plot.py 文件源码

def doit(csvfile):
    sensordata=[]
    timestamplist=[]
    if 1:#with open(fname, 'rb') as csvfile:

        for t in range(args.skip_lines): csvfile.readline()

        reader = csv.reader(csvfile, delimiter=args.delimiter)
        for a in reader:

            if a==[]: continue # empty line            
            try:
                values = [float(t.replace(',','.')) for t in a if t !='']
            except Exception,e:
                print a, e
                continue

            if args.columns:
                values = [values[t] for t in args.columns]

            if args.timestamps:
                sensordata.append(values[1:])
                timestamplist.append(values[0])

            else: 
                sensordata.append(values)


        if args.histogram:
            import matplotlib.mlab as mlab
            mu = mlab.np.average(sensordata)
            sigma = max(abs(mlab.np.max(sensordata)- mu), abs(mlab.np.min(sensordata)- mu))

            # the histogram of the data
            n, bins, patches = pylab.hist(mlab.np.array(sensordata), 100, normed=True, facecolor='green', alpha=0.75)

            pylab.grid()
            pylab.show()

        if args.output_file_name:
            outfile = open(args.output_file_name,'w')
            for line in sensordata:
                outfile.write(args.output_delimiter.join([args.output_formatter % round(t*args.output_multiplier) for t in line])+'\n')
        else:

            if timestamplist!=[]: # data with timestamp
                pylab.plot(timestamplist, sensordata, args.tick_mark)
                pylab.xlabel('time')
            else:
                pylab.plot(sensordata, args.tick_mark)
                pylab.xlabel('sample #')

            pylab.title(csvfile.name)

            if args.legend:
                pylab.legend(args.legend)

            pylab.grid()
            pylab.show()