From 9d2c85f7a2a23fcf9ce3c842d86227afed43a153 Mon Sep 17 00:00:00 2001 From: "Matthias P. Braendli" Date: Tue, 18 Dec 2018 16:53:56 +0100 Subject: GUI: Automatically iterate captures and show model plots --- python/dpd/Model_Poly.py | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) (limited to 'python/dpd/Model_Poly.py') diff --git a/python/dpd/Model_Poly.py b/python/dpd/Model_Poly.py index c8f6135..ca39492 100644 --- a/python/dpd/Model_Poly.py +++ b/python/dpd/Model_Poly.py @@ -36,20 +36,20 @@ class Poly: """Calculates new coefficients using the measurement and the previous coefficients""" - def __init__(self, - c, - learning_rate_am=1.0, - learning_rate_pm=1.0): + def __init__(self, c, learning_rate_am=1.0, learning_rate_pm=1.0): self.c = c - self.plot = c.MDL_plot self.learning_rate_am = learning_rate_am self.learning_rate_pm = learning_rate_pm self.reset_coefs() - self.model_am = Model_AM.Model_AM(c, plot=self.plot) - self.model_pm = Model_PM.Model_PM(c, plot=self.plot) + self.model_am = Model_AM.Model_AM(c) + self.model_pm = Model_PM.Model_PM(c) + + def plot(self, am_plot_location, pm_plot_location, title): + self.model_am.plot(am_plot_location, title) + self.model_pm.plot(pm_plot_location, title) def reset_coefs(self): self.coefs_am = np.zeros(5, dtype=np.float32) -- cgit v1.2.3 From f4ca82137e850e30d31e7008b34800d8b2699e5d Mon Sep 17 00:00:00 2001 From: "Matthias P. Braendli" Date: Wed, 19 Dec 2018 16:11:58 +0100 Subject: DPD: Merge Model_PM and _AM into _Poly --- python/dpd/ExtractStatistic.py | 8 +- python/dpd/GlobalConfig.py | 9 +- python/dpd/Model_AM.py | 119 ------------------------ python/dpd/Model_PM.py | 121 ------------------------- python/dpd/Model_Poly.py | 146 ++++++++++++++++++++++++++---- python/dpd/RX_Agc.py | 18 ++-- python/dpdce.py | 41 ++++++--- python/gui/static/js/odr-predistortion.js | 10 ++ python/gui/templates/predistortion.html | 5 + 9 files changed, 190 insertions(+), 287 deletions(-) delete mode 100644 python/dpd/Model_AM.py delete mode 100644 python/dpd/Model_PM.py (limited to 'python/dpd/Model_Poly.py') diff --git a/python/dpd/ExtractStatistic.py b/python/dpd/ExtractStatistic.py index 1aa4391..a23fa1a 100644 --- a/python/dpd/ExtractStatistic.py +++ b/python/dpd/ExtractStatistic.py @@ -38,7 +38,7 @@ class ExtractStatistic: """Calculate a low variance RX value for equally spaced tx values of a predefined range""" - def __init__(self, c): + def __init__(self, c, peak_amplitude): self.c = c self._plot_data = None @@ -47,7 +47,7 @@ class ExtractStatistic: self.n_meas = 0 # Boundaries for the bins - self.tx_boundaries = np.linspace(c.ES_start, c.ES_end, c.ES_n_bins + 1) + self.tx_boundaries = np.linspace(0.0, peak_amplitude, c.ES_n_bins + 1) self.n_per_bin = c.ES_n_per_bin # List of rx values for each bin @@ -60,6 +60,10 @@ class ExtractStatistic: for i in range(c.ES_n_bins): self.tx_values_lists.append([]) + def get_bin_info(self): + return "Binning: {} bins used for amplitudes between {} and {}".format( + len(self.tx_boundaries), np.min(self.tx_boundaries), np.max(self.tx_boundaries)) + def plot(self, plot_path, title): if self._plot_data is not None: tx_values, rx_values, phase_diffs_values, phase_diffs_values_lists = self._plot_data diff --git a/python/dpd/GlobalConfig.py b/python/dpd/GlobalConfig.py index 99280f2..632a63b 100644 --- a/python/dpd/GlobalConfig.py +++ b/python/dpd/GlobalConfig.py @@ -26,6 +26,8 @@ class GlobalConfig: self.T_U = oversample * 2048 # Inverse of carrier spacing self.T_C = oversample * 504 # Duration of cyclic prefix + self.median_to_peak = 12 # Estimated value for a DAB OFDM signal + # Frequency Domain # example: np.delete(fft[3328:4865], 768) self.FFT_delta = 1536 # Number of carrier frequencies @@ -40,10 +42,8 @@ class GlobalConfig: self.phase_offset_per_sample = 1. / self.sample_rate * 2 * np.pi * 1000 # Constants for ExtractStatistic - self.ES_plot = plot - self.ES_start = 0.0 self.ES_end = 1.0 - self.ES_n_bins = 64 # Number of bins between ES_start and ES_end + self.ES_n_bins = 64 self.ES_n_per_bin = 128 # Number of measurements pre bin # Constants for Measure_Shoulder @@ -68,9 +68,6 @@ class GlobalConfig: # Constants for MER self.MER_plot = plot - # Constants for Model - self.MDL_plot = plot - # Constants for Model_PM # Set all phase offsets to zero for TX amplitude < MPM_tx_min self.MPM_tx_min = 0.1 diff --git a/python/dpd/Model_AM.py b/python/dpd/Model_AM.py deleted file mode 100644 index b07a5a5..0000000 --- a/python/dpd/Model_AM.py +++ /dev/null @@ -1,119 +0,0 @@ -# -*- coding: utf-8 -*- -# -# DPD Computation Engine, model implementation for Amplitude and not Phase -# -# http://www.opendigitalradio.org -# Licence: The MIT License, see notice at the end of this file - -import datetime -import os -import logging -import numpy as np -import matplotlib.pyplot as plt - - -def is_npfloat32(array): - assert isinstance(array, np.ndarray), type(array) - assert array.dtype == np.float32, array.dtype - assert array.flags.contiguous - assert not any(np.isnan(array)) - - -def check_input_get_next_coefs(tx_dpd, rx_received): - is_npfloat32(tx_dpd) - is_npfloat32(rx_received) - - -def poly(sig): - return np.array([sig ** i for i in range(1, 6)]).T - - -def fit_poly(tx_abs, rx_abs): - return np.linalg.lstsq(poly(rx_abs), tx_abs, rcond=None)[0] - - -def calc_line(coefs, min_amp, max_amp): - rx_range = np.linspace(min_amp, max_amp) - tx_est = np.sum(poly(rx_range) * coefs, axis=1) - return tx_est, rx_range - - -class Model_AM: - """Calculates new coefficients using the measurement and the previous - coefficients""" - - def __init__(self, c, learning_rate_am=1): - self.c = c - self.learning_rate_am = learning_rate_am - self._plot_data = None - - def