GUI: add capture and plot to DPD

1 files changed, 93 insertions, 7 deletions

diff --git a/python/dpdce.py b/python/dpdce.py
index 379f3d0..a9ed140 100755
--- a/python/dpdce.py
+++ b/python/dpdce.py
@@ -43,7 +43,8 @@ rc_port = config.getint('rc_port')
 samplerate = config.getint('samplerate')
 samps = config.getint('samps')
 coef_file = config['coef_file']
-log_folder = config['log_folder']
+logs_directory = config['logs_directory']
+plot_directory = config['plot_directory']
 
 import logging
 import datetime
@@ -52,7 +53,7 @@ save_logs = False
 
 # Simple usage scenarios don't need to clutter /tmp
 if save_logs:
-    dt = datetime.datetime.now().isoformat()
+    dt = datetime.datetime.utcnow().isoformat()
     logging_path = '/tmp/dpd_{}'.format(dt).replace('.', '_').replace(':', '-')
     print("Logs and plots written to {}".format(logging_path))
     os.makedirs(logging_path)
@@ -71,7 +72,7 @@ if save_logs:
     # add the handler to the root logger
     logging.getLogger('').addHandler(console)
 else:
-    dt = datetime.datetime.now().isoformat()
+    dt = datetime.datetime.utcnow().isoformat()
     logging.basicConfig(format='%(asctime)s - %(module)s - %(levelname)s - %(message)s',
                         datefmt='%Y-%m-%d %H:%M:%S',
                         level=logging.INFO)
@@ -83,6 +84,7 @@ import socket
 from lib import yamlrpc
 import numpy as np
 import traceback
+import os.path
 from threading import Thread, Lock
 from queue import Queue
 from dpd.Model import Poly
@@ -96,13 +98,14 @@ from dpd.GlobalConfig import GlobalConfig
 from dpd.MER import MER
 from dpd.Measure_Shoulders import Measure_Shoulders
 
-c = GlobalConfig(samplerate, logging_path)
+plot_path = os.path.realpath(plot_directory)
+
+c = GlobalConfig(samplerate, plot_path)
 symbol_align = Symbol_align(c)
 mer = MER(c)
 meas_shoulders = Measure_Shoulders(c)
 meas = Measure(c, samplerate, dpd_port, samps)
-extStat = ExtractStatistic(c)
-adapt = Adapt(rc_port, coef_file, logging_path)
+adapt = Adapt(rc_port, coef_file, plot_path)
 
 model = Poly(c)
 
@@ -134,7 +137,11 @@ settings = {
         'digital_gain': digital_gain,
         'dpddata': dpddata,
         }
+internal_data = {
+        'n_runs': 0,
+        }
 results = {
+        'statplot': None,
         'tx_median': 0,
         'rx_median': 0,
         'state': 'Idle',
@@ -148,6 +155,7 @@ command_queue = Queue(maxsize=1)
 agc = Agc(meas, adapt, c)
 
 def engine_worker():
+    extStat = ExtractStatistic(c)
     try:
         while True:
             cmd = command_queue.get()
@@ -180,8 +188,86 @@ def engine_worker():
                     results['tx_median'] = float(tx_median)
                     results['rx_median'] = float(rx_median)
                     results['state'] = 'Idle'
-                    results['stateprogress'] = 0
+                    results['stateprogress'] = 100
                     results['summary'] = ["Calibration was done:"] + summary
+            elif cmd == "reset":
+                with lock:
+                    internal_data['n_runs'] = 0
+                    results['state'] = 'Idle'
+                    results['stateprogress'] = 0
+                    results['summary'] = ["Reset"]
+                extStat = ExtractStatistic(c)
+            elif cmd == "trigger_run":
+                with lock:
+                    results['state'] = 'Capture + Model'
+                    results['stateprogress'] = 0
+                    n_runs = internal_data['n_runs']
+
+                # Get Samples and check gain
+                txframe_aligned, tx_ts, rxframe_aligned, rx_ts, rx_median, tx_median = meas.get_samples()
+                # TODO Check TX median
+
+                with lock:
+                    results['stateprogress'] = 20
+                    results['summary'] = ["Captured {} samples".format(len(txframe_aligned)),
+                        "TX/RX median: {} / {}".format(tx_median, rx_median)]
+
+                # Extract usable data from measurement
+                tx, rx, phase_diff, n_per_bin = extStat.extract(txframe_aligned, rxframe_aligned)
+
+                time = datetime.datetime.utcnow()
+
+                plot_file = "stats_{}.png".format(time.strftime("%s"))
+                extStat.plot(os.path.join(plot_path, plot_file), time.strftime("%Y-%m-%dT%H%M%S"))
+
+                with lock:
+                    results['statplot'] = "dpd/" + plot_file
+                    results['stateprogress'] = 30
+                    results['summary'] += ["Extracted Statistics".format(tx_median, rx_median)]
+
+                n_meas = Heuristics.get_n_meas(n_runs)
+                if extStat.n_meas >= n_meas:  # Use as many measurements nr of runs
+                    if any(x is None for x in [tx, rx, phase_diff]):
+                        with lock:
+                            results['summary'] += ["Error! No data to calculate model"]
+                            results['state'] = 'Idle'
+                            results['stateprogress'] = 0
+                    else:
+                        with lock:
+                            results['state'] = 'Capture + Model'
+                            results['stateprogress'] = 40
+                            results['summary'] += ["Training model"]
+
+                        model.train(tx, rx, phase_diff, lr=Heuristics.get_learning_rate(n_runs))
+
+                        with lock:
+                            results['state'] = 'Capture + Model'
+                            results['stateprogress'] = 60
+                            results['summary'] += ["Getting DPD data"]
+
+                        dpddata = model.get_dpd_data()
+                        with lock:
+                            internal_data['dpddata'] = dpddata
+                            internal_data['n_runs'] = 0
+
+                            results['state'] = 'Capture + Model'
+                            results['stateprogress'] = 80
+                            results['summary'] += ["Reset statistics"]
+
+                        extStat = ExtractStatistic(c)
+
+                        with lock:
+                            results['state'] = 'Idle'
+                            results['stateprogress'] = 100
+                            results['summary'] += ["New DPD coefficients calculated"]
+
+                    with lock:
+                        internal_data['n_runs'] += 1
+                else:
+                    with lock:
+                        results['state'] = 'Idle'
+                        results['stateprogress'] = 100
+                        results['summary'] += ["More data required to train model"]
 
     finally:
         with lock: