From 877915ae38951a8aa8c2a6333f72e896ed9b0acf Mon Sep 17 00:00:00 2001
From: Gertjan Koolen <gjkoolen@gmail.com>
Date: Tue, 17 Mar 2026 09:48:12 +0100
Subject: [PATCH] frequency avoidance - work in progress

---
 scanner.py | 36 ++++++++++++++++++++----------------
 1 file changed, 20 insertions(+), 16 deletions(-)

diff --git a/scanner.py b/scanner.py
index 2fecf56..153c6ae 100644
--- a/scanner.py
+++ b/scanner.py
@@ -27,6 +27,8 @@ PATTERN = re.compile(
     r"(?P<adc_vmax>[0-9a-fA-F]+)\s+"    # Second hex
     r"(?P<adc_imin>[0-9a-fA-F]+)-"      # Third hex
     r"(?P<adc_imax>[0-9a-fA-F]+)"       # Fourth hex
+    r"nv=(?P<nv>-?\d+\.?\d*)\s+"        # voltage noise/interference
+    r"ni=(?P<ni>-?\d+\.?\d*)\s+"        # current noise/interference
 )
 
 config_path = '/home/bart/python-scanner/config.yaml'
@@ -63,12 +65,12 @@ def dump_into_database():
             if state["noise_scan"]==False:
                 # regular scan data
                 formatted_rows = [
-                    [sweep_insert_time, r[0], r[5], r[6], r[1], r[2], r[3], r[4]]
+                    [sweep_insert_time, r[0], r[5], r[6], r[1], r[2], r[3], r[4], r[11], r[12]]
                     for r in data_rows
                 ]
                 sql = """
-                      INSERT INTO SequenceValues (StartTimeOfSweep, Freq, ZR, ZX, Vampl, Vphase, Iampl, Iphase)
-                      VALUES (?, ?, ?, ?, ?, ?, ?, ?) \
+                      INSERT INTO SequenceValues (StartTimeOfSweep, Freq, ZR, ZX, Vampl, Vphase, Iampl, Iphase, Vnoise, Inoise)
+                      VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) \
                       """
             else:
                 # noise scan data
@@ -97,7 +99,7 @@ def dump_into_database():
 def dump_csv(filename="data.csv"):
     df = pd.DataFrame(
         data_rows,
-        columns=["Freq", "Va", "Vp", "Ia", "Ip", "ZR", "ZX", "adc_vmin", "adc_vmax", "adc_imin", "adc_imax"]
+        columns=["Freq", "Va", "Vp", "Ia", "Ip", "ZR", "ZX", "adc_vmin", "adc_vmax", "adc_imin", "adc_imax", "nv", "ni"]
     )
     df.to_csv(filename, index=False)
 
@@ -134,17 +136,19 @@ def extract_to_dataframe(line):
     if not match:
         return  # silently ignore malformed lines
     row = [
-        float(state["freq"]),
-        float(match.group("Va")),
-        float(match.group("Vp")),
-        float(match.group("Ia")),
-        float(match.group("Ip")),
-        float(match.group("ZR")),
-        float(match.group("ZX")),
-        int(match.group("adc_vmin"), 16),
-        int(match.group("adc_vmax"), 16),
-        int(match.group("adc_imin"), 16),
-        int(match.group("adc_imax"), 16),
+        float(state["freq"]),               # row 0
+        float(match.group("Va")),           # row 1
+        float(match.group("Vp")),           # row 2
+        float(match.group("Ia")),           # row 3
+        float(match.group("Ip")),           # row 4
+        float(match.group("ZR")),           # row 5
+        float(match.group("ZX")),           # row 6
+        int(match.group("adc_vmin"), 16),   # row 7
+        int(match.group("adc_vmax"), 16),   # row 8
+        int(match.group("adc_imin"), 16),   # row 9
+        int(match.group("adc_imax"), 16),   # row 10
+        float(match.group("nv")),           # row 11
+        float(match.group("ni")),           # row 12
     ]
     row[1] = row[1]/(2*3.14159*row[0]*0.00005 + 1)      # compensate Va for pole at 20kHz
     row[5] = row[1]/row[3] * math.cos(0.01745*(row[2]-row[4]))
@@ -160,7 +164,7 @@ def process_line(line):
 def get_dataframe():
     return pd.DataFrame(
         data_rows,
-        columns=["Va", "Vp", "Ia", "Ip", "ZR", "ZX", "adc_vmin", "adc_vmax", "adc_imin", "adc_imax"]
+        columns=["Va", "Vp", "Ia", "Ip", "ZR", "ZX", "adc_vmin", "adc_vmax", "adc_imin", "adc_imax", "nv", "ni"]
     )
 
 class TelnetReader: