2023-04-13 11:09:40 +02:00
|
|
|
"""
|
|
|
|
run this before using this library:
|
2023-06-18 17:38:10 +02:00
|
|
|
ipython -i m_teng_interactive.py
|
2023-04-13 17:50:40 +02:00
|
|
|
|
|
|
|
always records iv-t curves
|
|
|
|
i-data -> smua.nvbuffer1
|
|
|
|
v-data -> smua.nvbuffer2
|
2023-04-13 11:09:40 +02:00
|
|
|
"""
|
|
|
|
|
|
|
|
import numpy as np
|
|
|
|
import matplotlib.pyplot as plt
|
|
|
|
import pandas as pd
|
|
|
|
|
|
|
|
from datetime import datetime as dtime
|
|
|
|
from sys import exit
|
|
|
|
from time import sleep
|
|
|
|
from os import path, makedirs
|
|
|
|
import pickle as pkl
|
|
|
|
import json
|
2023-06-24 12:28:12 +02:00
|
|
|
import atexit
|
2023-04-13 11:09:40 +02:00
|
|
|
|
2023-06-18 17:38:10 +02:00
|
|
|
import argparse
|
|
|
|
|
|
|
|
|
2023-04-13 11:09:40 +02:00
|
|
|
if __name__ == "__main__":
|
2023-06-18 17:38:10 +02:00
|
|
|
import sys
|
2023-04-13 11:09:40 +02:00
|
|
|
if __package__ is None:
|
|
|
|
# make relative imports work as described here: https://peps.python.org/pep-0366/#proposed-change
|
2023-06-18 17:38:10 +02:00
|
|
|
__package__ = "m_teng"
|
2023-04-13 11:09:40 +02:00
|
|
|
from os import path
|
|
|
|
filepath = path.realpath(path.abspath(__file__))
|
|
|
|
sys.path.insert(0, path.dirname(path.dirname(filepath)))
|
2023-06-18 17:38:10 +02:00
|
|
|
parser = argparse.ArgumentParser(
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|
|
|
prog="m-teng",
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|
|
|
description="measure triboelectric nanogenerator output using a Keithley SMU or an Arduino",
|
|
|
|
)
|
|
|
|
backend_group = parser.add_mutually_exclusive_group(required=True)
|
|
|
|
backend_group.add_argument("-k", "--keithley", action="store_true")
|
|
|
|
backend_group.add_argument("-a", "--arduino", action="store_true")
|
|
|
|
backend_group.add_argument("-t", "--testing", action='store_true')
|
|
|
|
parser.add_argument("-c", "--config", action="store", help="alternate path to config file")
|
|
|
|
args = vars(parser.parse_args())
|
|
|
|
|
|
|
|
i = 1
|
|
|
|
while i < len(sys.argv):
|
|
|
|
if args["keithley"]:
|
|
|
|
import m_teng.backends.keithley.keithley as _backend
|
|
|
|
import m_teng.backends.keithley.measure as _measure
|
|
|
|
elif args["arduino"]:
|
|
|
|
import m_teng.backends.arduino.arduino as _backend
|
|
|
|
import m_teng.backends.arduino.measure as _measure
|
|
|
|
elif args["testing"]:
|
|
|
|
import m_teng.backends.testing.testing as _backend
|
|
|
|
import m_teng.backends.testing.measure as _measure
|
|
|
|
elif sys.argv[i] in ["-c", "--config"]:
|
|
|
|
if i+1 < len(sys.argv):
|
|
|
|
config_path = sys.argv[i+1]
|
|
|
|
else:
|
|
|
|
print("-c requires an extra argument: path of config file")
|
|
|
|
i += 1
|
|
|
|
i += 1
|
2023-04-13 11:09:40 +02:00
|
|
|
|
|
|
|
|
2023-06-18 17:38:10 +02:00
|
|
|
from m_teng.utility import data as _data
|
|
|
|
from m_teng.utility.data import load_dataframe
|
|
|
|
from m_teng.utility import file_io
|
|
|
|
from m_teng.update_funcs import _Monitor, _ModelPredict, _update_print
|
|
|
|
|
|
|
|
config_path = path.expanduser("~/.config/k-teng.json")
