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1 | import numpy | |
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2 | import sys | |
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3 | import zmq | |
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4 | import time | |
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5 | import h5py | |
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6 | import os | |
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7 | ||
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8 | path="/home/alex/Downloads/pedestal" | |
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9 | ext=".hdf5" | |
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10 | ||
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11 | port ="5556" | |
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12 | if len(sys.argv)>1: | |
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13 | port = sys.argv[1] | |
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14 | int(port) | |
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15 | ||
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16 | if len(sys.argv)>2: | |
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17 | port1 = sys.argv[2] | |
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18 | int(port1) | |
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19 | ||
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20 | #Socket to talk to server | |
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21 | context = zmq.Context() | |
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22 | socket = context.socket(zmq.SUB) | |
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23 | ||
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24 | print("Collecting updates from weather server...") | |
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25 | socket.connect("tcp://localhost:%s"%port) | |
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26 | ||
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27 | if len(sys.argv)>2: | |
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28 | socket.connect("tcp://localhost:%s"%port1) | |
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29 | ||
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30 | #Subscribe to zipcode, default is NYC,10001 | |
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31 | topicfilter = "10001" | |
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32 | socket.setsockopt_string(zmq.SUBSCRIBE,topicfilter) | |
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33 | #Process 5 updates | |
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34 | total_value=0 | |
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35 | count= -1 | |
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36 | azi= [] | |
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37 | elev=[] | |
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38 | time0=[] | |
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39 | #for update_nbr in range(250): | |
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40 | while(True): | |
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41 | string= socket.recv() | |
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42 | topic,ang_elev,ang_elev_dec,ang_azi,ang_azi_dec,seconds,seconds_dec= string.split() | |
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43 | ang_azi =float(ang_azi)+1e-3*float(ang_azi_dec) | |
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44 | ang_elev =float(ang_elev)+1e-3*float(ang_elev_dec) | |
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45 | seconds =float(seconds) +1e-6*float(seconds_dec) | |
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46 | azi.append(ang_azi) | |
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47 | elev.append(ang_elev) | |
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48 | time0.append(seconds) | |
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49 | count +=1 | |
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50 | if count == 100: | |
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51 | timetuple=time.localtime() | |
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52 | epoc = time.mktime(timetuple) | |
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53 | #print(epoc) | |
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54 | fullpath = path + ("/" if path[-1]!="/" else "") | |
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55 | ||
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56 | if not os.path.exists(fullpath): | |
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57 | os.mkdir(fullpath) | |
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58 | ||
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59 | azi_array = numpy.array(azi) | |
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60 | elev_array = numpy.array(elev) | |
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61 | time0_array= numpy.array(time0) | |
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62 | pedestal_array=numpy.array([azi,elev,time0]) | |
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63 | count=0 | |
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64 | azi= [] | |
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65 | elev=[] | |
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66 | time0=[] | |
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67 | #print(pedestal_array[0]) | |
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68 | #print(pedestal_array[1]) | |
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69 | ||
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70 | meta='PE' | |
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71 | filex="%s%4.4d%3.3d%10.4d%s"%(meta,timetuple.tm_year,timetuple.tm_yday,epoc,ext) | |
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72 | filename = os.path.join(fullpath,filex) | |
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73 | fp = h5py.File(filename,'w') | |
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74 | #print("Escribiendo HDF5...",epoc) | |
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75 | #Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· DataΒ·....Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· | |
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76 | grp = fp.create_group("Data") | |
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77 | dset = grp.create_dataset("azimuth" , data=pedestal_array[0]) | |
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78 | dset = grp.create_dataset("elevacion", data=pedestal_array[1]) | |
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79 | dset = grp.create_dataset("utc" , data=pedestal_array[2]) | |
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80 | #Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· MetadataΒ·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· | |
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81 | grp = fp.create_group("Metadata") | |
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82 | dset = grp.create_dataset("utctimeInit", data=pedestal_array[2][0]) | |
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83 | timeInterval = pedestal_array[2][1]-pedestal_array[2][0] | |
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84 | dset = grp.create_dataset("timeInterval", data=timeInterval) | |
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85 | fp.close() | |
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86 | ||
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87 | #print ("Average messagedata value for topic '%s' was %dF" % ( topicfilter,total_value / update_nbr)) | |
| @@ -0,0 +1,48 | |||
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1 | ########################################################################### | |
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2 | ############################### SERVIDOR################################### | |
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3 | ######################### SIMULADOR DE PEDESTAL############################ | |
