#!/usr/bin/env python

import sys
import os
import numpy as np
import scipy.signal
import scipy.fftpack as fft

import gnsstools.beidou.b2bi as b2bi
import gnsstools.nco as nco
import gnsstools.io as io

#
# Acquisition search
#

def search(x,prn):
  fs = 3*10230000.0
  n = 3*10230                                       # 1 ms coherent integration
  incr = float(b2bi.code_length)/n
  c = b2bi.code(prn,0,0,incr,n)                     # obtain samples of the E5b-I code
  c = fft.fft(np.concatenate((c,np.zeros(n))))
  m_metric,m_code,m_doppler = 0,0,0
  for doppler in np.arange(-7000,7000,200):         # doppler bins
    q = np.zeros(2*n)
    w = nco.nco(-doppler/fs,0,2*n)
    for block in range(80):                         # 80 incoherent sums
      b = x[(block*n):((block+2)*n)]
      b = b*w
      r = fft.ifft(c*np.conj(fft.fft(b)))
      q = q + np.absolute(r)
    idx = np.argmax(q)
    if q[idx]>m_metric:
      m_metric = q[idx]
      m_code = b2bi.code_length*(float(idx)/n)
      m_doppler = doppler
  m_code = m_code%b2bi.code_length
  return m_metric,m_code,m_doppler

#
# main program
#

# parse command-line arguments
# example:
#   ./acquire-beidou-b2bi.py /dev/stdin 69984000 0

filename = sys.argv[1]        # input data, raw file, i/q interleaved, 8 bit signed (two's complement)
fs = float(sys.argv[2])       # sampling rate, Hz
coffset = float(sys.argv[3])  # offset to B2b BeiDou carrier, Hz (positive or negative)

# read first 85 ms of file

n = int(fs*0.085)
fp = open(filename,"rb")
x = io.get_samples_complex(fp,n)

# resample to 3*10.230 MHz

fsr = 3*10230000.0/fs
nco.mix(x,-coffset/fs,0)
h = scipy.signal.firwin(161,12e6/(fs/2),window='hanning')
x = scipy.signal.filtfilt(h,[1],x)
xr = np.interp((1/fsr)*np.arange(85*3*10230),np.arange(len(x)),np.real(x))
xi = np.interp((1/fsr)*np.arange(85*3*10230),np.arange(len(x)),np.imag(x))
x = xr+(1j)*xi

# iterate (in parallel) over PRNs of interest

def worker(p):
  x,prn = p
  metric,code,doppler = search(x,prn)
  return 'prn %3d doppler % 7.1f metric % 7.1f code_offset %6.1f' % (prn,doppler,metric,code)

import multiprocessing as mp

#prns = list(range(1,64))
prns = [21,48]
cpus = mp.cpu_count()
results = mp.Pool(cpus).map(worker, map(lambda prn: (x,prn),prns))

for r in results:
  print(r)