Move python stuff to folder

1 files changed, 0 insertions, 276 deletions

diff --git a/dpd/show_spectrum.py b/dpd/show_spectrum.py
deleted file mode 100755
index f23dba2..0000000
--- a/dpd/show_spectrum.py
+++ /dev/null
@@ -1,276 +0,0 @@
-#!/usr/bin/env python
-# -*- coding: utf-8 -*-
-#
-# This is an example tool that shows how to connect to ODR-DabMod's dpd TCP
-# server and get samples from there.
-#
-# Since the TX and RX samples are not perfectly aligned, the tool has to align
-# them properly, which is done in two steps: First on sample-level using a
-# correlation, then with subsample accuracy using a FFT approach.
-#
-# It requires SciPy and matplotlib.
-#
-# http://www.opendigitalradio.org
-# Licence: The MIT License, see notice at the end of this file
-
-import sys
-import socket
-import struct
-import numpy as np
-import matplotlib.pyplot as pp
-from matplotlib.animation import FuncAnimation
-import argparse
-from scipy.misc import imsave
-
-SIZEOF_SAMPLE = 8 # complex floats
-
-# Constants for TM 1
-NbSymbols = 76
-NbCarriers = 1536
-Spacing = 2048
-NullSize = 2656
-SymSize = 2552
-FicSizeOut = 288
-
-def main():
-    parser = argparse.ArgumentParser(description="Plot the spectrum of ODR-DabMod's DPD feedback")
-    parser.add_argument('--samps', default='10240', help='Number of samples to request at once',
-            required=False)
-    parser.add_argument('--port', default='50055',
-            help='port to connect to ODR-DabMod DPD (default: 50055)',
-            required=False)
-    parser.add_argument('--animated', action='store_true', help='Enable real-time animation')
-    parser.add_argument('--constellation', action='store_true', help='Draw constellaton plot')
-    parser.add_argument('--samplerate', default='8192000', help='Sample rate',
-            required=False)
-
-    cli_args = parser.parse_args()
-
-    if cli_args.constellation:
-        plot_constellation_once(cli_args)
-    elif cli_args.animated:
-        plot_spectrum_animated(cli_args)
-    else:
-        plot_spectrum_once(cli_args)
-
-def recv_exact(sock, num_bytes):
-    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(port, num_samps_to_request):
-    """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', port))
-
-    print("Send version");
-    s.sendall(b"\x01")
-
-    print("Send request for {} samples".format(num_samps_to_request))
-    s.sendall(struct.pack("=I", num_samps_to_request))
-
-    print("Wait for TX metadata")
-    num_samps, tx_second, tx_pps = struct.unpack("=III", recv_exact(s, 12))
-    tx_ts = tx_second + tx_pps / 16384000.0
-
-    if num_samps > 0:
-        print("Receiving {} TX samples".format(num_samps))
-        txframe_bytes = recv_exact(s, num_samps * SIZEOF_SAMPLE)
-        txframe = np.fromstring(txframe_bytes, dtype=np.complex64)
-    else:
-        txframe = np.array([], dtype=np.complex64)
-
-
-    print("Wait for RX metadata")
-    rx_second, rx_pps = struct.unpack("=II", recv_exact(s, 8))
-    rx_ts = rx_second + rx_pps / 16384000.0
-
-    if num_samps > 0:
-        print("Receiving {} RX samples".format(num_samps))
-        rxframe_bytes = recv_exact(s, num_samps * SIZEOF_SAMPLE)
-        rxframe = np.fromstring(rxframe_bytes, dtype=np.complex64)
-    else:
-        rxframe = np.array([], dtype=np.complex64)
-
-    print("Disconnecting")
-    s.close()
-
-    return (tx_ts, txframe, rx_ts, rxframe)
-
-def recv_rxtx(port, num_samps_to_request):
-    tx_ts, txframe, rx_ts, rxframe = get_samples(port, num_samps_to_request)
-
-    # convert to complex doubles for more dynamic range
-    txframe = txframe.astype(np.complex128)
-    rxframe = rxframe.astype(np.complex128)
-
-    print("Received {} & {} frames at {} and {}".format(
-        len(txframe), len(rxframe), tx_ts, rx_ts))
-    return tx_ts, txframe, rx_ts, rxframe
-
-def get_spectrum(port, num_samps_to_request):
-    tx_ts, txframe, rx_ts, rxframe = recv_rxtx(port, num_samps_to_request)
-
-    print("Calculate TX and RX spectrum assuming 8192000 samples per second")
-    tx_spectrum = np.fft.fftshift(np.fft.fft(txframe, fft_size))
-    tx_power = 20*np.log10(np.abs(tx_spectrum))
-
-    rx_spectrum = np.fft.fftshift(np.fft.fft(rxframe, fft_size))
-    rx_power = 20*np.log10(np.abs(rx_spectrum))
-    return tx_power, rx_power
-
-def remove_guard_intervals(frame, options):
