The stgen module
This module offers various stochastic generators for point processes that can be used as spike trains.
The StGen class
Creation
Create an StGen object:
>>> st_gen = StGen()
This will initialize the stochastic generator and by default try to create a numpy random generator instance.
Optionally, you can also pass a random number generator instance to the constructor:
>>> import numpy >>> st_gen = StGen(rng = numpy.random.RandomState())
You can also use random number generators from gnu scientific library (gsl):
>>> from pygsl.rng import rng >>> st_gen_gsl = StGen(rng = rng())
If you want to seed the random number generator with a specific seed, you can do so in the constructor:
>>> st_gen = StGen(seed = 1234567)
Alternatively, you can re-seed the random number generator when the StGen object has already been created:
>>> st_gen.seed(7654321)
Poisson-distributed point processes
Using the StGen-object, you can generate point processes with inter-spike-intervals distributed according to a poisson distribution:
>>> st_gen = StGen() >>> spike_train_poisson = st_gen.poisson_generator(rate = 100., tstart = 0., tstop = 2500.)
This generates a NeuroTools.SpikeTrain object, containing spike times with an approximate rate of 100 Hz and a duration of 2.5 seconds.
If you want a numpy array of spike times rather than a SpikeTrain object, specify the array keyword:
>>> spike_train_array = st_gen.poisson_generator(rate = 100., array = True)
Dynamic poisson-distributes point processes
StGen can also generate inhomogeneous poisson processes, i.e. spike trains with dynamically changing rates:
>>> spike_train_dyn = st_gen.poissondyn_generator(rate = [50., 80., 30.],
t = [0., 1000., 2000.],
tstop = 2.5,
array = False)
This will generate a SpikeTrain object containing spike times with an approximate rate of 50 Hz for one second, followed by 80 Hz for one second, and finally 30 Hz for half a second. Note that t[0] is used as tstart.
For more stochastic generators see the source code.