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4 | ########################################################################### | |
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5 | import time | |
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6 | import math | |
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7 | import numpy | |
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8 | import struct | |
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9 | from time import sleep | |
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10 | import zmq | |
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11 | import pickle | |
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12 | port="5556" | |
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13 | context = zmq.Context() | |
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14 | socket = context.socket(zmq.PUB) | |
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15 | socket.bind("tcp://*:%s"%port) | |
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16 | ###### PARAMETROS DE ENTRADA################################ | |
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17 | print("PEDESTAL RESOLUCION 0.01") | |
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18 | print("MAXIMA VELOCIDAD DEL PEDESTAL") | |
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19 | ang_elev = 4.12 | |
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20 | ang_azi = 30 | |
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21 | velocidad= input ("Ingresa velocidad:") | |
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22 | velocidad= float(velocidad) | |
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23 | print (velocidad) | |
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24 | ############################################################ | |
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25 | sleep(3) | |
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26 | print("Start program") | |
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27 | t1 = time.time() | |
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28 | count=0 | |
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29 | while(True): | |
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30 | tmp_vuelta = int(360/velocidad) | |
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31 | t1=t1+tmp_vuelta*count | |
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32 | count= count+1 | |
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33 | muestras_seg = 100 | |
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34 | t2 = time.time() | |
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35 | for i in range(tmp_vuelta): | |
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36 | for j in range(muestras_seg): | |
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37 | tmp_variable = (i+j/100.0) | |
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38 | ang_azi = (tmp_variable)*float(velocidad) | |
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39 | seconds = t1+ tmp_variable | |
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40 | topic=10001 | |
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41 | print ("AzimΒ°: ","%.4f"%ang_azi,"Time:" ,"%.5f"%seconds) | |
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42 | seconds_dec=(seconds-int(seconds))*1e6 | |
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43 | ang_azi_dec= (ang_azi-int(ang_azi))*1e3 | |
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44 | ang_elev_dec=(ang_elev-int(ang_elev))*1e3 | |
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45 | sleep(0.0088) | |
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46 | socket.send_string("%d %d %d %d %d %d %d"%(topic,ang_elev,ang_elev_dec,ang_azi,ang_azi_dec,seconds,seconds_dec)) | |
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47 | t3 = time.time() | |
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48 | print ("Total time for 1 vuelta in Seconds",t3-t2) | |
| @@ -0,0 +1,82 | |||
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1 | import os, sys | |
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2 | import datetime | |
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3 | import time | |
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4 | from schainpy.controller import Project | |
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5 | ||
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6 | desc = "USRP_test" | |
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7 | filename = "USRP_processing.xml" | |
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8 | controllerObj = Project() | |
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9 | controllerObj.setup(id = '191', name='Test_USRP', description=desc) | |
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10 | ||
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11 | ############## USED TO PLOT IQ VOLTAGE, POWER AND SPECTRA ############# | |
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12 | ######PATH DE LECTURA, ESCRITURA, GRAFICOS Y ENVIO WEB################# | |
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13 | path = '/home/alex/Downloads/test_rawdata' | |
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14 | figpath = '/home/alex/Downloads/hdf5_test' | |
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15 | ######################## UNIDAD DE LECTURA############################# | |
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16 | ''' | |
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17 | readUnitConfObj = controllerObj.addReadUnit(datatype='VoltageReader', | |
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18 | path=path, | |
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19 | startDate="2020/01/01", #"2020/01/01",#today, | |
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20 | endDate= "2020/12/01", #"2020/12/30",#today, | |
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21 | startTime='00:00:00', | |
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22 | endTime='23:59:59', | |
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23 | delay=0, | |
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24 | #set=0, | |
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25 | online=0, | |
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26 | walk=1) | |
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27 | ||
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28 | ''' | |
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29 | readUnitConfObj = controllerObj.addReadUnit(datatype='SimulatorReader', | |
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30 | frequency=9.345e9, | |
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31 | FixRCP_IPP= 60, | |
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32 | Tau_0 = 30, | |
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33 | AcqH0_0=0, | |
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34 | samples=330, | |
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35 | AcqDH_0=0.15, | |
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36 | FixRCP_TXA=0.15, | |
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37 | FixRCP_TXB=0.15, | |
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38 | Fdoppler=600.0, | |
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39 | Hdoppler=36, | |
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40 | Adoppler=300,#300 | |
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41 | delay=0, | |
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42 | online=0, | |
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43 | walk=0, | |
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44 | profilesPerBlock=625, | |
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45 | dataBlocksPerFile=100) | |
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46 | #nTotalReadFiles=2) | |
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47 | ||
