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1 | #!python | |
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2 | ''' | |
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3 | ''' | |
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4 | ||
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5 | import os, sys | |
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6 | import datetime | |
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7 | import time | |
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8 | ||
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9 | #path = os.path.dirname(os.getcwd()) | |
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10 | #path = os.path.dirname(path) | |
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11 | #sys.path.insert(0, path) | |
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12 | ||
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13 | from schainpy.controller import Project | |
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14 | ||
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15 | desc = "USRP_test" | |
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16 | filename = "USRP_processing.xml" | |
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17 | controllerObj = Project() | |
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18 | controllerObj.setup(id = '191', name='Test_USRP', description=desc) | |
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19 | ||
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20 | ############## USED TO PLOT IQ VOLTAGE, POWER AND SPECTRA ############# | |
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21 | ||
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22 | ####################################################################### | |
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23 | ######PATH DE LECTURA, ESCRITURA, GRAFICOS Y ENVIO WEB################# | |
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24 | ####################################################################### | |
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25 | #path = '/media/data/data/vientos/57.2063km/echoes/NCO_Woodman' | |
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26 | #path = '/DATA_RM/TEST_INTEGRACION' | |
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27 | #path = '/DATA_RM/PRUEBA_USRP_RP' | |
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28 | #path = '/DATA_RM/PRUEBA_USRP_RP' | |
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29 | ||
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30 | path = '/DATA_RM/TEST_2M' | |
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31 | path = '/DATA_RM/TEST_2M_UD' | |
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32 | path = '/DATA_RM/2MHZ17022022' | |
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33 | path = '/DATA_RM/10MHZTEST/' | |
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34 | path = '/DATA_RM/10MHZDRONE/' | |
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35 | ||
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36 | ||
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37 | path= '/home/soporte/TEST_500mVPP' | |
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38 | path= '/home/soporte/TEST_1VPP+500mVDC' | |
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39 | path = '/home/soporte/TEST_500mVPP+500mVDC' | |
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40 | path = '/home/soporte/TEST_1.5VPP' | |
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41 | path = '/home/soporte/TEST_2VPP' | |
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42 | path= '/home/soporte/TEST_1VPP' | |
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43 | path = '/home/soporte/Documents/HUANCAYO/TEST_HYO_PM@2022-05-14T11-28-19/rawdata' | |
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44 | ||
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45 | #HYO_PM@2022-05-28T00-00-17 | |
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46 | path = '/DATA_RM/DATA/HYO_PM@2022-05-28T00-00-17/rawdata' | |
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47 | ||
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48 | #figpath = '/home/soporte/Pictures/TEST_RP_0001' | |
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49 | #figpath = '/home/soporte/Pictures/TEST_RP_6000' | |
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50 | figpath = '/home/soporte/Pictures/USRP_TEST_2M' | |
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51 | figpath = '/home/soporte/Pictures/USRP_TEST_2M_UD' | |
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52 | figpath = '/home/soporte/Pictures/10MHZDRONE' | |
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53 | figpath = '/home/soporte/Pictures/500mVPP' | |
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54 | figpath = '/home/soporte/Pictures/1VPP+500mVDC' | |
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55 | figpath = '/home/soporte/Pictures/TEST_500mVPP+500mVDC' | |
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56 | figpath = '/home/soporte/Pictures/TEST_1.5VPP' | |
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57 | figpath = '/home/soporte/Pictures/TEST_2VPP' | |
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58 | figpath = '/home/soporte/Pictures/TEST_1VPP' | |
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59 | ||
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60 | ||
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61 | ||
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62 | ||
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63 | #remotefolder = "/home/wmaster/graficos" | |
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64 | ####################################################################### | |
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65 | ################# RANGO DE PLOTEO###################################### | |
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66 | ####################################################################### | |
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67 | dBmin = '-60'#'-20' | |
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68 | dBmax = '-5'#'-85' | |
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69 | xmin = '0' | |
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70 | xmax ='24' | |
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71 | ymin = '0' | |
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72 | ymax = '10' | |
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73 | ####################################################################### | |
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74 | ########################FECHA########################################## | |
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75 | ####################################################################### | |
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76 | str = datetime.date.today() | |
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77 | today = str.strftime("%Y/%m/%d") | |
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78 | str2 = str - datetime.timedelta(days=1) | |
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79 | yesterday = str2.strftime("%Y/%m/%d") | |
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80 | ####################################################################### | |
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81 | ######################## UNIDAD DE LECTURA############################# | |
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82 | ####################################################################### | |
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83 | readUnitConfObj = controllerObj.addReadUnit(datatype='DigitalRFReader', | |
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84 | path=path, | |
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85 | startDate="2022/05/28",#today, | |
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86 | endDate="2022/05/28",#today, | |
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87 | startTime='00:00:00',# inicio libre | |
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88 | #startTime='00:00:00', | |
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89 | endTime='23:59:59', | |
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90 | delay=0, | |
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91 | #set=0, | |
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92 | online=0, | |
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93 | walk=1, | |
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94 | ippKm = 60) | |
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95 | ||
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96 | opObj11 = readUnitConfObj.addOperation(name='printInfo') | |
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97 | #opObj11 = readUnitConfObj.addOperation(name='printNumberOfBlock') | |
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98 | ####################################################################### | |
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99 | ################ OPERACIONES DOMINIO DEL TIEMPO######################## | |
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100 | ####################################################################### | |
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101 | ||
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102 | procUnitConfObjA = controllerObj.addProcUnit(datatype='VoltageProc', inputId=readUnitConfObj.getId()) | |
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103 | ||
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104 | op3 = procUnitConfObjA.addOperation(name='ProfileSelector', optype='other') | |
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105 | op3.addParameter(name='profileRangeList', value='1,123') | |
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106 | ||
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107 | ||
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108 | code=[[1]] | |
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109 | ||
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110 | opObj11 = procUnitConfObjA.addOperation(name='Decoder', optype='other') | |
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111 | opObj11.addParameter(name='code', value=code) | |
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112 | opObj11.addParameter(name='nCode', value='1', format='int') | |
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113 | opObj11.addParameter(name='nBaud', value='1', format='int') | |
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114 | ||
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115 | ||
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116 | ''' | |
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117 | op3 = procUnitConfObjA.addOperation(name='ProfileSelector', optype='other') | |
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118 | op3.addParameter(name='profileRangeList', value='122,249') | |
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119 | code8=[[1,1,1,0,1,1,0,1],[1,1,1,0,0,0,1,0]] | |
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120 | ||
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121 | opObj11 = procUnitConfObjA.addOperation(name='Decoder', optype='other') | |
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122 | opObj11.addParameter(name='code', value=code8) | |
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123 | opObj11.addParameter(name='nCode', value='2', format='int') | |
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124 | opObj11.addParameter(name='nBaud', value='8', format='int') | |
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125 | ''' | |
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126 | op = procUnitConfObjA.addOperation(name='CohInt', optype='other') #Minimo integrar 2 perfiles por ser codigo complementario | |
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127 | op.addParameter(name='n', value=2, format='int') | |
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128 | ||
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129 | ||
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130 | ''' | |
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131 | ||
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132 | # OJO SCOPE | |
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133 | opObj10 = procUnitConfObjA.addOperation(name='ScopePlot', optype='external') | |
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134 | opObj10.addParameter(name='id', value='10', format='int') | |
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135 | opObj10.addParameter(name='xmin', value='0', format='int') | |
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136 | opObj10.addParameter(name='xmax', value='60', format='int') | |
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137 | opObj10.addParameter(name='type', value='iq') | |
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138 | #opObj10.addParameter(name='ymin', value='-0.20000', format='int') | |
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139 | #opObj10.addParameter(name='ymax', value='0.20000', format='int') | |
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140 | opObj10.addParameter(name='save', value=figpath, format='str') | |
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141 | opObj10.addParameter(name='save_period', value=1, format='int') | |
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142 | ''' | |
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143 | ''' | |
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144 | opObj11 = procUnitConfObjA.addOperation(name='selectHeights') | |
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145 | opObj11.addParameter(name='minIndex', value='1', format='int') | |
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146 | # opObj11.addParameter(name='maxIndex', value='10000', format='int') | |
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147 | opObj11.addParameter(name='maxIndex', value='200', format='int') | |
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148 | ''' | |
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149 | # | |
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150 | # codigo64='1,1,1,0,1,1,0,1,1,1,1,0,0,0,1,0,1,1,1,0,1,1,0,1,0,0,0,1,1,1,0,1,1,1,1,0,1,1,0,1,1,1,1,0,0,0,1,0,0,0,0,1,0,0,1,0,1,1,1,0,0,0,1,0,'+\ | |
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151 | # '1,1,1,0,1,1,0,1,1,1,1,0,0,0,1,0,1,1,1,0,1,1,0,1,0,0,0,1,1,1,0,1,0,0,0,1,0,0,1,0,0,0,0,1,1,1,0,1,1,1,1,0,1,1,0,1,0,0,0,1,1,1,0,1' | |
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152 | ||
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153 | #opObj11 = procUnitConfObjA.addOperation(name='setRadarFrequency') | |
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154 | #opObj11.addParameter(name='frequency', value='49920000') | |
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155 | ||
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156 | ''' | |
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157 | opObj11 = procUnitConfObjA.addOperation(name='PulsePair', optype='other') | |
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158 | opObj11.addParameter(name='n', value='625', format='int')#10 | |
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159 | opObj11.addParameter(name='removeDC', value=1, format='int') | |
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160 | ''' | |
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161 | ||
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162 | # Ploteo TEST | |
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163 | ''' | |
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164 | opObj11 = procUnitConfObjA.addOperation(name='PulsepairPowerPlot', optype='other') | |
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165 | opObj11 = procUnitConfObjA.addOperation(name='PulsepairSignalPlot', optype='other') | |
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166 | opObj11 = procUnitConfObjA.addOperation(name='PulsepairVelocityPlot', optype='other') | |
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167 | #opObj11.addParameter(name='xmax', value=8) | |
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168 | opObj11 = procUnitConfObjA.addOperation(name='PulsepairSpecwidthPlot', optype='other') | |
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169 | ''' | |
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170 | # OJO SCOPE | |
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171 | #opObj10 = procUnitConfObjA.addOperation(name='ScopePlot', optype='external') | |
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172 | #opObj10.addParameter(name='id', value='10', format='int') | |
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173 | ##opObj10.addParameter(name='xmin', value='0', format='int') | |
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174 | ##opObj10.addParameter(name='xmax', value='50', format='int') | |
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175 | #opObj10.addParameter(name='type', value='iq') | |
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176 | ##opObj10.addParameter(name='ymin', value='-5000', format='int') | |
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177 | ##opObj10.addParameter(name='ymax', value='8500', format='int') | |
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178 | #opObj11.addParameter(name='save', value=figpath, format='str') | |
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179 | #opObj11.addParameter(name='save_period', value=10, format='int') | |
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180 | ||
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181 | #opObj10 = procUnitConfObjA.addOperation(name='setH0') | |
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182 | #opObj10.addParameter(name='h0', value='-5000', format='float') | |
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183 | ||
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184 | #opObj11 = procUnitConfObjA.addOperation(name='filterByHeights') | |
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185 | #opObj11.addParameter(name='window', value='1', format='int') | |
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186 | ||
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187 | #codigo='1,1,-1,1,1,-1,1,-1,-1,1,-1,-1,-1,1,-1,-1,-1,1,-1,-1,-1,1,1,1,1,-1,-1,-1' | |
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188 | #opObj11 = procUnitConfObjSousy.addOperation(name='Decoder', optype='other') | |
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189 | #opObj11.addParameter(name='code', value=codigo, format='floatlist') | |
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190 | #opObj11.addParameter(name='nCode', value='1', format='int') | |
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191 | #opObj11.addParameter(name='nBaud', value='28', format='int') | |
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192 | ||
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193 | #opObj11 = procUnitConfObjA.addOperation(name='CohInt', optype='other') | |
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194 | #opObj11.addParameter(name='n', value='100', format='int') | |
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195 | ||
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196 | ####################################################################### | |
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197 | ########## OPERACIONES ParametersProc######################## | |
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198 | ####################################################################### | |
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199 | ###procUnitConfObjB= controllerObj.addProcUnit(datatype='ParametersProc',inputId=procUnitConfObjA.getId()) | |
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200 | ''' | |
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201 | ||
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202 | opObj11 = procUnitConfObjA.addOperation(name='PedestalInformation') | |
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203 | opObj11.addParameter(name='path_ped', value=path_ped) | |
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204 | opObj11.addParameter(name='path_adq', value=path_adq) | |
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205 | opObj11.addParameter(name='t_Interval_p', value='0.01', format='float') | |
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206 | opObj11.addParameter(name='n_Muestras_p', value='100', format='float') | |
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207 | opObj11.addParameter(name='blocksPerfile', value='100', format='int') | |
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208 | opObj11.addParameter(name='f_a_p', value='25', format='int') | |
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209 | opObj11.addParameter(name='online', value='0', format='int') | |
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210 | ||
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211 | opObj11 = procUnitConfObjA.addOperation(name='Block360') | |
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212 | opObj11.addParameter(name='n', value='40', format='int') | |
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213 | ||
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214 | opObj11= procUnitConfObjA.addOperation(name='WeatherPlot',optype='other') | |
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215 | opObj11.addParameter(name='save', value=figpath) | |
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216 | opObj11.addParameter(name='save_period', value=1) | |
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217 | ||
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218 | 8 | |
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219 | ''' | |
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220 | ||
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221 | ||
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222 | ''' | |
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223 | opObj11 = procUnitConfObjA.addOperation(name='CohInt', optype='other') | |
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224 | opObj11.addParameter(name='n', value='250', format='int') | |
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225 | ''' | |
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226 | ####################################################################### | |
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227 | ########## OPERACIONES DOMINIO DE LA FRECUENCIA######################## | |
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228 | ####################################################################### | |
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229 | ''' | |
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230 | procUnitConfObjB = controllerObj.addProcUnit(datatype='SpectraProc', inputId=procUnitConfObjA.getId()) | |
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231 | procUnitConfObjB.addParameter(name='nFFTPoints', value='64', format='int') | |
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232 | procUnitConfObjB.addParameter(name='nProfiles', value='64', format='int') | |
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233 | ''' | |
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234 | ||
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235 | procUnitConfObjB = controllerObj.addProcUnit(datatype='SpectraProc', inputId=procUnitConfObjA.getId()) | |
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236 | procUnitConfObjB.addParameter(name='nFFTPoints', value='61', format='int') | |
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237 | procUnitConfObjB.addParameter(name='nProfiles', value='61', format='int') | |
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238 | ||
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239 | ''' | |
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240 | procUnitConfObjC = controllerObj.addProcUnit(datatype='SpectraHeisProc', inputId=procUnitConfObjA.getId()) | |
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241 | #procUnitConfObjB.addParameter(name='nFFTPoints', value='64', format='int') | |