|
2023-04-13 11:09:40 +02:00
|
|
|
|
|
|
|
_runtime_vars = {
|
|
|
|
"last-measurement": ""
|
|
|
|
}
|
|
|
|
|
|
|
|
settings = {
|
|
|
|
"datadir": path.expanduser("~/data"),
|
|
|
|
"name": "measurement",
|
2023-06-27 10:18:54 +02:00
|
|
|
"interval": 0.05,
|
2023-04-13 11:09:40 +02:00
|
|
|
"beep": True,
|
|
|
|
}
|
|
|
|
|
|
|
|
test = False
|
|
|
|
|
2023-06-18 17:38:10 +02:00
|
|
|
# global variable for the instrument/client returned by pyvisa/bleak
|
|
|
|
dev = None
|
2023-04-13 11:09:40 +02:00
|
|
|
|
2023-04-27 01:40:12 +02:00
|
|
|
|
2023-06-27 10:18:54 +02:00
|
|
|
def monitor_predict(model_dir: str, count=5000, interval=None, max_points_shown=160):
|
2023-04-13 11:09:40 +02:00
|
|
|
"""
|
2023-06-18 17:38:10 +02:00
|
|
|
Take <count> measurements in <interval> and predict with a machine learning model
|
2023-04-27 01:40:12 +02:00
|
|
|
"""
|
2023-06-27 10:18:54 +02:00
|
|
|
if not interval: interval = settings["interval"]
|
|
|
|
|
2023-06-18 17:38:10 +02:00
|
|
|
model_predict = _ModelPredict(dev, model_dir)
|
|
|
|
plt_monitor = _Monitor(max_points_shown, use_print=False)
|
|
|
|
skip_n = 0
|
|
|
|
def update(i, ival, vval):
|
|
|
|
plt_monitor.update(i, ival, vval)
|
|
|
|
if skip_n % 10 == 0:
|
|
|
|
model_predict.update(i, ival, vval)
|
|
|
|
skip_n += 1
|
2023-04-27 01:40:12 +02:00
|
|
|
|
2023-06-18 17:38:10 +02:00
|
|
|
print(f"Starting measurement with:\n\tinterval = {interval}s\nSave the data using 'save_csv()' afterwards.")
|
|
|
|
try:
|
2023-06-24 12:28:12 +02:00
|
|
|
_measure.measure_count(dev, count=count, interval=interval, beep_done=False, verbose=False, update_func=update, update_interval=0.1)
|
2023-06-18 17:38:10 +02:00
|
|
|
except KeyboardInterrupt:
|
|
|
|
if args["keithley"]:
|
|
|
|
dev.write(f"smua.source.output = smua.OUTPUT_OFF")
|
|
|
|
print("Monitoring cancelled, measurement might still continue" + " "*50)
|
|
|
|
else:
|
|
|
|
print("Measurement finished" + " "*50)
|
2023-04-27 01:40:12 +02:00
|
|
|
|
2023-06-27 10:18:54 +02:00
|
|
|
def monitor_count(count=5000, interval=None, max_points_shown=160):
|
2023-04-27 01:40:12 +02:00
|
|
|
"""
|
|
|
|
Take <count> measurements in <interval> and monitor live with matplotlib.
|
2023-04-13 11:09:40 +02:00
|
|
|
|
|
|
|
@details:
|
|
|
|
- Resets the buffers
|
|
|
|
- Opens a matplotlib window and takes measurements depending on settings["interval"]
|
2023-04-27 01:40:12 +02:00
|
|
|
Uses the device internal overlappedY measurement method, which allows for greater precision
|
|
|
|
You can take the data from the buffer afterwards, using save_csv
|
|
|
|
@param count: count
|
|
|
|
@param interval: interval, defaults to settings["interval"]
|
|
|
|
@param max_points_shown: how many points should be shown at once. None means infinite
|
|
|
|
"""
|
2023-06-27 10:18:54 +02:00
|
|
|
if not interval: interval = settings["interval"]
|
2023-04-27 01:40:12 +02:00
|
|
|
plt_monitor = _Monitor(max_points_shown, use_print=True)
|
|
|
|
update_func = plt_monitor.update
|
|
|
|
|
|
|
|
print(f"Starting measurement with:\n\tinterval = {interval}s\nSave the data using 'save_csv()' afterwards.")
