interpolate: refactor discrete_compensate

This commit is contained in:
Robert Jördens 2015-04-05 04:32:23 -06:00
parent 75dfa95b4d
commit 9fd4594c53
3 changed files with 18 additions and 23 deletions

View File

@ -6,6 +6,9 @@ import struct
import serial import serial
from artiq.wavesynth.interpolate import discrete_compensate
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
@ -53,24 +56,13 @@ class Segment:
values, widths, ud, fmt, e) values, widths, ud, fmt, e)
raise e raise e
@staticmethod
def compensate(coef):
"""compensates higher order spline coefficients for integrator chain
latency"""
order = len(coef)
if order > 2:
coef[1] += coef[2]/2.
if order > 3:
coef[1] += coef[3]/6.
coef[2] += coef[3]
return coef
def bias(self, amplitude=[], **kwargs): def bias(self, amplitude=[], **kwargs):
"""Append a bias line to this segment. """Append a bias line to this segment.
Amplitude in volts Amplitude in volts
""" """
coef = self.compensate([self.out_scale*a for a in amplitude]) coef = [self.out_scale*a for a in amplitude]
discrete_compensate(coef)
data = self.pack([0, 1, 2, 2], coef) data = self.pack([0, 1, 2, 2], coef)
self.line(typ=0, data=data, **kwargs) self.line(typ=0, data=data, **kwargs)
@ -83,7 +75,8 @@ class Segment:
phase[2] in turns*(sample_rate/2**shift)**2 phase[2] in turns*(sample_rate/2**shift)**2
""" """
scale = self.out_scale/self.cordic_gain scale = self.out_scale/self.cordic_gain
coef = self.compensate([scale*a for a in amplitude]) coef = [scale*a for a in amplitude]
discrete_compensate(coef)
if phase: if phase:
assert len(amplitude) == 4 assert len(amplitude) == 4
coef += [p*self.max_val*2 for p in phase] coef += [p*self.max_val*2 for p in phase]

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@ -1,13 +1,7 @@
from copy import copy from copy import copy
from math import cos, pi from math import cos, pi
from artiq.wavesynth.interpolate import discrete_compensate
def discrete_compensate(c):
if len(c) > 2:
c[1] += c[2]/2
if len(c) > 3:
c[1] += c[3]/6
c[2] += c[3]
class Spline: class Spline:

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@ -23,7 +23,15 @@ def _interpolate(time, data, sample_times, order=3):
return coeffs return coeffs
def _zip_program(times, channels, target=): def discrete_compensate(c):
if len(c) > 2:
c[1] += c[2]/2
if len(c) > 3:
c[1] += c[3]/6
c[2] += c[3]
def _zip_program(times, channels, target):
for tc in zip(times, *channels): for tc in zip(times, *channels):
yield { yield {
"duration": tc[0], "duration": tc[0],