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242 | #procUnitConfObjB.addParameter(name='nProfiles', value='64', format='int') | |
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243 | opObj11 = procUnitConfObjC.addOperation(name='IncohInt4SpectraHeis', optype='other') | |
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244 | #opObj11.addParameter(name='timeInterval', value='4', format='int') | |
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245 | opObj11.addParameter(name='n', value='100', format='int') | |
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246 | ||
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247 | #procUnitConfObjB.addParameter(name='pairsList', value='(0,0),(1,1),(0,1)', format='pairsList') | |
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248 | ||
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249 | #opObj13 = procUnitConfObjB.addOperation(name='removeDC') | |
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250 | #opObj13.addParameter(name='mode', value='2', format='int') | |
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251 | ||
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252 | #opObj11 = procUnitConfObjB.addOperation(name='IncohInt', optype='other') | |
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253 | #opObj11.addParameter(name='n', value='8', format='float') | |
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254 | ####################################################################### | |
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255 | ########## PLOTEO DOMINIO DE LA FRECUENCIA############################# | |
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256 | ####################################################################### | |
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257 | #---- | |
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258 | ''' | |
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259 | ''' | |
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260 | opObj11 = procUnitConfObjC.addOperation(name='SpectraHeisPlot') | |
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261 | opObj11.addParameter(name='id', value='10', format='int') | |
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262 | opObj11.addParameter(name='wintitle', value='Spectra_Alturas', format='str') | |
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263 | #opObj11.addParameter(name='xmin', value=-100000, format='float') | |
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264 | #opObj11.addParameter(name='xmax', value=100000, format='float') | |
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265 | opObj11.addParameter(name='oneFigure', value=False,format='bool') | |
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266 | #opObj11.addParameter(name='zmin', value=-10, format='int') | |
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267 | #opObj11.addParameter(name='zmax', value=40, format='int') | |
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268 | opObj11.addParameter(name='ymin', value=10, format='int') | |
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269 | opObj11.addParameter(name='ymax', value=55, format='int') | |
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270 | opObj11.addParameter(name='grid', value=True, format | |
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271 | [Reading] 2022-05-23 12:27:32.732775: 21333 samples <> 0.010667 sec | |
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272 | ='bool') | |
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273 | #opObj11.addParameter(name='showprofile', value='1', format='int') | |
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274 | opObj11.addParameter(name='save', value=figpath, format='str') | |
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275 | #opObj11.addParameter(name='save_period', value=10, format='int') | |
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276 | ''' | |
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277 | ''' | |
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278 | opObj11 = procUnitConfObjC.addOperation(name='RTIHeisPlot') | |
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279 | opObj11.addParameter(name='id', value='10', format='int') | |
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280 | opObj11.addParameter(name='wintitle', value='RTI_Alturas', format='str') | |
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281 | opObj11.addParameter(name='xmin', value=11.0, format='float') | |
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282 | opObj11.addParameter(name='xmax', value=18.0, format='float') | |
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283 | opObj11.addParameter(name='zmin', value=10, format='int') | |
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284 | opObj11.addParameter(name='zmax', value=30, format='int') | |
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285 | opObj11.addParameter(name='ymin', value=5, format='int') | |
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286 | opObj11.addParameter(name='ymax', value=28, format='int') | |
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287 | opObj11.addParameter(name='showprofile', value='1', format='int') | |
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288 | opObj11.addParameter(name='save', value=figpath, format='str') | |
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289 | opObj11.addParameter(name='save_period', value=10, format='int') | |
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290 | ''' | |
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291 | ||
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292 | #SpectraPlot | |
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293 | ||
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294 | opObj11 = procUnitConfObjB.addOperation(name='SpectraPlot', optype='external') | |
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295 | opObj11.addParameter(name='id', value='1', format='int') | |
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296 | opObj11.addParameter(name='wintitle', value='Spectra', format='str') | |
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297 | #opObj11.addParameter(name='xmin', value=-0.01, format='float') | |
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298 | #opObj11.addParameter(name='xmax', value=0.01, format='float') | |
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299 | opObj11.addParameter(name='zmin', value=dBmin, format='int') | |
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300 | opObj11.addParameter(name='zmax', value=dBmax, format='int') | |
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301 | opObj11.addParameter(name='ymin', value=ymin, format='int') | |
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302 | opObj11.addParameter(name='ymax', value=ymax, format='int') | |
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303 | opObj11.addParameter(name='showprofile', value='1', format='int') | |
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304 | opObj11.addParameter(name='save', value=figpath, format='str') | |
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305 | opObj11.addParameter(name='save_period', value=10, format='int') | |
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306 | ||
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307 | ||
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308 | #RTIPLOT | |
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309 | ''' | |
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310 | opObj11 = procUnitConfObjB.addOperation(name='RTIPlot', optype='external') | |
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311 | opObj11.addParameter(name='id', value='2', format='int') | |
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312 | opObj11.addParameter(name='wintitle', value='RTIPlot', format='str') | |
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313 | opObj11.addParameter(name='zmin', value=dBmin, format='int') | |
|
|
314 | opObj11.addParameter(name='zmax', value=dBmax, format='int') | |
|
|
315 | #opObj11.addParameter(name='ymin', value=ymin, format='int') | |
|
|
316 | #opObj11.addParameter(name='ymax', value=ymax, format='int') | |
|
|
317 | #opObj11.addParameter(name='xmin', value=15, format='int') | |
|
|
318 | #opObj11.addParameter(name='xmax', value=16, format='int') | |
|
|
319 | opObj11.addParameter(name='zmin', value=dBmin, format='int') | |
|
|
320 | opObj11.addParameter(name='zmax', value=dBmax, format='int') | |
|
|
321 | ||
|
|
322 | opObj11.addParameter(name='showprofile', value='1', format='int') | |
|
|
323 | opObj11.addParameter(name='save', value=figpath, format='str') | |
|
|
324 | opObj11.addParameter(name='save_period', value=10, format='int') | |
|
|
325 | ''' | |
|
|
326 | ''' | |
|
|
327 | # opObj11 = procUnitConfObjB.addOperation(name='CrossSpectraPlot', optype='other') | |
|
|
328 | # opObj11.addParameter(name='id', value='3', format='int') | |
|
|
329 | # opObj11.addParameter(name='wintitle', value='CrossSpectraPlot', format='str') | |
|
|
330 | # opObj11.addParameter(name='ymin', value=ymin, format='int') | |
|
|
331 | # opObj11.addParameter(name='ymax', value=ymax, format='int') | |
|
|
332 | # opObj11.addParameter(name='phase_cmap', value='jet', format='str') | |
|
|
333 | # opObj11.addParameter(name='zmin', value=dBmin, format='int') | |
|
|
334 | # opObj11.addParameter(name='zmax', value=dBmax, format='int') | |
|
|
335 | # opObj11.addParameter(name='figpath', value=figures_path, format='str') | |
|
|
336 | # opObj11.addParameter(name='save', value=0, format='bool') | |
|
|
337 | # opObj11.addParameter(name='pairsList', value='(0,1)', format='pairsList') | |
|
|
338 | # # | |
|
|
339 | # opObj11 = procUnitConfObjB.addOperation(name='CoherenceMap', optype='other') | |
|
|
340 | # opObj11.addParameter(name='id', value='4', format='int') | |
|
|
341 | # opObj11.addParameter(name='wintitle', value='Coherence', format='str') | |
|
|
342 | # opObj11.addParameter(name='phase_cmap', value='jet', format='str') | |
|
|
343 | # opObj11.addParameter(name='xmin', value=xmin, format='float') | |
|
|
344 | # opObj11.addParameter(name='xmax', value=xmax, format='float') | |
|
|
345 | # opObj11.addParameter(name='figpath', value=figures_path, format='str') | |
|
|
346 | # opObj11.addParameter(name='save', value=0, format='bool') | |
|
|
347 | # opObj11.addParameter(name='pairsList', value='(0,1)', format='pairsList') | |
|
|
348 | # | |
|
|
349 | ''' | |
|
|
350 | ''' | |
|
|
351 | ####################################################################### | |
|
|
352 | ############### UNIDAD DE ESCRITURA ################################### | |
|
|
353 | ####################################################################### | |
|
|
354 | #opObj11 = procUnitConfObjB.addOperation(name='SpectraWriter', optype='other') | |
|
|
355 | #opObj11.addParameter(name='path', value=wr_path) | |
|
|
356 | #opObj11.addParameter(name='blocksPerFile', value='50', format='int') | |
|
|
357 | print ("Escribiendo el archivo XML") | |
|
|
358 | print ("Leyendo el archivo XML") | |
|
|
359 | ''' | |
|
|
360 | ||
|
|
361 | ||
|
|
362 | controllerObj.start() | |
| @@ -0,0 +1,378 | |||
|
|
1 | ||
|
|
2 | # SOPHY PROC script | |
|
|
3 | import os, sys, json, argparse | |
|
|
4 | import datetime | |
|
|
5 | import time | |
|
|
6 | ||
|
|
7 | PATH = '/DATA_RM/DATA' | |
|
|
8 | # PATH = '/Users/jespinoza/workspace/data/' | |
|
|
9 | #PATH = '/home/soporte/Documents/HUANCAYO' | |
|
|
10 | PARAM = { | |
|
|
11 | 'P': {'name': 'dataPP_POWER', 'zmin': -45, 'zmax': -25, 'colormap': 'jet', 'label': 'Power', 'wrname': 'Pow','cb_label': 'dB', 'ch':0}, | |
|
|
12 | 'V': {'name': 'dataPP_DOP', 'zmin': -20, 'zmax': 20, 'colormap': 'seismic', 'label': 'Velocity', 'wrname': 'Vel', 'cb_label': 'm/s', 'ch':0}, | |
|
|
13 | 'RH': {'name': 'RhoHV_R', 'zmin': 0, 'zmax': 1, 'colormap': 'jet', 'label': 'Coef.Correlacion', 'wrname':'R', 'cb_label': '*', 'ch':0}, | |
|
|
14 | 'FD': {'name': 'PhiD_P', 'zmin': -180,'zmax': 180,'colormap': 'RdBu_r', 'label': 'Fase Diferencial', 'wrname':'P' , 'cb_label': 'º', 'ch':0}, | |
|
|
15 | 'ZD': {'name': 'Zdb_D', 'zmin': -20, 'zmax': 60, 'colormap': 'viridis','label': 'Reflect.Diferencial','wrname':'D' , 'cb_label': 'dBz','ch':0}, | |
|
|
16 | 'Z': {'name': 'Zdb', 'zmin': -20, 'zmax': 70, 'colormap': 'gist_ncar','label': 'Reflectividad', 'wrname':'Z', 'cb_label': 'dBz','ch':1}, | |
|
|
17 | 'W': {'name': 'Sigmav_W', 'zmin': 0, 'zmax':5, 'colormap': 'viridis','label': 'AnchoEspectral', 'wrname':'S', 'cb_label': 'hz', 'ch':1} | |
|
|
18 | } | |
|
|
19 | ||
|
|
20 | # | |
|
|
21 | def max_index(r, sample_rate, ipp): | |
|
|
22 | ||
|
|
23 | return int(sample_rate*ipp*1e6 * r / 60) + int(sample_rate*ipp*1e6 * 1.2 / 60) | |
|
|
24 | ||
|
|
25 | def main(args): | |
|
|
26 | ||
|
|
27 | experiment = args.experiment | |
|
|
28 | fp = open(os.path.join(PATH, experiment, 'experiment.conf')) | |
|
|
29 | conf = json.loads(fp.read()) | |
|
|
30 | ||
|
|
31 | ipp_km = conf['usrp_tx']['ipp'] | |
|
|
32 | ipp = ipp_km * 2 /300000 | |
|
|
33 | sample_rate = conf['usrp_rx']['sample_rate'] | |
|
|
34 | axis = ['0' if x=='elevation' else '1' for x in conf['pedestal']['axis']] # AZIMUTH 1 ELEVACION 0 | |
|
|
35 | speed_axis = conf['pedestal']['speed'] | |
|
|
36 | steeps = conf['pedestal']['table'] | |
|
|
37 | time_offset = args.time_offset | |
|
|
38 | parameters = args.parameters | |
|
|
39 | start_date = experiment.split('@')[1].split('T')[0].replace('-', '/') | |
|
|
40 | end_date = start_date | |
|
|
41 | start_time = experiment.split('@')[1].split('T')[1].replace('-', ':') | |
|
|
42 | end_time = '23:59:59' | |
|
|
43 | N = int(1/(speed_axis[0]*ipp)) # 1 GRADO DE RESOLUCION | |
|
|
44 | path = os.path.join(PATH, experiment, 'rawdata') | |
|
|
45 | path_ped = os.path.join(PATH, experiment, 'position') | |
|
|
46 | path_plots = os.path.join(PATH, experiment, 'plots_ch0') | |
|
|
47 | path_save = os.path.join(PATH, experiment, 'param') | |
|
|
48 | RMIX = 20 | |
|
|
49 | ||
|
|
50 | from schainpy.controller import Project | |
|
|
51 | ||
|
|
52 | project = Project() | |
|
|
53 | project.setup(id='1', name='Sophy', description='sophy proc') | |
|
|
54 | ||
|
|
55 | reader = project.addReadUnit(datatype='DigitalRFReader', | |
|
|
56 | path=path, | |
|
|
57 | startDate=start_date, | |
|
|
58 | endDate=end_date, | |
|
|
59 | startTime=start_time, | |
|
|
60 | endTime=end_time, | |
|
|
61 | delay=30, | |
|
|
62 | channelList='0', | |
|
|
63 | online=args.online, | |
|
|
64 | walk=1, | |
|
|
65 | ippKm = ipp_km, | |
|
|
66 | getByBlock = 1, | |
|
|
67 | nProfileBlocks = N, | |
|
|
68 | ) | |
|
|
69 | ||
|
|
70 | if not conf['usrp_tx']['enable_2']: # One Pulse | |
|
|
71 | voltage = project.addProcUnit(datatype='VoltageProc', inputId=reader.getId()) | |
|
|
72 | ||
|
|
73 | if conf['usrp_tx']['code_type_1']: | |
|
|
74 | code = [c.split() for c in conf['usrp']['code_1']] | |
|
|
75 | op = voltage.addOperation(name='Decoder', optype='other') | |
|
|
76 | op.addParameter(name='code', value=code) | |
|
|
77 | op.addParameter(name='nCode', value=len(code), format='int') | |
|
|
78 | op.addParameter(name='nBaud', value=len(code[0]), format='int') | |
|
|
79 | ||
|
|
80 | op = voltage.addOperation(name='setH0') | |
|
|
81 | op.addParameter(name='h0', value='-1.2') | |
|
|
82 | ||
|
|
83 | if args.range >= 0: | |
|
|
84 | op = voltage.addOperation(name='selectHeights') | |
|
|
85 | op.addParameter(name='minIndex', value='0', format='int') | |
|
|
86 | op.addParameter(name='maxIndex', value=max_index(RMIX, sample_rate, ipp), format='int') | |
|
|
87 | ||
|
|
88 | code=[[1]] | |
|
|
89 | opObj11 = voltage.addOperation(name='Decoder', optype='other') | |
|
|
90 | opObj11.addParameter(name='code', value=code) | |
|
|
91 | opObj11.addParameter(name='nCode', value='1', format='int') | |
|
|
92 | opObj11.addParameter(name='nBaud', value='1', format='int') | |
|
|
93 | ||
|
|
94 | op = voltage2.addOperation(name='CohInt', optype='other') #Minimo integrar 2 perfiles por ser codigo complementario | |
|
|
95 | op.addParameter(name='n', value=2*len(code), format='int') | |
|
|
96 | ||
|
|
97 | #op = voltage.addOperation(name='PulsePair_vRF', optype='other') | |
|
|
98 | #op.addParameter(name='n', value=int(N), format='int') | |
|
|
99 | ||
|
|
100 | if args.range >= 0: | |
|
|
101 | op = voltage.addOperation(name='selectHeights') | |
|
|
102 | op.addParameter(name='minIndex', value='0', format='int') | |
|
|
103 | op.addParameter(name='maxIndex', value=max_index(RMIX, sample_rate, ipp), format='int') | |
|
|
104 | ||
|
|
105 | ||
|
|
106 | op = voltage.addOperation(name='PulsePair_vRF', optype='other') | |
|
|
107 | op.addParameter(name='n', value=125, format='int') | |
|
|
108 | ||
|
|
109 | ||
|
|
110 | proc = project.addProcUnit(datatype='ParametersProc', inputId=voltage.getId()) | |
|
|
111 | #procUnitConfObjB.addParameter(name='runNextUnit', value=True) | |
|
|
112 | ||
|
|
113 | opObj10 = proc.addOperation(name="WeatherRadar") | |
|
|
114 | opObj10.addParameter(name='variableList',value='Reflectividad,VelocidadRadial,AnchoEspectral') | |
|
|
115 | ||
|
|
116 | # {"latitude": -12.0404828587, "longitude": -75.2147483647, "altitude": 3379.2147483647} | |
|
|
117 | ||
|
|
118 | op = proc.addOperation(name='PedestalInformation') | |
|
|
119 | op.addParameter(name='path', value=path_ped, format='str') | |
|
|
120 | op.addParameter(name='interval', value='0.04') | |
|
|
121 | op.addParameter(name='time_offset', value=time_offset) | |
|
|
122 | op.addParameter(name='az_offset', value=-26.2) | |
|
|
123 | ||
|
|
124 | for param in parameters: | |
|
|
125 | op = proc.addOperation(name='Block360_vRF4') | |
|
|
126 | #op.addParameter(name='axis', value=','.join(axis)) | |
|
|
127 | op.addParameter(name='attr_data', value=PARAM[param]['name']) | |
|
|
128 | op.addParameter(name='runNextOp', value=True) | |
|
|
129 | ||
|
|
130 | op= proc.addOperation(name='WeatherParamsPlot') | |
|
|
131 | if args.save: op.addParameter(name='save', value=path_plots, format='str') | |
|
|
132 | op.addParameter(name='save_period', value=-1) | |
|
|
133 | op.addParameter(name='show', value=args.show) | |
|
|
134 | op.addParameter(name='channels', value='0,') | |
|
|
135 | op.addParameter(name='zmin', value=PARAM[param]['zmin']) | |
|
|
136 | op.addParameter(name='zmax', value=PARAM[param]['zmax']) | |
|
|
137 | op.addParameter(name='attr_data', value=PARAM[param]['name'], format='str') | |
|
|
138 | op.addParameter(name='labels', value=[PARAM[param]['label']]) | |
|
|
139 | op.addParameter(name='save_code', value=param) | |
|
|
140 | op.addParameter(name='cb_label', value=PARAM[param]['cb_label']) | |
|
|
141 | op.addParameter(name='colormap', value=PARAM[param]['colormap']) | |
|
|
142 | ||
|
|
143 | desc = { | |
|
|
144 | 'Data': { | |
|
|
145 | PARAM[param]['name']: PARAM[param]['label'], | |
|
|
146 | 'utctime': 'time' | |
|
|
147 | }, | |
|
|
148 | 'Metadata': { | |
|
|
149 | 'heightList': 'range', | |
|
|
150 | 'data_azi': 'azimuth', | |
|
|
151 | 'data_ele': 'elevation', | |
|
|
152 | } | |
|
|
153 | } | |
|
|
154 | ||
|
|
155 | if args.save: | |
|
|
156 | opObj10 = proc.addOperation(name='HDFWriter') | |
|
|
157 | opObj10.addParameter(name='path',value=path_save+'-{}'.format(param), format='str') | |
|
|
158 | opObj10.addParameter(name='Reset',value=True) | |
|
|
159 | opObj10.addParameter(name='setType',value='weather') | |
|
|
160 | opObj10.addParameter(name='description',value='desc') | |
|
|
161 | opObj10.addParameter(name='blocksPerFile',value='1',format='int') | |
|
|
162 | opObj10.addParameter(name='metadataList',value='heightList,data_azi,data_ele') | |
|
|
163 | opObj10.addParameter(name='dataList',value='{},utctime'.format(PARAM[param]['name'])) | |
|
|
164 | ||
|
|
165 | else: #Two pulses | |
|
|
166 | ||
|
|
167 | voltage1 = project.addProcUnit(datatype='VoltageProc', inputId=reader.getId()) | |
|
|
168 | ||
|
|
169 | print("repetions",conf['usrp_tx']['repetitions_1']) | |
|
|
170 | ||
|
|
171 | op = voltage1.addOperation(name='ProfileSelector') | |
|
|
172 | op.addParameter(name='profileRangeList', value='0,{}'.format(conf['usrp_tx']['repetitions_1']-1)) | |
|
|
173 | ||
|
|
174 | ||
|
|
175 | #op3 = voltage1.addOperation(name='ProfileSelector', optype='other') | |
|
|
176 | #op3.addParameter(name='profileRangeList', value='1,123') | |
|
|
177 | ||
|
|
178 | ''' | |
|
|
179 | if conf['usrp_tx']['code_type_1'] != 'None': | |
|
|
180 | code = [c.split() for c in conf['usrp_tx']['code_1']] | |
|
|
181 | op = voltage1.addOperation(name='Decoder', optype='other') | |
|
|
182 | op.addParameter(name='code', value=code) | |
|
|
183 | op.addParameter(name='nCode', value=len(code), format='int') | |
|
|
184 | op.addParameter(name='nBaud', value=len(code[0]), format='int') | |
|
|
185 | ''' | |
|
|
186 | ||
|
|
187 | code=[[1]] | |
|
|
188 | ||
|
|
189 | opObj11 = voltage1.addOperation(name='Decoder', optype='other') | |
|
|
190 | opObj11.addParameter(name='code', value=code) | |
|
|
191 | opObj11.addParameter(name='nCode', value='1', format='int') | |
|
|
192 | opObj11.addParameter(name='nBaud', value='1', format='int') | |
|
|
193 | ||
|
|
194 | op = voltage1.addOperation(name='setH0') | |
|
|
195 | op.addParameter(name='h0', value='-1.2') | |
|
|
196 | ||
|
|
197 | if args.range >= 0: | |
|
|
198 | op = voltage1.addOperation(name='selectHeights') | |
|
|
199 | op.addParameter(name='minIndex', value='0', format='int') | |
|
|
200 | op.addParameter(name='maxIndex', value=max_index(RMIX, sample_rate, ipp), format='int') | |
|
|
201 | ||
|
|
202 | op = voltage1.addOperation(name='CohInt', optype='other') #Minimo integrar 2 perfiles por ser codigo complementario | |
|
|
203 | op.addParameter(name='n', value=2, format='int') | |
|
|
204 | ||
|
|
205 | op = voltage1.addOperation(name='PulsePair_vRF', optype='other') | |
|
|
206 | #op.addParameter(name='n', value=int(N), format='int') | |
|
|
207 | op.addParameter(name='n', value=61, format='int') | |
|
|
208 | #op.addParameter(name='removeDC',value=True) | |
|
|
209 | ||
|
|
210 | ''' | |
|
|
211 | if args.range >= 0: | |
|
|
212 | print("corto",max_index(RMIX, sample_rate, ipp)) | |
|
|
213 | op = voltage1.addOperation(name='selectHeights') | |
|
|
214 | op.addParameter(name='minIndex', value='0', format='int') | |
|
|
215 | op.addParameter(name='maxIndex', value=max_index(RMIX, sample_rate, ipp), format='int') | |
|
|
216 | ''' | |
|
|
217 | proc1 = project.addProcUnit(datatype='ParametersProc', inputId=voltage1.getId()) | |
|
|
218 | proc1.addParameter(name='runNextUnit', value=True) | |
|
|
219 | ||
|
|
220 | opObj10 = proc1.addOperation(name="WeatherRadar") | |
|
|
221 | opObj10.addParameter(name='variableList',value='Reflectividad,VelocidadRadial,AnchoEspectral') | |
|
|
222 | opObj10.addParameter(name='tauW',value=0.4*1e-6) | |
|
|
223 | opObj10.addParameter(name='Pt',value=0.2) | |
|
|
224 | ||
|
|
225 | # {"latitude": -12.0404828587, "longitude": -75.2147483647, "altitude": 3379.2147483647} | |
|
|
226 | ||
|
|
227 | op = proc1.addOperation(name='PedestalInformation') | |
|
|
228 | op.addParameter(name='path', value=path_ped, format='str') | |
|
|
229 | op.addParameter(name='interval', value='0.04') | |
|
|
230 | op.addParameter(name='time_offset', value=time_offset) | |
|
|
231 | op.addParameter(name='az_offset', value=-26.2) | |
|
|
232 | ||
|
|
233 | for param in parameters: | |
|
|
234 | op = proc1.addOperation(name='Block360_vRF4') | |
|
|
235 | op.addParameter(name='attr_data', value=PARAM[param]['name']) | |
|
|
236 | op.addParameter(name='runNextOp', value=True) | |
|
|
237 | ||
|
|
238 | voltage2 = project.addProcUnit(datatype='VoltageProc', inputId=reader.getId()) | |
|
|
239 | ||
|
|
240 | op = voltage2.addOperation(name='ProfileSelector') | |
|
|
241 | op.addParameter(name='profileRangeList', value='{},{}'.format(conf['usrp_tx']['repetitions_1'], conf['usrp_tx']['repetitions_1']+conf['usrp_tx']['repetitions_2']-1)) | |
|
|
242 | ||
|
|
243 | ||
|
|
244 | if conf['usrp_tx']['code_type_2']: | |
|
|
245 | print(conf['usrp_tx']['code_2']) | |
|
|
246 | codes = [ c.strip() for c in conf['usrp_tx']['code_2'].split(',')] | |
|
|
247 | code = [] | |
|
|
248 | for c in codes: | |
|
|
249 | code.append([int(x) for x in c]) | |
|
|
250 | print(code) | |
|
|
251 | print(code[0]) | |
|
|
252 | op = voltage2.addOperation(name='Decoder', optype='other') | |
|
|
253 | op.addParameter(name='code', value=code) | |
|
|
254 | op.addParameter(name='nCode', value=len(code), format='int') | |
|
|