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48 | ||
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49 | #opObj11 = readUnitConfObj.addOperation(name='printInfo') | |
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50 | ||
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51 | procUnitConfObjA = controllerObj.addProcUnit(datatype='VoltageProc', inputId=readUnitConfObj.getId()) | |
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52 | ||
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53 | procUnitConfObjB = controllerObj.addProcUnit(datatype='SpectraProc', inputId=procUnitConfObjA.getId()) | |
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54 | procUnitConfObjB.addParameter(name='nFFTPoints', value=625, format='int') | |
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55 | procUnitConfObjB.addParameter(name='nProfiles', value=625, format='int') | |
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56 | ||
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57 | opObj11 = procUnitConfObjB.addOperation(name='removeDC') | |
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58 | opObj11.addParameter(name='mode', value=2) | |
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59 | #opObj11 = procUnitConfObjB.addOperation(name='SpectraPlot') | |
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60 | #opObj11 = procUnitConfObjB.addOperation(name='PowerProfilePlot') | |
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61 | ||
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62 | procUnitConfObjC= controllerObj.addProcUnit(datatype='ParametersProc',inputId=procUnitConfObjB.getId()) | |
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63 | procUnitConfObjC.addOperation(name='SpectralMoments') | |
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64 | #opObj11 = procUnitConfObjC.addOperation(name='PowerPlot') | |
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65 | ||
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66 | ''' | |
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67 | opObj11 = procUnitConfObjC.addOperation(name='SpectralMomentsPlot') | |
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68 | #opObj11.addParameter(name='xmin', value=14) | |
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69 | #opObj11.addParameter(name='xmax', value=15) | |
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70 | #opObj11.addParameter(name='save', value=figpath) | |
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71 | opObj11.addParameter(name='showprofile', value=1) | |
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72 | #opObj11.addParameter(name='save_period', value=10) | |
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73 | ''' | |
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74 | ||
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75 | opObj10 = procUnitConfObjC.addOperation(name='ParameterWriter') | |
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76 | opObj10.addParameter(name='path',value=figpath) | |
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77 | #opObj10.addParameter(name='mode',value=0) | |
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78 | opObj10.addParameter(name='blocksPerFile',value='100',format='int') | |
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79 | opObj10.addParameter(name='metadataList',value='utctimeInit,timeInterval',format='list') | |
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80 | opObj10.addParameter(name='dataList',value='data_POW,data_DOP,data_WIDTH,data_SNR')#,format='list' | |
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81 | ||
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82 | controllerObj.start() | |
| @@ -0,0 +1,162 | |||
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1 | import os,numpy,h5py | |
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2 | from shutil import copyfile | |
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3 | ||
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4 | def isNumber(str): | |
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5 | try: | |
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6 | float(str) | |
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7 | return True | |
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8 | except: | |
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9 | return False | |
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10 | ||
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11 | def getfirstFilefromPath(path,meta,ext): | |
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12 | validFilelist = [] | |
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13 | fileList = os.listdir(path) | |
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14 | if len(fileList)<1: | |
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15 | return None | |
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16 | # meta 1234 567 8-18 BCDE | |
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17 | # H,D,PE YYYY DDD EPOC .ext | |
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18 | ||
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19 | for thisFile in fileList: | |
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20 | if meta =="PE": | |
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21 | try: | |
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22 | number= int(thisFile[len(meta)+7:len(meta)+17]) | |
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23 | except: | |
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24 | print("There is a file or folder with different format") | |
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25 | if meta == "D": | |
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26 | try: | |
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27 | number= int(thisFile[8:11]) | |
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28 | except: | |
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29 | print("There is a file or folder with different format") | |
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30 | ||
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31 | if not isNumber(str=number): | |
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32 | continue | |
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33 | if (os.path.splitext(thisFile)[-1].lower() != ext.lower()): | |
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34 | continue | |
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35 | validFilelist.sort() | |
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36 | validFilelist.append(thisFile) | |
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37 | if len(validFilelist)>0: | |
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38 | validFilelist = sorted(validFilelist,key=str.lower) | |
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39 | return validFilelist | |
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40 | return None | |
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41 | ||
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42 | def gettimeutcfromDirFilename(path,file): | |
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43 | dir_file= path+"/"+file | |
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44 | fp = h5py.File(dir_file,'r') | |
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45 | epoc = fp['Metadata'].get('utctimeInit')[()] | |
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46 | fp.close() | |
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47 | return epoc | |
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48 | ||
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49 | def getDatavaluefromDirFilename(path,file,value): | |
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50 | dir_file= path+"/"+file | |
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51 | fp = h5py.File(dir_file,'r') | |
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52 | array = fp['Data'].get(value)[()] | |
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53 | fp.close() | |
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54 | return array | |
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55 | ||
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56 | ||
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57 | #Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· Velocidad de PedestalΒ·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· | |
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58 | w = input ("Ingresa velocidad de Pedestal: ") | |
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59 | w = 4 | |
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60 | w = float(w) | |
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61 | #Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· Resolucion minimo en gradosΒ·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· | |
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62 | alfa = input ("Ingresa resolucion minima en grados: ") | |
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63 | alfa = 1 | |
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64 | alfa = float(alfa) | |
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65 | #Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· IPP del Experimento Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· | |
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66 | IPP = input ("Ingresa el IPP del experimento: ") | |
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67 | IPP = 0.0004 | |
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68 | IPP = float(IPP) | |
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69 | #Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· MODE Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· | |
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70 | mode = input ("Ingresa el MODO del experimento T or F: ") | |
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71 | mode = "T" | |
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72 | mode = str(mode) | |
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73 | ||
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74 | #Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· Tiempo en generar la resolucion minΒ·Β·Β· | |
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75 | #Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· MCU Β·Β· var_ang = w * (var_tiempo)Β·Β·Β· | |
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76 | var_tiempo = alfa/w | |
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77 | #Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· Tiempo Equivalente en perfilesΒ·Β·Β·Β·Β·Β·Β·Β· | |
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78 | #Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· var_tiempo = IPP * ( num_perfiles )Β· | |
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79 | num_perfiles = int(var_tiempo/IPP) | |
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80 | ||
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81 | #Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·DATA PEDESTALΒ·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· | |
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82 | dir_pedestal = "/home/alex/Downloads/pedestal" | |
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83 | #Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· DATA ADQΒ·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· | |
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84 | if mode=="T": | |
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85 | dir_adq = "/home/alex/Downloads/hdf5_testPP/d2020194" # Time domain | |
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86 | else: | |
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87 | dir_adq = "/home/alex/Downloads/hdf5_test/d2020194" # Frequency domain | |
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88 | ||
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89 | print( "Velocidad angular :", w) | |
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90 | print( "Resolucion minima en grados :", alfa) | |
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91 | print( "Numero de perfiles equivalente:", num_perfiles) | |
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92 | print( "Mode :", mode) | |
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93 | ||
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94 | #Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· First FileΒ·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· | |
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95 | list_pedestal = getfirstFilefromPath(path=dir_pedestal,meta="PE",ext=".hdf5") | |
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96 | list_adq = getfirstFilefromPath(path=dir_adq ,meta="D",ext=".hdf5") | |
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97 | ||
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98 | #Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· utc time Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· | |
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99 | utc_pedestal= gettimeutcfromDirFilename(path=dir_pedestal,file=list_pedestal[0]) | |
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100 | utc_adq = gettimeutcfromDirFilename(path=dir_adq ,file=list_adq[0]) | |
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101 | ||
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102 | print("utc_pedestal :",utc_pedestal) | |
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103 | print("utc_adq :",utc_adq) | |
|
|
104 | #Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Relacion: utc_adq (+/-) var_tiempo*nro_file= utc_pedestal | |
|
|
105 | time_Interval_p = 0.01 | |
|
|
106 | n_perfiles_p = 100 | |
|
|
107 | if utc_adq>utc_pedestal: | |
|
|
108 | nro_file = int((int(utc_adq) - int(utc_pedestal))/(time_Interval_p*n_perfiles_p)) | |
|
|
109 | ff_pedestal = list_pedestal[nro_file] | |
|
|
110 | utc_pedestal = gettimeutcfromDirFilename(path=dir_pedestal,file=ff_pedestal) | |
|
|
111 | nro_key_p = int((utc_adq-utc_pedestal)/time_Interval_p) | |
|
|
112 | if utc_adq >utc_pedestal: | |
|
|
113 | ff_pedestal = ff_pedestal | |
|
|
114 | else: | |
|
|
115 | nro_file = nro_file-1 | |
|
|
116 | ff_pedestal = list_pedestal[nro_file] | |
|
|
117 | angulo = getDatavaluefromDirFilename(path=dir_pedestal,file=ff_pedestal,value="azimuth") | |
|
|
118 | nro_key_p = int((utc_adq-utc_pedestal)/time_Interval_p) | |
|
|
119 | print("nro_file :",nro_file) | |
|
|
120 | print("name_file :",ff_pedestal) | |
|
|
121 | print("utc_pedestal_file :",utc_pedestal) | |
|
|
122 | print("nro_key_p :",nro_key_p) | |
|
|
123 | print("utc_pedestal_init :",utc_pedestal+nro_key_p*time_Interval_p) | |
|
|
124 | print("angulo_array :",angulo[nro_key_p]) | |
|
|
125 | #4+25+25+25+21 | |
|
|
126 | #while True: | |
|
|
127 | list_pedestal = getfirstFilefromPath(path=dir_pedestal,meta="PE",ext=".hdf5") | |
|
|
128 | list_adq = getfirstFilefromPath(path=dir_adq ,meta="D",ext=".hdf5") | |
|
|
129 | ||
|
|
130 | nro_file = nro_file #10 | |
|
|
131 | nro_key_perfil = nro_key_p | |
|
|
132 | blocksPerFile = 100 | |
|
|
133 | wr_path = "/home/alex/Downloads/hdf5_wr/" | |
|
|
134 | # Lectura de archivos de adquisicion para adicion de azimuth | |
|
|
135 | for thisFile in range(len(list_adq)): | |
|
|
136 | print("thisFileAdq",thisFile) | |
|
|
137 | angulo_adq = numpy.zeros(blocksPerFile) | |
|
|
138 | tmp = 0 | |
|
|
139 | for j in range(blocksPerFile): | |
|
|
140 | iterador = nro_key_perfil + 25*(j-tmp) | |
|
|
141 | if iterador < n_perfiles_p: | |
|
|
142 | nro_file = nro_file | |
|
|
143 | else: | |
|
|
144 | nro_file = nro_file+1 | |
|
|
145 | tmp = j | |
|
|
146 | iterador = nro_key_perfil | |
|
|
147 | ff_pedestal = list_pedestal[nro_file] | |
|
|
148 | angulo = getDatavaluefromDirFilename(path=dir_pedestal,file=ff_pedestal,value="azimuth") | |
|
|
149 | angulo_adq[j]= angulo[iterador] | |
|
|
150 | copyfile(dir_adq+"/"+list_adq[thisFile],wr_path+list_adq[thisFile]) | |
|
|
151 | fp = h5py.File(wr_path+list_adq[thisFile],'a') | |
