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1 | 1 | import numpy |
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2 | 2 | |
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3 | 3 | class AMISR: |
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4 | 4 | def __init__(self): |
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5 | 5 | self.flagNoData = True |
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6 | 6 | self.data = None |
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7 | 7 | self.utctime = None |
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8 | 8 | self.type = "AMISR" |
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9 | 9 | |
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10 | 10 | #propiedades para compatibilidad con Voltages |
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11 | 11 | self.timeZone = 0#timezone like jroheader, difference in minutes between UTC and localtime |
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12 | 12 | self.dstFlag = 0#self.dataIn.dstFlag |
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13 | 13 | self.errorCount = 0#self.dataIn.errorCount |
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14 | 14 | self.useLocalTime = True#self.dataIn.useLocalTime |
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15 | 15 | |
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16 | 16 | self.radarControllerHeaderObj = None#self.dataIn.radarControllerHeaderObj.copy() |
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17 | 17 | self.systemHeaderObj = None#self.dataIn.systemHeaderObj.copy() |
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18 | 18 | self.channelList = [0]#self.dataIn.channelList esto solo aplica para el caso de AMISR |
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19 | 19 | self.dtype = numpy.dtype([('real','<f4'),('imag','<f4')]) |
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20 | 20 | |
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21 | 21 | self.flagTimeBlock = None#self.dataIn.flagTimeBlock |
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22 | 22 | #self.utctime = #self.firstdatatime |
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23 | 23 | self.flagDecodeData = None#self.dataIn.flagDecodeData #asumo q la data esta decodificada |
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24 | 24 | self.flagDeflipData = None#self.dataIn.flagDeflipData #asumo q la data esta sin flip |
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25 | 25 | |
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26 | 26 | self.nCohInt = 1#self.dataIn.nCohInt |
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27 | 27 | self.nIncohInt = 1 |
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28 | 28 | self.ippSeconds = None#self.dataIn.ippSeconds, segun el filename/Setup/Tufile |
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29 | 29 | self.windowOfFilter = None#self.dataIn.windowOfFilter |
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30 | 30 | |
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31 | 31 | self.timeInterval = None#self.dataIn.timeInterval*self.dataOut.nFFTPoints*self.dataOut.nIncohInt |
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32 | 32 | self.frequency = None#self.dataIn.frequency |
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33 | 33 | self.realtime = 0#self.dataIn.realtime |
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34 | 34 | |
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35 | 35 | #actualizar en la lectura de datos |
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36 | 36 | self.heightList = None#self.dataIn.heightList |
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37 | 37 | self.nProfiles = None#Number of samples or nFFTPoints |
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38 | 38 | self.nRecords = None |
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39 | 39 | self.nBeams = None |
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40 | 40 | self.nBaud = None#self.dataIn.nBaud |
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41 | 41 | self.nCode = None#self.dataIn.nCode |
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42 | 42 | self.code = None#self.dataIn.code |
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43 | 43 | |
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44 | 44 | #consideracion para los Beams |
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45 | 45 | self.beamCodeDict = None |
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46 | 46 | self.beamRangeDict = None |
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47 | ||
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47 | self.beamcode = None | |
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48 | self.azimuth = None | |
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49 | self.zenith = None | |
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50 | self.gain = None | |
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51 | ||
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48 | 52 | self.npulseByFrame = None |
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49 | 53 | |
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50 | 54 | def copy(self, inputObj=None): |
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51 | 55 | |
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52 | 56 | if inputObj == None: |
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53 | 57 | return copy.deepcopy(self) |
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54 | 58 | |
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55 | 59 | for key in inputObj.__dict__.keys(): |
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56 | 60 | self.__dict__[key] = inputObj.__dict__[key] |
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57 | 61 | |
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58 | 62 | |
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59 | 63 | def isEmpty(self): |
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60 | 64 | |
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61 | 65 | return self.flagNoData No newline at end of file |
| @@ -1,736 +1,740 | |||
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1 | 1 | ''' |
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2 | 2 | |
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3 | 3 | $Author: murco $ |
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4 | 4 | $Id: JROData.py 173 2012-11-20 15:06:21Z murco $ |
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5 | 5 | ''' |
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6 | 6 | |
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7 | 7 | import copy |
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8 | 8 | import numpy |
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9 | 9 | import datetime |
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10 | 10 | |
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11 | 11 | from jroheaderIO import SystemHeader, RadarControllerHeader |
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12 | 12 | |
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13 | 13 | def getNumpyDtype(dataTypeCode): |
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14 | 14 | |
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15 | 15 | if dataTypeCode == 0: |
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16 | 16 | numpyDtype = numpy.dtype([('real','<i1'),('imag','<i1')]) |
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17 | 17 | elif dataTypeCode == 1: |
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18 | 18 | numpyDtype = numpy.dtype([('real','<i2'),('imag','<i2')]) |
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19 | 19 | elif dataTypeCode == 2: |
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20 | 20 | numpyDtype = numpy.dtype([('real','<i4'),('imag','<i4')]) |
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21 | 21 | elif dataTypeCode == 3: |
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22 | 22 | numpyDtype = numpy.dtype([('real','<i8'),('imag','<i8')]) |
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23 | 23 | elif dataTypeCode == 4: |
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24 | 24 | numpyDtype = numpy.dtype([('real','<f4'),('imag','<f4')]) |
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25 | 25 | elif dataTypeCode == 5: |
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26 | 26 | numpyDtype = numpy.dtype([('real','<f8'),('imag','<f8')]) |
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27 | 27 | else: |
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28 | 28 | raise ValueError, 'dataTypeCode was not defined' |
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29 | 29 | |
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30 | 30 | return numpyDtype |
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31 | 31 | |
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32 | 32 | def getDataTypeCode(numpyDtype): |
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33 | 33 | |
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34 | 34 | if numpyDtype == numpy.dtype([('real','<i1'),('imag','<i1')]): |
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35 | 35 | datatype = 0 |
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36 | 36 | elif numpyDtype == numpy.dtype([('real','<i2'),('imag','<i2')]): |
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37 | 37 | datatype = 1 |
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38 | 38 | elif numpyDtype == numpy.dtype([('real','<i4'),('imag','<i4')]): |
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39 | 39 | datatype = 2 |
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40 | 40 | elif numpyDtype == numpy.dtype([('real','<i8'),('imag','<i8')]): |
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41 | 41 | datatype = 3 |
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42 | 42 | elif numpyDtype == numpy.dtype([('real','<f4'),('imag','<f4')]): |
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43 | 43 | datatype = 4 |
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44 | 44 | elif numpyDtype == numpy.dtype([('real','<f8'),('imag','<f8')]): |
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45 | 45 | datatype = 5 |
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46 | 46 | else: |
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47 | 47 | datatype = None |
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48 | 48 | |
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49 | 49 | return datatype |
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50 | 50 | |
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51 | 51 | def hildebrand_sekhon(data, navg): |
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52 | 52 | |
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53 | 53 | data = data.copy() |
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54 | 54 | |
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55 | 55 | sortdata = numpy.sort(data,axis=None) |
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56 | 56 | lenOfData = len(sortdata) |
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57 | 57 | nums_min = lenOfData/10 |
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58 | 58 | |
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59 | 59 | if (lenOfData/10) > 2: |
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60 | 60 | nums_min = lenOfData/10 |
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61 | 61 | else: |
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62 | 62 | nums_min = 2 |
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63 | 63 | |
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64 | 64 | sump = 0. |
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65 | 65 | |
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66 | 66 | sumq = 0. |
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67 | 67 | |
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68 | 68 | j = 0 |
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69 | 69 | |
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70 | 70 | cont = 1 |
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71 | 71 | |
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72 | 72 | while((cont==1)and(j<lenOfData)): |
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73 | 73 | |
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74 | 74 | sump += sortdata[j] |
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75 | 75 | |
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76 | 76 | sumq += sortdata[j]**2 |
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77 | 77 | |
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78 | 78 | j += 1 |
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79 | 79 | |
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80 | 80 | if j > nums_min: |
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81 | 81 | rtest = float(j)/(j-1) + 1.0/navg |
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82 | 82 | if ((sumq*j) > (rtest*sump**2)): |
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83 | 83 | j = j - 1 |
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84 | 84 | sump = sump - sortdata[j] |
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85 | 85 | sumq = sumq - sortdata[j]**2 |
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86 | 86 | cont = 0 |
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87 | 87 | |
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88 | 88 | lnoise = sump /j |
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89 | 89 | stdv = numpy.sqrt((sumq - lnoise**2)/(j - 1)) |
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90 | 90 | return lnoise |
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91 | 91 | |
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92 | 92 | class GenericData(object): |
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93 | 93 | |
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94 | 94 | flagNoData = True |
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95 | 95 | |
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96 | 96 | def __init__(self): |
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97 | 97 | |
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98 | 98 | raise ValueError, "This class has not been implemented" |
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99 | 99 | |
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100 | 100 | def copy(self, inputObj=None): |
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101 | 101 | |
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102 | 102 | if inputObj == None: |
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103 | 103 | return copy.deepcopy(self) |
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104 | 104 | |
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105 | 105 | for key in inputObj.__dict__.keys(): |
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106 | 106 | self.__dict__[key] = inputObj.__dict__[key] |
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107 | 107 | |
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108 | 108 | def deepcopy(self): |
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109 | 109 | |
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110 | 110 | return copy.deepcopy(self) |
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111 | 111 | |
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112 | 112 | def isEmpty(self): |
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113 | 113 | |
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114 | 114 | return self.flagNoData |
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115 | 115 | |
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116 | 116 | class JROData(GenericData): |
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117 | 117 | |
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118 | 118 | # m_BasicHeader = BasicHeader() |
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119 | 119 | # m_ProcessingHeader = ProcessingHeader() |
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120 | 120 | |
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121 | 121 | systemHeaderObj = SystemHeader() |
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122 | 122 | |
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123 | 123 | radarControllerHeaderObj = RadarControllerHeader() |
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124 | 124 | |
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125 | 125 | # data = None |
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126 | 126 | |
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127 | 127 | type = None |
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128 | 128 | |
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129 | 129 | datatype = None #dtype but in string |
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130 | 130 | |
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131 | 131 | # dtype = None |
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132 | 132 | |
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133 | 133 | # nChannels = None |
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134 | 134 | |
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135 | 135 | # nHeights = None |
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136 | 136 | |
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137 | 137 | nProfiles = None |
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138 | 138 | |
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139 | 139 | heightList = None |
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140 | 140 | |
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141 | 141 | channelList = None |
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142 | 142 | |
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143 | 143 | flagTimeBlock = False |
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144 | 144 | |
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145 | 145 | useLocalTime = False |
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146 | 146 | |
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147 | 147 | utctime = None |
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148 | 148 | |
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149 | 149 | timeZone = None |
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150 | 150 | |
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151 | 151 | dstFlag = None |
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152 | 152 | |
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153 | 153 | errorCount = None |
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154 | 154 | |
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155 | 155 | blocksize = None |
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156 | 156 | |
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157 | 157 | nCode = None |
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158 | 158 | |
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159 | 159 | nBaud = None |
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160 | 160 | |
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161 | 161 | code = None |
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162 | 162 | |
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163 | 163 | flagDecodeData = False #asumo q la data no esta decodificada |
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164 | 164 | |
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165 | 165 | flagDeflipData = False #asumo q la data no esta sin flip |
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166 | 166 | |
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167 | 167 | flagShiftFFT = False |
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168 | 168 | |
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169 | 169 | # ippSeconds = None |
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170 | 170 | |
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171 | 171 | timeInterval = None |
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172 | 172 | |
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173 | 173 | nCohInt = None |
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174 | 174 | |
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175 | 175 | noise = None |
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176 | 176 | |
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177 | 177 | windowOfFilter = 1 |
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178 | 178 | |
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179 | 179 | #Speed of ligth |
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180 | 180 | C = 3e8 |
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181 | 181 | |
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182 | 182 | frequency = 49.92e6 |
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183 | 183 | |
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184 | 184 | realtime = False |
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185 | 185 | |
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186 | 186 | beacon_heiIndexList = None |
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187 | 187 | |
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188 | 188 | last_block = None |
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189 | 189 | |
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190 | 190 | blocknow = None |
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191 | 191 | |
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192 | azimuth = None | |
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193 | ||
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194 | zenith = None | |
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195 | ||
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192 | 196 | def __init__(self): |
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193 | 197 | |
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194 | 198 | raise ValueError, "This class has not been implemented" |
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195 | 199 | |
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196 | 200 | def getNoise(self): |
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197 | 201 | |
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198 | 202 | raise ValueError, "Not implemented" |
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199 | 203 | |
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200 | 204 | def getNChannels(self): |
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201 | 205 | |
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202 | 206 | return len(self.channelList) |
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203 | 207 | |
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204 | 208 | def getChannelIndexList(self): |
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205 | 209 | |
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206 | 210 | return range(self.nChannels) |
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207 | 211 | |
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208 | 212 | def getNHeights(self): |
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209 | 213 | |
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210 | 214 | return len(self.heightList) |
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211 | 215 | |
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212 | 216 | def getHeiRange(self, extrapoints=0): |
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213 | 217 | |
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214 | 218 | heis = self.heightList |
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215 | 219 | # deltah = self.heightList[1] - self.heightList[0] |
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216 | 220 | # |
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217 | 221 | # heis.append(self.heightList[-1]) |
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218 | 222 | |
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219 | 223 | return heis |
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220 | 224 | |
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221 | 225 | def getltctime(self): |
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222 | 226 | |
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223 | 227 | if self.useLocalTime: |
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224 | 228 | return self.utctime - self.timeZone*60 |
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225 | 229 | |
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226 | 230 | return self.utctime |
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227 | 231 | |
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228 | 232 | def getDatatime(self): |
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229 | 233 | |
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230 | 234 | datatimeValue = datetime.datetime.utcfromtimestamp(self.ltctime) |
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231 | 235 | return datatimeValue |
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232 | 236 | |
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233 | 237 | def getTimeRange(self): |
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234 | 238 | |
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235 | 239 | datatime = [] |
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236 | 240 | |
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237 | 241 | datatime.append(self.ltctime) |
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238 | 242 | datatime.append(self.ltctime + self.timeInterval) |
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239 | 243 | |
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240 | 244 | datatime = numpy.array(datatime) |
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241 | 245 | |
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242 | 246 | return datatime |
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243 | 247 | |
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244 | 248 | def getFmax(self): |
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245 | 249 | |
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246 | 250 | PRF = 1./(self.ippSeconds * self.nCohInt) |
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247 | 251 | |
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248 | 252 | fmax = PRF/2. |
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249 | 253 | |
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250 | 254 | return fmax |
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251 | 255 | |
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252 | 256 | def getVmax(self): |
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253 | 257 | |
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254 | 258 | _lambda = self.C/self.frequency |
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255 | 259 | |
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256 | 260 | vmax = self.getFmax() * _lambda |
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257 | 261 | |
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258 | 262 | return vmax |
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259 | 263 | |
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260 | 264 | def get_ippSeconds(self): |
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261 | 265 | ''' |
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262 | 266 | ''' |
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263 | 267 | return self.radarControllerHeaderObj.ippSeconds |
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264 | 268 | |
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265 | 269 | def set_ippSeconds(self, ippSeconds): |
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266 | 270 | ''' |
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267 | 271 | ''' |
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268 | 272 | |
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269 | 273 | self.radarControllerHeaderObj.ippSeconds = ippSeconds |
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270 | 274 | |
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271 | 275 | return |
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272 | 276 | |
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273 | 277 | def get_dtype(self): |
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274 | 278 | ''' |
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275 | 279 | ''' |
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276 | 280 | return getNumpyDtype(self.datatype) |
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277 | 281 | |
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278 | 282 | def set_dtype(self, numpyDtype): |
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279 | 283 | ''' |
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280 | 284 | ''' |
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281 | 285 | |
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282 | 286 | self.datatype = getDataTypeCode(numpyDtype) |
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283 | 287 | |
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284 | 288 | nChannels = property(getNChannels, "I'm the 'nChannel' property.") |
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285 | 289 | channelIndexList = property(getChannelIndexList, "I'm the 'channelIndexList' property.") |
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286 | 290 | nHeights = property(getNHeights, "I'm the 'nHeights' property.") |
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287 | 291 | #noise = property(getNoise, "I'm the 'nHeights' property.") |
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288 | 292 | datatime = property(getDatatime, "I'm the 'datatime' property") |
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289 | 293 | ltctime = property(getltctime, "I'm the 'ltctime' property") |
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290 | 294 | ippSeconds = property(get_ippSeconds, set_ippSeconds) |
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291 | 295 | dtype = property(get_dtype, set_dtype) |
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292 | 296 | |
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293 | 297 | class Voltage(JROData): |
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294 | 298 | |
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295 | 299 | #data es un numpy array de 2 dmensiones (canales, alturas) |
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296 | 300 | data = None |
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297 | 301 | |
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298 | 302 | def __init__(self): |
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299 | 303 | ''' |
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300 | 304 | Constructor |
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301 | 305 | ''' |
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302 | 306 | |
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303 | 307 | self.radarControllerHeaderObj = RadarControllerHeader() |
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304 | 308 | |
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305 | 309 | self.systemHeaderObj = SystemHeader() |
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306 | 310 | |
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307 | 311 | self.type = "Voltage" |
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308 | 312 | |
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309 | 313 | self.data = None |
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310 | 314 | |
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311 | 315 | # self.dtype = None |
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312 | 316 | |
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313 | 317 | # self.nChannels = 0 |
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314 | 318 | |
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315 | 319 | # self.nHeights = 0 |
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316 | 320 | |
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317 | 321 | self.nProfiles = None |
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318 | 322 | |
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319 | 323 | self.heightList = None |
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320 | 324 | |
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321 | 325 | self.channelList = None |
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322 | 326 | |
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323 | 327 | # self.channelIndexList = None |
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324 | 328 | |
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325 | 329 | self.flagNoData = True |
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326 | 330 | |
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327 | 331 | self.flagTimeBlock = False |
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328 | 332 | |
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329 | 333 | self.utctime = None |
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330 | 334 | |
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331 | 335 | self.timeZone = None |
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332 | 336 | |
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333 | 337 | self.dstFlag = None |
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334 | 338 | |
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335 | 339 | self.errorCount = None |
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336 | 340 | |
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337 | 341 | self.nCohInt = None |
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338 | 342 | |
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339 | 343 | self.blocksize = None |
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340 | 344 | |
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341 | 345 | self.flagDecodeData = False #asumo q la data no esta decodificada |
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342 | 346 | |
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343 | 347 | self.flagDeflipData = False #asumo q la data no esta sin flip |
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344 | 348 | |
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345 | 349 | self.flagShiftFFT = False |
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346 | 350 | |
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347 | 351 | |
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348 | 352 | def getNoisebyHildebrand(self): |
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349 | 353 | """ |
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350 | 354 | Determino el nivel de ruido usando el metodo Hildebrand-Sekhon |
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351 | 355 | |
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352 | 356 | Return: |
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353 | 357 | noiselevel |
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354 | 358 | """ |
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355 | 359 | |
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356 | 360 | for channel in range(self.nChannels): |
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357 | 361 | daux = self.data_spc[channel,:,:] |
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358 | 362 | self.noise[channel] = hildebrand_sekhon(daux, self.nCohInt) |
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359 | 363 | |
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360 | 364 | return self.noise |
|
|
361 | 365 | |
|
|
362 | 366 | def getNoise(self, type = 1): |
|
|
363 | 367 | |
|
|
364 | 368 | self.noise = numpy.zeros(self.nChannels) |
|
|
365 | 369 | |
|
|
366 | 370 | if type == 1: |
|
|
367 | 371 | noise = self.getNoisebyHildebrand() |
|
|
368 | 372 | |
|
|
369 | 373 | return 10*numpy.log10(noise) |
|
|
370 | 374 | |
|
|
371 | 375 | noise = property(getNoise, "I'm the 'nHeights' property.") |
|
|
372 | 376 | |
|
|
373 | 377 | class Spectra(JROData): |
|
|
374 | 378 | |
|
|
375 | 379 | #data es un numpy array de 2 dmensiones (canales, perfiles, alturas) |
|
|
376 | 380 | data_spc = None |
|
|
377 | 381 | |
|
|
378 | 382 | #data es un numpy array de 2 dmensiones (canales, pares, alturas) |
|
|
379 | 383 | data_cspc = None |
|
|
380 | 384 | |
|
|
381 | 385 | #data es un numpy array de 2 dmensiones (canales, alturas) |
|
|
382 | 386 | data_dc = None |
|
|
383 | 387 | |
|
|
384 | 388 | nFFTPoints = None |
|
|
385 | 389 | |
|
|
386 | 390 | # nPairs = None |
|
|
387 | 391 | |
|
|
388 | 392 | pairsList = None |
|
|
389 | 393 | |
|
|
390 | 394 | nIncohInt = None |
|
|
391 | 395 | |
|
|
392 | 396 | wavelength = None #Necesario para cacular el rango de velocidad desde la frecuencia |
|
|
393 | 397 | |
|
|
394 | 398 | nCohInt = None #se requiere para determinar el valor de timeInterval |
|
|
395 | 399 | |
|
|
396 | 400 | ippFactor = None |
|
|
397 | 401 | |
|
|
398 | 402 | def __init__(self): |
|
|
399 | 403 | ''' |
|
|
400 | 404 | Constructor |
|
|
401 | 405 | ''' |
|
|
402 | 406 | |
|
|
403 | 407 | self.radarControllerHeaderObj = RadarControllerHeader() |
|
|
404 | 408 | |
|
|
405 | 409 | self.systemHeaderObj = SystemHeader() |
|
|
406 | 410 | |
|
|
407 | 411 | self.type = "Spectra" |
|
|
408 | 412 | |
|
|
409 | 413 | # self.data = None |
|
|
410 | 414 | |
|
|
411 | 415 | # self.dtype = None |
|
|
412 | 416 | |
|
|
413 | 417 | # self.nChannels = 0 |
|
|
414 | 418 | |
|
|
415 | 419 | # self.nHeights = 0 |
|
|
416 | 420 | |
|
|
417 | 421 | self.nProfiles = None |
|
|
418 | 422 | |
|
|
419 | 423 | self.heightList = None |
|
|
420 | 424 | |
|
|
421 | 425 | self.channelList = None |
|
|
422 | 426 | |
|
|
423 | 427 | # self.channelIndexList = None |
|
|
424 | 428 | |
|
|
425 | 429 | self.pairsList = None |
|
|
426 | 430 | |
|
|
427 | 431 | self.flagNoData = True |
|
|
428 | 432 | |
|
|
429 | 433 | self.flagTimeBlock = False |
|
|
430 | 434 | |
|
|
431 | 435 | self.utctime = None |
|
|
432 | 436 | |
|
|
433 | 437 | self.nCohInt = None |
|
|
434 | 438 | |
|
|
435 | 439 | self.nIncohInt = None |
|
|
436 | 440 | |
|
|
437 | 441 | self.blocksize = None |
|
|
438 | 442 | |
|
|
439 | 443 | self.nFFTPoints = None |
|
|
440 | 444 | |
|
|
441 | 445 | self.wavelength = None |
|
|
442 | 446 | |
|
|
443 | 447 | self.flagDecodeData = False #asumo q la data no esta decodificada |
|
|
444 | 448 | |
|
|
445 | 449 | self.flagDeflipData = False #asumo q la data no esta sin flip |
|
|
446 | 450 | |
|
|
447 | 451 | self.flagShiftFFT = False |
|
|
448 | 452 | |
|
|
449 | 453 | self.ippFactor = 1 |
|
|
450 | 454 | |
|
|
451 | 455 | #self.noise = None |
|
|
452 | 456 | |
|
|
453 | 457 | self.beacon_heiIndexList = [] |
|
|
454 | 458 | |
|
|
455 | 459 | self.noise_estimation = None |
|
|
456 | 460 | |
|
|
457 | 461 | |
|
|
458 | 462 | def getNoisebyHildebrand(self): |
|
|
459 | 463 | """ |
|
|
460 | 464 | Determino el nivel de ruido usando el metodo Hildebrand-Sekhon |
|
|
461 | 465 | |
|
|
462 | 466 | Return: |
|
|
463 | 467 | noiselevel |
|
|
464 | 468 | """ |
|
|
465 | 469 | |
|
|
466 | 470 | noise = numpy.zeros(self.nChannels) |
|
|
467 | 471 | for channel in range(self.nChannels): |
|
|
468 | 472 | daux = self.data_spc[channel,:,:] |
|
|
469 | 473 | noise[channel] = hildebrand_sekhon(daux, self.nIncohInt) |
|
|
470 | 474 | |
|
|
471 | 475 | return noise |
|
|
472 | 476 | |
|
|
473 | 477 | def getNoise(self): |
|
|
474 | 478 | if self.noise_estimation != None: |
|
|
475 | 479 | return self.noise_estimation #this was estimated by getNoise Operation defined in jroproc_spectra.py |
|
|
476 | 480 | else: |
|
|
477 | 481 | noise = self.getNoisebyHildebrand() |
|
|
478 | 482 | return noise |
|
|
479 | 483 | |
|
|
480 | 484 | |
|
|
481 | 485 | def getFreqRange(self, extrapoints=0): |
|
|
482 | 486 | |
|
|
483 | 487 | deltafreq = self.getFmax() / (self.nFFTPoints*self.ippFactor) |
|
|
484 | 488 | freqrange = deltafreq*(numpy.arange(self.nFFTPoints+extrapoints)-self.nFFTPoints/2.) - deltafreq/2 |
|
|
485 | 489 | |
|
|
486 | 490 | return freqrange |
|
|
487 | 491 | |
|
|
488 | 492 | def getVelRange(self, extrapoints=0): |
|
|
489 | 493 | |
|
|
490 | 494 | deltav = self.getVmax() / (self.nFFTPoints*self.ippFactor) |
|
|
491 | 495 | velrange = deltav*(numpy.arange(self.nFFTPoints+extrapoints)-self.nFFTPoints/2.) - deltav/2 |
|
|
492 | 496 | |
|
|
493 | 497 | return velrange |
|
|
494 | 498 | |
|
|
495 | 499 | def getNPairs(self): |
|
|
496 | 500 | |
|
|
497 | 501 | return len(self.pairsList) |
|
|
498 | 502 | |
|
|
499 | 503 | def getPairsIndexList(self): |
|
|
500 | 504 | |
|
|
501 | 505 | return range(self.nPairs) |
|
|
502 | 506 | |
|
|
503 | 507 | def getNormFactor(self): |
|
|
504 | 508 | pwcode = 1 |
|
|
505 | 509 | if self.flagDecodeData: |
|
|
506 | 510 | pwcode = numpy.sum(self.code[0]**2) |
|
|
507 | 511 | #normFactor = min(self.nFFTPoints,self.nProfiles)*self.nIncohInt*self.nCohInt*pwcode*self.windowOfFilter |
|
|
508 | 512 | normFactor = self.nProfiles*self.nIncohInt*self.nCohInt*pwcode*self.windowOfFilter |
|
|
509 | 513 | |
|
|
510 | 514 | return normFactor |
|
|
511 | 515 | |
|
|
512 | 516 | def getFlagCspc(self): |
|
|
513 | 517 | |
|
|
514 | 518 | if self.data_cspc == None: |
|
|
515 | 519 | return True |
|
|
516 | 520 | |
|
|
517 | 521 | return False |
|
|
518 | 522 | |
|
|
519 | 523 | def getFlagDc(self): |
|
|
520 | 524 | |
|
|
521 | 525 | if self.data_dc == None: |
|
|
522 | 526 | return True |
|
|
523 | 527 | |
|
|
524 | 528 | return False |
|
|
525 | 529 | |
|
|
526 | 530 | nPairs = property(getNPairs, "I'm the 'nPairs' property.") |
|
|
527 | 531 | pairsIndexList = property(getPairsIndexList, "I'm the 'pairsIndexList' property.") |
|
|
528 | 532 | normFactor = property(getNormFactor, "I'm the 'getNormFactor' property.") |
|
|
529 | 533 | flag_cspc = property(getFlagCspc) |
|
|
530 | 534 | flag_dc = property(getFlagDc) |
|
|
531 | 535 | noise = property(getNoise, "I'm the 'nHeights' property.") |
|
|
532 | 536 | |
|
|
533 | 537 | class SpectraHeis(Spectra): |
|
|
534 | 538 | |
|
|
535 | 539 | data_spc = None |
|
|
536 | 540 | |
|
|
537 | 541 | data_cspc = None |
|
|
538 | 542 | |
|
|
539 | 543 | data_dc = None |
|
|
540 | 544 | |
|
|
541 | 545 | nFFTPoints = None |
|
|
542 | 546 | |
|
|
543 | 547 | # nPairs = None |
|
|
544 | 548 | |
|
|
545 | 549 | pairsList = None |
|
|
546 | 550 | |
|
|
547 | 551 | nIncohInt = None |
|
|
548 | 552 | |
|
|
549 | 553 | def __init__(self): |
|
|
550 | 554 | |
|
|
551 | 555 | self.radarControllerHeaderObj = RadarControllerHeader() |
|
|
552 | 556 | |
|
|
553 | 557 | self.systemHeaderObj = SystemHeader() |
|
|
554 | 558 | |
|
|
555 | 559 | self.type = "SpectraHeis" |
|
|
556 | 560 | |
|
|
557 | 561 | # self.dtype = None |
|
|
558 | 562 | |
|
|
559 | 563 | # self.nChannels = 0 |
|
|
560 | 564 | |
|
|
561 | 565 | # self.nHeights = 0 |
|
|
562 | 566 | |
|
|
563 | 567 | self.nProfiles = None |
|
|
564 | 568 | |
|
|
565 | 569 | self.heightList = None |
|
|
566 | 570 | |
|
|
567 | 571 | self.channelList = None |
|
|
568 | 572 | |
|
|
569 | 573 | # self.channelIndexList = None |
|
|
570 | 574 | |
|
|
571 | 575 | self.flagNoData = True |
|
|
572 | 576 | |
|
|
573 | 577 | self.flagTimeBlock = False |
|
|
574 | 578 | |
|
|
575 | 579 | # self.nPairs = 0 |
|
|
576 | 580 | |
|
|
577 | 581 | self.utctime = None |
|
|
578 | 582 | |
|
|
579 | 583 | self.blocksize = None |
|
|
580 | 584 | |
|
|
581 | 585 | def getNormFactor(self): |
|
|
582 | 586 | pwcode = 1 |
|
|
583 | 587 | if self.flagDecodeData: |
|
|
584 | 588 | pwcode = numpy.sum(self.code[0]**2) |
|
|
585 | 589 | |
|
|
586 | 590 | normFactor = self.nIncohInt*self.nCohInt*pwcode |
|
|
587 | 591 | |
|
|
588 | 592 | return normFactor |
|
|
589 | 593 | |
|
|
590 | 594 | normFactor = property(getNormFactor, "I'm the 'getNormFactor' property.") |
|
|
591 | 595 | |
|
|
592 | 596 | class Fits: |
|
|
593 | 597 | |
|
|
594 | 598 | heightList = None |
|
|
595 | 599 | |
|
|
596 | 600 | channelList = None |
|
|
597 | 601 | |
|
|
598 | 602 | flagNoData = True |
|
|
599 | 603 | |
|
|
600 | 604 | flagTimeBlock = False |
|
|
601 | 605 | |
|
|
602 | 606 | useLocalTime = False |
|
|
603 | 607 | |
|
|
604 | 608 | utctime = None |
|
|
605 | 609 | |
|
|
606 | 610 | timeZone = None |
|
|
607 | 611 | |
|
|
608 | 612 | # ippSeconds = None |
|
|
609 | 613 | |
|
|
610 | 614 | timeInterval = None |
|
|
611 | 615 | |
|
|
612 | 616 | nCohInt = None |
|
|
613 | 617 | |
|
|
614 | 618 | nIncohInt = None |
|
|
615 | 619 | |
|
|
616 | 620 | noise = None |
|
|
617 | 621 | |
|
|
618 | 622 | windowOfFilter = 1 |
|
|
619 | 623 | |
|
|
620 | 624 | #Speed of ligth |
|
|
621 | 625 | C = 3e8 |
|
|
622 | 626 | |
|
|
623 | 627 | frequency = 49.92e6 |
|
|
624 | 628 | |
|
|
625 | 629 | realtime = False |
|
|
626 | 630 | |
|
|
627 | 631 | |
|
|
628 | 632 | def __init__(self): |
|
|
629 | 633 | |
|
|
630 | 634 | self.type = "Fits" |
|
|
631 | 635 | |
|
|
632 | 636 | self.nProfiles = None |
|
|
633 | 637 | |
|
|
634 | 638 | self.heightList = None |
|
|
635 | 639 | |
|
|
636 | 640 | self.channelList = None |
|
|
637 | 641 | |
|
|
638 | 642 | # self.channelIndexList = None |
|
|
639 | 643 | |
|
|
640 | 644 | self.flagNoData = True |
|
|
641 | 645 | |
|
|
642 | 646 | self.utctime = None |
|
|
643 | 647 | |
|
|
644 | 648 | self.nCohInt = None |
|
|
645 | 649 | |
|
|
646 | 650 | self.nIncohInt = None |
|
|
647 | 651 | |
|
|
648 | 652 | self.useLocalTime = True |
|
|
649 | 653 | |
|
|
650 | 654 | # self.utctime = None |
|
|
651 | 655 | # self.timeZone = None |
|
|
652 | 656 | # self.ltctime = None |
|
|
653 | 657 | # self.timeInterval = None |
|
|
654 | 658 | # self.header = None |
|
|
655 | 659 | # self.data_header = None |
|
|
656 | 660 | # self.data = None |
|
|
657 | 661 | # self.datatime = None |
|
|
658 | 662 | # self.flagNoData = False |
|
|
659 | 663 | # self.expName = '' |
|
|
660 | 664 | # self.nChannels = None |
|
|
661 | 665 | # self.nSamples = None |
|
|
662 | 666 | # self.dataBlocksPerFile = None |
|
|
663 | 667 | # self.comments = '' |
|
|
664 | 668 | # |
|
|
665 | 669 | |
|
|
666 | 670 | |
|
|
667 | 671 | def getltctime(self): |
|
|
668 | 672 | |
|
|
669 | 673 | if self.useLocalTime: |
|
|
670 | 674 | return self.utctime - self.timeZone*60 |
|
|
671 | 675 | |
|
|
672 | 676 | return self.utctime |
|
|
673 | 677 | |
|
|
674 | 678 | def getDatatime(self): |
|
|
675 | 679 | |
|
|
676 | 680 | datatime = datetime.datetime.utcfromtimestamp(self.ltctime) |
|
|
677 | 681 | return datatime |
|
|
678 | 682 | |
|
|
679 | 683 | def getTimeRange(self): |
|
|
680 | 684 | |
|
|
681 | 685 | datatime = [] |
|
|
682 | 686 | |
|
|
683 | 687 | datatime.append(self.ltctime) |
|
|
684 | 688 | datatime.append(self.ltctime + self.timeInterval) |
|
|
685 | 689 | |
|
|
686 | 690 | datatime = numpy.array(datatime) |
|
|
687 | 691 | |
|
|
688 | 692 | return datatime |
|
|
689 | 693 | |
|
|
690 | 694 | def getHeiRange(self): |
|
|
691 | 695 | |
|
|
692 | 696 | heis = self.heightList |
|
|
693 | 697 | |
|
|
694 | 698 | return heis |
|
|
695 | 699 | |
|
|
696 | 700 | def isEmpty(self): |
|
|
697 | 701 | |
|
|
698 | 702 | return self.flagNoData |
|
|
699 | 703 | |
|
|
700 | 704 | def getNHeights(self): |
|
|
701 | 705 | |
|
|
702 | 706 | return len(self.heightList) |
|
|
703 | 707 | |
|
|
704 | 708 | def getNChannels(self): |
|
|
705 | 709 | |
|
|
706 | 710 | return len(self.channelList) |
|
|
707 | 711 | |
|
|
708 | 712 | def getChannelIndexList(self): |
|
|
709 | 713 | |
|
|
710 | 714 | return range(self.nChannels) |
|
|
711 | 715 | |
|
|
712 | 716 | def getNoise(self, type = 1): |
|
|
713 | 717 | |
|
|
714 | 718 | self.noise = numpy.zeros(self.nChannels) |
|
|
715 | 719 | |
|
|
716 | 720 | if type == 1: |
|
|
717 | 721 | noise = self.getNoisebyHildebrand() |
|
|
718 | 722 | |
|
|
719 | 723 | if type == 2: |
|
|
720 | 724 | noise = self.getNoisebySort() |
|
|
721 | 725 | |
|
|
722 | 726 | if type == 3: |
|
|
723 | 727 | noise = self.getNoisebyWindow() |
|
|
724 | 728 | |
|
|
725 | 729 | return noise |
|
|
726 | 730 | |
|
|
727 | 731 | datatime = property(getDatatime, "I'm the 'datatime' property") |
|
|
728 | 732 | nHeights = property(getNHeights, "I'm the 'nHeights' property.") |
|
|
729 | 733 | nChannels = property(getNChannels, "I'm the 'nChannel' property.") |
|
|
730 | 734 | channelIndexList = property(getChannelIndexList, "I'm the 'channelIndexList' property.") |
|
|
731 | 735 | noise = property(getNoise, "I'm the 'nHeights' property.") |
|
|
732 | 736 | datatime = property(getDatatime, "I'm the 'datatime' property") |
|
|
733 | 737 | ltctime = property(getltctime, "I'm the 'ltctime' property") |
|
|
734 | 738 | |
|
|
735 | 739 | ltctime = property(getltctime, "I'm the 'ltctime' property") |
|
|
736 | 740 | |
| @@ -1,1346 +1,1354 | |||
|
|
1 | 1 | ''' |
|
|
2 | 2 | @author: Daniel Suarez |
|
|
3 | 3 | ''' |
|
|
4 | 4 | import os |
|
|
5 | 5 | import datetime |
|
|
6 | 6 | import numpy |
|
|
7 | 7 | |
|
|
8 | 8 | from figure import Figure, isRealtime |
|
|
9 | 9 | |
|
|
10 | 10 | class SpectraPlot(Figure): |
|
|
11 | 11 | |
|
|
12 | 12 | isConfig = None |
|
|
13 | 13 | __nsubplots = None |
|
|
14 | 14 | |
|
|
15 | 15 | WIDTHPROF = None |
|
|
16 | 16 | HEIGHTPROF = None |
|
|
17 | 17 | PREFIX = 'spc' |
|
|
18 | 18 | |
|
|
19 | 19 | def __init__(self): |
|
|
20 | 20 | |
|
|
21 | 21 | self.isConfig = False |
|
|
22 | 22 | self.__nsubplots = 1 |
|
|
23 | 23 | |
|
|
24 | 24 | self.WIDTH = 280 |
|
|
25 | 25 | self.HEIGHT = 250 |
|
|
26 | 26 | self.WIDTHPROF = 120 |
|
|
27 | 27 | self.HEIGHTPROF = 0 |
|
|
28 | 28 | self.counter_imagwr = 0 |
|
|
29 | 29 | |
|
|
30 | 30 | self.PLOT_CODE = 1 |
|
|
31 | 31 | self.FTP_WEI = None |
|
|
32 | 32 | self.EXP_CODE = None |
|
|
33 | 33 | self.SUB_EXP_CODE = None |
|
|
34 | 34 | self.PLOT_POS = None |
|
|
35 | 35 | |
|
|
36 | 36 | def getSubplots(self): |
|
|
37 | 37 | |
|
|
38 | 38 | ncol = int(numpy.sqrt(self.nplots)+0.9) |
|
|
39 | 39 | nrow = int(self.nplots*1./ncol + 0.9) |
|
|
40 | 40 | |
|
|
41 | 41 | return nrow, ncol |
|
|
42 | 42 | |
|
|
43 | 43 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): |
|
|
44 | 44 | |
|
|
45 | 45 | self.__showprofile = showprofile |
|
|
46 | 46 | self.nplots = nplots |
|
|
47 | 47 | |
|
|
48 | 48 | ncolspan = 1 |
|
|
49 | 49 | colspan = 1 |
|
|
50 | 50 | if showprofile: |
|
|
51 | 51 | ncolspan = 3 |
|
|
52 | 52 | colspan = 2 |
|
|
53 | 53 | self.__nsubplots = 2 |
|
|
54 | 54 | |
|
|
55 | 55 | self.createFigure(id = id, |
|
|
56 | 56 | wintitle = wintitle, |
|
|
57 | 57 | widthplot = self.WIDTH + self.WIDTHPROF, |
|
|
58 | 58 | heightplot = self.HEIGHT + self.HEIGHTPROF, |
|
|
59 | 59 | show=show) |
|
|
60 | 60 | |
|
|
61 | 61 | nrow, ncol = self.getSubplots() |
|
|
62 | 62 | |
|
|
63 | 63 | counter = 0 |
|
|
64 | 64 | for y in range(nrow): |
|
|
65 | 65 | for x in range(ncol): |
|
|
66 | 66 | |
|
|
67 | 67 | if counter >= self.nplots: |
|
|
68 | 68 | break |
|
|
69 | 69 | |
|
|
70 | 70 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) |
|
|
71 | 71 | |
|
|
72 | 72 | if showprofile: |
|
|
73 | 73 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan+colspan, 1, 1) |
|
|
74 | 74 | |
|
|
75 | 75 | counter += 1 |
|
|
76 | 76 | |
|
|
77 | 77 | def run(self, dataOut, id, wintitle="", channelList=None, showprofile=True, |
|
|
78 | 78 | xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, |
|
|
79 | 79 | save=False, figpath='', figfile=None, show=True, ftp=False, wr_period=1, |
|
|
80 | 80 | server=None, folder=None, username=None, password=None, |
|
|
81 | 81 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, realtime=False): |
