| @@ -307,7 +307,7 class CrossSpectraPlot(Figure): | |||||
| 307 | z = dataOut.data_spc[:,:,:]/factor |
|
307 | z = dataOut.data_spc[:,:,:]/factor | |
| 308 | # z = numpy.where(numpy.isfinite(z), z, numpy.NAN) |
|
308 | # z = numpy.where(numpy.isfinite(z), z, numpy.NAN) | |
| 309 | avg = numpy.abs(numpy.average(z, axis=1)) |
|
309 | avg = numpy.abs(numpy.average(z, axis=1)) | |
| 310 |
noise = dataOut.noise |
|
310 | noise = dataOut.noise/factor | |
| 311 |
|
311 | |||
| 312 | zdB = 10*numpy.log10(z) |
|
312 | zdB = 10*numpy.log10(z) | |
| 313 | avgdB = 10*numpy.log10(avg) |
|
313 | avgdB = 10*numpy.log10(avg) | |
| @@ -1053,7 +1053,7 class Noise(Figure): | |||||
| 1053 | x = dataOut.getTimeRange() |
|
1053 | x = dataOut.getTimeRange() | |
| 1054 | y = dataOut.getHeiRange() |
|
1054 | y = dataOut.getHeiRange() | |
| 1055 | factor = dataOut.normFactor |
|
1055 | factor = dataOut.normFactor | |
| 1056 |
noise = dataOut.noise |
|
1056 | noise = dataOut.noise/factor | |
| 1057 | noisedB = 10*numpy.log10(noise) |
|
1057 | noisedB = 10*numpy.log10(noise) | |
| 1058 |
|
1058 | |||
| 1059 | #thisDatetime = dataOut.datatime |
|
1059 | #thisDatetime = dataOut.datatime | |
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