Merge LUT into 'next_memless'

1 files changed, 70 insertions, 30 deletions

diff --git a/dpd/main.py b/dpd/main.py
index de3453e..084ccd5 100755
--- a/dpd/main.py
+++ b/dpd/main.py
@@ -42,6 +42,7 @@ import numpy as np
 import traceback
 import src.Measure as Measure
 import src.Model as Model
+import src.ExtractStatistic as ExtractStatistic
 import src.Adapt as Adapt
 import src.Agc as Agc
 import src.TX_Agc as TX_Agc
@@ -52,19 +53,19 @@ import argparse
 
 parser = argparse.ArgumentParser(
     description="DPD Computation Engine for ODR-DabMod")
-parser.add_argument('--port', default='50055',
+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',
+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',
+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=71,
+parser.add_argument('--txgain', default=73,
                     help='TX Gain',
                     required=False,
                     type=int)
@@ -76,10 +77,10 @@ parser.add_argument('--digital_gain', default=1,
                     help='Digital Gain',
                     required=False,
                     type=float)
-parser.add_argument('--samps', default='81920',
+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='1',
+parser.add_argument('-i', '--iterations', default=1, type=int,
                     help='Number of iterations to run',
                     required=False)
 parser.add_argument('-L', '--lut',
@@ -88,29 +89,29 @@ parser.add_argument('-L', '--lut',
 
 cli_args = parser.parse_args()
 
-port = int(cli_args.port)
-port_rc = int(cli_args.rc_port)
+port = cli_args.port
+port_rc = cli_args.rc_port
 coef_path = cli_args.coefs
 digital_gain = cli_args.digital_gain
 txgain = cli_args.txgain
 rxgain = cli_args.rxgain
-num_req = int(cli_args.samps)
-samplerate = int(cli_args.samplerate)
-num_iter = int(cli_args.iterations)
+num_req = cli_args.samps
+samplerate = cli_args.samplerate
+num_iter = cli_args.iterations
 
 SA = src.Symbol_align.Symbol_align(samplerate)
 MER = src.MER.MER(samplerate)
 c = src.const.const(samplerate)
 
 meas = Measure.Measure(samplerate, port, num_req)
-
+extStat = ExtractStatistic.ExtractStatistic(c, plot=True)
 adapt = Adapt.Adapt(port_rc, coef_path)
 dpddata = adapt.get_predistorter()
 
 if cli_args.lut:
-    model = Model.LutModel(c, SA, MER, plot=True)
+    model = Model.Lut(c, plot=True)
 else:
-    model = Model.PolyModel(c, SA, MER, None, None, plot=True)
+    model = Model.Poly(c, plot=True)
 adapt.set_predistorter(model.get_dpd_data())
 adapt.set_digital_gain(digital_gain)
 adapt.set_txgain(txgain)
@@ -120,7 +121,7 @@ tx_gain = adapt.get_txgain()
 rx_gain = adapt.get_rxgain()
 digital_gain = adapt.get_digital_gain()
 
-dpddata = adapt.get_coefs()
+dpddata = adapt.get_predistorter()
 if dpddata[0] == "poly":
     coefs_am = dpddata[1]
     coefs_pm = dpddata[2]
@@ -148,23 +149,62 @@ tx_agc = TX_Agc.TX_Agc(adapt)
 agc = Agc.Agc(meas, adapt)
 agc.run()
 
-for i in range(num_iter):
+state = "measure"
+i = 0
+while i < num_iter:
     try:
-        txframe_aligned, tx_ts, rxframe_aligned, rx_ts, rx_median = meas.get_samples()
-        logging.debug("tx_ts {}, rx_ts {}".format(tx_ts, rx_ts))
-        assert tx_ts - rx_ts < 1e-5, "Time stamps do not match."
-
-        if tx_agc.adapt_if_necessary(txframe_aligned):
-            continue
-
-        model.train(txframe_aligned, rxframe_aligned)
-        adapt.set_predistorter(model.get_dpd_data())
+        # Measure
+        if state == "measure":
+            txframe_aligned, tx_ts, rxframe_aligned, rx_ts, rx_median = meas.get_samples()
+            tx, rx, phase_diff, n_per_bin = extStat.extract(txframe_aligned, rxframe_aligned)
+            n_use = int(len(n_per_bin) * 0.6)
+            tx = tx[:n_use]
+            rx = rx[:n_use]
+            phase_diff = phase_diff[:n_use]
+            if all(c.ES_n_per_bin == np.array(n_per_bin)[0:n_use]):
+                state = "model"
+            else:
+                state = "measure"
+
+        # Model
+        elif state == "model":
+            dpddata = model_poly.get_dpd_data(tx, rx, phase_diff)
+            del extStat
+            extStat = ExtractStatistic.ExtractStatistic(c, plot=True)
+            state = "adapt"
+
+        # Adapt
+        elif state == "adapt":
+            adapt.set_predistorter(dpddata)
+            state = "report"
+            i += 1
+
+        # Report
+        elif state == "report":
+            try:
+                off = SA.calc_offset(txframe_aligned)
+                tx_mer = MER.calc_mer(txframe_aligned[off:off+c.T_U], debug=True)
+                rx_mer = MER.calc_mer(rxframe_aligned[off:off+c.T_U], debug=True)
+                mse = np.mean(np.abs((txframe_aligned - rxframe_aligned)**2))
+
+                if dpddata[0] == "poly":
+                    coefs_am = dpddata[1]
+                    coefs_pm = dpddata[2]
+                    logging.info("It {}: TX_MER {}, RX_MER {}," \
+                                 " MSE {}, coefs_am {}, coefs_pm {}".
+                                 format(i, tx_mer, rx_mer, mse, coefs_am, coefs_pm))
+                if dpddata[0] == "lut":
+                    scalefactor = dpddata[1]
+                    lut = dpddata[2]
+                    logging.info("It {}: TX_MER {}, RX_MER {}," \
+                                 " MSE {}, LUT scalefactor {}, LUT {}".
+                                 format(i, tx_mer, rx_mer, mse, scalefactor, lut))
+                state = "measure"
+            except:
+                logging.warning("Iteration {}: Report failed.".format(i))
+                logging.warning(traceback.format_exc())
+                state = "measure"
 
-        off = SA.calc_offset(txframe_aligned)
-        tx_mer = MER.calc_mer(txframe_aligned[off:off + c.T_U])
-        rx_mer = MER.calc_mer(rxframe_aligned[off:off + c.T_U], debug=True)
-        logging.info("MER with lag in it. {}: TX {}, RX {}".
-                     format(i, tx_mer, rx_mer))
     except Exception as e:
         logging.warning("Iteration {} failed.".format(i))
         logging.warning(traceback.format_exc())