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-rwxr-xr-xdpd/main.py14
-rw-r--r--dpd/src/MER.py10
-rw-r--r--dpd/src/Measure_Shoulders.py2
-rw-r--r--dpd/src/Model_Poly.py5
-rw-r--r--dpd/src/const.py8
5 files changed, 24 insertions, 15 deletions
diff --git a/dpd/main.py b/dpd/main.py
index 871a404..ddbbfc4 100755
--- a/dpd/main.py
+++ b/dpd/main.py
@@ -109,17 +109,17 @@ txgain = cli_args.txgain
c = src.const.const(samplerate, target_median)
SA = src.Symbol_align.Symbol_align(c)
MER = src.MER.MER(c)
-MS = src.Measure_Shoulders.Measure_Shoulder(c, plot=True)
+MS = src.Measure_Shoulders.Measure_Shoulder(c)
meas = Measure.Measure(samplerate, port, num_req)
-extStat = ExtractStatistic.ExtractStatistic(c, plot=True)
+extStat = ExtractStatistic.ExtractStatistic(c)
adapt = Adapt.Adapt(port_rc, coef_path)
dpddata = adapt.get_predistorter()
if cli_args.lut:
- model = Model.Lut(c, plot=True)
+ model = Model.Lut(c)
else:
- model = Model.Poly(c, plot=True)
+ model = Model.Poly(c)
adapt.set_predistorter(model.get_dpd_data())
adapt.set_digital_gain(digital_gain)
@@ -190,7 +190,7 @@ while i < num_iter:
elif state == "model":
dpddata = model.train(tx, rx, phase_diff)
dpddata = model.get_dpd_data()
- extStat = ExtractStatistic.ExtractStatistic(c, plot=True)
+ extStat = ExtractStatistic.ExtractStatistic(c)
state = "adapt"
# Adapt
@@ -205,8 +205,8 @@ while i < num_iter:
path = adapt.dump()
off = SA.calc_offset(txframe_aligned)
- tx_mer = MER.calc_mer(txframe_aligned[off:off+c.T_U], debug=True, debug_name="TX")
- rx_mer = MER.calc_mer(rxframe_aligned[off:off+c.T_U], debug=True, debug_name="RX")
+ 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()
diff --git a/dpd/src/MER.py b/dpd/src/MER.py
index 7aea38f..393e55c 100644
--- a/dpd/src/MER.py
+++ b/dpd/src/MER.py
@@ -23,6 +23,8 @@ class MER:
def __init__(self, c):
self.c = c
+ self.plot = c.MER_plot
+
def _calc_spectrum(self, tx):
fft = np.fft.fftshift(np.fft.fft(tx))
return np.delete(fft[self.c.FFT_start:self.c.FFT_end],
@@ -69,13 +71,13 @@ class MER:
return x_mean, y_mean, U_RMS, U_ERR, MER
- def calc_mer(self, tx, debug=False, debug_name=""):
+ def calc_mer(self, tx, debug_name=""):
assert tx.shape[0] == self.c.T_U,\
"Wrong input length"
spectrum = self._calc_spectrum(tx)
- if debug:
+ if self.plot:
dt = datetime.datetime.now().isoformat()
fig_path = logging_path + "/" + dt + "_MER" + debug_name + ".svg"
@@ -91,7 +93,7 @@ class MER:
x_err = U_ERR * np.sin(tau) + x_mean
y_err = U_ERR * np.cos(tau) + y_mean
- if debug:
+ if self.plot:
ax = plt.subplot(221 + i)
ax.scatter(x, y, s=0.2, color='black')
ax.plot(x_mean, y_mean, 'p', color='red')
@@ -102,7 +104,7 @@ class MER:
ylim = ax.get_ylim()
ax.set_ylim(ylim[0] - (ylim[1] - ylim[0]) * 0.1, ylim[1])
- if debug:
+ if self.plot:
plt.tight_layout()
plt.savefig(fig_path)
plt.show()
diff --git a/dpd/src/Measure_Shoulders.py b/dpd/src/Measure_Shoulders.py
index 1417613..acb05b4 100644
--- a/dpd/src/Measure_Shoulders.py
+++ b/dpd/src/Measure_Shoulders.py
@@ -69,7 +69,7 @@ class Measure_Shoulder:
c,
plot=False):
self.c = c
- self.plot = plot
+ self.plot = c.MS_plot
def _plot(self, signal):
dt = datetime.datetime.now().isoformat()
diff --git a/dpd/src/Model_Poly.py b/dpd/src/Model_Poly.py
index f6c024c..e799f1e 100644
--- a/dpd/src/Model_Poly.py
+++ b/dpd/src/Model_Poly.py
@@ -44,8 +44,7 @@ class Poly:
def __init__(self,
c,
learning_rate_am=1.0,
- learning_rate_pm=1.0,
- plot=False):
+ learning_rate_pm=1.0):
self.c = c
self.learning_rate_am = learning_rate_am
@@ -56,7 +55,7 @@ class Poly:
self.model_am = Model_AM.Model_AM(c, plot=True)
self.model_pm = Model_PM.Model_PM(c, plot=True)
- self.plot = plot
+ self.plot = c.MDL_plot
def reset_coefs(self):
self.coefs_am = np.zeros(5, dtype=np.float32)
diff --git a/dpd/src/const.py b/dpd/src/const.py
index cbef8af..d95d0bf 100644
--- a/dpd/src/const.py
+++ b/dpd/src/const.py
@@ -38,6 +38,7 @@ class const:
self.phase_offset_per_sample = 1. / sample_rate * 2 * np.pi * 1000
# Constants for ExtractStatistic
+ self.ES_plot = True
self.ES_start = 0.0
self.ES_end = 1.0
self.ES_n_bins = 64
@@ -53,10 +54,17 @@ class const:
self.RAGC_min_rxgain = 25
self.RAGC_rx_median_target = self.TAGC_tx_median_target
+ # Constants for Model
+ self.MDL_plot = True
+
+ # Constants for MER
+ self.MER_plot = True
+
# Constants for Model_PM
self.MPM_tx_min = 0.1
# Constants for Measure_Shoulder
+ self.MS_plot = True
assert sample_rate==8192000
meas_offset = 976 # Offset from center frequency to measure shoulder [kHz]
meas_width = 100 # Size of frequency delta to measure shoulder [kHz]