Gertjan
17ec02c5be
Vanaf hier kan ik gaan groeien met mijn file structuur. Alle niet-Nextcloud files wil ik in GIT hebben, op deze locatie.
232 lines
6.4 KiB
Python
232 lines
6.4 KiB
Python
import numpy as np
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import pandas as pd
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import matplotlib.pyplot as plt
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import re
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import telnetlib3
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import csv
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import time
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Z_table = [
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[ 0.00007362 , 0.00007713 ],
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[ 0.00004428 , 0.00013248 ],
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[ 0.00007899 , 0.0002094 ],
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[ 0.00019893 , 0.00025827 ],
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[ 0.00039363 , 0.00020892 ],
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[ 0.00047154 , 0.00012468 ],
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[ 0.00050655 , 0.00009711 ],
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[ 0.00051549 , 0.00004863 ],
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[ 0.00051693 , 0.00003609 ],
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[ 0.00052323 , 0.00003429 ],
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[ 0.00053727 , 0.00004557 ],
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[ 0.00055146 , 0.00006702 ],
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[ 0.00058626 , 0.00009252 ],
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[ 0.00066285 , 0.00008859 ],
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[ 0.00066801 , 0.00004833 ],
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[ 0.00068286 , 0.00005697 ],
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[ 0.00073578 , 0.00000705 ],
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[ 0.0005028 , -0.00007668 ]
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]
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Z2_table = [
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#[ 0.000141451 , -0.001248057 ],
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[ 0.000482934 , -0.000453644 ],
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[ 0.000522226 , -0.000231466 ],
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[ 0.000532942 , -0.000115733 ],
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[ 0.000533657 , -5.21512E-05 ],
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[ 0.000528656 , -0.000028576 ],
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[ 0.000525084 , -1.28592E-05 ],
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[ 0.000522941 , 7.144E-07 ],
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[ 0.000527227 , 1.00016E-05 ],
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[ 0.000532228 , 1.85744E-05 ],
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[ 0.000540801 , 3.35768E-05 ],
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[ 0.000557232 , 5.85808E-05 ],
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[ 0.00059581 , 8.50136E-05 ],
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[ 0.000670822 , 8.71568E-05 ],
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[ 0.000706542 , 0.000060724 ]
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]
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data_rows = [] # global 2-D list
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state = {
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"remaining_receive_lines": 0,
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"freq": 10000.0,
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"freq_step_multiply": 0.92,
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"stop_freq": 0.1,
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"initializing": 1
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}
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PATTERN = re.compile(
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r"Va=(?P<Va>-?\d+\.?\d*)\s+"
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r"Vp=(?P<Vp>-?\d+\.?\d*)\s+\|\s+"
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r"Ia=(?P<Ia>-?\d+\.?\d*)\s+"
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r"Ip=(?P<Ip>-?\d+\.?\d*)\s+\|\s+"
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r"ZR=(?P<ZR>-?\d+\.?\d*)\s+"
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r"ZX=(?P<ZX>-?\d+\.?\d*)"
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)
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def dump_csv(filename="data.csv"):
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df = pd.DataFrame(
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data_rows,
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columns=["Freq", "Va", "Vp", "Ia", "Ip", "ZR", "ZX"]
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)
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df.to_csv(filename, index=False)
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def append_line_to_file(column_nr, filename):
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# Extract freq column (index 0)
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# Extract ZR column (index 5)
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# Extract ZX column (index 6)
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zr_values = [row[column_nr] for row in data_rows if len(row) > column_nr]
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if not zr_values:
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print("No ZR data to write")
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return
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with open(filename, "a", newline="") as f:
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writer = csv.writer(f)
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writer.writerow(zr_values)
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def extract_to_dataframe(line):
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# Extract Va, Vp, Ia, Ip, ZR, ZX from a line and append them as a row to the global data_rows list.
