Learned params¶

import numpy as np
import pandas as pd
from commplax import comm
from gdbp import gdbp_base as gb, plot as gplt, data as gdat

WARNING:absl:No GPU/TPU found, falling back to CPU. (Set TF_CPP_MIN_LOG_LEVEL=0 and rerun for more info.)

# load data
data_ch1 = gdat.load(1, 1, 1, 2)[0]
data_ch4 = gdat.load(1, 1, 4, 2)[0]

def train_gdbp(data, dtaps=261, ntaps=41):
  gdbp = gb.model_init(data, {'ntaps': ntaps, 'dtaps': dtaps, 'init_fn': gb.fdbp_init(data.a, xi=1.1, steps=3)}, [])
  params = list(zip(*list(gb.train(gdbp, data, n_iter=2000))))[1]
  return params

# start training 3 cases
params_ch1 = train_gdbp(data_ch1)
params_ch4 = train_gdbp(data_ch4)
params_few_taps = train_gdbp(data_ch4, dtaps=221, ntaps=11)

fig = gplt.gdbp_params(params_ch1, dpi=200)

gplt.gdbp_params(params_ch4, dpi=200)

gplt.gdbp_params(params_few_taps, dpi=200)