|
|
82 | 82 | |
|
|
83 | 83 | """ |
|
|
84 | 84 | |
|
|
85 | 85 | Input: |
|
|
86 | 86 | dataOut : |
|
|
87 | 87 | id : |
|
|
88 | 88 | wintitle : |
|
|
89 | 89 | channelList : |
|
|
90 | 90 | showProfile : |
|
|
91 | 91 | xmin : None, |
|
|
92 | 92 | xmax : None, |
|
|
93 | 93 | ymin : None, |
|
|
94 | 94 | ymax : None, |
|
|
95 | 95 | zmin : None, |
|
|
96 | 96 | zmax : None |
|
|
97 | 97 | """ |
|
|
98 | 98 | |
|
|
99 | 99 | if dataOut.flagNoData: |
|
|
100 | 100 | return None |
|
|
101 | 101 | |
|
|
102 | 102 | if realtime: |
|
|
103 | 103 | if not(isRealtime(utcdatatime = dataOut.utctime)): |
|
|
104 | 104 | print 'Skipping this plot function' |
|
|
105 | 105 | return |
|
|
106 | 106 | |
|
|
107 | 107 | if channelList == None: |
|
|
108 | 108 | channelIndexList = dataOut.channelIndexList |
|
|
109 | 109 | else: |
|
|
110 | 110 | channelIndexList = [] |
|
|
111 | 111 | for channel in channelList: |
|
|
112 | 112 | if channel not in dataOut.channelList: |
|
|
113 | 113 | raise ValueError, "Channel %d is not in dataOut.channelList" |
|
|
114 | 114 | channelIndexList.append(dataOut.channelList.index(channel)) |
|
|
115 | 115 | |
|
|
116 | 116 | factor = dataOut.normFactor |
|
|
117 | 117 | |
|
|
118 | 118 | x = dataOut.getVelRange(1) |
|
|
119 | 119 | y = dataOut.getHeiRange() |
|
|
120 | 120 | |
|
|
121 | 121 | z = dataOut.data_spc[channelIndexList,:,:]/factor |
|
|
122 | 122 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) |
|
|
123 | 123 | avg = numpy.average(z, axis=1) |
|
|
124 | 124 | avg = numpy.nanmean(z, axis=1) |
|
|
125 | 125 | noise = dataOut.noise/factor |
|
|
126 | 126 | |
|
|
127 | 127 | zdB = 10*numpy.log10(z) |
|
|
128 | 128 | avgdB = 10*numpy.log10(avg) |
|
|
129 | 129 | noisedB = 10*numpy.log10(noise) |
|
|
130 | 130 | |
|
|
131 | 131 | #thisDatetime = dataOut.datatime |
|
|
132 | 132 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[1]) |
|
|
133 | 133 | title = wintitle + " Spectra" |
|
|
134 | if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)): | |
|
|
135 | title = title + '_' + 'azimuth,zenith=%2.2f,%2.2f'%(dataOut.azimuth, dataOut.zenith) | |
|
|
136 | ||
|
|
134 | 137 | xlabel = "Velocity (m/s)" |
|
|
135 | 138 | ylabel = "Range (Km)" |
|
|
136 | 139 | |
|
|
137 | 140 | if not self.isConfig: |
|
|
138 | 141 | |
|
|
139 | 142 | nplots = len(channelIndexList) |
|
|
140 | 143 | |
|
|
141 | 144 | self.setup(id=id, |
|
|
142 | 145 | nplots=nplots, |
|
|
143 | 146 | wintitle=wintitle, |
|
|
144 | 147 | showprofile=showprofile, |
|
|
145 | 148 | show=show) |
|
|
146 | 149 | |
|
|
147 | 150 | if xmin == None: xmin = numpy.nanmin(x) |
|
|
148 | 151 | if xmax == None: xmax = numpy.nanmax(x) |
|
|
149 | 152 | if ymin == None: ymin = numpy.nanmin(y) |
|
|
150 | 153 | if ymax == None: ymax = numpy.nanmax(y) |
|
|
151 | 154 | if zmin == None: zmin = numpy.nanmin(avgdB)*0.9 |
|
|
152 | 155 | if zmax == None: zmax = numpy.nanmax(avgdB)*0.9 |
|
|
153 | 156 | |
|
|
154 | 157 | self.FTP_WEI = ftp_wei |
|
|
155 | 158 | self.EXP_CODE = exp_code |
|
|
156 | 159 | self.SUB_EXP_CODE = sub_exp_code |
|
|
157 | 160 | self.PLOT_POS = plot_pos |
|
|
158 | 161 | |
|
|
159 | 162 | self.isConfig = True |
|
|
160 | 163 | |
|
|
161 | 164 | self.setWinTitle(title) |
|
|
162 | 165 | |
|
|
163 | 166 | for i in range(self.nplots): |
|
|
164 | 167 | str_datetime = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S")) |
|
|
165 | 168 | title = "Channel %d: %4.2fdB: %s" %(dataOut.channelList[i]+1, noisedB[i], str_datetime) |
|
|
166 | 169 | axes = self.axesList[i*self.__nsubplots] |
|
|
167 | 170 | axes.pcolor(x, y, zdB[i,:,:], |
|
|
168 | 171 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax, |
|
|
169 | 172 | xlabel=xlabel, ylabel=ylabel, title=title, |
|
|
170 | 173 | ticksize=9, cblabel='') |
|
|
171 | 174 | |
|
|
172 | 175 | if self.__showprofile: |
|
|
173 | 176 | axes = self.axesList[i*self.__nsubplots +1] |
|
|
174 | 177 | axes.pline(avgdB[i], y, |
|
|
175 | 178 | xmin=zmin, xmax=zmax, ymin=ymin, ymax=ymax, |
|
|
176 | 179 | xlabel='dB', ylabel='', title='', |
|
|
177 | 180 | ytick_visible=False, |
|
|
178 | 181 | grid='x') |
|
|
179 | 182 | |
|
|
180 | 183 | noiseline = numpy.repeat(noisedB[i], len(y)) |
|
|
181 | 184 | axes.addpline(noiseline, y, idline=1, color="black", linestyle="dashed", lw=2) |
|
|
182 | 185 | |
|
|
183 | 186 | self.draw() |
|
|
184 | 187 | |
|
|
185 | 188 | if figfile == None: |
|
|
186 | 189 | str_datetime = thisDatetime.strftime("%Y%m%d_%H%M%S") |
|
|
187 | 190 | figfile = self.getFilename(name = str_datetime) |
|
|
188 | ||
|
|
191 | name = str_datetime | |
|
|
192 | if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)): | |
|
|
193 | name = name + '_az' + '_%2.2f'%(dataOut.azimuth) + '_zn' + '_%2.2f'%(dataOut.zenith) | |
|
|
194 | figfile = self.getFilename(name) | |
|
|
189 | 195 | if figpath != '': |
|
|
190 | 196 | self.counter_imagwr += 1 |
|
|
191 | 197 | if (self.counter_imagwr>=wr_period): |
|
|
192 | 198 | # store png plot to local folder |
|
|
193 | 199 | self.saveFigure(figpath, figfile) |
|
|
194 | 200 | # store png plot to FTP server according to RT-Web format |
|
|
195 | 201 | name = self.getNameToFtp(thisDatetime, self.FTP_WEI, self.EXP_CODE, self.SUB_EXP_CODE, self.PLOT_CODE, self.PLOT_POS) |
|
|
196 | 202 | ftp_filename = os.path.join(figpath, name) |
|
|
197 | 203 | self.saveFigure(figpath, ftp_filename) |
|
|
198 | 204 | self.counter_imagwr = 0 |
|
|
199 | 205 | |
|
|
200 | 206 | |
|
|
201 | 207 | class CrossSpectraPlot(Figure): |
|
|
202 | 208 | |
|
|
203 | 209 | isConfig = None |
|
|
204 | 210 | __nsubplots = None |
|
|
205 | 211 | |
|
|
206 | 212 | WIDTH = None |
|
|
207 | 213 | HEIGHT = None |
|
|
208 | 214 | WIDTHPROF = None |
|
|
209 | 215 | HEIGHTPROF = None |
|
|
210 | 216 | PREFIX = 'cspc' |
|
|
211 | 217 | |
|
|
212 | 218 | def __init__(self): |
|
|
213 | 219 | |
|
|
214 | 220 | self.isConfig = False |
|
|
215 | 221 | self.__nsubplots = 4 |
|
|
216 | 222 | self.counter_imagwr = 0 |
|
|
217 | 223 | self.WIDTH = 250 |
|
|
218 | 224 | self.HEIGHT = 250 |
|
|
219 | 225 | self.WIDTHPROF = 0 |
|
|
220 | 226 | self.HEIGHTPROF = 0 |
|
|
221 | 227 | |
|
|
222 | 228 | self.PLOT_CODE = 1 |
|
|
223 | 229 | self.FTP_WEI = None |
|
|
224 | 230 | self.EXP_CODE = None |
|
|
225 | 231 | self.SUB_EXP_CODE = None |
|
|
226 | 232 | self.PLOT_POS = None |
|
|
227 | 233 | |
|
|
228 | 234 | def getSubplots(self): |
|
|
229 | 235 | |
|
|
230 | 236 | ncol = 4 |
|
|
231 | 237 | nrow = self.nplots |
|
|
232 | 238 | |
|
|
233 | 239 | return nrow, ncol |
|
|
234 | 240 | |
|
|
235 | 241 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): |
|
|
236 | 242 | |
|
|
237 | 243 | self.__showprofile = showprofile |
|
|
238 | 244 | self.nplots = nplots |
|
|
239 | 245 | |
|
|
240 | 246 | ncolspan = 1 |
|
|
241 | 247 | colspan = 1 |
|
|
242 | 248 | |
|
|
243 | 249 | self.createFigure(id = id, |
|
|
244 | 250 | wintitle = wintitle, |
|
|
245 | 251 | widthplot = self.WIDTH + self.WIDTHPROF, |
|
|
246 | 252 | heightplot = self.HEIGHT + self.HEIGHTPROF, |
|
|
247 | 253 | show=True) |
|
|
248 | 254 | |
|
|
249 | 255 | nrow, ncol = self.getSubplots() |
|
|
250 | 256 | |
|
|
251 | 257 | counter = 0 |
|
|
252 | 258 | for y in range(nrow): |
|
|
253 | 259 | for x in range(ncol): |
|
|
254 | 260 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) |
|
|
255 | 261 | |
|
|
256 | 262 | counter += 1 |
|
|
257 | 263 | |
|
|
258 | 264 | def run(self, dataOut, id, wintitle="", pairsList=None, |
|
|
259 | 265 | xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, |
|
|
260 | 266 | save=False, figpath='', figfile=None, ftp=False, wr_period=1, |
|
|
261 | 267 | power_cmap='jet', coherence_cmap='jet', phase_cmap='RdBu_r', show=True, |
|
|
262 | 268 | server=None, folder=None, username=None, password=None, |
|
|
263 | 269 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0): |
|
|
264 | 270 | |
|
|
265 | 271 | """ |
|
|
266 | 272 | |
|
|
267 | 273 | Input: |
|
|
268 | 274 | dataOut : |
|
|
269 | 275 | id : |
|
|
270 | 276 | wintitle : |
|
|
271 | 277 | channelList : |
|
|
272 | 278 | showProfile : |
|
|
273 | 279 | xmin : None, |
|
|
274 | 280 | xmax : None, |
|
|
275 | 281 | ymin : None, |
|
|
276 | 282 | ymax : None, |
|
|
277 | 283 | zmin : None, |
|
|
278 | 284 | zmax : None |
|
|
279 | 285 | """ |
|
|
280 | 286 | |
|
|
281 | 287 | if pairsList == None: |
|
|
282 | 288 | pairsIndexList = dataOut.pairsIndexList |
|
|
283 | 289 | else: |
|
|
284 | 290 | pairsIndexList = [] |
|
|
285 | 291 | for pair in pairsList: |
|
|
286 | 292 | if pair not in dataOut.pairsList: |
|
|
287 | 293 | raise ValueError, "Pair %s is not in dataOut.pairsList" %(pair) |
|
|
288 | 294 | pairsIndexList.append(dataOut.pairsList.index(pair)) |
|
|
289 | 295 | |
|
|
290 | 296 | if pairsIndexList == []: |
|
|
291 | 297 | return |
|
|
292 | 298 | |
|
|
293 | 299 | if len(pairsIndexList) > 4: |
|
|
294 | 300 | pairsIndexList = pairsIndexList[0:4] |
|
|
295 | 301 | factor = dataOut.normFactor |
|
|
296 | 302 | x = dataOut.getVelRange(1) |
|
|
297 | 303 | y = dataOut.getHeiRange() |
|
|
298 | 304 | z = dataOut.data_spc[:,:,:]/factor |
|
|
299 | 305 | # z = numpy.where(numpy.isfinite(z), z, numpy.NAN) |
|
|
300 | 306 | avg = numpy.abs(numpy.average(z, axis=1)) |
|
|
301 | 307 | noise = dataOut.noise()/factor |
|
|
302 | 308 | |
|
|
303 | 309 | zdB = 10*numpy.log10(z) |
|
|
304 | 310 | avgdB = 10*numpy.log10(avg) |
|
|
305 | 311 | noisedB = 10*numpy.log10(noise) |
|
|
306 | 312 | |
|
|
307 | 313 | |
|
|
308 | 314 | #thisDatetime = dataOut.datatime |
|
|
309 | 315 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[1]) |
|
|
310 | 316 | title = wintitle + " Cross-Spectra: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) |
|
|
311 | 317 | xlabel = "Velocity (m/s)" |
|
|
312 | 318 | ylabel = "Range (Km)" |
|
|
313 | 319 | |
|
|
314 | 320 | if not self.isConfig: |
|
|
315 | 321 | |
|
|
316 | 322 | nplots = len(pairsIndexList) |
|
|
317 | 323 | |
|
|
318 | 324 | self.setup(id=id, |
|
|
319 | 325 | nplots=nplots, |
|
|
320 | 326 | wintitle=wintitle, |
|
|
321 | 327 | showprofile=False, |
|
|
322 | 328 | show=show) |
|
|
323 | 329 | |
|
|
324 | 330 | if xmin == None: xmin = numpy.nanmin(x) |
|
|
325 | 331 | if xmax == None: xmax = numpy.nanmax(x) |
|
|
326 | 332 | if ymin == None: ymin = numpy.nanmin(y) |
|
|
327 | 333 | if ymax == None: ymax = numpy.nanmax(y) |
|
|
328 | 334 | if zmin == None: zmin = numpy.nanmin(avgdB)*0.9 |
|
|
329 | 335 | if zmax == None: zmax = numpy.nanmax(avgdB)*0.9 |
|
|
330 | 336 | |
|
|
331 | 337 | self.FTP_WEI = ftp_wei |
|
|
332 | 338 | self.EXP_CODE = exp_code |
|
|
333 | 339 | self.SUB_EXP_CODE = sub_exp_code |
|
|
334 | 340 | self.PLOT_POS = plot_pos |
|
|
335 | 341 | |
|
|
336 | 342 | self.isConfig = True |
|
|
337 | 343 | |
|
|
338 | 344 | self.setWinTitle(title) |
|
|
339 | 345 | |
|
|
340 | 346 | for i in range(self.nplots): |
|
|
341 | 347 | pair = dataOut.pairsList[pairsIndexList[i]] |
|
|
342 | 348 | str_datetime = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S")) |
|
|
343 | 349 | title = "Ch%d: %4.2fdB: %s" %(pair[0], noisedB[pair[0]], str_datetime) |
|
|
344 | 350 | zdB = 10.*numpy.log10(dataOut.data_spc[pair[0],:,:]/factor) |
|
|
345 | 351 | axes0 = self.axesList[i*self.__nsubplots] |
|
|
346 | 352 | axes0.pcolor(x, y, zdB, |
|
|
347 | 353 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax, |
|
|
348 | 354 | xlabel=xlabel, ylabel=ylabel, title=title, |
|
|
349 | 355 | ticksize=9, colormap=power_cmap, cblabel='') |
|
|
350 | 356 | |
|
|
351 | 357 | title = "Ch%d: %4.2fdB: %s" %(pair[1], noisedB[pair[1]], str_datetime) |
|
|
352 | 358 | zdB = 10.*numpy.log10(dataOut.data_spc[pair[1],:,:]/factor) |
|
|
353 | 359 | axes0 = self.axesList[i*self.__nsubplots+1] |
|
|
354 | 360 | axes0.pcolor(x, y, zdB, |
|
|
355 | 361 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax, |
|
|
356 | 362 | xlabel=xlabel, ylabel=ylabel, title=title, |
|
|
357 | 363 | ticksize=9, colormap=power_cmap, cblabel='') |
|
|
358 | 364 | |
|
|
359 | 365 | coherenceComplex = dataOut.data_cspc[pairsIndexList[i],:,:]/numpy.sqrt(dataOut.data_spc[pair[0],:,:]*dataOut.data_spc[pair[1],:,:]) |
|
|
360 | 366 | coherence = numpy.abs(coherenceComplex) |
|
|
361 | 367 | # phase = numpy.arctan(-1*coherenceComplex.imag/coherenceComplex.real)*180/numpy.pi |
|
|
362 | 368 | phase = numpy.arctan2(coherenceComplex.imag, coherenceComplex.real)*180/numpy.pi |
|
|
363 | 369 | |
|
|
364 | 370 | title = "Coherence %d%d" %(pair[0], pair[1]) |
|
|
365 | 371 | axes0 = self.axesList[i*self.__nsubplots+2] |
|
|
366 | 372 | axes0.pcolor(x, y, coherence, |
|
|
367 | 373 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=0, zmax=1, |
|
|
368 | 374 | xlabel=xlabel, ylabel=ylabel, title=title, |
|
|
369 | 375 | ticksize=9, colormap=coherence_cmap, cblabel='') |
|
|
370 | 376 | |
|
|
371 | 377 | title = "Phase %d%d" %(pair[0], pair[1]) |
|
|
372 | 378 | axes0 = self.axesList[i*self.__nsubplots+3] |
|
|
373 | 379 | axes0.pcolor(x, y, phase, |
|
|
374 | 380 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=-180, zmax=180, |
|
|
375 | 381 | xlabel=xlabel, ylabel=ylabel, title=title, |
|
|
376 | 382 | ticksize=9, colormap=phase_cmap, cblabel='') |
|
|
377 | 383 | |
|
|
378 | 384 | |
|
|
379 | 385 | |
|
|
380 | 386 | self.draw() |
|
|
381 | 387 | |
|
|
382 | 388 | if figfile == None: |
|
|
383 | 389 | str_datetime = thisDatetime.strftime("%Y%m%d_%H%M%S") |
|
|
384 | 390 | figfile = self.getFilename(name = str_datetime) |
|
|
385 | 391 | |
|
|
386 | 392 | if figpath != '': |
|
|
387 | 393 | self.counter_imagwr += 1 |
|
|
388 | 394 | if (self.counter_imagwr>=wr_period): |
|
|
389 | 395 | # store png plot to local folder |
|
|
390 | 396 | self.saveFigure(figpath, figfile) |
|
|
391 | 397 | # store png plot to FTP server according to RT-Web format |
|
|
392 | 398 | name = self.getNameToFtp(thisDatetime, self.FTP_WEI, self.EXP_CODE, self.SUB_EXP_CODE, self.PLOT_CODE, self.PLOT_POS) |
|
|
393 | 399 | ftp_filename = os.path.join(figpath, name) |
|
|
394 | 400 | self.saveFigure(figpath, ftp_filename) |
|
|
395 | 401 | self.counter_imagwr = 0 |
|
|
396 | 402 | |
|
|
397 | 403 | |
|
|
398 | 404 | class RTIPlot(Figure): |
|
|
399 | 405 | |
|
|
400 | 406 | isConfig = None |
|
|
401 | 407 | __nsubplots = None |
|
|
402 | 408 | |
|
|
403 | 409 | WIDTHPROF = None |
|
|
404 | 410 | HEIGHTPROF = None |
|
|
405 | 411 | PREFIX = 'rti' |
|
|
406 | 412 | |
|
|
407 | 413 | def __init__(self): |
|
|
408 | 414 | |
|
|
409 | 415 | self.timerange = 2*60*60 |
|
|
410 | 416 | self.isConfig = False |
|
|
411 | 417 | self.__nsubplots = 1 |
|
|
412 | 418 | |
|
|
413 | 419 | self.WIDTH = 800 |
|
|
414 | 420 | self.HEIGHT = 150 |
|
|
415 | 421 | self.WIDTHPROF = 120 |
|
|
416 | 422 | self.HEIGHTPROF = 0 |
|
|
417 | 423 | self.counter_imagwr = 0 |
|
|
418 | 424 | |
|
|
419 | 425 | self.PLOT_CODE = 0 |
|
|
420 | 426 | self.FTP_WEI = None |
|
|
421 | 427 | self.EXP_CODE = None |
|
|
422 | 428 | self.SUB_EXP_CODE = None |
|
|
423 | 429 | self.PLOT_POS = None |
|
|
424 | 430 | self.tmin = None |
|
|
425 | 431 | self.tmax = None |
|
|
426 | 432 | |
|
|
427 | 433 | self.xmin = None |
|
|
428 | 434 | self.xmax = None |
|
|
429 | 435 | |
|
|
430 | 436 | self.figfile = None |
|
|
431 | 437 | |
|
|
432 | 438 | def getSubplots(self): |
|
|
433 | 439 | |
|
|
434 | 440 | ncol = 1 |
|
|
435 | 441 | nrow = self.nplots |
|
|
436 | 442 | |
|
|
437 | 443 | return nrow, ncol |
|
|
438 | 444 | |
|
|
439 | 445 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): |
|
|
440 | 446 | |
|
|
441 | 447 | self.__showprofile = showprofile |
|
|
442 | 448 | self.nplots = nplots |
|
|
443 | 449 | |
|
|
444 | 450 | ncolspan = 1 |
|
|
445 | 451 | colspan = 1 |
|
|
446 | 452 | if showprofile: |
|
|
447 | 453 | ncolspan = 7 |
|
|
448 | 454 | colspan = 6 |
|
|
449 | 455 | self.__nsubplots = 2 |
|
|
450 | 456 | |
|
|
451 | 457 | self.createFigure(id = id, |
|
|
452 | 458 | wintitle = wintitle, |
|
|
453 | 459 | widthplot = self.WIDTH + self.WIDTHPROF, |
|
|
454 | 460 | heightplot = self.HEIGHT + self.HEIGHTPROF, |
|
|
455 | 461 | show=show) |
|
|
456 | 462 | |
|
|
457 | 463 | nrow, ncol = self.getSubplots() |
|
|
458 | 464 | |
|
|
459 | 465 | counter = 0 |
|
|
460 | 466 | for y in range(nrow): |
|
|
461 | 467 | for x in range(ncol): |
|
|
462 | 468 | |
|
|
463 | 469 | if counter >= self.nplots: |
|
|
464 | 470 | break |
|
|
465 | 471 | |
|
|
466 | 472 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) |
|
|
467 | 473 | |
|
|
468 | 474 | if showprofile: |
|
|
469 | 475 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan+colspan, 1, 1) |
|
|
470 | 476 | |
|
|
471 | 477 | counter += 1 |
|
|
472 | 478 | |
|
|
473 | 479 | def run(self, dataOut, id, wintitle="", channelList=None, showprofile='True', |
|
|
474 | 480 | xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, |
|
|
475 | 481 | timerange=None, |
|
|
476 | 482 | save=False, figpath='', lastone=0,figfile=None, ftp=False, wr_period=1, show=True, |
|
|
477 | 483 | server=None, folder=None, username=None, password=None, |
|
|
478 | 484 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0): |
|
|
479 | 485 | |
|
|
480 | 486 | """ |
|
|
481 | 487 | |
|
|
482 | 488 | Input: |
|
|
483 | 489 | dataOut : |
|
|
484 | 490 | id : |
|
|
485 | 491 | wintitle : |
|
|
486 | 492 | channelList : |
|
|
487 | 493 | showProfile : |
|
|
488 | 494 | xmin : None, |
|
|
489 | 495 | xmax : None, |
|
|
490 | 496 | ymin : None, |
|
|
491 | 497 | ymax : None, |
|
|
492 | 498 | zmin : None, |
|
|
493 | 499 | zmax : None |
|
|
494 | 500 | """ |
|
|
495 | 501 | |
|
|
496 | 502 | if channelList == None: |
|
|
497 | 503 | channelIndexList = dataOut.channelIndexList |
|
|
498 | 504 | else: |
|
|
499 | 505 | channelIndexList = [] |
|
|
500 | 506 | for channel in channelList: |
|
|
501 | 507 | if channel not in dataOut.channelList: |
|
|
502 | 508 | raise ValueError, "Channel %d is not in dataOut.channelList" |
|
|
503 | 509 | channelIndexList.append(dataOut.channelList.index(channel)) |
|
|
504 | 510 | |
|
|
505 | 511 | if timerange != None: |
|
|
506 | 512 | self.timerange = timerange |
|
|
507 | 513 | |
|
|
508 | 514 | #tmin = None |
|
|
509 | 515 | #tmax = None |
|
|
510 | 516 | factor = dataOut.normFactor |
|
|
511 | 517 | x = dataOut.getTimeRange() |
|
|
512 | 518 | y = dataOut.getHeiRange() |
|
|
513 | 519 | |
|
|
514 | 520 | z = dataOut.data_spc[channelIndexList,:,:]/factor |
|
|
515 | 521 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) |
|
|
516 | 522 | avg = numpy.average(z, axis=1) |
|
|
517 | 523 | |
|
|
518 | 524 | avgdB = 10.*numpy.log10(avg) |
|
|
519 | 525 | |
|
|
520 | 526 | |
|
|
521 | 527 | # thisDatetime = dataOut.datatime |
|
|
522 | 528 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[1]) |
|
|
523 | 529 | title = wintitle + " RTI" #: %s" %(thisDatetime.strftime("%d-%b-%Y")) |
|
|
524 | 530 | xlabel = "" |
|
|
525 | 531 | ylabel = "Range (Km)" |
|
|
526 | 532 | |
|
|
527 | 533 | if not self.isConfig: |
|
|
528 | 534 | |
|
|
529 | 535 | nplots = len(channelIndexList) |
|
|
530 | 536 | |
|
|
531 | 537 | self.setup(id=id, |
|
|
532 | 538 | nplots=nplots, |
|
|
533 | 539 | wintitle=wintitle, |
|
|
534 | 540 | showprofile=showprofile, |
|
|
535 | 541 | show=show) |
|
|
536 | 542 | |
|
|
537 | 543 | self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange) |
|
|
538 | 544 | |
|
|
539 | 545 | # if timerange != None: |
|
|
540 | 546 | # self.timerange = timerange |
|
|
541 | 547 | # self.xmin, self.tmax = self.getTimeLim(x, xmin, xmax, timerange) |
|
|
542 | 548 | |
|
|
543 | 549 | |
|
|
544 | 550 | |
|
|
545 | 551 | if ymin == None: ymin = numpy.nanmin(y) |
|
|
546 | 552 | if ymax == None: ymax = numpy.nanmax(y) |
|
|
547 | 553 | if zmin == None: zmin = numpy.nanmin(avgdB)*0.9 |
|
|
548 | 554 | if zmax == None: zmax = numpy.nanmax(avgdB)*0.9 |
|
|
549 | 555 | |
|
|
550 | 556 | self.FTP_WEI = ftp_wei |
|
|
551 | 557 | self.EXP_CODE = exp_code |
|
|
552 | 558 | self.SUB_EXP_CODE = sub_exp_code |
|
|
553 | 559 | self.PLOT_POS = plot_pos |
|
|
554 | 560 | |
|
|
555 | 561 | self.name = thisDatetime.strftime("%Y%m%d_%H%M%S") |
|
|
556 | 562 | self.isConfig = True |
|
|
557 | 563 | self.figfile = figfile |
|
|
558 | 564 | |
|
|
559 | 565 | self.setWinTitle(title) |
|
|
560 | 566 | |
|
|
561 | 567 | if ((self.xmax - x[1]) < (x[1]-x[0])): |
|
|
562 | 568 | x[1] = self.xmax |
|
|
563 | 569 | |
|
|
564 | 570 | for i in range(self.nplots): |
|
|
565 | 571 | title = "Channel %d: %s" %(dataOut.channelList[i]+1, thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) |
|
|
572 | if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)): | |
|
|
573 | title = title + '_' + 'azimuth,zenith=%2.2f,%2.2f'%(dataOut.azimuth, dataOut.zenith) | |
|
|
566 | 574 | axes = self.axesList[i*self.__nsubplots] |
|
|
567 | 575 | zdB = avgdB[i].reshape((1,-1)) |
|
|
568 | 576 | axes.pcolorbuffer(x, y, zdB, |
|
|
569 | 577 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax, |
|
|
570 | 578 | xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True, |
|
|
571 | 579 | ticksize=9, cblabel='', cbsize="1%") |
|
|
572 | 580 | |
|
|
573 | 581 | if self.__showprofile: |
|
|
574 | 582 | axes = self.axesList[i*self.__nsubplots +1] |
|
|
575 | 583 | axes.pline(avgdB[i], y, |
|
|
576 | 584 | xmin=zmin, xmax=zmax, ymin=ymin, ymax=ymax, |
|
|
577 | 585 | xlabel='dB', ylabel='', title='', |
|
|
578 | 586 | ytick_visible=False, |
|
|
579 | 587 | grid='x') |
|
|
580 | 588 | |
|
|
581 | 589 | self.draw() |
|
|
582 | 590 | |
|
|
583 | 591 | if x[1] >= self.axesList[0].xmax: |
|
|
584 | 592 | self.counter_imagwr = wr_period |
|
|
585 | 593 | self.__isConfig = False |
|
|
586 | 594 | |
|
|
587 | 595 | |
|
|
588 | 596 | if self.figfile == None: |
|
|
589 | 597 | str_datetime = thisDatetime.strftime("%Y%m%d_%H%M%S") |
|
|
590 | 598 | self.figfile = self.getFilename(name = str_datetime) |
|
|
591 | 599 | |
|
|
592 | 600 | if figpath != '': |
|
|
593 | 601 | |
|
|
594 | 602 | self.counter_imagwr += 1 |
|
|
595 | 603 | if (self.counter_imagwr>=wr_period): |
|
|
596 | 604 | # store png plot to local folder |
|
|
597 | 605 | self.saveFigure(figpath, self.figfile) |
|
|
598 | 606 | # store png plot to FTP server according to RT-Web format |
|
|
599 | 607 | name = self.getNameToFtp(thisDatetime, self.FTP_WEI, self.EXP_CODE, self.SUB_EXP_CODE, self.PLOT_CODE, self.PLOT_POS) |
|
|
600 | 608 | ftp_filename = os.path.join(figpath, name) |
|
|
601 | 609 | self.saveFigure(figpath, ftp_filename) |
|
|
602 | 610 | |
|
|
603 | 611 | self.counter_imagwr = 0 |
|
|
604 | 612 | |
|
|
605 | 613 | |
|
|
606 | 614 | class CoherenceMap(Figure): |
|
|
607 | 615 | isConfig = None |
|
|
608 | 616 | __nsubplots = None |
|
|
609 | 617 | |
|
|
610 | 618 | WIDTHPROF = None |
|
|
611 | 619 | HEIGHTPROF = None |
|
|
612 | 620 | PREFIX = 'cmap' |
|
|
613 | 621 | |
|
|
614 | 622 | def __init__(self): |
|
|
615 | 623 | self.timerange = 2*60*60 |
|
|
616 | 624 | self.isConfig = False |
|
|
617 | 625 | self.__nsubplots = 1 |
|
|
618 | 626 | |
|
|
619 | 627 | self.WIDTH = 800 |
|
|
620 | 628 | self.HEIGHT = 150 |
|
|
621 | 629 | self.WIDTHPROF = 120 |
|
|
622 | 630 | self.HEIGHTPROF = 0 |
|
|
623 | 631 | self.counter_imagwr = 0 |
|
|
624 | 632 | |
|
|
625 | 633 | self.PLOT_CODE = 3 |
|
|
626 | 634 | self.FTP_WEI = None |
|
|
627 | 635 | self.EXP_CODE = None |
|
|
628 | 636 | self.SUB_EXP_CODE = None |
|
|
629 | 637 | self.PLOT_POS = None |
|
|
630 | 638 | self.counter_imagwr = 0 |
|
|
631 | 639 | |
|
|
632 | 640 | self.xmin = None |
|
|
633 | 641 | self.xmax = None |
|
|
634 | 642 | |
|
|
635 | 643 | def getSubplots(self): |
|
|
636 | 644 | ncol = 1 |
|
|
637 | 645 | nrow = self.nplots*2 |
|
|
638 | 646 | |
|
|
639 | 647 | return nrow, ncol |
|
|
640 | 648 | |
|
|
641 | 649 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): |
|
|
642 | 650 | self.__showprofile = showprofile |
|
|
643 | 651 | self.nplots = nplots |
|
|
644 | 652 | |
|
|
645 | 653 | ncolspan = 1 |
|
|
646 | 654 | colspan = 1 |
|
|
647 | 655 | if showprofile: |
|
|
648 | 656 | ncolspan = 7 |
|
|
649 | 657 | colspan = 6 |
|
|
650 | 658 | self.__nsubplots = 2 |
|
|
651 | 659 | |
|
|
652 | 660 | self.createFigure(id = id, |
|
|
653 | 661 | wintitle = wintitle, |
|
|
654 | 662 | widthplot = self.WIDTH + self.WIDTHPROF, |
|
|
655 | 663 | heightplot = self.HEIGHT + self.HEIGHTPROF, |
|
|
656 | 664 | show=True) |
|
|
657 | 665 | |
|
|
658 | 666 | nrow, ncol = self.getSubplots() |
|
|
659 | 667 | |
|
|
660 | 668 | for y in range(nrow): |
|
|
661 | 669 | for x in range(ncol): |
|
|
662 | 670 | |
|
|
663 | 671 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) |
|
|
664 | 672 | |
|
|
665 | 673 | if showprofile: |
|
|
666 | 674 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan+colspan, 1, 1) |
|
|
667 | 675 | |
|
|
668 | 676 | def run(self, dataOut, id, wintitle="", pairsList=None, showprofile='True', |
|
|
669 | 677 | xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, |
|
|
670 | 678 | timerange=None, |
|
|
671 | 679 | save=False, figpath='', figfile=None, ftp=False, wr_period=1, |
|
|
672 | 680 | coherence_cmap='jet', phase_cmap='RdBu_r', show=True, |
|
|
673 | 681 | server=None, folder=None, username=None, password=None, |
|
|
674 | 682 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0): |
|
|
675 | 683 | |
|
|
676 | 684 | if pairsList == None: |
|
|
677 | 685 | pairsIndexList = dataOut.pairsIndexList |
|
|
678 | 686 | else: |
|
|
679 | 687 | pairsIndexList = [] |
|
|
680 | 688 | for pair in pairsList: |
|
|
681 | 689 | if pair not in dataOut.pairsList: |
|
|
682 | 690 | raise ValueError, "Pair %s is not in dataOut.pairsList" %(pair) |
|
|
683 | 691 | pairsIndexList.append(dataOut.pairsList.index(pair)) |
|
|
684 | 692 | |
|
|
685 | 693 | if timerange != None: |
|
|
686 | 694 | self.timerange = timerange |
|
|
687 | 695 | |
|
|
688 | 696 | if pairsIndexList == []: |
|
|
689 | 697 | return |
|
|
690 | 698 | |
|
|
691 | 699 | if len(pairsIndexList) > 4: |
|
|
692 | 700 | pairsIndexList = pairsIndexList[0:4] |
|
|
693 | 701 | |
|
|
694 | 702 | # tmin = None |
|
|
695 | 703 | # tmax = None |
|
|
696 | 704 | x = dataOut.getTimeRange() |
|
|
697 | 705 | y = dataOut.getHeiRange() |
|
|
698 | 706 | |
|
