ddplot

一个gps小工具包

            ddr = float(words[10])
            h = int(words[11],16)
            # not adding health to the dataLists, this can be changed though
            
            if ordType[0:2] == "L1":
                # get all of this general epoch info from the C/A line only
                if ordType[3:6] == "C/A":
                    dataListL1[0].append(t)
                    dataListL1[1].append(ddr)
                    dataListL1[5].append(sv1)
                    dataListL1[6].append(elev1)
                    dataListL1[7].append(sv2)
                    dataListL1[8].append(elev2)
                elif ordType[5:12] == "range":  #this will be the L1 P/Y/W range
                    dataListL1[2].append(ddr)
                elif ordType[5:12] == "phase":
                    dataListL1[3].append(ddr)
                elif ordType[5:12] == "doppler":
                    dataListL1[4].append(ddr)
                else:
                    if (options.debugLevel):
                        print "Didn't understand this line:"
                        print line
            elif ordType[0:2] == "L2":
                # get all of the general epoch info from the range line only
                if ordType[5:12] == "range":
                    dataListL2[0].append(t)
                    dataListL2[1].append(ddr)
                    dataListL2[4].append(sv1)
                    dataListL2[5].append(elev1)
                    dataListL2[6].append(sv2)
                    dataListL2[7].append(elev2)
                elif ordType[5:12] == "phase":
                    dataListL2[2].append(ddr)
                elif ordType[5:12] == "doppler":
                    dataListL2[3].append(ddr)
                else:
                    if (options.debugLevel):
                        print "Didn't understand this line:"
                        print line           

    dataL1 = numpy.array(dataListL1)
    dataL2 = numpy.array(dataListL2)
    avergs = numpy.array(avergsList)
    
    del dataListL1, dataListL2, avergsList
    
    # make sure that there is some data to plot
    if (plotL1 and dataL1.shape[1] < 1):
        print "\n No L1 data to plot. Exiting...\n"
        exit;
    if (plotL2 and dataL2.shape[1] < 1):
        print "\n No L2 data to plot. Exiting...\n"
        exit;
    if (plotAvg and avergs.shape[1] < 1):
        print "\n No averages to plot. Exiting...\n"
        exit;    

    # done reading in the ord file

    # A key handler for matplotlib
    def press(event):
        if event.key=='q' or event.key==' ':
            pylab.close()

    # Here we start generating the plots
    fig = pylab.figure()
    pylab.connect('key_press_event', press)
    yprops = dict(rotation=90, horizontalalignment='right', verticalalignment='center', family='monospace', x=-0.01)
    scale_props = dict(horizontalalignment="right", verticalalignment="bottom", size=8, family="sans-serif") 

    xMajorFmt=pylab.DateFormatter("%02H:%02M\n%03j")
    xMinorFmt=pylab.NullFormatter()
    xMajorLoc=matplotlib.dates.DayLocator()
    xMinorLoc=matplotlib.dates.HourLocator()

    rExtent=0.89
    if options.legend:
        rExtent=0.80
        
    ax1 = fig.add_axes([0.08, 0.10, rExtent, 0.85])
    # experimented with alpha blending on the plot, but couldn't find anything that really helped
    
    # i know this looks rediculous, just trying to control the plotting order
    if plotL1:
        if plotRange:
            if (options.plotAverages < 2):
                ax1.plot_date(dataL1[0], dataL1[1], ',', color="r", label="C/A range")
                ax2=fig.add_axes(ax1.get_position())
                ax2.plot_date(dataL1[0], dataL1[2], ',', color="purple", label="L1 P/Y range")
                
        if plotPhase:
            if (options.plotAverages < 2):
                ax3=fig.add_axes(ax1.get_position())
                ax3.plot_date(dataL1[0], dataL1[3], ',', color="#FF6600", label="L1 P/Y phase")
                
        if plotDoppl:
            if (options.plotAverages < 2):
                ax4=fig.add_axes(ax1.get_position())
                ax4.plot_date(dataL1[0], dataL1[4], ',', color="navy", label="L1 P/Y doppler")
    
    if plotL2:
        if plotRange:
            if (options.plotAverages < 2):
                ax4=fig.add_axes(ax1.get_position())
                ax4.plot_date(dataL2[0], dataL2[1], ',', color="forestgreen", label="L2 P/Y range")
        if plotPhase:
            if (options.plotAverages < 2):
                ax5=fig.add_axes(ax1.get_position())
                ax5.plot_date(dataL2[0], dataL2[2], ',', color="darkslategray", label="L2 P/Y phase")
        if plotDoppl:
            if (options.plotAverages < 2):
                ax6=fig.add_axes(ax1.get_position())
                ax6.plot_date(dataL2[0], dataL2[3], ',', color="teal", label="L2 P/Y doppler")
    
                
    if plotL1 and plotAvg:
        if plotRange:
            ax7=fig.add_axes(ax1.get_position())
            ax7.plot_date(avergs[0], avergs[1], 'o', color="r", label="C/A rng avg")
            ax8=fig.add_axes(ax1.get_position())
            ax8.plot_date(avergs[0], avergs[2], 'o', color="purple", label="L1 P/Y rng avg")
        if plotPhase:
            ax9=fig.add_axes(ax1.get_position())
            ax9.plot_date(avergs[0], avergs[3], 'o', color="#FF6600", label="L1 P/Y ph avg")
        if plotDoppl:
            ax10=fig.add_axes(ax1.get_position())
            ax10.plot_date(avergs[0], avergs[4], 'o', color="navy", label="L1 P/Y dop avg") 
            
    if plotL2 and plotAvg:
        if plotRange:
            ax11=fig.add_axes(ax1.get_position())
            ax11.plot_date(avergs[0], avergs[5], 'o', color="forestgreen", label="L2 P/Y rng avg")
        if plotPhase:
            ax12=fig.add_axes(ax1.get_position())
            ax12.plot_date(avergs[0], avergs[6], 'o', color="darkslategray", label="L2 P/Y ph avg")
        if plotDoppl: 
            ax13=fig.add_axes(ax1.get_position())
            ax13.plot_date(dataL2[0], dataL2[7], 'o', color="teal", label="L2 P/Y dop avg")
            
            
    if options.legend:
        ax1.legend(numpoints=2, pad=0.1, labelsep = 0, handlelen=0.005, handletextsep=0.01, axespad=0.0, loc=(1,0))
        leg = pylab.gca().get_legend()
        ltext = leg.get_texts()
        llines = leg.get_lines()
        lframe = leg.get_frame()
        lframe.set_facecolor('0.4')
        pylab.setp(ltext, size=8, family="sans-serif")
        pylab.setp(llines, linewidth=2)
        leg.draw_frame(False)

    ax1.set_ylabel('Double Difference (meters)', **yprops)
    ax1.grid(True)
    if options.yRange:
        ax1.set_ylim(ymin=-options.yRange, ymax=options.yRange)
    else:
        pylab.figtext(rExtent+.08, 0.95, "y range autoscaled", **scale_props)
    ax1.xaxis.set_major_formatter(xMajorFmt)
    xlabels=ax1.get_xticklabels()
    ylabels=ax1.get_yticklabels()
    pylab.setp(xlabels, fontsize=10, family='sans-serif')
    pylab.setp(ylabels, fontsize=10, family='sans-serif')
    ax1.xaxis.set_minor_formatter(xMinorFmt)

    # set x axis range
    if options.tStart:
      tMin = parse_time(options.tStart.split()[0:3])
    else:
      tMin = min(dataL1[0])

    if options.tEnd:
      tMax = parse_time(options.tEnd.split()[0:3])
    else:
      tMax = max(dataL1[0])

    ax1.set_xlim(xmin=tMin, xmax=tMax)
    ax1.set_title(options.title)

    if (options.saveFig == None):
        pylab.show()
    else:
       pylab.savefig(options.saveFig)
# end of main


def parse_time(words):
    fsec = float(words[2][8:10])
    ydhms =  words[0]+" "+words[1]+" "+words[2][0:8]
    utime = time.strptime(ydhms, "%Y %j %H:%M:%S")
    dtime = datetime.datetime(utime[0], utime[1], utime[2],
                              utime[3], utime[4], utime[5], int(fsec*1e6))
    t0 = matplotlib.dates.date2num(dtime)
    return t0
# end of parse_time()

    
if __name__ == "__main__":
    main()