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path: root/dpd/src/Measure.py
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# -*- coding: utf-8 -*-

import sys
import socket
import struct
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
import argparse
import os
import time
import logging
import Dab_Util as DU
import datetime

class Measure:
    """Collect Measurement from DabMod"""
    def __init__(self, samplerate, port, num_samples_to_request):
        logging.info("Instantiate Measure object")
        self.samplerate = samplerate
        self.sizeof_sample = 8 # complex floats
        self.port = port
        self.num_samples_to_request = num_samples_to_request

    def _recv_exact(self, sock, num_bytes):
        """Receive an exact number of bytes from a socket. This is
        a wrapper around sock.recv() that can return less than the number
        of requested bytes.

        Args:
            sock (socket): Socket to receive data from.
            num_bytes (int): Number of bytes that will be returned.
        """
        bufs = []
        while num_bytes > 0:
            b = sock.recv(num_bytes)
            if len(b) == 0:
                break
            num_bytes -= len(b)
            bufs.append(b)
        return b''.join(bufs)

    def get_samples(self):
        """Connect to ODR-DabMod, retrieve TX and RX samples, load
        into numpy arrays, and return a tuple
        (tx_timestamp, tx_samples, rx_timestamp, rx_samples)
        where the timestamps are doubles, and the samples are numpy
        arrays of complex floats, both having the same size
        """
        s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
        s.connect(('localhost', self.port))

        logging.debug("Send version")
        s.sendall(b"\x01")

        logging.debug("Send request for {} samples".format(self.num_samples_to_request))
        s.sendall(struct.pack("=I", self.num_samples_to_request))

        logging.debug("Wait for TX metadata")
        num_samps, tx_second, tx_pps = struct.unpack("=III", self._recv_exact(s, 12))
        tx_ts = tx_second + tx_pps / 16384000.0

        if num_samps > 0:
            logging.debug("Receiving {} TX samples".format(num_samps))
            txframe_bytes = self._recv_exact(s, num_samps * self.sizeof_sample)
            txframe = np.fromstring(txframe_bytes, dtype=np.complex64)
        else:
            txframe = np.array([], dtype=np.complex64)

        logging.debug("Wait for RX metadata")
        rx_second, rx_pps = struct.unpack("=II", self._recv_exact(s, 8))
        rx_ts = rx_second + rx_pps / 16384000.0

        if num_samps > 0:
            logging.debug("Receiving {} RX samples".format(num_samps))
            rxframe_bytes = self._recv_exact(s, num_samps * self.sizeof_sample)
            rxframe = np.fromstring(rxframe_bytes, dtype=np.complex64)
        else:
            rxframe = np.array([], dtype=np.complex64)

        if logging.getLogger().getEffectiveLevel() == logging.DEBUG:
            txframe_path = ('/tmp/txframe_fft_' +
                            datetime.datetime.now().isoformat() +
                            '.pdf')
            plt.plot(np.abs(np.fft.fftshift(np.fft.fft(txframe[2048:]))))
            plt.savefig(txframe_path)
            plt.clf()

            rxframe_path = ('/tmp/rxframe_fft_' +
                            datetime.datetime.now().isoformat() +
                            '.pdf')
            plt.plot(np.abs(np.fft.fftshift(np.fft.fft(rxframe[2048:]))))
            plt.savefig(rxframe_path)
            plt.clf()

            logging.debug("txframe: min %f, max %f, median %f, spectrum %s" %
                (np.min(np.abs(txframe)),
                 np.max(np.abs(txframe)),
                 np.median(np.abs(txframe)),
                 txframe_path))

            logging.debug("rxframe: min %f, max %f, median %f, spectrum %s" %
                (np.min(np.abs(rxframe)),
                 np.max(np.abs(rxframe)),
                 np.median(np.abs(rxframe)),
                 rxframe_path))

        logging.debug("Disconnecting")
        s.close()

        du = DU.Dab_Util(samplerate)
        txframe_aligned, rxframe_aligned = du.subsample_align(txframe, rxframe)

        logging.info(
            "Measurement done, tx %d %s, rx %d %s, tx aligned %d %s, rx aligned %d %s"
            % (len(txframe), txframe.dtype, len(rxframe), rxframe.dtype,
            len(txframe_aligned), txframe_aligned.dtype, len(rxframe_aligned), rxframe_aligned.dtype) )

        return txframe_aligned, rxframe_aligned

# The MIT License (MIT)
#
# Copyright (c) 2017 Andreas Steger
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in all
# copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.