|
699 | 707 | #thisDatetime = dataOut.datatime |
|
|
700 | 708 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[1]) |
|
|
701 | 709 | title = wintitle + " CoherenceMap" #: %s" %(thisDatetime.strftime("%d-%b-%Y")) |
|
|
702 | 710 | xlabel = "" |
|
|
703 | 711 | ylabel = "Range (Km)" |
|
|
704 | 712 | |
|
|
705 | 713 | if not self.isConfig: |
|
|
706 | 714 | nplots = len(pairsIndexList) |
|
|
707 | 715 | self.setup(id=id, |
|
|
708 | 716 | nplots=nplots, |
|
|
709 | 717 | wintitle=wintitle, |
|
|
710 | 718 | showprofile=showprofile, |
|
|
711 | 719 | show=show) |
|
|
712 | 720 | |
|
|
713 | 721 | #tmin, tmax = self.getTimeLim(x, xmin, xmax) |
|
|
714 | 722 | |
|
|
715 | 723 | self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange) |
|
|
716 | 724 | |
|
|
717 | 725 | if ymin == None: ymin = numpy.nanmin(y) |
|
|
718 | 726 | if ymax == None: ymax = numpy.nanmax(y) |
|
|
719 | 727 | if zmin == None: zmin = 0. |
|
|
720 | 728 | if zmax == None: zmax = 1. |
|
|
721 | 729 | |
|
|
722 | 730 | self.FTP_WEI = ftp_wei |
|
|
723 | 731 | self.EXP_CODE = exp_code |
|
|
724 | 732 | self.SUB_EXP_CODE = sub_exp_code |
|
|
725 | 733 | self.PLOT_POS = plot_pos |
|
|
726 | 734 | |
|
|
727 | 735 | self.name = thisDatetime.strftime("%Y%m%d_%H%M%S") |
|
|
728 | 736 | |
|
|
729 | 737 | self.isConfig = True |
|
|
730 | 738 | |
|
|
731 | 739 | self.setWinTitle(title) |
|
|
732 | 740 | |
|
|
733 | 741 | if ((self.xmax - x[1]) < (x[1]-x[0])): |
|
|
734 | 742 | x[1] = self.xmax |
|
|
735 | 743 | |
|
|
736 | 744 | for i in range(self.nplots): |
|
|
737 | 745 | |
|
|
738 | 746 | pair = dataOut.pairsList[pairsIndexList[i]] |
|
|
739 | 747 | |
|
|
740 | 748 | ccf = numpy.average(dataOut.data_cspc[pairsIndexList[i],:,:],axis=0) |
|
|
741 | 749 | powa = numpy.average(dataOut.data_spc[pair[0],:,:],axis=0) |
|
|
742 | 750 | powb = numpy.average(dataOut.data_spc[pair[1],:,:],axis=0) |
|
|
743 | 751 | |
|
|
744 | 752 | |
|
|
745 | 753 | avgcoherenceComplex = ccf/numpy.sqrt(powa*powb) |
|
|
746 | 754 | coherence = numpy.abs(avgcoherenceComplex) |
|
|
747 | 755 | |
|
|
748 | 756 | z = coherence.reshape((1,-1)) |
|
|
749 | 757 | |
|
|
750 | 758 | counter = 0 |
|
|
751 | 759 | |
|
|
752 | 760 | title = "Coherence %d%d: %s" %(pair[0], pair[1], thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) |
|
|
753 | 761 | axes = self.axesList[i*self.__nsubplots*2] |
|
|
754 | 762 | axes.pcolorbuffer(x, y, z, |
|
|
755 | 763 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax, |
|
|
756 | 764 | xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True, |
|
|
757 | 765 | ticksize=9, cblabel='', colormap=coherence_cmap, cbsize="1%") |
|
|
758 | 766 | |
|
|
759 | 767 | if self.__showprofile: |
|
|
760 | 768 | counter += 1 |
|
|
761 | 769 | axes = self.axesList[i*self.__nsubplots*2 + counter] |
|
|
762 | 770 | axes.pline(coherence, y, |
|
|
763 | 771 | xmin=zmin, xmax=zmax, ymin=ymin, ymax=ymax, |
|
|
764 | 772 | xlabel='', ylabel='', title='', ticksize=7, |
|
|
765 | 773 | ytick_visible=False, nxticks=5, |
|
|
766 | 774 | grid='x') |
|
|
767 | 775 | |
|
|
768 | 776 | counter += 1 |
|
|
769 | 777 | |
|
|
770 | 778 | phase = numpy.arctan2(avgcoherenceComplex.imag, avgcoherenceComplex.real)*180/numpy.pi |
|
|
771 | 779 | |
|
|
772 | 780 | z = phase.reshape((1,-1)) |
|
|
773 | 781 | |
|
|
774 | 782 | title = "Phase %d%d: %s" %(pair[0], pair[1], thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) |
|
|
775 | 783 | axes = self.axesList[i*self.__nsubplots*2 + counter] |
|
|
776 | 784 | axes.pcolorbuffer(x, y, z, |
|
|
777 | 785 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=-180, zmax=180, |
|
|
778 | 786 | xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True, |
|
|
779 | 787 | ticksize=9, cblabel='', colormap=phase_cmap, cbsize="1%") |
|
|
780 | 788 | |
|
|
781 | 789 | if self.__showprofile: |
|
|
782 | 790 | counter += 1 |
|
|
783 | 791 | axes = self.axesList[i*self.__nsubplots*2 + counter] |
|
|
784 | 792 | axes.pline(phase, y, |
|
|
785 | 793 | xmin=-180, xmax=180, ymin=ymin, ymax=ymax, |
|
|
786 | 794 | xlabel='', ylabel='', title='', ticksize=7, |
|
|
787 | 795 | ytick_visible=False, nxticks=4, |
|
|
788 | 796 | grid='x') |
|
|
789 | 797 | |
|
|
790 | 798 | self.draw() |
|
|
791 | 799 | |
|
|
792 | 800 | if x[1] >= self.axesList[0].xmax: |
|
|
793 | 801 | self.counter_imagwr = wr_period |
|
|
794 | 802 | self.__isConfig = False |
|
|
795 | 803 | |
|
|
796 | 804 | if figfile == None: |
|
|
797 | 805 | str_datetime = thisDatetime.strftime("%Y%m%d_%H%M%S") |
|
|
798 | 806 | figfile = self.getFilename(name = str_datetime) |
|
|
799 | 807 | |
|
|
800 | 808 | if figpath != '': |
|
|
801 | 809 | |
|
|
802 | 810 | self.counter_imagwr += 1 |
|
|
803 | 811 | if (self.counter_imagwr>=wr_period): |
|
|
804 | 812 | # store png plot to local folder |
|
|
805 | 813 | self.saveFigure(figpath, figfile) |
|
|
806 | 814 | # store png plot to FTP server according to RT-Web format |
|
|
807 | 815 | name = self.getNameToFtp(thisDatetime, self.FTP_WEI, self.EXP_CODE, self.SUB_EXP_CODE, self.PLOT_CODE, self.PLOT_POS) |
|
|
808 | 816 | ftp_filename = os.path.join(figpath, name) |
|
|
809 | 817 | self.saveFigure(figpath, ftp_filename) |
|
|
810 | 818 | |
|
|
811 | 819 | self.counter_imagwr = 0 |
|
|
812 | 820 | |
|
|
813 | 821 | class PowerProfile(Figure): |
|
|
814 | 822 | isConfig = None |
|
|
815 | 823 | __nsubplots = None |
|
|
816 | 824 | |
|
|
817 | 825 | WIDTHPROF = None |
|
|
818 | 826 | HEIGHTPROF = None |
|
|
819 | 827 | PREFIX = 'spcprofile' |
|
|
820 | 828 | |
|
|
821 | 829 | def __init__(self): |
|
|
822 | 830 | self.isConfig = False |
|
|
823 | 831 | self.__nsubplots = 1 |
|
|
824 | 832 | |
|
|
825 | 833 | self.WIDTH = 300 |
|
|
826 | 834 | self.HEIGHT = 500 |
|
|
827 | 835 | self.counter_imagwr = 0 |
|
|
828 | 836 | |
|
|
829 | 837 | def getSubplots(self): |
|
|
830 | 838 | ncol = 1 |
|
|
831 | 839 | nrow = 1 |
|
|
832 | 840 | |
|
|
833 | 841 | return nrow, ncol |
|
|
834 | 842 | |
|
|
835 | 843 | def setup(self, id, nplots, wintitle, show): |
|
|
836 | 844 | |
|
|
837 | 845 | self.nplots = nplots |
|
|
838 | 846 | |
|
|
839 | 847 | ncolspan = 1 |
|
|
840 | 848 | colspan = 1 |
|
|
841 | 849 | |
|
|
842 | 850 | self.createFigure(id = id, |
|
|
843 | 851 | wintitle = wintitle, |
|
|
844 | 852 | widthplot = self.WIDTH, |
|
|
845 | 853 | heightplot = self.HEIGHT, |
|
|
846 | 854 | show=show) |
|
|
847 | 855 | |
|
|
848 | 856 | nrow, ncol = self.getSubplots() |
|
|
849 | 857 | |
|
|
850 | 858 | counter = 0 |
|
|
851 | 859 | for y in range(nrow): |
|
|
852 | 860 | for x in range(ncol): |
|
|
853 | 861 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) |
|
|
854 | 862 | |
|
|
855 | 863 | def run(self, dataOut, id, wintitle="", channelList=None, |
|
|
856 | 864 | xmin=None, xmax=None, ymin=None, ymax=None, |
|
|
857 | 865 | save=False, figpath='', figfile=None, show=True, wr_period=1, |
|
|
858 | 866 | server=None, folder=None, username=None, password=None,): |
|
|
859 | 867 | |
|
|
860 | 868 | if dataOut.flagNoData: |
|
|
861 | 869 | return None |
|
|
862 | 870 | |
|
|
863 | 871 | if channelList == None: |
|
|
864 | 872 | channelIndexList = dataOut.channelIndexList |
|
|
865 | 873 | channelList = dataOut.channelList |
|
|
866 | 874 | else: |
|
|
867 | 875 | channelIndexList = [] |
|
|
868 | 876 | for channel in channelList: |
|
|
869 | 877 | if channel not in dataOut.channelList: |
|
|
870 | 878 | raise ValueError, "Channel %d is not in dataOut.channelList" |
|
|
871 | 879 | channelIndexList.append(dataOut.channelList.index(channel)) |
|
|
872 | 880 | |
|
|
873 | 881 | try: |
|
|
874 | 882 | factor = dataOut.normFactor |
|
|
875 | 883 | except: |
|
|
876 | 884 | factor = 1 |
|
|
877 | 885 | |
|
|
878 | 886 | y = dataOut.getHeiRange() |
|
|
879 | 887 | |
|
|
880 | 888 | #for voltage |
|
|
881 | 889 | if dataOut.type == 'Voltage': |
|
|
882 | 890 | x = dataOut.data[channelIndexList,:] * numpy.conjugate(dataOut.data[channelIndexList,:]) |
|
|
883 | 891 | x = x.real |
|
|
884 | 892 | x = numpy.where(numpy.isfinite(x), x, numpy.NAN) |
|
|
885 | 893 | |
|
|
886 | 894 | #for spectra |
|
|
887 | 895 | if dataOut.type == 'Spectra': |
|
|
888 | 896 | x = dataOut.data_spc[channelIndexList,:,:]/factor |
|
|
889 | 897 | x = numpy.where(numpy.isfinite(x), x, numpy.NAN) |
|
|
890 | 898 | x = numpy.average(x, axis=1) |
|
|
891 | 899 | |
|
|
892 | 900 | |
|
|
893 | 901 | xdB = 10*numpy.log10(x) |
|
|
894 | 902 | |
|
|
895 | 903 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[1]) |
|
|
896 | 904 | title = wintitle + " Power Profile %s" %(thisDatetime.strftime("%d-%b-%Y")) |
|
|
897 | 905 | xlabel = "dB" |
|
|
898 | 906 | ylabel = "Range (Km)" |
|
|
899 | 907 | |
|
|
900 | 908 | if not self.isConfig: |
|
|
901 | 909 | |
|
|
902 | 910 | nplots = 1 |
|
|
903 | 911 | |
|
|
904 | 912 | self.setup(id=id, |
|
|
905 | 913 | nplots=nplots, |
|
|
906 | 914 | wintitle=wintitle, |
|
|
907 | 915 | show=show) |
|
|
908 | 916 | |
|
|
909 | 917 | if ymin == None: ymin = numpy.nanmin(y) |
|
|
910 | 918 | if ymax == None: ymax = numpy.nanmax(y) |
|
|
911 | 919 | if xmin == None: xmin = numpy.nanmin(xdB)*0.9 |
|
|
912 | 920 | if xmax == None: xmax = numpy.nanmax(xdB)*0.9 |
|
|
913 | 921 | |
|
|
914 | 922 | self.__isConfig = True |
|
|
915 | 923 | |
|
|
916 | 924 | self.setWinTitle(title) |
|
|
917 | 925 | |
|
|
918 | 926 | title = "Power Profile: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) |
|
|
919 | 927 | axes = self.axesList[0] |
|
|
920 | 928 | |
|
|
921 | 929 | legendlabels = ["channel %d"%x for x in channelList] |
|
|
922 | 930 | axes.pmultiline(xdB, y, |
|
|
923 | 931 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, |
|
|
924 | 932 | xlabel=xlabel, ylabel=ylabel, title=title, legendlabels=legendlabels, |
|
|
925 | 933 | ytick_visible=True, nxticks=5, |
|
|
926 | 934 | grid='x') |
|
|
927 | 935 | |
|
|
928 | 936 | self.draw() |
|
|
929 | 937 | |
|
|
930 | 938 | if figfile == None: |
|
|
931 | 939 | str_datetime = thisDatetime.strftime("%Y%m%d_%H%M%S") |
|
|
932 | 940 | figfile = self.getFilename(name = str_datetime) |
|
|
933 | 941 | |
|
|
934 | 942 | if figpath != '': |
|
|
935 | 943 | self.counter_imagwr += 1 |
|
|
936 | 944 | if (self.counter_imagwr>=wr_period): |
|
|
937 | 945 | # store png plot to local folder |
|
|
938 | 946 | self.saveFigure(figpath, figfile) |
|
|
939 | 947 | # store png plot to FTP server according to RT-Web format |
|
|
940 | 948 | #name = self.getNameToFtp(thisDatetime, self.FTP_WEI, self.EXP_CODE, self.SUB_EXP_CODE, self.PLOT_CODE, self.PLOT_POS) |
|
|
941 | 949 | #ftp_filename = os.path.join(figpath, name) |
|
|
942 | 950 | #self.saveFigure(figpath, ftp_filename) |
|
|
943 | 951 | self.counter_imagwr = 0 |
|
|
944 | 952 | |
|
|
945 | 953 | |
|
|
946 | 954 | |
|
|
947 | 955 | class Noise(Figure): |
|
|
948 | 956 | |
|
|
949 | 957 | isConfig = None |
|
|
950 | 958 | __nsubplots = None |
|
|
951 | 959 | |
|
|
952 | 960 | PREFIX = 'noise' |
|
|
953 | 961 | |
|
|
954 | 962 | def __init__(self): |
|
|
955 | 963 | |
|
|
956 | 964 | self.timerange = 24*60*60 |
|
|
957 | 965 | self.isConfig = False |
|
|
958 | 966 | self.__nsubplots = 1 |
|
|
959 | 967 | self.counter_imagwr = 0 |
|
|
960 | 968 | self.WIDTH = 600 |
|
|
961 | 969 | self.HEIGHT = 300 |
|
|
962 | 970 | self.WIDTHPROF = 120 |
|
|
963 | 971 | self.HEIGHTPROF = 0 |
|
|
964 | 972 | self.xdata = None |
|
|
965 | 973 | self.ydata = None |
|
|
966 | 974 | |
|
|
967 | 975 | self.PLOT_CODE = 17 |
|
|
968 | 976 | self.FTP_WEI = None |
|
|
969 | 977 | self.EXP_CODE = None |
|
|
970 | 978 | self.SUB_EXP_CODE = None |
|
|
971 | 979 | self.PLOT_POS = None |
|
|
972 | 980 | self.figfile = None |
|
|
973 | 981 | |
|
|
974 | 982 | def getSubplots(self): |
|
|
975 | 983 | |
|
|
976 | 984 | ncol = 1 |
|
|
977 | 985 | nrow = 1 |
|
|
978 | 986 | |
|
|
979 | 987 | return nrow, ncol |
|
|
980 | 988 | |
|
|
981 | 989 | def openfile(self, filename): |
|
|
982 | 990 | f = open(filename,'w+') |
|
|
983 | 991 | f.write('\n\n') |
|
|
984 | 992 | f.write('JICAMARCA RADIO OBSERVATORY - Noise \n') |
|
|
985 | 993 | f.write('DD MM YYYY HH MM SS Channel0 Channel1 Channel2 Channel3\n\n' ) |
|
|
986 | 994 | f.close() |
|
|
987 | 995 | |
|
|
988 | 996 | def save_data(self, filename_phase, data, data_datetime): |
|
|
989 | 997 | f=open(filename_phase,'a') |
|
|
990 | 998 | timetuple_data = data_datetime.timetuple() |
|
|
991 | 999 | day = str(timetuple_data.tm_mday) |
|
|
992 | 1000 | month = str(timetuple_data.tm_mon) |
|
|
993 | 1001 | year = str(timetuple_data.tm_year) |
|
|
994 | 1002 | hour = str(timetuple_data.tm_hour) |
|
|
995 | 1003 | minute = str(timetuple_data.tm_min) |
|
|
996 | 1004 | second = str(timetuple_data.tm_sec) |
|
|
997 | 1005 | f.write(day+' '+month+' '+year+' '+hour+' '+minute+' '+second+' '+str(data[0])+' '+str(data[1])+' '+str(data[2])+' '+str(data[3])+'\n') |
|
|
998 | 1006 | f.close() |
|
|
999 | 1007 | |
|
|
1000 | 1008 | |
|
|
1001 | 1009 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): |
|
|
1002 | 1010 | |
|
|
1003 | 1011 | self.__showprofile = showprofile |
|
|
1004 | 1012 | self.nplots = nplots |
|
|
1005 | 1013 | |
|
|
1006 | 1014 | ncolspan = 7 |
|
|
1007 | 1015 | colspan = 6 |
|
|
1008 | 1016 | self.__nsubplots = 2 |
|
|
1009 | 1017 | |
|
|
1010 | 1018 | self.createFigure(id = id, |
|
|
1011 | 1019 | wintitle = wintitle, |
|
|
1012 | 1020 | widthplot = self.WIDTH+self.WIDTHPROF, |
|
|
1013 | 1021 | heightplot = self.HEIGHT+self.HEIGHTPROF, |
|
|
1014 | 1022 | show=show) |
|
|
1015 | 1023 | |
|
|
1016 | 1024 | nrow, ncol = self.getSubplots() |
|
|
1017 | 1025 | |
|
|
1018 | 1026 | self.addAxes(nrow, ncol*ncolspan, 0, 0, colspan, 1) |
|
|
1019 | 1027 | |
|
|
1020 | 1028 | |
|
|
1021 | 1029 | def run(self, dataOut, id, wintitle="", channelList=None, showprofile='True', |
|
|
1022 | 1030 | xmin=None, xmax=None, ymin=None, ymax=None, |
|
|
1023 | 1031 | timerange=None, |
|
|
1024 | 1032 | save=False, figpath='', figfile=None, show=True, ftp=False, wr_period=1, |
|
|
1025 | 1033 | server=None, folder=None, username=None, password=None, |
|
|
1026 | 1034 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0): |
|
|
1027 | 1035 | |
|
|
1028 | 1036 | if channelList == None: |
|
|
1029 | 1037 | channelIndexList = dataOut.channelIndexList |
|
|
1030 | 1038 | channelList = dataOut.channelList |
|
|
1031 | 1039 | else: |
|
|
1032 | 1040 | channelIndexList = [] |
|
|
1033 | 1041 | for channel in channelList: |
|
|
1034 | 1042 | if channel not in dataOut.channelList: |
|
|
1035 | 1043 | raise ValueError, "Channel %d is not in dataOut.channelList" |
|
|
1036 | 1044 | channelIndexList.append(dataOut.channelList.index(channel)) |
|
|
1037 | 1045 | |
|
|
1038 | 1046 | if timerange != None: |
|
|
1039 | 1047 | self.timerange = timerange |
|
|
1040 | 1048 | |
|
|
1041 | 1049 | tmin = None |
|
|
1042 | 1050 | tmax = None |
|
|
1043 | 1051 | x = dataOut.getTimeRange() |
|
|
1044 | 1052 | y = dataOut.getHeiRange() |
|
|
1045 | 1053 | factor = dataOut.normFactor |
|
|
1046 | 1054 | noise = dataOut.noise()/factor |
|
|
1047 | 1055 | noisedB = 10*numpy.log10(noise) |
|
|
1048 | 1056 | |
|
|
1049 | 1057 | #thisDatetime = dataOut.datatime |
|
|
1050 | 1058 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[1]) |
|
|
1051 | 1059 | title = wintitle + " Noise" # : %s" %(thisDatetime.strftime("%d-%b-%Y")) |
|
|
1052 | 1060 | xlabel = "" |
|
|
1053 | 1061 | ylabel = "Intensity (dB)" |
|
|
1054 | 1062 | |
|
|
1055 | 1063 | if not self.isConfig: |
|
|
1056 | 1064 | |
|
|
1057 | 1065 | nplots = 1 |
|
|
1058 | 1066 | |
|
|
1059 | 1067 | self.setup(id=id, |
|
|
1060 | 1068 | nplots=nplots, |
|
|
1061 | 1069 | wintitle=wintitle, |
|
|
1062 | 1070 | showprofile=showprofile, |
|
|
1063 | 1071 | show=show) |
|
|
1064 | 1072 | |
|
|
1065 | 1073 | tmin, tmax = self.getTimeLim(x, xmin, xmax) |
|
|
1066 | 1074 | if ymin == None: ymin = numpy.nanmin(noisedB) - 10.0 |
|
|
1067 | 1075 | if ymax == None: ymax = numpy.nanmax(noisedB) + 10.0 |
|
|
1068 | 1076 | |
|
|
1069 | 1077 | self.FTP_WEI = ftp_wei |
|
|
1070 | 1078 | self.EXP_CODE = exp_code |
|
|
1071 | 1079 | self.SUB_EXP_CODE = sub_exp_code |
|
|
1072 | 1080 | self.PLOT_POS = plot_pos |
|
|
1073 | 1081 | |
|
|
1074 | 1082 | |
|
|
1075 | 1083 | self.name = thisDatetime.strftime("%Y%m%d_%H%M%S") |
|
|
1076 | 1084 | self.isConfig = True |
|
|
1077 | 1085 | self.figfile = figfile |
|
|
1078 | 1086 | self.xdata = numpy.array([]) |
|
|
1079 | 1087 | self.ydata = numpy.array([]) |
|
|
1080 | 1088 | |
|
|
1081 | 1089 | #open file beacon phase |
|
|
1082 | 1090 | path = '%s%03d' %(self.PREFIX, self.id) |
|
|
1083 | 1091 | noise_file = os.path.join(path,'%s.txt'%self.name) |
|
|
1084 | 1092 | self.filename_noise = os.path.join(figpath,noise_file) |
|
|
1085 | 1093 | self.openfile(self.filename_noise) |
|
|
1086 | 1094 | |
|
|
1087 | 1095 | |
|
|
1088 | 1096 | #store data beacon phase |
|
|
1089 | 1097 | self.save_data(self.filename_noise, noisedB, thisDatetime) |
|
|
1090 | 1098 | |
|
|
1091 | 1099 | |
|
|
1092 | 1100 | self.setWinTitle(title) |
|
|
1093 | 1101 | |
|
|
1094 | 1102 | |
|
|
1095 | 1103 | title = "Noise %s" %(thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) |
|
|
1096 | 1104 | |
|
|
1097 | 1105 | legendlabels = ["channel %d"%(idchannel+1) for idchannel in channelList] |
|
|
1098 | 1106 | axes = self.axesList[0] |
|
|
1099 | 1107 | |
|
|
1100 | 1108 | self.xdata = numpy.hstack((self.xdata, x[0:1])) |
|
|
1101 | 1109 | |
|
|
1102 | 1110 | if len(self.ydata)==0: |
|
|
1103 | 1111 | self.ydata = noisedB[channelIndexList].reshape(-1,1) |
|
|
1104 | 1112 | else: |
|
|
1105 | 1113 | self.ydata = numpy.hstack((self.ydata, noisedB[channelIndexList].reshape(-1,1))) |
|
|
1106 | 1114 | |
|
|
1107 | 1115 | |
|
|
1108 | 1116 | axes.pmultilineyaxis(x=self.xdata, y=self.ydata, |
|
|
1109 | 1117 | xmin=tmin, xmax=tmax, ymin=ymin, ymax=ymax, |
|
|
1110 | 1118 | xlabel=xlabel, ylabel=ylabel, title=title, legendlabels=legendlabels, marker='x', markersize=8, linestyle="solid", |
|
|
1111 | 1119 | XAxisAsTime=True, grid='both' |
|
|
1112 | 1120 | ) |
|
|
1113 | 1121 | |
|
|
1114 | 1122 | self.draw() |
|
|
1115 | 1123 | |
|
|
1116 | 1124 | if x[1] >= self.axesList[0].xmax: |
|
|
1117 | 1125 | self.counter_imagwr = wr_period |
|
|
1118 | 1126 | del self.xdata |
|
|
1119 | 1127 | del self.ydata |
|
|
1120 | 1128 | self.__isConfig = False |
|
|
1121 | 1129 | |
|
|
1122 | 1130 | if self.figfile == None: |
|
|
1123 | 1131 | str_datetime = thisDatetime.strftime("%Y%m%d_%H%M%S") |
|
|
1124 | 1132 | self.figfile = self.getFilename(name = str_datetime) |
|
|
1125 | 1133 | |
|
|
1126 | 1134 | if figpath != '': |
|
|
1127 | 1135 | self.counter_imagwr += 1 |
|
|
1128 | 1136 | if (self.counter_imagwr>=wr_period): |
|
|
1129 | 1137 | # store png plot to local folder |
|
|
1130 | 1138 | self.saveFigure(figpath, self.figfile) |
|
|
1131 | 1139 | # store png plot to FTP server according to RT-Web format |
|
|
1132 | 1140 | name = self.getNameToFtp(thisDatetime, self.FTP_WEI, self.EXP_CODE, self.SUB_EXP_CODE, self.PLOT_CODE, self.PLOT_POS) |
|
|
1133 | 1141 | ftp_filename = os.path.join(figpath, name) |
|
|
1134 | 1142 | self.saveFigure(figpath, ftp_filename) |
|
|
1135 | 1143 | self.counter_imagwr = 0 |
|
|
1136 | 1144 | |
|
|
1137 | 1145 | |
|
|
1138 | 1146 | class BeaconPhase(Figure): |
|
|
1139 | 1147 | |
|
|
1140 | 1148 | __isConfig = None |
|
|
1141 | 1149 | __nsubplots = None |
|
|
1142 | 1150 | |
|
|
1143 | 1151 | PREFIX = 'beacon_phase' |
|
|
1144 | 1152 | |
|
|
1145 | 1153 | def __init__(self): |
|
|
1146 | 1154 | |
|
|
1147 | 1155 | self.timerange = 24*60*60 |
|
|
1148 | 1156 | self.__isConfig = False |
|
|
1149 | 1157 | self.__nsubplots = 1 |
|
|
1150 | 1158 | self.counter_imagwr = 0 |
|
|
1151 | 1159 | self.WIDTH = 600 |
|
|
1152 | 1160 | self.HEIGHT = 300 |
|
|
1153 | 1161 | self.WIDTHPROF = 120 |
|
|
1154 | 1162 | self.HEIGHTPROF = 0 |
|
|
1155 | 1163 | self.xdata = None |
|
|
1156 | 1164 | self.ydata = None |
|
|
1157 | 1165 | |
|
|
1158 | 1166 | self.PLOT_CODE = 18 |
|
|
1159 | 1167 | self.FTP_WEI = None |
|
|
1160 | 1168 | self.EXP_CODE = None |
|
|
1161 | 1169 | self.SUB_EXP_CODE = None |
|
|
1162 | 1170 | self.PLOT_POS = None |
|
|
1163 | 1171 | |
|
|
1164 | 1172 | self.filename_phase = None |
|
|
1165 | 1173 | |
|
|
1166 | 1174 | self.figfile = None |
|
|
1167 | 1175 | |
|
|
1168 | 1176 | def getSubplots(self): |
|
|
1169 | 1177 | |
|
|
1170 | 1178 | ncol = 1 |
|
|
1171 | 1179 | nrow = 1 |
|
|
1172 | 1180 | |
|
|
1173 | 1181 | return nrow, ncol |
|
|
1174 | 1182 | |
|
|
1175 | 1183 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): |
|
|
1176 | 1184 | |
|
|
1177 | 1185 | self.__showprofile = showprofile |
|
|
1178 | 1186 | self.nplots = nplots |
|
|
1179 | 1187 | |
|
|
1180 | 1188 | ncolspan = 7 |
|
|
1181 | 1189 | colspan = 6 |
|
|
1182 | 1190 | self.__nsubplots = 2 |
|
|
1183 | 1191 | |
|
|
1184 | 1192 | self.createFigure(id = id, |
|
|
1185 | 1193 | wintitle = wintitle, |
|
|
1186 | 1194 | widthplot = self.WIDTH+self.WIDTHPROF, |
|
|
1187 | 1195 | heightplot = self.HEIGHT+self.HEIGHTPROF, |
|
|
1188 | 1196 | show=show) |
|
|
1189 | 1197 | |
|
|
1190 | 1198 | nrow, ncol = self.getSubplots() |
|
|
1191 | 1199 | |
|
|
1192 | 1200 | self.addAxes(nrow, ncol*ncolspan, 0, 0, colspan, 1) |
|
|
1193 | 1201 | |
|
|
1194 | 1202 | def save_phase(self, filename_phase): |
|
|
1195 | 1203 | f = open(filename_phase,'w+') |
|
|
1196 | 1204 | f.write('\n\n') |
|
|
1197 | 1205 | f.write('JICAMARCA RADIO OBSERVATORY - Beacon Phase \n') |
|
|
1198 | 1206 | f.write('DD MM YYYY HH MM SS pair(2,0) pair(2,1) pair(2,3) pair(2,4)\n\n' ) |
|
|
1199 | 1207 | f.close() |
|
|
1200 | 1208 | |
|
|
1201 | 1209 | def save_data(self, filename_phase, data, data_datetime): |
|
|
1202 | 1210 | f=open(filename_phase,'a') |
|
|
1203 | 1211 | timetuple_data = data_datetime.timetuple() |
|
|
1204 | 1212 | day = str(timetuple_data.tm_mday) |
|
|
1205 | 1213 | month = str(timetuple_data.tm_mon) |
|
|
1206 | 1214 | year = str(timetuple_data.tm_year) |
|
|
1207 | 1215 | hour = str(timetuple_data.tm_hour) |
|
|
1208 | 1216 | minute = str(timetuple_data.tm_min) |
|
|
1209 | 1217 | second = str(timetuple_data.tm_sec) |
|
|
1210 | 1218 | f.write(day+' '+month+' '+year+' '+hour+' '+minute+' '+second+' '+str(data[0])+' '+str(data[1])+' '+str(data[2])+' '+str(data[3])+'\n') |
|
|
1211 | 1219 | f.close() |
|
|
1212 | 1220 | |
|
|
1213 | 1221 | |
|
|
1214 | 1222 | def run(self, dataOut, id, wintitle="", pairsList=None, showprofile='True', |
|
|
1215 | 1223 | xmin=None, xmax=None, ymin=None, ymax=None, |
|
|
1216 | 1224 | timerange=None, |
|
|
1217 | 1225 | save=False, figpath='', figfile=None, show=True, ftp=False, wr_period=1, |
|
|
1218 | 1226 | server=None, folder=None, username=None, password=None, |
|
|
1219 | 1227 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0): |
|
|
1220 | 1228 | |
|
|
1221 | 1229 | if pairsList == None: |
|
|
1222 | 1230 | pairsIndexList = dataOut.pairsIndexList |
|
|
1223 | 1231 | else: |
|
|
1224 | 1232 | pairsIndexList = [] |
|
|
1225 | 1233 | for pair in pairsList: |
|
|
1226 | 1234 | if pair not in dataOut.pairsList: |
|
|
1227 | 1235 | raise ValueError, "Pair %s is not in dataOut.pairsList" %(pair) |
|
|
1228 | 1236 | pairsIndexList.append(dataOut.pairsList.index(pair)) |
|
|
1229 | 1237 | |
|
|
1230 | 1238 | if pairsIndexList == []: |
|
|
1231 | 1239 | return |
|
|
1232 | 1240 | |
|
|
1233 | 1241 | # if len(pairsIndexList) > 4: |
|
|
1234 | 1242 | # pairsIndexList = pairsIndexList[0:4] |
|
|
1235 | 1243 | |
|
|
1236 | 1244 | if timerange != None: |
|
|
1237 | 1245 | self.timerange = timerange |
|
|
1238 | 1246 | |
|
|
1239 | 1247 | tmin = None |
|
|
1240 | 1248 | tmax = None |
|
|
1241 | 1249 | x = dataOut.getTimeRange() |
|
|
1242 | 1250 | y = dataOut.getHeiRange() |
|
|
1243 | 1251 | |
|
|
1244 | 1252 | |
|
|
1245 | 1253 | #thisDatetime = dataOut.datatime |
|
|
1246 | 1254 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[1]) |
|
|
1247 | 1255 | title = wintitle + " Phase of Beacon Signal" # : %s" %(thisDatetime.strftime("%d-%b-%Y")) |
|
|
1248 | 1256 | xlabel = "Local Time" |
|
|
1249 | 1257 | ylabel = "Phase" |
|
|
1250 | 1258 | |
|
|
1251 | 1259 | nplots = len(pairsIndexList) |
|
|
1252 | 1260 | #phase = numpy.zeros((len(pairsIndexList),len(dataOut.beacon_heiIndexList))) |
|
|
1253 | 1261 | phase_beacon = numpy.zeros(len(pairsIndexList)) |
|
|
1254 | 1262 | for i in range(nplots): |
|
|
1255 | 1263 | pair = dataOut.pairsList[pairsIndexList[i]] |
|
|
1256 | 1264 | ccf = numpy.average(dataOut.data_cspc[pairsIndexList[i],:,:],axis=0) |
|
|
1257 | 1265 | powa = numpy.average(dataOut.data_spc[pair[0],:,:],axis=0) |
|
|
1258 | 1266 | powb = numpy.average(dataOut.data_spc[pair[1],:,:],axis=0) |
|
|
1259 | 1267 | avgcoherenceComplex = ccf/numpy.sqrt(powa*powb) |
|
|
1260 | 1268 | phase = numpy.arctan2(avgcoherenceComplex.imag, avgcoherenceComplex.real)*180/numpy.pi |
|
|
1261 | 1269 | |
|
|
1262 | 1270 | #print "Phase %d%d" %(pair[0], pair[1]) |
|
|
1263 | 1271 | #print phase[dataOut.beacon_heiIndexList] |
|
|
1264 | 1272 | |
|
|
1265 | 1273 | phase_beacon[i] = numpy.average(phase[dataOut.beacon_heiIndexList]) |
|
|
1266 | 1274 | |
|
|
1267 | 1275 | if not self.__isConfig: |
|
|
1268 | 1276 | |
|
|
1269 | 1277 | nplots = len(pairsIndexList) |
|
|
1270 | 1278 | |
|
|
1271 | 1279 | self.setup(id=id, |
|
|
1272 | 1280 | nplots=nplots, |
|
|
1273 | 1281 | wintitle=wintitle, |
|
|
1274 | 1282 | showprofile=showprofile, |
|
|
1275 | 1283 | show=show) |
|
|
1276 | 1284 | |
|
|
1277 | 1285 | tmin, tmax = self.getTimeLim(x, xmin, xmax) |
|
|
1278 | 1286 | if ymin == None: ymin = numpy.nanmin(phase_beacon) - 10.0 |
|
|
1279 | 1287 | if ymax == None: ymax = numpy.nanmax(phase_beacon) + 10.0 |
|
|
1280 | 1288 | |
|
|
1281 | 1289 | self.FTP_WEI = ftp_wei |
|
|
1282 | 1290 | self.EXP_CODE = exp_code |
|
|
1283 | 1291 | self.SUB_EXP_CODE = sub_exp_code |
|
|
1284 | 1292 | self.PLOT_POS = plot_pos |
|
|
1285 | 1293 | |
|
|
1286 | 1294 | self.name = thisDatetime.strftime("%Y%m%d_%H%M%S") |
|
|
1287 | 1295 | self.__isConfig = True |
|
|
1288 | 1296 | self.figfile = figfile |
|
|
1289 | 1297 | self.xdata = numpy.array([]) |
|
|
1290 | 1298 | self.ydata = numpy.array([]) |
|
|
