The mfng module
This is the reference of the mfng module. The references have been
created mainly from the documentation strings of the program, so it is
quite up-to-date. If you want to learn the basics of the mfng, see the
tutorial.
-
class mfng.Generator(T0, steps, Tlimit, m=2, K=3, n=200, divexponent=2, project='base', verbose=False)
Generate a network with given properties.
- Paremeters:
- T: float
- initial temperature
- steps: int
- the number of steps
- Tlimit: float
- the temperature when the generation stops
- m: integer
- the probmeasure will be mxm type
- K: integer
- it will use K iteration to average the energy
- divexponent: int
- the exponent in the formula for adjusting division points
- project: string
- The values will be stored in the directory named with
'project_' + project
E.g if project is 'base' the directory will be 'project_base'.
The generation of a generator measure - an example:
generator = mfng.Generator(T0=0.2, steps=10000, Tlimit=0.00002,
m=3, K=3,
n=8000,
divexponent = 7,
project = 'base',
bigfloat = False
division = True,
)
generator.append_property(
mfng.AverageDegree(avg_degree)
)
generator.go()
-
append_property(prop)
Appends the property prop to the list of properties.
-
go()
Starts the generation.
Classes for target properties
-
class mfng.DistributionFunction(function, maxdeg, mindeg=0, **kwargs)
The main class to give a degree distribution as a function to the Generator.
- Parameters:
- funtion: string
- A valid Python expression with the only variable ‘k’.
This describes the target degree distribution.
The function will be normalized.
numpy functions are allowed.
E.g.: “5*numpy.exp(-4*k)”
- maxdeg: integer
- the maximal degree we compare it the degree distribution
of the probability measure with.
- mindeg: int, default 0, 0 <= mindeg < maxdeg
- like maxdeg, but for minimal degree
-
class mfng.AverageDegree(value)
The class to give an average degree to the Generator.
- Parameter:
- value: float, value >= 0
- The target average degree.