plot(self, plot_location, title): - if self._plot_data is not None: - tx_dpd, rx_received, coefs_am, coefs_am_new = self._plot_data - - tx_range, rx_est = calc_line(coefs_am, 0, 0.6) - tx_range_new, rx_est_new = calc_line(coefs_am_new, 0, 0.6) - - sub_rows = 1 - sub_cols = 1 - fig = plt.figure(figsize=(sub_cols * 6, sub_rows / 2. * 6)) - i_sub = 0 - - i_sub += 1 - ax = plt.subplot(sub_rows, sub_cols, i_sub) - ax.plot(tx_range, rx_est, - label="Estimated TX", - alpha=0.3, - color="gray") - ax.plot(tx_range_new, rx_est_new, - label="New Estimated TX", - color="red") - ax.scatter(tx_dpd, rx_received, - label="Binned Data", - color="blue", - s=1) - ax.set_title("Model_AM {}".format(title)) - ax.set_xlabel("TX Amplitude") - ax.set_ylabel("RX Amplitude") - ax.set_xlim(-0.5, 1.5) - ax.legend(loc=4) - - fig.tight_layout() - fig.savefig(plot_location) - plt.close(fig) - - def get_next_coefs(self, tx_dpd, rx_received, coefs_am): - """Calculate the next AM/AM coefficients using the extracted - statistic of TX and RX amplitude""" - check_input_get_next_coefs(tx_dpd, rx_received) - - coefs_am_new = fit_poly(tx_dpd, rx_received) - coefs_am_new = coefs_am + \ - self.learning_rate_am * (coefs_am_new - coefs_am) - - self._plot_data = (tx_dpd, rx_received, coefs_am, coefs_am_new) - - return coefs_am_new - -# The MIT License (MIT) -# -# Copyright (c) 2017 Andreas Steger -# 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. diff --git a/python/dpd/Model_PM.py b/python/dpd/Model_PM.py deleted file mode 100644 index 40fa1d4..0000000 --- a/python/dpd/Model_PM.py +++ /dev/null @@ -1,121 +0,0 @@ -# -*- coding: utf-8 -*- -# -# DPD Computation Engine, model implementation for Amplitude and not Phase -# -# http://www.opendigitalradio.org -# Licence: The MIT License, see notice at the end of this file - -import datetime -import os -import logging -import numpy as np -import matplotlib.pyplot as plt - - -def is_npfloat32(array): - assert isinstance(array, np.ndarray), type(array) - assert array.dtype == np.float32, array.dtype - assert array.flags.contiguous - assert not any(np.isnan(array)) - - -def check_input_get_next_coefs(tx_dpd, phase_diff): - is_npfloat32(tx_dpd) - is_npfloat32(phase_diff) - - -class Model_PM: - """Calculates new coefficients using the measurement and the previous - coefficients""" - - def __init__(self, c, learning_rate_pm=1): - self.c = c - self.learning_rate_pm = learning_rate_pm - self._plot_data = None - - def plot(self, plot_location, title): - if self._plot_data is not None: - tx_dpd, phase_diff, coefs_pm, coefs_pm_new = self._plot_data - - tx_range, phase_diff_est = self.calc_line(coefs_pm, 0, 0.6) - tx_range_new, phase_diff_est_new = self.calc_line(coefs_pm_new, 0, 0.6) - - sub_rows = 1 - sub_cols = 1 - fig = plt.figure(figsize=(sub_cols * 6, sub_rows / 2. * 6)) - i_sub = 0 - - i_sub += 1 - ax = plt.subplot(sub_rows, sub_cols, i_sub) - ax.plot(tx_range, phase_diff_est, - label="Estimated Phase Diff", - alpha=0.3, - color="gray") - ax.plot(tx_range_new, phase_diff_est_new, - label="New Estimated Phase Diff", - color="red") - ax.scatter(tx_dpd, phase_diff, - label="Binned Data", - color="blue", - s=1) - ax.set_title("Model_PM {}".format(title)) - ax.set_xlabel("TX Amplitude") - ax.set_ylabel("Phase DIff") - ax.legend(loc=4) - - fig.tight_layout() - fig.savefig(plot_location) - plt.close(fig) - - def _discard_small_values(self, tx_dpd, phase_diff): - """ Assumes that the phase for small tx amplitudes is zero""" - mask = tx_dpd < self.c.MPM_tx_min - phase_diff[mask] = 0 - return tx_dpd, phase_diff - - def poly(self, sig): - return np.array([sig ** i for i in range(0, 5)]).T - - def fit_poly(self, tx_abs, phase_diff): - return np.linalg.lstsq(self.poly(tx_abs), phase_diff, rcond=None)[0] - - def calc_line(self, coefs, min_amp, max_amp): - tx_range = np.linspace(min_amp, max_amp) - phase_diff = np.sum(self.poly(tx_range) * coefs, axis=1) - return tx_range, phase_diff - - def get_next_coefs(self, tx_dpd, phase_diff, coefs_pm): - """Calculate the next AM/PM coefficients using the extracted - statistic of TX amplitude and phase difference""" - tx_dpd, phase_diff = self._discard_small_values(tx_dpd, phase_diff) - check_input_get_next_coefs(tx_dpd, phase_diff) - - coefs_pm_new = self.fit_poly(tx_dpd, phase_diff) - - coefs_pm_new = coefs_pm + self.learning_rate_pm * (coefs_pm_new - coefs_pm) - self._plot_data = (tx_dpd, phase_diff, coefs_pm, coefs_pm_new) - - return coefs_pm_new - -# The MIT License (MIT) -# -# Copyright (c) 2017 Andreas Steger -# 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. diff --git a/python/dpd/Model_Poly.py b/python/dpd/Model_Poly.py index ca39492..5722531 100644 --- a/python/dpd/Model_Poly.py +++ b/python/dpd/Model_Poly.py @@ -8,15 +8,13 @@ import os import logging import numpy as np +import matplotlib.pyplot as plt -import dpd.Model_AM as Model_AM -import dpd.Model_PM as Model_PM - - -def assert_np_float32(x): - assert isinstance(x, np.ndarray) - assert x.dtype == np.float32 - assert x.flags.contiguous +def assert_np_float32(array): + assert isinstance(array, np.ndarray), type(array) + assert array.dtype == np.float32, array.dtype + assert array.flags.contiguous + assert not any(np.isnan(array)) def _check_input_get_next_coefs(tx_abs, rx_abs, phase_diff): @@ -44,12 +42,73 @@ class Poly: self.reset_coefs() - self.model_am = Model_AM.Model_AM(c) - self.model_pm = Model_PM.Model_PM(c) - def plot(self, am_plot_location, pm_plot_location, title): - self.model_am.plot(am_plot_location, title) - self.model_pm.plot(pm_plot_location, title) + if self._am_plot_data is not None: + tx_dpd, rx_received, coefs_am, coefs_am_new = self._am_plot_data + + tx_range, rx_est = self._am_calc_line(coefs_am, 