255 | op.addParameter(name='nBaud', value=len(code[0]), format='int') | |
|
|
256 | import numpy | |
|
|
257 | pwcode = numpy.sum(numpy.array(code[0])**2) | |
|
|
258 | print("pwcode",pwcode) | |
|
|
259 | ||
|
|
260 | op = voltage2.addOperation(name='CohInt', optype='other') #Minimo integrar 2 perfiles por ser codigo complementario | |
|
|
261 | op.addParameter(name='n', value=len(code), format='int') | |
|
|
262 | ncode = len(code) | |
|
|
263 | else: | |
|
|
264 | ncode = 1 | |
|
|
265 | ||
|
|
266 | op = voltage2.addOperation(name='setH0') | |
|
|
267 | op.addParameter(name='h0', value='-1.2') | |
|
|
268 | ||
|
|
269 | if args.range >= 0: | |
|
|
270 | if args.range==0: | |
|
|
271 | args.range= ipp_km | |
|
|
272 | op = voltage2.addOperation(name='selectHeights') | |
|
|
273 | op.addParameter(name='minIndex', value=max_index(RMIX, sample_rate, ipp), format='int') | |
|
|
274 | op.addParameter(name='maxIndex', value=max_index(args.range, sample_rate, ipp), format='int') | |
|
|
275 | ||
|
|
276 | #op = voltage2.addOperation(name='PulsePair_vRF', optype='other') | |
|
|
277 | #op.addParameter(name='n', value=int(N)/ncode, format='int') | |
|
|
278 | op = voltage2.addOperation(name='PulsePair_vRF', optype='other') | |
|
|
279 | op.addParameter(name='n', value=64, format='int') | |
|
|
280 | #op.addParameter(name='removeDC',value=True) | |
|
|
281 | ||
|
|
282 | ''' | |
|
|
283 | ||
|
|
284 | if args.range >= 0: | |
|
|
285 | if args.range==0: | |
|
|
286 | args.range= ipp_km | |
|
|
287 | op = voltage2.addOperation(name='selectHeights') | |
|
|
288 | print("largo",max_index(RMIX, sample_rate, ipp)) | |
|
|
289 | print("largo2",max_index(args.range, sample_rate, ipp)) | |
|
|
290 | ||
|
|
291 | op.addParameter(name='minIndex', value=max_index(RMIX, sample_rate, ipp), format='int') | |
|
|
292 | op.addParameter(name='maxIndex', value=max_index(args.range, sample_rate, ipp), format='int') | |
|
|
293 | ''' | |
|
|
294 | ||
|
|
295 | proc2 = project.addProcUnit(datatype='ParametersProc', inputId=voltage2.getId()) | |
|
|
296 | ||
|
|
297 | opObj10 = proc2.addOperation(name="WeatherRadar") | |
|
|
298 | opObj10.addParameter(name='variableList',value='Reflectividad,AnchoEspectral') | |
|
|
299 | opObj10.addParameter(name='tauW',value=6.3*1e-6) | |
|
|
300 | opObj10.addParameter(name='Pt',value=3.2) | |
|
|
301 | ||
|
|
302 | ||
|
|
303 | # {"latitude": -12.0404828587, "longitude": -75.2147483647, "altitude": 3379.2147483647} | |
|
|
304 | ||
|
|
305 | op = proc2.addOperation(name='PedestalInformation') | |
|
|
306 | op.addParameter(name='path', value=path_ped, format='str') | |
|
|
307 | op.addParameter(name='interval', value='0.04') | |
|
|
308 | op.addParameter(name='time_offset', value=time_offset) | |
|
|
309 | op.addParameter(name='az_offset', value=-26.2) | |
|
|
310 | ||
|
|
311 | for param in parameters: | |
|
|
312 | op = proc2.addOperation(name='Block360_vRF4') | |
|
|
313 | #op.addParameter(name='axis', value=','.join(axis)) | |
|
|
314 | op.addParameter(name='attr_data', value=PARAM[param]['name']) | |
|
|
315 | op.addParameter(name='runNextOp', value=True) | |
|
|
316 | ||
|
|
317 | merge = project.addProcUnit(datatype='MergeProc', inputId=[proc1.getId(), proc2.getId()]) | |
|
|
318 | merge.addParameter(name='attr_data', value=PARAM[param]['name']) | |
|
|
319 | merge.addParameter(name='mode', value='7') #RM | |
|
|
320 | ||
|
|
321 | op= merge.addOperation(name='WeatherParamsPlot') | |
|
|
322 | if args.save: op.addParameter(name='save', value=path_plots, format='str') | |
|
|
323 | op.addParameter(name='save_period', value=-1) | |
|
|
324 | op.addParameter(name='show', value=args.show) | |
|
|
325 | op.addParameter(name='channels', value='0,') | |
|
|
326 | op.addParameter(name='zmin', value=PARAM[param]['zmin']) | |
|
|
327 | op.addParameter(name='zmax', value=PARAM[param]['zmax']) | |
|
|
328 | op.addParameter(name='attr_data', value=PARAM[param]['name'], format='str') | |
|
|
329 | op.addParameter(name='labels', value=[PARAM[param]['label']]) | |
|
|
330 | op.addParameter(name='save_code', value=param) | |
|
|
331 | op.addParameter(name='cb_label', value=PARAM[param]['cb_label']) | |
|
|
332 | op.addParameter(name='colormap', value=PARAM[param]['colormap']) | |
|
|
333 | ||
|
|
334 | desc = { | |
|
|
335 | 'Data': { | |
|
|
336 | PARAM[param]['name']: PARAM[param]['label'], | |
|
|
337 | 'utctime': 'time' | |
|
|
338 | }, | |
|
|
339 | 'Metadata': { | |
|
|
340 | 'heightList': 'range', | |
|
|
341 | 'data_azi': 'azimuth', | |
|
|
342 | 'data_ele': 'elevation', | |
|
|
343 | } | |
|
|
344 | } | |
|
|
345 | ||
|
|
346 | if args.save: | |
|
|
347 | opObj10 = merge.addOperation(name='HDFWriter') | |
|
|
348 | opObj10.addParameter(name='path',value=path_save, format='str') | |
|
|
349 | opObj10.addParameter(name='Reset',value=True) | |
|
|
350 | opObj10.addParameter(name='setType',value='weather') | |
|
|
351 | opObj10.addParameter(name='description',value='desc') | |
|
|
352 | opObj10.addParameter(name='blocksPerFile',value='1',format='int') | |
|
|
353 | opObj10.addParameter(name='metadataList',value='heightList,data_azi,data_ele') | |
|
|
354 | opObj10.addParameter(name='dataList',value='{},utctime'.format(PARAM[param]['name'])) | |
|
|
355 | ||
|
|
356 | project.start() | |
|
|
357 | ||
|
|
358 | if __name__ == '__main__': | |
|
|
359 | ||
|
|
360 | parser = argparse.ArgumentParser(description='Script to process SOPHy data.') | |
|
|
361 | parser.add_argument('experiment', | |
|
|
362 | help='Experiment name') | |
|
|
363 | parser.add_argument('--parameters', nargs='*', default=['P'], | |
|
|
364 | help='Variables to process: P, Z, V') | |
|
|
365 | parser.add_argument('--time_offset', default=0, | |
|
|
366 | help='Fix time offset') | |
|
|
367 | parser.add_argument('--range', default=0, type=float, | |
|
|
368 | help='Max range to plot') | |
|
|
369 | parser.add_argument('--save', action='store_true', | |
|
|
370 | help='Create output files') | |
|
|
371 | parser.add_argument('--show', action='store_true', | |
|
|
372 | help='Show matplotlib plot.') | |
|
|
373 | parser.add_argument('--online', action='store_true', | |
|
|
374 | help='Set online mode.') | |
|
|
375 | ||
|
|
376 | args = parser.parse_args() | |
|
|
377 | ||
|
|
378 | main(args) | |
| @@ -0,0 +1,376 | |||
|
|
1 | # SOPHY PROC script | |
|
|
2 | import os, sys, json, argparse | |
|
|
3 | import datetime | |
|
|
4 | import time | |
|
|
5 | ||
|
|
6 | PATH = '/DATA_RM/DATA' | |
|
|
7 | # PATH = '/Users/jespinoza/workspace/data/' | |
|
|
8 | #PATH = '/home/soporte/Documents/HUANCAYO' | |
|
|
9 | PARAM = { | |
|
|
10 | 'P': {'name': 'dataPP_POWER', 'zmin': -50, 'zmax': -15, 'colormap': 'jet', 'label': 'Power', 'wrname': 'Pow','cb_label': 'dB', 'ch':0}, | |
|
|
11 | 'V': {'name': 'dataPP_DOP', 'zmin': -20, 'zmax': 20, 'colormap': 'seismic', 'label': 'Velocity', 'wrname': 'Vel', 'cb_label': 'm/s', 'ch':0}, | |
|
|
12 | 'RH': {'name': 'RhoHV_R', 'zmin': 0, 'zmax': 1, 'colormap': 'jet', 'label': 'Coef.Correlacion', 'wrname':'R', 'cb_label': '*', 'ch':0}, | |
|
|
13 | 'FD': {'name': 'PhiD_P', 'zmin': -180,'zmax': 180,'colormap': 'RdBu_r', 'label': 'Fase Diferencial', 'wrname':'P' , 'cb_label': 'º', 'ch':0}, | |
|
|
14 | 'ZD': {'name': 'Zdb_D', 'zmin': -20, 'zmax': 60, 'colormap': 'viridis','label': 'Reflect.Diferencial','wrname':'D' , 'cb_label': 'dBz','ch':0}, | |
|
|
15 | 'Z': {'name': 'Zdb', 'zmin': -20, 'zmax': 70, 'colormap': 'gist_ncar','label': 'Reflectividad', 'wrname':'Z', 'cb_label': 'dBz','ch':1}, | |
|
|
16 | 'W': {'name': 'Sigmav_W', 'zmin': 0, 'zmax':5, 'colormap': 'viridis','label': 'AnchoEspectral', 'wrname':'S', 'cb_label': 'hz', 'ch':1} | |
|
|
17 | } | |
|
|
18 | ||
|
|
19 | def max_index(r, sample_rate, ipp): | |
|
|
20 | ||
|
|
21 | return int(sample_rate*ipp*1e6 * r / 60) + int(sample_rate*ipp*1e6 * 1.2 / 60) | |
|
|
22 | ||
|
|
23 | def main(args): | |
|
|
24 | ||
|
|
25 | experiment = args.experiment | |
|
|
26 | fp = open(os.path.join(PATH, experiment, 'experiment.conf')) | |
|
|
27 | conf = json.loads(fp.read()) | |
|
|
28 | ||
|
|
29 | ipp_km = conf['usrp_tx']['ipp'] | |
|
|
30 | ipp = ipp_km * 2 /300000 | |
|
|
31 | sample_rate = conf['usrp_rx']['sample_rate'] | |
|
|
32 | axis = ['0' if x=='elevation' else '1' for x in conf['pedestal']['axis']] # AZIMUTH 1 ELEVACION 0 | |
|
|
33 | speed_axis = conf['pedestal']['speed'] | |
|
|
34 | steeps = conf['pedestal']['table'] | |
|
|
35 | time_offset = args.time_offset | |
|
|
36 | parameters = args.parameters | |
|
|
37 | start_date = experiment.split('@')[1].split('T')[0].replace('-', '/') | |
|
|
38 | end_date = start_date | |
|
|
39 | start_time = experiment.split('@')[1].split('T')[1].replace('-', ':') | |
|
|
40 | end_time = '23:59:59' | |
|
|
41 | N = int(1/(speed_axis[0]*ipp)) # 1 GRADO DE RESOLUCION | |
|
|
42 | path = os.path.join(PATH, experiment, 'rawdata') | |
|
|
43 | path_ped = os.path.join(PATH, experiment, 'position') | |
|
|
44 | path_plots = os.path.join(PATH, experiment, 'plots_ch1') | |
|
|
45 | path_save = os.path.join(PATH, experiment, 'param') | |
|
|
46 | RMIX = 2 | |
|
|
47 | ||
|
|
48 | from schainpy.controller import Project | |
|
|
49 | ||
|
|
50 | project = Project() | |
|
|
51 | project.setup(id='1', name='Sophy', description='sophy proc') | |
|
|
52 | ||
|
|
53 | reader = project.addReadUnit(datatype='DigitalRFReader', | |
|
|
54 | path=path, | |
|
|
55 | startDate=start_date, | |
|
|
56 | endDate=end_date, | |
|
|
57 | startTime=start_time, | |
|
|
58 | endTime=end_time, | |
|
|
59 | delay=30, | |
|
|
60 | channelList='0', | |
|
|
61 | online=args.online, | |
|
|
62 | walk=1, | |
|
|
63 | ippKm = ipp_km, | |
|
|
64 | getByBlock = 1, | |
|
|
65 | nProfileBlocks = N, | |
|
|
66 | ) | |
|
|
67 | ||
|
|
68 | if not conf['usrp_tx']['enable_2']: # One Pulse | |
|
|
69 | voltage = project.addProcUnit(datatype='VoltageProc', inputId=reader.getId()) | |
|
|
70 | ||
|
|
71 | if conf['usrp_tx']['code_type_1']: | |
|
|
72 | code = [c.split() for c in conf['usrp']['code_1']] | |
|
|
73 | op = voltage.addOperation(name='Decoder', optype='other') | |
|
|
74 | op.addParameter(name='code', value=code) | |
|
|
75 | op.addParameter(name='nCode', value=len(code), format='int') | |
|
|
76 | op.addParameter(name='nBaud', value=len(code[0]), format='int') | |
|
|
77 | ||
|
|
78 | op = voltage.addOperation(name='setH0') | |
|
|
79 | op.addParameter(name='h0', value='-1.2') | |
|
|
80 | ||
|
|
81 | if args.range >= 0: | |
|
|
82 | op = voltage.addOperation(name='selectHeights') | |
|
|
83 | op.addParameter(name='minIndex', value='0', format='int') | |
|
|
84 | op.addParameter(name='maxIndex', value=max_index(RMIX, sample_rate, ipp), format='int') | |
|
|
85 | ||
|
|
86 | code=[[1]] | |
|
|
87 | opObj11 = voltage.addOperation(name='Decoder', optype='other') | |
|
|
88 | opObj11.addParameter(name='code', value=code) | |
|
|
89 | opObj11.addParameter(name='nCode', value='1', format='int') | |
|
|
90 | opObj11.addParameter(name='nBaud', value='1', format='int') | |
|
|
91 | ||
|
|
92 | op = voltage2.addOperation(name='CohInt', optype='other') #Minimo integrar 2 perfiles por ser codigo complementario | |
|
|
93 | op.addParameter(name='n', value=2*len(code), format='int') | |
|
|
94 | ||
|
|
95 | #op = voltage.addOperation(name='PulsePair_vRF', optype='other') | |
|
|
96 | #op.addParameter(name='n', value=int(N), format='int') | |
|
|
97 | ||
|
|
98 | if args.range >= 0: | |
|
|
99 | op = voltage.addOperation(name='selectHeights') | |
|
|
100 | op.addParameter(name='minIndex', value='0', format='int') | |
|
|
101 | op.addParameter(name='maxIndex', value=max_index(RMIX, sample_rate, ipp), format='int') | |
|
|
102 | ||
|
|
103 | ||
|
|
104 | op = voltage.addOperation(name='PulsePair_vRF', optype='other') | |
|
|
105 | op.addParameter(name='n', value=125, format='int') | |
|
|
106 | ||
|
|
107 | ||
|
|
108 | proc = project.addProcUnit(datatype='ParametersProc', inputId=voltage.getId()) | |
|
|
109 | #procUnitConfObjB.addParameter(name='runNextUnit', value=True) | |
|
|
110 | ||
|
|
111 | opObj10 = proc.addOperation(name="WeatherRadar") | |
|
|
112 | opObj10.addParameter(name='variableList',value='Reflectividad,VelocidadRadial,AnchoEspectral') | |
|
|
113 | ||
|
|
114 | # {"latitude": -12.0404828587, "longitude": -75.2147483647, "altitude": 3379.2147483647} | |
|
|
115 | ||
|
|
116 | op = proc.addOperation(name='PedestalInformation') | |
|
|
117 | op.addParameter(name='path', value=path_ped, format='str') | |
|
|
118 | op.addParameter(name='interval', value='0.04') | |
|
|
119 | op.addParameter(name='time_offset', value=time_offset) | |
|
|
120 | op.addParameter(name='az_offset', value=-26.2) | |
|
|
121 | ||
|
|
122 | for param in parameters: | |
|
|
123 | op = proc.addOperation(name='Block360_vRF4') | |
|
|
124 | #op.addParameter(name='axis', value=','.join(axis)) | |
|
|
125 | op.addParameter(name='attr_data', value=PARAM[param]['name']) | |
|
|
126 | op.addParameter(name='runNextOp', value=True) | |
|
|
127 | ||
|
|
128 | op= proc.addOperation(name='WeatherParamsPlot') | |
|
|
129 | if args.save: op.addParameter(name='save', value=path_plots, format='str') | |
|
|
130 | op.addParameter(name='save_period', value=-1) | |
|
|
131 | op.addParameter(name='show', value=args.show) | |
|
|
132 | op.addParameter(name='channels', value='1,') | |
|
|
133 | op.addParameter(name='zmin', value=PARAM[param]['zmin']) | |
|
|
134 | op.addParameter(name='zmax', value=PARAM[param]['zmax']) | |
|
|
135 | op.addParameter(name='attr_data', value=PARAM[param]['name'], format='str') | |
|
|
136 | op.addParameter(name='labels', value=[PARAM[param]['label']]) | |
|
|
137 | op.addParameter(name='save_code', value=param) | |
|
|
138 | op.addParameter(name='cb_label', value=PARAM[param]['cb_label']) | |
|
|
139 | op.addParameter(name='colormap', value=PARAM[param]['colormap']) | |
|
|
140 | ||
|
|
141 | desc = { | |
|
|
142 | 'Data': { | |
|
|
143 | PARAM[param]['name']: PARAM[param]['label'], | |
|
|
144 | 'utctime': 'time' | |
|
|
145 | }, | |
|
|
146 | 'Metadata': { | |
|
|
147 | 'heightList': 'range', | |
|
|
148 | 'data_azi': 'azimuth', | |
|
|
149 | 'data_ele': 'elevation', | |
|
|
150 | } | |
|
|
151 | } | |
|
|
152 | ||
|
|
153 | if args.save: | |
|
|
154 | opObj10 = proc.addOperation(name='HDFWriter') | |
|
|
155 | opObj10.addParameter(name='path',value=path_save+'-{}'.format(param), format='str') | |
|
|
156 | opObj10.addParameter(name='Reset',value=True) | |
|
|
157 | opObj10.addParameter(name='setType',value='weather') | |
|
|
158 | opObj10.addParameter(name='description',value='desc') | |
|
|
159 | opObj10.addParameter(name='blocksPerFile',value='1',format='int') | |
|
|
160 | opObj10.addParameter(name='metadataList',value='heightList,data_azi,data_ele') | |
|
|
161 | opObj10.addParameter(name='dataList',value='{},utctime'.format(PARAM[param]['name'])) | |
|
|
162 | ||
|
|
163 | else: #Two pulses | |
|
|
164 | ||
|
|
165 | voltage1 = project.addProcUnit(datatype='VoltageProc', inputId=reader.getId()) | |
|
|
166 | ||
|
|
167 | print("repetions",conf['usrp_tx']['repetitions_1']) | |
|
|
168 | ||
|
|
169 | op = voltage1.addOperation(name='ProfileSelector') | |
|
|
170 | op.addParameter(name='profileRangeList', value='0,{}'.format(conf['usrp_tx']['repetitions_1']-1)) | |
|
|
171 | ||
|
|
172 | ||
|
|
173 | #op3 = voltage1.addOperation(name='ProfileSelector', optype='other') | |
|
|
174 | #op3.addParameter(name='profileRangeList', value='1,123') | |
|
|
175 | ||
|
|
176 | ''' | |
|
|
177 | if conf['usrp_tx']['code_type_1'] != 'None': | |
|
|
178 | code = [c.split() for c in conf['usrp_tx']['code_1']] | |
|
|
179 | op = voltage1.addOperation(name='Decoder', optype='other') | |
|
|
180 | op.addParameter(name='code', value=code) | |
|
|
181 | op.addParameter(name='nCode', value=len(code), format='int') | |
|
|
182 | op.addParameter(name='nBaud', value=len(code[0]), format='int') | |
|
|
183 | ''' | |
|
|
184 | ||
|
|
185 | code=[[1]] | |
|
|
186 | ||
|
|
187 | opObj11 = voltage1.addOperation(name='Decoder', optype='other') | |
|
|
188 | opObj11.addParameter(name='code', value=code) | |
|
|
189 | opObj11.addParameter(name='nCode', value='1', format='int') | |
|
|
190 | opObj11.addParameter(name='nBaud', value='1', format='int') | |
|
|
191 | ||
|
|
192 | op = voltage1.addOperation(name='setH0') | |
|
|
193 | op.addParameter(name='h0', value='-1.2') | |
|
|
194 | ||
|
|
195 | if args.range >= 0: | |
|
|
196 | op = voltage1.addOperation(name='selectHeights') | |
|
|
197 | op.addParameter(name='minIndex', value='0', format='int') | |
|
|
198 | op.addParameter(name='maxIndex', value=max_index(RMIX, sample_rate, ipp), format='int') | |
|
|
199 | ||
|
|
200 | op = voltage1.addOperation(name='CohInt', optype='other') #Minimo integrar 2 perfiles por ser codigo complementario | |
|
|
201 | op.addParameter(name='n', value=2, format='int') | |
|
|
202 | ||
|
|
203 | op = voltage1.addOperation(name='PulsePair_vRF', optype='other') | |
|
|
204 | #op.addParameter(name='n', value=int(N), format='int') | |
|
|
205 | op.addParameter(name='n', value=61, format='int') | |
|
|
206 | #op.addParameter(name='removeDC',value=True) | |
|
|
207 | ||
|
|
208 | ''' | |
|
|
209 | if args.range >= 0: | |
|
|
210 | print("corto",max_index(RMIX, sample_rate, ipp)) | |
|
|
211 | op = voltage1.addOperation(name='selectHeights') | |
|
|
212 | op.addParameter(name='minIndex', value='0', format='int') | |
|
|
213 | op.addParameter(name='maxIndex', value=max_index(RMIX, sample_rate, ipp), format='int') | |
|
|
214 | ''' | |
|
|
215 | proc1 = project.addProcUnit(datatype='ParametersProc', inputId=voltage1.getId()) | |
|
|
216 | proc1.addParameter(name='runNextUnit', value=True) | |
|
|
217 | ||
|
|
218 | opObj10 = proc1.addOperation(name="WeatherRadar") | |
|
|
219 | opObj10.addParameter(name='variableList',value='Reflectividad,VelocidadRadial,AnchoEspectral') | |
|
|
220 | opObj10.addParameter(name='tauW',value=0.4*1e-6) | |
|
|
221 | opObj10.addParameter(name='Pt',value=0.2) | |
|
|
222 | ||
|
|
223 | # {"latitude": -12.0404828587, "longitude": -75.2147483647, "altitude": 3379.2147483647} | |
|
|
224 | ||
|
|
225 | op = proc1.addOperation(name='PedestalInformation') | |
|
|
226 | op.addParameter(name='path', value=path_ped, format='str') | |
|
|
227 | op.addParameter(name='interval', value='0.04') | |
|
|
228 | op.addParameter(name='time_offset', value=time_offset) | |
|
|
229 | op.addParameter(name='az_offset', value=-26.2) | |
|
|
230 | ||
|
|
231 | for param in parameters: | |
|
|
232 | op = proc1.addOperation(name='Block360_vRF4') | |
|
|
233 | op.addParameter(name='attr_data', value=PARAM[param]['name']) | |
|
|
234 | op.addParameter(name='runNextOp', value=True) | |
|
|
235 | ||
|
|
236 | voltage2 = project.addProcUnit(datatype='VoltageProc', inputId=reader.getId()) | |
|
|
237 | ||
|
|
238 | op = voltage2.addOperation(name='ProfileSelector') | |
|
|
239 | op.addParameter(name='profileRangeList', value='{},{}'.format(conf['usrp_tx']['repetitions_1'], conf['usrp_tx']['repetitions_1']+conf['usrp_tx']['repetitions_2']-1)) | |
|
|
240 | ||
|
|
241 | ||
|
|
242 | if conf['usrp_tx']['code_type_2']: | |
|
|
243 | print(conf['usrp_tx']['code_2']) | |
|
|
244 | codes = [ c.strip() for c in conf['usrp_tx']['code_2'].split(',')] | |
|
|
245 | code = [] | |
|
|
246 | for c in codes: | |
|
|
247 | code.append([int(x) for x in c]) | |
|
|
248 | print(code) | |
|
|
249 | print(code[0]) | |
|
|
250 | op = voltage2.addOperation(name='Decoder', optype='other') | |
|
|
251 | op.addParameter(name='code', value=code) | |
|
|
252 | op.addParameter(name='nCode', value=len(code), format='int') | |
|
|
253 | op.addParameter(name='nBaud', value=len(code[0]), format='int') | |
|
|
254 | import numpy | |
|
|
255 | pwcode = numpy.sum(numpy.array(code[0])**2) | |
|
|
256 | print("pwcode",pwcode) | |
|
|
257 | ||
|
|
258 | op = voltage2.addOperation(name='CohInt', optype='other') #Minimo integrar 2 perfiles por ser codigo complementario | |
|
|
259 | op.addParameter(name='n', value=len(code), format='int') | |
|
|
260 | ncode = len(code) | |
|
|
261 | else: | |
|
|
262 | ncode = 1 | |
|
|
263 | ||
|
|
264 | op = voltage2.addOperation(name='setH0') | |
|
|
265 | op.addParameter(name='h0', value='-1.2') | |
|
|
266 | ||
|
|
267 | if args.range >= 0: | |
|
|
268 | if args.range==0: | |
|
|
269 | args.range= ipp_km | |
|
|
270 | op = voltage2.addOperation(name='selectHeights') | |
|
|
271 | op.addParameter(name='minIndex', value=max_index(RMIX, sample_rate, ipp), format='int') | |
|
|
272 | op.addParameter(name='maxIndex', value=max_index(args.range, sample_rate, ipp), format='int') | |
|
|
273 | ||
|
|
274 | #op = voltage2.addOperation(name='PulsePair_vRF', optype='other') | |
|
|
275 | #op.addParameter(name='n', value=int(N)/ncode, format='int') | |
|
|
276 | op = voltage2.addOperation(name='PulsePair_vRF', optype='other') | |
|
|
277 | op.addParameter(name='n', value=64, format='int') | |
|
|
278 | #op.addParameter(name='removeDC',value=True) | |
|
|
279 | ||
|
|
280 | ''' | |
|
|
281 | ||
|
|
282 | if args.range >= 0: | |
|
|
283 | if args.range==0: | |
|
|
284 | args.range= ipp_km | |
|
|
285 | op = voltage2.addOperation(name='selectHeights') | |
|
|
286 | print("largo",max_index(RMIX, sample_rate, ipp)) | |
|
|
287 | print("largo2",max_index(args.range, sample_rate, ipp)) | |
|
|
288 | ||
|
|
289 | op.addParameter(name='minIndex', value=max_index(RMIX, sample_rate, ipp), format='int') | |
|
|
290 | op.addParameter(name='maxIndex', value=max_index(args.range, sample_rate, ipp), format='int') | |
|
|
291 | ''' | |
|
|
292 | ||
|
|
293 | proc2 = project.addProcUnit(datatype='ParametersProc', inputId=voltage2.getId()) | |
|
|
294 | ||
|
|
295 | opObj10 = proc2.addOperation(name="WeatherRadar") | |
|
|
296 | opObj10.addParameter(name='variableList',value='Reflectividad,AnchoEspectral') | |
|
|
297 | opObj10.addParameter(name='tauW',value=3.2*1e-6) | |
|
|
298 | opObj10.addParameter(name='Pt',value=1.6) | |
|
|
299 | ||
|
|
300 | ||
|
|
301 | # {"latitude": -12.0404828587, "longitude": -75.2147483647, "altitude": 3379.2147483647} | |
|
|
302 | ||
|
|
303 | op = proc2.addOperation(name='PedestalInformation') | |
|
|
304 | op.addParameter(name='path', value=path_ped, format='str') | |
|
|
305 | op.addParameter(name='interval', value='0.04') | |
|
|
306 | op.addParameter(name='time_offset', value=time_offset) | |
|
|
307 | op.addParameter(name='az_offset', value=-26.2) | |
|
|
308 | ||
|
|
309 | for param in parameters: | |
|
|
310 | op = proc2.addOperation(name='Block360_vRF4') | |
|
|
311 | #op.addParameter(name='axis', value=','.join(axis)) | |
|
|
312 | op.addParameter(name='attr_data', value=PARAM[param]['name']) | |
|
|
313 | op.addParameter(name='runNextOp', value=True) | |
|
|
314 | ||
|
|
315 | merge = project.addProcUnit(datatype='MergeProc', inputId=[proc1.getId(), proc2.getId()]) | |
|
|
316 | merge.addParameter(name='attr_data', value=PARAM[param]['name']) | |
|
|
317 | merge.addParameter(name='mode', value='7') #RM | |
|
|
318 | ||
|
|
319 | op= merge.addOperation(name='WeatherParamsPlot') | |
|
|
320 | if args.save: op.addParameter(name='save', value=path_plots, format='str') | |
|
|
321 | op.addParameter(name='save_period', value=-1) | |
|
|
322 | op.addParameter(name='show', value=args.show) | |
|
|
323 | op.addParameter(name='channels', value='1,') | |
|
|
324 | op.addParameter(name='zmin', value=PARAM[param]['zmin']) | |
|
|
325 | op.addParameter(name='zmax', value=PARAM[param]['zmax']) | |
|
|
326 | op.addParameter(name='attr_data', value=PARAM[param]['name'], format='str') | |
|
|
327 | op.addParameter(name='labels', value=[PARAM[param]['label']]) | |
|
|
328 | op.addParameter(name='save_code', value=param) | |
|
|
329 | op.addParameter(name='cb_label', value=PARAM[param]['cb_label']) | |
|
|
330 | op.addParameter(name='colormap', value=PARAM[param]['colormap']) | |
|
|
331 | ||
|
|
332 | desc = { | |
|
|
333 | 'Data': { | |
|
|
334 | PARAM[param]['name']: PARAM[param]['label'], | |
|
|
335 | 'utctime': 'time' | |
|
|
336 | }, | |
|
|
337 | 'Metadata': { | |
|
|
338 | 'heightList': 'range', | |
|
|
339 | 'data_azi': 'azimuth', | |
|
|
340 | 'data_ele': 'elevation', | |
|
|
341 | } | |
|
|
342 | } | |
|
|
343 | ||
|
|
344 | if args.save: | |
|
|
345 | opObj10 = merge.addOperation(name='HDFWriter') | |
|
|
346 | opObj10.addParameter(name='path',value=path_save, format='str') | |
|
|
347 | opObj10.addParameter(name='Reset',value=True) | |
|
|
348 | opObj10.addParameter(name='setType',value='weather') | |
|
|
349 | opObj10.addParameter(name='description',value='desc') | |
|
|
350 | opObj10.addParameter(name='blocksPerFile',value='1',format='int') | |
|
|
351 | opObj10.addParameter(name='metadataList',value='heightList,data_azi,data_ele') | |
|
|
352 | opObj10.addParameter(name='dataList',value='{},utctime'.format(PARAM[param]['name'])) | |
|
|
353 | ||
|
|
354 | project.start() | |
|
|
355 | ||
|
|
356 | if __name__ == '__main__': | |
|
|
357 | ||
|
|
358 | parser = argparse.ArgumentParser(description='Script to process SOPHy data.') | |
|
|
359 | parser.add_argument('experiment', | |
|
|
360 | help='Experiment name') | |
|
|
361 | parser.add_argument('--parameters', nargs='*', default=['P'], | |
|
|
362 | help='Variables to process: P, Z, V') | |
|
|
363 | parser.add_argument('--time_offset', default=0, | |
|
|
364 | help='Fix time offset') | |
|
|
365 | parser.add_argument('--range', default=0, type=float, | |
|
|
366 | help='Max range to plot') | |
|
|
367 | parser.add_argument('--save', action='store_true', | |
|
|
368 | help='Create output files') | |
|
|
369 | parser.add_argument('--show', action='store_true', | |
|
|
370 | help='Show matplotlib plot.') | |
|
|
371 | parser.add_argument('--online', action='store_true', | |
|
|
372 | help='Set online mode.') | |
|
|
373 | ||
|
|
374 | args = parser.parse_args() | |
|
|
375 | ||
|
|
376 | main(args) | |
| @@ -1,716 +1,739 | |||
|
|
1 | 1 | # Copyright (c) 2012-2020 Jicamarca Radio Observatory |
|
|
2 | 2 | # All rights reserved. |
|
|
3 | 3 | # |
|
|
4 | 4 | # Distributed under the terms of the BSD 3-clause license. |
|
|
5 | 5 | """Base class to create plot operations |
|
|
6 | 6 | |
|
|
7 | 7 | """ |
|
|
8 | 8 | |
|
|
9 | 9 | import os |
|
|
10 | 10 | import sys |
|
|
11 | 11 | import zmq |
|
|
12 | 12 | import time |
|
|
13 | 13 | import numpy |
|
|
14 | 14 | import datetime |
|
|
15 | 15 | from collections import deque |
|
|
16 | 16 | from functools import wraps |
|
|
17 | 17 | from threading import Thread |
|
|
18 | import matplotlib | |
|
|
18 | import matplotlib,re | |
|
|
19 | 19 | |
|
|
20 | 20 | if 'BACKEND' in os.environ: |
|
|
21 | 21 | matplotlib.use(os.environ['BACKEND']) |
|
|
22 | 22 | elif 'linux' in sys.platform: |
|
|
23 |
matplotlib.use(" |
|
|
|
23 | matplotlib.use("Agg")#TkAgg | |
|
|
24 | 24 | elif 'darwin' in sys.platform: |
|
|
25 | 25 | matplotlib.use('MacOSX') |
|
|
26 | 26 | else: |
|
|
27 | 27 | from schainpy.utils import log |
|
|
28 | 28 | log.warning('Using default Backend="Agg"', 'INFO') |
|
|
29 | 29 | matplotlib.use('Agg') |
|
|
30 | 30 | |
|
|
31 | 31 | import matplotlib.pyplot as plt |
|
|
32 | 32 | from matplotlib.patches import Polygon |
|
|
33 | 33 | from mpl_toolkits.axes_grid1 import make_axes_locatable |
|
|
34 | 34 | from matplotlib.ticker import FuncFormatter, LinearLocator, MultipleLocator |
|
|
35 | 35 | |
|
|
36 | 36 | from schainpy.model.data.jrodata import PlotterData |
|
|
37 | 37 | from schainpy.model.proc.jroproc_base import ProcessingUnit, Operation, MPDecorator |
|
|
38 | 38 | from schainpy.utils import log |
|
|
39 | 39 | |
|
|
40 | 40 | jet_values = matplotlib.pyplot.get_cmap('jet', 100)(numpy.arange(100))[10:90] |
|
|
41 | 41 | blu_values = matplotlib.pyplot.get_cmap( |
|
|
42 | 42 | 'seismic_r', 20)(numpy.arange(20))[10:15] |
|
|
43 | 43 | ncmap = matplotlib.colors.LinearSegmentedColormap.from_list( |
|
|
44 | 44 | 'jro', numpy.vstack((blu_values, jet_values))) |
|
|
45 | 45 | matplotlib.pyplot.register_cmap(cmap=ncmap) |
|
|
46 | 46 | |
|
|
47 | rwg=matplotlib.colors.LinearSegmentedColormap.from_list('rwg',["r", "w", "g"], N=256) | |
|
|
48 | matplotlib.pyplot.register_cmap(cmap=rwg) | |
|
|
49 | ||
|
|
47 | 50 | CMAPS = [plt.get_cmap(s) for s in ('jro', 'jet', 'viridis', |
|
|
48 | 'plasma', 'inferno', 'Greys', 'seismic', 'bwr', 'coolwarm')] | |
|
|
51 | 'plasma', 'inferno', 'Greys', 'seismic', 'bwr', 'coolwarm','rwg')] | |
|
|
49 | 52 | |
|
|
50 | 53 | EARTH_RADIUS = 6.3710e3 |
|
|
51 | 54 | |
|
|
52 | 55 | def ll2xy(lat1, lon1, lat2, lon2): |
|
|
53 | 56 | |
|
|
54 | 57 | p = 0.017453292519943295 |
|
|
55 | 58 | a = 0.5 - numpy.cos((lat2 - lat1) * p)/2 + numpy.cos(lat1 * p) * \ |
|
|
56 | 59 | numpy.cos(lat2 * p) * (1 - numpy.cos((lon2 - lon1) * p)) / 2 |
|
|
57 | 60 | r = 12742 * numpy.arcsin(numpy.sqrt(a)) |
|
|
58 | 61 | theta = numpy.arctan2(numpy.sin((lon2-lon1)*p)*numpy.cos(lat2*p), numpy.cos(lat1*p) |
|
|
59 | 62 | * numpy.sin(lat2*p)-numpy.sin(lat1*p)*numpy.cos(lat2*p)*numpy.cos((lon2-lon1)*p)) |
|
|
60 | 63 | theta = -theta + numpy.pi/2 |
|
|
61 | 64 | return r*numpy.cos(theta), r*numpy.sin(theta) |
|
|
62 | 65 | |
|
|
63 | 66 | |
|
|
64 | 67 | def km2deg(km): |
|
|
65 | 68 | ''' |
|
|
66 | 69 | Convert distance in km to degrees |
|
|
67 | 70 | ''' |
|
|
68 | 71 | |
|
|
69 | 72 | return numpy.rad2deg(km/EARTH_RADIUS) |
|
|
70 | 73 | |
|
|
71 | 74 | |
|
|
72 | 75 | def figpause(interval): |
|
|
73 | 76 | backend = plt.rcParams['backend'] |
|
|
74 | 77 | if backend in matplotlib.rcsetup.interactive_bk: |
|
|
75 | 78 | figManager = matplotlib._pylab_helpers.Gcf.get_active() |
|
|
76 | 79 | if figManager is not None: |
|
|
77 | 80 | canvas = figManager.canvas |
|
|
78 | 81 | if canvas.figure.stale: |
|
|
79 | 82 | canvas.draw() |
|
|
80 | 83 | try: |
|
|
81 | 84 | canvas.start_event_loop(interval) |
|
|
82 | 85 | except: |
|
|
83 | 86 | pass |
|
|
84 | 87 | return |
|
|
85 | 88 | |
|
|
86 | 89 | def popup(message): |
|
|
87 | 90 | ''' |
|
|
88 | 91 | ''' |
|
|
89 | 92 | |
|
|
90 | 93 | fig = plt.figure(figsize=(12, 8), facecolor='r') |
|
|
91 | 94 | text = '\n'.join([s.strip() for s in message.split(':')]) |
|
|
92 | 95 | fig.text(0.01, 0.5, text, ha='left', va='center', |
|
|
93 | 96 | size='20', weight='heavy', color='w') |
|
|
94 | 97 | fig.show() |
|
|
95 | 98 | figpause(1000) |
|
|
96 | 99 | |
|
|
97 | 100 | |
|
|
98 | 101 | class Throttle(object): |
|
|
99 | 102 | ''' |
|
|
100 | 103 | Decorator that prevents a function from being called more than once every |
|
|
101 | 104 | time period. |
|
|
102 | 105 | To create a function that cannot be called more than once a minute, but |
|
|
103 | 106 | will sleep until it can be called: |
|
|
104 | 107 | @Throttle(minutes=1) |
|
|
105 | 108 | def foo(): |
|
|
106 | 109 | pass |
|
|
107 | 110 | |
|
|
108 | 111 | for i in range(10): |
|
|
109 | 112 | foo() |
|
|
110 | 113 | print "This function has run %s times." % i |
|
|
111 | 114 | ''' |
|
|
112 | 115 | |
|
|
113 | 116 | def __init__(self, seconds=0, minutes=0, hours=0): |
|
|
114 | 117 | self.throttle_period = datetime.timedelta( |
|
|
115 | 118 | seconds=seconds, minutes=minutes, hours=hours |
|
|
116 | 119 | ) |
|
|
117 | 120 | |
|
|
118 | 121 | self.time_of_last_call = datetime.datetime.min |
|
|
119 | 122 | |
|
|
120 | 123 | def __call__(self, fn): |
|
|
121 | 124 | @wraps(fn) |
|
|
122 | 125 | def wrapper(*args, **kwargs): |
|
|
123 | 126 | coerce = kwargs.pop('coerce', None) |
|
|
124 | 127 | if coerce: |
|
|
125 | 128 | self.time_of_last_call = datetime.datetime.now() |
|
|
126 | 129 | return fn(*args, **kwargs) |
|
|
127 | 130 | else: |
|
|
128 | 131 | now = datetime.datetime.now() |
|
|
129 | 132 | time_since_last_call = now - self.time_of_last_call |
|
|
130 | 133 | time_left = self.throttle_period - time_since_last_call |
|
|
131 | 134 | |
|
|
132 | 135 | if time_left > datetime.timedelta(seconds=0): |
|
|
133 | 136 | return |
|
|
134 | 137 | |
|
|
135 | 138 | self.time_of_last_call = datetime.datetime.now() |
|
|
136 | 139 | return fn(*args, **kwargs) |
|
|
137 | 140 | |
|
|
138 | 141 | return wrapper |
|
|
139 | 142 | |
|
|
140 | 143 | def apply_throttle(value): |
|
|
141 | 144 | |
|
|
142 | 145 | @Throttle(seconds=value) |
|
|
143 | 146 | def fnThrottled(fn): |
|
|
144 | 147 | fn() |
|
|
145 | 148 | |
|
|
146 | 149 | return fnThrottled |
|
|
147 | 150 | |
|
|
148 | 151 | |
|
|
149 | 152 | @MPDecorator |
|
|
150 | 153 | class Plot(Operation): |
|
|
151 | 154 | """Base class for Schain plotting operations |
|
|
152 | 155 | |
|
|
153 | 156 | This class should never be use directtly you must subclass a new operation, |
|
|
154 | 157 | children classes must be defined as follow: |
|
|
155 | 158 | |
|
|
156 | 159 | ExamplePlot(Plot): |
|
|
157 | 160 | |
|
|
158 | 161 | CODE = 'code' |
|
|
159 | 162 | colormap = 'jet' |
|
|
160 | 163 | plot_type = 'pcolor' # options are ('pcolor', 'pcolorbuffer', 'scatter', 'scatterbuffer') |
|
|
161 | 164 | |
|
|
162 | 165 | def setup(self): |
|
|
163 | 166 | pass |
|
|
164 | 167 | |
|
|
165 | 168 | def plot(self): |
|
|
166 | 169 | pass |
|
|
167 | 170 | |
|
|
168 | 171 | """ |
|
|
169 | 172 | |
|
|
170 | 173 | CODE = 'Figure' |
|
|
171 | 174 | colormap = 'jet' |
|
|
172 | 175 | bgcolor = 'white' |
|
|
173 | 176 | buffering = True |
|
|
174 | 177 | __missing = 1E30 |
|
|
175 | 178 | |
|
|
176 | 179 | __attrs__ = ['show', 'save', 'ymin', 'ymax', 'zmin', 'zmax', 'title', |
|
|
177 | 180 | 'showprofile'] |
|
|
178 | 181 | |
|
|
179 | 182 | def __init__(self): |
|
|
180 | 183 | |
|
|
181 | 184 | Operation.__init__(self) |
|
|
182 | 185 | self.isConfig = False |
|
|
183 | 186 | self.isPlotConfig = False |
|
|
184 | 187 | self.save_time = 0 |
|
|
185 | 188 | self.sender_time = 0 |
|
|
186 | 189 | self.data = None |
|
|
187 | 190 | self.firsttime = True |
|
|
188 | 191 | self.sender_queue = deque(maxlen=10) |
|
|
189 | 192 | self.plots_adjust = {'left': 0.125, 'right': 0.9, 'bottom': 0.15, 'top': 0.9, 'wspace': 0.2, 'hspace': 0.2} |
|
|
190 | 193 | |
|
|
191 | 194 | def __fmtTime(self, x, pos): |
|
|
192 | 195 | ''' |
|
|
193 | 196 | ''' |
|
|
194 | 197 | |
|
|
195 | 198 | return '{}'.format(self.getDateTime(x).strftime('%H:%M')) |
|
|
196 | 199 | |
|
|
197 | 200 | def __setup(self, **kwargs): |
|
|
198 | 201 | ''' |
|
|
199 | 202 | Initialize variables |
|
|
200 | 203 | ''' |
|
|
201 | 204 | |
|
|
202 | 205 | self.figures = [] |
|
|
203 | 206 | self.axes = [] |
|
|
204 | 207 | self.cb_axes = [] |
|
|
205 | 208 | self.localtime = kwargs.pop('localtime', True) |
|
|
206 | 209 | self.show = kwargs.get('show', True) |
|
|
207 | 210 | self.save = kwargs.get('save', False) |
|
|
208 | 211 | self.save_period = kwargs.get('save_period', 0) |
|
|
209 | 212 | self.colormap = kwargs.get('colormap', self.colormap) |
|
|
210 | 213 | self.colormap_coh = kwargs.get('colormap_coh', 'jet') |
|
|
211 | 214 | self.colormap_phase = kwargs.get('colormap_phase', 'RdBu_r') |
|
|
212 | 215 | self.colormaps = kwargs.get('colormaps', None) |
|
|
213 | 216 | self.bgcolor = kwargs.get('bgcolor', self.bgcolor) |
|
|
214 | 217 | self.showprofile = kwargs.get('showprofile', False) |
|
|
215 | 218 | self.title = kwargs.get('wintitle', self.CODE.upper()) |
|
|
216 | 219 | self.cb_label = kwargs.get('cb_label', None) |
|
|
217 | 220 | self.cb_labels = kwargs.get('cb_labels', None) |
|
|
218 | 221 | self.labels = kwargs.get('labels', None) |
|
|
219 | 222 | self.xaxis = kwargs.get('xaxis', 'frequency') |
|
|
220 | 223 | self.zmin = kwargs.get('zmin', None) |
|
|
221 | 224 | self.zmax = kwargs.get('zmax', None) |
|
|
222 | 225 | self.zlimits = kwargs.get('zlimits', None) |
|
|
223 | 226 | self.xmin = kwargs.get('xmin', None) |
|
|
224 | 227 | self.xmax = kwargs.get('xmax', None) |
|
|
225 | 228 | self.xrange = kwargs.get('xrange', 12) |
|
|
226 | 229 | self.xscale = kwargs.get('xscale', None) |
|
|
227 | 230 | self.ymin = kwargs.get('ymin', None) |
|
|
228 | 231 | self.ymax = kwargs.get('ymax', None) |
|
|
229 | 232 | self.yscale = kwargs.get('yscale', None) |
|
|
230 | 233 | self.xlabel = kwargs.get('xlabel', None) |
|
|
231 | 234 | self.attr_time = kwargs.get('attr_time', 'utctime') |
|
|
232 | 235 | self.attr_data = kwargs.get('attr_data', 'data_param') |
|
|
233 | 236 | self.decimation = kwargs.get('decimation', None) |
|
|
234 | 237 | self.oneFigure = kwargs.get('oneFigure', True) |
|
|
235 | 238 | self.width = kwargs.get('width', None) |
|
|
236 | 239 | self.height = kwargs.get('height', None) |
|
|
237 | 240 | self.colorbar = kwargs.get('colorbar', True) |
|
|
238 | 241 | self.factors = kwargs.get('factors', [1, 1, 1, 1, 1, 1, 1, 1]) |
|
|
239 | 242 | self.channels = kwargs.get('channels', None) |
|
|
240 | 243 | self.titles = kwargs.get('titles', []) |
|
|
241 | 244 | self.polar = False |
|
|
242 | 245 | self.type = kwargs.get('type', 'iq') |
|
|
243 | 246 | self.grid = kwargs.get('grid', False) |
|
|
244 | 247 | self.pause = kwargs.get('pause', False) |
|
|
245 | 248 | self.save_code = kwargs.get('save_code', self.CODE) |
|
|
246 | 249 | self.throttle = kwargs.get('throttle', 0) |
|
|
247 | 250 | self.exp_code = kwargs.get('exp_code', None) |
|
|
248 | 251 | self.server = kwargs.get('server', False) |
|
|
249 | 252 | self.sender_period = kwargs.get('sender_period', 60) |
|
|
250 | 253 | self.tag = kwargs.get('tag', '') |
|
|
251 | 254 | self.height_index = kwargs.get('height_index', None) |
|
|
252 | 255 | self.__throttle_plot = apply_throttle(self.throttle) |
|
|
253 | 256 | code = self.attr_data if self.attr_data else self.CODE |
|
|
254 | 257 | self.data = PlotterData(self.CODE, self.exp_code, self.localtime) |
|
|
255 | 258 | self.ang_min = kwargs.get('ang_min', None) |
|
|
256 | 259 | self.ang_max = kwargs.get('ang_max', None) |
|
|
257 | 260 | self.mode = kwargs.get('mode', None) |
|
|
258 | 261 | |
|
|
259 | 262 | |
|
|
260 | 263 | |
|
|
261 | 264 | if self.server: |
|
|
262 | 265 | if not self.server.startswith('tcp://'): |
|
|
263 | 266 | self.server = 'tcp://{}'.format(self.server) |
|
|
264 | 267 | log.success( |
|
|
265 | 268 | 'Sending to server: {}'.format(self.server), |
|
|
266 | 269 | self.name |
|
|
267 | 270 | ) |
|
|
268 | 271 | |
|
|
269 | 272 | if isinstance(self.attr_data, str): |
|
|
270 | 273 | self.attr_data = [self.attr_data] |
|
|
271 | 274 | |
|
|
272 | 275 | def __setup_plot(self): |
|
|
273 | 276 | ''' |
|
|
274 | 277 | Common setup for all figures, here figures and axes are created |
|
|
275 | 278 | ''' |
|
|
276 | 279 | |
|
|
277 | 280 | self.setup() |
|
|
278 | 281 | |
|
|
279 | 282 | self.time_label = 'LT' if self.localtime else 'UTC' |
|
|
280 | 283 | |
|
|
281 | 284 | if self.width is None: |
|
|
282 | 285 | self.width = 8 |
|
|
283 | 286 | |
|
|
284 | 287 | self.figures = [] |
|
|
285 | 288 | self.axes = [] |
|
|
286 | 289 | self.cb_axes = [] |
|
|
287 | 290 | self.pf_axes = [] |
|
|
288 | 291 | self.cmaps = [] |
|
|
289 | 292 | |
|
|
290 | 293 | size = '15%' if self.ncols == 1 else '30%' |
|
|
291 | 294 | pad = '4%' if self.ncols == 1 else '8%' |
|
|
292 | 295 | |
|
|
293 | 296 | if self.oneFigure: |
|
|
294 | 297 | if self.height is None: |
|
|
295 | 298 | self.height = 1.4 * self.nrows + 1 |
|
|
296 | 299 | fig = plt.figure(figsize=(self.width, self.height), |
|
|
297 | 300 | edgecolor='k', |
|
|
298 | 301 | facecolor='w') |
|
|
299 | 302 | self.figures.append(fig) |
|
|
300 | 303 | for n in range(self.nplots): |
|
|
301 | 304 | ax = fig.add_subplot(self.nrows, self.ncols, |
|
|
302 | 305 | n + 1, polar=self.polar) |
|
|
303 | 306 | ax.tick_params(labelsize=8) |
|
|
304 | 307 | ax.firsttime = True |
|
|
305 | 308 | ax.index = 0 |
|
|
306 | 309 | ax.press = None |
|
|
307 | 310 | self.axes.append(ax) |
|
|
308 | 311 | if self.showprofile: |
|
|
309 | 312 | cax = self.__add_axes(ax, size=size, pad=pad) |
|
|
310 | 313 | cax.tick_params(labelsize=8) |
|
|
311 | 314 | self.pf_axes.append(cax) |
|
|
312 | 315 | else: |
|
|
313 | 316 | if self.height is None: |
|
|
314 | 317 | self.height = 3 |
|
|
315 | 318 | for n in range(self.nplots): |
|
|
316 | 319 | fig = plt.figure(figsize=(self.width, self.height), |
|
|
317 | 320 | edgecolor='k', |
|
|
318 | 321 | facecolor='w') |
|
|
319 | 322 | ax = fig.add_subplot(1, 1, 1, polar=self.polar) |
|
|
320 | 323 | ax.tick_params(labelsize=8) |
|
|
321 | 324 | ax.firsttime = True |
|
|
322 | 325 | ax.index = 0 |
|
|
323 | 326 | ax.press = None |
|
|
324 | 327 | self.figures.append(fig) |
|
|
325 | 328 | self.axes.append(ax) |
|
|
326 | 329 | if self.showprofile: |
|
|
327 | 330 | cax = self.__add_axes(ax, size=size, pad=pad) |
|
|
328 | 331 | cax.tick_params(labelsize=8) |
|
|
329 | 332 | self.pf_axes.append(cax) |
|
|
330 | 333 | |
|
|
331 | 334 | for n in range(self.nrows): |
|
|
332 | 335 | if self.colormaps is not None: |
|
|
333 | 336 | cmap = plt.get_cmap(self.colormaps[n]) |
|
|
334 | 337 | else: |
|
|
335 | 338 | cmap = plt.get_cmap(self.colormap) |
|
|
336 | 339 | cmap.set_bad(self.bgcolor, 1.) |
|
|
337 | 340 | self.cmaps.append(cmap) |
|
|
338 | 341 | |
|
|
339 | 342 | def __add_axes(self, ax, size='30%', pad='8%'): |
|
|
340 | 343 | ''' |
|
|
341 | 344 | Add new axes to the given figure |
|
|
342 | 345 | ''' |
|
|
343 | 346 | divider = make_axes_locatable(ax) |
|
|
344 | 347 | nax = divider.new_horizontal(size=size, pad=pad) |
|
|
345 | 348 | ax.figure.add_axes(nax) |
|
|
346 | 349 | return nax |
|
|
347 | 350 | |
|
|
348 | 351 | def fill_gaps(self, x_buffer, y_buffer, z_buffer): |
|
|
349 | 352 | ''' |
|
|
350 | 353 | Create a masked array for missing data |
|
|
351 | 354 | ''' |
|
|
352 | 355 | if x_buffer.shape[0] < 2: |
|
|
353 | 356 | return x_buffer, y_buffer, z_buffer |
|
|
354 | 357 | |
|
|
355 | 358 | deltas = x_buffer[1:] - x_buffer[0:-1] |
|
|
356 | 359 | x_median = numpy.median(deltas) |
|
|
357 | 360 | |
|
|
358 | 361 | index = numpy.where(deltas > 5 * x_median) |
|
|
359 | 362 | |
|
|
360 | 363 | if len(index[0]) != 0: |
|
|
361 | 364 | z_buffer[::, index[0], ::] = self.__missing |
|
|
362 | 365 | z_buffer = numpy.ma.masked_inside(z_buffer, |
|
|
363 | 366 | 0.99 * self.__missing, |
|
|
364 | 367 | 1.01 * self.__missing) |
|
|
365 | 368 | |
|
|
366 | 369 | return x_buffer, y_buffer, z_buffer |
|
|
367 | 370 | |
|
|
368 | 371 | def decimate(self): |
|
|
369 | 372 | |
|
|
370 | 373 | # dx = int(len(self.x)/self.__MAXNUMX) + 1 |
|
|
371 | 374 | dy = int(len(self.y) / self.decimation) + 1 |
|
|
372 | 375 | |
|
|
373 | 376 | # x = self.x[::dx] |
|
|
374 | 377 | x = self.x |
|
|
375 | 378 | y = self.y[::dy] |
|
|
376 | 379 | z = self.z[::, ::, ::dy] |
|
|
377 | 380 | |
|
|
378 | 381 | return x, y, z |
|
|
379 | 382 | |
|
|
380 | 383 | def format(self): |
|
|
381 | 384 | ''' |
|
|
382 | 385 | Set min and max values, labels, ticks and titles |
|
|
383 | 386 | ''' |
|
|
384 | 387 | |
|
|
385 | 388 | for n, ax in enumerate(self.axes): |
|
|
386 | 389 | if ax.firsttime: |
|
|
387 | 390 | if self.xaxis != 'time': |
|
|
388 | 391 | xmin = self.xmin |
|
|
389 | 392 | xmax = self.xmax |
|
|
390 | 393 | else: |
|
|
391 | 394 | xmin = self.tmin |
|
|
392 | 395 | xmax = self.tmin + self.xrange*60*60 |
|
|
393 | 396 | ax.xaxis.set_major_formatter(FuncFormatter(self.__fmtTime)) |
|
|
394 | 397 | ax.xaxis.set_major_locator(LinearLocator(9)) |
|
|
395 | 398 | ymin = self.ymin if self.ymin is not None else numpy.nanmin(self.y[numpy.isfinite(self.y)]) |
|
|
396 | 399 | ymax = self.ymax if self.ymax is not None else numpy.nanmax(self.y[numpy.isfinite(self.y)]) |
|
|
397 | 400 | ax.set_facecolor(self.bgcolor) |
|
|
398 | 401 | if self.xscale: |
|
|
399 | 402 | ax.xaxis.set_major_formatter(FuncFormatter( |
|
|
400 | 403 | lambda x, pos: '{0:g}'.format(x*self.xscale))) |
|
|
401 | 404 | if self.yscale: |
|
|
402 | 405 | ax.yaxis.set_major_formatter(FuncFormatter( |
|
|
403 | 406 | lambda x, pos: '{0:g}'.format(x*self.yscale))) |
|
|
404 | 407 | if self.xlabel is not None: |
|
|
405 | 408 | ax.set_xlabel(self.xlabel) |
|
|
406 | 409 | if self.ylabel is not None: |
|
|
407 | 410 | ax.set_ylabel(self.ylabel) |
|
|
408 | 411 | if self.showprofile: |
|
|
409 | 412 | self.pf_axes[n].set_ylim(ymin, ymax) |
|
|
410 | 413 | self.pf_axes[n].set_xlim(self.zmin, self.zmax) |
|
|
411 | 414 | self.pf_axes[n].set_xlabel('dB') |
|
|
412 | 415 | self.pf_axes[n].grid(b=True, axis='x') |
|
|
413 | 416 | [tick.set_visible(False) |
|
|
414 | 417 | for tick in self.pf_axes[n].get_yticklabels()] |
|
|
415 | 418 | if self.colorbar: |
|
|
416 | 419 | ax.cbar = plt.colorbar( |
|
|
417 |
ax.plt, ax=ax, fraction=0.05, pad=0.0 |
|
|
|
420 | ax.plt, ax=ax, fraction=0.05, pad=0.06, aspect=10) | |
|
|
418 | 421 | ax.cbar.ax.tick_params(labelsize=8) |
|
|
419 | 422 | ax.cbar.ax.press = None |
|
|
420 | 423 | if self.cb_label: |
|
|
421 | 424 | ax.cbar.set_label(self.cb_label, size=8) |
|
|
422 | 425 | elif self.cb_labels: |
|
|
423 | 426 | ax.cbar.set_label(self.cb_labels[n], size=8) |
|
|
424 | 427 | else: |
|
|
425 | 428 | ax.cbar = None |
|
|
426 | 429 | ax.set_xlim(xmin, xmax) |
|
|
427 | 430 | ax.set_ylim(ymin, ymax) |
|
|
428 | 431 | ax.firsttime = False |
|
|
429 | 432 | if self.grid: |
|
|
430 | 433 | ax.grid(True) |
|
|
431 | 434 | if not self.polar: |
|
|
432 | 435 | ax.set_title('{} {} {}'.format( |
|
|
433 | 436 | self.titles[n], |
|
|
434 | 437 | self.getDateTime(self.data.max_time).strftime( |
|
|
435 | 438 | '%Y-%m-%d %H:%M:%S'), |
|
|
436 | 439 | self.time_label), |
|
|
437 | 440 | size=8) |
|
|
438 | 441 | else: |
|
|
439 | 442 | #ax.set_title('{}'.format(self.titles[n]), size=8) |
|
|
440 | 443 | ax.set_title('{} {} {}'.format( |
|
|
441 | 444 | self.titles[n], |
|
|
442 | 445 | self.getDateTime(self.data.max_time).strftime( |
|
|
443 | 446 | '%Y-%m-%d %H:%M:%S'), |
|
|
444 | 447 | self.time_label), |
|
|
445 | 448 | size=8) |
|
|
446 | 449 | ax.set_ylim(0, self.ymax) |
|
|
447 | 450 | #ax.set_yticks(numpy.arange(0, self.ymax, 20)) |
|
|
448 |
ax.yaxis.labelpad = 2 |
|
|
|
451 | ax.yaxis.labelpad = 28 | |
|
|
449 | 452 | |
|
|
450 | 453 | if self.firsttime: |
|
|
451 | 454 | for n, fig in enumerate(self.figures): |
|
|
452 | 455 | fig.subplots_adjust(**self.plots_adjust) |
|
|
453 | 456 | self.firsttime = False |
|
|
454 | 457 | |
|
|
455 | 458 | def clear_figures(self): |
|
|
456 | 459 | ''' |
|
|
457 | 460 | Reset axes for redraw plots |
|
|
458 | 461 | ''' |
|
|
459 | 462 | |
|
|
460 | 463 | for ax in self.axes+self.pf_axes+self.cb_axes: |
|
|
461 | 464 | ax.clear() |
|
|
462 | 465 | ax.firsttime = True |
|
|
463 | 466 | if hasattr(ax, 'cbar') and ax.cbar: |
|
|
464 | 467 | ax.cbar.remove() |
|
|
465 | 468 | |
|
|
466 | 469 | def __plot(self): |
|
|
467 | 470 | ''' |
|
|
468 | 471 | Main function to plot, format and save figures |
|
|
469 | 472 | ''' |
|
|
470 | 473 | |
|
|
471 | 474 | self.plot() |
|
|
472 | 475 | self.format() |
|
|
473 | 476 | |
|
|
474 | 477 | for n, fig in enumerate(self.figures): |
|
|
475 | 478 | if self.nrows == 0 or self.nplots == 0: |
|
|
476 | 479 | log.warning('No data', self.name) |
|
|
477 | 480 | fig.text(0.5, 0.5, 'No Data', fontsize='large', ha='center') |
|
|
478 | 481 | fig.canvas.manager.set_window_title(self.CODE) |
|
|
479 | 482 | continue |
|
|
480 | 483 | |
|
|
481 | 484 | fig.canvas.manager.set_window_title('{} - {}'.format(self.title, |
|
|
482 | 485 | self.getDateTime(self.data.max_time).strftime('%Y/%m/%d'))) |
|
|
483 | 486 | fig.canvas.draw() |
|
|
484 | 487 | if self.show: |
|
|
485 | 488 | fig.show() |
|
|
486 | 489 | figpause(0.01) |
|
|
487 | 490 | |
|
|
488 | 491 | if self.save: |
|
|
492 | if self.CODE=="PPI" or self.CODE=="RHI": | |
|
|
493 | self.save_figure(n,stitle =self.titles) | |
|
|
494 | else: | |
|
|
489 | 495 | self.save_figure(n) |
|
|
490 | 496 | |
|
|
491 | 497 | if self.server: |
|
|
492 | 498 | self.send_to_server() |
|
|
493 | 499 | |
|
|
494 | 500 | def __update(self, dataOut, timestamp): |
|
|
495 | 501 | ''' |
|
|
496 | 502 | ''' |
|
|
497 | 503 | |
|
|
498 | 504 | metadata = { |
|
|
499 | 505 | 'yrange': dataOut.heightList, |
|
|
500 | 506 | 'interval': dataOut.timeInterval, |
|
|
501 | 507 | 'channels': dataOut.channelList |
|
|
502 | 508 | } |
|
|
503 | 509 | |
|
|
504 | 510 | data, meta = self.update(dataOut) |
|
|
505 | 511 | metadata.update(meta) |
|
|
506 | 512 | self.data.update(data, timestamp, metadata) |
|
|
507 | 513 | |
|
|
508 | def save_figure(self, n): | |
|
|
514 | def save_figure(self, n,stitle=None): | |
|
|
509 | 515 | ''' |
|
|
510 | 516 | ''' |
|
|
517 | if stitle is not None: | |
|
|
518 | s_string = re.sub(r"[^A-Z0-9.]","",str(stitle)) | |
|
|
519 | new_string=s_string[:3]+"_"+"_"+s_string[4:6]+"_"+s_string[6:] | |
|
|
520 | ||
|
|
511 | 521 | if self.oneFigure: |
|
|
512 | 522 | if (self.data.max_time - self.save_time) <= self.save_period: |
|
|
513 | 523 | return |
|
|
514 | 524 | |
|
|
515 | 525 | self.save_time = self.data.max_time |
|
|
516 | 526 | |
|
|
517 | 527 | fig = self.figures[n] |
|
|
518 | 528 | |
|
|
519 | 529 | if self.throttle == 0: |
|
|
520 | 530 | if self.oneFigure: |
|
|
531 | if stitle is not None: | |
|
|
532 | figname = os.path.join( | |
|
|
533 | self.save, | |
|
|
534 | self.save_code, | |
|
|
535 | '{}_{}_{}.png'.format( | |
|
|
536 | self.save_code, | |
|
|
537 | self.getDateTime(self.data.max_time).strftime( | |
|
|
538 | '%Y%m%d_%H%M%S', | |
|
|
539 | ), | |
|
|
540 | new_string, | |
|
|
541 | ) | |
|
|
542 | ) | |
|
|
543 | else: | |
|
|
521 | 544 | figname = os.path.join( |
|
|
522 | 545 | self.save, |
|
|
523 | 546 | self.save_code, |
|
|
524 | 547 | '{}_{}.png'.format( |
|
|
525 | 548 | self.save_code, |
|
|
526 | 549 | self.getDateTime(self.data.max_time).strftime( |
|
|