|
|
152 | grp = fp.create_group("Pedestal") | |
|
|
153 | dset = grp.create_dataset("azimuth" , data=angulo_adq) | |
|
|
154 | fp.close() | |
|
|
155 | print("Angulo",angulo_adq) | |
|
|
156 | print("Angulo",len(angulo_adq)) | |
|
|
157 | nro_key_perfil=iterador + 25 | |
|
|
158 | if nro_key_perfil< n_perfiles_p: | |
|
|
159 | nro_file = nro_file | |
|
|
160 | else: | |
|
|
161 | nro_file = nro_file+1 | |
|
|
162 | nro_key_perfil= nro_key_p | |
| @@ -1,1397 +1,1403 | |||
|
|
1 | 1 | ''' |
|
|
2 | 2 | |
|
|
3 | 3 | $Author: murco $ |
|
|
4 | 4 | $Id: JROData.py 173 2012-11-20 15:06:21Z murco $ |
|
|
5 | 5 | ''' |
|
|
6 | 6 | |
|
|
7 | 7 | import copy |
|
|
8 | 8 | import numpy |
|
|
9 | 9 | import datetime |
|
|
10 | 10 | import json |
|
|
11 | 11 | |
|
|
12 | 12 | import schainpy.admin |
|
|
13 | 13 | from schainpy.utils import log |
|
|
14 | 14 | from .jroheaderIO import SystemHeader, RadarControllerHeader |
|
|
15 | 15 | from schainpy.model.data import _noise |
|
|
16 | 16 | |
|
|
17 | 17 | |
|
|
18 | 18 | def getNumpyDtype(dataTypeCode): |
|
|
19 | 19 | |
|
|
20 | 20 | if dataTypeCode == 0: |
|
|
21 | 21 | numpyDtype = numpy.dtype([('real', '<i1'), ('imag', '<i1')]) |
|
|
22 | 22 | elif dataTypeCode == 1: |
|
|
23 | 23 | numpyDtype = numpy.dtype([('real', '<i2'), ('imag', '<i2')]) |
|
|
24 | 24 | elif dataTypeCode == 2: |
|
|
25 | 25 | numpyDtype = numpy.dtype([('real', '<i4'), ('imag', '<i4')]) |
|
|
26 | 26 | elif dataTypeCode == 3: |
|
|
27 | 27 | numpyDtype = numpy.dtype([('real', '<i8'), ('imag', '<i8')]) |
|
|
28 | 28 | elif dataTypeCode == 4: |
|
|
29 | 29 | numpyDtype = numpy.dtype([('real', '<f4'), ('imag', '<f4')]) |
|
|
30 | 30 | elif dataTypeCode == 5: |
|
|
31 | 31 | numpyDtype = numpy.dtype([('real', '<f8'), ('imag', '<f8')]) |
|
|
32 | 32 | else: |
|
|
33 | 33 | raise ValueError('dataTypeCode was not defined') |
|
|
34 | 34 | |
|
|
35 | 35 | return numpyDtype |
|
|
36 | 36 | |
|
|
37 | 37 | |
|
|
38 | 38 | def getDataTypeCode(numpyDtype): |
|
|
39 | 39 | |
|
|
40 | 40 | if numpyDtype == numpy.dtype([('real', '<i1'), ('imag', '<i1')]): |
|
|
41 | 41 | datatype = 0 |
|
|
42 | 42 | elif numpyDtype == numpy.dtype([('real', '<i2'), ('imag', '<i2')]): |
|
|
43 | 43 | datatype = 1 |
|
|
44 | 44 | elif numpyDtype == numpy.dtype([('real', '<i4'), ('imag', '<i4')]): |
|
|
45 | 45 | datatype = 2 |
|
|
46 | 46 | elif numpyDtype == numpy.dtype([('real', '<i8'), ('imag', '<i8')]): |
|
|
47 | 47 | datatype = 3 |
|
|
48 | 48 | elif numpyDtype == numpy.dtype([('real', '<f4'), ('imag', '<f4')]): |
|
|
49 | 49 | datatype = 4 |
|
|
50 | 50 | elif numpyDtype == numpy.dtype([('real', '<f8'), ('imag', '<f8')]): |
|
|
51 | 51 | datatype = 5 |
|
|
52 | 52 | else: |
|
|
53 | 53 | datatype = None |
|
|
54 | 54 | |
|
|
55 | 55 | return datatype |
|
|
56 | 56 | |
|
|
57 | 57 | |
|
|
58 | 58 | def hildebrand_sekhon(data, navg): |
|
|
59 | 59 | """ |
|
|
60 | 60 | This method is for the objective determination of the noise level in Doppler spectra. This |
|
|
61 | 61 | implementation technique is based on the fact that the standard deviation of the spectral |
|
|
62 | 62 | densities is equal to the mean spectral density for white Gaussian noise |
|
|
63 | 63 | |
|
|
64 | 64 | Inputs: |
|
|
65 | 65 | Data : heights |
|
|
66 | 66 | navg : numbers of averages |
|
|
67 | 67 | |
|
|
68 | 68 | Return: |
|
|
69 | 69 | mean : noise's level |
|
|
70 | 70 | """ |
|
|
71 | 71 | |
|
|
72 | 72 | sortdata = numpy.sort(data, axis=None) |
|
|
73 | 73 | ''' |
|
|
74 | 74 | lenOfData = len(sortdata) |
|
|
75 | 75 | nums_min = lenOfData*0.2 |
|
|
76 | 76 | |
|
|
77 | 77 | if nums_min <= 5: |
|
|
78 | 78 | |
|
|
79 | 79 | nums_min = 5 |
|
|
80 | 80 | |
|
|
81 | 81 | sump = 0. |
|
|
82 | 82 | sumq = 0. |
|
|
83 | 83 | |
|
|
84 | 84 | j = 0 |
|
|
85 | 85 | cont = 1 |
|
|
86 | 86 | |
|
|
87 | 87 | while((cont == 1)and(j < lenOfData)): |
|
|
88 | 88 | |
|
|
89 | 89 | sump += sortdata[j] |
|
|
90 | 90 | sumq += sortdata[j]**2 |
|
|
91 | 91 | |
|
|
92 | 92 | if j > nums_min: |
|
|
93 | 93 | rtest = float(j)/(j-1) + 1.0/navg |
|
|
94 | 94 | if ((sumq*j) > (rtest*sump**2)): |
|
|
95 | 95 | j = j - 1 |
|
|
96 | 96 | sump = sump - sortdata[j] |
|
|
97 | 97 | sumq = sumq - sortdata[j]**2 |
|
|
98 | 98 | cont = 0 |
|
|
99 | 99 | |
|
|
100 | 100 | j += 1 |
|
|
101 | 101 | |
|
|
102 | 102 | lnoise = sump / j |
|
|
103 | 103 | ''' |
|
|
104 | 104 | return _noise.hildebrand_sekhon(sortdata, navg) |
|
|
105 | 105 | |
|
|
106 | 106 | |
|
|
107 | 107 | class Beam: |
|
|
108 | 108 | |
|
|
109 | 109 | def __init__(self): |
|
|
110 | 110 | self.codeList = [] |
|
|
111 | 111 | self.azimuthList = [] |
|
|
112 | 112 | self.zenithList = [] |
|
|
113 | 113 | |
|
|
114 | 114 | |
|
|
115 | 115 | class GenericData(object): |
|
|
116 | 116 | |
|
|
117 | 117 | flagNoData = True |
|
|
118 | 118 | |
|
|
119 | 119 | def copy(self, inputObj=None): |
|
|
120 | 120 | |
|
|
121 | 121 | if inputObj == None: |
|
|
122 | 122 | return copy.deepcopy(self) |
|
|
123 | 123 | |
|
|
124 | 124 | for key in list(inputObj.__dict__.keys()): |
|
|
125 | 125 | |
|
|
126 | 126 | attribute = inputObj.__dict__[key] |
|
|
127 | 127 | |
|
|
128 | 128 | # If this attribute is a tuple or list |
|
|
129 | 129 | if type(inputObj.__dict__[key]) in (tuple, list): |
|
|
130 | 130 | self.__dict__[key] = attribute[:] |
|
|
131 | 131 | continue |
|
|
132 | 132 | |
|
|
133 | 133 | # If this attribute is another object or instance |
|
|
134 | 134 | if hasattr(attribute, '__dict__'): |
|
|
135 | 135 | self.__dict__[key] = attribute.copy() |
|
|
136 | 136 | continue |
|
|
137 | 137 | |
|
|
138 | 138 | self.__dict__[key] = inputObj.__dict__[key] |
|
|
139 | 139 | |
|
|
140 | 140 | def deepcopy(self): |
|
|
141 | 141 | |
|
|
142 | 142 | return copy.deepcopy(self) |
|
|
143 | 143 | |
|
|
144 | 144 | def isEmpty(self): |
|
|
145 | 145 | |
|
|
146 | 146 | return self.flagNoData |
|
|
147 | 147 | |
|
|
148 | 148 | def isReady(self): |
|
|
149 | 149 | |
|
|
150 | 150 | return not self.flagNoData |
|
|
151 | 151 | |
|
|
152 | 152 | |
|
|
153 | 153 | class JROData(GenericData): |
|
|
154 | 154 | |
|
|
155 | 155 | # m_BasicHeader = BasicHeader() |
|
|
156 | 156 | # m_ProcessingHeader = ProcessingHeader() |
|
|
157 | 157 | |
|
|
158 | 158 | systemHeaderObj = SystemHeader() |
|
|
159 | 159 | radarControllerHeaderObj = RadarControllerHeader() |
|
|
160 | 160 | # data = None |
|
|
161 | 161 | type = None |
|
|
162 | 162 | datatype = None # dtype but in string |
|
|
163 | 163 | # dtype = None |
|
|
164 | 164 | # nChannels = None |
|
|
165 | 165 | # nHeights = None |
|
|
166 | 166 | nProfiles = None |
|
|
167 | 167 | heightList = None |
|
|
168 | 168 | channelList = None |
|
|
169 | 169 | flagDiscontinuousBlock = False |
|
|
170 | 170 | useLocalTime = False |
|
|
171 | 171 | utctime = None |
|
|
172 | 172 | timeZone = None |
|
|
173 | 173 | dstFlag = None |
|
|
174 | 174 | errorCount = None |
|
|
175 | 175 | blocksize = None |
|
|
176 | 176 | # nCode = None |
|
|
177 | 177 | # nBaud = None |
|
|
178 | 178 | # code = None |
|
|
179 | 179 | flagDecodeData = False # asumo q la data no esta decodificada |
|
|
180 | 180 | flagDeflipData = False # asumo q la data no esta sin flip |
|
|
181 | 181 | flagShiftFFT = False |
|
|
182 | 182 | # ippSeconds = None |
|
|
183 | 183 | # timeInterval = None |
|
|
184 | 184 | nCohInt = None |
|
|
185 | 185 | # noise = None |
|
|
186 | 186 | windowOfFilter = 1 |
|
|
187 | 187 | # Speed of ligth |
|
|
188 | 188 | C = 3e8 |
|
|
189 | 189 | frequency = 49.92e6 |
|
|
190 | 190 | realtime = False |
|
|
191 | 191 | beacon_heiIndexList = None |
|
|
192 | 192 | last_block = None |
|
|
193 | 193 | blocknow = None |
|
|
194 | 194 | azimuth = None |
|
|
195 | 195 | zenith = None |
|
|
196 | 196 | beam = Beam() |
|
|
197 | 197 | profileIndex = None |
|
|
198 | 198 | error = None |
|
|
199 | 199 | data = None |
|
|
200 | 200 | nmodes = None |
|
|
201 | 201 | |
|
|
202 | 202 | def __str__(self): |
|
|
203 | 203 | |
|
|
204 | 204 | return '{} - {}'.format(self.type, self.getDatatime()) |
|
|
205 | 205 | |
|
|
206 | 206 | def getNoise(self): |
|
|
207 | 207 | |
|
|
208 | 208 | raise NotImplementedError |
|
|
