PR-2501/scanner_script
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frequency avoidance - work in progress

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This commit is contained in:
Gertjan Koolen 2026-03-17 09:48:12 +01:00
parent 1bfefa94bb
commit 877915ae38
1 changed files with 20 additions and 16 deletions
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36
scanner.py
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@ -27,6 +27,8 @@ PATTERN = re.compile(
r"(?P<adc_vmax>[0-9a-fA-F]+)\s+" # Second hex r"(?P<adc_vmax>[0-9a-fA-F]+)\s+" # Second hex
r"(?P<adc_imin>[0-9a-fA-F]+)-" # Third hex r"(?P<adc_imin>[0-9a-fA-F]+)-" # Third hex
r"(?P<adc_imax>[0-9a-fA-F]+)" # Fourth 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' config_path = '/home/bart/python-scanner/config.yaml'
@ -63,12 +65,12 @@ def dump_into_database():
if state["noise_scan"]==False: if state["noise_scan"]==False:
# regular scan data # regular scan data
formatted_rows = [ 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 for r in data_rows
] ]
sql = """ sql = """
INSERT INTO SequenceValues (StartTimeOfSweep, Freq, ZR, ZX, Vampl, Vphase, Iampl, Iphase) INSERT INTO SequenceValues (StartTimeOfSweep, Freq, ZR, ZX, Vampl, Vphase, Iampl, Iphase, Vnoise, Inoise)
VALUES (?, ?, ?, ?, ?, ?, ?, ?) \ VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?) \
""" """
else: else:
# noise scan data # noise scan data
@ -97,7 +99,7 @@ def dump_into_database():
def dump_csv(filename="data.csv"): def dump_csv(filename="data.csv"):
df = pd.DataFrame( df = pd.DataFrame(
data_rows, 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) df.to_csv(filename, index=False)
@ -134,17 +136,19 @@ def extract_to_dataframe(line):
if not match: if not match:
return # silently ignore malformed lines return # silently ignore malformed lines
row = [ row = [
float(state["freq"]), float(state["freq"]), # row 0
float(match.group("Va")), float(match.group("Va")), # row 1
float(match.group("Vp")), float(match.group("Vp")), # row 2
float(match.group("Ia")), float(match.group("Ia")), # row 3
float(match.group("Ip")), float(match.group("Ip")), # row 4
float(match.group("ZR")), float(match.group("ZR")), # row 5
float(match.group("ZX")), float(match.group("ZX")), # row 6
int(match.group("adc_vmin"), 16), int(match.group("adc_vmin"), 16), # row 7
int(match.group("adc_vmax"), 16), int(match.group("adc_vmax"), 16), # row 8
int(match.group("adc_imin"), 16), int(match.group("adc_imin"), 16), # row 9
int(match.group("adc_imax"), 16), 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[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])) 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(): def get_dataframe():
return pd.DataFrame( return pd.DataFrame(
data_rows, 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: class TelnetReader: