70 lines
1.8 KiB
Python
70 lines
1.8 KiB
Python
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import multiprocessing
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from multiprocessing import Queue
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from datetime import datetime
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import time
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class serialworker(multiprocessing.Process):
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def __init__ (self, device, df, buffer_length = 10, raster = 0.2, verbose = True):
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multiprocessing.Process.__init__(self)
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self.input = Queue()
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self.output = Queue()
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self.device = device
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self.columns = list(df.columns.values)
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self.dataframe = df
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self.example = df.set_index('Time')
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self.buffer_length = buffer_length
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self.verbose = verbose
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self.raster = raster
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self.std_out(f'Initialised serial worker for device on port {self.device.serialPort_name}. Buffering {self.buffer_length} samples')
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def std_out(self, msg):
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if self.verbose: print (msg)
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def run(self):
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import pandas as pd
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import numpy as np
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count_buffer = 0
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self.device.flush()
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last = datetime.now()
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while True:
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if not self.input.empty():
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task = self.input.get()
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if task == "stop":
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self.std_out('Terminating serialworker')
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self.terminate()
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self.join()
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time.sleep(0.1)
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if not self.is_alive():
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self.std_out('Time out set to 1')
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self.join(timeout=1.0)
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self.input.close()
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break
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now = datetime.now()
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data = self.device.read_line()
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if (now - last).total_seconds() > self.raster:
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last = now
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if 'Time' in self.columns:
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if len(data) < len (self.columns): data.insert(0, pd.to_datetime(now))
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else: data[0] = pd.to_datetime(data[0])
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try: data[1:] = list(map(float, data[1:]))
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except: data[1:] = [np.nan]; pass
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df_stream = pd.DataFrame([data[:]], columns = self.columns)
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self.dataframe = pd.concat([self.dataframe, df_stream], sort=False)
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count_buffer += 1
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if count_buffer == self.buffer_length:
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self.output.put(self.dataframe)
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count_buffer = 0
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self.dataframe = self.example
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