527 | 550 | '%Y%m%d_%H%M%S' |
|
|
528 | 551 | ), |
|
|
529 | 552 | ) |
|
|
530 | 553 | ) |
|
|
531 | 554 | else: |
|
|
532 | 555 | figname = os.path.join( |
|
|
533 | 556 | self.save, |
|
|
534 | 557 | self.save_code, |
|
|
535 | 558 | '{}_ch{}_{}.png'.format( |
|
|
536 | 559 | self.save_code,n, |
|
|
537 | 560 | self.getDateTime(self.data.max_time).strftime( |
|
|
538 | 561 | '%Y%m%d_%H%M%S' |
|
|
539 | 562 | ), |
|
|
540 | 563 | ) |
|
|
541 | 564 | ) |
|
|
542 | 565 | log.log('Saving figure: {}'.format(figname), self.name) |
|
|
543 | 566 | if not os.path.isdir(os.path.dirname(figname)): |
|
|
544 | 567 | os.makedirs(os.path.dirname(figname)) |
|
|
545 | 568 | fig.savefig(figname) |
|
|
546 | 569 | |
|
|
547 | 570 | figname = os.path.join( |
|
|
548 | 571 | self.save, |
|
|
549 | 572 | '{}_{}.png'.format( |
|
|
550 | 573 | self.save_code, |
|
|
551 | 574 | self.getDateTime(self.data.min_time).strftime( |
|
|
552 | 575 | '%Y%m%d' |
|
|
553 | 576 | ), |
|
|
554 | 577 | ) |
|
|
555 | 578 | ) |
|
|
556 | 579 | |
|
|
557 | 580 | log.log('Saving figure: {}'.format(figname), self.name) |
|
|
558 | 581 | if not os.path.isdir(os.path.dirname(figname)): |
|
|
559 | 582 | os.makedirs(os.path.dirname(figname)) |
|
|
560 | 583 | fig.savefig(figname) |
|
|
561 | 584 | |
|
|
562 | 585 | def send_to_server(self): |
|
|
563 | 586 | ''' |
|
|
564 | 587 | ''' |
|
|
565 | 588 | |
|
|
566 | 589 | if self.exp_code == None: |
|
|
567 | 590 | log.warning('Missing `exp_code` skipping sending to server...') |
|
|
568 | 591 | |
|
|
569 | 592 | last_time = self.data.max_time |
|
|
570 | 593 | interval = last_time - self.sender_time |
|
|
571 | 594 | if interval < self.sender_period: |
|
|
572 | 595 | return |
|
|
573 | 596 | |
|
|
574 | 597 | self.sender_time = last_time |
|
|
575 | 598 | |
|
|
576 | 599 | attrs = ['titles', 'zmin', 'zmax', 'tag', 'ymin', 'ymax'] |
|
|
577 | 600 | for attr in attrs: |
|
|
578 | 601 | value = getattr(self, attr) |
|
|
579 | 602 | if value: |
|
|
580 | 603 | if isinstance(value, (numpy.float32, numpy.float64)): |
|
|
581 | 604 | value = round(float(value), 2) |
|
|
582 | 605 | self.data.meta[attr] = value |
|
|
583 | 606 | if self.colormap == 'jet': |
|
|
584 | 607 | self.data.meta['colormap'] = 'Jet' |
|
|
585 | 608 | elif 'RdBu' in self.colormap: |
|
|
586 | 609 | self.data.meta['colormap'] = 'RdBu' |
|
|
587 | 610 | else: |
|
|
588 | 611 | self.data.meta['colormap'] = 'Viridis' |
|
|
589 | 612 | self.data.meta['interval'] = int(interval) |
|
|
590 | 613 | |
|
|
591 | 614 | self.sender_queue.append(last_time) |
|
|
592 | 615 | |
|
|
593 | 616 | while True: |
|
|
594 | 617 | try: |
|
|
595 | 618 | tm = self.sender_queue.popleft() |
|
|
596 | 619 | except IndexError: |
|
|
597 | 620 | break |
|
|
598 | 621 | msg = self.data.jsonify(tm, self.save_code, self.plot_type) |
|
|
599 | 622 | self.socket.send_string(msg) |
|
|
600 | 623 | socks = dict(self.poll.poll(2000)) |
|
|
601 | 624 | if socks.get(self.socket) == zmq.POLLIN: |
|
|
602 | 625 | reply = self.socket.recv_string() |
|
|
603 | 626 | if reply == 'ok': |
|
|
604 | 627 | log.log("Response from server ok", self.name) |
|
|
605 | 628 | time.sleep(0.1) |
|
|
606 | 629 | continue |
|
|
607 | 630 | else: |
|
|
608 | 631 | log.warning( |
|
|
609 | 632 | "Malformed reply from server: {}".format(reply), self.name) |
|
|
610 | 633 | else: |
|
|
611 | 634 | log.warning( |
|
|
612 | 635 | "No response from server, retrying...", self.name) |
|
|
613 | 636 | self.sender_queue.appendleft(tm) |
|
|
614 | 637 | self.socket.setsockopt(zmq.LINGER, 0) |
|
|
615 | 638 | self.socket.close() |
|
|
616 | 639 | self.poll.unregister(self.socket) |
|
|
617 | 640 | self.socket = self.context.socket(zmq.REQ) |
|
|
618 | 641 | self.socket.connect(self.server) |
|
|
619 | 642 | self.poll.register(self.socket, zmq.POLLIN) |
|
|
620 | 643 | break |
|
|
621 | 644 | |
|
|
622 | 645 | def setup(self): |
|
|
623 | 646 | ''' |
|
|
624 | 647 | This method should be implemented in the child class, the following |
|
|
625 | 648 | attributes should be set: |
|
|
626 | 649 | |
|
|
627 | 650 | self.nrows: number of rows |
|
|
628 | 651 | self.ncols: number of cols |
|
|
629 | 652 | self.nplots: number of plots (channels or pairs) |
|
|
630 | 653 | self.ylabel: label for Y axes |
|
|
631 | 654 | self.titles: list of axes title |
|
|
632 | 655 | |
|
|
633 | 656 | ''' |
|
|
634 | 657 | raise NotImplementedError |
|
|
635 | 658 | |
|
|
636 | 659 | def plot(self): |
|
|
637 | 660 | ''' |
|
|
638 | 661 | Must be defined in the child class, the actual plotting method |
|
|
639 | 662 | ''' |
|
|
640 | 663 | raise NotImplementedError |
|
|
641 | 664 | |
|
|
642 | 665 | def update(self, dataOut): |
|
|
643 | 666 | ''' |
|
|
644 | 667 | Must be defined in the child class, update self.data with new data |
|
|
645 | 668 | ''' |
|
|
646 | 669 | |
|
|
647 | 670 | data = { |
|
|
648 | 671 | self.CODE: getattr(dataOut, 'data_{}'.format(self.CODE)) |
|
|
649 | 672 | } |
|
|
650 | 673 | meta = {} |
|
|
651 | 674 | |
|
|
652 | 675 | return data, meta |
|
|
653 | 676 | |
|
|
654 | 677 | def run(self, dataOut, **kwargs): |
|
|
655 | 678 | ''' |
|
|
656 | 679 | Main plotting routine |
|
|
657 | 680 | ''' |
|
|
658 | 681 | |
|
|
659 | 682 | if self.isConfig is False: |
|
|
660 | 683 | self.__setup(**kwargs) |
|
|
661 | 684 | |
|
|
662 | 685 | if self.localtime: |
|
|
663 | 686 | self.getDateTime = datetime.datetime.fromtimestamp |
|
|
664 | 687 | else: |
|
|
665 | 688 | self.getDateTime = datetime.datetime.utcfromtimestamp |
|
|
666 | 689 | |
|
|
667 | 690 | self.data.setup() |
|
|
668 | 691 | self.isConfig = True |
|
|
669 | 692 | if self.server: |
|
|
670 | 693 | self.context = zmq.Context() |
|
|
671 | 694 | self.socket = self.context.socket(zmq.REQ) |
|
|
672 | 695 | self.socket.connect(self.server) |
|
|
673 | 696 | self.poll = zmq.Poller() |
|
|
674 | 697 | self.poll.register(self.socket, zmq.POLLIN) |
|
|
675 | 698 | |
|
|
676 | 699 | tm = getattr(dataOut, self.attr_time) |
|
|
677 | 700 | |
|
|
678 | 701 | if self.data and 'time' in self.xaxis and (tm - self.tmin) >= self.xrange*60*60: |
|
|
679 | 702 | self.save_time = tm |
|
|
680 | 703 | self.__plot() |
|
|
681 | 704 | self.tmin += self.xrange*60*60 |
|
|
682 | 705 | self.data.setup() |
|
|
683 | 706 | self.clear_figures() |
|
|
684 | 707 | |
|
|
685 | 708 | self.__update(dataOut, tm) |
|
|
686 | 709 | |
|
|
687 | 710 | if self.isPlotConfig is False: |
|
|
688 | 711 | self.__setup_plot() |
|
|
689 | 712 | self.isPlotConfig = True |
|
|
690 | 713 | if self.xaxis == 'time': |
|
|
691 | 714 | dt = self.getDateTime(tm) |
|
|
692 | 715 | if self.xmin is None: |
|
|
693 | 716 | self.tmin = tm |
|
|
694 | 717 | self.xmin = dt.hour |
|
|
695 | 718 | minutes = (self.xmin-int(self.xmin)) * 60 |
|
|
696 | 719 | seconds = (minutes - int(minutes)) * 60 |
|
|
697 | 720 | self.tmin = (dt.replace(hour=int(self.xmin), minute=int(minutes), second=int(seconds)) - |
|
|
698 | 721 | datetime.datetime(1970, 1, 1)).total_seconds() |
|
|
699 | 722 | if self.localtime: |
|
|
700 | 723 | self.tmin += time.timezone |
|
|
701 | 724 | |
|
|
702 | 725 | if self.xmin is not None and self.xmax is not None: |
|
|
703 | 726 | self.xrange = self.xmax - self.xmin |
|
|
704 | 727 | |
|
|
705 | 728 | if self.throttle == 0: |
|
|
706 | 729 | self.__plot() |
|
|
707 | 730 | else: |
|
|
708 | 731 | self.__throttle_plot(self.__plot)#, coerce=coerce) |
|
|
709 | 732 | |
|
|
710 | 733 | def close(self): |
|
|
711 | 734 | |
|
|
712 | 735 | if self.data and not self.data.flagNoData: |
|
|
713 | 736 | self.save_time = 0 |
|
|
714 | 737 | self.__plot() |
|
|
715 | 738 | if self.data and not self.data.flagNoData and self.pause: |
|
|
716 | 739 | figpause(10) |
| @@ -1,1936 +1,1936 | |||
|
|
1 | 1 | import os |
|
|
2 | 2 | import datetime |
|
|
3 | 3 | import numpy |
|
|
4 | 4 | from mpl_toolkits.axisartist.grid_finder import FixedLocator, DictFormatter |
|
|
5 | 5 | |
|
|
6 | 6 | from schainpy.model.graphics.jroplot_base import Plot, plt |
|
|
7 | 7 | from schainpy.model.graphics.jroplot_spectra import SpectraPlot, RTIPlot, CoherencePlot, SpectraCutPlot |
|
|
8 | 8 | from schainpy.utils import log |
|
|
9 | 9 | # libreria wradlib |
|
|
10 | 10 | #import wradlib as wrl |
|
|
11 | 11 | |
|
|
12 | 12 | EARTH_RADIUS = 6.3710e3 |
|
|
13 | 13 | |
|
|
14 | 14 | |
|
|
15 | 15 | def ll2xy(lat1, lon1, lat2, lon2): |
|
|
16 | 16 | |
|
|
17 | 17 | p = 0.017453292519943295 |
|
|
18 | 18 | a = 0.5 - numpy.cos((lat2 - lat1) * p)/2 + numpy.cos(lat1 * p) * \ |
|
|
19 | 19 | numpy.cos(lat2 * p) * (1 - numpy.cos((lon2 - lon1) * p)) / 2 |
|
|
20 | 20 | r = 12742 * numpy.arcsin(numpy.sqrt(a)) |
|
|
21 | 21 | theta = numpy.arctan2(numpy.sin((lon2-lon1)*p)*numpy.cos(lat2*p), numpy.cos(lat1*p) |
|
|
22 | 22 | * numpy.sin(lat2*p)-numpy.sin(lat1*p)*numpy.cos(lat2*p)*numpy.cos((lon2-lon1)*p)) |
|
|
23 | 23 | theta = -theta + numpy.pi/2 |
|
|
24 | 24 | return r*numpy.cos(theta), r*numpy.sin(theta) |
|
|
25 | 25 | |
|
|
26 | 26 | |
|
|
27 | 27 | def km2deg(km): |
|
|
28 | 28 | ''' |
|
|
29 | 29 | Convert distance in km to degrees |
|
|
30 | 30 | ''' |
|
|
31 | 31 | |
|
|
32 | 32 | return numpy.rad2deg(km/EARTH_RADIUS) |
|
|
33 | 33 | |
|
|
34 | 34 | |
|
|
35 | 35 | |
|
|
36 | 36 | class SpectralMomentsPlot(SpectraPlot): |
|
|
37 | 37 | ''' |
|
|
38 | 38 | Plot for Spectral Moments |
|
|
39 | 39 | ''' |
|
|
40 | 40 | CODE = 'spc_moments' |
|
|
41 | 41 | # colormap = 'jet' |
|
|
42 | 42 | # plot_type = 'pcolor' |
|
|
43 | 43 | |
|
|
44 | 44 | class DobleGaussianPlot(SpectraPlot): |
|
|
45 | 45 | ''' |
|
|
46 | 46 | Plot for Double Gaussian Plot |
|
|
47 | 47 | ''' |
|
|
48 | 48 | CODE = 'gaussian_fit' |
|
|
49 | 49 | # colormap = 'jet' |
|
|
50 | 50 | # plot_type = 'pcolor' |
|
|
51 | 51 | |
|
|
52 | 52 | class DoubleGaussianSpectraCutPlot(SpectraCutPlot): |
|
|
53 | 53 | ''' |
|
|
54 | 54 | Plot SpectraCut with Double Gaussian Fit |
|
|
55 | 55 | ''' |
|
|
56 | 56 | CODE = 'cut_gaussian_fit' |
|
|
57 | 57 | |
|
|
58 | 58 | class SnrPlot(RTIPlot): |
|
|
59 | 59 | ''' |
|
|
60 | 60 | Plot for SNR Data |
|
|
61 | 61 | ''' |
|
|
62 | 62 | |
|
|
63 | 63 | CODE = 'snr' |
|
|
64 | 64 | colormap = 'jet' |
|
|
65 | 65 | |
|
|
66 | 66 | def update(self, dataOut): |
|
|
67 | 67 | |
|
|
68 | 68 | data = { |
|
|
69 | 69 | 'snr': 10*numpy.log10(dataOut.data_snr) |
|
|
70 | 70 | } |
|
|
71 | 71 | |
|
|
72 | 72 | return data, {} |
|
|
73 | 73 | |
|
|
74 | 74 | class DopplerPlot(RTIPlot): |
|
|
75 | 75 | ''' |
|
|
76 | 76 | Plot for DOPPLER Data (1st moment) |
|
|
77 | 77 | ''' |
|
|
78 | 78 | |
|
|
79 | 79 | CODE = 'dop' |
|
|
80 | 80 | colormap = 'jet' |
|
|
81 | 81 | |
|
|
82 | 82 | def update(self, dataOut): |
|
|
83 | 83 | |
|
|
84 | 84 | data = { |
|
|
85 | 85 | 'dop': 10*numpy.log10(dataOut.data_dop) |
|
|
86 | 86 | } |
|
|
87 | 87 | |
|
|
88 | 88 | return data, {} |
|
|
89 | 89 | |
|
|
90 | 90 | class PowerPlot(RTIPlot): |
|
|
91 | 91 | ''' |
|
|
92 | 92 | Plot for Power Data (0 moment) |
|
|
93 | 93 | ''' |
|
|
94 | 94 | |
|
|
95 | 95 | CODE = 'pow' |
|
|
96 | 96 | colormap = 'jet' |
|
|
97 | 97 | |
|
|
98 | 98 | def update(self, dataOut): |
|
|
99 | 99 | data = { |
|
|
100 | 100 | 'pow': 10*numpy.log10(dataOut.data_pow/dataOut.normFactor) |
|
|
101 | 101 | } |
|
|
102 | 102 | return data, {} |
|
|
103 | 103 | |
|
|
104 | 104 | class SpectralWidthPlot(RTIPlot): |
|
|
105 | 105 | ''' |
|
|
106 | 106 | Plot for Spectral Width Data (2nd moment) |
|
|
107 | 107 | ''' |
|
|
108 | 108 | |
|
|
109 | 109 | CODE = 'width' |
|
|
110 | 110 | colormap = 'jet' |
|
|
111 | 111 | |
|
|
112 | 112 | def update(self, dataOut): |
|
|
113 | 113 | |
|
|
114 | 114 | data = { |
|
|
115 | 115 | 'width': dataOut.data_width |
|
|
116 | 116 | } |
|
|
117 | 117 | |
|
|
118 | 118 | return data, {} |
|
|
119 | 119 | |
|
|
120 | 120 | class SkyMapPlot(Plot): |
|
|
121 | 121 | ''' |
|
|
122 | 122 | Plot for meteors detection data |
|
|
123 | 123 | ''' |
|
|
124 | 124 | |
|
|
125 | 125 | CODE = 'param' |
|
|
126 | 126 | |
|
|
127 | 127 | def setup(self): |
|
|
128 | 128 | |
|
|
129 | 129 | self.ncols = 1 |
|
|
130 | 130 | self.nrows = 1 |
|
|
131 | 131 | self.width = 7.2 |
|
|
132 | 132 | self.height = 7.2 |
|
|
133 | 133 | self.nplots = 1 |
|
|
134 | 134 | self.xlabel = 'Zonal Zenith Angle (deg)' |
|
|
135 | 135 | self.ylabel = 'Meridional Zenith Angle (deg)' |
|
|
136 | 136 | self.polar = True |
|
|
137 | 137 | self.ymin = -180 |
|
|
138 | 138 | self.ymax = 180 |
|
|
139 | 139 | self.colorbar = False |
|
|
140 | 140 | |
|
|
141 | 141 | def plot(self): |
|
|
142 | 142 | |
|
|
143 | 143 | arrayParameters = numpy.concatenate(self.data['param']) |
|
|
144 | 144 | error = arrayParameters[:, -1] |
|
|
145 | 145 | indValid = numpy.where(error == 0)[0] |
|
|
146 | 146 | finalMeteor = arrayParameters[indValid, :] |
|
|
147 | 147 | finalAzimuth = finalMeteor[:, 3] |
|
|
148 | 148 | finalZenith = finalMeteor[:, 4] |
|
|
149 | 149 | |
|
|
150 | 150 | x = finalAzimuth * numpy.pi / 180 |
|
|
151 | 151 | y = finalZenith |
|
|
152 | 152 | |
|
|
153 | 153 | ax = self.axes[0] |
|
|
154 | 154 | |
|
|
155 | 155 | if ax.firsttime: |
|
|
156 | 156 | ax.plot = ax.plot(x, y, 'bo', markersize=5)[0] |
|
|
157 | 157 | else: |
|
|
158 | 158 | ax.plot.set_data(x, y) |
|
|
159 | 159 | |
|
|
160 | 160 | dt1 = self.getDateTime(self.data.min_time).strftime('%y/%m/%d %H:%M:%S') |
|
|
161 | 161 | dt2 = self.getDateTime(self.data.max_time).strftime('%y/%m/%d %H:%M:%S') |
|
|
162 | 162 | title = 'Meteor Detection Sky Map\n %s - %s \n Number of events: %5.0f\n' % (dt1, |
|
|
163 | 163 | dt2, |
|
|
164 | 164 | len(x)) |
|
|
165 | 165 | self.titles[0] = title |
|
|
166 | 166 | |
|
|
167 | 167 | |
|
|
168 | 168 | class GenericRTIPlot(Plot): |
|
|
169 | 169 | ''' |
|
|
170 | 170 | Plot for data_xxxx object |
|
|
171 | 171 | ''' |
|
|
172 | 172 | |
|
|
173 | 173 | CODE = 'param' |
|
|
174 | 174 | colormap = 'viridis' |
|
|
175 | 175 | plot_type = 'pcolorbuffer' |
|
|
176 | 176 | |
|
|
177 | 177 | def setup(self): |
|
|
178 | 178 | self.xaxis = 'time' |
|
|
179 | 179 | self.ncols = 1 |
|
|
180 | 180 | self.nrows = self.data.shape('param')[0] |
|
|
181 | 181 | self.nplots = self.nrows |
|
|
182 | 182 | self.plots_adjust.update({'hspace':0.8, 'left': 0.1, 'bottom': 0.08, 'right':0.95, 'top': 0.95}) |
|
|
183 | 183 | |
|
|
184 | 184 | if not self.xlabel: |
|
|
185 | 185 | self.xlabel = 'Time' |
|
|
186 | 186 | |
|
|
187 | 187 | self.ylabel = 'Range [km]' |
|
|
188 | 188 | if not self.titles: |
|
|
189 | 189 | self.titles = ['Param {}'.format(x) for x in range(self.nrows)] |
|
|
190 | 190 | |
|
|
191 | 191 | def update(self, dataOut): |
|
|
192 | 192 | |
|
|
193 | 193 | data = { |
|
|
194 | 194 | 'param' : numpy.concatenate([getattr(dataOut, attr) for attr in self.attr_data], axis=0) |
|
|
195 | 195 | } |
|
|
196 | 196 | |
|
|
197 | 197 | meta = {} |
|
|
198 | 198 | |
|
|
199 | 199 | return data, meta |
|
|
200 | 200 | |
|
|
201 | 201 | def plot(self): |
|
|
202 | 202 | # self.data.normalize_heights() |
|
|
203 | 203 | self.x = self.data.times |
|
|
204 | 204 | self.y = self.data.yrange |
|
|
205 | 205 | self.z = self.data['param'] |
|
|
206 | 206 | self.z = 10*numpy.log10(self.z) |
|
|
207 | 207 | self.z = numpy.ma.masked_invalid(self.z) |
|
|
208 | 208 | |
|
|
209 | 209 | if self.decimation is None: |
|
|
210 | 210 | x, y, z = self.fill_gaps(self.x, self.y, self.z) |
|
|
211 | 211 | else: |
|
|
212 | 212 | x, y, z = self.fill_gaps(*self.decimate()) |
|
|
213 | 213 | |
|
|
214 | 214 | for n, ax in enumerate(self.axes): |
|
|
215 | 215 | |
|
|
216 | 216 | self.zmax = self.zmax if self.zmax is not None else numpy.max( |
|
|
217 | 217 | self.z[n]) |
|
|
218 | 218 | self.zmin = self.zmin if self.zmin is not None else numpy.min( |
|
|
219 | 219 | self.z[n]) |
|
|
220 | 220 | |
|
|
221 | 221 | if ax.firsttime: |
|
|
222 | 222 | if self.zlimits is not None: |
|
|
223 | 223 | self.zmin, self.zmax = self.zlimits[n] |
|
|
224 | 224 | |
|
|
225 | 225 | ax.plt = ax.pcolormesh(x, y, z[n].T * self.factors[n], |
|
|
226 | 226 | vmin=self.zmin, |
|
|
227 | 227 | vmax=self.zmax, |
|
|
228 | 228 | cmap=self.cmaps[n] |
|
|
229 | 229 | ) |
|
|
230 | 230 | else: |
|
|
231 | 231 | if self.zlimits is not None: |
|
|
232 | 232 | self.zmin, self.zmax = self.zlimits[n] |
|
|
233 | 233 | ax.collections.remove(ax.collections[0]) |
|
|
234 | 234 | ax.plt = ax.pcolormesh(x, y, z[n].T * self.factors[n], |
|
|
235 | 235 | vmin=self.zmin, |
|
|
236 | 236 | vmax=self.zmax, |
|
|
237 | 237 | cmap=self.cmaps[n] |
|
|
238 | 238 | ) |
|
|
239 | 239 | |
|
|
240 | 240 | |
|
|
241 | 241 | class PolarMapPlot(Plot): |
|
|
242 | 242 | ''' |
|
|
243 | 243 | Plot for weather radar |
|
|
244 | 244 | ''' |
|
|
245 | 245 | |
|
|
246 | 246 | CODE = 'param' |
|
|
247 | 247 | colormap = 'seismic' |
|
|
248 | 248 | |
|
|
249 | 249 | def setup(self): |
|
|
250 | 250 | self.ncols = 1 |
|
|
251 | 251 | self.nrows = 1 |
|
|
252 | 252 | self.width = 9 |
|
|
253 | 253 | self.height = 8 |
|
|
254 | 254 | self.mode = self.data.meta['mode'] |
|
|
255 | 255 | if self.channels is not None: |
|
|
256 | 256 | self.nplots = len(self.channels) |
|
|
257 | 257 | self.nrows = len(self.channels) |
|
|
258 | 258 | else: |
|
|
259 | 259 | self.nplots = self.data.shape(self.CODE)[0] |
|
|
260 | 260 | self.nrows = self.nplots |
|
|
261 | 261 | self.channels = list(range(self.nplots)) |
|
|
262 | 262 | if self.mode == 'E': |
|
|
263 | 263 | self.xlabel = 'Longitude' |
|
|
264 | 264 | self.ylabel = 'Latitude' |
|
|
265 | 265 | else: |
|
|
266 | 266 | self.xlabel = 'Range (km)' |
|
|
267 | 267 | self.ylabel = 'Height (km)' |
|
|
268 | 268 | self.bgcolor = 'white' |
|
|
269 | 269 | self.cb_labels = self.data.meta['units'] |
|
|
270 | 270 | self.lat = self.data.meta['latitude'] |
|
|
271 | 271 | self.lon = self.data.meta['longitude'] |
|
|
272 | 272 | self.xmin, self.xmax = float( |
|
|
273 | 273 | km2deg(self.xmin) + self.lon), float(km2deg(self.xmax) + self.lon) |
|
|
274 | 274 | self.ymin, self.ymax = float( |
|
|
275 | 275 | km2deg(self.ymin) + self.lat), float(km2deg(self.ymax) + self.lat) |
|
|
276 | 276 | # self.polar = True |
|
|
277 | 277 | |
|
|
278 | 278 | def plot(self): |
|
|
279 | 279 | |
|
|
280 | 280 | for n, ax in enumerate(self.axes): |
|
|
281 | 281 | data = self.data['param'][self.channels[n]] |
|
|
282 | 282 | |
|
|
283 | 283 | zeniths = numpy.linspace( |
|
|
284 | 284 | 0, self.data.meta['max_range'], data.shape[1]) |
|
|
285 | 285 | if self.mode == 'E': |
|
|
286 | 286 | azimuths = -numpy.radians(self.data.yrange)+numpy.pi/2 |
|
|
287 | 287 | r, theta = numpy.meshgrid(zeniths, azimuths) |
|
|
288 | 288 | x, y = r*numpy.cos(theta)*numpy.cos(numpy.radians(self.data.meta['elevation'])), r*numpy.sin( |
|
|
289 | 289 | theta)*numpy.cos(numpy.radians(self.data.meta['elevation'])) |
|
|
290 | 290 | x = km2deg(x) + self.lon |
|
|
291 | 291 | y = km2deg(y) + self.lat |
|
|
292 | 292 | else: |
|
|
293 | 293 | azimuths = numpy.radians(self.data.yrange) |
|
|
294 | 294 | r, theta = numpy.meshgrid(zeniths, azimuths) |
|
|
295 | 295 | x, y = r*numpy.cos(theta), r*numpy.sin(theta) |
|
|
296 | 296 | self.y = zeniths |
|
|
297 | 297 | |
|
|
298 | 298 | if ax.firsttime: |
|
|
299 | 299 | if self.zlimits is not None: |
|
|
300 | 300 | self.zmin, self.zmax = self.zlimits[n] |
|
|
301 | 301 | ax.plt = ax.pcolormesh( # r, theta, numpy.ma.array(data, mask=numpy.isnan(data)), |
|
|
302 | 302 | x, y, numpy.ma.array(data, mask=numpy.isnan(data)), |
|
|
303 | 303 | vmin=self.zmin, |
|
|
304 | 304 | vmax=self.zmax, |
|
|
305 | 305 | cmap=self.cmaps[n]) |
|
|
306 | 306 | else: |
|
|
307 | 307 | if self.zlimits is not None: |
|
|
308 | 308 | self.zmin, self.zmax = self.zlimits[n] |
|
|
309 | 309 | ax.collections.remove(ax.collections[0]) |
|
|
310 | 310 | ax.plt = ax.pcolormesh( # r, theta, numpy.ma.array(data, mask=numpy.isnan(data)), |
|
|
311 | 311 | x, y, numpy.ma.array(data, mask=numpy.isnan(data)), |
|
|
312 | 312 | vmin=self.zmin, |
|
|
313 | 313 | vmax=self.zmax, |
|
|
314 | 314 | cmap=self.cmaps[n]) |
|
|
315 | 315 | |
|
|
316 | 316 | if self.mode == 'A': |
|
|
317 | 317 | continue |
|
|
318 | 318 | |
|
|
319 | 319 | # plot district names |
|
|
320 | 320 | f = open('/data/workspace/schain_scripts/distrito.csv') |
|
|
321 | 321 | for line in f: |
|
|
322 | 322 | label, lon, lat = [s.strip() for s in line.split(',') if s] |
|
|
323 | 323 | lat = float(lat) |
|
|
324 | 324 | lon = float(lon) |
|
|
325 | 325 | # ax.plot(lon, lat, '.b', ms=2) |
|
|
326 | 326 | ax.text(lon, lat, label.decode('utf8'), ha='center', |
|
|
327 | 327 | va='bottom', size='8', color='black') |
|
|
328 | 328 | |
|
|
329 | 329 | # plot limites |
|
|
330 | 330 | limites = [] |
|
|
331 | 331 | tmp = [] |
|
|
332 | 332 | for line in open('/data/workspace/schain_scripts/lima.csv'): |
|
|
333 | 333 | if '#' in line: |
|
|
334 | 334 | if tmp: |
|
|
335 | 335 | limites.append(tmp) |
|
|
336 | 336 | tmp = [] |
|
|
337 | 337 | continue |
|
|
338 | 338 | values = line.strip().split(',') |
|
|
339 | 339 | tmp.append((float(values[0]), float(values[1]))) |
|
|
340 | 340 | for points in limites: |
|
|
341 | 341 | ax.add_patch( |
|
|
342 | 342 | Polygon(points, ec='k', fc='none', ls='--', lw=0.5)) |
|
|
343 | 343 | |
|
|
344 | 344 | # plot Cuencas |
|
|
345 | 345 | for cuenca in ('rimac', 'lurin', 'mala', 'chillon', 'chilca', 'chancay-huaral'): |
|
|
346 | 346 | f = open('/data/workspace/schain_scripts/{}.csv'.format(cuenca)) |
|
|
347 | 347 | values = [line.strip().split(',') for line in f] |
|
|
348 | 348 | points = [(float(s[0]), float(s[1])) for s in values] |
|
|
349 | 349 | ax.add_patch(Polygon(points, ec='b', fc='none')) |
|
|
350 | 350 | |
|
|
351 | 351 | # plot grid |
|
|
352 | 352 | for r in (15, 30, 45, 60): |
|
|
353 | 353 | ax.add_artist(plt.Circle((self.lon, self.lat), |
|
|
354 | 354 | km2deg(r), color='0.6', fill=False, lw=0.2)) |
|
|
355 | 355 | ax.text( |
|
|
356 | 356 | self.lon + (km2deg(r))*numpy.cos(60*numpy.pi/180), |
|
|
357 | 357 | self.lat + (km2deg(r))*numpy.sin(60*numpy.pi/180), |
|
|
358 | 358 | '{}km'.format(r), |
|
|
359 | 359 | ha='center', va='bottom', size='8', color='0.6', weight='heavy') |
|
|
360 | 360 | |
|
|
361 | 361 | if self.mode == 'E': |
|
|
362 | 362 | title = 'El={}$^\circ$'.format(self.data.meta['elevation']) |
|
|
363 | 363 | label = 'E{:02d}'.format(int(self.data.meta['elevation'])) |
|
|
364 | 364 | else: |
|
|
365 | 365 | title = 'Az={}$^\circ$'.format(self.data.meta['azimuth']) |
|
|
366 | 366 | label = 'A{:02d}'.format(int(self.data.meta['azimuth'])) |
|
|
367 | 367 | |
|
|
368 | 368 | self.save_labels = ['{}-{}'.format(lbl, label) for lbl in self.labels] |
|
|
369 | 369 | self.titles = ['{} {}'.format( |
|
|
370 | 370 | self.data.parameters[x], title) for x in self.channels] |
|
|
371 | 371 | |
|
|
372 | 372 | class WeatherPlot(Plot): |
|
|
373 | 373 | CODE = 'weather' |
|
|
374 | 374 | plot_name = 'weather' |
|
|
375 | 375 | plot_type = 'ppistyle' |
|
|
376 | 376 | buffering = False |
|
|
377 | 377 | |
|
|
378 | 378 | def setup(self): |
|
|
379 | 379 | self.ncols = 1 |
|
|
380 | 380 | self.nrows = 1 |
|
|
381 | 381 | self.width =8 |
|
|
382 | 382 | self.height =8 |
|
|
383 | 383 | self.nplots= 1 |
|
|
384 | 384 | self.ylabel= 'Range [Km]' |
|
|
385 | 385 | self.titles= ['Weather'] |
|
|
386 | 386 | self.colorbar=False |
|
|
387 | 387 | self.ini =0 |
|
|
388 | 388 | self.len_azi =0 |
|
|
389 | 389 | self.buffer_ini = None |
|
|
390 | 390 | self.buffer_azi = None |
|
|
391 | 391 | self.plots_adjust.update({'wspace': 0.4, 'hspace':0.4, 'left': 0.1, 'right': 0.9, 'bottom': 0.08}) |
|
|
392 | 392 | self.flag =0 |
|
|
393 | 393 | self.indicador= 0 |
|
|
394 | 394 | self.last_data_azi = None |
|
|
395 | 395 | self.val_mean = None |
|
|
396 | 396 | |
|
|
397 | 397 | def update(self, dataOut): |
|
|
398 | 398 | |
|
|
399 | 399 | data = {} |
|
|
400 | 400 | meta = {} |
|
|
401 | 401 | if hasattr(dataOut, 'dataPP_POWER'): |
|
|
402 | 402 | factor = 1 |
|
|
403 | 403 | if hasattr(dataOut, 'nFFTPoints'): |
|
|
404 | 404 | factor = dataOut.normFactor |
|
|
405 | 405 | #print("DIME EL SHAPE PORFAVOR",dataOut.data_360.shape) |
|
|
406 | 406 | data['weather'] = 10*numpy.log10(dataOut.data_360[1]/(factor)) |
|
|
407 | 407 | data['azi'] = dataOut.data_azi |
|
|
408 | 408 | data['ele'] = dataOut.data_ele |
|
|
409 | 409 | return data, meta |
|
|
410 | 410 | |
|
|
411 | 411 | def get2List(self,angulos): |
|
|
412 | 412 | list1=[] |
|
|
413 | 413 | list2=[] |
|
|
414 | 414 | for i in reversed(range(len(angulos))): |
|
|
415 | 415 | diff_ = angulos[i]-angulos[i-1] |
|
|
416 | 416 | if diff_ >1.5: |
|
|
417 | 417 | list1.append(i-1) |
|
|
418 | 418 | list2.append(diff_) |
|
|
419 | 419 | return list(reversed(list1)),list(reversed(list2)) |
|
|
420 | 420 | |
|
|
421 | 421 | def fixData360(self,list_,ang_): |
|
|
