#########################################################################################

##

## COMPARATOR BLOCK

## (blocks/comparator.py)

##

#########################################################################################

# IMPORTS ===============================================================================

import numpy as np

from ._block import Block

from ..utils.register import Register

from ..events.zerocrossing import ZeroCrossing

# MIXED SIGNAL BLOCKS ===================================================================

class Comparator(Block):

"""Comparator block that sets output depending on predefined thresholds for the input.

Sets the output to '1' if the input signal crosses a predefined threshold and to '-1'

if it crosses in the reverse direction.

This is realized by the block spawning a zero-crossing event detector that watches

the input of the block and locates the transition up to a tolerance.

The block output is determined by a simple sign check in

the 'update' method.

Parameters

----------

threshold : float

threshold value for the comparator

tolerance : float

tolerance for zero crossing detection

span : list[float] or tuple[float], optional

output value range [min, max]

Attributes

----------

events : list[ZeroCrossing]

internal zero crossing event

"""

input_port_labels = {"in": 0}

output_port_labels = {"out":0}

def __init__(self, threshold=0, tolerance=1e-4, span=[-1, 1]):

super().__init__()

#block parameters

self.threshold = threshold

self.tolerance = tolerance

self.span = span

def func_evt(t):

return self.inputs[0] - self.threshold

#internal event for transition detection

self.events = [

ZeroCrossing(

func_evt=func_evt,

tolerance=tolerance

)

]

def update(self, t):

"""update system equation for fixed point loop,

here just setting the outputs

Note

----

no direct passthrough, so the 'update' method

is optimized for this case

Parameters

----------

t : float

evaluation time

Returns

-------

error : float

absolute error to previous iteration for convergence

control (here '0.0' because discrete block)

"""

if self.inputs[0] >= self.threshold:

self.outputs[0] = max(self.span)

else:

self.outputs[0] = min(self.span)