|
|
|
|
try:
|
2023-06-24 12:28:12 +02:00
|
|
|
_measure.measure_count(dev, count=count, interval=interval, beep_done=False, verbose=False, update_func=update_func, update_interval=0.05)
|
2023-04-27 01:40:12 +02:00
|
|
|
except KeyboardInterrupt:
|
2023-06-18 17:38:10 +02:00
|
|
|
if args["keithley"]:
|
|
|
|
dev.write(f"smua.source.output = smua.OUTPUT_OFF")
|
2023-04-27 01:40:12 +02:00
|
|
|
print("Monitoring cancelled, measurement might still continue" + " "*50)
|
|
|
|
else:
|
|
|
|
print("Measurement finished" + " "*50)
|
2023-04-13 17:50:40 +02:00
|
|
|
|
2023-06-27 10:18:54 +02:00
|
|
|
def measure_count(count=5000, interval=None):
|
2023-04-27 01:40:12 +02:00
|
|
|
"""
|
|
|
|
Take <count> measurements in <interval>
|
|
|
|
|
|
|
|
@details:
|
|
|
|
- Resets the buffers
|
|
|
|
- Takes <count> measurements depending on settings["interval"]
|
|
|
|
Uses the device internal overlappedY measurement method, which allows for greater precision
|
|
|
|
You can take the data from the buffer afterwards, using save_csv
|
|
|
|
@param count: count
|
|
|
|
@param interval: interval, defaults to settings["interval"]
|
|
|
|
"""
|
2023-06-27 10:18:54 +02:00
|
|
|
if not interval: interval = settings["interval"]
|
2023-04-27 01:40:12 +02:00
|
|
|
update_func = _update_print
|
2023-04-13 17:50:40 +02:00
|
|
|
|
2023-04-27 01:40:12 +02:00
|
|
|
print(f"Starting measurement with:\n\tinterval = {interval}s\nSave the data using 'save_csv()' afterwards.")
|
2023-04-13 11:09:40 +02:00
|
|
|
try:
|
2023-06-18 17:38:10 +02:00
|
|
|
_measure.measure_count(dev, count=count, interval=interval, beep_done=False, verbose=False, update_func=update_func, update_interval=0.05)
|
2023-04-13 11:09:40 +02:00
|
|
|
except KeyboardInterrupt:
|
2023-06-18 17:38:10 +02:00
|
|
|
if args["keithley"]:
|
|
|
|
dev.write(f"smua.source.output = smua.OUTPUT_OFF")
|
2023-04-27 01:40:12 +02:00
|
|
|
print("Monitoring cancelled, measurement might still continue" + " "*50)
|
|
|
|
else:
|
|
|
|
print("Measurement finished" + " "*50)
|
|
|
|
|
2023-04-13 11:09:40 +02:00
|
|
|
|
|
|
|
|
2023-04-27 01:40:12 +02:00
|
|
|
|
2023-06-27 10:18:54 +02:00
|
|
|
def monitor(interval=None, max_measurements=None, max_points_shown=160):
|
2023-04-13 11:09:40 +02:00
|
|
|
"""
|
|
|
|
Monitor the voltage with matplotlib.
|
|
|
|
|
|
|
|
@details:
|
|
|
|
- Resets the buffers
|
|
|
|
- Opens a matplotlib window and takes measurements depending on settings["interval"]
|
|
|
|
- Waits for the user to press a key
|
2023-04-27 01:40:12 +02:00
|
|
|
Uses python's time.sleep() for waiting the interval, which is not very precise. Use measure_count for better precision.
|
|
|
|
You can take the data from the buffer afterwards, using save_csv.
|
2023-04-13 11:09:40 +02:00
|
|
|
@param max_points_shown : how many points should be shown at once. None means infinite
|
|
|
|
@param max_measurements : maximum number of measurements. None means infinite
|
2023-04-27 01:40:12 +02:00
|
|
|
"""
|
|
|
|
global _runtime_vars
|
|
|
|
_runtime_vars["last_measurement"] = dtime.now().isoformat()
|
2023-06-27 10:18:54 +02:00
|
|
|
if not interval: interval = settings["interval"]
|
2023-04-27 01:40:12 +02:00
|
|
|
print(f"Starting measurement with:\n\tinterval = {interval}s\nUse <C-c> to stop. Save the data using 'save_csv()' afterwards.")
|
|
|
|
plt_monitor = _Monitor(use_print=True, max_points_shown=max_points_shown)
|
|
|
|
update_func = plt_monitor.update
|
2023-06-18 17:38:10 +02:00
|
|
|
_measure.measure(dev, interval=interval, max_measurements=max_measurements, update_func=update_func)
|
2023-04-13 11:09:40 +02:00
|
|
|
|
|
|
|
|
2023-06-27 10:18:54 +02:00
|
|
|
def measure(interval=None, max_measurements=None):
|
2023-04-13 11:09:40 +02:00
|
|
|
"""
|
|
|
|
Measure voltages
|
|
|
|
|
|
|
|
@details:
|
|
|
|
- Resets the buffers
|
|
|
|
- Measure voltages
|
|
|
|
- Waits for the user to press a key
|
2023-04-27 01:40:12 +02:00
|
|
|
Uses python's time.sleep() for waiting the interval, which is not very precise. Use measure_count for better precision.