1291 | 1299 | |
|
|
1292 | 1300 | #open file beacon phase |
|
|
1293 | 1301 | path = '%s%03d' %(self.PREFIX, self.id) |
|
|
1294 | 1302 | beacon_file = os.path.join(path,'%s.txt'%self.name) |
|
|
1295 | 1303 | self.filename_phase = os.path.join(figpath,beacon_file) |
|
|
1296 | 1304 | #self.save_phase(self.filename_phase) |
|
|
1297 | 1305 | |
|
|
1298 | 1306 | |
|
|
1299 | 1307 | #store data beacon phase |
|
|
1300 | 1308 | #self.save_data(self.filename_phase, phase_beacon, thisDatetime) |
|
|
1301 | 1309 | |
|
|
1302 | 1310 | self.setWinTitle(title) |
|
|
1303 | 1311 | |
|
|
1304 | 1312 | |
|
|
1305 | 1313 | title = "Beacon Signal %s" %(thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) |
|
|
1306 | 1314 | |
|
|
1307 | 1315 | legendlabels = ["pairs %d%d"%(pair[0], pair[1]) for pair in dataOut.pairsList] |
|
|
1308 | 1316 | |
|
|
1309 | 1317 | axes = self.axesList[0] |
|
|
1310 | 1318 | |
|
|
1311 | 1319 | self.xdata = numpy.hstack((self.xdata, x[0:1])) |
|
|
1312 | 1320 | |
|
|
1313 | 1321 | if len(self.ydata)==0: |
|
|
1314 | 1322 | self.ydata = phase_beacon.reshape(-1,1) |
|
|
1315 | 1323 | else: |
|
|
1316 | 1324 | self.ydata = numpy.hstack((self.ydata, phase_beacon.reshape(-1,1))) |
|
|
1317 | 1325 | |
|
|
1318 | 1326 | |
|
|
1319 | 1327 | axes.pmultilineyaxis(x=self.xdata, y=self.ydata, |
|
|
1320 | 1328 | xmin=tmin, xmax=tmax, ymin=ymin, ymax=ymax, |
|
|
1321 | 1329 | xlabel=xlabel, ylabel=ylabel, title=title, legendlabels=legendlabels, marker='x', markersize=8, linestyle="solid", |
|
|
1322 | 1330 | XAxisAsTime=True, grid='both' |
|
|
1323 | 1331 | ) |
|
|
1324 | 1332 | |
|
|
1325 | 1333 | self.draw() |
|
|
1326 | 1334 | |
|
|
1327 | 1335 | if x[1] >= self.axesList[0].xmax: |
|
|
1328 | 1336 | self.counter_imagwr = wr_period |
|
|
1329 | 1337 | del self.xdata |
|
|
1330 | 1338 | del self.ydata |
|
|
1331 | 1339 | self.__isConfig = False |
|
|
1332 | 1340 | |
|
|
1333 | 1341 | if self.figfile == None: |
|
|
1334 | 1342 | str_datetime = thisDatetime.strftime("%Y%m%d_%H%M%S") |
|
|
1335 | 1343 | self.figfile = self.getFilename(name = str_datetime) |
|
|
1336 | 1344 | |
|
|
1337 | 1345 | if figpath != '': |
|
|
1338 | 1346 | self.counter_imagwr += 1 |
|
|
1339 | 1347 | if (self.counter_imagwr>=wr_period): |
|
|
1340 | 1348 | # store png plot to local folder |
|
|
1341 | 1349 | self.saveFigure(figpath, self.figfile) |
|
|
1342 | 1350 | # store png plot to FTP server according to RT-Web format |
|
|
1343 | 1351 | name = self.getNameToFtp(thisDatetime, self.FTP_WEI, self.EXP_CODE, self.SUB_EXP_CODE, self.PLOT_CODE, self.PLOT_POS) |
|
|
1344 | 1352 | ftp_filename = os.path.join(figpath, name) |
|
|
1345 | 1353 | self.saveFigure(figpath, ftp_filename) |
|
|
1346 | 1354 | self.counter_imagwr = 0 |
| @@ -1,573 +1,616 | |||
|
|
1 | 1 | ''' |
|
|
2 | 2 | @author: Daniel Suarez |
|
|
3 | 3 | ''' |
|
|
4 | 4 | |
|
|
5 | 5 | import os |
|
|
6 | 6 | import sys |
|
|
7 | 7 | import glob |
|
|
8 | 8 | import fnmatch |
|
|
9 | 9 | import datetime |
|
|
10 | 10 | import time |
|
|
11 | 11 | import re |
|
|
12 | 12 | import h5py |
|
|
13 | 13 | import numpy |
|
|
14 | 14 | |
|
|
15 | 15 | from model.proc.jroproc_base import ProcessingUnit, Operation |
|
|
16 | 16 | from model.data.jroamisr import AMISR |
|
|
17 | 17 | |
|
|
18 | 18 | class RadacHeader(): |
|
|
19 | 19 | def __init__(self, fp): |
|
|
20 | 20 | header = 'Raw11/Data/RadacHeader' |
|
|
21 | 21 | self.beamCodeByPulse = fp.get(header+'/BeamCode') |
|
|
22 | 22 | self.beamCode = fp.get('Raw11/Data/Beamcodes') |
|
|
23 | 23 | self.code = fp.get(header+'/Code') |
|
|
24 | 24 | self.frameCount = fp.get(header+'/FrameCount') |
|
|
25 | 25 | self.modeGroup = fp.get(header+'/ModeGroup') |
|
|
26 | 26 | self.nsamplesPulse = fp.get(header+'/NSamplesPulse') |
|
|
27 | 27 | self.pulseCount = fp.get(header+'/PulseCount') |
|
|
28 | 28 | self.radacTime = fp.get(header+'/RadacTime') |
|
|
29 | 29 | self.timeCount = fp.get(header+'/TimeCount') |
|
|
30 | 30 | self.timeStatus = fp.get(header+'/TimeStatus') |
|
|
31 | 31 | |
|
|
32 | 32 | self.nrecords = self.pulseCount.shape[0] #nblocks |
|
|
33 | 33 | self.npulses = self.pulseCount.shape[1] #nprofile |
|
|
34 | 34 | self.nsamples = self.nsamplesPulse[0,0] #ngates |
|
|
35 | 35 | self.nbeams = self.beamCode.shape[1] |
|
|
36 | 36 | |
|
|
37 | 37 | |
|
|
38 | 38 | def getIndexRangeToPulse(self, idrecord=0): |
|
|
39 | 39 | #indexToZero = numpy.where(self.pulseCount.value[idrecord,:]==0) |
|
|
40 | 40 | #startPulseCountId = indexToZero[0][0] |
|
|
41 | 41 | #endPulseCountId = startPulseCountId - 1 |
|
|
42 | 42 | #range1 = numpy.arange(startPulseCountId,self.npulses,1) |
|
|
43 | 43 | #range2 = numpy.arange(0,startPulseCountId,1) |
|
|
44 | 44 | #return range1, range2 |
|
|
45 | 45 | |
|
|
46 | 46 | looking_zeros_index = numpy.where(self.pulseCount.value[idrecord,:]==0)[0] |
|
|
47 | 47 | getLastIndexZero = looking_zeros_index[-1] |
|
|
48 | 48 | index_data = numpy.arange(0,getLastIndexZero,1) |
|
|
49 | 49 | index_buffer = numpy.arange(getLastIndexZero,self.npulses,1) |
|
|
50 | 50 | return index_data, index_buffer |
|
|
51 | 51 | |
|
|
52 | 52 | class AMISRReader(ProcessingUnit): |
|
|
53 | 53 | |
|
|
54 | 54 | path = None |
|
|
55 | 55 | startDate = None |
|
|
56 | 56 | endDate = None |
|
|
57 | 57 | startTime = None |
|
|
58 | 58 | endTime = None |
|
|
59 | 59 | walk = None |
|
|
60 | 60 | isConfig = False |
|
|
61 | 61 | |
|
|
62 | 62 | def __init__(self): |
|
|
63 | 63 | self.set = None |
|
|
64 | 64 | self.subset = None |
|
|
65 | 65 | self.extension_file = '.h5' |
|
|
66 | 66 | self.dtc_str = 'dtc' |
|
|
67 | 67 | self.dtc_id = 0 |
|
|
68 | 68 | self.status = True |
|
|
69 | 69 | self.isConfig = False |
|
|
70 | 70 | self.dirnameList = [] |
|
|
71 | 71 | self.filenameList = [] |
|
|
72 | 72 | self.fileIndex = None |
|
|
73 | 73 | self.flagNoMoreFiles = False |
|
|
74 | 74 | self.flagIsNewFile = 0 |
|
|
75 | 75 | self.filename = '' |
|
|
76 | 76 | self.amisrFilePointer = None |
|
|
77 | 77 | self.radacHeaderObj = None |
|
|
78 | 78 | self.dataOut = self.__createObjByDefault() |
|
|
79 | 79 | self.datablock = None |
|
|
80 | 80 | self.rest_datablock = None |
|
|
81 | 81 | self.range = None |
|
|
82 | 82 | self.idrecord_count = 0 |
|
|
83 | 83 | self.profileIndex = 0 |
|
|
84 | 84 | self.index_amisr_sample = None |
|
|
85 | 85 | self.index_amisr_buffer = None |
|
|
86 | 86 | self.beamCodeByFrame = None |
|
|
87 | 87 | self.radacTimeByFrame = None |
|
|
88 | 88 | #atributos originales tal y como esta en el archivo de datos |
|
|
89 | 89 | self.beamCodesFromFile = None |
|
|
90 | 90 | self.radacTimeFromFile = None |
|
|
91 | 91 | self.rangeFromFile = None |
|
|
92 | 92 | self.dataByFrame = None |
|
|
93 | 93 | self.dataset = None |
|
|
94 | 94 | |
|
|
95 | 95 | self.beamCodeDict = {} |
|
|
96 | 96 | self.beamRangeDict = {} |
|
|
97 | 97 | |
|
|
98 | 98 | #experiment cgf file |
|
|
99 | 99 | self.npulsesint_fromfile = None |
|
|
100 | 100 | self.recordsperfile_fromfile = None |
|
|
101 | 101 | self.nbeamcodes_fromfile = None |
|
|
102 | 102 | self.ngates_fromfile = None |
|
|
103 | 103 | self.ippSeconds_fromfile = None |
|
|
104 | 104 | self.frequency_h5file = None |
|
|
105 | 105 | |
|
|
106 | 106 | |
|
|
107 | 107 | self.__firstFile = True |
|
|
108 | 108 | self.buffer_radactime = None |
|
|
109 | 109 | |
|
|
110 | 110 | self.index4_schain_datablock = None |
|
|
111 | 111 | self.index4_buffer = None |
|
|
112 | 112 | self.schain_datablock = None |
|
|
113 | 113 | self.buffer = None |
|
|
114 | 114 | self.linear_pulseCount = None |
|
|
115 | 115 | self.npulseByFrame = None |
|
|
116 | 116 | self.profileIndex_offset = None |
|
|
117 | 117 | self.timezone = 'ut' |
|
|
118 | 118 | |
|
|
119 | 119 | def __createObjByDefault(self): |
|
|
120 | 120 | |
|
|
121 | 121 | dataObj = AMISR() |
|
|
122 | 122 | |
|
|
123 | 123 | return dataObj |
|
|
124 | 124 | |
|
|
125 | 125 | def __setParameters(self,path,startDate,endDate,startTime,endTime,walk): |
|
|
126 | 126 | self.path = path |
|
|
127 | 127 | self.startDate = startDate |
|
|
128 | 128 | self.endDate = endDate |
|
|
129 | 129 | self.startTime = startTime |
|
|
130 | 130 | self.endTime = endTime |
|
|
131 | 131 | self.walk = walk |
|
|
132 | 132 | |
|
|
133 | 133 | def __checkPath(self): |
|
|
134 | 134 | if os.path.exists(self.path): |
|
|
135 | 135 | self.status = 1 |
|
|
136 | 136 | else: |
|
|
137 | 137 | self.status = 0 |
|
|
138 | 138 | print 'Path:%s does not exists'%self.path |
|
|
139 | 139 | |
|
|
140 | 140 | return |
|
|
141 | 141 | |
|
|
142 | 142 | def __selDates(self, amisr_dirname_format): |
|
|
143 | 143 | try: |
|
|
144 | 144 | year = int(amisr_dirname_format[0:4]) |
|
|
145 | 145 | month = int(amisr_dirname_format[4:6]) |
|
|
146 | 146 | dom = int(amisr_dirname_format[6:8]) |
|
|
147 | 147 | thisDate = datetime.date(year,month,dom) |
|
|
148 | 148 | |
|
|
149 | 149 | if (thisDate>=self.startDate and thisDate <= self.endDate): |
|
|
150 | 150 | return amisr_dirname_format |
|
|
151 | 151 | except: |
|
|
152 | 152 | return None |
|
|
153 | 153 | |
|
|
154 | 154 | def __findDataForDates(self): |
|
|
155 | 155 | |
|
|
156 | 156 | |
|
|
157 | 157 | |
|
|
158 | 158 | if not(self.status): |
|
|
159 | 159 | return None |
|
|
160 | 160 | |
|
|
161 | 161 | pat = '\d+.\d+' |
|
|
162 | 162 | dirnameList = [re.search(pat,x) for x in os.listdir(self.path)] |
|
|
163 | 163 | dirnameList = filter(lambda x:x!=None,dirnameList) |
|
|
164 | 164 | dirnameList = [x.string for x in dirnameList] |
|
|
165 | 165 | dirnameList = [self.__selDates(x) for x in dirnameList] |
|
|
166 | 166 | dirnameList = filter(lambda x:x!=None,dirnameList) |
|
|
167 | 167 | if len(dirnameList)>0: |
|
|
168 | 168 | self.status = 1 |
|
|
169 | 169 | self.dirnameList = dirnameList |
|
|
170 | 170 | self.dirnameList.sort() |
|
|
171 | 171 | else: |
|
|
172 | 172 | self.status = 0 |
|
|
173 | 173 | return None |
|
|
174 | 174 | |
|
|
175 | 175 | def __getTimeFromData(self): |
|
|
176 | pass | |
|
|
176 | startDateTime_Reader = datetime.datetime.combine(self.startDate,self.startTime) | |
|
|
177 | endDateTime_Reader = datetime.datetime.combine(self.endDate,self.endTime) | |
|
|
178 | ||
|
|
179 | print 'Filtering Files from %s to %s'%(startDateTime_Reader, endDateTime_Reader) | |
|
|
180 | print '........................................' | |
|
|
181 | filter_filenameList = [] | |
|
|
182 | for filename in self.filenameList: | |
|
|
183 | fp = h5py.File(filename,'r') | |
|
|
184 | time_str = fp.get('Time/RadacTimeString') | |
|
|
185 | ||
|
|
186 | startDateTimeStr_File = time_str[0][0].split('.')[0] | |
|
|
187 | junk = time.strptime(startDateTimeStr_File, '%Y-%m-%d %H:%M:%S') | |
|
|
188 | startDateTime_File = datetime.datetime(junk.tm_year,junk.tm_mon,junk.tm_mday,junk.tm_hour, junk.tm_min, junk.tm_sec) | |
|
|
189 | ||
|
|
190 | endDateTimeStr_File = time_str[-1][-1].split('.')[0] | |
|
|
191 | junk = time.strptime(endDateTimeStr_File, '%Y-%m-%d %H:%M:%S') | |
|
|
192 | endDateTime_File = datetime.datetime(junk.tm_year,junk.tm_mon,junk.tm_mday,junk.tm_hour, junk.tm_min, junk.tm_sec) | |
|
|
193 | ||
|
|
194 | fp.close() | |
|
|
195 | ||
|
|
196 | if self.timezone == 'lt': | |
|
|
197 | startDateTime_File = startDateTime_File - datetime.timedelta(minutes = 300) | |
|
|
198 | endDateTime_File = endDateTime_File - datetime.timedelta(minutes = 300) | |
|
|
199 | ||
|
|
200 | if (endDateTime_File>=startDateTime_Reader and endDateTime_File<endDateTime_Reader): | |
|
|
201 | #self.filenameList.remove(filename) | |
|
|
202 | filter_filenameList.append(filename) | |
|
|
203 | ||
|
|
204 | filter_filenameList.sort() | |
|
|
205 | self.filenameList = filter_filenameList | |
|
|
206 | return 1 | |
|
|
177 | 207 | |
|
|
178 | 208 | def __filterByGlob1(self, dirName): |
|
|
179 | 209 | filter_files = glob.glob1(dirName, '*.*%s'%self.extension_file) |
|
|
180 | 210 | filterDict = {} |
|
|
181 | 211 | filterDict.setdefault(dirName) |
|
|
182 | 212 | filterDict[dirName] = filter_files |
|
|
183 | 213 | return filterDict |
|
|
184 | 214 | |
|
|
185 | 215 | def __getFilenameList(self, fileListInKeys, dirList): |
|
|
186 | 216 | for value in fileListInKeys: |
|
|
187 | 217 | dirName = value.keys()[0] |
|
|
188 | 218 | for file in value[dirName]: |
|
|
189 | 219 | filename = os.path.join(dirName, file) |
|
|
190 | 220 | self.filenameList.append(filename) |
|
|
191 | 221 | |
|
|
192 | 222 | |
|
|
193 | 223 | def __selectDataForTimes(self): |
|
|
194 | 224 | #aun no esta implementado el filtro for tiempo |
|
|
195 | 225 | if not(self.status): |
|
|
196 | 226 | return None |
|
|
197 | 227 | |
|
|
198 | 228 | dirList = [os.path.join(self.path,x) for x in self.dirnameList] |
|
|
199 | 229 | |
|
|
200 | 230 | fileListInKeys = [self.__filterByGlob1(x) for x in dirList] |
|
|
201 | 231 | |
|
|
202 | 232 | self.__getFilenameList(fileListInKeys, dirList) |
|
|
203 | ||
|
|
233 | #filtro por tiempo | |
|
|
234 | if not(self.all): | |
|
|
235 | self.__getTimeFromData() | |
|
|
236 | ||
|
|
237 | ||
|
|
204 | 238 | if len(self.filenameList)>0: |
|
|
205 | 239 | self.status = 1 |
|
|
206 | 240 | self.filenameList.sort() |
|
|
207 | 241 | else: |
|
|
208 | 242 | self.status = 0 |
|
|
209 | 243 | return None |
|
|
210 | 244 | |
|
|
211 | 245 | |
|
|
212 | 246 | def __searchFilesOffline(self, |
|
|
213 | 247 | path, |
|
|
214 | 248 | startDate, |
|
|
215 | 249 | endDate, |
|
|
216 | 250 | startTime=datetime.time(0,0,0), |
|
|
217 | 251 | endTime=datetime.time(23,59,59), |
|
|
218 | 252 | walk=True): |
|
|
219 | 253 | |
|
|
220 | 254 | self.__setParameters(path, startDate, endDate, startTime, endTime, walk) |
|
|
221 | 255 | |
|
|
222 | 256 | self.__checkPath() |
|
|
223 | 257 | |
|
|
224 | 258 | self.__findDataForDates() |
|
|
225 | 259 | |
|
|
226 | 260 | self.__selectDataForTimes() |
|
|
227 | 261 | |
|
|
228 | 262 | for i in range(len(self.filenameList)): |
|
|
229 | 263 | print "%s" %(self.filenameList[i]) |
|
|
230 | 264 | |
|
|
231 | 265 | return |
|
|
232 | 266 | |
|
|
233 | 267 | def __setNextFileOffline(self): |
|
|
234 | 268 | idFile = self.fileIndex |
|
|
235 | 269 | |
|
|
236 | 270 | while (True): |
|
|
237 | 271 | idFile += 1 |
|
|
238 | 272 | if not(idFile < len(self.filenameList)): |
|
|
239 | 273 | self.flagNoMoreFiles = 1 |
|
|
240 | 274 | print "No more Files" |
|
|
241 | 275 | return 0 |
|
|
242 | 276 | |
|
|
243 | 277 | filename = self.filenameList[idFile] |
|
|
244 | 278 | |
|
|
245 | 279 | amisrFilePointer = h5py.File(filename,'r') |
|
|
246 | 280 | |
|
|
247 | 281 | break |
|
|
248 | 282 | |
|
|
249 | 283 | self.flagIsNewFile = 1 |
|
|
250 | 284 | self.fileIndex = idFile |
|
|
251 | 285 | self.filename = filename |
|
|
252 | 286 | |
|
|
253 | 287 | self.amisrFilePointer = amisrFilePointer |
|
|
254 | 288 | |
|
|
255 | 289 | print "Setting the file: %s"%self.filename |
|
|
256 | 290 | |
|
|
257 | 291 | return 1 |
|
|
258 | 292 | |
|
|
259 | 293 | def __readHeader(self): |
|
|
260 | 294 | self.radacHeaderObj = RadacHeader(self.amisrFilePointer) |
|
|
261 | 295 | |
|
|
262 | 296 | #update values from experiment cfg file |
|
|
263 | 297 | if self.radacHeaderObj.nrecords == self.recordsperfile_fromfile: |
|
|
264 | 298 | self.radacHeaderObj.nrecords = self.recordsperfile_fromfile |
|
|
265 | 299 | self.radacHeaderObj.nbeams = self.nbeamcodes_fromfile |
|
|
266 | 300 | self.radacHeaderObj.npulses = self.npulsesint_fromfile |
|
|
267 | 301 | self.radacHeaderObj.nsamples = self.ngates_fromfile |
|
|
268 | 302 | |
|
|
269 | 303 | #looking index list for data |
|
|
270 | 304 | start_index = self.radacHeaderObj.pulseCount[0,:][0] |
|
|
271 | 305 | end_index = self.radacHeaderObj.npulses |
|
|
272 | 306 | range4data = range(start_index, end_index) |
|
|
273 | 307 | self.index4_schain_datablock = numpy.array(range4data) |
|
|
274 | 308 | |
|
|
275 | 309 | buffer_start_index = 0 |
|
|
276 | 310 | buffer_end_index = self.radacHeaderObj.pulseCount[0,:][0] |
|
|
277 | 311 | range4buffer = range(buffer_start_index, buffer_end_index) |
|
|
278 | 312 | self.index4_buffer = numpy.array(range4buffer) |
|
|
279 | 313 | |
|
|
280 | 314 | self.linear_pulseCount = numpy.array(range4data + range4buffer) |
|
|
281 | 315 | self.npulseByFrame = max(self.radacHeaderObj.pulseCount[0,:]+1) |
|
|
282 | 316 | |
|
|
283 | 317 | #get tuning frequency |
|
|
284 | 318 | frequency_h5file_dataset = self.amisrFilePointer.get('Rx'+'/TuningFrequency') |
|
|
285 | 319 | self.frequency_h5file = frequency_h5file_dataset[0,0] |
|
|
286 | 320 | |
|
|
287 | 321 | self.flagIsNewFile = 1 |
|
|
288 | 322 | |
|
|
289 | 323 | def __getBeamCode(self): |
|
|
290 | 324 | self.beamCodeDict = {} |
|
|
291 | 325 | self.beamRangeDict = {} |
|
|
292 | 326 | |
|
|
327 | beamCodeMap = self.amisrFilePointer.get('Setup/BeamcodeMap') | |
|
|
328 | ||
|
|
293 | 329 | for i in range(len(self.radacHeaderObj.beamCode[0,:])): |
|
|
294 | 330 | self.beamCodeDict.setdefault(i) |
|
|
295 | 331 | self.beamRangeDict.setdefault(i) |
|
|
296 |
|
|
|
|
332 | beamcodeValue = self.radacHeaderObj.beamCode[0,i] | |
|
|
333 | beamcodeIndex = numpy.where(beamCodeMap[:,0] == beamcodeValue)[0][0] | |
|
|
334 | x = beamCodeMap[beamcodeIndex][1] | |
|
|
335 | y = beamCodeMap[beamcodeIndex][2] | |
|
|
336 | z = beamCodeMap[beamcodeIndex][3] | |
|
|
337 | self.beamCodeDict[i] = [beamcodeValue, x, y, z] | |
|
|
297 | 338 | |
|
|
298 | ||
|
|
299 | 339 | just4record0 = self.radacHeaderObj.beamCodeByPulse[0,:] |
|
|
300 | 340 | |
|
|
301 | 341 | for i in range(len(self.beamCodeDict.values())): |
|
|
302 | xx = numpy.where(just4record0==self.beamCodeDict.values()[i]) | |
|
|
342 | xx = numpy.where(just4record0==self.beamCodeDict.values()[i][0]) | |
|
|
303 | 343 | self.beamRangeDict[i] = xx[0] |
|
|
304 | 344 | |
|
|
305 | 345 | def __getExpParameters(self): |
|
|
306 | 346 | if not(self.status): |
|
|
307 | 347 | return None |
|
|
308 | 348 | |
|
|
309 | 349 | experimentCfgPath = os.path.join(self.path, self.dirnameList[0], 'Setup') |
|
|
310 | 350 | |
|
|
311 | 351 | expFinder = glob.glob1(experimentCfgPath,'*.exp') |
|
|
312 | 352 | if len(expFinder)== 0: |
|
|
313 | 353 | self.status = 0 |
|
|
314 | 354 | return None |
|
|
315 | 355 | |
|
|
316 | 356 | experimentFilename = os.path.join(experimentCfgPath,expFinder[0]) |
|
|
317 | 357 | |
|
|
318 | 358 | f = open(experimentFilename) |
|
|
319 | 359 | lines = f.readlines() |
|
|
320 | 360 | f.close() |
|
|
321 | 361 | |
|
|
322 | 362 | parmsList = ['npulsesint*','recordsperfile*','nbeamcodes*','ngates*'] |
|
|
323 | 363 | filterList = [fnmatch.filter(lines, x) for x in parmsList] |
|
|
324 | 364 | |
|
|
325 | 365 | |
|
|
326 | 366 | values = [re.sub(r'\D',"",x[0]) for x in filterList] |
|
|
327 | 367 | |
|
|
328 | 368 | self.npulsesint_fromfile = int(values[0]) |
|
|
329 | 369 | self.recordsperfile_fromfile = int(values[1]) |
|
|
330 | 370 | self.nbeamcodes_fromfile = int(values[2]) |
|
|
331 | 371 | self.ngates_fromfile = int(values[3]) |
|
|
332 | 372 | |
|
|
333 | 373 | tufileFinder = fnmatch.filter(lines, 'tufile=*') |
|
|
334 | 374 | tufile = tufileFinder[0].split('=')[1].split('\n')[0] |
|
|
375 | tufile = tufile.split('\r')[0] | |
|
|
335 | 376 | tufilename = os.path.join(experimentCfgPath,tufile) |
|
|
336 | 377 | |
|
|
337 | 378 | f = open(tufilename) |
|
|
338 | 379 | lines = f.readlines() |
|
|
339 | 380 | f.close() |
|
|
340 | 381 | self.ippSeconds_fromfile = float(lines[1].split()[2])/1E6 |
|
|
341 | 382 | |
|
|
342 | 383 | |
|
|
343 | 384 | self.status = 1 |
|
|
344 | 385 | |
|
|
345 | 386 | def __setIdsAndArrays(self): |
|
|
346 | 387 | self.dataByFrame = self.__setDataByFrame() |
|
|
347 | 388 | self.beamCodeByFrame = self.amisrFilePointer.get('Raw11/Data/RadacHeader/BeamCode').value[0, :] |
|
|
348 | 389 | self.readRanges() |
|
|
349 | 390 | self.index_amisr_sample, self.index_amisr_buffer = self.radacHeaderObj.getIndexRangeToPulse(0) |
|
|
350 | 391 | self.radacTimeByFrame = numpy.zeros(self.radacHeaderObj.npulses) |
|
|
351 | 392 | self.buffer_radactime = numpy.zeros_like(self.radacTimeByFrame) |
|
|
352 | 393 | |
|
|
353 | 394 | |
|
|
354 | 395 | def __setNextFile(self): |
|
|
355 | 396 | |
|
|
356 | 397 | newFile = self.__setNextFileOffline() |
|
|
357 | 398 | |
|
|
358 | 399 | if not(newFile): |
|
|
359 | 400 | return 0 |
|
|
360 | 401 | |
|
|
361 | 402 | self.__readHeader() |
|
|
362 | 403 | |
|
|
363 | 404 | if self.__firstFile: |
|
|
364 | 405 | self.__setIdsAndArrays() |
|
|
365 | 406 | self.__firstFile = False |
|
|
366 | 407 | |
|
|
367 | 408 | self.__getBeamCode() |
|
|
368 | 409 | self.readDataBlock() |
|
|
369 | 410 | |
|
|
370 | 411 | |
|
|
371 | 412 | def setup(self,path=None, |
|
|
372 | 413 | startDate=None, |
|
|
373 | 414 | endDate=None, |
|
|
374 | 415 | startTime=datetime.time(0,0,0), |
|
|
375 | 416 | endTime=datetime.time(23,59,59), |
|
|
376 | 417 | walk=True, |
|
|
377 |
timezone='ut', |
|
|
|
418 | timezone='ut', | |
|
|
419 | all=0,): | |
|
|
378 | 420 | |
|
|
379 | 421 | self.timezone = timezone |
|
|
422 | self.all = all | |
|
|
380 | 423 | #Busqueda de archivos offline |
|
|
381 | 424 | self.__searchFilesOffline(path, startDate, endDate, startTime, endTime, walk) |
|
|
382 | 425 | |
|
|
383 | 426 | if not(self.filenameList): |
|
|
384 | 427 | print "There is no files into the folder: %s"%(path) |
|
|
385 | 428 | |
|
|
386 | 429 | sys.exit(-1) |
|
|
387 | 430 | |
|
|
388 | 431 | self.__getExpParameters() |
|
|
389 | 432 | |
|
|
390 | 433 | self.fileIndex = -1 |
|
|
391 | 434 | |
|
|
392 | 435 | self.__setNextFile() |
|
|
393 | 436 | |
|
|
394 | 437 | first_beamcode = self.radacHeaderObj.beamCodeByPulse[0,0] |
|
|
395 | 438 | index = numpy.where(self.radacHeaderObj.beamCodeByPulse[0,:]!=first_beamcode)[0][0] |
|
|
396 | 439 | self.profileIndex_offset = self.radacHeaderObj.pulseCount[0,:][index] |
|
|
397 | 440 | self.profileIndex = self.profileIndex_offset |
|
|
398 | 441 | |
|
|
399 | 442 | def readRanges(self): |
|
|
400 | 443 | dataset = self.amisrFilePointer.get('Raw11/Data/Samples/Range') |
|
|
401 | 444 | #self.rangeFromFile = dataset.value |
|
|
402 | 445 | self.rangeFromFile = numpy.reshape(dataset.value,(-1)) |
|
|
403 | 446 | return range |
|
|
404 | 447 | |
|
|
405 | 448 | |
|
|
406 | 449 | def readRadacTime(self,idrecord, range1, range2): |
|
|
407 | 450 | self.radacTimeFromFile = self.radacHeaderObj.radacTime.value |
|
|
408 | 451 | |
|
|
409 | 452 | radacTimeByFrame = numpy.zeros((self.radacHeaderObj.npulses)) |
|
|
410 | 453 | #radacTimeByFrame = dataset[idrecord - 1,range1] |
|
|
411 | 454 | #radacTimeByFrame = dataset[idrecord,range2] |
|
|
412 | 455 | |
|
|
413 | 456 | return radacTimeByFrame |
|
|
414 | 457 | |
|
|
415 | 458 | def readBeamCode(self, idrecord, range1, range2): |
|
|
416 | 459 | dataset = self.amisrFilePointer.get('Raw11/Data/RadacHeader/BeamCode') |
|
|
417 | 460 | beamcodeByFrame = numpy.zeros((self.radacHeaderObj.npulses)) |
|
|
418 | 461 | self.beamCodesFromFile = dataset.value |
|
|
419 | 462 | |
|
|
420 | 463 | #beamcodeByFrame[range1] = dataset[idrecord - 1, range1] |
|
|
421 | 464 | #beamcodeByFrame[range2] = dataset[idrecord, range2] |
|
|
422 | 465 | beamcodeByFrame[range1] = dataset[idrecord, range1] |
|
|
423 | 466 | beamcodeByFrame[range2] = dataset[idrecord, range2] |
|
|
424 | 467 | |
|
|
425 | 468 | return beamcodeByFrame |
|
|
426 | 469 | |
|
|
427 | 470 | |
|
|
428 | 471 | def __setDataByFrame(self): |
|
|
429 | 472 | ndata = 2 # porque es complejo |
|
|
430 | 473 | dataByFrame = numpy.zeros((self.radacHeaderObj.npulses, self.radacHeaderObj.nsamples, ndata)) |
|
|
431 | 474 | return dataByFrame |
|
|
432 | 475 | |
|
|
433 | 476 | def __readDataSet(self): |
|
|
434 | 477 | dataset = self.amisrFilePointer.get('Raw11/Data/Samples/Data') |
|
|
435 | 478 | return dataset |
|
|
436 | 479 | |
|
|
437 | 480 | def __setDataBlock(self,): |
|
|
438 | 481 | real = self.dataByFrame[:,:,0] #asumo que 0 es real |
|
|
439 | 482 | imag = self.dataByFrame[:,:,1] #asumo que 1 es imaginario |
|
|
440 | 483 | datablock = real + imag*1j #armo el complejo |
|
|
441 | 484 | return datablock |
|
|
442 | 485 | |
|
|
443 | 486 | def readSamples_version1(self,idrecord): |
|
|
444 | 487 | #estas tres primeras lineas solo se deben ejecutar una vez |
|
|
445 | 488 | if self.flagIsNewFile: |
|
|
446 | 489 | #reading dataset |
|
|
447 | 490 | self.dataset = self.__readDataSet() |
|
|
448 | 491 | self.flagIsNewFile = 0 |
|
|
449 | 492 | |
|
|
450 | 493 | if idrecord == 0: |
|
|
451 | 494 | self.dataByFrame[self.index4_schain_datablock, : ,:] = self.dataset[0, self.index_amisr_sample,:,:] |
|
|
452 | 495 | self.radacTimeByFrame[self.index4_schain_datablock] = self.radacHeaderObj.radacTime[0, self.index_amisr_sample] |
|
|
453 | 496 | datablock = self.__setDataBlock() |
|
|
454 | 497 | |
|
|
455 | 498 | self.buffer = self.dataset[0, self.index_amisr_buffer,:,:] |
|
|
456 | 499 | self.buffer_radactime = self.radacHeaderObj.radacTime[0, self.index_amisr_buffer] |
|
|
457 | 500 | |
|
|
458 | 501 | return datablock |
|
|
459 | 502 | |
|
|
460 | 503 | self.dataByFrame[self.index4_buffer,:,:] = self.buffer.copy() |
|
|
461 | 504 | self.radacTimeByFrame[self.index4_buffer] = self.buffer_radactime.copy() |
|
|
462 | 505 | self.dataByFrame[self.index4_schain_datablock,:,:] = self.dataset[idrecord, self.index_amisr_sample,:,:] |
|
|
463 | 506 | self.radacTimeByFrame[self.index4_schain_datablock] = self.radacHeaderObj.radacTime[idrecord, self.index_amisr_sample] |
|
|
464 | 507 | datablock = self.__setDataBlock() |
|
|
465 | 508 | |
|
|
466 | 509 | self.buffer = self.dataset[idrecord, self.index_amisr_buffer, :, :] |
|
|
467 | 510 | self.buffer_radactime = self.radacHeaderObj.radacTime[idrecord, self.index_amisr_buffer] |
|
|
468 | 511 | |
|
|
469 | 512 | return datablock |
|
|
470 | 513 | |
|
|
471 | 514 | |
|
|
472 | 515 | def readSamples(self,idrecord): |
|
|
473 | 516 | if self.flagIsNewFile: |
|
|
474 | 517 | self.dataByFrame = self.__setDataByFrame() |
|
|
475 | 518 | self.beamCodeByFrame = self.amisrFilePointer.get('Raw11/Data/RadacHeader/BeamCode').value[idrecord, :] |
|
|
476 | 519 | |
|
|
477 | 520 | #reading ranges |
|
|
478 | 521 | self.readRanges() |
|
|
479 | 522 | #reading dataset |
|
|
