The attached archive contains sources of the converter allowing to read the
QUCS generated data into the Python program.
The data read from a QUCS file are placed into a qucs_data object.
This object contains two dictionaries:
* deps - for dependent variables
* indeps - for independent variables

Entry for each independent variable contains just a vector with values
of that variable
Entry for each dependent variable is an object of the qucs_dep_var
class, with the followinf fields:
* val - multi-dimensional array with values of that variable
* ind_vars - the vector with the names of the independent variables
corresponding to indices of the "val" array

The archive contains also source of the demo QUCS project (test1.sch
and test1.dpl). If you run the simulation, you should get the test1.dat
file. Then you can read it in the following way (below is the sample
interactive ipython session):

$ipython -pylab
In [1]: import qucs
In [2]: r=qucs.qucs_data("test1.dat")
In [3]: r.deps["Pr1.v"].ind_vars
Out[3]: ['acfrequency', 'Cctr', 'A1']
In [4]: plot(log(abs(r.deps["Pr1.v"].val[:,2,:])))