|
|
|
|
You can take the data from the buffer afterwards, using save_csv.
|
2023-04-13 11:09:40 +02:00
|
|
|
@param max_measurements : maximum number of measurements. None means infinite
|
2023-04-27 01:40:12 +02:00
|
|
|
"""
|
|
|
|
global _runtime_vars
|
2023-06-27 10:18:54 +02:00
|
|
|
if not interval: interval = settings["interval"]
|
2023-04-27 01:40:12 +02:00
|
|
|
_runtime_vars["last_measurement"] = dtime.now().isoformat()
|
|
|
|
print(f"Starting measurement with:\n\tinterval = {interval}s\nUse <C-c> to stop. Save the data using 'save_csv()' afterwards.")
|
|
|
|
update_func = _update_print
|
2023-06-18 17:38:10 +02:00
|
|
|
_measure.measure(dev, interval=interval, max_measurements=max_measurements, update_func=update_func)
|
2023-04-13 11:09:40 +02:00
|
|
|
|
2023-04-27 01:40:12 +02:00
|
|
|
|
|
|
|
def repeat(measure_func: callable, count: int, repeat_delay=0):
|
2023-04-16 17:12:16 +02:00
|
|
|
"""
|
|
|
|
Measure and save to csv multiple times
|
2023-04-27 01:40:12 +02:00
|
|
|
|
|
|
|
@details
|
|
|
|
Repeat count times:
|
|
|
|
- call measure_func
|
|
|
|
- call save_csv
|
|
|
|
- sleep for repeat_delay
|
|
|
|
|
|
|
|
@param measure_func: The measurement function to use. Use a lambda to bind your parameters!
|
|
|
|
@param count: Repeat count times
|
|
|
|
|
|
|
|
Example: Repeat 10 times:
|
|
|
|
repeat(lambda : monitor_count(count=6000, interval=0.02, max_points_shown=200), 10)
|
2023-04-16 17:12:16 +02:00
|
|
|
"""
|
2023-04-27 01:40:12 +02:00
|
|
|
try:
|
|
|
|
for _ in range(count):
|
|
|
|
measure_func()
|
|
|
|
save_csv()
|
|
|
|
sleep(repeat_delay)
|
|
|
|
except KeyboardInterrupt:
|
|
|
|
pass
|
2023-06-18 17:38:10 +02:00
|
|
|
if settings["beep"]: _backend.beep()
|
2023-04-16 17:12:16 +02:00
|
|
|
|
2023-04-13 11:09:40 +02:00
|
|
|
|
|
|
|
def get_dataframe():
|
2023-04-13 17:50:40 +02:00
|
|
|
"""
|
2023-04-27 01:40:12 +02:00
|
|
|
Get a pandas dataframe from the data in smua.nvbuffer1 and smua.nvbuffer2
|
2023-04-13 17:50:40 +02:00
|
|
|
"""
|
2023-04-13 11:09:40 +02:00
|
|
|
global k, settings, _runtime_vars
|
2023-06-18 17:38:10 +02:00
|
|
|
ibuffer = _backend.collect_buffer(dev, 1)
|
|
|
|
vbuffer = _backend.collect_buffer(dev, 2)
|
2023-04-13 17:50:40 +02:00
|
|
|
df = _data.buffers2dataframe(ibuffer, vbuffer)
|
2023-04-13 11:09:40 +02:00
|
|
|
df.basename = file_io.get_next_filename(settings["name"], settings["datadir"])
|
|
|
|
df.name = f"{df.basename} @ {_runtime_vars['last-measurement']}"
|
|
|
|
return df
|
|
|
|
|
2023-06-18 17:38:10 +02:00
|
|
|
|
2023-04-13 11:09:40 +02:00
|
|
|
def save_csv():
|
|
|
|
"""
|
|
|
|
Saves the contents of nvbuffer1 as .csv
|
|
|
|
The settings 'datadir' and 'name' are used for determining the filepath:
|
|
|
|
'datadir/nameXXX.csv', where XXX is the number of files that exist in datadir with the same name.