480 | 523 | self.dataset = self.__readDataSet() |
|
|
481 | 524 | |
|
|
482 | 525 | self.flagIsNewFile = 0 |
|
|
483 | 526 | self.radacTimeByFrame = self.radacHeaderObj.radacTime.value[idrecord, :] |
|
|
484 | 527 | self.dataByFrame = self.dataset[idrecord, :, :, :] |
|
|
485 | 528 | datablock = self.__setDataBlock() |
|
|
486 | 529 | return datablock |
|
|
487 | 530 | |
|
|
488 | 531 | |
|
|
489 | 532 | def readDataBlock(self): |
|
|
490 | 533 | |
|
|
491 | 534 | self.datablock = self.readSamples_version1(self.idrecord_count) |
|
|
492 | 535 | #self.datablock = self.readSamples(self.idrecord_count) |
|
|
493 | 536 | #print 'record:', self.idrecord_count |
|
|
494 | 537 | |
|
|
495 | 538 | self.idrecord_count += 1 |
|
|
496 | 539 | self.profileIndex = 0 |
|
|
497 | 540 | |
|
|
498 | 541 | if self.idrecord_count >= self.radacHeaderObj.nrecords: |
|
|
499 | 542 | self.idrecord_count = 0 |
|
|
500 | 543 | self.flagIsNewFile = 1 |
|
|
501 | 544 | |
|
|
502 | 545 | def readNextBlock(self): |
|
|
503 | 546 | |
|
|
504 | 547 | self.readDataBlock() |
|
|
505 | 548 | |
|
|
506 | 549 | if self.flagIsNewFile: |
|
|
507 | 550 | self.__setNextFile() |
|
|
508 | 551 | pass |
|
|
509 | 552 | |
|
|
510 | 553 | def __hasNotDataInBuffer(self): |
|
|
511 | 554 | #self.radacHeaderObj.npulses debe ser otra variable para considerar el numero de pulsos a tomar en el primer y ultimo record |
|
|
512 | 555 | if self.profileIndex >= self.radacHeaderObj.npulses: |
|
|
513 | 556 | return 1 |
|
|
514 | 557 | return 0 |
|
|
515 | 558 | |
|
|
516 | 559 | def printUTC(self): |
|
|
517 | 560 | print self.dataOut.utctime |
|
|
518 | 561 | print '' |
|
|
519 | 562 | |
|
|
520 | 563 | def setObjProperties(self): |
|
|
521 | 564 | self.dataOut.heightList = self.rangeFromFile/1000.0 #km |
|
|
522 | 565 | self.dataOut.nProfiles = self.radacHeaderObj.npulses |
|
|
523 | 566 | self.dataOut.nRecords = self.radacHeaderObj.nrecords |
|
|
524 | 567 | self.dataOut.nBeams = self.radacHeaderObj.nbeams |
|
|
525 | 568 | self.dataOut.ippSeconds = self.ippSeconds_fromfile |
|
|
526 | 569 | self.dataOut.timeInterval = self.dataOut.ippSeconds * self.dataOut.nCohInt |
|
|
527 | 570 | self.dataOut.frequency = self.frequency_h5file |
|
|
528 | 571 | self.dataOut.npulseByFrame = self.npulseByFrame |
|
|
529 | 572 | self.dataOut.nBaud = None |
|
|
530 | 573 | self.dataOut.nCode = None |
|
|
531 | 574 | self.dataOut.code = None |
|
|
532 | 575 | |
|
|
533 | 576 | self.dataOut.beamCodeDict = self.beamCodeDict |
|
|
534 | 577 | self.dataOut.beamRangeDict = self.beamRangeDict |
|
|
535 | 578 | |
|
|
536 | 579 | if self.timezone == 'lt': |
|
|
537 | 580 | self.dataOut.timeZone = time.timezone / 60. #get the timezone in minutes |
|
|
538 | 581 | else: |
|
|
539 | 582 | self.dataOut.timeZone = 0 #by default time is UTC |
|
|
540 | 583 | |
|
|
541 | 584 | def getData(self): |
|
|
542 | 585 | |
|
|
543 | 586 | if self.flagNoMoreFiles: |
|
|
544 | 587 | self.dataOut.flagNoData = True |
|
|
545 | 588 | print 'Process finished' |
|
|
546 | 589 | return 0 |
|
|
547 | 590 | |
|
|
548 | 591 | if self.__hasNotDataInBuffer(): |
|
|
549 | 592 | self.readNextBlock() |
|
|
550 | 593 | |
|
|
551 | 594 | |
|
|
552 | 595 | if self.datablock == None: # setear esta condicion cuando no hayan datos por leers |
|
|
553 | 596 | self.dataOut.flagNoData = True |
|
|
554 | 597 | return 0 |
|
|
555 | 598 | |
|
|
556 | 599 | self.dataOut.data = numpy.reshape(self.datablock[self.profileIndex,:],(1,-1)) |
|
|
557 | 600 | |
|
|
558 | 601 | self.dataOut.utctime = self.radacTimeByFrame[self.profileIndex] |
|
|
559 | 602 | |
|
|
560 | 603 | self.dataOut.flagNoData = False |
|
|
561 | 604 | |
|
|
562 | 605 | self.profileIndex += 1 |
|
|
563 | 606 | |
|
|
564 | 607 | return self.dataOut.data |
|
|
565 | 608 | |
|
|
566 | 609 | |
|
|
567 | 610 | def run(self, **kwargs): |
|
|
568 | 611 | if not(self.isConfig): |
|
|
569 | 612 | self.setup(**kwargs) |
|
|
570 | 613 | self.setObjProperties() |
|
|
571 | 614 | self.isConfig = True |
|
|
572 | 615 | |
|
|
573 | 616 | self.getData() |
| @@ -1,87 +1,91 | |||
|
|
1 | 1 | ''' |
|
|
2 | 2 | @author: Daniel Suarez |
|
|
3 | 3 | ''' |
|
|
4 | 4 | |
|
|
5 | 5 | from jroproc_base import ProcessingUnit, Operation |
|
|
6 | 6 | from model.data.jroamisr import AMISR |
|
|
7 | 7 | |
|
|
8 | 8 | class AMISRProc(ProcessingUnit): |
|
|
9 | 9 | def __init__(self): |
|
|
10 | 10 | ProcessingUnit.__init__(self) |
|
|
11 | 11 | self.objectDict = {} |
|
|
12 | 12 | self.dataOut = AMISR() |
|
|
13 | 13 | |
|
|
14 | 14 | def run(self): |
|
|
15 | 15 | if self.dataIn.type == 'AMISR': |
|
|
16 | 16 | self.dataOut.copy(self.dataIn) |
|
|
17 | 17 | |
|
|
18 | 18 | |
|
|
19 | 19 | class PrintInfo(Operation): |
|
|
20 | 20 | def __init__(self): |
|
|
21 | 21 | self.__isPrinted = False |
|
|
22 | 22 | |
|
|
23 | 23 | def run(self, dataOut): |
|
|
24 | 24 | |
|
|
25 | 25 | if not self.__isPrinted: |
|
|
26 | 26 | print 'Number of Records by File: %d'%dataOut.nRecords |
|
|
27 | 27 | print 'Number of Pulses: %d'%dataOut.nProfiles |
|
|
28 | 28 | print 'Number of Pulses by Frame: %d'%dataOut.npulseByFrame |
|
|
29 | 29 | print 'Number of Samples by Pulse: %d'%len(dataOut.heightList) |
|
|
30 | 30 | print 'Ipp Seconds: %f'%dataOut.ippSeconds |
|
|
31 | 31 | print 'Number of Beams: %d'%dataOut.nBeams |
|
|
32 | 32 | print 'BeamCodes:' |
|
|
33 |
beamStrList = ['Beam %d -> Code |
|
|
|
33 | beamStrList = ['Beam %d -> Code=%d, azimuth=%2.2f, zenith=%2.2f, gain=%2.2f'%(k,v[0],v[1],v[2],v[3]) for k,v in dataOut.beamCodeDict.items()] | |
|
|
34 | 34 | for b in beamStrList: |
|
|
35 | 35 | print b |
|
|
36 | 36 | self.__isPrinted = True |
|
|
37 | 37 | |
|
|
38 | 38 | return |
|
|
39 | 39 | |
|
|
40 | 40 | |
|
|
41 | 41 | class BeamSelector(Operation): |
|
|
42 | 42 | profileIndex = None |
|
|
43 | 43 | nProfiles = None |
|
|
44 | 44 | |
|
|
45 | 45 | def __init__(self): |
|
|
46 | 46 | |
|
|
47 | 47 | self.profileIndex = 0 |
|
|
48 | 48 | |
|
|
49 | 49 | def incIndex(self): |
|
|
50 | 50 | self.profileIndex += 1 |
|
|
51 | 51 | |
|
|
52 | 52 | if self.profileIndex >= self.nProfiles: |
|
|
53 | 53 | self.profileIndex = 0 |
|
|
54 | 54 | |
|
|
55 | 55 | def isProfileInRange(self, minIndex, maxIndex): |
|
|
56 | 56 | |
|
|
57 | 57 | if self.profileIndex < minIndex: |
|
|
58 | 58 | return False |
|
|
59 | 59 | |
|
|
60 | 60 | if self.profileIndex > maxIndex: |
|
|
61 | 61 | return False |
|
|
62 | 62 | |
|
|
63 | 63 | return True |
|
|
64 | 64 | |
|
|
65 | 65 | def isProfileInList(self, profileList): |
|
|
66 | 66 | |
|
|
67 | 67 | if self.profileIndex not in profileList: |
|
|
68 | 68 | return False |
|
|
69 | 69 | |
|
|
70 | 70 | return True |
|
|
71 | 71 | |
|
|
72 | 72 | def run(self, dataOut, beam=None): |
|
|
73 | 73 | |
|
|
74 | 74 | dataOut.flagNoData = True |
|
|
75 | 75 | self.nProfiles = dataOut.nProfiles |
|
|
76 | 76 | |
|
|
77 | 77 | if beam != None: |
|
|
78 | 78 | if self.isProfileInList(dataOut.beamRangeDict[beam]): |
|
|
79 | beamInfo = dataOut.beamCodeDict[beam] | |
|
|
80 | dataOut.azimuth = beamInfo[1] | |
|
|
81 | dataOut.zenith = beamInfo[2] | |
|
|
82 | dataOut.gain = beamInfo[3] | |
|
|
79 | 83 | dataOut.flagNoData = False |
|
|
80 | 84 | |
|
|
81 | 85 | self.incIndex() |
|
|
82 | 86 | return 1 |
|
|
83 | 87 | |
|
|
84 | 88 | else: |
|
|
85 | 89 | raise ValueError, "BeamSelector needs beam value" |
|
|
86 | 90 | |
|
|
87 | 91 | return 0 No newline at end of file |
| @@ -1,927 +1,930 | |||
|
|
1 | 1 | import numpy |
|
|
2 | 2 | |
|
|
3 | 3 | from jroproc_base import ProcessingUnit, Operation |
|
|
4 | 4 | from model.data.jrodata import Spectra |
|
|
5 | 5 | from model.data.jrodata import hildebrand_sekhon |
|
|
6 | 6 | |
|
|
7 | 7 | class SpectraProc(ProcessingUnit): |
|
|
8 | 8 | |
|
|
9 | 9 | def __init__(self): |
|
|
10 | 10 | |
|
|
11 | 11 | ProcessingUnit.__init__(self) |
|
|
12 | 12 | |
|
|
13 | 13 | self.buffer = None |
|
|
14 | 14 | self.firstdatatime = None |
|
|
15 | 15 | self.profIndex = 0 |
|
|
16 | 16 | self.dataOut = Spectra() |
|
|
17 | 17 | self.id_min = None |
|
|
18 | 18 | self.id_max = None |
|
|
19 | 19 | |
|
|
20 | 20 | def __updateObjFromInput(self): |
|
|
21 | 21 | |
|
|
22 | 22 | self.dataOut.timeZone = self.dataIn.timeZone |
|
|
23 | 23 | self.dataOut.dstFlag = self.dataIn.dstFlag |
|
|
24 | 24 | self.dataOut.errorCount = self.dataIn.errorCount |
|
|
25 | 25 | self.dataOut.useLocalTime = self.dataIn.useLocalTime |
|
|
26 | 26 | |
|
|
27 | 27 | self.dataOut.radarControllerHeaderObj = self.dataIn.radarControllerHeaderObj.copy() |
|
|
28 | 28 | self.dataOut.systemHeaderObj = self.dataIn.systemHeaderObj.copy() |
|
|
29 | 29 | self.dataOut.channelList = self.dataIn.channelList |
|
|
30 | 30 | self.dataOut.heightList = self.dataIn.heightList |
|
|
31 | 31 | self.dataOut.dtype = numpy.dtype([('real','<f4'),('imag','<f4')]) |
|
|
32 | 32 | # self.dataOut.nHeights = self.dataIn.nHeights |
|
|
33 | 33 | # self.dataOut.nChannels = self.dataIn.nChannels |
|
|
34 | 34 | self.dataOut.nBaud = self.dataIn.nBaud |
|
|
35 | 35 | self.dataOut.nCode = self.dataIn.nCode |
|
|
36 | 36 | self.dataOut.code = self.dataIn.code |
|
|
37 | 37 | self.dataOut.nProfiles = self.dataOut.nFFTPoints |
|
|
38 | 38 | # self.dataOut.channelIndexList = self.dataIn.channelIndexList |
|
|
39 | 39 | self.dataOut.flagTimeBlock = self.dataIn.flagTimeBlock |
|
|
40 | 40 | self.dataOut.utctime = self.firstdatatime |
|
|
41 | 41 | self.dataOut.flagDecodeData = self.dataIn.flagDecodeData #asumo q la data esta decodificada |
|
|
42 | 42 | self.dataOut.flagDeflipData = self.dataIn.flagDeflipData #asumo q la data esta sin flip |
|
|
43 | 43 | # self.dataOut.flagShiftFFT = self.dataIn.flagShiftFFT |
|
|
44 | 44 | self.dataOut.nCohInt = self.dataIn.nCohInt |
|
|
45 | 45 | self.dataOut.nIncohInt = 1 |
|
|
46 | 46 | # self.dataOut.ippSeconds = self.dataIn.ippSeconds |
|
|
47 | 47 | self.dataOut.windowOfFilter = self.dataIn.windowOfFilter |
|
|
48 | 48 | |
|
|
49 | 49 | self.dataOut.timeInterval = self.dataIn.timeInterval*self.dataOut.nFFTPoints*self.dataOut.nIncohInt |
|
|
50 | 50 | self.dataOut.frequency = self.dataIn.frequency |
|
|
51 | 51 | self.dataOut.realtime = self.dataIn.realtime |
|
|
52 | 52 | |
|
|
53 | self.dataOut.azimuth = self.dataIn.azimuth | |
|
|
54 | self.dataOut.zenith = self.dataIn.zenith | |
|
|
55 | ||
|
|
53 | 56 | def __getFft(self): |
|
|
54 | 57 | """ |
|
|
55 | 58 | Convierte valores de Voltaje a Spectra |
|
|
56 | 59 | |
|
|
57 | 60 | Affected: |
|
|
58 | 61 | self.dataOut.data_spc |
|
|
59 | 62 | self.dataOut.data_cspc |
|
|
60 | 63 | self.dataOut.data_dc |
|
|
61 | 64 | self.dataOut.heightList |
|
|
62 | 65 | self.profIndex |
|
|
63 | 66 | self.buffer |
|
|
64 | 67 | self.dataOut.flagNoData |
|
|
65 | 68 | """ |
|
|
66 | 69 | fft_volt = numpy.fft.fft(self.buffer,n=self.dataOut.nFFTPoints,axis=1) |
|
|
67 | 70 | fft_volt = fft_volt.astype(numpy.dtype('complex')) |
|
|
68 | 71 | dc = fft_volt[:,0,:] |
|
|
69 | 72 | |
|
|
70 | 73 | #calculo de self-spectra |
|
|
71 | 74 | fft_volt = numpy.fft.fftshift(fft_volt,axes=(1,)) |
|
|
72 | 75 | spc = fft_volt * numpy.conjugate(fft_volt) |
|
|
73 | 76 | spc = spc.real |
|
|
74 | 77 | |
|
|
75 | 78 | blocksize = 0 |
|
|
76 | 79 | blocksize += dc.size |
|
|
77 | 80 | blocksize += spc.size |
|
|
78 | 81 | |
|
|
79 | 82 | cspc = None |
|
|
80 | 83 | pairIndex = 0 |
|
|
81 | 84 | if self.dataOut.pairsList != None: |
|
|
82 | 85 | #calculo de cross-spectra |
|
|
83 | 86 | cspc = numpy.zeros((self.dataOut.nPairs, self.dataOut.nFFTPoints, self.dataOut.nHeights), dtype='complex') |
|
|
84 | 87 | for pair in self.dataOut.pairsList: |
|
|
85 | 88 | cspc[pairIndex,:,:] = fft_volt[pair[0],:,:] * numpy.conjugate(fft_volt[pair[1],:,:]) |
|
|
86 | 89 | pairIndex += 1 |
|
|
87 | 90 | blocksize += cspc.size |
|
|
88 | 91 | |
|
|
89 | 92 | self.dataOut.data_spc = spc |
|
|
90 | 93 | self.dataOut.data_cspc = cspc |
|
|
91 | 94 | self.dataOut.data_dc = dc |
|
|
92 | 95 | self.dataOut.blockSize = blocksize |
|
|
93 | 96 | self.dataOut.flagShiftFFT = False |
|
|
94 | 97 | |
|
|
95 | 98 | def run(self, nProfiles=None, nFFTPoints=None, pairsList=[], ippFactor=None): |
|
|
96 | 99 | |
|
|
97 | 100 | self.dataOut.flagNoData = True |
|
|
98 | 101 | |
|
|
99 | 102 | if self.dataIn.type == "Spectra": |
|
|
100 | 103 | self.dataOut.copy(self.dataIn) |
|
|
101 | 104 | return True |
|
|
102 | 105 | |
|
|
103 | 106 | if self.dataIn.type == "Voltage": |
|
|
104 | 107 | |
|
|
105 | 108 | if nFFTPoints == None: |
|
|
106 | 109 | raise ValueError, "This SpectraProc.run() need nFFTPoints input variable" |
|
|
107 | 110 | |
|
|
108 | 111 | if nProfiles == None: |
|
|
109 | 112 | raise ValueError, "This SpectraProc.run() need nProfiles input variable" |
|
|
110 | 113 | |
|
|
111 | 114 | |
|
|
112 | 115 | if ippFactor == None: |
|
|
113 | 116 | ippFactor = 1 |
|
|
114 | 117 | self.dataOut.ippFactor = ippFactor |
|
|
115 | 118 | |
|
|
116 | 119 | self.dataOut.nFFTPoints = nFFTPoints |
|
|
117 | 120 | self.dataOut.pairsList = pairsList |
|
|
118 | 121 | |
|
|
119 | 122 | if self.buffer == None: |
|
|
120 | 123 | self.buffer = numpy.zeros((self.dataIn.nChannels, |
|
|
121 | 124 | nProfiles, |
|
|
122 | 125 | self.dataIn.nHeights), |
|
|
123 | 126 | dtype='complex') |
|
|
124 | 127 | self.id_min = 0 |
|
|
125 | 128 | self.id_max = self.dataIn.data.shape[1] |
|
|
126 | 129 | |
|
|
127 | 130 | if len(self.dataIn.data.shape) == 2: |
|
|
128 | 131 | self.buffer[:,self.profIndex,:] = self.dataIn.data.copy() |
|
|
129 | 132 | self.profIndex += 1 |
|
|
130 | 133 | else: |
|
|
131 | 134 | if self.dataIn.data.shape[1] == nProfiles: |
|
|
132 | 135 | self.buffer = self.dataIn.data.copy() |
|
|
133 | 136 | self.profIndex = nProfiles |
|
|
134 | 137 | elif self.dataIn.data.shape[1] < nProfiles: |
|
|
135 | 138 | self.buffer[:,self.id_min:self.id_max,:] = self.dataIn.data |
|
|
136 | 139 | self.profIndex += self.dataIn.data.shape[1] |
|
|
137 | 140 | self.id_min += self.dataIn.data.shape[1] |
|
|
138 | 141 | self.id_max += self.dataIn.data.shape[1] |
|
|
139 | 142 | else: |
|
|
140 | 143 | raise ValueError, "The type object %s has %d profiles, it should be equal to %d profiles"%(self.dataIn.type,self.dataIn.data.shape[1],nProfiles) |
|
|
141 | 144 | self.dataOut.flagNoData = True |
|
|
142 | 145 | return 0 |
|
|
143 | 146 | |
|
|
144 | 147 | |
|
|
145 | 148 | if self.firstdatatime == None: |
|
|
146 | 149 | self.firstdatatime = self.dataIn.utctime |
|
|
147 | 150 | |
|
|
148 | 151 | if self.profIndex == nProfiles: |
|
|
149 | 152 | self.__updateObjFromInput() |
|
|
150 | 153 | self.__getFft() |
|
|
151 | 154 | |
|
|
152 | 155 | self.dataOut.flagNoData = False |
|
|
153 | 156 | |
|
|
154 | 157 | self.buffer = None |
|
|
155 | 158 | self.firstdatatime = None |
|
|
156 | 159 | self.profIndex = 0 |
|
|
157 | 160 | |
|
|
158 | 161 | return True |
|
|
159 | 162 | |
|
|
160 | 163 | raise ValueError, "The type object %s is not valid"%(self.dataIn.type) |
|
|
161 | 164 | |
|
|
162 | 165 | def selectChannels(self, channelList): |
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163 | 166 | |
|
|
164 | 167 | channelIndexList = [] |
|
|
165 | 168 | |
|
|
166 | 169 | for channel in channelList: |
|
|
167 | 170 | index = self.dataOut.channelList.index(channel) |
|
|
168 | 171 | channelIndexList.append(index) |
|
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169 | 172 | |
|
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170 | 173 | self.selectChannelsByIndex(channelIndexList) |
|
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171 | 174 | |
|
|
172 | 175 | def selectChannelsByIndex(self, channelIndexList): |
|
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173 | 176 | """ |
|
|
174 | 177 | Selecciona un bloque de datos en base a canales segun el channelIndexList |
|
|
175 | 178 | |
|
|
176 | 179 | Input: |
|
|
177 | 180 | channelIndexList : lista sencilla de canales a seleccionar por ej. [2,3,7] |
|
|
178 | 181 | |
|
|
179 | 182 | Affected: |
|
|
180 | 183 | self.dataOut.data_spc |
|
|
181 | 184 | self.dataOut.channelIndexList |
|
|
182 | 185 | self.dataOut.nChannels |
|
|
183 | 186 | |
|
|
184 | 187 | Return: |
|
|
185 | 188 | None |
|
|
186 | 189 | """ |
|
|
187 | 190 | |
|
|
188 | 191 | for channelIndex in channelIndexList: |
|
|
189 | 192 | if channelIndex not in self.dataOut.channelIndexList: |
|
|
190 | 193 | print channelIndexList |
|
|
191 | 194 | raise ValueError, "The value %d in channelIndexList is not valid" %channelIndex |
|
|
192 | 195 | |
|
|
193 | 196 | # nChannels = len(channelIndexList) |
|
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194 | 197 | |
|
|
195 | 198 | data_spc = self.dataOut.data_spc[channelIndexList,:] |
|
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196 | 199 | |
|
|
197 | 200 | self.dataOut.data_spc = data_spc |
|
|
198 | 201 | self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList] |
|
|
199 | 202 | # self.dataOut.nChannels = nChannels |
|
|
200 | 203 | |
|
|
201 | 204 | return 1 |
|
|
202 | 205 | |
|
|
203 | 206 | def selectHeights(self, minHei, maxHei): |
|
|
204 | 207 | """ |
|
|
205 | 208 | Selecciona un bloque de datos en base a un grupo de valores de alturas segun el rango |
|
|
206 | 209 | minHei <= height <= maxHei |
|
|
207 | 210 | |
|
|
208 | 211 | Input: |
|
|
209 | 212 | minHei : valor minimo de altura a considerar |
|
|
210 | 213 | maxHei : valor maximo de altura a considerar |
|
|
211 | 214 | |
|
|
212 | 215 | Affected: |
|
|
213 | 216 | Indirectamente son cambiados varios valores a travez del metodo selectHeightsByIndex |
|
|
214 | 217 | |
|
|
215 | 218 | Return: |
|
|
216 | 219 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 |
|
|
217 | 220 | """ |
|
|
218 | 221 | if (minHei < self.dataOut.heightList[0]) or (minHei > maxHei): |
|
|
219 | 222 | raise ValueError, "some value in (%d,%d) is not valid" % (minHei, maxHei) |
|
|
220 | 223 | |
|
|
221 | 224 | if (maxHei > self.dataOut.heightList[-1]): |
|
|
222 | 225 | maxHei = self.dataOut.heightList[-1] |
|
|
223 | 226 | # raise ValueError, "some value in (%d,%d) is not valid" % (minHei, maxHei) |
|
|
224 | 227 | |
|
|
225 | 228 | minIndex = 0 |
|
|
226 | 229 | maxIndex = 0 |
|
|
227 | 230 | heights = self.dataOut.heightList |
|
|
228 | 231 | |
|
|
229 | 232 | inda = numpy.where(heights >= minHei) |
|
|
230 | 233 | indb = numpy.where(heights <= maxHei) |
|
|
231 | 234 | |
|
|
232 | 235 | try: |
|
|
233 | 236 | minIndex = inda[0][0] |
|
|
234 | 237 | except: |
|
|
235 | 238 | minIndex = 0 |
|
|
236 | 239 | |
|
|
237 | 240 | try: |
|
|
238 | 241 | maxIndex = indb[0][-1] |
|
|
239 | 242 | except: |
|
|
240 | 243 | maxIndex = len(heights) |
|
|
241 | 244 | |
|
|
242 | 245 | self.selectHeightsByIndex(minIndex, maxIndex) |
|
|
243 | 246 | |
|
|
244 | 247 | return 1 |
|
|
245 | 248 | |
|
|
246 | 249 | def getBeaconSignal(self, tauindex = 0, channelindex = 0, hei_ref=None): |
|
|
247 | 250 | newheis = numpy.where(self.dataOut.heightList>self.dataOut.radarControllerHeaderObj.Taus[tauindex]) |
|
|
248 | 251 | |
|
|
249 | 252 | if hei_ref != None: |
|
|
250 | 253 | newheis = numpy.where(self.dataOut.heightList>hei_ref) |
|
|
251 | 254 | |
|
|
252 | 255 | minIndex = min(newheis[0]) |
|
|
253 | 256 | maxIndex = max(newheis[0]) |
|
|
254 | 257 | data_spc = self.dataOut.data_spc[:,:,minIndex:maxIndex+1] |
|
|
255 | 258 | heightList = self.dataOut.heightList[minIndex:maxIndex+1] |
|
|
256 | 259 | |
|
|
257 | 260 | # determina indices |
|
|
258 | 261 | nheis = int(self.dataOut.radarControllerHeaderObj.txB/(self.dataOut.heightList[1]-self.dataOut.heightList[0])) |
|
|
259 | 262 | avg_dB = 10*numpy.log10(numpy.sum(data_spc[channelindex,:,:],axis=0)) |
|
|
260 | 263 | beacon_dB = numpy.sort(avg_dB)[-nheis:] |
|
|
261 | 264 | beacon_heiIndexList = [] |
|
|
262 | 265 | for val in avg_dB.tolist(): |
|
|
263 | 266 | if val >= beacon_dB[0]: |
|
|
264 | 267 | beacon_heiIndexList.append(avg_dB.tolist().index(val)) |
|
|
265 | 268 | |
|
|
266 | 269 | #data_spc = data_spc[:,:,beacon_heiIndexList] |
|
|
267 | 270 | data_cspc = None |
|
|
268 | 271 | if self.dataOut.data_cspc != None: |
|
|
269 | 272 | data_cspc = self.dataOut.data_cspc[:,:,minIndex:maxIndex+1] |
|
|
270 | 273 | #data_cspc = data_cspc[:,:,beacon_heiIndexList] |
|
|
271 | 274 | |
|
|
272 | 275 | data_dc = None |
|
|
273 | 276 | if self.dataOut.data_dc != None: |
|
|
274 | 277 | data_dc = self.dataOut.data_dc[:,minIndex:maxIndex+1] |
|
|
275 | 278 | #data_dc = data_dc[:,beacon_heiIndexList] |
|
|
276 | 279 | |
|
|
277 | 280 | self.dataOut.data_spc = data_spc |
|
|
278 | 281 | self.dataOut.data_cspc = data_cspc |
|
|
279 | 282 | self.dataOut.data_dc = data_dc |
|
|
280 | 283 | self.dataOut.heightList = heightList |
|
|
281 | 284 | self.dataOut.beacon_heiIndexList = beacon_heiIndexList |
|
|
282 | 285 | |
|
|
283 | 286 | return 1 |
|
|
284 | 287 | |
|
|
285 | 288 | |
|
|
286 | 289 | def selectHeightsByIndex(self, minIndex, maxIndex): |
|
|
287 | 290 | """ |
|
|
288 | 291 | Selecciona un bloque de datos en base a un grupo indices de alturas segun el rango |
|
|
289 | 292 | minIndex <= index <= maxIndex |
|
|
290 | 293 | |
|
|
291 | 294 | Input: |
|
|
292 | 295 | minIndex : valor de indice minimo de altura a considerar |
|
|
293 | 296 | maxIndex : valor de indice maximo de altura a considerar |
|
|
294 | 297 | |
|
|
295 | 298 | Affected: |
|
|
296 | 299 | self.dataOut.data_spc |
|
|
297 | 300 | self.dataOut.data_cspc |
|
|
298 | 301 | self.dataOut.data_dc |
|
|
299 | 302 | self.dataOut.heightList |
|
|
300 | 303 | |
|
|
301 | 304 | Return: |
|
|
302 | 305 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 |
|
|
303 | 306 | """ |
|
|
304 | 307 | |
|
|
305 | 308 | if (minIndex < 0) or (minIndex > maxIndex): |
|
|
306 | 309 | raise ValueError, "some value in (%d,%d) is not valid" % (minIndex, maxIndex) |
|
|
307 | 310 | |
|
|
308 | 311 | if (maxIndex >= self.dataOut.nHeights): |
|
|
309 | 312 | maxIndex = self.dataOut.nHeights-1 |
|
|
310 | 313 | # raise ValueError, "some value in (%d,%d) is not valid" % (minIndex, maxIndex) |
|
|
311 | 314 | |
|
|
312 | 315 | # nHeights = maxIndex - minIndex + 1 |
|
|
313 | 316 | |
|
|
314 | 317 | #Spectra |
|
|
315 | 318 | data_spc = self.dataOut.data_spc[:,:,minIndex:maxIndex+1] |
|
|
316 | 319 | |
|
|
317 | 320 | data_cspc = None |
|
|
318 | 321 | if self.dataOut.data_cspc != None: |
|
|
319 | 322 | data_cspc = self.dataOut.data_cspc[:,:,minIndex:maxIndex+1] |
|
|
320 | 323 | |
|
|
321 | 324 | data_dc = None |
|
|
322 | 325 | if self.dataOut.data_dc != None: |
|
|
323 | 326 | data_dc = self.dataOut.data_dc[:,minIndex:maxIndex+1] |
|
|
324 | 327 | |
|
|
325 | 328 | self.dataOut.data_spc = data_spc |
|
|
326 | 329 | self.dataOut.data_cspc = data_cspc |
|
|
327 | 330 | self.dataOut.data_dc = data_dc |
|
|
328 | 331 | |
|
|
329 | 332 | self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex+1] |
|
|
330 | 333 | |
|
|
331 | 334 | return 1 |
|
|
332 | 335 | |
|
|
333 | 336 | def removeDC(self, mode = 2): |
|
|
334 | 337 | jspectra = self.dataOut.data_spc |
|
|
335 | 338 | jcspectra = self.dataOut.data_cspc |
|
|
336 | 339 | |
|
|
337 | 340 | |
|
|
338 | 341 | num_chan = jspectra.shape[0] |
|
|
339 | 342 | num_hei = jspectra.shape[2] |
|
|
340 | 343 | |
|
|
341 | 344 | if jcspectra != None: |
|
|
342 | 345 | jcspectraExist = True |
|
|
343 | 346 | num_pairs = jcspectra.shape[0] |
|
|
344 | 347 | else: jcspectraExist = False |
|
|
345 | 348 | |
|
|
346 | 349 | freq_dc = jspectra.shape[1]/2 |
|
|
347 | 350 | ind_vel = numpy.array([-2,-1,1,2]) + freq_dc |
|
|
348 | 351 | |
|
|
349 | 352 | if ind_vel[0]<0: |
|
|
350 | 353 | ind_vel[range(0,1)] = ind_vel[range(0,1)] + self.num_prof |
|
|
351 | 354 | |
|
|
352 | 355 | if mode == 1: |
|
|
353 | 356 | jspectra[:,freq_dc,:] = (jspectra[:,ind_vel[1],:] + jspectra[:,ind_vel[2],:])/2 #CORRECCION |
|
|
354 | 357 | |
|
|
355 | 358 | if jcspectraExist: |
|
|
356 | 359 | jcspectra[:,freq_dc,:] = (jcspectra[:,ind_vel[1],:] + jcspectra[:,ind_vel[2],:])/2 |
|
|
357 | 360 | |
|
|
358 | 361 | if mode == 2: |
|
|
359 | 362 | |
|
|
360 | 363 | vel = numpy.array([-2,-1,1,2]) |
|
|
361 | 364 | xx = numpy.zeros([4,4]) |
|
|
362 | 365 | |
|
|
363 | 366 | for fil in range(4): |
|
|
364 | 367 | xx[fil,:] = vel[fil]**numpy.asarray(range(4)) |
|
|
365 | 368 | |
|
|
366 | 369 | xx_inv = numpy.linalg.inv(xx) |
|
|
367 | 370 | xx_aux = xx_inv[0,:] |
|
|
368 | 371 | |
|
|
369 | 372 | for ich in range(num_chan): |
|
|
370 | 373 | yy = jspectra[ich,ind_vel,:] |
|
|
371 | 374 | jspectra[ich,freq_dc,:] = numpy.dot(xx_aux,yy) |
|
|
372 | 375 | |
|
|
373 | 376 | junkid = jspectra[ich,freq_dc,:]<=0 |
|
|
374 | 377 | cjunkid = sum(junkid) |
|
|
375 | 378 | |
|
|
376 | 379 | if cjunkid.any(): |
|
|
377 | 380 | jspectra[ich,freq_dc,junkid.nonzero()] = (jspectra[ich,ind_vel[1],junkid] + jspectra[ich,ind_vel[2],junkid])/2 |
|
|
378 | 381 | |
|
|
379 | 382 | if jcspectraExist: |
|
|
380 | 383 | for ip in range(num_pairs): |
|
|
381 | 384 | yy = jcspectra[ip,ind_vel,:] |
|
|
382 | 385 | jcspectra[ip,freq_dc,:] = numpy.dot(xx_aux,yy) |
|
|
383 | 386 | |
|
|
384 | 387 | |
|
|
385 | 388 | self.dataOut.data_spc = jspectra |
|
|
386 | 389 | self.dataOut.data_cspc = jcspectra |
|
|
387 | 390 | |
|
|
388 | 391 | return 1 |
|
|
389 | 392 | |
|
|
390 | 393 | def removeInterference(self, interf = 2,hei_interf = None, nhei_interf = None, offhei_interf = None): |
|
|
391 | 394 | |
|
|
392 | 395 | jspectra = self.dataOut.data_spc |
|
|
393 | 396 | jcspectra = self.dataOut.data_cspc |
|
|
394 | 397 | jnoise = self.dataOut.getNoise() |
|
|
395 | 398 | num_incoh = self.dataOut.nIncohInt |
|
|
396 | 399 | |
|
|
397 | 400 | num_channel = jspectra.shape[0] |
|
|
398 | 401 | num_prof = jspectra.shape[1] |
|
|
399 | 402 | num_hei = jspectra.shape[2] |
|
|
400 | 403 | |
|
|
401 | 404 | #hei_interf |
|
|
402 | 405 | if hei_interf == None: |
|
|
403 | 406 | count_hei = num_hei/2 #Como es entero no importa |
|
|
404 | 407 | hei_interf = numpy.asmatrix(range(count_hei)) + num_hei - count_hei |
|
|
405 | 408 | hei_interf = numpy.asarray(hei_interf)[0] |
|
|
406 | 409 | #nhei_interf |
|
|
407 | 410 | if (nhei_interf == None): |
|
|
408 | 411 | nhei_interf = 5 |
|
|
409 | 412 | if (nhei_interf < 1): |
|
|
410 | 413 | nhei_interf = 1 |