0, 0.6) + tx_range_new, rx_est_new = self._am_calc_line(coefs_am_new, 0, 0.6) + + sub_rows = 1 + sub_cols = 1 + fig = plt.figure(figsize=(sub_cols * 6, sub_rows / 2. * 6)) + i_sub = 0 + + i_sub += 1 + ax = plt.subplot(sub_rows, sub_cols, i_sub) + ax.plot(tx_range, rx_est, + label="Estimated TX", + alpha=0.3, + color="gray") + ax.plot(tx_range_new, rx_est_new, + label="New Estimated TX", + color="red") + ax.scatter(tx_dpd, rx_received, + label="Binned Data", + color="blue", + s=1) + ax.set_title("Model AM {}".format(title)) + ax.set_xlabel("TX Amplitude") + ax.set_ylabel("RX Amplitude") + ax.set_xlim(-0.5, 1.5) + ax.legend(loc=4) + + fig.tight_layout() + fig.savefig(am_plot_location) + plt.close(fig) + + if self._pm_plot_data is not None: + tx_dpd, phase_diff, coefs_pm, coefs_pm_new = self._pm_plot_data + + tx_range, phase_diff_est = self._pm_calc_line(coefs_pm, 0, 0.6) + tx_range_new, phase_diff_est_new = self._pm_calc_line(coefs_pm_new, 0, 0.6) + + sub_rows = 1 + sub_cols = 1 + fig = plt.figure(figsize=(sub_cols * 6, sub_rows / 2. * 6)) + i_sub = 0 + + i_sub += 1 + ax = plt.subplot(sub_rows, sub_cols, i_sub) + ax.plot(tx_range, phase_diff_est, + label="Estimated Phase Diff", + alpha=0.3, + color="gray") + ax.plot(tx_range_new, phase_diff_est_new, + label="New Estimated Phase Diff", + color="red") + ax.scatter(tx_dpd, phase_diff, + label="Binned Data", + color="blue", + s=1) + ax.set_title("Model PM {}".format(title)) + ax.set_xlabel("TX Amplitude") + ax.set_ylabel("Phase DIff") + ax.legend(loc=4) + + fig.tight_layout() + fig.savefig(pm_plot_location) + plt.close(fig) def reset_coefs(self): self.coefs_am = np.zeros(5, dtype=np.float32) @@ -65,12 +124,8 @@ class Poly: """ _check_input_get_next_coefs(tx_abs, rx_abs, phase_diff) - if not lr is None: - self.model_am.learning_rate_am = lr - self.model_pm.learning_rate_pm = lr - - coefs_am_new = self.model_am.get_next_coefs(tx_abs, rx_abs, self.coefs_am) - coefs_pm_new = self.model_pm.get_next_coefs(tx_abs, phase_diff, self.coefs_pm) + coefs_am_new = self._am_get_next_coefs(tx_abs, rx_abs, self.coefs_am) + coefs_pm_new = self._pm_get_next_coefs(tx_abs, phase_diff, self.coefs_pm) self.coefs_am = self.coefs_am + (coefs_am_new - self.coefs_am) * self.learning_rate_am self.coefs_pm = self.coefs_pm + (coefs_pm_new - self.coefs_pm) * self.learning_rate_pm @@ -78,9 +133,62 @@ class Poly: def get_dpd_data(self): return "poly", self.coefs_am, self.coefs_pm + def _am_calc_line(self, coefs, min_amp, max_amp): + rx_range = np.linspace(min_amp, max_amp) + tx_est = np.sum(self._am_poly(rx_range) * coefs, axis=1) + return tx_est, rx_range + + def _am_poly(self, sig): + return np.array([sig ** i for i in range(1, 6)]).T + + def _am_fit_poly(self, tx_abs, rx_abs): + return np.linalg.lstsq(self._am_poly(rx_abs), tx_abs, rcond=None)[0] + + def _am_get_next_coefs(self, tx_dpd, rx_received, coefs_am): + """Calculate the next AM/AM coefficients using the extracted + statistic of TX and RX amplitude""" + + coefs_am_new = self._am_fit_poly(tx_dpd, rx_received) + coefs_am_new = coefs_am + \ + self.learning_rate_am * (coefs_am_new - coefs_am) + + self._am_plot_data = (tx_dpd, rx_received, coefs_am, coefs_am_new) + + return coefs_am_new + + def _pm_poly(self, sig): + return np.array([sig ** i for i in range(0, 5)]).T + + def _pm_calc_line(self, coefs, min_amp, max_amp): + tx_range = np.linspace(min_amp, max_amp) + phase_diff = np.sum(self._pm_poly(tx_range) * coefs, axis=1) + return tx_range, phase_diff + + def _discard_small_values(self, tx_dpd, phase_diff): + """ Assumes that the phase for small tx amplitudes is zero""" + mask = tx_dpd < self.c.MPM_tx_min + phase_diff[mask] = 0 + return tx_dpd, phase_diff + + def _pm_fit_poly(self, tx_abs, phase_diff): + return np.linalg.lstsq(self._pm_poly(tx_abs), phase_diff, rcond=None)[0] + + def _pm_get_next_coefs(self, tx_dpd, phase_diff, coefs_pm): + """Calculate the next AM/PM coefficients using the extracted + statistic of TX amplitude and phase difference""" + tx_dpd, phase_diff = self._discard_small_values(tx_dpd, phase_diff) + + coefs_pm_new = self._pm_fit_poly(tx_dpd, phase_diff) + + coefs_pm_new = coefs_pm + self.learning_rate_pm * (coefs_pm_new - coefs_pm) + self._pm_plot_data = (tx_dpd, phase_diff, coefs_pm, coefs_pm_new) + + return coefs_pm_new + # The MIT License (MIT) # # Copyright (c) 2017 Andreas Steger +# Copyright (c) 2018 Matthias P. Brandli # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal diff --git a/python/dpd/RX_Agc.py b/python/dpd/RX_Agc.py index 4700e68..911f3c9 100644 --- a/python/dpd/RX_Agc.py +++ b/python/dpd/RX_Agc.py @@ -19,19 +19,19 @@ import dpd.Adapt as Adapt import dpd.Measure as Measure class Agc: - """The goal of the automatic gain control is to set the - RX gain to a value at which all received amplitudes can - be detected. This means that the maximum possible amplitude + """The goal of the automatic gain control is to set the + RX gain to a value at which all received amplitudes can + be detected. This means that the maximum possible amplitude should be quantized at the highest possible digital value. - A problem we have to face, is that the estimation of the - maximum amplitude by applying the max() function is very - unstable. This is due to the maximum’s rareness. Therefore - we estimate a far more robust value, such as the median, + A problem we have to face, is that the estimation of the + maximum amplitude by applying the max() function is very + unstable. This is due to the maximum’s rareness. Therefore + we estimate a far more robust value, such as the median, and then approximate the maximum amplitude from it. - Given this, we tune the RX gain in such a way, that the - received signal fulfills