422 | 422 | if list_[0]==-1: |
|
|
423 | 423 | vec = numpy.where(ang_<ang_[0]) |
|
|
424 | 424 | ang_[vec] = ang_[vec]+360 |
|
|
425 | 425 | return ang_ |
|
|
426 | 426 | return ang_ |
|
|
427 | 427 | |
|
|
428 | 428 | def fixData360HL(self,angulos): |
|
|
429 | 429 | vec = numpy.where(angulos>=360) |
|
|
430 | 430 | angulos[vec]=angulos[vec]-360 |
|
|
431 | 431 | return angulos |
|
|
432 | 432 | |
|
|
433 | 433 | def search_pos(self,pos,list_): |
|
|
434 | 434 | for i in range(len(list_)): |
|
|
435 | 435 | if pos == list_[i]: |
|
|
436 | 436 | return True,i |
|
|
437 | 437 | i=None |
|
|
438 | 438 | return False,i |
|
|
439 | 439 | |
|
|
440 | 440 | def fixDataComp(self,ang_,list1_,list2_): |
|
|
441 | 441 | size = len(ang_) |
|
|
442 | 442 | size2 = 0 |
|
|
443 | 443 | for i in range(len(list2_)): |
|
|
444 | 444 | size2=size2+round(list2_[i])-1 |
|
|
445 | 445 | new_size= size+size2 |
|
|
446 | 446 | ang_new = numpy.zeros(new_size) |
|
|
447 | 447 | ang_new2 = numpy.zeros(new_size) |
|
|
448 | 448 | |
|
|
449 | 449 | tmp = 0 |
|
|
450 | 450 | c = 0 |
|
|
451 | 451 | for i in range(len(ang_)): |
|
|
452 | 452 | ang_new[tmp +c] = ang_[i] |
|
|
453 | 453 | ang_new2[tmp+c] = ang_[i] |
|
|
454 | 454 | condition , value = self.search_pos(i,list1_) |
|
|
455 | 455 | if condition: |
|
|
456 | 456 | pos = tmp + c + 1 |
|
|
457 | 457 | for k in range(round(list2_[value])-1): |
|
|
458 | 458 | ang_new[pos+k] = ang_new[pos+k-1]+1 |
|
|
459 | 459 | ang_new2[pos+k] = numpy.nan |
|
|
460 | 460 | tmp = pos +k |
|
|
461 | 461 | c = 0 |
|
|
462 | 462 | c=c+1 |
|
|
463 | 463 | return ang_new,ang_new2 |
|
|
464 | 464 | |
|
|
465 | 465 | def globalCheckPED(self,angulos): |
|
|
466 | 466 | l1,l2 = self.get2List(angulos) |
|
|
467 | 467 | if len(l1)>0: |
|
|
468 | 468 | angulos2 = self.fixData360(list_=l1,ang_=angulos) |
|
|
469 | 469 | l1,l2 = self.get2List(angulos2) |
|
|
470 | 470 | |
|
|
471 | 471 | ang1_,ang2_ = self.fixDataComp(ang_=angulos2,list1_=l1,list2_=l2) |
|
|
472 | 472 | ang1_ = self.fixData360HL(ang1_) |
|
|
473 | 473 | ang2_ = self.fixData360HL(ang2_) |
|
|
474 | 474 | else: |
|
|
475 | 475 | ang1_= angulos |
|
|
476 | 476 | ang2_= angulos |
|
|
477 | 477 | return ang1_,ang2_ |
|
|
478 | 478 | |
|
|
479 | 479 | def analizeDATA(self,data_azi): |
|
|
480 | 480 | list1 = [] |
|
|
481 | 481 | list2 = [] |
|
|
482 | 482 | dat = data_azi |
|
|
483 | 483 | for i in reversed(range(1,len(dat))): |
|
|
484 | 484 | if dat[i]>dat[i-1]: |
|
|
485 | 485 | diff = int(dat[i])-int(dat[i-1]) |
|
|
486 | 486 | else: |
|
|
487 | 487 | diff = 360+int(dat[i])-int(dat[i-1]) |
|
|
488 | 488 | if diff > 1: |
|
|
489 | 489 | list1.append(i-1) |
|
|
490 | 490 | list2.append(diff-1) |
|
|
491 | 491 | return list1,list2 |
|
|
492 | 492 | |
|
|
493 | 493 | def fixDATANEW(self,data_azi,data_weather): |
|
|
494 | 494 | list1,list2 = self.analizeDATA(data_azi) |
|
|
495 | 495 | if len(list1)== 0: |
|
|
496 | 496 | return data_azi,data_weather |
|
|
497 | 497 | else: |
|
|
498 | 498 | resize = 0 |
|
|
499 | 499 | for i in range(len(list2)): |
|
|
500 | 500 | resize= resize + list2[i] |
|
|
501 | 501 | new_data_azi = numpy.resize(data_azi,resize) |
|
|
502 | 502 | new_data_weather= numpy.resize(date_weather,resize) |
|
|
503 | 503 | |
|
|
504 | 504 | for i in range(len(list2)): |
|
|
505 | 505 | j=0 |
|
|
506 | 506 | position=list1[i]+1 |
|
|
507 | 507 | for j in range(list2[i]): |
|
|
508 | 508 | new_data_azi[position+j]=new_data_azi[position+j-1]+1 |
|
|
509 | 509 | return new_data_azi |
|
|
510 | 510 | |
|
|
511 | 511 | def fixDATA(self,data_azi): |
|
|
512 | 512 | data=data_azi |
|
|
513 | 513 | for i in range(len(data)): |
|
|
514 | 514 | if numpy.isnan(data[i]): |
|
|
515 | 515 | data[i]=data[i-1]+1 |
|
|
516 | 516 | return data |
|
|
517 | 517 | |
|
|
518 | 518 | def replaceNAN(self,data_weather,data_azi,val): |
|
|
519 | 519 | data= data_azi |
|
|
520 | 520 | data_T= data_weather |
|
|
521 | 521 | if data.shape[0]> data_T.shape[0]: |
|
|
522 | 522 | data_N = numpy.ones( [data.shape[0],data_T.shape[1]]) |
|
|
523 | 523 | c = 0 |
|
|
524 | 524 | for i in range(len(data)): |
|
|
525 | 525 | if numpy.isnan(data[i]): |
|
|
526 | 526 | data_N[i,:]=numpy.ones(data_T.shape[1])*numpy.nan |
|
|
527 | 527 | else: |
|
|
528 | 528 | data_N[i,:]=data_T[c,:] |
|
|
529 | 529 | c=c+1 |
|
|
530 | 530 | return data_N |
|
|
531 | 531 | else: |
|
|
532 | 532 | for i in range(len(data)): |
|
|
533 | 533 | if numpy.isnan(data[i]): |
|
|
534 | 534 | data_T[i,:]=numpy.ones(data_T.shape[1])*numpy.nan |
|
|
535 | 535 | return data_T |
|
|
536 | 536 | |
|
|
537 | 537 | def const_ploteo(self,data_weather,data_azi,step,res): |
|
|
538 | 538 | if self.ini==0: |
|
|
539 | 539 | #------- |
|
|
540 | 540 | n = (360/res)-len(data_azi) |
|
|
541 | 541 | #--------------------- new ------------------------- |
|
|
542 | 542 | data_azi_new ,data_azi_old= self.globalCheckPED(data_azi) |
|
|
543 | 543 | #------------------------ |
|
|
544 | 544 | start = data_azi_new[-1] + res |
|
|
545 | 545 | end = data_azi_new[0] - res |
|
|
546 | 546 | #------ new |
|
|
547 | 547 | self.last_data_azi = end |
|
|
548 | 548 | if start>end: |
|
|
549 | 549 | end = end + 360 |
|
|
550 | 550 | azi_vacia = numpy.linspace(start,end,int(n)) |
|
|
551 | 551 | azi_vacia = numpy.where(azi_vacia>360,azi_vacia-360,azi_vacia) |
|
|
552 | 552 | data_azi = numpy.hstack((data_azi_new,azi_vacia)) |
|
|
553 | 553 | # RADAR |
|
|
554 | 554 | val_mean = numpy.mean(data_weather[:,-1]) |
|
|
555 | 555 | self.val_mean = val_mean |
|
|
556 | 556 | data_weather_cmp = numpy.ones([(360-data_weather.shape[0]),data_weather.shape[1]])*val_mean |
|
|
557 | 557 | data_weather = self.replaceNAN(data_weather=data_weather,data_azi=data_azi_old,val=self.val_mean) |
|
|
558 | 558 | data_weather = numpy.vstack((data_weather,data_weather_cmp)) |
|
|
559 | 559 | else: |
|
|
560 | 560 | # azimuth |
|
|
561 | 561 | flag=0 |
|
|
562 | 562 | start_azi = self.res_azi[0] |
|
|
563 | 563 | #-----------new------------ |
|
|
564 | 564 | data_azi ,data_azi_old= self.globalCheckPED(data_azi) |
|
|
565 | 565 | data_weather = self.replaceNAN(data_weather=data_weather,data_azi=data_azi_old,val=self.val_mean) |
|
|
566 | 566 | #-------------------------- |
|
|
567 | 567 | start = data_azi[0] |
|
|
568 | 568 | end = data_azi[-1] |
|
|
569 | 569 | self.last_data_azi= end |
|
|
570 | 570 | if start< start_azi: |
|
|
571 | 571 | start = start +360 |
|
|
572 | 572 | if end <start_azi: |
|
|
573 | 573 | end = end +360 |
|
|
574 | 574 | |
|
|
575 | 575 | pos_ini = int((start-start_azi)/res) |
|
|
576 | 576 | len_azi = len(data_azi) |
|
|
577 | 577 | if (360-pos_ini)<len_azi: |
|
|
578 | 578 | if pos_ini+1==360: |
|
|
579 | 579 | pos_ini=0 |
|
|
580 | 580 | else: |
|
|
581 | 581 | flag=1 |
|
|
582 | 582 | dif= 360-pos_ini |
|
|
583 | 583 | comp= len_azi-dif |
|
|
584 | 584 | #----------------- |
|
|
585 | 585 | if flag==0: |
|
|
586 | 586 | # AZIMUTH |
|
|
587 | 587 | self.res_azi[pos_ini:pos_ini+len_azi] = data_azi |
|
|
588 | 588 | # RADAR |
|
|
589 | 589 | self.res_weather[pos_ini:pos_ini+len_azi,:] = data_weather |
|
|
590 | 590 | else: |
|
|
591 | 591 | # AZIMUTH |
|
|
592 | 592 | self.res_azi[pos_ini:pos_ini+dif] = data_azi[0:dif] |
|
|
593 | 593 | self.res_azi[0:comp] = data_azi[dif:] |
|
|
594 | 594 | # RADAR |
|
|
595 | 595 | self.res_weather[pos_ini:pos_ini+dif,:] = data_weather[0:dif,:] |
|
|
596 | 596 | self.res_weather[0:comp,:] = data_weather[dif:,:] |
|
|
597 | 597 | flag=0 |
|
|
598 | 598 | data_azi = self.res_azi |
|
|
599 | 599 | data_weather = self.res_weather |
|
|
600 | 600 | |
|
|
601 | 601 | return data_weather,data_azi |
|
|
602 | 602 | |
|
|
603 | 603 | def plot(self): |
|
|
604 | 604 | thisDatetime = datetime.datetime.utcfromtimestamp(self.data.times[-1]).strftime('%Y-%m-%d %H:%M:%S') |
|
|
605 | 605 | data = self.data[-1] |
|
|
606 | 606 | r = self.data.yrange |
|
|
607 | 607 | delta_height = r[1]-r[0] |
|
|
608 | 608 | r_mask = numpy.where(r>=0)[0] |
|
|
609 | 609 | r = numpy.arange(len(r_mask))*delta_height |
|
|
610 | 610 | self.y = 2*r |
|
|
611 | 611 | # RADAR |
|
|
612 | 612 | #data_weather = data['weather'] |
|
|
613 | 613 | # PEDESTAL |
|
|
614 | 614 | #data_azi = data['azi'] |
|
|
615 | 615 | res = 1 |
|
|
616 | 616 | # STEP |
|
|
617 | 617 | step = (360/(res*data['weather'].shape[0])) |
|
|
618 | 618 | |
|
|
619 | 619 | self.res_weather, self.res_azi = self.const_ploteo(data_weather=data['weather'][:,r_mask],data_azi=data['azi'],step=step,res=res) |
|
|
620 | 620 | self.res_ele = numpy.mean(data['ele']) |
|
|
621 | 621 | ################# PLOTEO ################### |
|
|
622 | 622 | for i,ax in enumerate(self.axes): |
|
|
623 | 623 | self.zmin = self.zmin if self.zmin else 20 |
|
|
624 | 624 | self.zmax = self.zmax if self.zmax else 80 |
|
|
625 | 625 | if ax.firsttime: |
|
|
626 | 626 | plt.clf() |
|
|
627 | 627 | cgax, pm = wrl.vis.plot_ppi(self.res_weather,r=r,az=self.res_azi,fig=self.figures[0], proj='cg', vmin=self.zmin, vmax=self.zmax) |
|
|
628 | 628 | else: |
|
|
629 | 629 | plt.clf() |
|
|
630 | 630 | cgax, pm = wrl.vis.plot_ppi(self.res_weather,r=r,az=self.res_azi,fig=self.figures[0], proj='cg', vmin=self.zmin, vmax=self.zmax) |
|
|
631 | 631 | caax = cgax.parasites[0] |
|
|
632 | 632 | paax = cgax.parasites[1] |
|
|
633 | 633 | cbar = plt.gcf().colorbar(pm, pad=0.075) |
|
|
634 | 634 | caax.set_xlabel('x_range [km]') |
|
|
635 | 635 | caax.set_ylabel('y_range [km]') |
|
|
636 | 636 | plt.text(1.0, 1.05, 'Azimuth '+str(thisDatetime)+" Step "+str(self.ini)+ " EL: "+str(round(self.res_ele, 1)), transform=caax.transAxes, va='bottom',ha='right') |
|
|
637 | 637 | |
|
|
638 | 638 | self.ini= self.ini+1 |
|
|
639 | 639 | |
|
|
640 | 640 | |
|
|
641 | 641 | class WeatherRHIPlot(Plot): |
|
|
642 | 642 | CODE = 'weather' |
|
|
643 | 643 | plot_name = 'weather' |
|
|
644 | 644 | plot_type = 'rhistyle' |
|
|
645 | 645 | buffering = False |
|
|
646 | 646 | data_ele_tmp = None |
|
|
647 | 647 | |
|
|
648 | 648 | def setup(self): |
|
|
649 | 649 | print("********************") |
|
|
650 | 650 | print("********************") |
|
|
651 | 651 | print("********************") |
|
|
652 | 652 | print("SETUP WEATHER PLOT") |
|
|
653 | 653 | self.ncols = 1 |
|
|
654 | 654 | self.nrows = 1 |
|
|
655 | 655 | self.nplots= 1 |
|
|
656 | 656 | self.ylabel= 'Range [Km]' |
|
|
657 | 657 | self.titles= ['Weather'] |
|
|
658 | 658 | if self.channels is not None: |
|
|
659 | 659 | self.nplots = len(self.channels) |
|
|
660 | 660 | self.nrows = len(self.channels) |
|
|
661 | 661 | else: |
|
|
662 | 662 | self.nplots = self.data.shape(self.CODE)[0] |
|
|
663 | 663 | self.nrows = self.nplots |
|
|
664 | 664 | self.channels = list(range(self.nplots)) |
|
|
665 | 665 | print("channels",self.channels) |
|
|
666 | 666 | print("que saldra", self.data.shape(self.CODE)[0]) |
|
|
667 | 667 | self.titles = ['{} Channel {}'.format(self.CODE.upper(), x) for x in range(self.nrows)] |
|
|
668 | 668 | print("self.titles",self.titles) |
|
|
669 | 669 | self.colorbar=False |
|
|
670 | 670 | self.width =12 |
|
|
671 | 671 | self.height =8 |
|
|
672 | 672 | self.ini =0 |
|
|
673 | 673 | self.len_azi =0 |
|
|
674 | 674 | self.buffer_ini = None |
|
|
675 | 675 | self.buffer_ele = None |
|
|
676 | 676 | self.plots_adjust.update({'wspace': 0.4, 'hspace':0.4, 'left': 0.1, 'right': 0.9, 'bottom': 0.08}) |
|
|
677 | 677 | self.flag =0 |
|
|
678 | 678 | self.indicador= 0 |
|
|
679 | 679 | self.last_data_ele = None |
|
|
680 | 680 | self.val_mean = None |
|
|
681 | 681 | |
|
|
682 | 682 | def update(self, dataOut): |
|
|
683 | 683 | |
|
|
684 | 684 | data = {} |
|
|
685 | 685 | meta = {} |
|
|
686 | 686 | if hasattr(dataOut, 'dataPP_POWER'): |
|
|
687 | 687 | factor = 1 |
|
|
688 | 688 | if hasattr(dataOut, 'nFFTPoints'): |
|
|
689 | 689 | factor = dataOut.normFactor |
|
|
690 | 690 | print("dataOut",dataOut.data_360.shape) |
|
|
691 | 691 | # |
|
|
692 | 692 | data['weather'] = 10*numpy.log10(dataOut.data_360/(factor)) |
|
|
693 | 693 | # |
|
|
694 | 694 | #data['weather'] = 10*numpy.log10(dataOut.data_360[1]/(factor)) |
|
|
695 | 695 | data['azi'] = dataOut.data_azi |
|
|
696 | 696 | data['ele'] = dataOut.data_ele |
|
|
697 | 697 | #print("UPDATE") |
|
|
698 | 698 | #print("data[weather]",data['weather'].shape) |
|
|
699 | 699 | #print("data[azi]",data['azi']) |
|
|
700 | 700 | return data, meta |
|
|
701 | 701 | |
|
|
702 | 702 | def get2List(self,angulos): |
|
|
703 | 703 | list1=[] |
|
|
704 | 704 | list2=[] |
|
|
705 | 705 | for i in reversed(range(len(angulos))): |
|
|
706 | 706 | if not i==0:#el caso de i=0 evalula el primero de la lista con el ultimo y no es relevante |
|
|
707 | 707 | diff_ = angulos[i]-angulos[i-1] |
|
|
708 | 708 | if abs(diff_) >1.5: |
|
|
709 | 709 | list1.append(i-1) |
|
|
710 | 710 | list2.append(diff_) |
|
|
711 | 711 | return list(reversed(list1)),list(reversed(list2)) |
|
|
712 | 712 | |
|
|
713 | 713 | def fixData90(self,list_,ang_): |
|
|
714 | 714 | if list_[0]==-1: |
|
|
715 | 715 | vec = numpy.where(ang_<ang_[0]) |
|
|
716 | 716 | ang_[vec] = ang_[vec]+90 |
|
|
717 | 717 | return ang_ |
|
|
718 | 718 | return ang_ |
|
|
719 | 719 | |
|
|
720 | 720 | def fixData90HL(self,angulos): |
|
|
721 | 721 | vec = numpy.where(angulos>=90) |
|
|
722 | 722 | angulos[vec]=angulos[vec]-90 |
|
|
723 | 723 | return angulos |
|
|
724 | 724 | |
|
|
725 | 725 | |
|
|
726 | 726 | def search_pos(self,pos,list_): |
|
|
727 | 727 | for i in range(len(list_)): |
|
|
728 | 728 | if pos == list_[i]: |
|
|
729 | 729 | return True,i |
|
|
730 | 730 | i=None |
|
|
731 | 731 | return False,i |
|
|
732 | 732 | |
|
|
733 | 733 | def fixDataComp(self,ang_,list1_,list2_,tipo_case): |
|
|
734 | 734 | size = len(ang_) |
|
|
735 | 735 | size2 = 0 |
|
|
736 | 736 | for i in range(len(list2_)): |
|
|
737 | 737 | size2=size2+round(abs(list2_[i]))-1 |
|
|
738 | 738 | new_size= size+size2 |
|
|
739 | 739 | ang_new = numpy.zeros(new_size) |
|
|
740 | 740 | ang_new2 = numpy.zeros(new_size) |
|
|
741 | 741 | |
|
|
742 | 742 | tmp = 0 |
|
|
743 | 743 | c = 0 |
|
|
744 | 744 | for i in range(len(ang_)): |
|
|
745 | 745 | ang_new[tmp +c] = ang_[i] |
|
|
746 | 746 | ang_new2[tmp+c] = ang_[i] |
|
|
747 | 747 | condition , value = self.search_pos(i,list1_) |
|
|
748 | 748 | if condition: |
|
|
749 | 749 | pos = tmp + c + 1 |
|
|
750 | 750 | for k in range(round(abs(list2_[value]))-1): |
|
|
751 | 751 | if tipo_case==0 or tipo_case==3:#subida |
|
|
752 | 752 | ang_new[pos+k] = ang_new[pos+k-1]+1 |
|
|
753 | 753 | ang_new2[pos+k] = numpy.nan |
|
|
754 | 754 | elif tipo_case==1 or tipo_case==2:#bajada |
|
|
755 | 755 | ang_new[pos+k] = ang_new[pos+k-1]-1 |
|
|
756 | 756 | ang_new2[pos+k] = numpy.nan |
|
|
757 | 757 | |
|
|
758 | 758 | tmp = pos +k |
|
|
759 | 759 | c = 0 |
|
|
760 | 760 | c=c+1 |
|
|
761 | 761 | return ang_new,ang_new2 |
|
|
762 | 762 | |
|
|
763 | 763 | def globalCheckPED(self,angulos,tipo_case): |
|
|
764 | 764 | l1,l2 = self.get2List(angulos) |
|
|
765 | 765 | ##print("l1",l1) |
|
|
766 | 766 | ##print("l2",l2) |
|
|
767 | 767 | if len(l1)>0: |
|
|
768 | 768 | #angulos2 = self.fixData90(list_=l1,ang_=angulos) |
|
|
769 | 769 | #l1,l2 = self.get2List(angulos2) |
|
|
770 | 770 | ang1_,ang2_ = self.fixDataComp(ang_=angulos,list1_=l1,list2_=l2,tipo_case=tipo_case) |
|
|
771 | 771 | #ang1_ = self.fixData90HL(ang1_) |
|
|
772 | 772 | #ang2_ = self.fixData90HL(ang2_) |
|
|
773 | 773 | else: |
|
|
774 | 774 | ang1_= angulos |
|
|
775 | 775 | ang2_= angulos |
|
|
776 | 776 | return ang1_,ang2_ |
|
|
777 | 777 | |
|
|
778 | 778 | |
|
|
779 | 779 | def replaceNAN(self,data_weather,data_ele,val): |
|
|
780 | 780 | data= data_ele |
|
|
781 | 781 | data_T= data_weather |
|
|
782 | 782 | if data.shape[0]> data_T.shape[0]: |
|
|
783 | 783 | data_N = numpy.ones( [data.shape[0],data_T.shape[1]]) |
|
|
784 | 784 | c = 0 |
|
|
785 | 785 | for i in range(len(data)): |
|
|
786 | 786 | if numpy.isnan(data[i]): |
|
|
787 | 787 | data_N[i,:]=numpy.ones(data_T.shape[1])*numpy.nan |
|
|
788 | 788 | else: |
|
|
789 | 789 | data_N[i,:]=data_T[c,:] |
|
|
790 | 790 | c=c+1 |
|
|
791 | 791 | return data_N |
|
|
792 | 792 | else: |
|
|
793 | 793 | for i in range(len(data)): |
|
|
794 | 794 | if numpy.isnan(data[i]): |
|
|
795 | 795 | data_T[i,:]=numpy.ones(data_T.shape[1])*numpy.nan |
|
|
796 | 796 | return data_T |
|
|
797 | 797 | |
|
|
798 | 798 | def check_case(self,data_ele,ang_max,ang_min): |
|
|
799 | 799 | start = data_ele[0] |
|
|
800 | 800 | end = data_ele[-1] |
|
|
801 | 801 | number = (end-start) |
|
|
802 | 802 | len_ang=len(data_ele) |
|
|
803 | 803 | print("start",start) |
|
|
804 | 804 | print("end",end) |
|
|
805 | 805 | print("number",number) |
|
|
806 | 806 | |
|
|
807 | 807 | print("len_ang",len_ang) |
|
|
808 | 808 | |
|
|
809 | 809 | #exit(1) |
|
|
810 | 810 | |
|
|
811 | 811 | if start<end and (round(abs(number)+1)>=len_ang or (numpy.argmin(data_ele)==0)):#caso subida |
|
|
812 | 812 | return 0 |
|
|
813 | 813 | #elif start>end and (round(abs(number)+1)>=len_ang or(numpy.argmax(data_ele)==0)):#caso bajada |
|
|
814 | 814 | # return 1 |
|
|
815 | 815 | elif round(abs(number)+1)>=len_ang and (start>end or(numpy.argmax(data_ele)==0)):#caso bajada |
|
|
816 | 816 | return 1 |
|
|
817 | 817 | elif round(abs(number)+1)<len_ang and data_ele[-2]>data_ele[-1]:# caso BAJADA CAMBIO ANG MAX |
|
|
818 | 818 | return 2 |
|
|
819 | 819 | elif round(abs(number)+1)<len_ang and data_ele[-2]<data_ele[-1] :# caso SUBIDA CAMBIO ANG MIN |
|
|
820 | 820 | return 3 |
|
|
821 | 821 | |
|
|
822 | 822 | |
|
|
823 | 823 | def const_ploteo(self,val_ch,data_weather,data_ele,step,res,ang_max,ang_min): |
|
|
824 | 824 | ang_max= ang_max |
|
|
825 | 825 | ang_min= ang_min |
|
|
826 | 826 | data_weather=data_weather |
|
|
827 | 827 | val_ch=val_ch |
|
|
828 | 828 | ##print("*********************DATA WEATHER**************************************") |
|
|
829 | 829 | ##print(data_weather) |
|
|
830 | 830 | if self.ini==0: |
|
|
831 | 831 | ''' |
|
|
832 | 832 | print("**********************************************") |
|
|
833 | 833 | print("**********************************************") |
|
|
834 | 834 | print("***************ini**************") |
|
|
835 | 835 | print("**********************************************") |
|
|
836 | 836 | print("**********************************************") |
|
|
837 | 837 | ''' |
|
|
838 | 838 | #print("data_ele",data_ele) |
|
|
839 | 839 | #---------------------------------------------------------- |
|
|
840 | 840 | tipo_case = self.check_case(data_ele,ang_max,ang_min) |
|
|
841 | 841 | print("check_case",tipo_case) |
|
|
842 | 842 | #exit(1) |
|
|
843 | 843 | #--------------------- new ------------------------- |
|
|
844 | 844 | data_ele_new ,data_ele_old= self.globalCheckPED(data_ele,tipo_case) |
|
|
845 | 845 | |
|
|
846 | 846 | #-------------------------CAMBIOS RHI--------------------------------- |
|
|
847 | 847 | start= ang_min |
|
|
848 | 848 | end = ang_max |
|
|
849 | 849 | n= (ang_max-ang_min)/res |
|
|
850 | 850 | #------ new |
|
|
851 | 851 | self.start_data_ele = data_ele_new[0] |
|
|
852 | 852 | self.end_data_ele = data_ele_new[-1] |
|
|
853 | 853 | if tipo_case==0 or tipo_case==3: # SUBIDA |
|
|
854 | 854 | n1= round(self.start_data_ele)- start |
|
|
855 | 855 | n2= end - round(self.end_data_ele) |
|
|
856 | 856 | print(self.start_data_ele) |
|
|
857 | 857 | print(self.end_data_ele) |
|
|
858 | 858 | if n1>0: |
|
|
859 | 859 | ele1= numpy.linspace(ang_min+1,self.start_data_ele-1,n1) |
|
|
860 | 860 | ele1_nan= numpy.ones(n1)*numpy.nan |
|
|
861 | 861 | data_ele = numpy.hstack((ele1,data_ele_new)) |
|
|
862 | 862 | print("ele1_nan",ele1_nan.shape) |
|
|
863 | 863 | print("data_ele_old",data_ele_old.shape) |
|
|
864 | 864 | data_ele_old = numpy.hstack((ele1_nan,data_ele_old)) |
|
|
865 | 865 | if n2>0: |
|
|
866 | 866 | ele2= numpy.linspace(self.end_data_ele+1,end,n2) |
|
|
867 | 867 | ele2_nan= numpy.ones(n2)*numpy.nan |
|
|
868 | 868 | data_ele = numpy.hstack((data_ele,ele2)) |
|
|
869 | 869 | print("ele2_nan",ele2_nan.shape) |
|
|
870 | 870 | print("data_ele_old",data_ele_old.shape) |
|
|
871 | 871 | data_ele_old = numpy.hstack((data_ele_old,ele2_nan)) |
|
|
872 | 872 | |
|
|
873 | 873 | if tipo_case==1 or tipo_case==2: # BAJADA |
|
|
874 | 874 | data_ele_new = data_ele_new[::-1] # reversa |
|
|
875 | 875 | data_ele_old = data_ele_old[::-1]# reversa |
|
|
876 | 876 | data_weather = data_weather[::-1,:]# reversa |
|
|
877 | 877 | vec= numpy.where(data_ele_new<ang_max) |
|
|
878 | 878 | data_ele_new = data_ele_new[vec] |
|
|
879 | 879 | data_ele_old = data_ele_old[vec] |
|
|
880 | 880 | data_weather = data_weather[vec[0]] |
|
|
881 | 881 | vec2= numpy.where(0<data_ele_new) |
|
|
882 | 882 | data_ele_new = data_ele_new[vec2] |
|
|
883 | 883 | data_ele_old = data_ele_old[vec2] |
|
|
884 | 884 | data_weather = data_weather[vec2[0]] |
|
|
885 | 885 | self.start_data_ele = data_ele_new[0] |
|
|
886 | 886 | self.end_data_ele = data_ele_new[-1] |
|
|
887 | 887 | |
|
|
888 | 888 | n1= round(self.start_data_ele)- start |
|
|
889 | 889 | n2= end - round(self.end_data_ele)-1 |
|
|
890 | 890 | print(self.start_data_ele) |
|
|
891 | 891 | print(self.end_data_ele) |
|
|
892 | 892 | if n1>0: |
|
|
893 | 893 | ele1= numpy.linspace(ang_min+1,self.start_data_ele-1,n1) |
|
|
894 | 894 | ele1_nan= numpy.ones(n1)*numpy.nan |
|
|
895 | 895 | data_ele = numpy.hstack((ele1,data_ele_new)) |
|
|
896 | 896 | data_ele_old = numpy.hstack((ele1_nan,data_ele_old)) |
|
|
897 | 897 | if n2>0: |
|
|
898 | 898 | ele2= numpy.linspace(self.end_data_ele+1,end,n2) |
|
|
899 | 899 | ele2_nan= numpy.ones(n2)*numpy.nan |
|
|
900 | 900 | data_ele = numpy.hstack((data_ele,ele2)) |
|
|
901 | 901 | data_ele_old = numpy.hstack((data_ele_old,ele2_nan)) |
|
|
902 | 902 | # RADAR |
|
|
903 | 903 | # NOTA data_ele y data_weather es la variable que retorna |
|
|
904 | 904 | val_mean = numpy.mean(data_weather[:,-1]) |
|
|
905 | 905 | self.val_mean = val_mean |
|
|
906 | 906 | data_weather = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean) |
|
|
907 | 907 | self.data_ele_tmp[val_ch]= data_ele_old |
|
|
908 | 908 | else: |
|
|
909 | 909 | #print("**********************************************") |
|
|
910 | 910 | #print("****************VARIABLE**********************") |
|
|
911 | 911 | #-------------------------CAMBIOS RHI--------------------------------- |
|
|
912 | 912 | #--------------------------------------------------------------------- |
|
|
913 | 913 | ##print("INPUT data_ele",data_ele) |
|
|
914 | 914 | flag=0 |
|
|
915 | 915 | start_ele = self.res_ele[0] |
|
|
916 | 916 | tipo_case = self.check_case(data_ele,ang_max,ang_min) |
|
|
917 | 917 | #print("TIPO DE DATA",tipo_case) |
|
|
918 | 918 | #-----------new------------ |
|
|
919 | 919 | data_ele ,data_ele_old = self.globalCheckPED(data_ele,tipo_case) |
|
|
920 | 920 | data_weather = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean) |
|
|
921 | 921 | |
|
|
922 | 922 | #-------------------------------NEW RHI ITERATIVO------------------------- |
|
|
923 | 923 | |
|
|
924 | 924 | if tipo_case==0 : # SUBIDA |
|
|
925 | 925 | vec = numpy.where(data_ele<ang_max) |
|
|
926 | 926 | data_ele = data_ele[vec] |
|
|
927 | 927 | data_ele_old = data_ele_old[vec] |
|
|
928 | 928 | data_weather = data_weather[vec[0]] |
|
|
929 | 929 | |
|
|
930 | 930 | vec2 = numpy.where(0<data_ele) |
|
|
931 | 931 | data_ele= data_ele[vec2] |
|
|
932 | 932 | data_ele_old= data_ele_old[vec2] |
|
|
933 | 933 | ##print(data_ele_new) |
|
|
934 | 934 | data_weather= data_weather[vec2[0]] |
|
|
935 | 935 | |
|
|
936 | 936 | new_i_ele = int(round(data_ele[0])) |
|
|
937 | 937 | new_f_ele = int(round(data_ele[-1])) |
|
|
938 | 938 | #print(new_i_ele) |
|
|
939 | 939 | #print(new_f_ele) |
|
|
940 | 940 | #print(data_ele,len(data_ele)) |
|
|
941 | 941 | #print(data_ele_old,len(data_ele_old)) |
|
|
942 | 942 | if new_i_ele< 2: |
|
|
943 | 943 | self.data_ele_tmp[val_ch] = numpy.ones(ang_max-ang_min)*numpy.nan |
|
|
944 | 944 | self.res_weather[val_ch] = self.replaceNAN(data_weather=self.res_weather[val_ch],data_ele=self.data_ele_tmp[val_ch],val=self.val_mean) |
|
|
945 | 945 | self.data_ele_tmp[val_ch][new_i_ele:new_i_ele+len(data_ele)]=data_ele_old |
|
|
946 | 946 | self.res_ele[new_i_ele:new_i_ele+len(data_ele)]= data_ele |
|
|
947 | 947 | self.res_weather[val_ch][new_i_ele:new_i_ele+len(data_ele),:]= data_weather |
|
|
948 | 948 | data_ele = self.res_ele |
|
|
949 | 949 | data_weather = self.res_weather[val_ch] |
|
|
950 | 950 | |
|
|
951 | 951 | elif tipo_case==1 : #BAJADA |
|
|
952 | 952 | data_ele = data_ele[::-1] # reversa |
|
|
953 | 953 | data_ele_old = data_ele_old[::-1]# reversa |
|
|
954 | 954 | data_weather = data_weather[::-1,:]# reversa |
|
|
955 | 955 | vec= numpy.where(data_ele<ang_max) |
