Cleanup

7 files changed, 42 insertions, 39 deletions

diff --git a/dpd/environment.yml b/dpd/environment.yml
index 2d7f260..5c19258 100644
--- a/dpd/environment.yml
+++ b/dpd/environment.yml
@@ -84,7 +84,6 @@ dependencies:
 - readline=6.2=2
 - requests=2.14.2=py27_0
 - scandir=1.5=py27_0
-- scikit-learn=0.18.1=np112py27_1
 - scipy=0.19.0=np112py27_0
 - setuptools=27.2.0=py27_0
 - simplegeneric=0.8.1=py27_1
diff --git a/dpd/main.py b/dpd/main.py
index 3424572..d71fd2d 100755
--- a/dpd/main.py
+++ b/dpd/main.py
@@ -123,7 +123,6 @@ MS = Measure_Shoulders(c)
 meas = Measure.Measure(samplerate, port, num_req)
 extStat = ExtractStatistic.ExtractStatistic(c)
 adapt = Adapt.Adapt(port_rc, coef_path)
-dpddata = adapt.get_predistorter()
 
 if cli_args.lut:
     model = Model.Lut(c)
@@ -181,41 +180,43 @@ i = 0
 while i < num_iter:
     try:
         # Measure
-        if state == "measure":
+        if state == 'measure':
+            # Get Samples and check gain
             txframe_aligned, tx_ts, rxframe_aligned, rx_ts, rx_median = meas.get_samples()
-            rxframe_aligned.tofile("/tmp/rxframe_aligned.np")
-            txframe_aligned.tofile("/tmp/txframe_aligned.np")
             if tx_agc.adapt_if_necessary(txframe_aligned):
                 continue
 
+            # Extract usable data from measurement
             tx, rx, phase_diff, n_per_bin = extStat.extract(txframe_aligned, rxframe_aligned)
 
             if extStat.n_meas >= c.n_meas:
-                state = "model"
+                state = 'model'
             else:
-                state = "measure"
+                state = 'measure'
 
         # Model
-        elif state == "model":
-            dpddata = model.train(tx, rx, phase_diff)
+        elif state == 'model':
+            # Calculate new model parameters and delete old measurements
+            model.train(tx, rx, phase_diff)
             dpddata = model.get_dpd_data()
             extStat = ExtractStatistic.ExtractStatistic(c)
-            state = "adapt"
+            state = 'adapt'
 
         # Adapt
-        elif state == "adapt":
+        elif state == 'adapt':
             adapt.set_predistorter(dpddata)
-            state = "report"
+            state = 'report'
 
         # Report
-        elif state == "report":
+        elif state == 'report':
             try:
-                i += 1
-                path = adapt.dump()
+                # Store all settings for pre-distortion, tx and rx
+                adapt.dump()
 
+                # Collect logging data
                 off = SA.calc_offset(txframe_aligned)
-                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")
+                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()
@@ -224,36 +225,35 @@ while i < num_iter:
                 rx_shoulder_tuple = MS.average_shoulders(rxframe_aligned) if c.MS_enable else None
                 tx_shoulder_tuple = MS.average_shoulders(txframe_aligned) if c.MS_enable else None
 
+                # Generic logging
                 logging.info(list((name, eval(name)) for name in
                                   ['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":
+
+                # Model specific logging
+                if dpddata[0] == 'poly':
                     coefs_am = dpddata[1]
                     coefs_pm = dpddata[2]
-                    logging.info("It {}: coefs_am {}".
+                    logging.info('It {}: coefs_am {}'.
                                  format(i, coefs_am))
-                    logging.info("It {}: coefs_pm {}".
+                    logging.info('It {}: coefs_pm {}'.
                                  format(i, coefs_pm))
-                if dpddata[0] == "lut":
+                elif dpddata[0] == 'lut':
                     scalefactor = dpddata[1]
                     lut = dpddata[2]
-                    logging.info("It {}: LUT scalefactor {}, LUT {}".
+                    logging.info('It {}: LUT scalefactor {}, LUT {}'.
                                  format(i, scalefactor, lut))
-                if tx_gain < 89:
-                    adapt.set_txgain(tx_gain)
-                else:
-                    break
-                state = "measure"
             except:
-                logging.warning("Iteration {}: Report failed.".format(i))
-                logging.warning(traceback.format_exc())
-                state = "measure"
+                logging.error('Iteration {}: Report failed.'.format(i))
+                logging.error(traceback.format_exc())
+            i += 1
+            state = 'measure'
 
     except Exception as e:
-        logging.warning("Iteration {} failed.".format(i))
-        logging.warning(traceback.format_exc())
+        logging.error('Iteration {} failed.'.format(i))
+        logging.error(traceback.format_exc())
 
 # The MIT License (MIT)
 #
diff --git a/dpd/src/Adapt.py b/dpd/src/Adapt.py
index 84b65f6..b17f059 100644
--- a/dpd/src/Adapt.py
+++ b/dpd/src/Adapt.py
@@ -137,7 +137,8 @@ class Adapt:
 
     def get_predistorter(self):
         """Load the coefficients from the file in the format given in the README,
-        return ("poly", [AM coef], [PM coef]) or ("lut", scalefactor, [LUT entries])"""
+        return ("poly", [AM coef], [PM coef]) or ("lut", scalefactor, [LUT entries])
+        """
         f = open(self.coef_path, 'r')
         lines = f.readlines()
         predistorter_format = int(lines[0])
@@ -155,7 +156,7 @@ class Adapt:
                 else:
                     raise ValueError(
                         "Incorrect coef file format: too many coefficients in {}, should be {}, coefs are {}"
-                            .format(path, n_coefs, coefs))
+                            .format(self.coef_path, n_coefs, coefs))
                 i += 1
             f.close()
             return ("poly", coefs_am_out, coefs_pm_out)
@@ -206,8 +207,7 @@ class Adapt:
         self.send_receive("set memlesspoly coeffile {}".format(self.coef_path))
 
     def dump(self, path=None):
-        if path is None:
-            dt = datetime.datetime.now().isoformat()
+        dt = datetime.datetime.now().isoformat()
         path = logging_path + "/" + dt + "_adapt.pkl"
         d = {
             "txgain":self.get_txgain(),
diff --git a/dpd/src/Const.py b/dpd/src/Const.py
index 2504c1e..2f9e151 100644
--- a/dpd/src/Const.py
+++ b/dpd/src/Const.py
@@ -10,6 +10,8 @@ class Const:
         self.sample_rate = sample_rate
         self.n_meas = n_meas
 
+        self.tx_gain_max = 89
+
         # Time domain
         self.T_F = sample_rate / 2048000 * 196608  # Transmission frame duration
         self.T_NULL = sample_rate / 2048000 * 2656  # Null symbol duration
diff --git a/dpd/src/Model_AM.py b/dpd/src/Model_AM.py
index 2704255..4b88e08 100644
--- a/dpd/src/Model_AM.py
+++ b/dpd/src/Model_AM.py
@@ -13,7 +13,6 @@ logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFil
 
 import numpy as np
 import matplotlib.pyplot as plt
-from sklearn import linear_model
 
 
 def check_input_get_next_coefs(tx_dpd, rx_received):
diff --git a/dpd/src/Model_PM.py b/dpd/src/Model_PM.py
index eab5ec5..75fb055 100644
--- a/dpd/src/Model_PM.py
+++ b/dpd/src/Model_PM.py
@@ -13,7 +13,6 @@ logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFil
 
 import numpy as np
 import matplotlib.pyplot as plt
-from sklearn import linear_model
 
 
 def check_input_get_next_coefs(tx_dpd, phase_diff):
diff --git a/dpd/src/Model_Poly.py b/dpd/src/Model_Poly.py
index 6a74bea..78bab91 100644
--- a/dpd/src/Model_Poly.py
+++ b/dpd/src/Model_Poly.py
@@ -62,7 +62,11 @@ class Poly:
         return self.coefs_am, self.coefs_pm
 
     def train(self, tx_abs, rx_abs, phase_diff):
-        # type: (np.ndarray, np.ndarray, np.ndarray) -> (str, np.ndarray, np.ndarray)
+        """
+        :type tx_abs: np.ndarray
+        :type rx_abs: np.ndarray
+        :type phase_diff: np.ndarray
+        """
         _check_input_get_next_coefs(tx_abs, rx_abs, phase_diff)
 
         coefs_am_new = self.model_am.get_next_coefs(tx_abs, rx_abs, self.coefs_am)