209 | 209 | |
|
|
210 | 210 | def getNChannels(self): |
|
|
211 | 211 | |
|
|
212 | 212 | return len(self.channelList) |
|
|
213 | 213 | |
|
|
214 | 214 | def getChannelIndexList(self): |
|
|
215 | 215 | |
|
|
216 | 216 | return list(range(self.nChannels)) |
|
|
217 | 217 | |
|
|
218 | 218 | def getNHeights(self): |
|
|
219 | 219 | |
|
|
220 | 220 | return len(self.heightList) |
|
|
221 | 221 | |
|
|
222 | 222 | def getHeiRange(self, extrapoints=0): |
|
|
223 | 223 | |
|
|
224 | 224 | heis = self.heightList |
|
|
225 | 225 | # deltah = self.heightList[1] - self.heightList[0] |
|
|
226 | 226 | # |
|
|
227 | 227 | # heis.append(self.heightList[-1]) |
|
|
228 | 228 | |
|
|
229 | 229 | return heis |
|
|
230 | 230 | |
|
|
231 | 231 | def getDeltaH(self): |
|
|
232 | 232 | |
|
|
233 | 233 | delta = self.heightList[1] - self.heightList[0] |
|
|
234 | 234 | |
|
|
235 | 235 | return delta |
|
|
236 | 236 | |
|
|
237 | 237 | def getltctime(self): |
|
|
238 | 238 | |
|
|
239 | 239 | if self.useLocalTime: |
|
|
240 | 240 | return self.utctime - self.timeZone * 60 |
|
|
241 | 241 | |
|
|
242 | 242 | return self.utctime |
|
|
243 | 243 | |
|
|
244 | 244 | def getDatatime(self): |
|
|
245 | 245 | |
|
|
246 | 246 | datatimeValue = datetime.datetime.utcfromtimestamp(self.ltctime) |
|
|
247 | 247 | return datatimeValue |
|
|
248 | 248 | |
|
|
249 | 249 | def getTimeRange(self): |
|
|
250 | 250 | |
|
|
251 | 251 | datatime = [] |
|
|
252 | 252 | |
|
|
253 | 253 | datatime.append(self.ltctime) |
|
|
254 | 254 | datatime.append(self.ltctime + self.timeInterval + 1) |
|
|
255 | 255 | |
|
|
256 | 256 | datatime = numpy.array(datatime) |
|
|
257 | 257 | |
|
|
258 | 258 | return datatime |
|
|
259 | 259 | |
|
|
260 | 260 | def getFmaxTimeResponse(self): |
|
|
261 | 261 | |
|
|
262 | 262 | period = (10**-6) * self.getDeltaH() / (0.15) |
|
|
263 | 263 | |
|
|
264 | 264 | PRF = 1. / (period * self.nCohInt) |
|
|
265 | 265 | |
|
|
266 | 266 | fmax = PRF |
|
|
267 | 267 | |
|
|
268 | 268 | return fmax |
|
|
269 | 269 | |
|
|
270 | 270 | def getFmax(self): |
|
|
271 | 271 | PRF = 1. / (self.ippSeconds * self.nCohInt) |
|
|
272 | 272 | |
|
|
273 | 273 | fmax = PRF |
|
|
274 | 274 | return fmax |
|
|
275 | 275 | |
|
|
276 | 276 | def getVmax(self): |
|
|
277 | 277 | |
|
|
278 | 278 | _lambda = self.C / self.frequency |
|
|
279 | 279 | |
|
|
280 | 280 | vmax = self.getFmax() * _lambda / 2 |
|
|
281 | 281 | |
|
|
282 | 282 | return vmax |
|
|
283 | 283 | |
|
|
284 | 284 | def get_ippSeconds(self): |
|
|
285 | 285 | ''' |
|
|
286 | 286 | ''' |
|
|
287 | 287 | return self.radarControllerHeaderObj.ippSeconds |
|
|
288 | 288 | |
|
|
289 | 289 | def set_ippSeconds(self, ippSeconds): |
|
|
290 | 290 | ''' |
|
|
291 | 291 | ''' |
|
|
292 | 292 | |
|
|
293 | 293 | self.radarControllerHeaderObj.ippSeconds = ippSeconds |
|
|
294 | 294 | |
|
|
295 | 295 | return |
|
|
296 | 296 | |
|
|
297 | 297 | def get_dtype(self): |
|
|
298 | 298 | ''' |
|
|
299 | 299 | ''' |
|
|
300 | 300 | return getNumpyDtype(self.datatype) |
|
|
301 | 301 | |
|
|
302 | 302 | def set_dtype(self, numpyDtype): |
|
|
303 | 303 | ''' |
|
|
304 | 304 | ''' |
|
|
305 | 305 | |
|
|
306 | 306 | self.datatype = getDataTypeCode(numpyDtype) |
|
|
307 | 307 | |
|
|
308 | 308 | def get_code(self): |
|
|
309 | 309 | ''' |
|
|
310 | 310 | ''' |
|
|
311 | 311 | return self.radarControllerHeaderObj.code |
|
|
312 | 312 | |
|
|
313 | 313 | def set_code(self, code): |
|
|
314 | 314 | ''' |
|
|
315 | 315 | ''' |
|
|
316 | 316 | self.radarControllerHeaderObj.code = code |
|
|
317 | 317 | |
|
|
318 | 318 | return |
|
|
319 | 319 | |
|
|
320 | 320 | def get_ncode(self): |
|
|
321 | 321 | ''' |
|
|
322 | 322 | ''' |
|
|
323 | 323 | return self.radarControllerHeaderObj.nCode |
|
|
324 | 324 | |
|
|
325 | 325 | def set_ncode(self, nCode): |
|
|
326 | 326 | ''' |
|
|
327 | 327 | ''' |
|
|
328 | 328 | self.radarControllerHeaderObj.nCode = nCode |
|
|
329 | 329 | |
|
|
330 | 330 | return |
|
|
331 | 331 | |
|
|
332 | 332 | def get_nbaud(self): |
|
|
333 | 333 | ''' |
|
|
334 | 334 | ''' |
|
|
335 | 335 | return self.radarControllerHeaderObj.nBaud |
|
|
336 | 336 | |
|
|
337 | 337 | def set_nbaud(self, nBaud): |
|
|
338 | 338 | ''' |
|
|
339 | 339 | ''' |
|
|
340 | 340 | self.radarControllerHeaderObj.nBaud = nBaud |
|
|
341 | 341 | |
|
|
342 | 342 | return |
|
|
343 | 343 | |
|
|
344 | 344 | nChannels = property(getNChannels, "I'm the 'nChannel' property.") |
|
|
345 | 345 | channelIndexList = property( |
|
|
346 | 346 | getChannelIndexList, "I'm the 'channelIndexList' property.") |
|
|
347 | 347 | nHeights = property(getNHeights, "I'm the 'nHeights' property.") |
|
|
348 | 348 | #noise = property(getNoise, "I'm the 'nHeights' property.") |
|
|
349 | 349 | datatime = property(getDatatime, "I'm the 'datatime' property") |
|
|
350 | 350 | ltctime = property(getltctime, "I'm the 'ltctime' property") |
|
|
351 | 351 | ippSeconds = property(get_ippSeconds, set_ippSeconds) |
|
|
352 | 352 | dtype = property(get_dtype, set_dtype) |
|
|
353 | 353 | # timeInterval = property(getTimeInterval, "I'm the 'timeInterval' property") |
|
|
354 | 354 | code = property(get_code, set_code) |
|
|
355 | 355 | nCode = property(get_ncode, set_ncode) |
|
|
356 | 356 | nBaud = property(get_nbaud, set_nbaud) |
|
|
357 | 357 | |
|
|
358 | 358 | |
|
|
359 | 359 | class Voltage(JROData): |
|
|
360 | 360 | |
|
|
361 | 361 | # data es un numpy array de 2 dmensiones (canales, alturas) |
|
|
362 | 362 | data = None |
|
|
363 |
data |
|
|
|
364 |
data |
|
|
|
365 |
data |
|
|
|
363 | dataPP_POW = None | |
|
|
364 | dataPP_DOP = None | |
|
|
365 | dataPP_WIDTH = None | |
|
|
366 | dataPP_SNR = None | |
|
|
367 | ||
|
|
366 | 368 | def __init__(self): |
|
|
367 | 369 | ''' |
|
|
368 | 370 | Constructor |
|
|
369 | 371 | ''' |
|
|
370 | 372 | |
|
|
371 | 373 | self.useLocalTime = True |
|
|
372 | 374 | self.radarControllerHeaderObj = RadarControllerHeader() |
|
|
373 | 375 | self.systemHeaderObj = SystemHeader() |
|
|
374 | 376 | self.type = "Voltage" |
|
|
375 | 377 | self.data = None |
|
|
376 | 378 | # self.dtype = None |
|
|
377 | 379 | # self.nChannels = 0 |
|
|
378 | 380 | # self.nHeights = 0 |
|
|
379 | 381 | self.nProfiles = None |
|
|
380 | 382 | self.heightList = None |
|
|
381 | 383 | self.channelList = None |
|
|
382 | 384 | # self.channelIndexList = None |
|
|
383 | 385 | self.flagNoData = True |
|
|
384 | 386 | self.flagDiscontinuousBlock = False |
|
|
385 | 387 | self.utctime = None |
|
|
386 | 388 | self.timeZone = None |
|
|
387 | 389 | self.dstFlag = None |
|
|
388 | 390 | self.errorCount = None |
|
|
389 | 391 | self.nCohInt = None |
|
|
390 | 392 | self.blocksize = None |
|
|
391 | 393 | self.flagCohInt = False |
|
|
392 | 394 | self.flagDecodeData = False # asumo q la data no esta decodificada |
|
|
393 | 395 | self.flagDeflipData = False # asumo q la data no esta sin flip |
|
|
394 | 396 | self.flagShiftFFT = False |
|
|
395 | 397 | self.flagDataAsBlock = False # Asumo que la data es leida perfil a perfil |
|
|
396 | 398 | self.profileIndex = 0 |
|
|
397 | 399 | |
|
|
398 | 400 | def getNoisebyHildebrand(self, channel=None): |
|
|
399 | 401 | """ |
|
|
400 | 402 | Determino el nivel de ruido usando el metodo Hildebrand-Sekhon |
|
|
401 | 403 | |
|
|
402 | 404 | Return: |
|
|
403 | 405 | noiselevel |
|
|
404 | 406 | """ |
|
|
405 | 407 | |
|
|
406 | 408 | if channel != None: |
|
|
407 | 409 | data = self.data[channel] |
|
|
408 | 410 | nChannels = 1 |
|
|
409 | 411 | else: |
|
|
410 | 412 | data = self.data |
|
|
411 | 413 | nChannels = self.nChannels |
|
|
412 | 414 | |
|
|
413 | 415 | noise = numpy.zeros(nChannels) |
|
|
414 | 416 | power = data * numpy.conjugate(data) |
|
|
415 | 417 | |
|
|
416 | 418 | for thisChannel in range(nChannels): |
|
|
417 | 419 | if nChannels == 1: |
|
|
418 | 420 | daux = power[:].real |
|
|
419 | 421 | else: |
|
|
420 | 422 | daux = power[thisChannel, :].real |
|
|
421 | 423 | noise[thisChannel] = hildebrand_sekhon(daux, self.nCohInt) |
|
|
422 | 424 | |
|
|
423 | 425 | return noise |
|
|
424 | 426 | |
|
|
425 | 427 | def getNoise(self, type=1, channel=None): |
|
|
426 | 428 | |
|
|
427 | 429 | if type == 1: |
