PR-2501/scanner_script
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tested and tuned on Veghel Lab system

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gertjan 2026-03-17 23:20:26 +01:00
parent 1bfefa94bb
commit f0cc0a2b93
2 changed files with 37 additions and 22 deletions
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51
scanner.py
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@ -14,6 +14,8 @@ import os
data_rows = [] # global 2-D list
state = {}
blacklist = []
Inoise_baseline = 0.1
PATTERN = re.compile(
r"Va=(?P<Va>-?\d+\.?\d*)\s+"
@ -196,24 +198,27 @@ class TelnetReader:
except KeyboardInterrupt:
print("Interrupted by user.")
print(data_rows)
if state["freq"]>0.00001: # check if scan endeed normally (e.g. no abort due to clipping)
#dump_csv("measurements.csv")
dump_into_database()
#append_line_to_file(0, "scan_freq.csv")
#append_line_to_file(1, "scan_Va.csv")
#append_line_to_file(2, "scan_Vp.csv")
#append_line_to_file(3, "scan_Ia.csv")
#append_line_to_file(4, "scan_Ip.csv")
#append_line_to_file(5, "scan_ZR.csv")
#append_line_to_file(6, "scan_ZX.csv")
#append_Nyquist_run("scan_Nyquist.csv")
#state["noise_scan"] = not state["noise_scan"]
if state["freq"]>0.00001: # check if scan ended normally (e.g. no abort due to clipping)
if True: # XXXDB
dump_into_database()
else:
dump_csv("measurements.csv")
#append_line_to_file(0, "scan_freq.csv")
#append_line_to_file(1, "scan_Va.csv")
#append_line_to_file(2, "scan_Vp.csv")
#append_line_to_file(3, "scan_Ia.csv")
#append_line_to_file(4, "scan_Ip.csv")
#append_line_to_file(5, "scan_ZR.csv")
#append_line_to_file(6, "scan_ZX.csv")
#append_Nyquist_run("scan_Nyquist.csv")
#state["noise_scan"] = not state["noise_scan"]
else:
print("scan aborted\r")
gc.collect() # clean up internal memory (garbage collect)
def process_line(self, line):
global state
global Inoise_baseline
# print(f"RAW: {line}")
if not line.startswith("Va="): # skip lines that are not to be analyzed
return
@ -236,12 +241,17 @@ class TelnetReader:
# there will be a lot of lines, but they will be skipped as they do not match the pattern
else: # regular loop (not initializing)
extract_to_dataframe(line) # capture the measurement
# print(f"minmax: {data_rows[7]},{data_rows[8]},{data_rows[9]},{data_rows[10] }\n")
if data_rows and (data_rows[-1][7]<5 or data_rows[-1][8]>250 or data_rows[-1][9]<5 or data_rows[-1][10]>250):
#response = f"a{state["ampl"]:.1f}\r" # send ampl to trigger sweep
#self.tn.write(response.encode("utf-8"))
# there will be a lot of lines, but they will be skipped as they do not match the pattern
state["freq"] = 0 # force ending of the scan, and write no data in the database
if state["freq"]>3.0:
Inoise_baseline = 0.8*Inoise_baseline + 0.2*data_rows[-1][12] # remember last baseline around 3Hz (assuming top-down scanning)
if data_rows and (data_rows[-1][11]>state["allowed_noise_level"] or data_rows[-1][12]>state["allowed_noise_level"] or (state["freq"]<3.0 and data_rows[-1][12]>1.25*Inoise_baseline)):
# Too much noise: add to blacklist
print("Too much noise - adding to blacklist")
blacklist.append({"Freq": state["freq"], "NrToSkip": state["skip_scans_for_noisy_freqs"]})
print(f"Blacklist: {blacklist}\r")
del data_rows[-1] # remove this last entry from the list (for DB it is okay, but for CSV things will shift)
else:
if data_rows and (data_rows[-1][7]<5 or data_rows[-1][8]>250 or data_rows[-1][9]<5 or data_rows[-1][10]>250): # XXXDB
state["freq"] = 0 # force ending of the scan, and write no data in the database
# calculate next freq
if state["freq"] > 1.0:
freq_multiplier = state["freq_step_multiply"] # calc next freq
@ -302,6 +312,11 @@ if __name__ == "__main__":
state["initializing"] = 1;
reader.read_loop()
# decrement all freq's in blacklist:
for item in blacklist:
item["NrToSkip"] -= 1
blacklist = [item for item in blacklist if item["NrToSkip"] != 0] # remove all zero items
print(f"Blacklist: {blacklist}")
finally:
reader.disconnect()