|
|
956 | 956 | data_ele = data_ele[vec] |
|
|
957 | 957 | data_ele_old = data_ele_old[vec] |
|
|
958 | 958 | data_weather = data_weather[vec[0]] |
|
|
959 | 959 | vec2= numpy.where(0<data_ele) |
|
|
960 | 960 | data_ele = data_ele[vec2] |
|
|
961 | 961 | data_ele_old = data_ele_old[vec2] |
|
|
962 | 962 | data_weather = data_weather[vec2[0]] |
|
|
963 | 963 | |
|
|
964 | 964 | |
|
|
965 | 965 | new_i_ele = int(round(data_ele[0])) |
|
|
966 | 966 | new_f_ele = int(round(data_ele[-1])) |
|
|
967 | 967 | #print(data_ele) |
|
|
968 | 968 | #print(ang_max) |
|
|
969 | 969 | #print(data_ele_old) |
|
|
970 | 970 | if new_i_ele <= 1: |
|
|
971 | 971 | new_i_ele = 1 |
|
|
972 | 972 | if round(data_ele[-1])>=ang_max-1: |
|
|
973 | 973 | self.data_ele_tmp[val_ch] = numpy.ones(ang_max-ang_min)*numpy.nan |
|
|
974 | 974 | self.res_weather[val_ch] = self.replaceNAN(data_weather=self.res_weather[val_ch],data_ele=self.data_ele_tmp[val_ch],val=self.val_mean) |
|
|
975 | 975 | self.data_ele_tmp[val_ch][new_i_ele-1:new_i_ele+len(data_ele)-1]=data_ele_old |
|
|
976 | 976 | self.res_ele[new_i_ele-1:new_i_ele+len(data_ele)-1]= data_ele |
|
|
977 | 977 | self.res_weather[val_ch][new_i_ele-1:new_i_ele+len(data_ele)-1,:]= data_weather |
|
|
978 | 978 | data_ele = self.res_ele |
|
|
979 | 979 | data_weather = self.res_weather[val_ch] |
|
|
980 | 980 | |
|
|
981 | 981 | elif tipo_case==2: #bajada |
|
|
982 | 982 | vec = numpy.where(data_ele<ang_max) |
|
|
983 | 983 | data_ele = data_ele[vec] |
|
|
984 | 984 | data_weather= data_weather[vec[0]] |
|
|
985 | 985 | |
|
|
986 | 986 | len_vec = len(vec) |
|
|
987 | 987 | data_ele_new = data_ele[::-1] # reversa |
|
|
988 | 988 | data_weather = data_weather[::-1,:] |
|
|
989 | 989 | new_i_ele = int(data_ele_new[0]) |
|
|
990 | 990 | new_f_ele = int(data_ele_new[-1]) |
|
|
991 | 991 | |
|
|
992 | 992 | n1= new_i_ele- ang_min |
|
|
993 | 993 | n2= ang_max - new_f_ele-1 |
|
|
994 | 994 | if n1>0: |
|
|
995 | 995 | ele1= numpy.linspace(ang_min+1,new_i_ele-1,n1) |
|
|
996 | 996 | ele1_nan= numpy.ones(n1)*numpy.nan |
|
|
997 | 997 | data_ele = numpy.hstack((ele1,data_ele_new)) |
|
|
998 | 998 | data_ele_old = numpy.hstack((ele1_nan,data_ele_new)) |
|
|
999 | 999 | if n2>0: |
|
|
1000 | 1000 | ele2= numpy.linspace(new_f_ele+1,ang_max,n2) |
|
|
1001 | 1001 | ele2_nan= numpy.ones(n2)*numpy.nan |
|
|
1002 | 1002 | data_ele = numpy.hstack((data_ele,ele2)) |
|
|
1003 | 1003 | data_ele_old = numpy.hstack((data_ele_old,ele2_nan)) |
|
|
1004 | 1004 | |
|
|
1005 | 1005 | self.data_ele_tmp[val_ch] = data_ele_old |
|
|
1006 | 1006 | self.res_ele = data_ele |
|
|
1007 | 1007 | self.res_weather[val_ch] = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean) |
|
|
1008 | 1008 | data_ele = self.res_ele |
|
|
1009 | 1009 | data_weather = self.res_weather[val_ch] |
|
|
1010 | 1010 | |
|
|
1011 | 1011 | elif tipo_case==3:#subida |
|
|
1012 | 1012 | vec = numpy.where(0<data_ele) |
|
|
1013 | 1013 | data_ele= data_ele[vec] |
|
|
1014 | 1014 | data_ele_new = data_ele |
|
|
1015 | 1015 | data_ele_old= data_ele_old[vec] |
|
|
1016 | 1016 | data_weather= data_weather[vec[0]] |
|
|
1017 | 1017 | pos_ini = numpy.argmin(data_ele) |
|
|
1018 | 1018 | if pos_ini>0: |
|
|
1019 | 1019 | len_vec= len(data_ele) |
|
|
1020 | 1020 | vec3 = numpy.linspace(pos_ini,len_vec-1,len_vec-pos_ini).astype(int) |
|
|
1021 | 1021 | #print(vec3) |
|
|
1022 | 1022 | data_ele= data_ele[vec3] |
|
|
1023 | 1023 | data_ele_new = data_ele |
|
|
1024 | 1024 | data_ele_old= data_ele_old[vec3] |
|
|
1025 | 1025 | data_weather= data_weather[vec3] |
|
|
1026 | 1026 | |
|
|
1027 | 1027 | new_i_ele = int(data_ele_new[0]) |
|
|
1028 | 1028 | new_f_ele = int(data_ele_new[-1]) |
|
|
1029 | 1029 | n1= new_i_ele- ang_min |
|
|
1030 | 1030 | n2= ang_max - new_f_ele-1 |
|
|
1031 | 1031 | if n1>0: |
|
|
1032 | 1032 | ele1= numpy.linspace(ang_min+1,new_i_ele-1,n1) |
|
|
1033 | 1033 | ele1_nan= numpy.ones(n1)*numpy.nan |
|
|
1034 | 1034 | data_ele = numpy.hstack((ele1,data_ele_new)) |
|
|
1035 | 1035 | data_ele_old = numpy.hstack((ele1_nan,data_ele_new)) |
|
|
1036 | 1036 | if n2>0: |
|
|
1037 | 1037 | ele2= numpy.linspace(new_f_ele+1,ang_max,n2) |
|
|
1038 | 1038 | ele2_nan= numpy.ones(n2)*numpy.nan |
|
|
1039 | 1039 | data_ele = numpy.hstack((data_ele,ele2)) |
|
|
1040 | 1040 | data_ele_old = numpy.hstack((data_ele_old,ele2_nan)) |
|
|
1041 | 1041 | |
|
|
1042 | 1042 | self.data_ele_tmp[val_ch] = data_ele_old |
|
|
1043 | 1043 | self.res_ele = data_ele |
|
|
1044 | 1044 | self.res_weather[val_ch] = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean) |
|
|
1045 | 1045 | data_ele = self.res_ele |
|
|
1046 | 1046 | data_weather = self.res_weather[val_ch] |
|
|
1047 | 1047 | #print("self.data_ele_tmp",self.data_ele_tmp) |
|
|
1048 | 1048 | return data_weather,data_ele |
|
|
1049 | 1049 | |
|
|
1050 | 1050 | |
|
|
1051 | 1051 | def plot(self): |
|
|
1052 | 1052 | thisDatetime = datetime.datetime.utcfromtimestamp(self.data.times[-1]).strftime('%Y-%m-%d %H:%M:%S') |
|
|
1053 | 1053 | data = self.data[-1] |
|
|
1054 | 1054 | r = self.data.yrange |
|
|
1055 | 1055 | delta_height = r[1]-r[0] |
|
|
1056 | 1056 | r_mask = numpy.where(r>=0)[0] |
|
|
1057 | 1057 | ##print("delta_height",delta_height) |
|
|
1058 | 1058 | #print("r_mask",r_mask,len(r_mask)) |
|
|
1059 | 1059 | r = numpy.arange(len(r_mask))*delta_height |
|
|
1060 | 1060 | self.y = 2*r |
|
|
1061 | 1061 | res = 1 |
|
|
1062 | 1062 | ###print("data['weather'].shape[0]",data['weather'].shape[0]) |
|
|
1063 | 1063 | ang_max = self.ang_max |
|
|
1064 | 1064 | ang_min = self.ang_min |
|
|
1065 | 1065 | var_ang =ang_max - ang_min |
|
|
1066 | 1066 | step = (int(var_ang)/(res*data['weather'].shape[0])) |
|
|
1067 | 1067 | ###print("step",step) |
|
|
1068 | 1068 | #-------------------------------------------------------- |
|
|
1069 | 1069 | ##print('weather',data['weather'].shape) |
|
|
1070 | 1070 | ##print('ele',data['ele'].shape) |
|
|
1071 | 1071 | |
|
|
1072 | 1072 | ###self.res_weather, self.res_ele = self.const_ploteo(data_weather=data['weather'][:,r_mask],data_ele=data['ele'],step=step,res=res,ang_max=ang_max,ang_min=ang_min) |
|
|
1073 | 1073 | ###self.res_azi = numpy.mean(data['azi']) |
|
|
1074 | 1074 | ###print("self.res_ele",self.res_ele) |
|
|
1075 | 1075 | plt.clf() |
|
|
1076 | 1076 | subplots = [121, 122] |
|
|
1077 | 1077 | cg={'angular_spacing': 20.} |
|
|
1078 | 1078 | if self.ini==0: |
|
|
1079 | 1079 | self.data_ele_tmp = numpy.ones([self.nplots,int(var_ang)])*numpy.nan |
|
|
1080 | 1080 | self.res_weather= numpy.ones([self.nplots,int(var_ang),len(r_mask)])*numpy.nan |
|
|
1081 | 1081 | print("SHAPE",self.data_ele_tmp.shape) |
|
|
1082 | 1082 | |
|
|
1083 | 1083 | for i,ax in enumerate(self.axes): |
|
|
1084 | 1084 | self.res_weather[i], self.res_ele = self.const_ploteo(val_ch=i, data_weather=data['weather'][i][:,r_mask],data_ele=data['ele'],step=step,res=res,ang_max=ang_max,ang_min=ang_min) |
|
|
1085 | 1085 | self.res_azi = numpy.mean(data['azi']) |
|
|
1086 | 1086 | if i==0: |
|
|
1087 | 1087 | print("*****************************************************************************to plot**************************",self.res_weather[i].shape) |
|
|
1088 | 1088 | self.zmin = self.zmin if self.zmin else 20 |
|
|
1089 | 1089 | self.zmax = self.zmax if self.zmax else 80 |
|
|
1090 | 1090 | if ax.firsttime: |
|
|
1091 | 1091 | #plt.clf() |
|
|
1092 | 1092 | cgax, pm = wrl.vis.plot_rhi(self.res_weather[i],r=r,th=self.res_ele,ax=subplots[i], proj=cg,vmin=self.zmin, vmax=self.zmax) |
|
|
1093 | 1093 | #fig=self.figures[0] |
|
|
1094 | 1094 | else: |
|
|
1095 | 1095 | #plt.clf() |
|
|
1096 | 1096 | if i==0: |
|
|
1097 | 1097 | print(self.res_weather[i]) |
|
|
1098 | 1098 | print(self.res_ele) |
|
|
1099 | 1099 | cgax, pm = wrl.vis.plot_rhi(self.res_weather[i],r=r,th=self.res_ele,ax=subplots[i], proj=cg,vmin=self.zmin, vmax=self.zmax) |
|
|
1100 | 1100 | caax = cgax.parasites[0] |
|
|
1101 | 1101 | paax = cgax.parasites[1] |
|
|
1102 | 1102 | cbar = plt.gcf().colorbar(pm, pad=0.075) |
|
|
1103 | 1103 | caax.set_xlabel('x_range [km]') |
|
|
1104 | 1104 | caax.set_ylabel('y_range [km]') |
|
|
1105 | 1105 | plt.text(1.0, 1.05, 'Elevacion '+str(thisDatetime)+" Step "+str(self.ini)+ " Azi: "+str(round(self.res_azi,2)), transform=caax.transAxes, va='bottom',ha='right') |
|
|
1106 | 1106 | print("***************************self.ini****************************",self.ini) |
|
|
1107 | 1107 | self.ini= self.ini+1 |
|
|
1108 | 1108 | |
|
|
1109 | 1109 | class Weather_vRF_Plot(Plot): |
|
|
1110 | 1110 | CODE = 'PPI' |
|
|
1111 | 1111 | plot_name = 'PPI' |
|
|
1112 | 1112 | #plot_type = 'ppistyle' |
|
|
1113 | 1113 | buffering = False |
|
|
1114 | 1114 | |
|
|
1115 | 1115 | def setup(self): |
|
|
1116 | 1116 | |
|
|
1117 | 1117 | self.ncols = 1 |
|
|
1118 | 1118 | self.nrows = 1 |
|
|
1119 | 1119 | self.width =8 |
|
|
1120 | 1120 | self.height =8 |
|
|
1121 | 1121 | self.nplots= 1 |
|
|
1122 | 1122 | self.ylabel= 'Range [Km]' |
|
|
1123 | 1123 | self.xlabel= 'Range [Km]' |
|
|
1124 | 1124 | self.titles= ['PPI'] |
|
|
1125 | 1125 | self.polar = True |
|
|
1126 | 1126 | if self.channels is not None: |
|
|
1127 | 1127 | self.nplots = len(self.channels) |
|
|
1128 | 1128 | self.nrows = len(self.channels) |
|
|
1129 | 1129 | else: |
|
|
1130 | 1130 | self.nplots = self.data.shape(self.CODE)[0] |
|
|
1131 | 1131 | self.nrows = self.nplots |
|
|
1132 | 1132 | self.channels = list(range(self.nplots)) |
|
|
1133 | 1133 | |
|
|
1134 | 1134 | if self.CODE == 'POWER': |
|
|
1135 | 1135 | self.cb_label = r'Power (dB)' |
|
|
1136 | 1136 | elif self.CODE == 'DOPPLER': |
|
|
1137 | 1137 | self.cb_label = r'Velocity (m/s)' |
|
|
1138 | 1138 | self.colorbar=True |
|
|
1139 | 1139 | self.width = 9 |
|
|
1140 | 1140 | self.height =8 |
|
|
1141 | 1141 | self.ini =0 |
|
|
1142 | 1142 | self.len_azi =0 |
|
|
1143 | 1143 | self.buffer_ini = None |
|
|
1144 | 1144 | self.buffer_ele = None |
|
|
1145 | 1145 | self.plots_adjust.update({'wspace': 0.4, 'hspace':0.4, 'left': 0.15, 'right': 0.9, 'bottom': 0.08}) |
|
|
1146 | 1146 | self.flag =0 |
|
|
1147 | 1147 | self.indicador= 0 |
|
|
1148 | 1148 | self.last_data_ele = None |
|
|
1149 | 1149 | self.val_mean = None |
|
|
1150 | 1150 | |
|
|
1151 | 1151 | def update(self, dataOut): |
|
|
1152 | 1152 | |
|
|
1153 | 1153 | data = {} |
|
|
1154 | 1154 | meta = {} |
|
|
1155 | 1155 | if hasattr(dataOut, 'dataPP_POWER'): |
|
|
1156 | 1156 | factor = 1 |
|
|
1157 | 1157 | if hasattr(dataOut, 'nFFTPoints'): |
|
|
1158 | 1158 | factor = dataOut.normFactor |
|
|
1159 | 1159 | |
|
|
1160 | 1160 | if 'pow' in self.attr_data[0].lower(): |
|
|
1161 | 1161 | data['data'] = 10*numpy.log10(getattr(dataOut, self.attr_data[0])/(factor)) |
|
|
1162 | 1162 | else: |
|
|
1163 | 1163 | data['data'] = getattr(dataOut, self.attr_data[0])/(factor) |
|
|
1164 | 1164 | |
|
|
1165 | 1165 | data['azi'] = dataOut.data_azi |
|
|
1166 | 1166 | data['ele'] = dataOut.data_ele |
|
|
1167 | 1167 | |
|
|
1168 | 1168 | return data, meta |
|
|
1169 | 1169 | |
|
|
1170 | 1170 | def plot(self): |
|
|
1171 | 1171 | data = self.data[-1] |
|
|
1172 | 1172 | r = self.data.yrange |
|
|
1173 | 1173 | delta_height = r[1]-r[0] |
|
|
1174 | 1174 | r_mask = numpy.where(r>=0)[0] |
|
|
1175 | 1175 | self.r_mask = r_mask |
|
|
1176 | 1176 | r = numpy.arange(len(r_mask))*delta_height |
|
|
1177 | 1177 | self.y = 2*r |
|
|
1178 | 1178 | |
|
|
1179 | 1179 | try: |
|
|
1180 | 1180 | z = data['data'][self.channels[0]][:,r_mask] |
|
|
1181 | 1181 | |
|
|
1182 | 1182 | except: |
|
|
1183 | 1183 | z = data['data'][0][:,r_mask] |
|
|
1184 | 1184 | |
|
|
1185 | 1185 | self.titles = [] |
|
|
1186 | 1186 | |
|
|
1187 | 1187 | self.ymax = self.ymax if self.ymax else numpy.nanmax(r) |
|
|
1188 | 1188 | self.ymin = self.ymin if self.ymin else numpy.nanmin(r) |
|
|
1189 | 1189 | self.zmax = self.zmax if self.zmax else numpy.nanmax(z) |
|
|
1190 | 1190 | self.zmin = self.zmin if self.zmin else numpy.nanmin(z) |
|
|
1191 | 1191 | self.ang_min = self.ang_min if self.ang_min else 0 |
|
|
1192 | 1192 | self.ang_max = self.ang_max if self.ang_max else 360 |
|
|
1193 | 1193 | |
|
|
1194 | 1194 | r, theta = numpy.meshgrid(r, numpy.radians(data['azi']) ) |
|
|
1195 | 1195 | |
|
|
1196 | 1196 | for i,ax in enumerate(self.axes): |
|
|
1197 | 1197 | |
|
|
1198 | 1198 | if ax.firsttime: |
|
|
1199 | 1199 | ax.set_xlim(numpy.radians(self.ang_min),numpy.radians(self.ang_max)) |
|
|
1200 | 1200 | ax.plt = ax.pcolormesh(theta, r, z, cmap=self.colormap, vmin=self.zmin, vmax=self.zmax) |
|
|
1201 | 1201 | ax.set_theta_direction(-1) |
|
|
1202 | 1202 | |
|
|
1203 | 1203 | else: |
|
|
1204 | 1204 | ax.set_xlim(numpy.radians(self.ang_min),numpy.radians(self.ang_max)) |
|
|
1205 | 1205 | ax.plt = ax.pcolormesh(theta, r, z, cmap=self.colormap, vmin=self.zmin, vmax=self.zmax) |
|
|
1206 | 1206 | ax.set_theta_direction(-1) |
|
|
1207 | 1207 | |
|
|
1208 | 1208 | ax.grid(True) |
|
|
1209 | 1209 | |
|
|
1210 | 1210 | if len(self.channels) !=1: |
|
|
1211 | 1211 | self.titles = ['PPI {} at EL: {} Channel {}'.format(self.self.labels[x], str(round(numpy.mean(data['ele']),1)), x) for x in range(self.nrows)] |
|
|
1212 | 1212 | else: |
|
|
1213 | 1213 | self.titles = ['PPI {} at EL: {} Channel {}'.format(self.labels[0], str(round(numpy.mean(data['ele']),1)), self.channels[0])] |
|
|
1214 | 1214 | |
|
|
1215 | 1215 | class WeatherRHI_vRF2_Plot(Plot): |
|
|
1216 | 1216 | CODE = 'weather' |
|
|
1217 | 1217 | plot_name = 'weather' |
|
|
1218 | 1218 | plot_type = 'rhistyle' |
|
|
1219 | 1219 | buffering = False |
|
|
1220 | 1220 | data_ele_tmp = None |
|
|
1221 | 1221 | |
|
|
1222 | 1222 | def setup(self): |
|
|
1223 | 1223 | print("********************") |
|
|
1224 | 1224 | print("********************") |
|
|
1225 | 1225 | print("********************") |
|
|
1226 | 1226 | print("SETUP WEATHER PLOT") |
|
|
1227 | 1227 | self.ncols = 1 |
|
|
1228 | 1228 | self.nrows = 1 |
|
|
1229 | 1229 | self.nplots= 1 |
|
|
1230 | 1230 | self.ylabel= 'Range [Km]' |
|
|
1231 | 1231 | self.titles= ['Weather'] |
|
|
1232 | 1232 | if self.channels is not None: |
|
|
1233 | 1233 | self.nplots = len(self.channels) |
|
|
1234 | 1234 | self.nrows = len(self.channels) |
|
|
1235 | 1235 | else: |
|
|
1236 | 1236 | self.nplots = self.data.shape(self.CODE)[0] |
|
|
1237 | 1237 | self.nrows = self.nplots |
|
|
1238 | 1238 | self.channels = list(range(self.nplots)) |
|
|
1239 | 1239 | print("channels",self.channels) |
|
|
1240 | 1240 | print("que saldra", self.data.shape(self.CODE)[0]) |
|
|
1241 | 1241 | self.titles = ['{} Channel {}'.format(self.CODE.upper(), x) for x in range(self.nrows)] |
|
|
1242 | 1242 | print("self.titles",self.titles) |
|
|
1243 | 1243 | self.colorbar=False |
|
|
1244 | 1244 | self.width =8 |
|
|
1245 | 1245 | self.height =8 |
|
|
1246 | 1246 | self.ini =0 |
|
|
1247 | 1247 | self.len_azi =0 |
|
|
1248 | 1248 | self.buffer_ini = None |
|
|
1249 | 1249 | self.buffer_ele = None |
|
|
1250 | 1250 | self.plots_adjust.update({'wspace': 0.4, 'hspace':0.4, 'left': 0.1, 'right': 0.9, 'bottom': 0.08}) |
|
|
1251 | 1251 | self.flag =0 |
|
|
1252 | 1252 | self.indicador= 0 |
|
|
1253 | 1253 | self.last_data_ele = None |
|
|
1254 | 1254 | self.val_mean = None |
|
|
1255 | 1255 | |
|
|
1256 | 1256 | def update(self, dataOut): |
|
|
1257 | 1257 | |
|
|
1258 | 1258 | data = {} |
|
|
1259 | 1259 | meta = {} |
|
|
1260 | 1260 | if hasattr(dataOut, 'dataPP_POWER'): |
|
|
1261 | 1261 | factor = 1 |
|
|
1262 | 1262 | if hasattr(dataOut, 'nFFTPoints'): |
|
|
1263 | 1263 | factor = dataOut.normFactor |
|
|
1264 | 1264 | print("dataOut",dataOut.data_360.shape) |
|
|
1265 | 1265 | # |
|
|
1266 | 1266 | data['weather'] = 10*numpy.log10(dataOut.data_360/(factor)) |
|
|
1267 | 1267 | # |
|
|
1268 | 1268 | #data['weather'] = 10*numpy.log10(dataOut.data_360[1]/(factor)) |
|
|
1269 | 1269 | data['azi'] = dataOut.data_azi |
|
|
1270 | 1270 | data['ele'] = dataOut.data_ele |
|
|
1271 | 1271 | data['case_flag'] = dataOut.case_flag |
|
|
1272 | 1272 | #print("UPDATE") |
|
|
1273 | 1273 | #print("data[weather]",data['weather'].shape) |
|
|
1274 | 1274 | #print("data[azi]",data['azi']) |
|
|
1275 | 1275 | return data, meta |
|
|
1276 | 1276 | |
|
|
1277 | 1277 | def get2List(self,angulos): |
|
|
1278 | 1278 | list1=[] |
|
|
1279 | 1279 | list2=[] |
|
|
1280 | 1280 | for i in reversed(range(len(angulos))): |
|
|
1281 | 1281 | if not i==0:#el caso de i=0 evalula el primero de la lista con el ultimo y no es relevante |
|
|
1282 | 1282 | diff_ = angulos[i]-angulos[i-1] |
|
|
1283 | 1283 | if abs(diff_) >1.5: |
|
|
1284 | 1284 | list1.append(i-1) |
|
|
1285 | 1285 | list2.append(diff_) |
|
|
1286 | 1286 | return list(reversed(list1)),list(reversed(list2)) |
|
|
1287 | 1287 | |
|
|
1288 | 1288 | def fixData90(self,list_,ang_): |
|
|
1289 | 1289 | if list_[0]==-1: |
|
|
1290 | 1290 | vec = numpy.where(ang_<ang_[0]) |
|
|
1291 | 1291 | ang_[vec] = ang_[vec]+90 |
|
|
1292 | 1292 | return ang_ |
|
|
1293 | 1293 | return ang_ |
|
|
1294 | 1294 | |
|
|
1295 | 1295 | def fixData90HL(self,angulos): |
|
|
1296 | 1296 | vec = numpy.where(angulos>=90) |
|
|
1297 | 1297 | angulos[vec]=angulos[vec]-90 |
|
|
1298 | 1298 | return angulos |
|
|
1299 | 1299 | |
|
|
1300 | 1300 | |
|
|
1301 | 1301 | def search_pos(self,pos,list_): |
|
|
1302 | 1302 | for i in range(len(list_)): |
|
|
1303 | 1303 | if pos == list_[i]: |
|
|
1304 | 1304 | return True,i |
|
|
1305 | 1305 | i=None |
|
|
1306 | 1306 | return False,i |
|
|
1307 | 1307 | |
|
|
1308 | 1308 | def fixDataComp(self,ang_,list1_,list2_,tipo_case): |
|
|
1309 | 1309 | size = len(ang_) |
|
|
1310 | 1310 | size2 = 0 |
|
|
1311 | 1311 | for i in range(len(list2_)): |
|
|
1312 | 1312 | size2=size2+round(abs(list2_[i]))-1 |
|
|
1313 | 1313 | new_size= size+size2 |
|
|
1314 | 1314 | ang_new = numpy.zeros(new_size) |
|
|
1315 | 1315 | ang_new2 = numpy.zeros(new_size) |
|
|
1316 | 1316 | |
|
|
1317 | 1317 | tmp = 0 |
|
|
1318 | 1318 | c = 0 |
|
|
1319 | 1319 | for i in range(len(ang_)): |
|
|
1320 | 1320 | ang_new[tmp +c] = ang_[i] |
|
|
1321 | 1321 | ang_new2[tmp+c] = ang_[i] |
|
|
1322 | 1322 | condition , value = self.search_pos(i,list1_) |
|
|
1323 | 1323 | if condition: |
|
|
1324 | 1324 | pos = tmp + c + 1 |
|
|
1325 | 1325 | for k in range(round(abs(list2_[value]))-1): |
|
|
1326 | 1326 | if tipo_case==0 or tipo_case==3:#subida |
|
|
1327 | 1327 | ang_new[pos+k] = ang_new[pos+k-1]+1 |
|
|
1328 | 1328 | ang_new2[pos+k] = numpy.nan |
|
|
1329 | 1329 | elif tipo_case==1 or tipo_case==2:#bajada |
|
|
1330 | 1330 | ang_new[pos+k] = ang_new[pos+k-1]-1 |
|
|
1331 | 1331 | ang_new2[pos+k] = numpy.nan |
|
|
1332 | 1332 | |
|
|
1333 | 1333 | tmp = pos +k |
|
|
1334 | 1334 | c = 0 |
|
|
1335 | 1335 | c=c+1 |
|
|
1336 | 1336 | return ang_new,ang_new2 |
|
|
1337 | 1337 | |
|
|
1338 | 1338 | def globalCheckPED(self,angulos,tipo_case): |
|
|
1339 | 1339 | l1,l2 = self.get2List(angulos) |
|
|
1340 | 1340 | ##print("l1",l1) |
|
|
1341 | 1341 | ##print("l2",l2) |
|
|
1342 | 1342 | if len(l1)>0: |
|
|
1343 | 1343 | #angulos2 = self.fixData90(list_=l1,ang_=angulos) |
|
|
1344 | 1344 | #l1,l2 = self.get2List(angulos2) |
|
|
1345 | 1345 | ang1_,ang2_ = self.fixDataComp(ang_=angulos,list1_=l1,list2_=l2,tipo_case=tipo_case) |
|
|
1346 | 1346 | #ang1_ = self.fixData90HL(ang1_) |
|
|
1347 | 1347 | #ang2_ = self.fixData90HL(ang2_) |
|
|
1348 | 1348 | else: |
|
|
1349 | 1349 | ang1_= angulos |
|
|
1350 | 1350 | ang2_= angulos |
|
|
1351 | 1351 | return ang1_,ang2_ |
|
|
1352 | 1352 | |
|
|
1353 | 1353 | |
|
|
1354 | 1354 | def replaceNAN(self,data_weather,data_ele,val): |
|
|
1355 | 1355 | data= data_ele |
|
|
1356 | 1356 | data_T= data_weather |
|
|
1357 | 1357 | if data.shape[0]> data_T.shape[0]: |
|
|
1358 | 1358 | data_N = numpy.ones( [data.shape[0],data_T.shape[1]]) |
|
|
1359 | 1359 | c = 0 |
|
|
1360 | 1360 | for i in range(len(data)): |
|
|
1361 | 1361 | if numpy.isnan(data[i]): |
|
|
1362 | 1362 | data_N[i,:]=numpy.ones(data_T.shape[1])*numpy.nan |
|
|
1363 | 1363 | else: |
|
|
1364 | 1364 | data_N[i,:]=data_T[c,:] |
|
|
1365 | 1365 | c=c+1 |
|
|
1366 | 1366 | return data_N |
|
|
1367 | 1367 | else: |
|
|
1368 | 1368 | for i in range(len(data)): |
|
|
1369 | 1369 | if numpy.isnan(data[i]): |
|
|
1370 | 1370 | data_T[i,:]=numpy.ones(data_T.shape[1])*numpy.nan |
|
|
1371 | 1371 | return data_T |
|
|
1372 | 1372 | |
|
|
1373 | 1373 | def check_case(self,data_ele,ang_max,ang_min): |
|
|
1374 | 1374 | start = data_ele[0] |
|
|
1375 | 1375 | end = data_ele[-1] |
|
|
1376 | 1376 | number = (end-start) |
|
|
1377 | 1377 | len_ang=len(data_ele) |
|
|
1378 | 1378 | print("start",start) |
|
|
1379 | 1379 | print("end",end) |
|
|
1380 | 1380 | print("number",number) |
|
|
1381 | 1381 | |
|
|
1382 | 1382 | print("len_ang",len_ang) |
|
|
1383 | 1383 | |
|
|
1384 | 1384 | #exit(1) |
|
|
1385 | 1385 | |
|
|
1386 | 1386 | if start<end and (round(abs(number)+1)>=len_ang or (numpy.argmin(data_ele)==0)):#caso subida |
|
|
1387 | 1387 | return 0 |
|
|
1388 | 1388 | #elif start>end and (round(abs(number)+1)>=len_ang or(numpy.argmax(data_ele)==0)):#caso bajada |
|
|
1389 | 1389 | # return 1 |
|
|
1390 | 1390 | elif round(abs(number)+1)>=len_ang and (start>end or(numpy.argmax(data_ele)==0)):#caso bajada |
|
|
1391 | 1391 | return 1 |
|
|
1392 | 1392 | elif round(abs(number)+1)<len_ang and data_ele[-2]>data_ele[-1]:# caso BAJADA CAMBIO ANG MAX |
|
|
1393 | 1393 | return 2 |
|
|
1394 | 1394 | elif round(abs(number)+1)<len_ang and data_ele[-2]<data_ele[-1] :# caso SUBIDA CAMBIO ANG MIN |
|
|
1395 | 1395 | return 3 |
|
|
1396 | 1396 | |
|
|
1397 | 1397 | |
|
|
1398 | 1398 | def const_ploteo(self,val_ch,data_weather,data_ele,step,res,ang_max,ang_min,case_flag): |
|
|
1399 | 1399 | ang_max= ang_max |
|
|
1400 | 1400 | ang_min= ang_min |
|
|
1401 | 1401 | data_weather=data_weather |
|
|
1402 | 1402 | val_ch=val_ch |
|
|
1403 | 1403 | ##print("*********************DATA WEATHER**************************************") |
|
|
1404 | 1404 | ##print(data_weather) |
|
|
1405 | 1405 | if self.ini==0: |
|
|
1406 | 1406 | ''' |
|
|
1407 | 1407 | print("**********************************************") |
|
|
1408 | 1408 | print("**********************************************") |
|
|
1409 | 1409 | print("***************ini**************") |
|
|
1410 | 1410 | print("**********************************************") |
|
|
1411 | 1411 | print("**********************************************") |
|
|
1412 | 1412 | ''' |
|
|
1413 | 1413 | #print("data_ele",data_ele) |
|
|
1414 | 1414 | #---------------------------------------------------------- |
|
|
1415 | 1415 | tipo_case = case_flag[-1] |
|
|
1416 | 1416 | #tipo_case = self.check_case(data_ele,ang_max,ang_min) |
|
|
1417 | 1417 | print("check_case",tipo_case) |
|
|
1418 | 1418 | #exit(1) |
|
|
1419 | 1419 | #--------------------- new ------------------------- |
|
|
1420 | 1420 | data_ele_new ,data_ele_old= self.globalCheckPED(data_ele,tipo_case) |
|
|
1421 | 1421 | |
|
|
1422 | 1422 | #-------------------------CAMBIOS RHI--------------------------------- |
|
|
1423 | 1423 | start= ang_min |
|
|
1424 | 1424 | end = ang_max |
|
|
1425 | 1425 | n= (ang_max-ang_min)/res |
|
|
1426 | 1426 | #------ new |
|
|
1427 | 1427 | self.start_data_ele = data_ele_new[0] |
|
|
1428 | 1428 | self.end_data_ele = data_ele_new[-1] |
|
|
1429 | 1429 | if tipo_case==0 or tipo_case==3: # SUBIDA |
|
|
1430 | 1430 | n1= round(self.start_data_ele)- start |
|
|
1431 | 1431 | n2= end - round(self.end_data_ele) |
|
|
1432 | 1432 | print(self.start_data_ele) |
|
|
1433 | 1433 | print(self.end_data_ele) |
|
|
1434 | 1434 | if n1>0: |
|
|
1435 | 1435 | ele1= numpy.linspace(ang_min+1,self.start_data_ele-1,n1) |
|
|
1436 | 1436 | ele1_nan= numpy.ones(n1)*numpy.nan |
|
|
1437 | 1437 | data_ele = numpy.hstack((ele1,data_ele_new)) |
|
|
1438 | 1438 | print("ele1_nan",ele1_nan.shape) |
|
|
1439 | 1439 | print("data_ele_old",data_ele_old.shape) |
|
|
1440 | 1440 | data_ele_old = numpy.hstack((ele1_nan,data_ele_old)) |
|
|
1441 | 1441 | if n2>0: |
|
|
1442 | 1442 | ele2= numpy.linspace(self.end_data_ele+1,end,n2) |
|
|
1443 | 1443 | ele2_nan= numpy.ones(n2)*numpy.nan |
|
|
1444 | 1444 | data_ele = numpy.hstack((data_ele,ele2)) |
|
|
1445 | 1445 | print("ele2_nan",ele2_nan.shape) |
|
|
1446 | 1446 | print("data_ele_old",data_ele_old.shape) |
|
|
1447 | 1447 | data_ele_old = numpy.hstack((data_ele_old,ele2_nan)) |
|
|
1448 | 1448 | |
|
|
1449 | 1449 | if tipo_case==1 or tipo_case==2: # BAJADA |
|
|
1450 | 1450 | data_ele_new = data_ele_new[::-1] # reversa |
|
|
1451 | 1451 | data_ele_old = data_ele_old[::-1]# reversa |
|
|
1452 | 1452 | data_weather = data_weather[::-1,:]# reversa |
|
|
1453 | 1453 | vec= numpy.where(data_ele_new<ang_max) |
|
|
1454 | 1454 | data_ele_new = data_ele_new[vec] |