|
|
428 | 430 | noise = self.getNoisebyHildebrand(channel) |
|
|
429 | 431 | |
|
|
430 | 432 | return noise |
|
|
431 | 433 | |
|
|
432 | 434 | def getPower(self, channel=None): |
|
|
433 | 435 | |
|
|
434 | 436 | if channel != None: |
|
|
435 | 437 | data = self.data[channel] |
|
|
436 | 438 | else: |
|
|
437 | 439 | data = self.data |
|
|
438 | 440 | |
|
|
439 | 441 | power = data * numpy.conjugate(data) |
|
|
440 | 442 | powerdB = 10 * numpy.log10(power.real) |
|
|
441 | 443 | powerdB = numpy.squeeze(powerdB) |
|
|
442 | 444 | |
|
|
443 | 445 | return powerdB |
|
|
444 | 446 | |
|
|
445 | 447 | def getTimeInterval(self): |
|
|
446 | 448 | |
|
|
447 | 449 | timeInterval = self.ippSeconds * self.nCohInt |
|
|
448 | 450 | |
|
|
449 | 451 | return timeInterval |
|
|
450 | 452 | |
|
|
451 | 453 | noise = property(getNoise, "I'm the 'nHeights' property.") |
|
|
452 | 454 | timeInterval = property(getTimeInterval, "I'm the 'timeInterval' property") |
|
|
453 | 455 | |
|
|
454 | 456 | |
|
|
455 | 457 | class Spectra(JROData): |
|
|
456 | 458 | |
|
|
457 | 459 | # data spc es un numpy array de 2 dmensiones (canales, perfiles, alturas) |
|
|
458 | 460 | data_spc = None |
|
|
459 | 461 | # data cspc es un numpy array de 2 dmensiones (canales, pares, alturas) |
|
|
460 | 462 | data_cspc = None |
|
|
461 | 463 | # data dc es un numpy array de 2 dmensiones (canales, alturas) |
|
|
462 | 464 | data_dc = None |
|
|
463 | 465 | # data power |
|
|
464 | 466 | data_pwr = None |
|
|
465 | 467 | nFFTPoints = None |
|
|
466 | 468 | # nPairs = None |
|
|
467 | 469 | pairsList = None |
|
|
468 | 470 | nIncohInt = None |
|
|
469 | 471 | wavelength = None # Necesario para cacular el rango de velocidad desde la frecuencia |
|
|
470 | 472 | nCohInt = None # se requiere para determinar el valor de timeInterval |
|
|
471 | 473 | ippFactor = None |
|
|
472 | 474 | profileIndex = 0 |
|
|
473 | 475 | plotting = "spectra" |
|
|
474 | 476 | |
|
|
475 | 477 | def __init__(self): |
|
|
476 | 478 | ''' |
|
|
477 | 479 | Constructor |
|
|
478 | 480 | ''' |
|
|
479 | 481 | |
|
|
480 | 482 | self.useLocalTime = True |
|
|
481 | 483 | self.radarControllerHeaderObj = RadarControllerHeader() |
|
|
482 | 484 | self.systemHeaderObj = SystemHeader() |
|
|
483 | 485 | self.type = "Spectra" |
|
|
484 | 486 | # self.data = None |
|
|
485 | 487 | # self.dtype = None |
|
|
486 | 488 | # self.nChannels = 0 |
|
|
487 | 489 | # self.nHeights = 0 |
|
|
488 | 490 | self.nProfiles = None |
|
|
489 | 491 | self.heightList = None |
|
|
490 | 492 | self.channelList = None |
|
|
491 | 493 | # self.channelIndexList = None |
|
|
492 | 494 | self.pairsList = None |
|
|
493 | 495 | self.flagNoData = True |
|
|
494 | 496 | self.flagDiscontinuousBlock = False |
|
|
495 | 497 | self.utctime = None |
|
|
496 | 498 | self.nCohInt = None |
|
|
497 | 499 | self.nIncohInt = None |
|
|
498 | 500 | self.blocksize = None |
|
|
499 | 501 | self.nFFTPoints = None |
|
|
500 | 502 | self.wavelength = None |
|
|
501 | 503 | self.flagDecodeData = False # asumo q la data no esta decodificada |
|
|
502 | 504 | self.flagDeflipData = False # asumo q la data no esta sin flip |
|
|
503 | 505 | self.flagShiftFFT = False |
|
|
504 | 506 | self.ippFactor = 1 |
|
|
505 | 507 | #self.noise = None |
|
|
506 | 508 | self.beacon_heiIndexList = [] |
|
|
507 | 509 | self.noise_estimation = None |
|
|
508 | 510 | |
|
|
509 | 511 | def getNoisebyHildebrand(self, xmin_index=None, xmax_index=None, ymin_index=None, ymax_index=None): |
|
|
510 | 512 | """ |
|
|
511 | 513 | Determino el nivel de ruido usando el metodo Hildebrand-Sekhon |
|
|
512 | 514 | |
|
|
513 | 515 | Return: |
|
|
514 | 516 | noiselevel |
|
|
515 | 517 | """ |
|
|
516 | 518 | |
|
|
517 | 519 | noise = numpy.zeros(self.nChannels) |
|
|
518 | 520 | |
|
|
519 | 521 | for channel in range(self.nChannels): |
|
|
520 | 522 | daux = self.data_spc[channel, |
|
|
521 | 523 | xmin_index:xmax_index, ymin_index:ymax_index] |
|
|
522 | 524 | noise[channel] = hildebrand_sekhon(daux, self.nIncohInt) |
|
|
523 | 525 | |
|
|
524 | 526 | return noise |
|
|
525 | 527 | |
|
|
526 | 528 | def getNoise(self, xmin_index=None, xmax_index=None, ymin_index=None, ymax_index=None): |
|
|
527 | 529 | |
|
|
528 | 530 | if self.noise_estimation is not None: |
|
|
529 | 531 | # this was estimated by getNoise Operation defined in jroproc_spectra.py |
|
|
530 | 532 | return self.noise_estimation |
|
|
531 | 533 | else: |
|
|
532 | 534 | noise = self.getNoisebyHildebrand( |
|
|
533 | 535 | xmin_index, xmax_index, ymin_index, ymax_index) |
|
|
534 | 536 | return noise |
|
|
535 | 537 | |
|
|
536 | 538 | def getFreqRangeTimeResponse(self, extrapoints=0): |
|
|
537 | 539 | |
|
|
538 | 540 | deltafreq = self.getFmaxTimeResponse() / (self.nFFTPoints * self.ippFactor) |
|
|
539 | 541 | freqrange = deltafreq * (numpy.arange(self.nFFTPoints + extrapoints) - self.nFFTPoints / 2.) - deltafreq / 2 |
|
|
540 | 542 | |
|
|
541 | 543 | return freqrange |
|
|
542 | 544 | |
|
|
543 | 545 | def getAcfRange(self, extrapoints=0): |
|
|
544 | 546 | |
|
|
545 | 547 | deltafreq = 10. / (self.getFmax() / (self.nFFTPoints * self.ippFactor)) |
|
|
546 | 548 | freqrange = deltafreq * (numpy.arange(self.nFFTPoints + extrapoints) -self.nFFTPoints / 2.) - deltafreq / 2 |
|
|
547 | 549 | |
|
|
548 | 550 | return freqrange |
|
|
549 | 551 | |
|
|
550 | 552 | def getFreqRange(self, extrapoints=0): |
|
|
551 | 553 | |
|
|
552 | 554 | deltafreq = self.getFmax() / (self.nFFTPoints * self.ippFactor) |
|
|
553 | 555 | freqrange = deltafreq * (numpy.arange(self.nFFTPoints + extrapoints) -self.nFFTPoints / 2.) - deltafreq / 2 |
|
|
554 | 556 | |
|
|
555 | 557 | return freqrange |
|
|
556 | 558 | |
|
|
557 | 559 | def getVelRange(self, extrapoints=0): |
|
|
558 | 560 | |
|
|
559 | 561 | deltav = self.getVmax() / (self.nFFTPoints * self.ippFactor) |
|
|
560 | 562 | velrange = deltav * (numpy.arange(self.nFFTPoints + extrapoints) - self.nFFTPoints / 2.) |
|
|
561 | 563 | |
|
|
562 | 564 | if self.nmodes: |
|
|
563 | 565 | return velrange/self.nmodes |
|
|
564 | 566 | else: |
|
|
565 | 567 | return velrange |
|
|
566 | 568 | |
|
|
567 | 569 | def getNPairs(self): |
|
|
568 | 570 | |
|
|
569 | 571 | return len(self.pairsList) |
|
|
570 | 572 | |
|
|
571 | 573 | def getPairsIndexList(self): |
|
|
572 | 574 | |
|
|
573 | 575 | return list(range(self.nPairs)) |
|
|
574 | 576 | |
|
|
575 | 577 | def getNormFactor(self): |
|
|
576 | 578 | |
|
|
577 | 579 | pwcode = 1 |
|
|
578 | 580 | |
|
|
579 | 581 | if self.flagDecodeData: |
|
|
580 | 582 | pwcode = numpy.sum(self.code[0]**2) |
|
|
581 | 583 | #normFactor = min(self.nFFTPoints,self.nProfiles)*self.nIncohInt*self.nCohInt*pwcode*self.windowOfFilter |
|
|
582 | 584 | normFactor = self.nProfiles * self.nIncohInt * self.nCohInt * pwcode * self.windowOfFilter |
|
|
583 | 585 | |
|
|
584 | 586 | return normFactor |
|
|
585 | 587 | |
|
|
586 | 588 | def getFlagCspc(self): |
|
|
587 | 589 | |
|
|
588 | 590 | if self.data_cspc is None: |
|
|
589 | 591 | return True |
|
|
590 | 592 | |
|
|
591 | 593 | return False |
|
|
592 | 594 | |
|
|
593 | 595 | def getFlagDc(self): |
|
|
594 | 596 | |
|
|
595 | 597 | if self.data_dc is None: |
|
|
596 | 598 | return True |
|
|
597 | 599 | |
|
|
598 | 600 | return False |
|
|
599 | 601 | |
|
|
600 | 602 | def getTimeInterval(self): |
|
|
601 | 603 | |
|
|
602 | 604 | timeInterval = self.ippSeconds * self.nCohInt * self.nIncohInt * self.nProfiles * self.ippFactor |
|
|
603 | 605 | if self.nmodes: |
|
|
604 | 606 | return self.nmodes*timeInterval |
|
|
605 | 607 | else: |
|
|
606 | 608 | return timeInterval |
|
|
607 | 609 | |
|
|
608 | 610 | def getPower(self): |
|
|
609 | 611 | |
|
|
610 | 612 | factor = self.normFactor |
|
|
611 | 613 | z = self.data_spc / factor |
|
|
612 | 614 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) |
|
|
613 | 615 | avg = numpy.average(z, axis=1) |
|
|
614 | 616 | |
|
|
615 | 617 | return 10 * numpy.log10(avg) |
|
|
616 | 618 | |
|
|
617 | 619 | def getCoherence(self, pairsList=None, phase=False): |
|
|
618 | 620 | |
|
|
619 | 621 | z = [] |
|
|
620 | 622 | if pairsList is None: |
|
|