our desired property, of having + Given this, we tune the RX gain in such a way, that the + received signal fulfills our desired property, of having all amplitudes properly quantized.""" def __init__(self, measure, adapt, c): diff --git a/python/dpdce.py b/python/dpdce.py index e601d9c..18e628b 100755 --- a/python/dpdce.py +++ b/python/dpdce.py @@ -85,6 +85,7 @@ from lib import yamlrpc import numpy as np import traceback import os.path +import glob from threading import Thread, Lock from queue import Queue from dpd.Model import Poly @@ -156,8 +157,19 @@ command_queue = Queue(maxsize=1) # Automatic Gain Control for the RX gain agc = Agc(meas, adapt, c) +def clear_pngs(results): + results['statplot'] = None + results['amplot'] = None + results['pmplot'] = None + pngs = glob.glob(os.path.join(plot_path, "*.png")) + for png in pngs: + try: + os.remove(png) + except: + results['summary'] += ["failed to delete " + png] + def engine_worker(): - extStat = ExtractStatistic(c) + extStat = None try: while True: cmd = command_queue.get() @@ -168,12 +180,13 @@ def engine_worker(): with lock: results['state'] = 'RX Gain Calibration' results['stateprogress'] = 0 + clear_pngs(results) summary = [] N_ITER = 5 for i in range(N_ITER): agc_success, agc_summary = agc.run() - summary += ["calibration run {}:".format(i)] + agc_summary.split("\n") + summary += ["Iteration {}:".format(i)] + agc_summary.split("\n") with lock: results['stateprogress'] = int((i + 1) * 100/N_ITER) @@ -191,14 +204,16 @@ def engine_worker(): results['rx_median'] = float(rx_median) results['state'] = 'Idle' results['stateprogress'] = 100 - results['summary'] = ["Calibration was done:"] + summary + results['summary'] = summary + ["Calibration done"] elif cmd == "reset": with lock: internal_data['n_runs'] = 0 results['state'] = 'Idle' results['stateprogress'] = 0 results['summary'] = ["Reset"] - extStat = ExtractStatistic(c) + clear_pngs(results) + extStat = None + model.reset_coefs() elif cmd == "trigger_run": with lock: results['state'] = 'Capture + Model' @@ -208,12 +223,17 @@ def engine_worker(): while True: # Get Samples and check gain txframe_aligned, tx_ts, rxframe_aligned, rx_ts, rx_median, tx_median = meas.get_samples() - # TODO Check TX median + + if extStat is None: + # At first run, we must decide how to create the bins + peak_estimated = tx_median * c.median_to_peak + extStat = ExtractStatistic(c, peak_estimated) with lock: results['stateprogress'] += 5 results['summary'] = ["Captured {} samples".format(len(txframe_aligned)), - "TX/RX median: {} / {}".format(tx_median, rx_median)] + "TX/RX median: {} / {}".format(tx_median, rx_median), + extStat.get_bin_info()] # Extract usable data from measurement tx, rx, phase_diff, n_per_bin = extStat.extract(txframe_aligned, rxframe_aligned) @@ -240,7 +260,7 @@ def engine_worker(): else: with lock: results['state'] = 'Capture + Model' - results['stateprogress'] = 60 + results['stateprogress'] = 80 results['summary'] += ["Training model"] model.train(tx, rx, phase_diff, lr=Heuristics.get_learning_rate(n_runs)) @@ -257,7 +277,7 @@ def engine_worker(): results['amplot'] = "dpd/" + am_plot_file results['pmplot'] = "dpd/" + pm_plot_file results['state'] = 'Capture + Model' - results['stateprogress'] = 70 + results['stateprogress'] = 85 results['summary'] += ["Getting DPD data"] dpddata = model.get_dpd_data() @@ -266,16 +286,15 @@ def engine_worker(): internal_data['n_runs'] = 0 results['state'] = 'Capture + Model' - results['stateprogress'] = 80 + results['stateprogress'] = 90 results['summary'] += ["Reset statistics"] - extStat = ExtractStatistic(c) + extStat = None with lock: results['state'] = 'Idle' results['stateprogress'] = 100 results['summary'] += ["New DPD coefficients calculated"] - finally: with lock: results['state'] = 'Terminated' diff --git a/python/gui/static/js/odr-predistortion.js b/python/gui/static/js/odr-predistortion.js index ff82142..59dcd82 100644 --- a/python/gui/static/js/odr-predistortion.js +++ b/python/gui/static/js/odr-predistortion.js @@ -39,13 +39,23 @@ function resultrefresh() { if (data['statplot']) { $('#dpdcapturestats').attr('src', data['statplot']); } + else { + $('#dpdcapturestats').attr('src', ""); + } if (data['amplot']) { $('#dpdamplot').attr('src', data['amplot']); } + else { + $('#dpdamplot').attr('src', ""); + } + if (data['pmplot']) { $('#dpdpmplot').attr('src', data['pmplot']); } + else { + $('#dpdpmplot').attr('src', ""); + } }); jqxhr.always(function() { diff --git a/python/gui/templates/predistortion.html b/python/gui/templates/predistortion.html index e21c688..d953dff 100644 --- a/python/gui/templates/predistortion.html +++ b/python/gui/templates/predistortion.html @@ -42,6 +42,11 @@
Capture Statistics
+
+ +
+
AM/AM and AM/PM Model
+
-- cgit v1.2.3 From 49620ea6940543a875e0499a1554b33ffb85fa85 Mon Sep 17 00:00:00 2001 From: "Matthias P. Braendli" Date: Wed, 19 Dec 2018 16:29:39 +0100 Subject: GUI: Combine model plots into single plot --- .gitignore | 1 + python/dpd/ExtractStatistic.py | 2 +- python/dpd/Model_Poly.py | 26 +++++++++----------------- python/dpdce.py | 22 ++++++++++------------ python/gui/static/js/odr-predistortion.js | 13 ++++--------- python/gui/templates/predistortion.html | 13 +++++++++++-- 6 files changed, 36 insertions(+), 41 deletions(-) (limited to 'python/dpd/Model_Poly.py') diff --git a/.gitignore b/.gitignore index 21d7201..3ac59f6 100644 --- a/.gitignore +++ b/.gitignore @@ -24,3 +24,4 @@ __pycache__/ python/gui/logs/access.log python/gui/logs/error.log +python/gui/static/dpd/*png diff --git a/python/dpd/ExtractStatistic.py b/python/dpd/ExtractStatistic.py index a23fa1a..25647a6 100644 --- a/python/dpd/ExtractStatistic.py +++ b/python/dpd/ExtractStatistic.py @@ -115,7 +115,7 @@ class ExtractStatistic: i_sub += 1 ax = plt.subplot(sub_rows, sub_cols, i_sub) ax.plot(num) - ax.set_xlabel("TX Amplitude") + ax.set_xlabel("TX Amplitude bin") ax.set_ylabel("Number of Samples") ax.set_ylim(0, self.n_per_bin * 1.2) diff --git a/python/dpd/Model_Poly.py b/python/dpd/Model_Poly.py index 5722531..7ab6aa1 100644 --- a/python/dpd/Model_Poly.py +++ b/python/dpd/Model_Poly.py @@ -42,18 +42,19 @@ class Poly: self.reset_coefs() - def plot(self, am_plot_location, pm_plot_location, title): - if self._am_plot_data is not None: + def plot(self, plot_location, title): + if self._am_plot_data is not None and self._pm_plot_data is not None: tx_dpd, rx_received, coefs_am, coefs_am_new = self._am_plot_data tx_range, rx_est = self._am_calc_line(coefs_am, 0, 0.6) tx_range_new, rx_est_new = self._am_calc_line(coefs_am_new, 0, 0.6) - sub_rows = 1 + sub_rows = 2 sub_cols = 1 fig = plt.figure(figsize=(sub_cols * 6, sub_rows / 2. * 6)) i_sub = 0 + # AM subplot i_sub += 1 ax = plt.subplot(sub_rows, sub_cols, i_sub) ax.plot(tx_range, rx_est, @@ -67,27 +68,18 @@ class Poly: label="Binned Data", color="blue", s=1) - ax.set_title("Model AM {}".format(title)) + ax.set_title("Model AM and PM {}".format(title)) ax.set_xlabel("TX Amplitude") ax.set_ylabel("RX Amplitude") - ax.set_xlim(-0.5, 1.5) + ax.set_xlim(0, 1.0) ax.legend(loc=4) - fig.tight_layout() - fig.savefig(am_plot_location) - plt.close(fig) - - if self._pm_plot_data is not None: + # PM sub plot tx_dpd, phase_diff, coefs_pm, coefs_pm_new = self._pm_plot_data tx_range, phase_diff_est = self._pm_calc_line(coefs_pm, 0, 0.6) tx_range_new, phase_diff_est_new = self._pm_calc_line(coefs_pm_new, 0, 0.6) - sub_rows = 1 - sub_cols = 1 - fig = plt.figure(figsize=(sub_cols * 6, sub_rows / 2. * 6)) - i_sub = 0 - i_sub += 1 ax = plt.subplot(sub_rows, sub_cols, i_sub) ax.plot(tx_range, phase_diff_est, @@ -101,13 +93,13 @@ class Poly: label="Binned Data", color="blue", s=1) - ax.set_title("Model PM {}".format(title)) ax.set_xlabel("TX Amplitude") ax.set_ylabel("Phase DIff") + ax.set_xlim(0, 1.0) ax.legend(loc=4) fig.tight_layout() - fig.savefig(pm_plot_location) + fig.savefig(plot_location) plt.close(fig) def reset_coefs(self): diff --git a/python/dpdce.py b/python/dpdce.py index 18e628b..f76b0f6 100755 --- a/python/dpdce.py +++ b/python/dpdce.py @@ -143,8 +143,8 @@ internal_data = { } results = { 'statplot': None, - 'amplot': None, - 'pmplot': None, + 'modelplot': None, + 'modeldata': "", 'tx_median': 0, 'rx_median': 0, 'state': 'Idle', @@ -159,8 +159,7 @@ agc = Agc(meas, adapt, c) def clear_pngs(results): results['statplot'] = None - results['amplot'] = None - results['pmplot'] = None + results['modelplot'] = None pngs = glob.glob(os.path.join(plot_path, "*.png")) for png in pngs: try: @@ -206,14 +205,15 @@ def engine_worker(): results['stateprogress'] = 100 results['summary'] = summary + ["Calibration done"] elif cmd == "reset": + model.reset_coefs() with lock: internal_data['n_runs'] = 0 results['state'] = 'Idle' results['stateprogress'] = 0 results['summary'] = ["Reset"] + results['modeldata'] = repr(model.get_dpd_data()) clear_pngs(results) extStat = None - model.reset_coefs() elif cmd == "trigger_run": with lock: results['state'] = 'Capture + Model' @@ -246,7 +246,7 @@ def engine_worker(): with lock: results['statplot'] = "dpd/" + plot_file results['stateprogress'] += 5 - results['summary'] += ["Extracted Statistics".format(tx_median, rx_median), + results['summary'] += ["Extracted Statistics: TX median={} RX median={}".format(tx_median, rx_median), "Runs: {}/{}".format(extStat.n_meas, n_meas)] internal_data['n_runs'] += 1 if extStat.n_meas >= n_meas: @@ -266,16 +266,13 @@ def engine_worker(): model.train(tx, rx, phase_diff, lr=Heuristics.get_learning_rate(n_runs)) time = datetime.datetime.utcnow() - am_plot_file = "model_am_{}.png".format(time.strftime("%s")) - pm_plot_file = "model_pm_{}.png".format(time.strftime("%s")) + model_plot_file = "model_{}.png".format(time.strftime("%s")) model.plot( - os.path.join(plot_path, am_plot_file), - os.path.join(plot_path, pm_plot_file), + os.path.join(plot_path, model_plot_file), time.strftime("%Y-%m-%dT%H%M%S")) with lock: - results['amplot'] = "dpd/" + am_plot_file - results['pmplot'] = "dpd/" + pm_plot_file + results['modelplot'] = "dpd/" + model_plot_file results['state'] = 'Capture + Model' results['stateprogress'] = 85 results['summary'] += ["Getting DPD data"] @@ -285,6 +282,7 @@ def engine_worker(): internal_data['dpddata'] = dpddata internal_data['n_runs'] = 0 + results['modeldata'] = repr(dpddata) results['state'] = 'Capture + Model' results['stateprogress'] = 90 results['summary'] += ["Reset statistics"] diff --git a/python/gui/static/js/odr-predistortion.js b/python/gui/static/js/odr-predistortion.js index 59dcd82..f46219c 100644 --- a/python/gui/static/js/odr-predistortion.js +++ b/python/gui/static/js/odr-predistortion.js @@ -43,18 +43,13 @@ function resultrefresh() { $('#dpdcapturestats').attr('src', ""); } - if (data['amplot']) { - $('#dpdamplot').attr('src', data['amplot']); - } - else { - $('#dpdamplot').attr('src', ""); - } + $('#dpdmodeldata').html(data['modeldata']); - if (data['pmplot']) { - $('#dpdpmplot').attr('src', data['pmplot']); + if (data['modelplot']) { + $('#dpdmodelplot').attr('src', data['modelplot']); } else { - $('#dpdpmplot').attr('src', ""); + $('#dpdmodelplot').attr('src', ""); } }); diff --git a/python/gui/templates/predistortion.html b/python/gui/templates/predistortion.html index d953dff..d102101 100644 --- a/python/gui/templates/predistortion.html +++ b/python/gui/templates/predistortion.html @@ -47,8 +47,17 @@
AM/AM and AM/PM Model
- - +
+
+
+