|
|
1455 | 1455 | data_ele_old = data_ele_old[vec] |
|
|
1456 | 1456 | data_weather = data_weather[vec[0]] |
|
|
1457 | 1457 | vec2= numpy.where(0<data_ele_new) |
|
|
1458 | 1458 | data_ele_new = data_ele_new[vec2] |
|
|
1459 | 1459 | data_ele_old = data_ele_old[vec2] |
|
|
1460 | 1460 | data_weather = data_weather[vec2[0]] |
|
|
1461 | 1461 | self.start_data_ele = data_ele_new[0] |
|
|
1462 | 1462 | self.end_data_ele = data_ele_new[-1] |
|
|
1463 | 1463 | |
|
|
1464 | 1464 | n1= round(self.start_data_ele)- start |
|
|
1465 | 1465 | n2= end - round(self.end_data_ele)-1 |
|
|
1466 | 1466 | print(self.start_data_ele) |
|
|
1467 | 1467 | print(self.end_data_ele) |
|
|
1468 | 1468 | if n1>0: |
|
|
1469 | 1469 | ele1= numpy.linspace(ang_min+1,self.start_data_ele-1,n1) |
|
|
1470 | 1470 | ele1_nan= numpy.ones(n1)*numpy.nan |
|
|
1471 | 1471 | data_ele = numpy.hstack((ele1,data_ele_new)) |
|
|
1472 | 1472 | data_ele_old = numpy.hstack((ele1_nan,data_ele_old)) |
|
|
1473 | 1473 | if n2>0: |
|
|
1474 | 1474 | ele2= numpy.linspace(self.end_data_ele+1,end,n2) |
|
|
1475 | 1475 | ele2_nan= numpy.ones(n2)*numpy.nan |
|
|
1476 | 1476 | data_ele = numpy.hstack((data_ele,ele2)) |
|
|
1477 | 1477 | data_ele_old = numpy.hstack((data_ele_old,ele2_nan)) |
|
|
1478 | 1478 | # RADAR |
|
|
1479 | 1479 | # NOTA data_ele y data_weather es la variable que retorna |
|
|
1480 | 1480 | val_mean = numpy.mean(data_weather[:,-1]) |
|
|
1481 | 1481 | self.val_mean = val_mean |
|
|
1482 | 1482 | data_weather = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean) |
|
|
1483 | 1483 | print("eleold",data_ele_old) |
|
|
1484 | 1484 | print(self.data_ele_tmp[val_ch]) |
|
|
1485 | 1485 | print(data_ele_old.shape[0]) |
|
|
1486 | 1486 | print(self.data_ele_tmp[val_ch].shape[0]) |
|
|
1487 | 1487 | if (data_ele_old.shape[0]==91 or self.data_ele_tmp[val_ch].shape[0]==91): |
|
|
1488 | 1488 | import sys |
|
|
1489 | 1489 | print("EXIT",self.ini) |
|
|
1490 | 1490 | |
|
|
1491 | 1491 | sys.exit(1) |
|
|
1492 | 1492 | self.data_ele_tmp[val_ch]= data_ele_old |
|
|
1493 | 1493 | else: |
|
|
1494 | 1494 | #print("**********************************************") |
|
|
1495 | 1495 | #print("****************VARIABLE**********************") |
|
|
1496 | 1496 | #-------------------------CAMBIOS RHI--------------------------------- |
|
|
1497 | 1497 | #--------------------------------------------------------------------- |
|
|
1498 | 1498 | ##print("INPUT data_ele",data_ele) |
|
|
1499 | 1499 | flag=0 |
|
|
1500 | 1500 | start_ele = self.res_ele[0] |
|
|
1501 | 1501 | #tipo_case = self.check_case(data_ele,ang_max,ang_min) |
|
|
1502 | 1502 | tipo_case = case_flag[-1] |
|
|
1503 | 1503 | #print("TIPO DE DATA",tipo_case) |
|
|
1504 | 1504 | #-----------new------------ |
|
|
1505 | 1505 | data_ele ,data_ele_old = self.globalCheckPED(data_ele,tipo_case) |
|
|
1506 | 1506 | data_weather = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean) |
|
|
1507 | 1507 | |
|
|
1508 | 1508 | #-------------------------------NEW RHI ITERATIVO------------------------- |
|
|
1509 | 1509 | |
|
|
1510 | 1510 | if tipo_case==0 : # SUBIDA |
|
|
1511 | 1511 | vec = numpy.where(data_ele<ang_max) |
|
|
1512 | 1512 | data_ele = data_ele[vec] |
|
|
1513 | 1513 | data_ele_old = data_ele_old[vec] |
|
|
1514 | 1514 | data_weather = data_weather[vec[0]] |
|
|
1515 | 1515 | |
|
|
1516 | 1516 | vec2 = numpy.where(0<data_ele) |
|
|
1517 | 1517 | data_ele= data_ele[vec2] |
|
|
1518 | 1518 | data_ele_old= data_ele_old[vec2] |
|
|
1519 | 1519 | ##print(data_ele_new) |
|
|
1520 | 1520 | data_weather= data_weather[vec2[0]] |
|
|
1521 | 1521 | |
|
|
1522 | 1522 | new_i_ele = int(round(data_ele[0])) |
|
|
1523 | 1523 | new_f_ele = int(round(data_ele[-1])) |
|
|
1524 | 1524 | #print(new_i_ele) |
|
|
1525 | 1525 | #print(new_f_ele) |
|
|
1526 | 1526 | #print(data_ele,len(data_ele)) |
|
|
1527 | 1527 | #print(data_ele_old,len(data_ele_old)) |
|
|
1528 | 1528 | if new_i_ele< 2: |
|
|
1529 | 1529 | self.data_ele_tmp[val_ch] = numpy.ones(ang_max-ang_min)*numpy.nan |
|
|
1530 | 1530 | self.res_weather[val_ch] = self.replaceNAN(data_weather=self.res_weather[val_ch],data_ele=self.data_ele_tmp[val_ch],val=self.val_mean) |
|
|
1531 | 1531 | self.data_ele_tmp[val_ch][new_i_ele:new_i_ele+len(data_ele)]=data_ele_old |
|
|
1532 | 1532 | self.res_ele[new_i_ele:new_i_ele+len(data_ele)]= data_ele |
|
|
1533 | 1533 | self.res_weather[val_ch][new_i_ele:new_i_ele+len(data_ele),:]= data_weather |
|
|
1534 | 1534 | data_ele = self.res_ele |
|
|
1535 | 1535 | data_weather = self.res_weather[val_ch] |
|
|
1536 | 1536 | |
|
|
1537 | 1537 | elif tipo_case==1 : #BAJADA |
|
|
1538 | 1538 | data_ele = data_ele[::-1] # reversa |
|
|
1539 | 1539 | data_ele_old = data_ele_old[::-1]# reversa |
|
|
1540 | 1540 | data_weather = data_weather[::-1,:]# reversa |
|
|
1541 | 1541 | vec= numpy.where(data_ele<ang_max) |
|
|
1542 | 1542 | data_ele = data_ele[vec] |
|
|
1543 | 1543 | data_ele_old = data_ele_old[vec] |
|
|
1544 | 1544 | data_weather = data_weather[vec[0]] |
|
|
1545 | 1545 | vec2= numpy.where(0<data_ele) |
|
|
1546 | 1546 | data_ele = data_ele[vec2] |
|
|
1547 | 1547 | data_ele_old = data_ele_old[vec2] |
|
|
1548 | 1548 | data_weather = data_weather[vec2[0]] |
|
|
1549 | 1549 | |
|
|
1550 | 1550 | |
|
|
1551 | 1551 | new_i_ele = int(round(data_ele[0])) |
|
|
1552 | 1552 | new_f_ele = int(round(data_ele[-1])) |
|
|
1553 | 1553 | #print(data_ele) |
|
|
1554 | 1554 | #print(ang_max) |
|
|
1555 | 1555 | #print(data_ele_old) |
|
|
1556 | 1556 | if new_i_ele <= 1: |
|
|
1557 | 1557 | new_i_ele = 1 |
|
|
1558 | 1558 | if round(data_ele[-1])>=ang_max-1: |
|
|
1559 | 1559 | self.data_ele_tmp[val_ch] = numpy.ones(ang_max-ang_min)*numpy.nan |
|
|
1560 | 1560 | self.res_weather[val_ch] = self.replaceNAN(data_weather=self.res_weather[val_ch],data_ele=self.data_ele_tmp[val_ch],val=self.val_mean) |
|
|
1561 | 1561 | self.data_ele_tmp[val_ch][new_i_ele-1:new_i_ele+len(data_ele)-1]=data_ele_old |
|
|
1562 | 1562 | self.res_ele[new_i_ele-1:new_i_ele+len(data_ele)-1]= data_ele |
|
|
1563 | 1563 | self.res_weather[val_ch][new_i_ele-1:new_i_ele+len(data_ele)-1,:]= data_weather |
|
|
1564 | 1564 | data_ele = self.res_ele |
|
|
1565 | 1565 | data_weather = self.res_weather[val_ch] |
|
|
1566 | 1566 | |
|
|
1567 | 1567 | elif tipo_case==2: #bajada |
|
|
1568 | 1568 | vec = numpy.where(data_ele<ang_max) |
|
|
1569 | 1569 | data_ele = data_ele[vec] |
|
|
1570 | 1570 | data_weather= data_weather[vec[0]] |
|
|
1571 | 1571 | |
|
|
1572 | 1572 | len_vec = len(vec) |
|
|
1573 | 1573 | data_ele_new = data_ele[::-1] # reversa |
|
|
1574 | 1574 | data_weather = data_weather[::-1,:] |
|
|
1575 | 1575 | new_i_ele = int(data_ele_new[0]) |
|
|
1576 | 1576 | new_f_ele = int(data_ele_new[-1]) |
|
|
1577 | 1577 | |
|
|
1578 | 1578 | n1= new_i_ele- ang_min |
|
|
1579 | 1579 | n2= ang_max - new_f_ele-1 |
|
|
1580 | 1580 | if n1>0: |
|
|
1581 | 1581 | ele1= numpy.linspace(ang_min+1,new_i_ele-1,n1) |
|
|
1582 | 1582 | ele1_nan= numpy.ones(n1)*numpy.nan |
|
|
1583 | 1583 | data_ele = numpy.hstack((ele1,data_ele_new)) |
|
|
1584 | 1584 | data_ele_old = numpy.hstack((ele1_nan,data_ele_new)) |
|
|
1585 | 1585 | if n2>0: |
|
|
1586 | 1586 | ele2= numpy.linspace(new_f_ele+1,ang_max,n2) |
|
|
1587 | 1587 | ele2_nan= numpy.ones(n2)*numpy.nan |
|
|
1588 | 1588 | data_ele = numpy.hstack((data_ele,ele2)) |
|
|
1589 | 1589 | data_ele_old = numpy.hstack((data_ele_old,ele2_nan)) |
|
|
1590 | 1590 | |
|
|
1591 | 1591 | self.data_ele_tmp[val_ch] = data_ele_old |
|
|
1592 | 1592 | self.res_ele = data_ele |
|
|
1593 | 1593 | self.res_weather[val_ch] = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean) |
|
|
1594 | 1594 | data_ele = self.res_ele |
|
|
1595 | 1595 | data_weather = self.res_weather[val_ch] |
|
|
1596 | 1596 | |
|
|
1597 | 1597 | elif tipo_case==3:#subida |
|
|
1598 | 1598 | vec = numpy.where(0<data_ele) |
|
|
1599 | 1599 | data_ele= data_ele[vec] |
|
|
1600 | 1600 | data_ele_new = data_ele |
|
|
1601 | 1601 | data_ele_old= data_ele_old[vec] |
|
|
1602 | 1602 | data_weather= data_weather[vec[0]] |
|
|
1603 | 1603 | pos_ini = numpy.argmin(data_ele) |
|
|
1604 | 1604 | if pos_ini>0: |
|
|
1605 | 1605 | len_vec= len(data_ele) |
|
|
1606 | 1606 | vec3 = numpy.linspace(pos_ini,len_vec-1,len_vec-pos_ini).astype(int) |
|
|
1607 | 1607 | #print(vec3) |
|
|
1608 | 1608 | data_ele= data_ele[vec3] |
|
|
1609 | 1609 | data_ele_new = data_ele |
|
|
1610 | 1610 | data_ele_old= data_ele_old[vec3] |
|
|
1611 | 1611 | data_weather= data_weather[vec3] |
|
|
1612 | 1612 | |
|
|
1613 | 1613 | new_i_ele = int(data_ele_new[0]) |
|
|
1614 | 1614 | new_f_ele = int(data_ele_new[-1]) |
|
|
1615 | 1615 | n1= new_i_ele- ang_min |
|
|
1616 | 1616 | n2= ang_max - new_f_ele-1 |
|
|
1617 | 1617 | if n1>0: |
|
|
1618 | 1618 | ele1= numpy.linspace(ang_min+1,new_i_ele-1,n1) |
|
|
1619 | 1619 | ele1_nan= numpy.ones(n1)*numpy.nan |
|
|
1620 | 1620 | data_ele = numpy.hstack((ele1,data_ele_new)) |
|
|
1621 | 1621 | data_ele_old = numpy.hstack((ele1_nan,data_ele_new)) |
|
|
1622 | 1622 | if n2>0: |
|
|
1623 | 1623 | ele2= numpy.linspace(new_f_ele+1,ang_max,n2) |
|
|
1624 | 1624 | ele2_nan= numpy.ones(n2)*numpy.nan |
|
|
1625 | 1625 | data_ele = numpy.hstack((data_ele,ele2)) |
|
|
1626 | 1626 | data_ele_old = numpy.hstack((data_ele_old,ele2_nan)) |
|
|
1627 | 1627 | |
|
|
1628 | 1628 | self.data_ele_tmp[val_ch] = data_ele_old |
|
|
1629 | 1629 | self.res_ele = data_ele |
|
|
1630 | 1630 | self.res_weather[val_ch] = self.replaceNAN(data_weather=data_weather,data_ele=data_ele_old,val=self.val_mean) |
|
|
1631 | 1631 | data_ele = self.res_ele |
|
|
1632 | 1632 | data_weather = self.res_weather[val_ch] |
|
|
1633 | 1633 | #print("self.data_ele_tmp",self.data_ele_tmp) |
|
|
1634 | 1634 | return data_weather,data_ele |
|
|
1635 | 1635 | |
|
|
1636 | 1636 | |
|
|
1637 | 1637 | def plot(self): |
|
|
1638 | 1638 | thisDatetime = datetime.datetime.utcfromtimestamp(self.data.times[-1]).strftime('%Y-%m-%d %H:%M:%S') |
|
|
1639 | 1639 | data = self.data[-1] |
|
|
1640 | 1640 | r = self.data.yrange |
|
|
1641 | 1641 | delta_height = r[1]-r[0] |
|
|
1642 | 1642 | r_mask = numpy.where(r>=0)[0] |
|
|
1643 | 1643 | ##print("delta_height",delta_height) |
|
|
1644 | 1644 | #print("r_mask",r_mask,len(r_mask)) |
|
|
1645 | 1645 | r = numpy.arange(len(r_mask))*delta_height |
|
|
1646 | 1646 | self.y = 2*r |
|
|
1647 | 1647 | res = 1 |
|
|
1648 | 1648 | ###print("data['weather'].shape[0]",data['weather'].shape[0]) |
|
|
1649 | 1649 | ang_max = self.ang_max |
|
|
1650 | 1650 | ang_min = self.ang_min |
|
|
1651 | 1651 | var_ang =ang_max - ang_min |
|
|
1652 | 1652 | step = (int(var_ang)/(res*data['weather'].shape[0])) |
|
|
1653 | 1653 | ###print("step",step) |
|
|
1654 | 1654 | #-------------------------------------------------------- |
|
|
1655 | 1655 | ##print('weather',data['weather'].shape) |
|
|
1656 | 1656 | ##print('ele',data['ele'].shape) |
|
|
1657 | 1657 | |
|
|
1658 | 1658 | ###self.res_weather, self.res_ele = self.const_ploteo(data_weather=data['weather'][:,r_mask],data_ele=data['ele'],step=step,res=res,ang_max=ang_max,ang_min=ang_min) |
|
|
1659 | 1659 | ###self.res_azi = numpy.mean(data['azi']) |
|
|
1660 | 1660 | ###print("self.res_ele",self.res_ele) |
|
|
1661 | 1661 | plt.clf() |
|
|
1662 | 1662 | subplots = [121, 122] |
|
|
1663 | 1663 | try: |
|
|
1664 | 1664 | if self.data[-2]['ele'].max()<data['ele'].max(): |
|
|
1665 | 1665 | self.ini=0 |
|
|
1666 | 1666 | except: |
|
|
1667 | 1667 | pass |
|
|
1668 | 1668 | if self.ini==0: |
|
|
1669 | 1669 | self.data_ele_tmp = numpy.ones([self.nplots,int(var_ang)])*numpy.nan |
|
|
1670 | 1670 | self.res_weather= numpy.ones([self.nplots,int(var_ang),len(r_mask)])*numpy.nan |
|
|
1671 | 1671 | print("SHAPE",self.data_ele_tmp.shape) |
|
|
1672 | 1672 | |
|
|
1673 | 1673 | for i,ax in enumerate(self.axes): |
|
|
1674 | 1674 | self.res_weather[i], self.res_ele = self.const_ploteo(val_ch=i, data_weather=data['weather'][i][:,r_mask],data_ele=data['ele'],step=step,res=res,ang_max=ang_max,ang_min=ang_min,case_flag=self.data['case_flag']) |
|
|
1675 | 1675 | self.res_azi = numpy.mean(data['azi']) |
|
|
1676 | 1676 | |
|
|
1677 | 1677 | if ax.firsttime: |
|
|
1678 | 1678 | #plt.clf() |
|
|
1679 | 1679 | print("Frist Plot") |
|
|
1680 | 1680 | cgax, pm = wrl.vis.plot_rhi(self.res_weather[i],r=r,th=self.res_ele,ax=subplots[i], proj='cg',vmin=20, vmax=80) |
|
|
1681 | 1681 | #fig=self.figures[0] |
|
|
1682 | 1682 | else: |
|
|
1683 | 1683 | #plt.clf() |
|
|
1684 | 1684 | print("ELSE PLOT") |
|
|
1685 | 1685 | cgax, pm = wrl.vis.plot_rhi(self.res_weather[i],r=r,th=self.res_ele,ax=subplots[i], proj='cg',vmin=20, vmax=80) |
|
|
1686 | 1686 | caax = cgax.parasites[0] |
|
|
1687 | 1687 | paax = cgax.parasites[1] |
|
|
1688 | 1688 | cbar = plt.gcf().colorbar(pm, pad=0.075) |
|
|
1689 | 1689 | caax.set_xlabel('x_range [km]') |
|
|
1690 | 1690 | caax.set_ylabel('y_range [km]') |
|
|
1691 | 1691 | plt.text(1.0, 1.05, 'Elevacion '+str(thisDatetime)+" Step "+str(self.ini)+ " Azi: "+str(round(self.res_azi,2)), transform=caax.transAxes, va='bottom',ha='right') |
|
|
1692 | 1692 | print("***************************self.ini****************************",self.ini) |
|
|
1693 | 1693 | self.ini= self.ini+1 |
|
|
1694 | 1694 | |
|
|
1695 | 1695 | |
|
|
1696 | 1696 | |
|
|
1697 | 1697 | |
|
|
1698 | 1698 | |
|
|
1699 | 1699 | class WeatherRHI_vRF4_Plot(Plot): |
|
|
1700 | 1700 | CODE = 'RHI' |
|
|
1701 | 1701 | plot_name = 'RHI' |
|
|
1702 | 1702 | #plot_type = 'rhistyle' |
|
|
1703 | 1703 | buffering = False |
|
|
1704 | 1704 | |
|
|
1705 | 1705 | def setup(self): |
|
|
1706 | 1706 | |
|
|
1707 | 1707 | self.ncols = 1 |
|
|
1708 | 1708 | self.nrows = 1 |
|
|
1709 | 1709 | self.nplots= 1 |
|
|
1710 | 1710 | self.ylabel= 'Range [Km]' |
|
|
1711 | 1711 | self.xlabel= 'Range [Km]' |
|
|
1712 | 1712 | self.titles= ['RHI'] |
|
|
1713 | 1713 | self.polar = True |
|
|
1714 | 1714 | self.grid = True |
|
|
1715 | 1715 | if self.channels is not None: |
|
|
1716 | 1716 | self.nplots = len(self.channels) |
|
|
1717 | 1717 | self.nrows = len(self.channels) |
|
|
1718 | 1718 | else: |
|
|
1719 | 1719 | self.nplots = self.data.shape(self.CODE)[0] |
|
|
1720 | 1720 | self.nrows = self.nplots |
|
|
1721 | 1721 | self.channels = list(range(self.nplots)) |
|
|
1722 | 1722 | |
|
|
1723 | 1723 | if self.CODE == 'Power': |
|
|
1724 | 1724 | self.cb_label = r'Power (dB)' |
|
|
1725 | 1725 | elif self.CODE == 'Doppler': |
|
|
1726 | 1726 | self.cb_label = r'Velocity (m/s)' |
|
|
1727 | 1727 | self.colorbar=True |
|
|
1728 | 1728 | self.width =8 |
|
|
1729 | 1729 | self.height =8 |
|
|
1730 | 1730 | self.ini =0 |
|
|
1731 | 1731 | self.len_azi =0 |
|
|
1732 | 1732 | self.buffer_ini = None |
|
|
1733 | 1733 | self.buffer_ele = None |
|
|
1734 | 1734 | self.plots_adjust.update({'wspace': 0.4, 'hspace':0.4, 'left': 0.1, 'right': 0.9, 'bottom': 0.08}) |
|
|
1735 | 1735 | self.flag =0 |
|
|
1736 | 1736 | self.indicador= 0 |
|
|
1737 | 1737 | self.last_data_ele = None |
|
|
1738 | 1738 | self.val_mean = None |
|
|
1739 | 1739 | |
|
|
1740 | 1740 | def update(self, dataOut): |
|
|
1741 | 1741 | |
|
|
1742 | 1742 | data = {} |
|
|
1743 | 1743 | meta = {} |
|
|
1744 | 1744 | if hasattr(dataOut, 'dataPP_POWER'): |
|
|
1745 | 1745 | factor = 1 |
|
|
1746 | 1746 | if hasattr(dataOut, 'nFFTPoints'): |
|
|
1747 | 1747 | factor = dataOut.normFactor |
|
|
1748 | 1748 | |
|
|
1749 | 1749 | if 'pow' in self.attr_data[0].lower(): |
|
|
1750 | 1750 | data['data'] = 10*numpy.log10(getattr(dataOut, self.attr_data[0])/(factor)) |
|
|
1751 | 1751 | else: |
|
|
1752 | 1752 | data['data'] = getattr(dataOut, self.attr_data[0])/(factor) |
|
|
1753 | 1753 | |
|
|
1754 | 1754 | data['azi'] = dataOut.data_azi |
|
|
1755 | 1755 | data['ele'] = dataOut.data_ele |
|
|
1756 | 1756 | |
|
|
1757 | 1757 | return data, meta |
|
|
1758 | 1758 | |
|
|
1759 | 1759 | def plot(self): |
|
|
1760 | 1760 | data = self.data[-1] |
|
|
1761 | 1761 | r = self.data.yrange |
|
|
1762 | 1762 | delta_height = r[1]-r[0] |
|
|
1763 | 1763 | r_mask = numpy.where(r>=0)[0] |
|
|
1764 | 1764 | self.r_mask =r_mask |
|
|
1765 | 1765 | r = numpy.arange(len(r_mask))*delta_height |
|
|
1766 | 1766 | self.y = 2*r |
|
|
1767 | 1767 | |
|
|
1768 | 1768 | try: |
|
|
1769 | 1769 | z = data['data'][self.channels[0]][:,r_mask] |
|
|
1770 | 1770 | except: |
|
|
1771 | 1771 | z = data['data'][0][:,r_mask] |
|
|
1772 | 1772 | |
|
|
1773 | 1773 | self.titles = [] |
|
|
1774 | 1774 | |
|
|
1775 | 1775 | self.ymax = self.ymax if self.ymax else numpy.nanmax(r) |
|
|
1776 | 1776 | self.ymin = self.ymin if self.ymin else numpy.nanmin(r) |
|
|
1777 | 1777 | self.zmax = self.zmax if self.zmax else numpy.nanmax(z) |
|
|
1778 | 1778 | self.zmin = self.zmin if self.zmin else numpy.nanmin(z) |
|
|
1779 | 1779 | self.ang_min = self.ang_min if self.ang_min else 0 |
|
|
1780 | 1780 | self.ang_max = self.ang_max if self.ang_max else 90 |
|
|
1781 | 1781 | |
|
|
1782 | 1782 | r, theta = numpy.meshgrid(r, numpy.radians(data['ele']) ) |
|
|
1783 | 1783 | |
|
|
1784 | 1784 | for i,ax in enumerate(self.axes): |
|
|
1785 | 1785 | |
|
|
1786 | 1786 | if ax.firsttime: |
|
|
1787 | 1787 | ax.set_xlim(numpy.radians(self.ang_min),numpy.radians(self.ang_max)) |
|
|
1788 | 1788 | ax.plt = ax.pcolormesh(theta, r, z, cmap=self.colormap, vmin=self.zmin, vmax=self.zmax) |
|
|
1789 | 1789 | |
|
|
1790 | 1790 | else: |
|
|
1791 | 1791 | ax.set_xlim(numpy.radians(self.ang_min),numpy.radians(self.ang_max)) |
|
|
1792 | 1792 | ax.plt = ax.pcolormesh(theta, r, z, cmap=self.colormap, vmin=self.zmin, vmax=self.zmax) |
|
|
1793 | 1793 | ax.grid(True) |
|
|
1794 | 1794 | if len(self.channels) !=1: |
|
|
1795 | 1795 | self.titles = ['RHI {} at AZ: {} Channel {}'.format(self.labels[x], str(round(numpy.mean(data['azi']),1)), x) for x in range(self.nrows)] |
|
|
1796 | 1796 | else: |
|
|
1797 | 1797 | self.titles = ['RHI {} at AZ: {} Channel {}'.format(self.labels[0], str(round(numpy.mean(data['azi']),1)), self.channels[0])] |
|
|
1798 | 1798 | |
|
|
1799 | 1799 | class WeatherParamsPlot(Plot): |
|
|
1800 | 1800 | #CODE = 'RHI' |
|
|
1801 | 1801 | #plot_name = 'RHI' |
|
|
1802 | 1802 | #plot_type = 'rhistyle' |
|
|
1803 | 1803 | buffering = False |
|
|
1804 | 1804 | |
|
|
1805 | 1805 | def setup(self): |
|
|
1806 | 1806 | |
|
|
1807 | 1807 | self.ncols = 1 |
|
|
1808 | 1808 | self.nrows = 1 |
|
|
1809 | 1809 | self.nplots= 1 |
|
|
1810 | 1810 | self.ylabel= 'Range [km]' |
|
|
1811 | 1811 | self.xlabel= 'Range [km]' |
|
|
1812 | 1812 | self.polar = True |
|
|
1813 | 1813 | self.grid = True |
|
|
1814 | 1814 | if self.channels is not None: |
|
|
1815 | 1815 | self.nplots = len(self.channels) |
|
|
1816 | 1816 | self.nrows = len(self.channels) |
|
|
1817 | 1817 | else: |
|
|
1818 | 1818 | self.nplots = self.data.shape(self.CODE)[0] |
|
|
1819 | 1819 | self.nrows = self.nplots |
|
|
1820 | 1820 | self.channels = list(range(self.nplots)) |
|
|
1821 | 1821 | |
|
|
1822 | 1822 | self.colorbar=True |
|
|
1823 | 1823 | self.width =8 |
|
|
1824 | 1824 | self.height =8 |
|
|
1825 | 1825 | self.ini =0 |
|
|
1826 | 1826 | self.len_azi =0 |
|
|
1827 | 1827 | self.buffer_ini = None |
|
|
1828 | 1828 | self.buffer_ele = None |
|
|
1829 |
self.plots_adjust.update({'wspace': 0.4, 'hspace':0.4, 'left': 0. |
|
|
|
1829 | self.plots_adjust.update({'wspace': 0.4, 'hspace':0.4, 'left': 0.1, 'right': 0.9, 'bottom': 0.08}) | |
|
|
1830 | 1830 | self.flag =0 |
|
|
1831 | 1831 | self.indicador= 0 |
|
|
1832 | 1832 | self.last_data_ele = None |
|
|
1833 | 1833 | self.val_mean = None |
|
|
1834 | 1834 | |
|
|
1835 | 1835 | def update(self, dataOut): |
|
|
1836 | 1836 | |
|
|
1837 | 1837 | data = {} |
|
|
1838 | 1838 | meta = {} |
|
|
1839 | 1839 | if hasattr(dataOut, 'dataPP_POWER'): |
|
|
1840 | 1840 | factor = 1 |
|
|
1841 | 1841 | if hasattr(dataOut, 'nFFTPoints'): |
|
|
1842 | 1842 | factor = dataOut.normFactor |
|
|
1843 | 1843 | |
|
|
1844 | 1844 | if 'pow' in self.attr_data[0].lower(): |
|
|
1845 | 1845 | data['data'] = 10*numpy.log10(getattr(dataOut, self.attr_data[0])/(factor)) |
|
|
1846 | 1846 | else: |
|
|
1847 | 1847 | data['data'] = getattr(dataOut, self.attr_data[0])/(factor) |
|
|
1848 | 1848 | |
|
|
1849 | 1849 | if dataOut.mode_op == 'PPI': |
|
|
1850 | 1850 | self.CODE = 'PPI' |
|
|
1851 | 1851 | self.title = self.CODE |
|
|
1852 | 1852 | elif dataOut.mode_op == 'RHI': |
|
|
1853 | 1853 | self.CODE = 'RHI' |
|
|
1854 | 1854 | self.title = self.CODE |
|
|
1855 | 1855 | |
|
|
1856 | 1856 | data['azi'] = dataOut.data_azi |
|
|
1857 | 1857 | data['ele'] = dataOut.data_ele |
|
|
1858 | 1858 | data['mode_op'] = dataOut.mode_op |
|
|
1859 | 1859 | |
|
|
1860 | 1860 | return data, meta |
|
|
1861 | 1861 | |
|
|
1862 | 1862 | def plot(self): |
|
|
1863 | 1863 | data = self.data[-1] |
|
|
1864 | 1864 | r = self.data.yrange |
|
|
1865 | 1865 | delta_height = r[1]-r[0] |
|
|
1866 | 1866 | r_mask = numpy.where(r>=0)[0] |
|
|
1867 | 1867 | self.r_mask =r_mask |
|
|
1868 | 1868 | r = numpy.arange(len(r_mask))*delta_height |
|
|
1869 | 1869 | self.y = 2*r |
|
|
1870 | 1870 | |
|
|
1871 | 1871 | try: |
|
|
1872 | 1872 | z = data['data'][self.channels[0]][:,r_mask] |
|
|
1873 | 1873 | except: |
|
|
1874 | 1874 | z = data['data'][0][:,r_mask] |
|
|
1875 | 1875 | |
|
|
1876 | 1876 | self.titles = [] |
|
|
1877 | 1877 | |
|
|
1878 | 1878 | self.ymax = self.ymax if self.ymax else numpy.nanmax(r) |
|
|
1879 | 1879 | self.ymin = self.ymin if self.ymin else numpy.nanmin(r) |
|
|
1880 | 1880 | self.zmax = self.zmax if self.zmax else numpy.nanmax(z) |
|
|
1881 | 1881 | self.zmin = self.zmin if self.zmin else numpy.nanmin(z) |
|
|
1882 | 1882 | print("mode inside plot",self.data['mode_op'],data['mode_op']) |
|
|
1883 | 1883 | if data['mode_op'] == 'RHI': |
|
|
1884 | 1884 | try: |
|
|
1885 | 1885 | if self.data['mode_op'][-2] == 'PPI': |
|
|
1886 | 1886 | self.ang_min = None |
|
|
1887 | 1887 | self.ang_max = None |
|
|
1888 | 1888 | except: |
|
|
1889 | 1889 | pass |
|
|
1890 | 1890 | self.ang_min = self.ang_min if self.ang_min else 0 |
|
|
1891 | 1891 | self.ang_max = self.ang_max if self.ang_max else 90 |
|
|
1892 | 1892 | r, theta = numpy.meshgrid(r, numpy.radians(data['ele']) ) |
|
|
1893 | 1893 | elif data['mode_op'] == 'PPI': |
|
|
1894 | 1894 | try: |
|
|
1895 | 1895 | if self.data['mode_op'][-2] == 'RHI': |
|
|
1896 | 1896 | self.ang_min = None |
|
|
1897 | 1897 | self.ang_max = None |
|
|
1898 | 1898 | except: |
|
|
1899 | 1899 | pass |
|
|
1900 | 1900 | self.ang_min = self.ang_min if self.ang_min else 0 |
|
|
1901 | 1901 | self.ang_max = self.ang_max if self.ang_max else 360 |
|
|
1902 | 1902 | r, theta = numpy.meshgrid(r, numpy.radians(data['azi']) ) |
|
|
1903 | 1903 | |
|
|
1904 | 1904 | self.clear_figures() |
|
|
1905 | 1905 | |
|
|
1906 | 1906 | for i,ax in enumerate(self.axes): |
|
|
1907 | 1907 | |
|
|
1908 | 1908 | if ax.firsttime: |
|
|
1909 | 1909 | ax.set_xlim(numpy.radians(self.ang_min),numpy.radians(self.ang_max)) |
|
|
1910 | 1910 | ax.plt = ax.pcolormesh(theta, r, z, cmap=self.colormap, vmin=self.zmin, vmax=self.zmax) |
|
|
1911 | 1911 | if data['mode_op'] == 'PPI': |
|
|
1912 | 1912 | ax.set_theta_direction(-1) |
|
|
1913 | 1913 | ax.set_theta_offset(numpy.pi/2) |
|
|
1914 | 1914 | |
|
|
1915 | 1915 | else: |
|
|
1916 | 1916 | ax.set_xlim(numpy.radians(self.ang_min),numpy.radians(self.ang_max)) |
|
|
1917 | 1917 | ax.plt = ax.pcolormesh(theta, r, z, cmap=self.colormap, vmin=self.zmin, vmax=self.zmax) |
|
|
1918 | 1918 | if data['mode_op'] == 'PPI': |
|
|
1919 | 1919 | ax.set_theta_direction(-1) |
|
|
1920 | 1920 | ax.set_theta_offset(numpy.pi/2) |
|
|
1921 | 1921 | |
|
|
1922 | 1922 | ax.grid(True) |
|
|
1923 | 1923 | if data['mode_op'] == 'RHI': |
|
|
1924 | 1924 | len_aux = int(data['azi'].shape[0]/4) |
|
|
1925 | 1925 | mean = numpy.mean(data['azi'][len_aux:-len_aux]) |
|
|
1926 | 1926 | if len(self.channels) !=1: |
|
|
1927 | 1927 | self.titles = ['RHI {} at AZ: {} Channel {}'.format(self.labels[x], str(round(mean,1)), x) for x in range(self.nrows)] |
|
|
1928 | 1928 | else: |
|
|
1929 | 1929 | self.titles = ['RHI {} at AZ: {} Channel {}'.format(self.labels[0], str(round(mean,1)), self.channels[0])] |
|
|
1930 | 1930 | elif data['mode_op'] == 'PPI': |
|
|
1931 | 1931 | len_aux = int(data['ele'].shape[0]/4) |
|
|
1932 | 1932 | mean = numpy.mean(data['ele'][len_aux:-len_aux]) |
|
|
1933 | 1933 | if len(self.channels) !=1: |
|
|
1934 | 1934 | self.titles = ['PPI {} at EL: {} Channel {}'.format(self.self.labels[x], str(round(mean,1)), x) for x in range(self.nrows)] |
|
|
1935 | 1935 | else: |
|
|
1936 | 1936 | self.titles = ['PPI {} at EL: {} Channel {}'.format(self.labels[0], str(round(mean,1)), self.channels[0])] |
|
|
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