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author | Matthias P. Braendli <matthias.braendli@mpb.li> | 2018-12-22 13:32:34 +0100 |
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committer | Matthias P. Braendli <matthias.braendli@mpb.li> | 2018-12-22 13:32:34 +0100 |
commit | b72f76d4154bb4c8bc356b624627e9d6bc4f7328 (patch) | |
tree | bc52c0f473b7d705f8fca280ea7f33538cd84be9 | |
parent | aa3abebd804129f2eff361a1b4f21d0c04c61cfd (diff) | |
download | dabmod-b72f76d4154bb4c8bc356b624627e9d6bc4f7328.tar.gz dabmod-b72f76d4154bb4c8bc356b624627e9d6bc4f7328.tar.bz2 dabmod-b72f76d4154bb4c8bc356b624627e9d6bc4f7328.zip |
GUI: fix path for adapt step
-rw-r--r-- | python/dpd/Adapt.py | 2 | ||||
-rwxr-xr-x | python/dpdce.py | 6 |
2 files changed, 5 insertions, 3 deletions
diff --git a/python/dpd/Adapt.py b/python/dpd/Adapt.py index 840aee9..8108375 100644 --- a/python/dpd/Adapt.py +++ b/python/dpd/Adapt.py @@ -232,7 +232,7 @@ class Adapt: _write_lut_file(scalefactor, lut, self.coef_path) else: raise ValueError("Unknown predistorter '{}'".format(dpddata[0])) - self.send_receive("set memlesspoly coeffile {}".format(self.coef_path)) + return self.send_receive("set memlesspoly coeffile {}".format(self.coef_path)) def dump(self, path=None): """Backup current settings to a file""" diff --git a/python/dpdce.py b/python/dpdce.py index 90cd436..f855f9c 100755 --- a/python/dpdce.py +++ b/python/dpdce.py @@ -101,6 +101,7 @@ from dpd.MER import MER from dpd.Measure_Shoulders import Measure_Shoulders plot_path = os.path.realpath(plot_directory) +coef_file = os.path.realpath(config['coef_file']) c = GlobalConfig(samplerate, plot_path) symbol_align = Symbol_align(c) @@ -302,7 +303,7 @@ def engine_worker(): iteration = internal_data['n_runs'] internal_data['n_runs'] += 1 - adapt.set_predistorter(dpddata) + answer = adapt.set_predistorter(dpddata) time.sleep(2) @@ -324,7 +325,8 @@ def engine_worker(): lr = Heuristics.get_learning_rate(iteration) - summary = [f"Signal measurements after iteration {iteration} with learning rate {lr}", + summary = [f"Set predistorter: {answer}", + 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), f"Mean-square error: {mse}", |