Mario Fink
83922c343f
* imc_object: asc_time, localtime: make threadsafe * imc_datatype: satisfy 'rule of two' * python: remove all unused imports
138 lines
4.5 KiB
Python
138 lines
4.5 KiB
Python
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#-----------------------------------------------------------------------------#
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import raw_eater
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import raw_meat
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import pyarrow as pa
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import pyarrow.parquet as pq
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from pathlib import Path
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fileobj1 = Path("smp/Rangerover_Evoque_F-RR534_2019-05-07/").rglob("*.raw")
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rawlist1 = [str(fl) for fl in fileobj1]
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fileobj2 = Path("smp/Mercedes_E-Klasse-2019-08-08/").rglob("*.raw")
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rawlist2 = [str(fl) for fl in fileobj2]
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rawlist = rawlist1 #[rawlist1[0],rawlist1[4],rawlist2[0],rawlist2[6]]
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for fil in rawlist2 :
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rawlist.append(fil)
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rawlist.append("smp/pressure_Vacuum.asc")
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print("")
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print(rawlist)
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print()
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#-----------------------------------------------------------------------------#
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# alternatively create "empty" instance of "raw_eater" and set file names
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eatraw = raw_eater.raweater()
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# eatraw.set_file("../smp/pressure_Vacuum.raw".encode())
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# convert every single listed file
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for rf in rawlist :
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print("converting " + str(rf) + "...\n" + 90*("-") + "\n")
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# setup instance of "raw_eater" and trigger conversion
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# eatraw = raw_eater.raweater(rf.encode())
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# eatraw = raw_meat.rawmerger(rf.encode())
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# use global instance of "raw_eater" to set file and perform decoding
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eatraw.set_file(rf.encode())
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try :
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eatraw.do_conversion()
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except RuntimeError as e :
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print("conversion failed: " + str(e))
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# check validity of file format
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if eatraw.validity() :
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# show channel name and its unit
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entity = eatraw.channel_name().decode(encoding='UTF-8',errors='ignore')
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unit = eatraw.unit().decode(encoding='UTF-8',errors='ignore')
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print("\nentity: " + str(entity))
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print("unit: " + str(unit) + "\n")
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# obtain extracted data
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xt = eatraw.get_time()
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yt = eatraw.get_channel()
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# show excerpt of data
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print("time (length: " + str(len(xt)) + ") \n"
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+ str(xt[:10]) + "\n...\n" + str(xt[-10:]) + "\n")
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yttrunc = [round(y,4) for y in yt]
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print(str(entity) + " (length: " + str(len(yttrunc)) + ") \n"
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+ str(yttrunc[:10]) + "\n...\n" + str(yttrunc[-10:]) + "\n")
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outname = rf.split('/')[-1].replace('raw','csv')
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print("write output to : " + outname)
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eatraw.write_table(("output/"+outname).encode(),ord(' '))
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else :
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print("\nerror: invalid/corrupt .raw file")
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print("\n")
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#-----------------------------------------------------------------------------#
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print("convert and merge channels " + "\n" + 90*("-") + "\n")
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# setup new instance to merge channels
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eatmea = raw_meat.rawmerger(''.encode()) #rawlist[0].encode())
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# add every single channel/file in list
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for rf in rawlist :
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print("\nadding channel " + str(rf))
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try :
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succ = eatmea.add_channel(rf.encode())
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print("\nrecent time series: length: " + str(len(eatmea.get_time_series())) + "\n")
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except RuntimeError as e :
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print("failed to add channel: " + str(e))
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# show summary of successfully merged channels
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print("\nmerged channels:\n")
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# write merged table to .csv output
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eatmea.write_table_all('output/allchannels.csv'.encode(),ord(','))
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# get number of successfully merged channels and their names (+units)
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numch = eatmea.get_num_channels()
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chnames = [chnm.decode(encoding='UTF-8',errors='ignore') for chnm in eatmea.get_channel_names()]
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print("number of channels: " + str(numch))
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print("channel names: " + str(chnames))
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# obtain final time series
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timse = eatmea.get_time_series()
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print("\nfinal time series:\nlength:" + str(len(timse)) + "\n")
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# get time unit and prepend column name
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chnames.insert(0,"Time ["+str(eatmea.time_unit().decode(encoding='UTF-8',errors='ignore'))+"]")
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# prepare list of pyarrow arrays
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pyarrs = []
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pyarrs.append(pa.array(timse))
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for i in range(0,numch) :
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print("\n" + str(i) + " " + str(chnames[i]))
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dat = eatmea.get_channel_by_index(i)
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print("length: " + str(len(dat)))
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pyarrs.append(pa.array(dat))
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print("")
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# print("\npyarrow arrays\n" + str(pyarrs))
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# create pyarrow table from data
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pyarwtab = pa.Table.from_arrays(pyarrs,chnames)
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print("\n" + 60*"-" + "\n" + str(pyarwtab) + "\n")
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# write pyarrow table to .parquet file with compression
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pq.write_table(pyarwtab,'output/allchannels.parquet',compression='BROTLI') # compression='BROTLI', 'SNAPPY')
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# try to read and decode the .parquet file
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df = pq.read_table('output/allchannels.parquet')
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print(df.to_pandas())
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# df.to_pandas().to_csv('allchannels.csv',index=False,encoding='utf-8',sep=",")
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#-----------------------------------------------------------------------------#
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