Function

class pathsim.blocks.function.Function(func=<function Function.<lambda>>)

Bases: Block

Arbitrary MIMO function block, defined by a function or lambda expression.

The function can have multiple arguments that are then provided by the input channels of the function block.

Form multi input, the function has to specify multiple arguments and for multi output, the aoutputs have to be provided as a tuple or list.

In the context of the global system, this block implements algebraic components of the global system ODE/DAE.

\[\vec{y} = \mathrm{func}(\vec{u})\]

Note

This block is purely algebraic and its operation (op_alg) will be called multiple times per timestep, each time when Simulation._update(t) is called in the global simulation loop. Therefore func must be purely algebraic and not introduce states, delay, etc. For interfacing with external stateful APIs, use the Wrapper block.

Note

If the outputs are provided as a single numpy array, they are considered a single output. For MIMO, output has to be tuple.

Example

consider the function:

from pathsim.blocks import Function

def f(a, b, c):
    return a**2, a*b, b/c

fn = Function(f)

then, when the block is updated, the input channels of the block are assigned to the function arguments following this scheme:

inputs[0] -> a
inputs[1] -> b
inputs[2] -> c

and the function outputs are assigned to the output channels of the block in the same way:

a**2 -> outputs[0]
a*b  -> outputs[1]
b/c  -> outputs[2]

Because the Function block only has a single argument, it can be used to decorate a function and make it a PathSim block. This might be handy in some cases to keep definitions concise and localized in the code:

from pathsim.blocks import Function

#does the same as the definition above

@Function
def fn(a, b, c):
    return a**2, a*b, b/c

#'fn' is now a PathSim block

Parameters:

func (callable) – MIMO function that defines algebraic block IO behaviour, signature func(*tuple)

op_alg

internal algebraic operator that wraps func

Type:

Operator

update(t)

Evaluate function block as part of algebraic component of global system DAE.

Parameters:

t (float) – evaluation time

class pathsim.blocks.function.DynamicalFunction(func=<function DynamicalFunction.<lambda>>)

Bases: Block

Arbitrary MIMO time and input dependent function block.

The function signature needs two arguments f(u, t) where u is the (possibly vectorial) block input and t is a time dependency.

\[\vec{y} = \mathrm{func}(\vec{u}, t)\]

Note

This block does essentially the same as Function but with different requirements for the signature of the function to be wrapped. Block inputs are packed into an array u and this block additionally accepts time dependency in the function provided. Thats where the prefix Dynamical.. comes from.

Example

Lets say we want to implement a super simple model for a voltage controlled oscillator (VCO), where the block input controls the frequency of a sine wave at the output.

import numpy as np
from pathsim.blocks import DynamicalFunction

f_0 = 100

def f_vco(u, t):
    return np.sin(2*np.pi*f_0*u*t)

vco = DynamicalFunction(f_vco)

Using it as a decorator also works:

import numpy as np
from pathsim.blocks import DynamicalFunction

f_0 = 100

@DynamicalFunction
def vco(u, t):
    return np.sin(2*np.pi*f_0*u*t)

#'vco' is now a PathSim block

Parameters:

func (callable) – function that defines algebraic block IO behaviour with time dependency, signature func(u, t) where u is numpy.ndarray and t is float

op_alg

internal operator that wraps func

Type:

DynamicOperator

update(t)

Evaluate function with time dependency as part of algebraic component of global system DAE.

Parameters:

t (float) – evaluation time