Usage

The fitter can be run directly on the local machine:

import park
M1 = park.models.Peaks(datafile=park.sampledata('peak.dat'))
M1.add_peak('P1', 'gaussian', A=[4,6], mu=[0.2, 0.5], sigma=0.1)
result = park.fit(models=[M1])
print result

The default settings print results every time the fit improves, and print a global result when the fit is complete. This is a suitable interface for a fitting script.

For larger fit jobs you will want to run the fit on a remote server. The model setup is identical, but the fit call is different:

service = park.FitService('server:port')
result = park.fit(models=[M1], service=service)
print result

Again, the default settings print results every time the fit improves, and print a global result when the fit is complete.

For long running fit jobs, you want to be able to disconnect from the server after submitting the job, and later reconnect to fetch the results. An additional email field will send notification by email when the fit starts and ends, and daily updates on the status of all fits:

service = park.FitService('server:port')
service.notify(email='me@my.email.address',update='daily')
fit = park.Fit(models=[M1])
id = service.start(fit, jobname='peaks')
print id

The results can be retrieved either by id returned from the server, or by the given jobname:

import park
service = park.FitService('server:port',user='userid')
fitlist = service.retrieve('peaks')
for fit in fitlist:
    print fit.summary()

The fit itself is a complicated object, including the model, the optimizer, and the type of uncertainty analysis to perform.

GUI Usage

When used from a graphical user interface, a different programming interface is needed. In this case, the user may want to watch the progress of the fit and perhaps stop it. Also, as fits can take some time to complete, the user would like to be able to set up additional fits and run them at the same time, switching between them as necessary to monitor progress:

import park

def start
service = park.FitService('server:port',user='userid')
fit = park.Fit(models=[M1])
id = sevice.start(fit,