Add n_bins, n_per_bin, n_meas parameter; Cleanup import

2 files changed, 106 insertions, 13 deletions

diff --git a/dpd/main.py b/dpd/main.py
index ddbbfc4..921afb2 100755
--- a/dpd/main.py
+++ b/dpd/main.py
@@ -12,8 +12,6 @@ predistortion module of ODR-DabMod."""
 
 import datetime
 import os
-import time
-import sys
 import matplotlib
 matplotlib.use('GTKAgg')
 
@@ -46,10 +44,10 @@ import src.ExtractStatistic as ExtractStatistic
 import src.Adapt as Adapt
 import src.Agc as Agc
 import src.TX_Agc as TX_Agc
-import src.Symbol_align
-import src.const
-import src.MER
-import src.Measure_Shoulders
+from src.Symbol_align import Symbol_align
+from src.Const import Const
+from src.MER import MER
+from src.Measure_Shoulders import Measure_Shoulders
 import argparse
 
 parser = argparse.ArgumentParser(
@@ -91,6 +89,13 @@ parser.add_argument('-i', '--iterations', default=1, type=int,
 parser.add_argument('-L', '--lut',
                     help='Use lookup table instead of polynomial predistorter',
                     action="store_true")
+parser.add_argument('--n_bins', default='64', type=int,
+                    required=False)
+parser.add_argument('--n_per_bin', default='128', type=int,
+                    required=False)
+parser.add_argument('--n_meas', default='20', type=int,
+                    help='Number of samples to request from ODR-DabMod',
+                    required=False)
 
 cli_args = parser.parse_args()
 logging.info(cli_args)
@@ -106,10 +111,14 @@ target_median = cli_args.target_median
 rxgain = cli_args.rxgain
 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)
+n_bins = cli_args.n_bins
+n_per_bin = cli_args.n_per_bin
+n_meas = cli_args.n_meas
+
+c = Const(samplerate, target_median, n_bins, n_per_bin, n_meas)
+SA = Symbol_align(c)
+MER = MER(c)
+MS = Measure_Shoulders(c)
 
 meas = Measure.Measure(samplerate, port, num_req)
 extStat = ExtractStatistic.ExtractStatistic(c)
@@ -181,7 +190,7 @@ while i < num_iter:
 
             tx, rx, phase_diff, n_per_bin = extStat.extract(txframe_aligned, rxframe_aligned)
 
-            if extStat.n_meas >= 100:
+            if extStat.n_meas >= c.n_meas:
                 state = "model"
             else:
                 state = "measure"
@@ -212,8 +221,8 @@ while i < num_iter:
                 rx_gain = adapt.get_rxgain()
                 digital_gain = adapt.get_digital_gain()
                 tx_median = np.median(np.abs(txframe_aligned))
-                rx_shoulder_tuple = MS.average_shoulders(rxframe_aligned)
-                tx_shoulder_tuple = MS.average_shoulders(txframe_aligned)
+                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
 
                 logging.info(list((name, eval(name)) for name in
                                   ['i', 'tx_mer', 'tx_shoulder_tuple', 'rx_mer',
diff --git a/dpd/src/Const.py b/dpd/src/Const.py
new file mode 100644
index 0000000..2504c1e
--- /dev/null
+++ b/dpd/src/Const.py
@@ -0,0 +1,84 @@
+# DAB Frame constants
+# Sources:
+#   - etsi_EN_300_401_v010401p p145
+#   - Measured with USRP B200
+
+import numpy as np
+
+class Const:
+    def __init__(self, sample_rate, target_median, n_bins, n_per_bin, n_meas):
+        self.sample_rate = sample_rate
+        self.n_meas = n_meas
+
+        # Time domain
+        self.T_F = sample_rate / 2048000 * 196608  # Transmission frame duration
+        self.T_NULL = sample_rate / 2048000 * 2656  # Null symbol duration
+        self.T_S = sample_rate / 2048000 * 2552  # Duration of OFDM symbols of indices l = 1, 2, 3,... L;
+        self.T_U = sample_rate / 2048000 * 2048  # Inverse of carrier spacing
+        self.T_C = sample_rate / 2048000 * 504  # Duration of cyclic prefix
+
+        # Frequency Domain
+        # example: np.delete(fft[3328:4865], 768)
+        self.FFT_delete = 768
+        self.FFT_delta = 1536  # Number of carrier frequencies
+        if sample_rate == 2048000:
+            self.FFT_start = 256
+            self.FFT_end = 1793
+        elif sample_rate == 8192000:
+            self.FFT_start = 3328
+            self.FFT_end = 4865
+        else:
+            raise RuntimeError("Sample Rate '{}' not supported".format(
+                sample_rate
+            ))
+
+        # Calculate sample offset from phase rotation
+        # time per sample = 1 / sample_rate
+        # frequency per bin = 1kHz
+        # phase difference per sample offset = delta_t * 2 * pi * delta_freq
+        self.phase_offset_per_sample = 1. / sample_rate * 2 * np.pi * 1000
+
+        # Constants for ExtractStatistic
+        self.ES_plot = False
+        self.ES_start = 0.0
+        self.ES_end = 1.0
+        self.ES_n_bins = n_bins
+        self.ES_n_per_bin = n_per_bin
+
+        # Constants for TX_Agc
+        self.TAGC_max_txgain = 89
+        self.TAGC_tx_median_target = target_median
+        self.TAGC_tx_median_max = self.TAGC_tx_median_target*1.4
+        self.TAGC_tx_median_min = self.TAGC_tx_median_target/1.4
+
+
+        self.RAGC_min_rxgain = 25
+        self.RAGC_rx_median_target = self.TAGC_tx_median_target
+
+        # Constants for Model
+        self.MDL_plot = False
+
+        # Constants for MER
+        self.MER_plot = False
+
+        # Constants for Model_PM
+        self.MPM_tx_min = 0.1
+
+        # Constants for Measure_Shoulder
+        self.MS_enable = False
+        self.MS_plot = False
+        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]
+        shoulder_offset_edge = np.abs(meas_offset - self.FFT_delta)
+        self.MS_shoulder_left_start = self.FFT_start - shoulder_offset_edge - meas_width / 2
+        self.MS_shoulder_left_end = self.FFT_start - shoulder_offset_edge + meas_width / 2
+        self.MS_shoulder_right_start = self.FFT_end + shoulder_offset_edge - meas_width / 2
+        self.MS_shoulder_right_end = self.FFT_end + shoulder_offset_edge + meas_width / 2
+        self.MS_peak_start = self.FFT_start + 100 # Ignore region near edges
+        self.MS_peak_end = self.FFT_end - 100
+
+        self.MS_FFT_size = 8192
+        self.MS_averaging_size = 4 * self.MS_FFT_size
+        self.MS_n_averaging = 40
+        self.MS_n_proc = 4