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global state
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match = PATTERN.search(line)
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if not match:
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return # silently ignore malformed lines
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row = [
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float(state["freq"]),
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float(match.group("Va")),
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float(match.group("Vp")),
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float(match.group("Ia")),
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float(match.group("Ip")),
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float(match.group("ZR")),
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float(match.group("ZX")),
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]
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data_rows.append(row)
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def process_line(line):
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extract_to_dataframe(line)
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# Example: print last row
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if data_rows:
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print("Last row:", data_rows[-1])
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def get_dataframe():
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return pd.DataFrame(
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data_rows,
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columns=["Va", "Vp", "Ia", "Ip", "ZR", "ZX"]
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)
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class TelnetReader:
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def __init__(self, host, port=23, timeout=10):
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self.host = host
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self.port = port
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self.timeout = timeout
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self.tn = None
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def connect(self):
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print(f"Connecting to {self.host}:{self.port} ...")
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self.tn = telnetlib3.Telnet(self.host, self.port, self.timeout)
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print("Connected.")
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def disconnect(self):
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if self.tn:
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self.tn.close()
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self.tn = None
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print("Disconnected.")
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def read_loop(self):
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global state
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# Main loop: reads incoming lines forever
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try:
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while state["freq"] > state["stop_freq"]:
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line = self.tn.read_until(b"\n")
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if not line:
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break
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decoded = line.decode("utf-8", errors="ignore").strip()
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self.process_line(decoded)
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except KeyboardInterrupt:
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print("Interrupted by user.")
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print(data_rows)
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dump_csv("measurements.csv")
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def process_line(self, line):
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global state
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# Override or extend this method to extract data.
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# print(f"RAW: {line}")
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if state["remaining_receive_lines"] > 0 :
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state["remaining_receive_lines"] -= 1 # we are waiting for settling - just skip the line
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else:
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# prepare new frequency measurement
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if not state["initializing"] == 1:
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extract_to_dataframe(line) # capture the measurement
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if state["freq"] > 0.7:
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state["freq"] *= state["freq_step_multiply"] # calc next freq
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else:
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if state["freq"] > 0.4:
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state["freq"] *= state["freq_step_multiply"] ** 2 # skip 1/2 steps to speed up
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else:
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state["freq"] *= state["freq_step_multiply"] ** 4 # skip 3/4 steps to speed up
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if state["freq"] <= state["stop_freq"]:
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print("Reached stop frequency")
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else:
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if state["freq"] > 1:
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response = f"\rf{state["freq"]:.1f}\r" # new freq
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else:
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response = f"\rf{state["freq"]:.3f}\r" # new freq
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self.tn.write(response.encode("utf-8"))
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bandwidth = state["freq"]/10
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if bandwidth > 1 :
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bandwidth = 1
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response = f"b{bandwidth:.3f}\r" # new freq
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self.tn.write(response.encode("utf-8"))
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state["remaining_receive_lines"] = 1 + 3/bandwidth
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print(line)
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print(state)
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state["initializing"] = 0
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# Example:
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# value = self.extract_value(line)
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# self.store_value(value)
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# Example placeholder methods
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def extract_value(self, line):
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pass
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def store_value(self, value):
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pass
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if __name__ == "__main__":
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reader = TelnetReader(host="10.1.122.152", port=2002)
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try:
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reader.connect()
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reader.read_loop()
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finally:
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reader.disconnect()
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Z_points = [complex(r, i) for r, i in Z_table]
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Zp = np.array(Z_points)
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Z2_points = [complex(r, i) for r, i in Z2_table]
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Z2p = np.array(Z2_points)
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plt.plot(
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Zp.real,
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Zp.imag,
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marker='x',
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color='blue',
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label="shunt-300u"
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)
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plt.plot(
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Z2p.real,
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Z2p.imag,
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marker='x',
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color='red',
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label="clamp"
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)
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plt.xlabel("Re{Z} [Ω]")
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plt.ylabel("-Im{Z} [Ω]")
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plt.title("Nyquist Plot")
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plt.grid(True)
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plt.legend()
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plt.show()
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