-    """Remove the cyclic prefix. The frame needs to be aligned to the
-    end of the transmission frame. Transmission Mode 1 is assumed"""
-    oversample = int(int(options.samplerate) / 2048000)
-
-    # From the end, take 2048 samples, then skip 504 samples
-    frame = frame[::-1]
-
-    stride_len = Spacing * oversample
-    stride_advance = SymSize * oversample
-
-    # Truncate the frame to an integer length of strides
-    newlen = len(frame) - (len(frame) % stride_advance)
-    print("Truncating frame from {} to {}".format(len(frame), newlen))
-    frame = frame[:newlen]
-
-    # Remove the cyclic prefix
-    frame = frame.reshape(-1, stride_advance)[:,:stride_len].reshape(-1)
-
-    # Reverse again
-    return frame[::-1]
-
-
-def plot_constellation_once(options):
-    port = int(options.port)
-    num_samps_to_request = int(options.samps)
-
-    tx_ts, txframe, rx_ts, rxframe = recv_rxtx(port, num_samps_to_request)
-
-    frame = remove_guard_intervals(txframe, options)
-
-    oversample = int(int(options.samplerate) / 2048000)
-
-    n = Spacing * oversample # is also number of samples per symbol
-    if len(frame) % n != 0:
-        raise ValueError("Frame length doesn't contain exact number of symbols")
-    num_syms = int(len(frame) / n)
-    print("frame {} has {} symbols".format(len(frame), num_syms))
-    spectrums = np.array([np.fft.fftshift(np.fft.fft(frame[n*i:n*(i+1)], n)) for i in range(num_syms)])
-
-    def normalise(x):
-        """Normalise a real-valued array x to the range [0,1]"""
-        y = x + np.min(x)
-        return x / np.max(x)
-
-    imsave("spectrums.png", np.concatenate([
-        normalise(np.abs(spectrums)),
-        normalise(np.angle(spectrums))]))
-
-    # Only take bins that are supposed to contain energy
-    # i.e. the middle 1536 bins, excluding the bin at n/2
-    assert(n % 2 == 0)
-    n_half = int(n/2)
-    spectrums = np.concatenate(
-            [spectrums[...,n_half-768:n_half],
-             spectrums[...,n_half + 1:n_half + 769]], axis=1)
-
-    sym_indices = (np.tile(np.arange(num_syms-1).reshape(num_syms-1,1), (1,NbCarriers)) +
-                   np.tile(np.linspace(-0.4, 0.4, NbCarriers), (num_syms-1, 1) ) )
-    sym_indices = sym_indices.reshape(-1)
-    diff_angles = np.mod(np.diff(np.angle(spectrums, deg=1), axis=0), 360)
-    #sym_points = spectrums[:-1].reshape(-1)
-    # Set amplitude and phase of low power points to zero, avoid cluttering diagram
-    #sym_points[np.abs(sym_points) < np.mean(np.abs(sym_points)) * 0.1] = 0
-
-    print("ix {}  spec {} da {}".format(
-        sym_indices.shape, spectrums.shape, diff_angles.shape))
-
-    fig = pp.figure()
-
-    fig.suptitle("Constellation")
-    ax1 = fig.add_subplot(111)
-    ax1.set_title("TX")
-    ax1.scatter(sym_indices, diff_angles.reshape(-1), alpha=0.1)
-
-    pp.show()
-
-fft_size = 4096
-
-def plot_spectrum_once(options):
-    port = int(options.port)
-    num_samps_to_request = int(options.samps)
-    freqs = np.fft.fftshift(np.fft.fftfreq(fft_size, d=1./int(options.samplerate)))
-
-    tx_power, rx_power = get_spectrum(port, num_samps_to_request)
-    fig = pp.figure()
-
-    fig.suptitle("TX and RX spectrum")
-    ax1 = fig.add_subplot(211)
-    ax1.set_title("TX")
-    ax1.plot(freqs, tx_power, 'r')
-    ax2 = fig.add_subplot(212)
-    ax2.set_title("RX")
-    ax2.plot(freqs, rx_power, 'b')
-    pp.show()
-
-def plot_spectrum_animated(options):
-    port = int(options.port)
-    num_samps_to_request = int(options.samps)
-    freqs = np.fft.fftshift(np.fft.fftfreq(fft_size, d=1./int(options.samplerate)))
-
-    fig, axes = pp.subplots(2, sharex=True)
-    line1, = axes[0].plot(freqs, np.ones(len(freqs)), 'r', animated=True)
-    axes[0].set_title("TX")
-    line2, = axes[1].plot(freqs, np.ones(len(freqs)), 'b', animated=True)
-    axes[1].set_title("RX")
-    lines = [line1, line2]
-
-    axes[0].set_ylim(-30, 50)
-    axes[1].set_ylim(-60, 40)
-
-    def update(frame):
-        tx_power, rx_power = get_spectrum(port, num_samps_to_request)
-
-        lines[0].set_ydata(tx_power)
-        lines[1].set_ydata(rx_power)
-        return lines
-
-    ani = FuncAnimation(fig, update, blit=True)
-    pp.show()
-
-main()
-
-# The MIT License (MIT)
-#
-# Copyright (c) 2017 Matthias P. Braendli
-#
-# 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.