diff --git a/.gitignore b/.gitignore index 21d0b89..fa1a06e 100644 --- a/.gitignore +++ b/.gitignore @@ -1 +1,2 @@ .venv/ +config.yaml \ No newline at end of file diff --git a/config.yaml b/config.yaml index 6e3e2c2..5a2cb4e 100644 --- a/config.yaml +++ b/config.yaml @@ -1,9 +1,9 @@ # Configuration file for scanner service # it is automatically re-loaded between scans -start_freq: 10000.0 -stop_freq: 0.1 +start_freq: 1000 +stop_freq: 0.2 freq_step_multiply: 0.95 +allowed_noise_level: 9 +skip_scans_for_noisy_freqs: 5 ampl: 1600 -interference_freq: 0.052 -interference_bandwidth: 0.008 noise_scan: False diff --git a/scanner.py b/scanner.py index 2fecf56..0e67a39 100644 --- a/scanner.py +++ b/scanner.py @@ -6,7 +6,7 @@ import re import telnetlib3 import csv import time -import pyodbc +import pyodbc # XXXDB import math from datetime import datetime import yaml @@ -14,22 +14,23 @@ import os data_rows = [] # global 2-D list state = {} +blacklist = [] +Inoise_baseline = 0.1 +n_clip_events = 0 PATTERN = re.compile( - r"Va=(?P-?\d+\.?\d*)\s+" - r"Vp=(?P-?\d+\.?\d*)\s+\|\s+" - r"Ia=(?P-?\d+\.?\d*)\s+" - r"Ip=(?P-?\d+\.?\d*)\s+\|\s+" - r"ZR=(?P-?\d+\.?\d*)\s+" - r"ZX=(?P-?\d+\.?\d*)" - r".*?irq=\d+\s+" # Skip to 'irq=', match the first digits and space - r"(?P[0-9a-fA-F]+)-" # First hex - r"(?P[0-9a-fA-F]+)\s+" # Second hex - r"(?P[0-9a-fA-F]+)-" # Third hex - r"(?P[0-9a-fA-F]+)" # Fourth hex + r"Va=(?P[\d.-]+)\s+Vp=(?P[\d.-]+)\s*\|\s*" + r"Ia=(?P[\d.-]+)\s+Ip=(?P[\d.-]+)\s*\|\s*" + r"ZR=(?P[\d.-]+)\s+ZX=(?P[\d.-]+).*?\|\s*" + r".*?irq=\w+\s+" + r"(?P[0-9a-fA-F]+)-(?P[0-9a-fA-F]+)\s+" + r"(?P[0-9a-fA-F]+)-(?P[0-9a-fA-F]+).*?\|\s*" + r"nv=(?P[\d.-]+)\s+ni=(?P[\d.-]+)\s*\|\s*" + r"QZR=(?P[\d.-]+)\s+QZX=(?P[\d.-]+)" ) -config_path = '/home/bart/python-scanner/config.yaml' +config_path = '/home/bart/python-scanner/config.yaml' # XXXDB +#config_path = 'config.yaml' def load_yaml_config(state_dict): if os.path.exists(config_path): @@ -63,12 +64,12 @@ 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[13], r[14], 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 +98,7 @@ 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", "QZR", "QZX", "adc_vmin", "adc_vmax", "adc_imin", "adc_imax", "nv", "ni"] ) df.to_csv(filename, index=False) @@ -134,21 +135,23 @@ 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 + float(match.group("QZR")), # row 13 + float(match.group("QZX")), # row 14 ] - 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[6] = row[1]/row[3] * math.sin(0.01745*(row[2]-row[4])) +# print(row) #### XX data_rows.append(row) def process_line(line): @@ -160,7 +163,7 @@ 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", "QZR", "QZX", "adc_vmin", "adc_vmax", "adc_imin", "adc_imax", "nv", "ni"] ) class TelnetReader: @@ -186,62 +189,76 @@ class TelnetReader: # Main loop: reads incoming lines forever try: while state["freq"] > state["stop_freq"]: - line = self.tn.read_until(b"\n") # read line - if not line: - break - - decoded = line.decode("utf-8", errors="ignore").strip() - self.process_line(decoded) # extract all info from line + if state["initializing"]>0: + self.process_line("Va=") + else: + line = self.tn.read_until(b"\n") # read line + if not line: + break + decoded = line.decode("utf-8", errors="ignore").strip() + self.process_line(decoded) # extract all info from line 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 -# print(f"RAW: {line}") + global Inoise_baseline + global n_clip_events + print(line) if not line.startswith("Va="): # skip lines that are not to be analyzed return - if state["remaining_receive_lines"] > 