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4 Commits
Author | SHA1 | Date | |
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55f093156d | |||
ff69c329cc | |||
d0accd6e0b | |||
89b7f045a4 |
@@ -318,16 +318,16 @@ namespace imc
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// convert buffer to actual datatype
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// convert buffer to actual datatype
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void convert_buffer()
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void convert_buffer()
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{
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{
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// TODO no clue how/if/when to handle buffer offset/mask/subsequent_bytes
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// etc. and whatever that shit is!
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std::vector<imc::parameter> prms = blocks_->at(chnenv_.CSuuid_).get_parameters();
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std::vector<imc::parameter> prms = blocks_->at(chnenv_.CSuuid_).get_parameters();
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if ( prms.size() < 4)
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if ( prms.size() < 4)
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{
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{
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throw std::runtime_error("CS block is invalid and features to few parameters");
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throw std::runtime_error("CS block is invalid and features to few parameters");
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}
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}
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// extract (channel dependent) part of buffer
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unsigned long int buffstrt = prms[3].begin();
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unsigned long int buffstrt = prms[3].begin();
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std::vector<unsigned char> CSbuffer( buffer_->begin()+buffstrt+1,
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std::vector<unsigned char> CSbuffer( buffer_->begin()+buffstrt+buffer_offset_+1,
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buffer_->begin()+buffstrt+buffer_size_+1 );
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buffer_->begin()+buffstrt+buffer_offset_+buffer_size_+1 );
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// determine number of values in buffer
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// determine number of values in buffer
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unsigned long int num_values = (unsigned long int)(CSbuffer.size()/(signbits_/8));
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unsigned long int num_values = (unsigned long int)(CSbuffer.size()/(signbits_/8));
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@@ -2,3 +2,4 @@ include lib/*.hpp
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include *.cpp
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include *.cpp
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include *.pyx
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include *.pyx
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include *.pxd
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include *.pxd
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include VERSION
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@@ -1 +1 @@
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2.0.6
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2.0.8
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43
python/examples/multichannel.py
Normal file
43
python/examples/multichannel.py
Normal file
@@ -0,0 +1,43 @@
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import IMCtermite
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import pandas
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import datetime
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def add_trigger_time(trigger_time, add_time) :
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trgts = datetime.datetime.strptime(trigger_time,'%Y-%m-%dT%H:%M:%S')
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dt = datetime.timedelta(seconds=add_time)
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return (trgts + dt).strftime('%Y-%m-%dT%H:%M:%S:%f')
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if __name__ == "__main__" :
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# read file and extract data
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imctm = IMCtermite.imctermite(b"Measurement.raw")
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chns = imctm.get_channels(True)
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# prepare abscissa
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xcol = "time ["+chns[0]['xunit']+"]"
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#xcol = "timestamp"
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xsts = [add_trigger_time(chns[0]['trigger-time'],tm) for tm in chns[0]['xdata']]
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# sort channels
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chnnms = sorted([chn['name'] for chn in chns], reverse=False)
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chnsdict = {}
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for chn in chns :
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chnsdict[chn['name']] = chn
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# construct dataframe
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df = pandas.DataFrame()
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df[xcol] = pandas.Series(chns[0]['xdata'])
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#df[xcol] = pandas.Series(xsts)
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#for idx,chn in enumerate(chns) :
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for chnnm in chnnms :
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chn = chnsdict[chnnm]
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#xcol = (chn['xname'] if chn['xname'] != '' else "x_"+str(idx))+" ["+chn['xunit']+"]"
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#df[xcol] = pandas.Series(chn['xdata'])
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ycol = chn['yname']+" ["+chn['yunit']+"]"
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df[ycol] = pandas.Series(chn['ydata'])
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# show entire dataframe and write file
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print(df)
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df.to_csv("Measurement.csv",header=True,sep='\t',index=False)
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