Model data:

+
+
+ 

+              

+            

+          

+          
         

       

 
-- 
cgit v1.2.3


From 75ba4f064a65ebad77d130f160b9469418e49c9f Mon Sep 17 00:00:00 2001
From: "Matthias P. Braendli" 
Date: Wed, 9 Jan 2019 12:21:21 +0100
Subject: GUI: Add ability to restore previous DPD settings

---
 python/dpd/Adapt.py                       |  15 ++--
 python/dpd/Model_Poly.py                  |   5 ++
 python/dpdce.py                           | 114 ++++++++++++++++++++++--------
 python/gui/api.py                         |  18 +++--
 python/gui/static/js/odr-predistortion.js |  98 ++++++++++---------------
 python/gui/templates/predistortion.html   |  23 +++++-
 6 files changed, 169 insertions(+), 104 deletions(-)

(limited to 'python/dpd/Model_Poly.py')

diff --git a/python/dpd/Adapt.py b/python/dpd/Adapt.py
index 9c2c2b6..8023a53 100644
--- a/python/dpd/Adapt.py
+++ b/python/dpd/Adapt.py
@@ -152,7 +152,7 @@ class Adapt:
             _write_lut_file(scalefactor, lut, self._coef_path)
         else:
             raise ValueError("Unknown predistorter '{}'".format(dpddata[0]))
-        self._mod_rc.set_param_value("memlesspoly", "coefffile", self._coef_path)
+        self._mod_rc.set_param_value("memlesspoly", "coeffile", self._coef_path)
 
     def dump(self, path: str) -> None:
         """Backup current settings to a file"""
@@ -161,26 +161,31 @@ class Adapt:
             "txgain": self.get_txgain(),
             "rxgain": self.get_rxgain(),
             "digital_gain": self.get_digital_gain(),
-            "predistorter": self.get_predistorter()
+            "dpddata": self.get_predistorter()
         }
 
         with open(path, "wb") as f:
             pickle.dump(d, f)
 
-    def load(self, path: str) -> None:
+    def restore(self, path: str):
         """Restore settings from a file"""
         with open(path, "rb") as f:
             d = pickle.load(f)
 
             self.set_txgain(0)
+
+            # If any of the following fail, we will be running
+            # with the safe value of txgain=0
             self.set_digital_gain(d["digital_gain"])
             self.set_rxgain(d["rxgain"])
-            self.set_predistorter(d["predistorter"])
+            self.set_predistorter(d["dpddata"])
             self.set_txgain(d["txgain"])
 
+            return d
+
 # The MIT License (MIT)
 #
-# Copyright (c) 2018 Matthias P. Braendli
+# Copyright (c) 2019 Matthias P. Braendli
 # Copyright (c) 2017 Andreas Steger
 #
 # Permission is hereby granted, free of charge, to any person obtaining a copy
diff --git a/python/dpd/Model_Poly.py b/python/dpd/Model_Poly.py
index 7ab6aa1..ef3fed3 100644
--- a/python/dpd/Model_Poly.py
+++ b/python/dpd/Model_Poly.py
@@ -125,6 +125,11 @@ class Poly:
     def get_dpd_data(self):
         return "poly", self.coefs_am, self.coefs_pm
 
+    def set_dpd_data(self, dpddata):
+        if dpddata[0] != "poly" or len(dpddata) != 3:
+            raise ValueError("dpddata is not of 'poly' format")
+        _, self.coefs_am, self.coefs_pm = dpddata
+
     def _am_calc_line(self, coefs, min_amp, max_amp):
         rx_range = np.linspace(min_amp, max_amp)
         tx_est = np.sum(self._am_poly(rx_range) * coefs, axis=1)
diff --git a/python/dpdce.py b/python/dpdce.py
index 6c373fd..27c5253 100755
--- a/python/dpdce.py
+++ b/python/dpdce.py
@@ -87,6 +87,7 @@ import numpy as np
 import traceback
 import os.path
 import glob
+import re
 from threading import Thread, Lock
 from queue import Queue
 from dpd.Model import Poly
@@ -134,19 +135,14 @@ if cli_args.reset:
 cmd_socket = yamlrpc.Socket(bind_port=control_port)
 
 # The following is accessed by both threads and need to be locked
-settings = {
-        'rx_gain': rx_gain,
-        'tx_gain': tx_gain,
-        'digital_gain': digital_gain,
-        'dpddata': dpddata,
-        }
 internal_data = {
         'n_runs': 0,
         }
 results = {
+        'adapt_dumps': [],
         'statplot': None,
         'modelplot': None,
-        'modeldata': "",
+        'modeldata': repr(dpddata),
         'tx_median': 0,
         'rx_median': 0,
         'state': 'Idle',
@@ -156,6 +152,17 @@ results = {
 lock = Lock()
 command_queue = Queue(maxsize=1)
 
+# Fill list of adapt dumps so that user can choose a previous
+# setting across restarts.
+results['adapt_dumps'].append("defaults")
+
+adapt_dump_files = glob.glob(os.path.join(plot_path, "adapt_*.pkl"))
+re_adaptfile = re.compile(r"adapt_(.*)\.pkl")
+for f in adapt_dump_files:
+    match = re_adaptfile.search(f)
+    if match:
+        results['adapt_dumps'].append(match.group(1))
+
 # Automatic Gain Control for the RX gain
 agc = Agc(meas, adapt, c)
 
@@ -171,8 +178,8 @@ def clear_pngs(results):
 
 def engine_worker():
     extStat = None
-    try:
-        while True:
+    while True:
+        try:
             cmd = command_queue.get()
 
             if cmd == "quit":
@@ -184,7 +191,7 @@ def engine_worker():
                     clear_pngs(results)
 
                 summary = []
-                N_ITER = 5
+                N_ITER = 3
                 for i in range(N_ITER):
                     agc_success, agc_summary = agc.run()
                     summary += ["Iteration {}:".format(i)] + agc_summary.split("\n")
@@ -199,8 +206,6 @@ def engine_worker():
                 txframe_aligned, tx_ts, rxframe_aligned, rx_ts, rx_median, tx_median = meas.get_samples()
 
                 with lock:
-                    settings['rx_gain'] = adapt.get_rxgain()
-                    settings['digital_gain'] = adapt.get_digital_gain()
                     results['tx_median'] = float(tx_median)
                     results['rx_median'] = float(rx_median)
                     results['state'] = 'Idle'
@@ -233,9 +238,6 @@ def engine_worker():
 
                     with lock:
                         results['stateprogress'] += 5
-                        results['summary'] = ["Captured {} samples".format(len(txframe_aligned)),
-                            "TX/RX median: {} / {}".format(tx_median, rx_median),
-                            extStat.get_bin_info()]
 
                     # Extract usable data from measurement
                     tx, rx, phase_diff, n_per_bin = extStat.extract(txframe_aligned, rxframe_aligned)
@@ -248,8 +250,11 @@ def engine_worker():
                     with lock:
                         results['statplot'] = "dpd/" + plot_file
                         results['stateprogress'] += 5
-                        results['summary'] += ["Extracted Statistics: TX median={} RX median={}".format(tx_median, rx_median),
-                                "Runs: {}/{}".format(extStat.n_meas, n_meas)]
+                        results['summary'] = ["Captured {} samples".format(len(txframe_aligned)),
+                            "TX/RX median: {} / {}".format(tx_median, rx_median),
+                            extStat.get_bin_info(),
+                            "Extracted Statistics: TX median={} RX median={}".format(tx_median, rx_median),
+                            "Runs: {}/{}".format(extStat.n_meas, n_meas)]
                     if extStat.n_meas >= n_meas:
                         break
 
@@ -303,7 +308,7 @@ def engine_worker():
                     iteration = internal_data['n_runs']
                     internal_data['n_runs'] += 1
 
-                answer = adapt.set_predistorter(dpddata)
+                adapt.set_predistorter(dpddata)
 
                 time.sleep(2)
 
@@ -314,6 +319,9 @@ def engine_worker():
                 dump_file = "adapt_{}.pkl".format(utctime.strftime("%s"))
                 adapt.dump(os.path.join(plot_path, dump_file))
 
+                with lock:
+                    results['adapt_dumps'].append(utctime.strftime("%s"))
+
                 # Collect logging data
                 off = symbol_align.calc_offset(txframe_aligned)
                 tx_mer = mer.calc_mer(txframe_aligned[off:off + c.T_U], debug_name='TX')
@@ -327,7 +335,7 @@ def engine_worker():
 
                 lr = Heuristics.get_learning_rate(iteration)
 