0 : - state["remaining_receive_lines"] -= 1 # we are waiting for settling - just skip the line - else: - # prepare new frequency measurement - if state["initializing"] == 1: - # since we just start a frequency scan, let's set the R, Max and Amplitude - response = f"\rr516\r" # set Resistance value for scaling HAL sensor - self.tn.write(response.encode("utf-8")) - response = f"m1600\r" # set max amplitude value - self.tn.write(response.encode("utf-8")) - # for noise scans the amplitude is zero, else the state["ampl"] - if state["noise_scan"]==True: - response = f"a0\r" # zero amplitude for noise measurement - else: - response = f"a{state["ampl"]:.1f}\r" # set amplitude - 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 - else: # regular loop (not initializing) + # prepare new frequency measurement + if state["initializing"] == 1: + # since we just start a frequency scan, let's set the R, Max and Amplitude + response = f"\rr516\r" # set Resistance value for scaling HAL sensor + self.tn.write(response.encode("utf-8")) + response = f"m1600\r" # set max amplitude value + self.tn.write(response.encode("utf-8")) + # for noise scans the amplitude is zero, else the state["ampl"] + if state["noise_scan"]==True: + response = f"a0\r" # zero amplitude for noise measurement + else: + response = f"a{state["ampl"]:.1f}\r" # set amplitude + 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["initializing"] = 2 + else: # regular loop (initializing is 0 (normal) or 2 (first sample)) + if state["initializing"] == 0: 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 (state["freq"]>10) 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 + if (++n_clip_events > 2): # react only after multiple clip events (solves startup issue) + if data_rows[-1][9]>0: # make exception (for our broken hardware?) + state["freq"] = 0 # force ending of the scan, and write no data in the database + else: + n_clip_events=0 # calculate next freq if state["freq"] > 1.0: freq_multiplier = state["freq_step_multiply"] # calc next freq @@ -251,26 +268,17 @@ class TelnetReader: else: freq_multiplier = state["freq_step_multiply"] ** 4 # skip 3/4 steps to speed up state["freq"] *= freq_multiplier - if (state["freq"]>40) and (state["freq"]<660) and ((state["freq"]%50<2.5) or (-state["freq"]%50<2.5)): - state["freq"] *= freq_multiplier # if near a 50Hz harmonic, skip to the next frequency - while (state["freq"]<0.6) and ((state["freq"]%state["interference_freq"] 0.01: - response = f"\rf{state["freq"]:.1f}\r" # new freq - else: - response = f"\rf{state["freq"]:.3f}\r" # new freq + # program the health monitor to go to the next frequency: + response = f"\rQ{state["freq"]:.3f}\r" # new freq self.tn.write(response.encode("utf-8")) - bandwidth = state["freq"]/20 - if bandwidth > 0.5 : - bandwidth = 0.5 - response = f"b{bandwidth:.3f}\r" # new freq - self.tn.write(response.encode("utf-8")) - state["remaining_receive_lines"] = 1 + 4/bandwidth - print(line) - print(state) +# print(state) state["initializing"] = 0 # Example: @@ -288,7 +296,7 @@ class TelnetReader: if __name__ == "__main__": reader = TelnetReader(host="localhost", port=2002) # reader = TelnetReader(host="10.1.122.152", port=2002) -# reader = TelnetReader(host="192.168.1.196", port=2002) +# reader = TelnetReader(host="192.168.1.235", port=2002) try: reader.connect() @@ -298,10 +306,14 @@ if __name__ == "__main__": load_yaml_config(state) # Load configuration settings state["freq"] = state["start_freq"]; - state["remaining_receive_lines"] = 0; 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()