|
|
|
|
"""
|
|
|
|
df = get_dataframe()
|
|
|
|
filename = settings["datadir"] + "/" + df.basename + ".csv"
|
|
|
|
df.to_csv(filename, index=False, header=True)
|
|
|
|
print(f"Saved as '{filename}'")
|
|
|
|
|
|
|
|
|
|
|
|
def save_pickle():
|
|
|
|
"""
|
|
|
|
Saves the contents of nvbuffer1 as .pkl
|
|
|
|
The settings 'datadir' and 'name' are used for determining the filepath:
|
|
|
|
'datadir/nameXXX.pkl', where XXX is the number of files that exist in datadir with the same name.
|
|
|
|
"""
|
|
|
|
df = get_dataframe()
|
|
|
|
filename = settings["datadir"] + "/" + df.basename + ".pkl"
|
|
|
|
df.to_pickle(filename)
|
|
|
|
print(f"Saved as '{filename}'")
|
|
|
|
|
2023-06-18 17:38:10 +02:00
|
|
|
|
2023-04-13 11:09:40 +02:00
|
|
|
def run_script(script_path):
|
|
|
|
"""
|
|
|
|
Run a lua script on the Keithley device
|
|
|
|
@param script_path : relative or absolute path to the .lua script
|
|
|
|
"""
|
|
|
|
global k, settings
|
|
|
|
if test:
|
|
|
|
print("run_script: Test mode enabled, ignoring call to run_script")
|
|
|
|
else:
|
2023-06-18 17:38:10 +02:00
|
|
|
_keithley.run_lua(dev, script_path=script_path)
|
2023-04-13 11:09:40 +02:00
|
|
|
|
|
|
|
|
|
|
|
def set(setting, value):
|
|
|
|
global settings, config_path
|
|
|
|
if setting in settings:
|
|
|
|
if type(value) != type(settings[setting]):
|
|
|
|
print(f"set: setting '{setting}' currently holds a value of type '{type(settings[setting])}'")
|
|
|
|
return
|
|
|
|
settings[setting] = value
|
|
|
|
|
2023-04-13 17:50:40 +02:00
|
|
|
def name(s:str):
|
|
|
|
global settings
|
|
|
|
settings["name"] = s
|
2023-04-13 11:09:40 +02:00
|
|
|
|
|
|
|
def save_settings():
|
|
|
|
with open(config_path, "w") as file:
|
|
|
|
json.dump(settings, file, indent=4)
|
|
|
|
|
|
|
|
def load_settings():
|
|
|
|
global settings, config_path
|
|
|
|
with open(config_path, "r") as file:
|
|
|
|
settings = json.load(file)
|
2023-04-27 01:40:12 +02:00
|
|
|
settings["datadir"] = path.expanduser(settings["datadir"]) # replace ~
|
2023-04-13 11:09:40 +02:00
|
|
|
|
|
|
|
def help(topic=None):
|
|
|
|
if topic == None:
|
|
|
|
print("""
|
|
|
|
Functions:
|
2023-06-24 12:28:12 +02:00
|
|
|
measure [kat] - take measurements
|
|
|
|
monitor [kat] - take measurements with live monitoring in a matplotlib window
|
|
|
|
measure_count [kat] - take a fixed number of measurements
|
|
|
|
monitor_count [kat] - take a fixed number of measurements with live monitoring in a matplotlib window
|
|
|
|
repeat [kat] - measure and save to csv multiple times
|
|
|
|
get_dataframe [kat] - return device internal buffer as pandas dataframe
|
|
|
|
save_csv [kat] - save the last measurement as csv file
|
|
|
|
save_pickle [kat] - save the last measurement as pickled pandas dataframe
|
|
|
|
load_dataframe [kat] - load a pandas dataframe from csv or pickle
|
|
|
|
run_script [k ] - run a lua script on the Keithely device
|
2023-04-13 11:09:40 +02:00
|
|
|
Run 'help(function)' to see more information on a function
|
|
|
|
|
|
|
|
Available topics:
|
|
|
|
imports
|
|
|
|
device
|
|
|
|
settings
|
|
|
|
Run 'help("topic")' to see more information on a topic""")
|
|
|
|
|
|
|
|
elif topic in [settings, "settings"]:
|
|
|
|
print("""Settings:
|
|
|
|
name: str - name of the measurement, determines filename of 'save_csv'
|
|
|
|
datadir: str - output directory for the csv files
|
|
|
|
interval: int - interval (inverse frequency) of the measurements, in seconds
|
|
|
|
beep: bool - wether the device should beep or not
|
|
|
|
|
|
|
|
Functions:
|
2023-04-13 17:50:40 +02:00
|
|
|
name("<name>") - short for set("name", "<name>")
|
|
|
|
set("setting", value) - set a setting to a value
|
2023-06-18 17:38:10 +02:00
|
|
|
save_settings() - store the settings as "m-teng.json" in the working directory
|
2023-04-13 17:50:40 +02:00
|
|
|
load_settings() - load settings from a file
|
2023-04-13 11:09:40 +02:00
|
|
|
The global variable 'config_path' determines the path used by save/load_settings. Use -c '<path>' to set another path.
