diff options
Diffstat (limited to 'python/dpd/old')
| -rwxr-xr-x | python/dpd/old/apply_adapt_dumps.py | 75 | ||||
| -rwxr-xr-x | python/dpd/old/iq_file_server.py | 120 | ||||
| -rwxr-xr-x | python/dpd/old/main.py | 338 | ||||
| -rwxr-xr-x | python/dpd/old/show_spectrum.py | 276 | ||||
| -rwxr-xr-x | python/dpd/old/store_received.py | 85 |
5 files changed, 894 insertions, 0 deletions
diff --git a/python/dpd/old/apply_adapt_dumps.py b/python/dpd/old/apply_adapt_dumps.py new file mode 100755 index 0000000..20bc013 --- /dev/null +++ b/python/dpd/old/apply_adapt_dumps.py @@ -0,0 +1,75 @@ +#!/usr/bin/env python +# -*- coding: utf-8 -*- +# +# DPD Computation Engine, apply stored configuration. +# +# http://www.opendigitalradio.org +# Licence: The MIT License, see notice at the end of this file + +import datetime +import os +import glob +import logging + +dt = datetime.datetime.now().isoformat() +logging.basicConfig(format='%(asctime)s - %(module)s - %(levelname)s - %(message)s', + datefmt='%Y-%m-%d %H:%M:%S', + level=logging.DEBUG) + +import src.Adapt as Adapt +import argparse + +parser = argparse.ArgumentParser( + description="Load pkl dumps DPD settings into ODR-DabMod") +parser.add_argument('--port', default=50055, type=int, + help='port of DPD server to connect to (default: 50055)', + required=False) +parser.add_argument('--rc-port', default=9400, type=int, + help='port of ODR-DabMod ZMQ Remote Control to connect to (default: 9400)', + required=False) +parser.add_argument('--coefs', default='poly.coef', + help='File with DPD coefficients, which will be read by ODR-DabMod', + required=False) +parser.add_argument('file', help='File to read the DPD settings from') + +cli_args = parser.parse_args() + +port = cli_args.port +port_rc = cli_args.rc_port +coef_path = cli_args.coefs +filename = cli_args.file + +# No need to initialise a GlobalConfig since adapt only needs this one field +class DummyConfig: + def __init__(self): + self.plot_location = None + +c = DummyConfig() + +adapt = Adapt.Adapt(c, port_rc, coef_path) + +print("Loading and applying DPD settings from {}".format(filename)) +adapt.load(filename) + +# The MIT License (MIT) +# +# Copyright (c) 2017 Andreas Steger +# 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. diff --git a/python/dpd/old/iq_file_server.py b/python/dpd/old/iq_file_server.py new file mode 100755 index 0000000..7a4e570 --- /dev/null +++ b/python/dpd/old/iq_file_server.py @@ -0,0 +1,120 @@ +#!/usr/bin/env python +# -*- coding: utf-8 -*- +# +# This example server simulates the ODR-DabMod's +# DPD server, taking samples from an IQ file +# +# http://www.opendigitalradio.org +# Licence: The MIT License, see notice at the end of this file + +import sys +import socket +import struct +import argparse +import numpy as np +from datetime import datetime + +SIZEOF_SAMPLE = 8 # complex floats +# Constants for TM 1 +NbSymbols = 76 +NbCarriers = 1536 +Spacing = 2048 +NullSize = 2656 +SymSize = 2552 +FicSizeOut = 288 +FrameSize = NullSize + NbSymbols*SymSize + +def main(): + parser = argparse.ArgumentParser(description="Simulate ODR-DabMod DPD server") + parser.add_argument('--port', default='50055', + help='port to listen on (default: 50055)', + required=False) + parser.add_argument('--file', help='I/Q File to read from (complex floats)', + required=True) + parser.add_argument('--samplerate', default='8192000', help='Sample rate', + required=False) + + cli_args = parser.parse_args() + + serve_file(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 serve_file(options): + oversampling = int(int(options.samplerate) / 2048000) + consumesamples = 8*FrameSize * oversampling + iq_data = np.fromfile(options.file, count=consumesamples, dtype=np.complex64) + + print("Loaded {} samples of IQ data".format(len(iq_data))) + + s = socket.socket(socket.AF_INET, socket.SOCK_STREAM) + s.bind(('localhost', int(options.port))) + s.listen() + + try: + while True: + sock, addr_info = s.accept() + print("Got a connection from {}".format(addr_info)) + + ver = recv_exact(sock, 1) + (num_samps,) = struct.unpack("=I", recv_exact(sock, 4)) + num_bytes = num_samps * SIZEOF_SAMPLE + + if num_bytes > len(iq_data): + print("Truncating length to {} samples".format(len(iq_data))) + num_samps = len(iq_data) + num_bytes = num_samps * 4 + + tx_sec = datetime.now().timestamp() + tx_pps = int(16384000 * (tx_sec - int(tx_sec))) + tx_second = int(tx_sec) + + # TX metadata and data + sock.sendall(struct.pack("=III", num_samps, tx_second, tx_pps)) + sock.sendall(iq_data[-num_samps:].tobytes()) + + # RX metadata and data + rx_second = tx_second + 1 + rx_pps = tx_pps + sock.sendall(struct.pack("=III", num_samps, rx_second, rx_pps)) + sock.sendall(iq_data[-num_samps:].tobytes()) + + print("Sent {} samples".format(num_samps)) + + sock.close() + finally: + s.close() + raise + +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. diff --git a/python/dpd/old/main.py b/python/dpd/old/main.py new file mode 100755 index 0000000..9ea5a39 --- /dev/null +++ b/python/dpd/old/main.py @@ -0,0 +1,338 @@ +#!/usr/bin/env python +# -*- coding: utf-8 -*- +# +# DPD Computation Engine standalone main file. +# +# http://www.opendigitalradio.org +# Licence: The MIT License, see notice at the end of this file + +"""This Python script is the main file for ODR-DabMod's DPD Computation Engine running +in stand-alone mode. + +This engine calculates and updates the parameter of the digital +predistortion module of ODR-DabMod.""" + +import sys +import datetime +import os +import argparse +import matplotlib + +matplotlib.use('Agg') + +parser = argparse.ArgumentParser( + description="DPD Computation Engine for ODR-DabMod") +parser.add_argument('--port', default=50055, type=int, + help='port of DPD server to connect to (default: 50055)', + required=False) +parser.add_argument('--rc-port', default=9400, type=int, + help='port of ODR-DabMod ZMQ Remote Control to connect to (default: 9400)', + required=False) +parser.add_argument('--samplerate', default=8192000, type=int, + help='Sample rate', + required=False) +parser.add_argument('--coefs', default='poly.coef', + help='File with DPD coefficients, which will be read by ODR-DabMod', + required=False) +parser.add_argument('--txgain', default=-1, + help='TX Gain, -1 to leave unchanged', + required=False, + type=int) +parser.add_argument('--rxgain', default=30, + help='TX Gain, -1 to leave unchanged', + required=False, + type=int) +parser.add_argument('--digital_gain', default=0.01, + help='Digital Gain', + required=False, + type=float) +parser.add_argument('--target_median', default=0.05, + help='The target median for the RX and TX AGC', + required=False, + type=float) +parser.add_argument('--samps', default='81920', type=int, + help='Number of samples to request from ODR-DabMod', + required=False) +parser.add_argument('-i', '--iterations', default=10, type=int, + help='Number of iterations to run', + required=False) +parser.add_argument('-L', '--lut', + help='Use lookup table instead of polynomial predistorter', + action="store_true") +parser.add_argument('--enable-txgain-agc', + help='Enable the TX gain AGC', + action="store_true") +parser.add_argument('--plot', + help='Enable all plots, to be more selective choose plots in GlobalConfig.py', + action="store_true") +parser.add_argument('--name', default="", type=str, + help='Name of the logging directory') +parser.add_argument('-r', '--reset', action="store_true", + help='Reset the DPD settings to the defaults.') +parser.add_argument('-s', '--status', action="store_true", + help='Display the currently running DPD settings.') +parser.add_argument('--measure', action="store_true", + help='Only measure metrics once') + +cli_args = parser.parse_args() + +port = cli_args.port +port_rc = cli_args.rc_port +coef_path = cli_args.coefs +digital_gain = cli_args.digital_gain +num_iter = cli_args.iterations +rxgain = cli_args.rxgain +txgain = cli_args.txgain +name = cli_args.name +plot = cli_args.plot + +# Logging +import logging + +# Simple usage scenarios don't need to clutter /tmp +if not (cli_args.status or cli_args.reset or cli_args.measure): + dt = datetime.datetime.now().isoformat() + logging_path = '/tmp/dpd_{}'.format(dt).replace('.', '_').replace(':', '-') + if name: + logging_path += '_' + name + print("Logs and plots written to {}".format(logging_path)) + os.makedirs(logging_path) + logging.basicConfig(format='%(asctime)s - %(module)s - %(levelname)s - %(message)s', + datefmt='%Y-%m-%d %H:%M:%S', + filename='{}/dpd.log'.format(logging_path), + filemode='w', + level=logging.DEBUG) + # also log up to INFO to console + console = logging.StreamHandler() + console.setLevel(logging.INFO) + # set a format which is simpler for console use + formatter = logging.Formatter('%(asctime)s - %(module)s - %(levelname)s - %(message)s') + # tell the handler to use this format + console.setFormatter(formatter) + # add the handler to the root logger + logging.getLogger('').addHandler(console) +else: + dt = datetime.datetime.now().isoformat() + logging.basicConfig(format='%(asctime)s - %(module)s - %(levelname)s - %(message)s', + datefmt='%Y-%m-%d %H:%M:%S', + level=logging.INFO) + logging_path = None + +logging.info("DPDCE starting up with options: {}".format(cli_args)) + +import numpy as np +import traceback +from src.Model import Lut, Poly +import src.Heuristics as Heuristics +from src.Measure import Measure +from src.ExtractStatistic import ExtractStatistic +from src.Adapt import Adapt, dpddata_to_str +from src.RX_Agc import Agc +from src.TX_Agc import TX_Agc +from src.Symbol_align import Symbol_align +from src.GlobalConfig import GlobalConfig +from src.MER import MER +from src.Measure_Shoulders import Measure_Shoulders + +c = GlobalConfig(cli_args, logging_path) +SA = Symbol_align(c) +MER = MER(c) +MS = Measure_Shoulders(c) +meas = Measure(c, cli_args.samplerate, port, cli_args.samps) +extStat = ExtractStatistic(c) +adapt = Adapt(c, port_rc, coef_path) + +if cli_args.status: + txgain = adapt.get_txgain() + rxgain = adapt.get_rxgain() + digital_gain = adapt.get_digital_gain() + dpddata = dpddata_to_str(adapt.get_predistorter()) + + logging.info("ODR-DabMod currently running with TXGain {}, RXGain {}, digital gain {} and {}".format( + txgain, rxgain, digital_gain, dpddata)) + sys.exit(0) + +if cli_args.lut: + model = Lut(c) +else: + model = Poly(c) + +# Models have the default settings on startup +adapt.set_predistorter(model.get_dpd_data()) +adapt.set_digital_gain(digital_gain) + +# Set RX Gain +if rxgain == -1: + rxgain = adapt.get_rxgain() +else: + adapt.set_rxgain(rxgain) + +# Set TX Gain +if txgain == -1: + txgain = adapt.get_txgain() +else: + adapt.set_txgain(txgain) + +tx_gain = adapt.get_txgain() +rx_gain = adapt.get_rxgain() +digital_gain = adapt.get_digital_gain() + +dpddata = adapt.get_predistorter() + +logging.info("TX gain {}, RX gain {}, digital_gain {}, {!s}".format( + tx_gain, rx_gain, digital_gain, dpddata_to_str(dpddata))) + +if cli_args.reset: + logging.info("DPD Settings were reset to default values.") + sys.exit(0) + +# Automatic Gain Control +agc = Agc(meas, adapt, c) +agc.run() + +if cli_args.measure: + txframe_aligned, tx_ts, rxframe_aligned, rx_ts, rx_median = meas.get_samples() + + print("TX signal median {}".format(np.median(np.abs(txframe_aligned)))) + print("RX signal median {}".format(rx_median)) + + tx, rx, phase_diff, n_per_bin = extStat.extract(txframe_aligned, rxframe_aligned) + + off = SA.calc_offset(txframe_aligned) + print("off {}".format(off)) + tx_mer = MER.calc_mer(txframe_aligned[off:off + c.T_U], debug_name='TX') + print("tx_mer {}".format(tx_mer)) + rx_mer = MER.calc_mer(rxframe_aligned[off:off + c.T_U], debug_name='RX') + print("rx_mer {}".format(rx_mer)) + + mse = np.mean(np.abs((txframe_aligned - rxframe_aligned) ** 2)) + print("mse {}".format(mse)) + + digital_gain = adapt.get_digital_gain() + print("digital_gain {}".format(digital_gain)) + + #rx_shoulder_tuple = MS.average_shoulders(rxframe_aligned) + #tx_shoulder_tuple = MS.average_shoulders(txframe_aligned) + sys.exit(0) + +# Disable TXGain AGC by default, so that the experiments are controlled +# better. +tx_agc = None +if cli_args.enable_txgain_agc: + tx_agc = TX_Agc(adapt, c) + +state = 'report' +i = 0 +lr = None +n_meas = None +while i < num_iter: + try: + # Measure + if state == 'measure': + # Get Samples and check gain + txframe_aligned, tx_ts, rxframe_aligned, rx_ts, rx_median = meas.get_samples() + if tx_agc and tx_agc.adapt_if_necessary(txframe_aligned): + continue + + # Extract usable data from measurement + tx, rx, phase_diff, n_per_bin = extStat.extract(txframe_aligned, rxframe_aligned) + + n_meas = Heuristics.get_n_meas(i) + if extStat.n_meas >= n_meas: # Use as many measurements nr of runs + state = 'model' + else: + state = 'measure' + + # Model + elif state == 'model': + # Calculate new model parameters and delete old measurements + if any([x is None for x in [tx, rx, phase_diff]]): + logging.error("No data to calculate model") + state = 'measure' + continue + + lr = Heuristics.get_learning_rate(i) + model.train(tx, rx, phase_diff, lr=lr) + dpddata = model.get_dpd_data() + extStat = ExtractStatistic(c) + state = 'adapt' + + # Adapt + elif state == 'adapt': + adapt.set_predistorter(dpddata) + state = 'report' + + # Report + elif state == 'report': + try: + txframe_aligned, tx_ts, rxframe_aligned, rx_ts, rx_median = meas.get_samples() + + # Store all settings for pre-distortion, tx and rx + adapt.dump() + + # Collect logging data + off = SA.calc_offset(txframe_aligned) + tx_mer = MER.calc_mer(txframe_aligned[off:off + c.T_U], debug_name='TX') + rx_mer = MER.calc_mer(rxframe_aligned[off:off + c.T_U], debug_name='RX') + mse = np.mean(np.abs((txframe_aligned - rxframe_aligned) ** 2)) + tx_gain = adapt.get_txgain() + rx_gain = adapt.get_rxgain() + digital_gain = adapt.get_digital_gain() + tx_median = np.median(np.abs(txframe_aligned)) + rx_shoulder_tuple = MS.average_shoulders(rxframe_aligned) + tx_shoulder_tuple = MS.average_shoulders(txframe_aligned) + + # Generic logging + logging.info(list((name, eval(name)) for name in + ['i', 'tx_mer', 'tx_shoulder_tuple', 'rx_mer', + 'rx_shoulder_tuple', 'mse', 'tx_gain', + 'digital_gain', 'rx_gain', 'rx_median', + 'tx_median', 'lr', 'n_meas'])) + + # Model specific logging + if dpddata[0] == 'poly': + coefs_am = dpddata[1] + coefs_pm = dpddata[2] + logging.info('It {}: coefs_am {}'. + format(i, coefs_am)) + logging.info('It {}: coefs_pm {}'. + format(i, coefs_pm)) + elif dpddata[0] == 'lut': + scalefactor = dpddata[1] + lut = dpddata[2] + logging.info('It {}: LUT scalefactor {}, LUT {}'. + format(i, scalefactor, lut)) + except: + logging.error('Iteration {}: Report failed.'.format(i)) + logging.error(traceback.format_exc()) + i += 1 + state = 'measure' + + except: + logging.error('Iteration {} failed.'.format(i)) + logging.error(traceback.format_exc()) + i += 1 + state = 'measure' + +# The MIT License (MIT) +# +# Copyright (c) 2017 Andreas Steger +# 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. diff --git a/python/dpd/old/show_spectrum.py b/python/dpd/old/show_spectrum.py new file mode 100755 index 0000000..f23dba2 --- /dev/null +++ b/python/dpd/old/show_spectrum.py @@ -0,0 +1,276 @@ +#!/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. diff --git a/python/dpd/old/store_received.py b/python/dpd/old/store_received.py new file mode 100755 index 0000000..19b735e --- /dev/null +++ b/python/dpd/old/store_received.py @@ -0,0 +1,85 @@ +#!/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. +# +# Copyright (C) 2017 Matthias P. Braendli +# http://www.opendigitalradio.org +# Licence: The MIT License, see notice at the end of this file + +import sys +import socket +import struct +import argparse +import os +import time +from src.GlobalConfig import GlobalConfig +from src.Measure import Measure + +SIZEOF_SAMPLE = 8 # complex floats + +parser = argparse.ArgumentParser(description="Plot the spectrum of ODR-DabMod's DPD feedback") +parser.add_argument('--samps', default='10240', type=int, + help='Number of samples to request at once', + required=False) +parser.add_argument('--port', default='50055', type=int, + help='port to connect to ODR-DabMod DPD (default: 50055)', + required=False) +parser.add_argument('--count', default='1', type=int, + help='Number of recordings', + required=False) +parser.add_argument('--verbose', type=int, default=0, + help='Level of verbosity', + required=False) +parser.add_argument('--plot', + help='Enable all plots, to be more selective choose plots in GlobalConfig.py', + action="store_true") +parser.add_argument('--samplerate', default=8192000, type=int, + help='Sample rate', + required=False) + +cli_args = parser.parse_args() + +cli_args.target_median = 0.05 + +c = GlobalConfig(cli_args, None) + +meas = Measure(c, cli_args.samplerate, cli_args.port, cli_args.samps) + +for i in range(int(cli_args.count)): + if i>0: + time.sleep(0.1) + + txframe_aligned, tx_ts, rxframe_aligned, rx_ts, rx_median = meas.get_samples() + + txframe_aligned.tofile("%d_tx_record.iq" % i) + rxframe_aligned.tofile("%d_rx_record.iq" % i) + +# The MIT License (MIT) +# +# Copyright (c) 2018 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. |