Move constants to const.py

4 files changed, 28 insertions, 26 deletions

diff --git a/dpd/main.py b/dpd/main.py
index 923a7f8..8de0f86 100755
--- a/dpd/main.py
+++ b/dpd/main.py
@@ -145,10 +145,10 @@ elif dpddata[0] == "lut":
 else:
     logging.error("Unknown dpd data format {}".format(dpddata[0]))
 
-tx_agc = TX_Agc.TX_Agc(adapt)
+tx_agc = TX_Agc.TX_Agc(adapt, c)
 
 # Automatic Gain Control
-agc = Agc.Agc(meas, adapt)
+agc = Agc.Agc(meas, adapt, c)
 agc.run()
 
 state = "measure"
@@ -165,7 +165,7 @@ while i < num_iter:
 
             tx, rx, phase_diff, n_per_bin = extStat.extract(txframe_aligned, rxframe_aligned)
 
-            if extStat.n_meas >= 15:
+            if extStat.n_meas >= 200:
                 state = "model"
             else:
                 state = "measure"
@@ -181,11 +181,11 @@ while i < num_iter:
         elif state == "adapt":
             adapt.set_predistorter(dpddata)
             state = "report"
-            i += 1
 
         # Report
         elif state == "report":
             try:
+                i += 1
                 path = adapt.dump()
 
                 off = SA.calc_offset(txframe_aligned)
@@ -196,12 +196,12 @@ while i < num_iter:
                 rx_gain = adapt.get_rxgain()
                 digital_gain = adapt.get_digital_gain()
                 tx_median = np.median(np.abs(txframe_aligned))
-                rx_shoulders = MS.average_shoulders(rxframe_aligned)
-                tx_shoulders = MS.average_shoulders(txframe_aligned)
+                rx_shoulder_tuple = MS.average_shoulders(rxframe_aligned)
+                tx_shoulder_tuple = MS.average_shoulders(txframe_aligned)
 
                 logging.info(list((name, eval(name)) for name in
-                                  ['i', 'tx_mer', 'tx_shoulders', 'rx_mer',
-                                   'rx_shoulders', 'mse', 'tx_gain',
+                                  ['i', 'tx_mer', 'tx_shoulder_tuple', 'rx_mer',
+                                   'rx_shoulder_tuple', 'mse', 'tx_gain',
                                    'digital_gain', 'rx_gain', 'rx_median',
                                    'tx_median']))
                 if dpddata[0] == "poly":
@@ -216,11 +216,6 @@ while i < num_iter:
                     lut = dpddata[2]
                     logging.info("It {}: LUT scalefactor {}, LUT {}".
                                  format(i, scalefactor, lut))
-
-                model.reset_coefs()
-                dpd_data = model.get_dpd_data()
-                adapt.set_predistorter(dpd_data)
-                tx_gain = tx_gain - 1
                 if tx_gain < 89:
                     adapt.set_txgain(tx_gain)
                 else:
diff --git a/dpd/src/Agc.py b/dpd/src/Agc.py
index b83c91e..670fbbb 100644
--- a/dpd/src/Agc.py
+++ b/dpd/src/Agc.py
@@ -35,14 +35,14 @@ class Agc:
     received signal fulfills our desired property, of having 
     all amplitudes properly quantized."""
 
-    def __init__(self, measure, adapt, min_rxgain=25, peak_to_median=20):
+    def __init__(self, measure, adapt, c):
         assert isinstance(measure, Measure.Measure)
         assert isinstance(adapt, Adapt.Adapt)
         self.measure = measure
         self.adapt = adapt
-        self.min_rxgain = min_rxgain
+        self.min_rxgain = c.RAGC_min_rxgain
         self.rxgain = self.min_rxgain
-        self.peak_to_median = peak_to_median
+        self.peak_to_median = 1./c.RAGC_rx_median_target
 
     def run(self):
         self.adapt.set_rxgain(self.rxgain)
diff --git a/dpd/src/TX_Agc.py b/dpd/src/TX_Agc.py
index affc42f..b9226b2 100644
--- a/dpd/src/TX_Agc.py
+++ b/dpd/src/TX_Agc.py
@@ -24,10 +24,7 @@ import src.Adapt as Adapt
 class TX_Agc:
     def __init__(self,
                  adapt,
-                 max_txgain=89,
-                 tx_median_target=0.16,
-                 tx_median_threshold_max=0.18,
-                 tx_median_threshold_min=0.14):
+                 c):
         """
         In order to avoid digital clipping, this class increases the
         TX gain and reduces the digital gain. Digital clipping happens
@@ -47,16 +44,16 @@ class TX_Agc:
         :param tx_median_target: The digital gain is reduced in a way that
                 the median TX value is expected to be lower than this value.
         """
+
+
         assert isinstance(adapt, Adapt.Adapt)
         self.adapt = adapt
-        self.max_txgain = max_txgain
+        self.max_txgain = c.TAGC_max_txgain
         self.txgain = self.max_txgain
 
-        assert tx_median_threshold_max > tx_median_target,\
-            "The tolerated tx_median has to be larger then the goal tx_median"
-        self.tx_median_threshold_tolerate_max = tx_median_threshold_max
-        self.tx_median_threshold_tolerate_min = tx_median_threshold_min
-        self.tx_median_target = tx_median_target
+        self.tx_median_threshold_tolerate_max = c.TAGC_tx_median_max
+        self.tx_median_threshold_tolerate_min = c.TAGC_tx_median_min
+        self.tx_median_target = c.TAGC_tx_median_target
 
     def adapt_if_necessary(self, tx):
         tx_median = np.median(np.abs(tx))
diff --git a/dpd/src/const.py b/dpd/src/const.py
index c7f4b7c..63a095b 100644
--- a/dpd/src/const.py
+++ b/dpd/src/const.py
@@ -43,6 +43,16 @@ class const:
         self.ES_n_bins = 64
         self.ES_n_per_bin = 128
 
+        # Constants for TX_Agc
+        self.TAGC_max_txgain = 89
+        self.TAGC_tx_median_target = 0.1
+        self.TAGC_tx_median_max = self.TAGC_tx_median_target*1.4
+        self.TAGC_tx_median_min = self.TAGC_tx_median_target/1.4
+
+        # Constants for Agc
+        self.RAGC_min_rxgain = 25
+        self.RAGC_rx_median_target = self.TAGC_tx_median_target
+
         # Constants for Model_PM
         self.MPM_tx_min = 0.1