|
|
|
|
The serach path is:
|
2023-06-18 17:38:10 +02:00
|
|
|
<working-dir>/m-teng.json
|
|
|
|
$XDG_CONFIG_HOME/m-teng.json
|
|
|
|
~/.config/m-teng.json
|
2023-04-13 11:09:40 +02:00
|
|
|
""")
|
|
|
|
elif topic == "imports":
|
|
|
|
print("""Imports:
|
|
|
|
numpy as np
|
|
|
|
pandas as pd
|
|
|
|
matplotlib.pyplot as plt
|
|
|
|
os.path """)
|
|
|
|
elif topic == "device":
|
|
|
|
print("""Device:
|
2023-06-24 12:28:12 +02:00
|
|
|
keithley backend:
|
|
|
|
The opened pyvisa resource (deveithley device) is the global variable 'dev'.
|
|
|
|
You can interact using pyvisa functions, such as
|
|
|
|
k.write("command"), k.query("command") etc. to interact with the device.
|
|
|
|
arduino backend:
|
|
|
|
The Arduino will be avaiable as BleakClient using the global variable 'dev'. """)
|
2023-04-13 11:09:40 +02:00
|
|
|
else:
|
|
|
|
print(topic.__doc__)
|
|
|
|
|
|
|
|
|
|
|
|
def init():
|
2023-06-18 17:38:10 +02:00
|
|
|
global dev, settings, config_path
|
|
|
|
print(r""" ______________________ _______ ________
|
|
|
|
_____ \__ ___/\_ _____/ \ \ / _____/
|
|
|
|
/ \ ______| | | __)_ / | \ / \ ___
|
|
|
|
| Y Y \/_____/| | | \/ | \\ \_\ \
|
|
|
|
|__|_| / |____| /_______ /\____|__ / \______ /
|
|
|
|
\/ \/ \/ \/ 1.2
|
2023-04-13 11:09:40 +02:00
|
|
|
Interactive Shell for TENG measurements with Keithley 2600B
|
|
|
|
---
|
|
|
|
Enter 'help()' for a list of commands""")
|
|
|
|
from os import environ
|
2023-06-18 17:38:10 +02:00
|
|
|
if path.isfile("m-teng.json"):
|
|
|
|
config_path = "m-teng.json"
|
2023-04-13 11:09:40 +02:00
|
|
|
elif 'XDG_CONFIG_HOME' in environ.keys():
|
2023-06-18 17:38:10 +02:00
|
|
|
# and path.isfile(environ["XDG_CONFIG_HOME"] + "/m-teng.json"):
|
|
|
|
config_path = environ["XDG_CONFIG_HOME"] + "/m-teng.json"
|
2023-04-13 11:09:40 +02:00
|
|
|
else:
|
2023-06-18 17:38:10 +02:00
|
|
|
config_path = path.expanduser("~/.config/m-teng.json")
|
|
|
|
if args["config"]:
|
|
|
|
config_path = args["config"]
|
2023-04-13 11:09:40 +02:00
|
|
|
|
|
|
|
|
|
|
|
if not path.isdir(path.dirname(config_path)):
|
|
|
|
makedirs(path.dirname(config_path))
|
|
|
|
|
|
|
|
if path.isfile(config_path):
|
|
|
|
load_settings()
|
|
|
|
|
|
|
|
if not path.isdir(settings["datadir"]):
|
|
|
|
makedirs(settings["datadir"])
|
|
|
|
|
2023-06-18 17:38:10 +02:00
|
|
|
try:
|
|
|
|
dev = _backend.init(beep_success=settings["beep"])
|
|
|
|
except Exception as e:
|
|
|
|
print(e)
|
|
|
|
exit(1)
|
2023-06-24 12:28:12 +02:00
|
|
|
atexit.register(_backend.exit, dev)
|
2023-04-13 11:09:40 +02:00
|
|
|
|
|
|
|
|
|
|
|
if __name__ == "__main__":
|
|
|
|
init()
|