

hydroinform-0.1.11.tar.gz (43.3 kB view hashes)

Uploaded Source

Built Distribution

hydroinform-0.1.11-py3-none-any.whl (48.2 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page