|
|
411 | 414 | if (nhei_interf > count_hei): |
|
|
412 | 415 | nhei_interf = count_hei |
|
|
413 | 416 | if (offhei_interf == None): |
|
|
414 | 417 | offhei_interf = 0 |
|
|
415 | 418 | |
|
|
416 | 419 | ind_hei = range(num_hei) |
|
|
417 | 420 | # mask_prof = numpy.asarray(range(num_prof - 2)) + 1 |
|
|
418 | 421 | # mask_prof[range(num_prof/2 - 1,len(mask_prof))] += 1 |
|
|
419 | 422 | mask_prof = numpy.asarray(range(num_prof)) |
|
|
420 | 423 | num_mask_prof = mask_prof.size |
|
|
421 | 424 | comp_mask_prof = [0, num_prof/2] |
|
|
422 | 425 | |
|
|
423 | 426 | |
|
|
424 | 427 | #noise_exist: Determina si la variable jnoise ha sido definida y contiene la informacion del ruido de cada canal |
|
|
425 | 428 | if (jnoise.size < num_channel or numpy.isnan(jnoise).any()): |
|
|
426 | 429 | jnoise = numpy.nan |
|
|
427 | 430 | noise_exist = jnoise[0] < numpy.Inf |
|
|
428 | 431 | |
|
|
429 | 432 | #Subrutina de Remocion de la Interferencia |
|
|
430 | 433 | for ich in range(num_channel): |
|
|
431 | 434 | #Se ordena los espectros segun su potencia (menor a mayor) |
|
|
432 | 435 | power = jspectra[ich,mask_prof,:] |
|
|
433 | 436 | power = power[:,hei_interf] |
|
|
434 | 437 | power = power.sum(axis = 0) |
|
|
435 | 438 | psort = power.ravel().argsort() |
|
|
436 | 439 | |
|
|
437 | 440 | #Se estima la interferencia promedio en los Espectros de Potencia empleando |
|
|
438 | 441 | junkspc_interf = jspectra[ich,:,hei_interf[psort[range(offhei_interf, nhei_interf + offhei_interf)]]] |
|
|
439 | 442 | |
|
|
440 | 443 | if noise_exist: |
|
|
441 | 444 | # tmp_noise = jnoise[ich] / num_prof |
|
|
442 | 445 | tmp_noise = jnoise[ich] |
|
|
443 | 446 | junkspc_interf = junkspc_interf - tmp_noise |
|
|
444 | 447 | #junkspc_interf[:,comp_mask_prof] = 0 |
|
|
445 | 448 | |
|
|
446 | 449 | jspc_interf = junkspc_interf.sum(axis = 0) / nhei_interf |
|
|
447 | 450 | jspc_interf = jspc_interf.transpose() |
|
|
448 | 451 | #Calculando el espectro de interferencia promedio |
|
|
449 | 452 | noiseid = numpy.where(jspc_interf <= tmp_noise/ math.sqrt(num_incoh)) |
|
|
450 | 453 | noiseid = noiseid[0] |
|
|
451 | 454 | cnoiseid = noiseid.size |
|
|
452 | 455 | interfid = numpy.where(jspc_interf > tmp_noise/ math.sqrt(num_incoh)) |
|
|
453 | 456 | interfid = interfid[0] |
|
|
454 | 457 | cinterfid = interfid.size |
|
|
455 | 458 | |
|
|
456 | 459 | if (cnoiseid > 0): jspc_interf[noiseid] = 0 |
|
|
457 | 460 | |
|
|
458 | 461 | #Expandiendo los perfiles a limpiar |
|
|
459 | 462 | if (cinterfid > 0): |
|
|
460 | 463 | new_interfid = (numpy.r_[interfid - 1, interfid, interfid + 1] + num_prof)%num_prof |
|
|
461 | 464 | new_interfid = numpy.asarray(new_interfid) |
|
|
462 | 465 | new_interfid = {x for x in new_interfid} |
|
|
463 | 466 | new_interfid = numpy.array(list(new_interfid)) |
|
|
464 | 467 | new_cinterfid = new_interfid.size |
|
|
465 | 468 | else: new_cinterfid = 0 |
|
|
466 | 469 | |
|
|
467 | 470 | for ip in range(new_cinterfid): |
|
|
468 | 471 | ind = junkspc_interf[:,new_interfid[ip]].ravel().argsort() |
|
|
469 | 472 | jspc_interf[new_interfid[ip]] = junkspc_interf[ind[nhei_interf/2],new_interfid[ip]] |
|
|
470 | 473 | |
|
|
471 | 474 | |
|
|
472 | 475 | jspectra[ich,:,ind_hei] = jspectra[ich,:,ind_hei] - jspc_interf #Corregir indices |
|
|
473 | 476 | |
|
|
474 | 477 | #Removiendo la interferencia del punto de mayor interferencia |
|
|
475 | 478 | ListAux = jspc_interf[mask_prof].tolist() |
|
|
476 | 479 | maxid = ListAux.index(max(ListAux)) |
|
|
477 | 480 | |
|
|
478 | 481 | |
|
|
479 | 482 | if cinterfid > 0: |
|
|
480 | 483 | for ip in range(cinterfid*(interf == 2) - 1): |
|
|
481 | 484 | ind = (jspectra[ich,interfid[ip],:] < tmp_noise*(1 + 1/math.sqrt(num_incoh))).nonzero() |
|
|
482 | 485 | cind = len(ind) |
|
|
483 | 486 | |
|
|
484 | 487 | if (cind > 0): |
|
|
485 | 488 | jspectra[ich,interfid[ip],ind] = tmp_noise*(1 + (numpy.random.uniform(cind) - 0.5)/math.sqrt(num_incoh)) |
|
|
486 | 489 | |
|
|
487 | 490 | ind = numpy.array([-2,-1,1,2]) |
|
|
488 | 491 | xx = numpy.zeros([4,4]) |
|
|
489 | 492 | |
|
|
490 | 493 | for id1 in range(4): |
|
|
491 | 494 | xx[:,id1] = ind[id1]**numpy.asarray(range(4)) |
|
|
492 | 495 | |
|
|
493 | 496 | xx_inv = numpy.linalg.inv(xx) |
|
|
494 | 497 | xx = xx_inv[:,0] |
|
|
495 | 498 | ind = (ind + maxid + num_mask_prof)%num_mask_prof |
|
|
496 | 499 | yy = jspectra[ich,mask_prof[ind],:] |
|
|
497 | 500 | jspectra[ich,mask_prof[maxid],:] = numpy.dot(yy.transpose(),xx) |
|
|
498 | 501 | |
|
|
499 | 502 | |
|
|
500 | 503 | indAux = (jspectra[ich,:,:] < tmp_noise*(1-1/math.sqrt(num_incoh))).nonzero() |
|
|
501 | 504 | jspectra[ich,indAux[0],indAux[1]] = tmp_noise * (1 - 1/math.sqrt(num_incoh)) |
|
|
502 | 505 | |
|
|
503 | 506 | #Remocion de Interferencia en el Cross Spectra |
|
|
504 | 507 | if jcspectra == None: return jspectra, jcspectra |
|
|
505 | 508 | num_pairs = jcspectra.size/(num_prof*num_hei) |
|
|
506 | 509 | jcspectra = jcspectra.reshape(num_pairs, num_prof, num_hei) |
|
|
507 | 510 | |
|
|
508 | 511 | for ip in range(num_pairs): |
|
|
509 | 512 | |
|
|
510 | 513 | #------------------------------------------- |
|
|
511 | 514 | |
|
|
512 | 515 | cspower = numpy.abs(jcspectra[ip,mask_prof,:]) |
|
|
513 | 516 | cspower = cspower[:,hei_interf] |
|
|
514 | 517 | cspower = cspower.sum(axis = 0) |
|
|
515 | 518 | |
|
|
516 | 519 | cspsort = cspower.ravel().argsort() |
|
|
517 | 520 | junkcspc_interf = jcspectra[ip,:,hei_interf[cspsort[range(offhei_interf, nhei_interf + offhei_interf)]]] |
|
|
518 | 521 | junkcspc_interf = junkcspc_interf.transpose() |
|
|
519 | 522 | jcspc_interf = junkcspc_interf.sum(axis = 1)/nhei_interf |
|
|
520 | 523 | |
|
|
521 | 524 | ind = numpy.abs(jcspc_interf[mask_prof]).ravel().argsort() |
|
|
522 | 525 | |
|
|
523 | 526 | median_real = numpy.median(numpy.real(junkcspc_interf[mask_prof[ind[range(3*num_prof/4)]],:])) |
|
|
524 | 527 | median_imag = numpy.median(numpy.imag(junkcspc_interf[mask_prof[ind[range(3*num_prof/4)]],:])) |
|
|
525 | 528 | junkcspc_interf[comp_mask_prof,:] = numpy.complex(median_real, median_imag) |
|
|
526 | 529 | |
|
|
527 | 530 | for iprof in range(num_prof): |
|
|
528 | 531 | ind = numpy.abs(junkcspc_interf[iprof,:]).ravel().argsort() |
|
|
529 | 532 | jcspc_interf[iprof] = junkcspc_interf[iprof, ind[nhei_interf/2]] |
|
|
530 | 533 | |
|
|
531 | 534 | #Removiendo la Interferencia |
|
|
532 | 535 | jcspectra[ip,:,ind_hei] = jcspectra[ip,:,ind_hei] - jcspc_interf |
|
|
533 | 536 | |
|
|
534 | 537 | ListAux = numpy.abs(jcspc_interf[mask_prof]).tolist() |
|
|
535 | 538 | maxid = ListAux.index(max(ListAux)) |
|
|
536 | 539 | |
|
|
537 | 540 | ind = numpy.array([-2,-1,1,2]) |
|
|
538 | 541 | xx = numpy.zeros([4,4]) |
|
|
539 | 542 | |
|
|
540 | 543 | for id1 in range(4): |
|
|
541 | 544 | xx[:,id1] = ind[id1]**numpy.asarray(range(4)) |
|
|
542 | 545 | |
|
|
543 | 546 | xx_inv = numpy.linalg.inv(xx) |
|
|
544 | 547 | xx = xx_inv[:,0] |
|
|
545 | 548 | |
|
|
546 | 549 | ind = (ind + maxid + num_mask_prof)%num_mask_prof |
|
|
547 | 550 | yy = jcspectra[ip,mask_prof[ind],:] |
|
|
548 | 551 | jcspectra[ip,mask_prof[maxid],:] = numpy.dot(yy.transpose(),xx) |
|
|
549 | 552 | |
|
|
550 | 553 | #Guardar Resultados |
|
|
551 | 554 | self.dataOut.data_spc = jspectra |
|
|
552 | 555 | self.dataOut.data_cspc = jcspectra |
|
|
553 | 556 | |
|
|
554 | 557 | return 1 |
|
|
555 | 558 | |
|
|
556 | 559 | def setRadarFrequency(self, frequency=None): |
|
|
557 | 560 | if frequency != None: |
|
|
558 | 561 | self.dataOut.frequency = frequency |
|
|
559 | 562 | |
|
|
560 | 563 | return 1 |
|
|
561 | 564 | |
|
|
562 | 565 | def getNoise(self, minHei=None, maxHei=None, minVel=None, maxVel=None): |
|
|
563 | 566 | #validacion de rango |
|
|
564 | 567 | if minHei == None: |
|
|
565 | 568 | minHei = self.dataOut.heightList[0] |
|
|
566 | 569 | |
|
|
567 | 570 | if maxHei == None: |
|
|
568 | 571 | maxHei = self.dataOut.heightList[-1] |
|
|
569 | 572 | |
|
|
570 | 573 | if (minHei < self.dataOut.heightList[0]) or (minHei > maxHei): |
|
|
571 | 574 | print 'minHei: %.2f is out of the heights range'%(minHei) |
|
|
572 | 575 | print 'minHei is setting to %.2f'%(self.dataOut.heightList[0]) |
|
|
573 | 576 | minHei = self.dataOut.heightList[0] |
|
|
574 | 577 | |
|
|
575 | 578 | if (maxHei > self.dataOut.heightList[-1]) or (maxHei < minHei): |
|
|
576 | 579 | print 'maxHei: %.2f is out of the heights range'%(maxHei) |
|
|
577 | 580 | print 'maxHei is setting to %.2f'%(self.dataOut.heightList[-1]) |
|
|
578 | 581 | maxHei = self.dataOut.heightList[-1] |
|
|
579 | 582 | |
|
|
580 | 583 | # validacion de velocidades |
|
|
581 | 584 | velrange = self.dataOut.getVelRange(1) |
|
|
582 | 585 | |
|
|
583 | 586 | if minVel == None: |
|
|
584 | 587 | minVel = velrange[0] |
|
|
585 | 588 | |
|
|
586 | 589 | if maxVel == None: |
|
|
587 | 590 | maxVel = velrange[-1] |
|
|
588 | 591 | |
|
|
589 | 592 | if (minVel < velrange[0]) or (minVel > maxVel): |
|
|
590 | 593 | print 'minVel: %.2f is out of the velocity range'%(minVel) |
|
|
591 | 594 | print 'minVel is setting to %.2f'%(velrange[0]) |
|
|
592 | 595 | minVel = velrange[0] |
|
|
593 | 596 | |
|
|
594 | 597 | if (maxVel > velrange[-1]) or (maxVel < minVel): |
|
|
595 | 598 | print 'maxVel: %.2f is out of the velocity range'%(maxVel) |
|
|
596 | 599 | print 'maxVel is setting to %.2f'%(velrange[-1]) |
|
|
597 | 600 | maxVel = velrange[-1] |
|
|
598 | 601 | |
|
|
599 | 602 | # seleccion de indices para rango |
|
|
600 | 603 | minIndex = 0 |
|
|
601 | 604 | maxIndex = 0 |
|
|
602 | 605 | heights = self.dataOut.heightList |
|
|
603 | 606 | |
|
|
604 | 607 | inda = numpy.where(heights >= minHei) |
|
|
605 | 608 | indb = numpy.where(heights <= maxHei) |
|
|
606 | 609 | |
|
|
607 | 610 | try: |
|
|
608 | 611 | minIndex = inda[0][0] |
|
|
609 | 612 | except: |
|
|
610 | 613 | minIndex = 0 |
|
|
611 | 614 | |
|
|
612 | 615 | try: |
|
|
613 | 616 | maxIndex = indb[0][-1] |
|
|
614 | 617 | except: |
|
|
615 | 618 | maxIndex = len(heights) |
|
|
616 | 619 | |
|
|
617 | 620 | if (minIndex < 0) or (minIndex > maxIndex): |
|
|
618 | 621 | raise ValueError, "some value in (%d,%d) is not valid" % (minIndex, maxIndex) |
|
|
619 | 622 | |
|
|
620 | 623 | if (maxIndex >= self.dataOut.nHeights): |
|
|
621 | 624 | maxIndex = self.dataOut.nHeights-1 |
|
|
622 | 625 | |
|
|
623 | 626 | # seleccion de indices para velocidades |
|
|
624 | 627 | indminvel = numpy.where(velrange >= minVel) |
|
|
625 | 628 | indmaxvel = numpy.where(velrange <= maxVel) |
|
|
626 | 629 | try: |
|
|
627 | 630 | minIndexVel = indminvel[0][0] |
|
|
628 | 631 | except: |
|
|
629 | 632 | minIndexVel = 0 |
|
|
630 | 633 | |
|
|
631 | 634 | try: |
|
|
632 | 635 | maxIndexVel = indmaxvel[0][-1] |
|
|
633 | 636 | except: |
|
|
634 | 637 | maxIndexVel = len(velrange) |
|
|
635 | 638 | |
|
|
636 | 639 | #seleccion del espectro |
|
|
637 | 640 | data_spc = self.dataOut.data_spc[:,minIndexVel:maxIndexVel+1,minIndex:maxIndex+1] |
|
|
638 | 641 | #estimacion de ruido |
|
|
639 | 642 | noise = numpy.zeros(self.dataOut.nChannels) |
|
|
640 | 643 | |
|
|
641 | 644 | for channel in range(self.dataOut.nChannels): |
|
|
642 | 645 | daux = data_spc[channel,:,:] |
|
|
643 | 646 | noise[channel] = hildebrand_sekhon(daux, self.dataOut.nIncohInt) |
|
|
644 | 647 | |
|
|
645 | 648 | self.dataOut.noise_estimation = noise.copy() |
|
|
646 | 649 | |
|
|
647 | 650 | return 1 |
|
|
648 | 651 | |
|
|
649 | 652 | class IncohInt(Operation): |
|
|
650 | 653 | |
|
|
651 | 654 | |
|
|
652 | 655 | __profIndex = 0 |
|
|
653 | 656 | __withOverapping = False |
|
|
654 | 657 | |
|
|
655 | 658 | __byTime = False |
|
|
656 | 659 | __initime = None |
|
|
657 | 660 | __lastdatatime = None |
|
|
658 | 661 | __integrationtime = None |
|
|
659 | 662 | |
|
|
660 | 663 | __buffer_spc = None |
|
|
661 | 664 | __buffer_cspc = None |
|
|
662 | 665 | __buffer_dc = None |
|
|
663 | 666 | |
|
|
664 | 667 | __dataReady = False |
|
|
665 | 668 | |
|
|
666 | 669 | __timeInterval = None |
|
|
667 | 670 | |
|
|
668 | 671 | n = None |
|
|
669 | 672 | |
|
|
670 | 673 | |
|
|
671 | 674 | |
|
|
672 | 675 | def __init__(self): |
|
|
673 | 676 | |
|
|
674 | 677 | Operation.__init__(self) |
|
|
675 | 678 | # self.isConfig = False |
|
|
676 | 679 | |
|
|
677 | 680 | def setup(self, n=None, timeInterval=None, overlapping=False): |
|
|
678 | 681 | """ |
|
|
679 | 682 | Set the parameters of the integration class. |
|
|
680 | 683 | |
|
|
681 | 684 | Inputs: |
|
|
682 | 685 | |
|
|
683 | 686 | n : Number of coherent integrations |
|
|
684 | 687 | timeInterval : Time of integration. If the parameter "n" is selected this one does not work |
|
|
685 | 688 | overlapping : |
|
|
686 | 689 | |
|
|
687 | 690 | """ |
|
|
688 | 691 | |
|
|
689 | 692 | self.__initime = None |
|
|
690 | 693 | self.__lastdatatime = 0 |
|
|
691 | 694 | self.__buffer_spc = None |
|
|
692 | 695 | self.__buffer_cspc = None |
|
|
693 | 696 | self.__buffer_dc = None |
|
|
694 | 697 | self.__dataReady = False |
|
|
695 | 698 | |
|
|
696 | 699 | |
|
|
697 | 700 | if n == None and timeInterval == None: |
|
|
698 | 701 | raise ValueError, "n or timeInterval should be specified ..." |
|
|
699 | 702 | |
|
|
700 | 703 | if n != None: |
|
|
701 | 704 | self.n = n |
|
|
702 | 705 | self.__byTime = False |
|
|
703 | 706 | else: |
|
|
704 | 707 | self.__integrationtime = timeInterval #if (type(timeInterval)!=integer) -> change this line |
|
|
705 | 708 | self.n = 9999 |
|
|
706 | 709 | self.__byTime = True |
|
|
707 | 710 | |
|
|
708 | 711 | if overlapping: |
|
|
709 | 712 | self.__withOverapping = True |
|
|
710 | 713 | else: |
|
|
711 | 714 | self.__withOverapping = False |
|
|
712 | 715 | self.__buffer_spc = 0 |
|
|
713 | 716 | self.__buffer_cspc = 0 |
|
|
714 | 717 | self.__buffer_dc = 0 |
|
|
715 | 718 | |
|
|
716 | 719 | self.__profIndex = 0 |
|
|
717 | 720 | |
|
|
718 | 721 | def putData(self, data_spc, data_cspc, data_dc): |
|
|
719 | 722 | |
|
|
720 | 723 | """ |
|
|
721 | 724 | Add a profile to the __buffer_spc and increase in one the __profileIndex |
|
|
722 | 725 | |
|
|
723 | 726 | """ |
|
|
724 | 727 | |
|
|
725 | 728 | if not self.__withOverapping: |
|
|
726 | 729 | self.__buffer_spc += data_spc |
|
|
727 | 730 | |
|
|
728 | 731 | if data_cspc == None: |
|
|
729 | 732 | self.__buffer_cspc = None |
|
|
730 | 733 | else: |
|
|
731 | 734 | self.__buffer_cspc += data_cspc |
|
|
732 | 735 | |
|
|
733 | 736 | if data_dc == None: |
|
|
734 | 737 | self.__buffer_dc = None |
|
|
735 | 738 | else: |
|
|
736 | 739 | self.__buffer_dc += data_dc |
|
|
737 | 740 | |
|
|
738 | 741 | self.__profIndex += 1 |
|
|
739 | 742 | return |
|
|
740 | 743 | |
|
|
741 | 744 | #Overlapping data |
|
|
742 | 745 | nChannels, nFFTPoints, nHeis = data_spc.shape |
|
|
743 | 746 | data_spc = numpy.reshape(data_spc, (1, nChannels, nFFTPoints, nHeis)) |
|
|
744 | 747 | if data_cspc != None: |
|
|
745 | 748 | data_cspc = numpy.reshape(data_cspc, (1, -1, nFFTPoints, nHeis)) |
|
|
746 | 749 | if data_dc != None: |
|
|
747 | 750 | data_dc = numpy.reshape(data_dc, (1, -1, nHeis)) |
|
|
748 | 751 | |
|
|
749 | 752 | #If the buffer is empty then it takes the data value |
|
|
750 | 753 | if self.__buffer_spc == None: |
|
|
751 | 754 | self.__buffer_spc = data_spc |
|
|
752 | 755 | |
|
|
753 | 756 | if data_cspc == None: |
|
|
754 | 757 | self.__buffer_cspc = None |
|
|
755 | 758 | else: |
|
|
756 | 759 | self.__buffer_cspc += data_cspc |
|
|
757 | 760 | |
|
|
758 | 761 | if data_dc == None: |
|
|
759 | 762 | self.__buffer_dc = None |
|
|
760 | 763 | else: |
|
|
761 | 764 | self.__buffer_dc += data_dc |
|
|
762 | 765 | |
|
|
763 | 766 | self.__profIndex += 1 |
|
|
764 | 767 | return |
|
|
765 | 768 | |
|
|
766 | 769 | #If the buffer length is lower than n then stakcing the data value |
|
|
767 | 770 | if self.__profIndex < self.n: |
|
|
768 | 771 | self.__buffer_spc = numpy.vstack((self.__buffer_spc, data_spc)) |
|
|
769 | 772 | |
|
|
770 | 773 | if data_cspc != None: |
|
|
771 | 774 | self.__buffer_cspc = numpy.vstack((self.__buffer_cspc, data_cspc)) |
|
|
772 | 775 | |
|
|
773 | 776 | if data_dc != None: |
|
|
774 | 777 | self.__buffer_dc = numpy.vstack((self.__buffer_dc, data_dc)) |
|
|
775 | 778 | |
|
|
776 | 779 | self.__profIndex += 1 |
|
|
777 | 780 | return |
|
|
778 | 781 | |
|
|
779 | 782 | #If the buffer length is equal to n then replacing the last buffer value with the data value |
|
|
780 | 783 | self.__buffer_spc = numpy.roll(self.__buffer_spc, -1, axis=0) |
|
|
781 | 784 | self.__buffer_spc[self.n-1] = data_spc |
|
|
782 | 785 | |
|
|
783 | 786 | if data_cspc != None: |
|
|
784 | 787 | self.__buffer_cspc = numpy.roll(self.__buffer_cspc, -1, axis=0) |
|
|
785 | 788 | self.__buffer_cspc[self.n-1] = data_cspc |
|
|
786 | 789 | |
|
|
787 | 790 | if data_dc != None: |
|
|
788 | 791 | self.__buffer_dc = numpy.roll(self.__buffer_dc, -1, axis=0) |
|
|
789 | 792 | self.__buffer_dc[self.n-1] = data_dc |
|
|
790 | 793 | |
|
|
791 | 794 | self.__profIndex = self.n |
|
|
792 | 795 | return |
|
|
793 | 796 | |
|
|
794 | 797 | |
|
|
795 | 798 | def pushData(self): |
|
|
796 | 799 | """ |
|
|
797 | 800 | Return the sum of the last profiles and the profiles used in the sum. |
|
|
798 | 801 | |
|
|
799 | 802 | Affected: |
|
|
800 | 803 | |
|
|
801 | 804 | self.__profileIndex |
|
|
802 | 805 | |
|
|
803 | 806 | """ |
|
|
804 | 807 | data_spc = None |
|
|
805 | 808 | data_cspc = None |
|
|
806 | 809 | data_dc = None |
|
|
807 | 810 | |
|
|
808 | 811 | if not self.__withOverapping: |
|
|
809 | 812 | data_spc = self.__buffer_spc |
|
|
810 | 813 | data_cspc = self.__buffer_cspc |
|
|
811 | 814 | data_dc = self.__buffer_dc |
|
|
812 | 815 | |
|
|
813 | 816 | n = self.__profIndex |
|
|
814 | 817 | |
|
|
815 | 818 | self.__buffer_spc = 0 |
|
|
816 | 819 | self.__buffer_cspc = 0 |
|
|
817 | 820 | self.__buffer_dc = 0 |
|
|
818 | 821 | self.__profIndex = 0 |
|
|
819 | 822 | |
|
|
820 | 823 | return data_spc, data_cspc, data_dc, n |
|
|
821 | 824 | |
|
|
822 | 825 | #Integration with Overlapping |
|
|
823 | 826 | data_spc = numpy.sum(self.__buffer_spc, axis=0) |
|
|
824 | 827 | |
|
|
825 | 828 | if self.__buffer_cspc != None: |
|
|
826 | 829 | data_cspc = numpy.sum(self.__buffer_cspc, axis=0) |
|
|
827 | 830 | |
|
|
828 | 831 | if self.__buffer_dc != None: |
|
|
829 | 832 | data_dc = numpy.sum(self.__buffer_dc, axis=0) |
|
|
830 | 833 | |
|
|
831 | 834 | n = self.__profIndex |
|
|
832 | 835 | |
|
|
833 | 836 | return data_spc, data_cspc, data_dc, n |
|
|
834 | 837 | |
|
|
835 | 838 | def byProfiles(self, *args): |
|
|
836 | 839 | |
|
|
837 | 840 | self.__dataReady = False |
|
|
838 | 841 | avgdata_spc = None |
|
|
839 | 842 | avgdata_cspc = None |
|
|
840 | 843 | avgdata_dc = None |
|
|
841 | 844 | # n = None |
|
|
842 | 845 | |
|
|
843 | 846 | self.putData(*args) |
|
|
844 | 847 | |
|
|
845 | 848 | if self.__profIndex == self.n: |
|
|
846 | 849 | |
|
|
847 | 850 | avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData() |
|
|
848 | 851 | self.__dataReady = True |
|
|
849 | 852 | |
|
|
850 | 853 | return avgdata_spc, avgdata_cspc, avgdata_dc |
|
|
851 | 854 | |
|
|
852 | 855 | def byTime(self, datatime, *args): |
|
|
853 | 856 | |
|
|
854 | 857 | self.__dataReady = False |
|
|
855 | 858 | avgdata_spc = None |
|
|
856 | 859 | avgdata_cspc = None |
|
|
857 | 860 | avgdata_dc = None |
|
|
858 | 861 | n = None |
|
|
859 | 862 | |
|
|
860 | 863 | self.putData(*args) |
|
|
861 | 864 | |
|
|
862 | 865 | if (datatime - self.__initime) >= self.__integrationtime: |
|
|
863 | 866 | avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData() |
|
|
864 | 867 | self.n = n |
|
|
865 | 868 | self.__dataReady = True |
|
|
866 | 869 | |
|
|
867 | 870 | return avgdata_spc, avgdata_cspc, avgdata_dc |
|
|
868 | 871 | |
|
|
869 | 872 | def integrate(self, datatime, *args): |
|
|
870 | 873 | |
|
|
871 | 874 | if self.__initime == None: |
|
|
872 | 875 | self.__initime = datatime |
|
|
873 | 876 | |
|
|
874 | 877 | if self.__byTime: |
|
|
875 | 878 | avgdata_spc, avgdata_cspc, avgdata_dc = self.byTime(datatime, *args) |
|
|
876 | 879 | else: |
|
|
877 | 880 | avgdata_spc, avgdata_cspc, avgdata_dc = self.byProfiles(*args) |
|
|
878 | 881 | |
|
|
879 | 882 | self.__lastdatatime = datatime |
|
|
880 | 883 | |
|
|
881 | 884 | if avgdata_spc == None: |
|
|
882 | 885 | return None, None, None, None |
|
|
883 | 886 | |
|
|
884 | 887 | avgdatatime = self.__initime |
|
|
885 | 888 | try: |
|
|
886 | 889 | self.__timeInterval = (self.__lastdatatime - self.__initime)/(self.n - 1) |
|
|
887 | 890 | except: |
|
|
888 | 891 | self.__timeInterval = self.__lastdatatime - self.__initime |
|
|
889 | 892 | |
|
|
890 | 893 | deltatime = datatime -self.__lastdatatime |
|
|
891 | 894 | |
|
|
892 | 895 | if not self.__withOverapping: |
|
|
893 | 896 | self.__initime = datatime |
|
|
894 | 897 | else: |
|
|
895 | 898 | self.__initime += deltatime |
|
|
896 | 899 | |
|
|
897 | 900 | return avgdatatime, avgdata_spc, avgdata_cspc, avgdata_dc |
|
|
898 | 901 | |
|
|
899 | 902 | def run(self, dataOut, n=None, timeInterval=None, overlapping=False): |
|
|
900 | 903 | |
|
|
901 | 904 | if n==1: |
|
|
902 | 905 | dataOut.flagNoData = False |
|
|
903 | 906 | return |
|
|
904 | 907 | |
|
|
905 | 908 | if not self.isConfig: |
|
|
906 | 909 | self.setup(n, timeInterval, overlapping) |
|
|
907 | 910 | self.isConfig = True |
|
|
908 | 911 | |
|
|
909 | 912 | avgdatatime, avgdata_spc, avgdata_cspc, avgdata_dc = self.integrate(dataOut.utctime, |
|
|
910 | 913 | dataOut.data_spc, |
|
|
911 | 914 | dataOut.data_cspc, |
|
|
912 | 915 | dataOut.data_dc) |
|
|
913 | 916 | |
|
|
914 | 917 | # dataOut.timeInterval *= n |
|
|
915 | 918 | dataOut.flagNoData = True |
|
|
916 | 919 | |
|
|
917 | 920 | if self.__dataReady: |
|
|
918 | 921 | |
|
|
919 | 922 | dataOut.data_spc = avgdata_spc |
|
|
920 | 923 | dataOut.data_cspc = avgdata_cspc |
|
|
921 | 924 | dataOut.data_dc = avgdata_dc |
|
|
922 | 925 | |
|
|
923 | 926 | dataOut.nIncohInt *= self.n |
|
|
924 | 927 | dataOut.utctime = avgdatatime |
|
|
925 | 928 | #dataOut.timeInterval = dataOut.ippSeconds * dataOut.nCohInt * dataOut.nIncohInt * dataOut.nFFTPoints |
|
|
926 | 929 | dataOut.timeInterval = self.__timeInterval*self.n |
|
|
927 | 930 | dataOut.flagNoData = False |
| @@ -1,751 +1,754 | |||
|
|
1 | 1 | import numpy |
|
|
2 | 2 | |
|
|
3 | 3 | from jroproc_base import ProcessingUnit, Operation |
|
|
4 | 4 | from model.data.jrodata import Voltage |
|
|
5 | 5 | |
|
|
6 | 6 | class VoltageProc(ProcessingUnit): |
|
|
7 | 7 | |
|
|
8 | 8 | |
|
|
9 | 9 | def __init__(self): |
|
|
10 | 10 | |
|
|
11 | 11 | ProcessingUnit.__init__(self) |
|
|
12 | 12 | |
|
|
13 | 13 | # self.objectDict = {} |
|
|
14 | 14 | self.dataOut = Voltage() |
|
|
15 | 15 | self.flip = 1 |
|
|
16 | 16 | |
|
|
17 | 17 | def run(self): |
|
|
18 | 18 | if self.dataIn.type == 'AMISR': |
|
|
19 | 19 | self.__updateObjFromAmisrInput() |
|
|
20 | 20 | |
|
|
21 | 21 | if self.dataIn.type == 'Voltage': |
|
|
22 | 22 | self.dataOut.copy(self.dataIn) |
|
|
23 | 23 | |
|
|
24 | 24 | # self.dataOut.copy(self.dataIn) |
|
|
25 | 25 | |
|
|
26 | 26 | def __updateObjFromAmisrInput(self): |
|
|
27 | 27 | |
|
|
28 | 28 | self.dataOut.timeZone = self.dataIn.timeZone |
|
|
29 | 29 | self.dataOut.dstFlag = self.dataIn.dstFlag |
|
|
30 | 30 | self.dataOut.errorCount = self.dataIn.errorCount |
|
|
31 | 31 | self.dataOut.useLocalTime = self.dataIn.useLocalTime |
|
|
32 | 32 | |
|
|
33 | 33 | self.dataOut.flagNoData = self.dataIn.flagNoData |
|
|
34 | 34 | self.dataOut.data = self.dataIn.data |
|
|
35 | 35 | self.dataOut.utctime = self.dataIn.utctime |
|
|
36 | 36 | self.dataOut.channelList = self.dataIn.channelList |
|
|
37 | 37 | self.dataOut.timeInterval = self.dataIn.timeInterval |
|
|
38 | 38 | self.dataOut.heightList = self.dataIn.heightList |
|
|
39 | 39 | self.dataOut.nProfiles = self.dataIn.nProfiles |
|
|
40 | 40 | |
|
|
41 | 41 | self.dataOut.nCohInt = self.dataIn.nCohInt |
|
|
42 | 42 | self.dataOut.ippSeconds = self.dataIn.ippSeconds |
|
|
43 | 43 | self.dataOut.frequency = self.dataIn.frequency |
|
|
44 | ||
|
|
45 | self.dataOut.azimuth = self.dataIn.azimuth | |
|
|
46 | self.dataOut.zenith = self.dataIn.zenith | |
|
|
44 | 47 | # |
|
|
45 | 48 | # pass# |
|
|
46 | 49 | # |
|
|
47 | 50 | # def init(self): |
|
|
48 | 51 | # |
|
|
49 | 52 | # |
|
|
50 | 53 | # if self.dataIn.type == 'AMISR': |
|
|
51 | 54 | # self.__updateObjFromAmisrInput() |
|
|
52 | 55 | # |
|
|
53 | 56 | # if self.dataIn.type == 'Voltage': |
|
|
54 | 57 | # self.dataOut.copy(self.dataIn) |
|
|
55 | 58 | # # No necesita copiar en cada init() los atributos de dataIn |
|
|
56 | 59 | # # la copia deberia hacerse por cada nuevo bloque de datos |
|
|
57 | 60 | |
|
|
58 | 61 | def selectChannels(self, channelList): |
|
|
59 | 62 | |
|
|
60 | 63 | channelIndexList = [] |
|
|
61 | 64 | |
|
|
62 | 65 | for channel in channelList: |
|
|
63 | 66 | index = self.dataOut.channelList.index(channel) |
|
|
64 | 67 | channelIndexList.append(index) |
|
|
65 | 68 | |
|
|
66 | 69 | self.selectChannelsByIndex(channelIndexList) |
|
|
67 | 70 | |
|
|
68 | 71 | def selectChannelsByIndex(self, channelIndexList): |
|
|
69 | 72 | """ |
|
|
70 | 73 | Selecciona un bloque de datos en base a canales segun el channelIndexList |
|
|
71 | 74 | |
|
|
72 | 75 | Input: |
|
|
73 | 76 | channelIndexList : lista sencilla de canales a seleccionar por ej. [2,3,7] |
|
|
74 | 77 | |
|
|
75 | 78 | Affected: |
|
|
76 | 79 | self.dataOut.data |
|
|
77 | 80 | self.dataOut.channelIndexList |
|
|
78 | 81 | self.dataOut.nChannels |
|
|
79 | 82 | self.dataOut.m_ProcessingHeader.totalSpectra |
|
|
80 | 83 | self.dataOut.systemHeaderObj.numChannels |
|
|
81 | 84 | self.dataOut.m_ProcessingHeader.blockSize |
|
|
82 | 85 | |
|
|
83 | 86 | Return: |
|
|
84 | 87 | None |
|
|
85 | 88 | """ |
|
|
86 | 89 | |
|
|
87 | 90 | for channelIndex in channelIndexList: |
|
|
88 | 91 | if channelIndex not in self.dataOut.channelIndexList: |
|
|
89 | 92 | print channelIndexList |
|
|
90 | 93 | raise ValueError, "The value %d in channelIndexList is not valid" %channelIndex |
|
|
91 | 94 | |
|
|
92 | 95 | # nChannels = len(channelIndexList) |
|
|
93 | 96 | |
|
|