-                summary = [f"Set predistorter: {answer}",
+                summary = [f"Set predistorter:",
                         f"Signal measurements after iteration {iteration} with learning rate {lr}",
                         f"TX MER {tx_mer}, RX MER {rx_mer}",
                         "Shoulders: TX {!r}, RX {!r}".format(tx_shoulder_tuple, rx_shoulder_tuple),
@@ -338,10 +346,59 @@ def engine_worker():
                     results['state'] = 'Update Predistorter'
                     results['stateprogress'] = 100
                     results['summary'] = ["Signal measurements after predistortion update"] + summary
-    finally:
-        with lock:
-            results['state'] = 'Terminated'
-            results['stateprogress'] = 0
+            elif cmd.startswith("restore_dump-"):
+                _, _, dump_id = cmd.partition("-")
+                if dump_id == "defaults":
+                    model.reset_coefs()
+                    dpddata = model.get_dpd_data()
+                    adapt.set_predistorter(dpddata)
+
+                    tx_gain = adapt.get_txgain()
+                    rx_gain = adapt.get_rxgain()
+                    digital_gain = adapt.get_digital_gain()
+                    with lock:
+                        results['state'] = 'Idle'
+                        results['stateprogress'] = 100
+                        results['summary'] = [f"Restored DPD defaults",
+                            f"Running with digital gain {digital_gain}, TX gain {tx_gain} and RX gain {rx_gain}"]
+                        results['modeldata'] = repr(dpddata)
+                else:
+                    dump_file = os.path.join(plot_path, f"adapt_{dump_id}.pkl")
+                    try:
+                        d = adapt.restore(dump_file)
+                        logging.info(f"Restore: {d}")
+                        model.set_dpd_data(d['dpddata'])
+                        with lock:
+                            results['state'] = 'Idle'
+                            results['stateprogress'] = 100
+                            results['summary'] = [f"Restored DPD settings from dumpfile {dump_id}",
+                                f"Running with digital gain {d['digital_gain']}, TX gain {d['txgain']} and RX gain {d['rxgain']}"]
+                            results['modeldata'] = repr(d["dpddata"])
+                    except:
+                        e = traceback.format_exc()
+                        with lock:
+                            results['state'] = 'Idle'
+                            results['stateprogress'] = 100
+                            results['summary'] = [f"Failed to restore DPD settings from dumpfile {dump_id}",
+                                    f"Error: {e}"]
+        except:
+            e = traceback.format_exc()
+            logging.error(e)
+            with lock:
+                results['summary'] = [f"Exception:"] + e.split("\n")
+                results['state'] = 'Autorestart pending'
+                results['stateprogress'] = 0
+
+            for i in range(5):
+                time.sleep(2)
+                with lock:
+                    results['stateprogress'] += 20
+            time.sleep(2)
+            with lock:
+                dt = datetime.datetime.utcnow().isoformat()
+                results['summary'] = [f"DPD engine auto-restarted at {dt} UTC", f"After exception {e}"]
+                results['state'] = 'Idle'
+                results['stateprogress'] = 0
 
 
 engine = Thread(target=engine_worker)
@@ -367,13 +424,10 @@ try:
             logging.info('YAML-RPC request : {}'.format(method))
             command_queue.put(method)
             cmd_socket.send_success_response(addr, msg_id, None)
-        elif method == 'set_setting':
-            logging.info('YAML-RPC request : {} -> {}'.format(method, params))
-            # params == {'setting': ..., 'value': ...}
+        elif method == 'restore_dump':
+            logging.info('YAML-RPC restore dump {}'.format(params['dump_id']))
+            command_queue.put(f"restore_dump-{params['dump_id']}")
             cmd_socket.send_success_response(addr, msg_id, None)
-        elif method == 'get_settings':
-            with lock:
-                cmd_socket.send_success_response(addr, msg_id, settings)
         elif method == 'get_results':
             with lock:
                 cmd_socket.send_success_response(addr, msg_id, results)
@@ -511,7 +565,7 @@ while i < num_iter:
 # The MIT License (MIT)
 #
 # Copyright (c) 2017 Andreas Steger
-# Copyright (c) 2018 Matthias P. Braendli
+# Copyright (c) 2019 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
diff --git a/python/gui/api.py b/python/gui/api.py
index 42c89c9..c0effde 100755
--- a/python/gui/api.py
+++ b/python/gui/api.py
@@ -1,6 +1,6 @@
 # -*- coding: utf-8 -*-
 #
-#   Copyright (C) 2018
+#   Copyright (C) 2019
 #   Matthias P. Braendli, matthias.braendli@mpb.li
 #
 #    http://www.opendigitalradio.org
@@ -125,12 +125,20 @@ class API:
 
     @cherrypy.expose
     @cherrypy.tools.json_out()
-    def dpd_settings(self, setting: str, value: str, **kwargs):
+    def dpd_restore_dump(self, **kwargs):
         if cherrypy.request.method == 'POST':
-            data = {'setting': setting, 'value': value}
-            return self._wrap_dpd("set_setting", data)
+            cl = cherrypy.request.headers['Content-Length']
+            rawbody = cherrypy.request.body.read(int(cl))
+            params = json.loads(rawbody.decode())
+            if 'dump_id' in params:
+                data = {'dump_id': params['dump_id']}
+                return self._wrap_dpd("restore_dump", data)
+            else:
+                cherrypy.response.status = 400
+                return send_error("Missing dump_id")
         else:
-            return self._wrap_dpd("get_settings")
+            cherrypy.response.status = 400
+            return send_error("POST only")
 
     @cherrypy.expose
     @cherrypy.tools.json_out()
diff --git a/python/gui/static/js/odr-predistortion.js b/python/gui/static/js/odr-predistortion.js
index b5f29ea..4dae068 100644
--- a/python/gui/static/js/odr-predistortion.js
+++ b/python/gui/static/js/odr-predistortion.js
@@ -1,4 +1,4 @@
-//   Copyright (C) 2018
+//   Copyright (C) 2019
 //   Matthias P. Braendli, matthias.braendli@mpb.li
 //
 //    http://www.opendigitalradio.org
@@ -18,6 +18,8 @@
 //   You should have received a copy of the GNU General Public License
 //   along with ODR-DabMod.  If not, see .
 
+var adapt_dumps = [];
+
 function resultrefresh() {
     var jqxhr = doApiRequestGET("/api/dpd_results", function(data) {
         var summary = "";
@@ -51,6 +53,8 @@ function resultrefresh() {
         else {
             $('#dpdmodelplot').attr('src', "");
         }
+
+        adapt_dumps = data['adapt_dumps'];
     });
 
     jqxhr.always(function() {
@@ -58,6 +62,30 @@ function resultrefresh() {
     });
 }
 
+function adaptdumpsrefresh() {
+    $('#dpdadaptdumps').html("");
+
+    $.each(adapt_dumps, function(i, item) {
+        console.log(item);
+
+        if (isNaN(+item)) {
+            $('#dpdadaptdumps').append($('

 
@@ -97,7 +114,7 @@