94 | 97 | data = self.dataOut.data[channelIndexList,:] |
|
|
95 | 98 | |
|
|
96 | 99 | self.dataOut.data = data |
|
|
97 | 100 | self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList] |
|
|
98 | 101 | # self.dataOut.nChannels = nChannels |
|
|
99 | 102 | |
|
|
100 | 103 | return 1 |
|
|
101 | 104 | |
|
|
102 | 105 | def selectHeights(self, minHei=None, maxHei=None): |
|
|
103 | 106 | """ |
|
|
104 | 107 | Selecciona un bloque de datos en base a un grupo de valores de alturas segun el rango |
|
|
105 | 108 | minHei <= height <= maxHei |
|
|
106 | 109 | |
|
|
107 | 110 | Input: |
|
|
108 | 111 | minHei : valor minimo de altura a considerar |
|
|
109 | 112 | maxHei : valor maximo de altura a considerar |
|
|
110 | 113 | |
|
|
111 | 114 | Affected: |
|
|
112 | 115 | Indirectamente son cambiados varios valores a travez del metodo selectHeightsByIndex |
|
|
113 | 116 | |
|
|
114 | 117 | Return: |
|
|
115 | 118 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 |
|
|
116 | 119 | """ |
|
|
117 | 120 | |
|
|
118 | 121 | if minHei == None: |
|
|
119 | 122 | minHei = self.dataOut.heightList[0] |
|
|
120 | 123 | |
|
|
121 | 124 | if maxHei == None: |
|
|
122 | 125 | maxHei = self.dataOut.heightList[-1] |
|
|
123 | 126 | |
|
|
124 | 127 | if (minHei < self.dataOut.heightList[0]) or (minHei > maxHei): |
|
|
125 | 128 | raise ValueError, "some value in (%d,%d) is not valid" % (minHei, maxHei) |
|
|
126 | 129 | |
|
|
127 | 130 | |
|
|
128 | 131 | if (maxHei > self.dataOut.heightList[-1]): |
|
|
129 | 132 | maxHei = self.dataOut.heightList[-1] |
|
|
130 | 133 | # raise ValueError, "some value in (%d,%d) is not valid" % (minHei, maxHei) |
|
|
131 | 134 | |
|
|
132 | 135 | minIndex = 0 |
|
|
133 | 136 | maxIndex = 0 |
|
|
134 | 137 | heights = self.dataOut.heightList |
|
|
135 | 138 | |
|
|
136 | 139 | inda = numpy.where(heights >= minHei) |
|
|
137 | 140 | indb = numpy.where(heights <= maxHei) |
|
|
138 | 141 | |
|
|
139 | 142 | try: |
|
|
140 | 143 | minIndex = inda[0][0] |
|
|
141 | 144 | except: |
|
|
142 | 145 | minIndex = 0 |
|
|
143 | 146 | |
|
|
144 | 147 | try: |
|
|
145 | 148 | maxIndex = indb[0][-1] |
|
|
146 | 149 | except: |
|
|
147 | 150 | maxIndex = len(heights) |
|
|
148 | 151 | |
|
|
149 | 152 | self.selectHeightsByIndex(minIndex, maxIndex) |
|
|
150 | 153 | |
|
|
151 | 154 | return 1 |
|
|
152 | 155 | |
|
|
153 | 156 | |
|
|
154 | 157 | def selectHeightsByIndex(self, minIndex, maxIndex): |
|
|
155 | 158 | """ |
|
|
156 | 159 | Selecciona un bloque de datos en base a un grupo indices de alturas segun el rango |
|
|
157 | 160 | minIndex <= index <= maxIndex |
|
|
158 | 161 | |
|
|
159 | 162 | Input: |
|
|
160 | 163 | minIndex : valor de indice minimo de altura a considerar |
|
|
161 | 164 | maxIndex : valor de indice maximo de altura a considerar |
|
|
162 | 165 | |
|
|
163 | 166 | Affected: |
|
|
164 | 167 | self.dataOut.data |
|
|
165 | 168 | self.dataOut.heightList |
|
|
166 | 169 | |
|
|
167 | 170 | Return: |
|
|
168 | 171 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 |
|
|
169 | 172 | """ |
|
|
170 | 173 | |
|
|
171 | 174 | if (minIndex < 0) or (minIndex > maxIndex): |
|
|
172 | 175 | raise ValueError, "some value in (%d,%d) is not valid" % (minIndex, maxIndex) |
|
|
173 | 176 | |
|
|
174 | 177 | if (maxIndex >= self.dataOut.nHeights): |
|
|
175 | 178 | maxIndex = self.dataOut.nHeights-1 |
|
|
176 | 179 | # raise ValueError, "some value in (%d,%d) is not valid" % (minIndex, maxIndex) |
|
|
177 | 180 | |
|
|
178 | 181 | # nHeights = maxIndex - minIndex + 1 |
|
|
179 | 182 | |
|
|
180 | 183 | #voltage |
|
|
181 | 184 | data = self.dataOut.data[:,minIndex:maxIndex+1] |
|
|
182 | 185 | |
|
|
183 | 186 | # firstHeight = self.dataOut.heightList[minIndex] |
|
|
184 | 187 | |
|
|
185 | 188 | self.dataOut.data = data |
|
|
186 | 189 | self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex+1] |
|
|
187 | 190 | |
|
|
188 | 191 | return 1 |
|
|
189 | 192 | |
|
|
190 | 193 | |
|
|
191 | 194 | def filterByHeights(self, window, axis=1): |
|
|
192 | 195 | deltaHeight = self.dataOut.heightList[1] - self.dataOut.heightList[0] |
|
|
193 | 196 | |
|
|
194 | 197 | if window == None: |
|
|
195 | 198 | window = (self.dataOut.radarControllerHeaderObj.txA/self.dataOut.radarControllerHeaderObj.nBaud) / deltaHeight |
|
|
196 | 199 | |
|
|
197 | 200 | newdelta = deltaHeight * window |
|
|
198 | 201 | r = self.dataOut.data.shape[axis] % window |
|
|
199 | 202 | if axis == 1: |
|
|
200 | 203 | buffer = self.dataOut.data[:,0:self.dataOut.data.shape[axis]-r] |
|
|
201 | 204 | buffer = buffer.reshape(self.dataOut.data.shape[0],self.dataOut.data.shape[axis]/window,window) |
|
|
202 | 205 | buffer = numpy.sum(buffer,axis+1) |
|
|
203 | 206 | |
|
|
204 | 207 | elif axis == 2: |
|
|
205 | 208 | buffer = self.dataOut.data[:, :, 0:self.dataOut.data.shape[axis]-r] |
|
|
206 | 209 | buffer = buffer.reshape(self.dataOut.data.shape[0],self.dataOut.data.shape[1],self.dataOut.data.shape[axis]/window,window) |
|
|
207 | 210 | buffer = numpy.sum(buffer,axis+1) |
|
|
208 | 211 | |
|
|
209 | 212 | else: |
|
|
210 | 213 | raise ValueError, "axis value should be 1 or 2, the input value %d is not valid" % (axis) |
|
|
211 | 214 | |
|
|
212 | 215 | self.dataOut.data = buffer.copy() |
|
|
213 | 216 | self.dataOut.heightList = numpy.arange(self.dataOut.heightList[0],newdelta*(self.dataOut.nHeights-r)/window,newdelta) |
|
|
214 | 217 | self.dataOut.windowOfFilter = window |
|
|
215 | 218 | |
|
|
216 | 219 | return 1 |
|
|
217 | 220 | |
|
|
218 | 221 | def deFlip(self): |
|
|
219 | 222 | self.dataOut.data *= self.flip |
|
|
220 | 223 | self.flip *= -1. |
|
|
221 | 224 | |
|
|
222 | 225 | def setRadarFrequency(self, frequency=None): |
|
|
223 | 226 | if frequency != None: |
|
|
224 | 227 | self.dataOut.frequency = frequency |
|
|
225 | 228 | |
|
|
226 | 229 | return 1 |
|
|
227 | 230 | |
|
|
228 | 231 | class CohInt(Operation): |
|
|
229 | 232 | |
|
|
230 | 233 | isConfig = False |
|
|
231 | 234 | |
|
|
232 | 235 | __profIndex = 0 |
|
|
233 | 236 | __withOverapping = False |
|
|
234 | 237 | |
|
|
235 | 238 | __byTime = False |
|
|
236 | 239 | __initime = None |
|
|
237 | 240 | __lastdatatime = None |
|
|
238 | 241 | __integrationtime = None |
|
|
239 | 242 | |
|
|
240 | 243 | __buffer = None |
|
|
241 | 244 | |
|
|
242 | 245 | __dataReady = False |
|
|
243 | 246 | |
|
|
244 | 247 | n = None |
|
|
245 | 248 | |
|
|
246 | 249 | |
|
|
247 | 250 | def __init__(self): |
|
|
248 | 251 | |
|
|
249 | 252 | Operation.__init__(self) |
|
|
250 | 253 | |
|
|
251 | 254 | # self.isConfig = False |
|
|
252 | 255 | |
|
|
253 | 256 | def setup(self, n=None, timeInterval=None, overlapping=False, byblock=False): |
|
|
254 | 257 | """ |
|
|
255 | 258 | Set the parameters of the integration class. |
|
|
256 | 259 | |
|
|
257 | 260 | Inputs: |
|
|
258 | 261 | |
|
|
259 | 262 | n : Number of coherent integrations |
|
|
260 | 263 | timeInterval : Time of integration. If the parameter "n" is selected this one does not work |
|
|
261 | 264 | overlapping : |
|
|
262 | 265 | |
|
|
263 | 266 | """ |
|
|
264 | 267 | |
|
|
265 | 268 | self.__initime = None |
|
|
266 | 269 | self.__lastdatatime = 0 |
|
|
267 | 270 | self.__buffer = None |
|
|
268 | 271 | self.__dataReady = False |
|
|
269 | 272 | self.byblock = byblock |
|
|
270 | 273 | |
|
|
271 | 274 | if n == None and timeInterval == None: |
|
|
272 | 275 | raise ValueError, "n or timeInterval should be specified ..." |
|
|
273 | 276 | |
|
|
274 | 277 | if n != None: |
|
|
275 | 278 | self.n = n |
|
|
276 | 279 | self.__byTime = False |
|
|
277 | 280 | else: |
|
|
278 | 281 | self.__integrationtime = timeInterval * 60. #if (type(timeInterval)!=integer) -> change this line |
|
|
279 | 282 | self.n = 9999 |
|
|
280 | 283 | self.__byTime = True |
|
|
281 | 284 | |
|
|
282 | 285 | if overlapping: |
|
|
283 | 286 | self.__withOverapping = True |
|
|
284 | 287 | self.__buffer = None |
|
|
285 | 288 | else: |
|
|
286 | 289 | self.__withOverapping = False |
|
|
287 | 290 | self.__buffer = 0 |
|
|
288 | 291 | |
|
|
289 | 292 | self.__profIndex = 0 |
|
|
290 | 293 | |
|
|
291 | 294 | def putData(self, data): |
|
|
292 | 295 | |
|
|
293 | 296 | """ |
|
|
294 | 297 | Add a profile to the __buffer and increase in one the __profileIndex |
|
|
295 | 298 | |
|
|
296 | 299 | """ |
|
|
297 | 300 | |
|
|
298 | 301 | if not self.__withOverapping: |
|
|
299 | 302 | self.__buffer += data.copy() |
|
|
300 | 303 | self.__profIndex += 1 |
|
|
301 | 304 | return |
|
|
302 | 305 | |
|
|
303 | 306 | #Overlapping data |
|
|
304 | 307 | nChannels, nHeis = data.shape |
|
|
305 | 308 | data = numpy.reshape(data, (1, nChannels, nHeis)) |
|
|
306 | 309 | |
|
|
307 | 310 | #If the buffer is empty then it takes the data value |
|
|
308 | 311 | if self.__buffer == None: |
|
|
309 | 312 | self.__buffer = data |
|
|
310 | 313 | self.__profIndex += 1 |
|
|
311 | 314 | return |
|
|
312 | 315 | |
|
|
313 | 316 | #If the buffer length is lower than n then stakcing the data value |
|
|
314 | 317 | if self.__profIndex < self.n: |
|
|
315 | 318 | self.__buffer = numpy.vstack((self.__buffer, data)) |
|
|
316 | 319 | self.__profIndex += 1 |
|
|
317 | 320 | return |
|
|
318 | 321 | |
|
|
319 | 322 | #If the buffer length is equal to n then replacing the last buffer value with the data value |
|
|
320 | 323 | self.__buffer = numpy.roll(self.__buffer, -1, axis=0) |
|
|
321 | 324 | self.__buffer[self.n-1] = data |
|
|
322 | 325 | self.__profIndex = self.n |
|
|
323 | 326 | return |
|
|
324 | 327 | |
|
|
325 | 328 | |
|
|
326 | 329 | def pushData(self): |
|
|
327 | 330 | """ |
|
|
328 | 331 | Return the sum of the last profiles and the profiles used in the sum. |
|
|
329 | 332 | |
|
|
330 | 333 | Affected: |
|
|
331 | 334 | |
|
|
332 | 335 | self.__profileIndex |
|
|
333 | 336 | |
|
|
334 | 337 | """ |
|
|
335 | 338 | |
|
|
336 | 339 | if not self.__withOverapping: |
|
|
337 | 340 | data = self.__buffer |
|
|
338 | 341 | n = self.__profIndex |
|
|
339 | 342 | |
|
|
340 | 343 | self.__buffer = 0 |
|
|
341 | 344 | self.__profIndex = 0 |
|
|
342 | 345 | |
|
|
343 | 346 | return data, n |
|
|
344 | 347 | |
|
|
345 | 348 | #Integration with Overlapping |
|
|
346 | 349 | data = numpy.sum(self.__buffer, axis=0) |
|
|
347 | 350 | n = self.__profIndex |
|
|
348 | 351 | |
|
|
349 | 352 | return data, n |
|
|
350 | 353 | |
|
|
351 | 354 | def byProfiles(self, data): |
|
|
352 | 355 | |
|
|
353 | 356 | self.__dataReady = False |
|
|
354 | 357 | avgdata = None |
|
|
355 | 358 | # n = None |
|
|
356 | 359 | |
|
|
357 | 360 | self.putData(data) |
|
|
358 | 361 | |
|
|
359 | 362 | if self.__profIndex == self.n: |
|
|
360 | 363 | |
|
|
361 | 364 | avgdata, n = self.pushData() |
|
|
362 | 365 | self.__dataReady = True |
|
|
363 | 366 | |
|
|
364 | 367 | return avgdata |
|
|
365 | 368 | |
|
|
366 | 369 | def byTime(self, data, datatime): |
|
|
367 | 370 | |
|
|
368 | 371 | self.__dataReady = False |
|
|
369 | 372 | avgdata = None |
|
|
370 | 373 | n = None |
|
|
371 | 374 | |
|
|
372 | 375 | self.putData(data) |
|
|
373 | 376 | |
|
|
374 | 377 | if (datatime - self.__initime) >= self.__integrationtime: |
|
|
375 | 378 | avgdata, n = self.pushData() |
|
|
376 | 379 | self.n = n |
|
|
377 | 380 | self.__dataReady = True |
|
|
378 | 381 | |
|
|
379 | 382 | return avgdata |
|
|
380 | 383 | |
|
|
381 | 384 | def integrate(self, data, datatime=None): |
|
|
382 | 385 | |
|
|
383 | 386 | if self.__initime == None: |
|
|
384 | 387 | self.__initime = datatime |
|
|
385 | 388 | |
|
|
386 | 389 | if self.__byTime: |
|
|
387 | 390 | avgdata = self.byTime(data, datatime) |
|
|
388 | 391 | else: |
|
|
389 | 392 | avgdata = self.byProfiles(data) |
|
|
390 | 393 | |
|
|
391 | 394 | |
|
|
392 | 395 | self.__lastdatatime = datatime |
|
|
393 | 396 | |
|
|
394 | 397 | if avgdata == None: |
|
|
395 | 398 | return None, None |
|
|
396 | 399 | |
|
|
397 | 400 | avgdatatime = self.__initime |
|
|
398 | 401 | |
|
|
399 | 402 | deltatime = datatime -self.__lastdatatime |
|
|
400 | 403 | |
|
|
401 | 404 | if not self.__withOverapping: |
|
|
402 | 405 | self.__initime = datatime |
|
|
403 | 406 | else: |
|
|
404 | 407 | self.__initime += deltatime |
|
|
405 | 408 | |
|
|
406 | 409 | return avgdata, avgdatatime |
|
|
407 | 410 | |
|
|
408 | 411 | def integrateByBlock(self, dataOut): |
|
|
409 | 412 | times = int(dataOut.data.shape[1]/self.n) |
|
|
410 | 413 | avgdata = numpy.zeros((dataOut.nChannels, times, dataOut.nHeights), dtype=numpy.complex) |
|
|
411 | 414 | |
|
|
412 | 415 | id_min = 0 |
|
|
413 | 416 | id_max = self.n |
|
|
414 | 417 | |
|
|
415 | 418 | for i in range(times): |
|
|
416 | 419 | junk = dataOut.data[:,id_min:id_max,:] |
|
|
417 | 420 | avgdata[:,i,:] = junk.sum(axis=1) |
|
|
418 | 421 | id_min += self.n |
|
|
419 | 422 | id_max += self.n |
|
|
420 | 423 | |
|
|
421 | 424 | timeInterval = dataOut.ippSeconds*self.n |
|
|
422 | 425 | avgdatatime = (times - 1) * timeInterval + dataOut.utctime |
|
|
423 | 426 | self.__dataReady = True |
|
|
424 | 427 | return avgdata, avgdatatime |
|
|
425 | 428 | |
|
|
426 | 429 | def run(self, dataOut, **kwargs): |
|
|
427 | 430 | |
|
|
428 | 431 | if not self.isConfig: |
|
|
429 | 432 | self.setup(**kwargs) |
|
|
430 | 433 | self.isConfig = True |
|
|
431 | 434 | |
|
|
432 | 435 | if self.byblock: |
|
|
433 | 436 | avgdata, avgdatatime = self.integrateByBlock(dataOut) |
|
|
434 | 437 | else: |
|
|
435 | 438 | avgdata, avgdatatime = self.integrate(dataOut.data, dataOut.utctime) |
|
|
436 | 439 | |
|
|
437 | 440 | # dataOut.timeInterval *= n |
|
|
438 | 441 | dataOut.flagNoData = True |
|
|
439 | 442 | |
|
|
440 | 443 | if self.__dataReady: |
|
|
441 | 444 | dataOut.data = avgdata |
|
|
442 | 445 | dataOut.nCohInt *= self.n |
|
|
443 | 446 | dataOut.utctime = avgdatatime |
|
|
444 | 447 | dataOut.timeInterval = dataOut.ippSeconds * dataOut.nCohInt |
|
|
445 | 448 | dataOut.flagNoData = False |
|
|
446 | 449 | |
|
|
447 | 450 | class Decoder(Operation): |
|
|
448 | 451 | |
|
|
449 | 452 | isConfig = False |
|
|
450 | 453 | __profIndex = 0 |
|
|
451 | 454 | |
|
|
452 | 455 | code = None |
|
|
453 | 456 | |
|
|
454 | 457 | nCode = None |
|
|
455 | 458 | nBaud = None |
|
|
456 | 459 | |
|
|
457 | 460 | |
|
|
458 | 461 | def __init__(self): |
|
|
459 | 462 | |
|
|
460 | 463 | Operation.__init__(self) |
|
|
461 | 464 | |
|
|
462 | 465 | self.times = None |
|
|
463 | 466 | self.osamp = None |
|
|
464 | 467 | self.__setValues = False |
|
|
465 | 468 | # self.isConfig = False |
|
|
466 | 469 | |
|
|
467 | 470 | def setup(self, code, shape, times, osamp): |
|
|
468 | 471 | |
|
|
469 | 472 | self.__profIndex = 0 |
|
|
470 | 473 | |
|
|
471 | 474 | self.code = code |
|
|
472 | 475 | |
|
|
473 | 476 | self.nCode = len(code) |
|
|
474 | 477 | self.nBaud = len(code[0]) |
|
|
475 | 478 | |
|
|
476 | 479 | if times != None: |
|
|
477 | 480 | self.times = times |
|
|
478 | 481 | |
|
|
479 | 482 | if ((osamp != None) and (osamp >1)): |
|
|
480 | 483 | self.osamp = osamp |
|
|
481 | 484 | self.code = numpy.repeat(code, repeats=self.osamp,axis=1) |
|
|
482 | 485 | self.nBaud = self.nBaud*self.osamp |
|
|
483 | 486 | |
|
|
484 | 487 | if len(shape) == 2: |
|
|
485 | 488 | self.__nChannels, self.__nHeis = shape |
|
|
486 | 489 | |
|
|
487 | 490 | __codeBuffer = numpy.zeros((self.nCode, self.__nHeis), dtype=numpy.complex) |
|
|
488 | 491 | |
|
|
489 | 492 | __codeBuffer[:,0:self.nBaud] = self.code |
|
|
490 | 493 | |
|
|
491 | 494 | self.fft_code = numpy.conj(numpy.fft.fft(__codeBuffer, axis=1)) |
|
|
492 | 495 | |
|
|
493 | 496 | self.ndatadec = self.__nHeis - self.nBaud + 1 |
|
|
494 | 497 | |
|
|
495 | 498 | self.datadecTime = numpy.zeros((self.__nChannels, self.ndatadec), dtype=numpy.complex) |
|
|
496 | 499 | else: |
|
|
497 | 500 | self.__nChannels, self.__nProfiles, self.__nHeis = shape |
|
|
498 | 501 | |
|
|
499 | 502 | self.ndatadec = self.__nHeis - self.nBaud + 1 |
|
|
500 | 503 | |
|
|
501 | 504 | self.datadecTime = numpy.zeros((self.__nChannels, self.__nProfiles, self.ndatadec), dtype=numpy.complex) |
|
|
502 | 505 | |
|
|
503 | 506 | |
|
|
504 | 507 | |
|
|
505 | 508 | def convolutionInFreq(self, data): |
|
|
506 | 509 | |
|
|
507 | 510 | fft_code = self.fft_code[self.__profIndex].reshape(1,-1) |
|
|
508 | 511 | |
|
|
509 | 512 | fft_data = numpy.fft.fft(data, axis=1) |
|
|
510 | 513 | |
|
|
511 | 514 | conv = fft_data*fft_code |
|
|
512 | 515 | |
|
|
513 | 516 | data = numpy.fft.ifft(conv,axis=1) |
|
|
514 | 517 | |
|
|
515 | 518 | datadec = data[:,:-self.nBaud+1] |
|
|
516 | 519 | |
|
|
517 | 520 | return datadec |
|
|
518 | 521 | |
|
|
519 | 522 | def convolutionInFreqOpt(self, data): |
|
|
520 | 523 | |
|
|
521 | 524 | fft_code = self.fft_code[self.__profIndex].reshape(1,-1) |
|
|
522 | 525 | |
|
|
523 | 526 | data = cfunctions.decoder(fft_code, data) |
|
|
524 | 527 | |
|
|
525 | 528 | datadec = data[:,:-self.nBaud+1] |
|
|
526 | 529 | |
|
|
527 | 530 | return datadec |
|
|
528 | 531 | |
|
|
529 | 532 | def convolutionInTime(self, data): |
|
|
530 | 533 | |
|
|
531 | 534 | code = self.code[self.__profIndex] |
|
|
532 | 535 | |
|
|
533 | 536 | for i in range(self.__nChannels): |
|
|
534 | 537 | self.datadecTime[i,:] = numpy.correlate(data[i,:], code, mode='valid') |
|
|
535 | 538 | |
|
|
536 | 539 | return self.datadecTime |
|
|
537 | 540 | |
|
|
538 | 541 | def convolutionByBlockInTime(self, data): |
|
|
539 | 542 | junk = numpy.lib.stride_tricks.as_strided(self.code, (self.times, self.code.size), (0, self.code.itemsize)) |
|
|
540 | 543 | junk = junk.flatten() |
|
|
541 | 544 | code_block = numpy.reshape(junk, (self.nCode*self.times,self.nBaud)) |
|
|
542 | 545 | |
|
|
543 | 546 | for i in range(self.__nChannels): |
|
|
544 | 547 | for j in range(self.__nProfiles): |
|
|
545 | 548 | self.datadecTime[i,j,:] = numpy.correlate(data[i,j,:], code_block[j,:], mode='valid') |
|
|
546 | 549 | |
|
|
547 | 550 | return self.datadecTime |
|
|
548 | 551 | |
|
|
549 | 552 | def run(self, dataOut, code=None, nCode=None, nBaud=None, mode = 0, times=None, osamp=None): |
|
|
550 | 553 | |
|
|
551 | 554 | if code == None: |
|
|
552 | 555 | code = dataOut.code |
|
|
553 | 556 | else: |
|
|
554 | 557 | code = numpy.array(code).reshape(nCode,nBaud) |
|
|
555 | 558 | |
|
|
556 | 559 | |
|
|
557 | 560 | |
|
|
558 | 561 | if not self.isConfig: |
|
|
559 | 562 | |
|
|
560 | 563 | self.setup(code, dataOut.data.shape, times, osamp) |
|
|
561 | 564 | |
|
|
562 | 565 | dataOut.code = code |
|
|
563 | 566 | dataOut.nCode = nCode |
|
|
564 | 567 | dataOut.nBaud = nBaud |
|
|
565 | 568 | dataOut.radarControllerHeaderObj.code = code |
|
|
566 | 569 | dataOut.radarControllerHeaderObj.nCode = nCode |
|
|
567 | 570 | dataOut.radarControllerHeaderObj.nBaud = nBaud |
|
|
568 | 571 | |
|
|
569 | 572 | self.isConfig = True |
|
|
570 | 573 | |
|
|
571 | 574 | if mode == 0: |
|
|
572 | 575 | datadec = self.convolutionInTime(dataOut.data) |
|
|
573 | 576 | |
|
|
574 | 577 | if mode == 1: |
|
|
575 | 578 | datadec = self.convolutionInFreq(dataOut.data) |
|
|
576 | 579 | |
|
|
577 | 580 | if mode == 2: |
|
|
578 | 581 | datadec = self.convolutionInFreqOpt(dataOut.data) |
|
|
579 | 582 | |
|
|
580 | 583 | if mode == 3: |
|
|
581 | 584 | datadec = self.convolutionByBlockInTime(dataOut.data) |
|
|
582 | 585 | |
|
|
583 | 586 | if not(self.__setValues): |
|
|
584 | 587 | dataOut.code = self.code |
|
|
585 | 588 | dataOut.nCode = self.nCode |
|
|
586 | 589 | dataOut.nBaud = self.nBaud |
|
|
587 | 590 | dataOut.radarControllerHeaderObj.code = self.code |
|
|
588 | 591 | dataOut.radarControllerHeaderObj.nCode = self.nCode |
|
|
589 | 592 | dataOut.radarControllerHeaderObj.nBaud = self.nBaud |
|
|
590 | 593 | self.__setValues = True |
|
|
591 | 594 | |
|
|
592 | 595 | dataOut.data = datadec |
|
|
593 | 596 | |
|
|
594 | 597 | dataOut.heightList = dataOut.heightList[0:self.ndatadec] |
|
|
595 | 598 | |
|
|
596 | 599 | dataOut.flagDecodeData = True #asumo q la data no esta decodificada |
|
|
597 | 600 | |
|
|
598 | 601 | if self.__profIndex == self.nCode-1: |
|
|
599 | 602 | self.__profIndex = 0 |
|
|
600 | 603 | return 1 |
|
|
601 | 604 | |
|
|
602 | 605 | self.__profIndex += 1 |
|
|
603 | 606 | |
|
|
604 | 607 | return 1 |
|
|
605 | 608 | # dataOut.flagDeflipData = True #asumo q la data no esta sin flip |
|
|
606 | 609 | |
|
|
607 | 610 | |
|
|
608 | 611 | class ProfileConcat(Operation): |
|
|
609 | 612 | |
|
|
610 | 613 | isConfig = False |
|
|
611 | 614 | buffer = None |
|
|
612 | 615 | |
|
|
613 | 616 | def __init__(self): |
|
|
614 | 617 | |
|
|
615 | 618 | Operation.__init__(self) |
|
|
616 | 619 | self.profileIndex = 0 |
|
|
617 | 620 | |
|
|
618 | 621 | def reset(self): |
|
|
619 | 622 | self.buffer = numpy.zeros_like(self.buffer) |
|
|
620 | 623 | self.start_index = 0 |
|
|
621 | 624 | self.times = 1 |
|
|
622 | 625 | |
|
|
623 | 626 | def setup(self, data, m, n=1): |
|
|
624 | 627 | self.buffer = numpy.zeros((data.shape[0],data.shape[1]*m),dtype=type(data[0,0])) |
|
|
625 | 628 | self.profiles = data.shape[1] |
|
|
626 | 629 | self.start_index = 0 |
|
|
627 | 630 | self.times = 1 |
|
|
628 | 631 | |
|
|
629 | 632 | def concat(self, data): |
|
|
630 | 633 | |
|
|
631 | 634 | self.buffer[:,self.start_index:self.profiles*self.times] = data.copy() |
|
|
632 | 635 | self.start_index = self.start_index + self.profiles |
|
|
633 | 636 | |
|
|
634 | 637 | def run(self, dataOut, m): |
|
|
635 | 638 | |
|
|
636 | 639 | dataOut.flagNoData = True |
|
|
637 | 640 | |
|
|
638 | 641 | if not self.isConfig: |
|
|
639 | 642 | self.setup(dataOut.data, m, 1) |
|
|
640 | 643 | self.isConfig = True |
|
|
641 | 644 | |
|
|
642 | 645 | self.concat(dataOut.data) |
|
|
643 | 646 | self.times += 1 |
|
|
644 | 647 | if self.times > m: |
|
|
645 | 648 | dataOut.data = self.buffer |
|
|
646 | 649 | self.reset() |
|
|
647 | 650 | dataOut.flagNoData = False |
|
|
648 | 651 | # se deben actualizar mas propiedades del header y del objeto dataOut, por ejemplo, las alturas |
|
|
649 | 652 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
|
650 | 653 | xf = dataOut.heightList[0] + dataOut.nHeights * deltaHeight * 5 |
|
|
651 | 654 | dataOut.heightList = numpy.arange(dataOut.heightList[0], xf, deltaHeight) |
|
|
652 | 655 | |
|
|
653 | 656 | class ProfileSelector(Operation): |
|
|
654 | 657 | |
|
|
655 | 658 | profileIndex = None |
|
|
656 | 659 | # Tamanho total de los perfiles |
|
|
657 | 660 | nProfiles = None |
|
|
658 | 661 | |
|
|
659 | 662 | def __init__(self): |
|
|
660 | 663 | |
|
|
661 | 664 | Operation.__init__(self) |
|
|
662 | 665 | self.profileIndex = 0 |
|
|
663 | 666 | |
|
|
664 | 667 | def incIndex(self): |
|
|
665 | 668 | self.profileIndex += 1 |
|
|
666 | 669 | |
|
|
667 | 670 | if self.profileIndex >= self.nProfiles: |
|
|
668 | 671 | self.profileIndex = 0 |
|
|
669 | 672 | |
|
|
670 | 673 | def isProfileInRange(self, minIndex, maxIndex): |
|
|
671 | 674 | |
|
|
672 | 675 | if self.profileIndex < minIndex: |
|
|
673 | 676 | return False |
|
|
674 | 677 | |
|
|
675 | 678 | if self.profileIndex > maxIndex: |
|
|
676 | 679 | return False |
|
|
677 | 680 | |
|
|
678 | 681 | return True |
|
|
679 | 682 | |
|
|
680 | 683 | def isProfileInList(self, profileList): |
|
|
681 | 684 | |
|
|
682 | 685 | if self.profileIndex not in profileList: |
|
|
683 | 686 | return False |
|
|
684 | 687 | |
|
|
685 | 688 | return True |
|
|
686 | 689 | |
|
|
687 | 690 | def run(self, dataOut, profileList=None, profileRangeList=None, beam=None, byblock=False): |
|
|
688 | 691 | |
|
|
689 | 692 | dataOut.flagNoData = True |
|
|
690 | 693 | self.nProfiles = dataOut.nProfiles |
|
|
691 | 694 | |
|
|
692 | 695 | if byblock: |
|
|
693 | 696 | |
|
|
694 | 697 | if profileList != None: |
|
|
695 | 698 | dataOut.data = dataOut.data[:,profileList,:] |
|
|
696 | 699 | pass |
|
|
697 | 700 | else: |
|
|
698 | 701 | pmin = profileRangeList[0] |
|
|
699 | 702 | pmax = profileRangeList[1] |
|
|
700 | 703 | dataOut.data = dataOut.data[:,pmin:pmax+1,:] |
|
|
701 | 704 | dataOut.flagNoData = False |
|
|
702 | 705 | self.profileIndex = 0 |
|
|
703 | 706 | return 1 |
|
|
704 | 707 | |
|
|
705 | 708 | if profileList != None: |
|
|
706 | 709 | if self.isProfileInList(profileList): |
|
|
707 | 710 | dataOut.flagNoData = False |
|
|
708 | 711 | |
|
|
709 | 712 | self.incIndex() |
|
|
710 | 713 | return 1 |
|
|
711 | 714 | |
|
|
712 | 715 | |
|
|
713 | 716 | elif profileRangeList != None: |
|
|
714 | 717 | minIndex = profileRangeList[0] |
|
|
715 | 718 | maxIndex = profileRangeList[1] |
|
|
716 | 719 | if self.isProfileInRange(minIndex, maxIndex): |
|
|
717 | 720 | dataOut.flagNoData = False |
|
|
718 | 721 | |
|
|
719 | 722 | self.incIndex() |
|
|
720 | 723 | return 1 |
|
|
721 | 724 | elif beam != None: #beam is only for AMISR data |
|
|
722 | 725 | if self.isProfileInList(dataOut.beamRangeDict[beam]): |
|
|
723 | 726 | dataOut.flagNoData = False |
|
|
724 | 727 | |
|
|
725 | 728 | self.incIndex() |
|
|
726 | 729 | return 1 |
|
|
727 | 730 | |
|
|
728 | 731 | else: |
|
|
729 | 732 | raise ValueError, "ProfileSelector needs profileList or profileRangeList" |
|
|
730 | 733 | |
|
|
731 | 734 | return 0 |
|
|
732 | 735 | |
|
|
733 | 736 | |
|
|
734 | 737 | |
|
|
735 | 738 | class Reshaper(Operation): |
|
|
736 | 739 | def __init__(self): |
|
|
737 | 740 | Operation.__init__(self) |
|
|
738 | 741 | self.updateNewHeights = False |
|
|
739 | 742 | |
|
|
740 | 743 | def run(self, dataOut, shape): |
|
|
741 | 744 | shape_tuple = tuple(shape) |
|
|
742 | 745 | dataOut.data = numpy.reshape(dataOut.data, shape_tuple) |
|
|
743 | 746 | dataOut.flagNoData = False |
|
|
744 | 747 | |
|
|
745 | 748 | if not(self.updateNewHeights): |
|
|
746 | 749 | old_nheights = dataOut.nHeights |
|
|
747 | 750 | new_nheights = dataOut.data.shape[2] |
|
|
748 | 751 | factor = new_nheights / old_nheights |
|
|
749 | 752 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
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750 | 753 | xf = dataOut.heightList[0] + dataOut.nHeights * deltaHeight * factor |
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751 | 754 | dataOut.heightList = numpy.arange(dataOut.heightList[0], xf, deltaHeight) No newline at end of file |
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