621 | 623 | pairsIndexList = self.pairsIndexList |
|
|
622 | 624 | else: |
|
|
623 | 625 | pairsIndexList = [] |
|
|
624 | 626 | for pair in pairsList: |
|
|
625 | 627 | if pair not in self.pairsList: |
|
|
626 | 628 | raise ValueError("Pair %s is not in dataOut.pairsList" % ( |
|
|
627 | 629 | pair)) |
|
|
628 | 630 | pairsIndexList.append(self.pairsList.index(pair)) |
|
|
629 | 631 | for i in range(len(pairsIndexList)): |
|
|
630 | 632 | pair = self.pairsList[pairsIndexList[i]] |
|
|
631 | 633 | ccf = numpy.average(self.data_cspc[pairsIndexList[i], :, :], axis=0) |
|
|
632 | 634 | powa = numpy.average(self.data_spc[pair[0], :, :], axis=0) |
|
|
633 | 635 | powb = numpy.average(self.data_spc[pair[1], :, :], axis=0) |
|
|
634 | 636 | avgcoherenceComplex = ccf / numpy.sqrt(powa * powb) |
|
|
635 | 637 | if phase: |
|
|
636 | 638 | data = numpy.arctan2(avgcoherenceComplex.imag, |
|
|
637 | 639 | avgcoherenceComplex.real) * 180 / numpy.pi |
|
|
638 | 640 | else: |
|
|
639 | 641 | data = numpy.abs(avgcoherenceComplex) |
|
|
640 | 642 | |
|
|
641 | 643 | z.append(data) |
|
|
642 | 644 | |
|
|
643 | 645 | return numpy.array(z) |
|
|
644 | 646 | |
|
|
645 | 647 | def setValue(self, value): |
|
|
646 | 648 | |
|
|
647 | 649 | print("This property should not be initialized") |
|
|
648 | 650 | |
|
|
649 | 651 | return |
|
|
650 | 652 | |
|
|
651 | 653 | nPairs = property(getNPairs, setValue, "I'm the 'nPairs' property.") |
|
|
652 | 654 | pairsIndexList = property( |
|
|
653 | 655 | getPairsIndexList, setValue, "I'm the 'pairsIndexList' property.") |
|
|
654 | 656 | normFactor = property(getNormFactor, setValue, |
|
|
655 | 657 | "I'm the 'getNormFactor' property.") |
|
|
656 | 658 | flag_cspc = property(getFlagCspc, setValue) |
|
|
657 | 659 | flag_dc = property(getFlagDc, setValue) |
|
|
658 | 660 | noise = property(getNoise, setValue, "I'm the 'nHeights' property.") |
|
|
659 | 661 | timeInterval = property(getTimeInterval, setValue, |
|
|
660 | 662 | "I'm the 'timeInterval' property") |
|
|
661 | 663 | |
|
|
662 | 664 | |
|
|
663 | 665 | class SpectraHeis(Spectra): |
|
|
664 | 666 | |
|
|
665 | 667 | data_spc = None |
|
|
666 | 668 | data_cspc = None |
|
|
667 | 669 | data_dc = None |
|
|
668 | 670 | nFFTPoints = None |
|
|
669 | 671 | # nPairs = None |
|
|
670 | 672 | pairsList = None |
|
|
671 | 673 | nCohInt = None |
|
|
672 | 674 | nIncohInt = None |
|
|
673 | 675 | |
|
|
674 | 676 | def __init__(self): |
|
|
675 | 677 | |
|
|
676 | 678 | self.radarControllerHeaderObj = RadarControllerHeader() |
|
|
677 | 679 | |
|
|
678 | 680 | self.systemHeaderObj = SystemHeader() |
|
|
679 | 681 | |
|
|
680 | 682 | self.type = "SpectraHeis" |
|
|
681 | 683 | |
|
|
682 | 684 | # self.dtype = None |
|
|
683 | 685 | |
|
|
684 | 686 | # self.nChannels = 0 |
|
|
685 | 687 | |
|
|
686 | 688 | # self.nHeights = 0 |
|
|
687 | 689 | |
|
|
688 | 690 | self.nProfiles = None |
|
|
689 | 691 | |
|
|
690 | 692 | self.heightList = None |
|
|
691 | 693 | |
|
|
692 | 694 | self.channelList = None |
|
|
693 | 695 | |
|
|
694 | 696 | # self.channelIndexList = None |
|
|
695 | 697 | |
|
|
696 | 698 | self.flagNoData = True |
|
|
697 | 699 | |
|
|
698 | 700 | self.flagDiscontinuousBlock = False |
|
|
699 | 701 | |
|
|
700 | 702 | # self.nPairs = 0 |
|
|
701 | 703 | |
|
|
702 | 704 | self.utctime = None |
|
|
703 | 705 | |
|
|
704 | 706 | self.blocksize = None |
|
|
705 | 707 | |
|
|
706 | 708 | self.profileIndex = 0 |
|
|
707 | 709 | |
|
|
708 | 710 | self.nCohInt = 1 |
|
|
709 | 711 | |
|
|
710 | 712 | self.nIncohInt = 1 |
|
|
711 | 713 | |
|
|
712 | 714 | def getNormFactor(self): |
|
|
713 | 715 | pwcode = 1 |
|
|
714 | 716 | if self.flagDecodeData: |
|
|
715 | 717 | pwcode = numpy.sum(self.code[0]**2) |
|
|
716 | 718 | |
|
|
717 | 719 | normFactor = self.nIncohInt * self.nCohInt * pwcode |
|
|
718 | 720 | |
|
|
719 | 721 | return normFactor |
|
|
720 | 722 | |
|
|
721 | 723 | def getTimeInterval(self): |
|
|
722 | 724 | |
|
|
723 | 725 | timeInterval = self.ippSeconds * self.nCohInt * self.nIncohInt |
|
|
724 | 726 | |
|
|
725 | 727 | return timeInterval |
|
|
726 | 728 | |
|
|
727 | 729 | normFactor = property(getNormFactor, "I'm the 'getNormFactor' property.") |
|
|
728 | 730 | timeInterval = property(getTimeInterval, "I'm the 'timeInterval' property") |
|
|
729 | 731 | |
|
|
730 | 732 | |
|
|
731 | 733 | class Fits(JROData): |
|
|
732 | 734 | |
|
|
733 | 735 | heightList = None |
|
|
734 | 736 | channelList = None |
|
|
735 | 737 | flagNoData = True |
|
|
736 | 738 | flagDiscontinuousBlock = False |
|
|
737 | 739 | useLocalTime = False |
|
|
738 | 740 | utctime = None |
|
|
739 | 741 | timeZone = None |
|
|
740 | 742 | # ippSeconds = None |
|
|
741 | 743 | # timeInterval = None |
|
|
742 | 744 | nCohInt = None |
|
|
743 | 745 | nIncohInt = None |
|
|
744 | 746 | noise = None |
|
|
745 | 747 | windowOfFilter = 1 |
|
|
746 | 748 | # Speed of ligth |
|
|
747 | 749 | C = 3e8 |
|
|
748 | 750 | frequency = 49.92e6 |
|
|
749 | 751 | realtime = False |
|
|
750 | 752 | |
|
|
751 | 753 | def __init__(self): |
|
|
752 | 754 | |
|
|
753 | 755 | self.type = "Fits" |
|
|
754 | 756 | |
|
|
755 | 757 | self.nProfiles = None |
|
|
756 | 758 | |
|
|
757 | 759 | self.heightList = None |
|
|
758 | 760 | |
|
|
759 | 761 | self.channelList = None |
|
|
760 | 762 | |
|
|
761 | 763 | # self.channelIndexList = None |
|
|
762 | 764 | |
|
|
763 | 765 | self.flagNoData = True |
|
|
764 | 766 | |
|
|
765 | 767 | self.utctime = None |
|
|
766 | 768 | |
|
|
767 | 769 | self.nCohInt = 1 |
|
|
768 | 770 | |
|
|
769 | 771 | self.nIncohInt = 1 |
|
|
770 | 772 | |
|
|
771 | 773 | self.useLocalTime = True |
|
|
772 | 774 | |
|
|
773 | 775 | self.profileIndex = 0 |
|
|
774 | 776 | |
|
|
775 | 777 | # self.utctime = None |
|
|
776 | 778 | # self.timeZone = None |
|
|
777 | 779 | # self.ltctime = None |
|
|
778 | 780 | # self.timeInterval = None |
|
|
779 | 781 | # self.header = None |
|
|
780 | 782 | # self.data_header = None |
|
|
781 | 783 | # self.data = None |
|
|
782 | 784 | # self.datatime = None |
|
|
783 | 785 | # self.flagNoData = False |
|
|
784 | 786 | # self.expName = '' |
|
|
785 | 787 | # self.nChannels = None |
|
|
786 | 788 | # self.nSamples = None |
|
|
787 | 789 | # self.dataBlocksPerFile = None |
|
|
788 | 790 | # self.comments = '' |
|
|
789 | 791 | # |
|
|
790 | 792 | |
|
|
791 | 793 | def getltctime(self): |
|
|
792 | 794 | |
|
|
793 | 795 | if self.useLocalTime: |
|
|
794 | 796 | return self.utctime - self.timeZone * 60 |
|
|
795 | 797 | |
|
|
796 | 798 | return self.utctime |
|
|
797 | 799 | |
|
|
798 | 800 | def getDatatime(self): |
|
|
799 | 801 | |
|
|
800 | 802 | datatime = datetime.datetime.utcfromtimestamp(self.ltctime) |
|
|
801 | 803 | return datatime |
|
|
802 | 804 | |
|
|
803 | 805 | def getTimeRange(self): |
|
|
804 | 806 | |
|
|
805 | 807 | datatime = [] |
|
|
806 | 808 | |
|
|
807 | 809 | datatime.append(self.ltctime) |
|
|
808 | 810 | datatime.append(self.ltctime + self.timeInterval) |
|
|
809 | 811 | |
|
|
810 | 812 | datatime = numpy.array(datatime) |
|
|
811 | 813 | |
|
|
812 | 814 | return datatime |
|
|
813 | 815 | |
|
|
814 | 816 | def getHeiRange(self): |
|
|
815 | 817 | |
|
|
816 | 818 | heis = self.heightList |
|
|
817 | 819 | |
|
|
818 | 820 | return heis |
|
|
819 | 821 | |
|
|
820 | 822 | def getNHeights(self): |
|
|
821 | 823 | |
|
|
822 | 824 | return len(self.heightList) |
|
|
823 | 825 | |
|
|
824 | 826 | def getNChannels(self): |
|
|
825 | 827 | |
|
|
826 | 828 | return len(self.channelList) |
|
|
827 | 829 | |
|
|
828 | 830 | def getChannelIndexList(self): |
|
|
829 | 831 | |
|
|
830 | 832 | return list(range(self.nChannels)) |
|
|
831 | 833 | |
|
|
832 | 834 | def getNoise(self, type=1): |
|
|
833 | 835 | |
|
|
834 | 836 | #noise = numpy.zeros(self.nChannels) |
|
|
835 | 837 | |
|
|
836 | 838 | if type == 1: |
|
|
837 | 839 | noise = self.getNoisebyHildebrand() |
|
|
838 | 840 | |
|
|
839 | 841 | if type == 2: |
|
|
840 | 842 | noise = self.getNoisebySort() |
|
|
841 | 843 | |
|
|
842 | 844 | if type == 3: |
|
|
843 | 845 | noise = self.getNoisebyWindow() |
|
|
844 | 846 | |
|
|
845 | 847 | return noise |
|
|
846 | 848 | |
|
|
847 | 849 | def getTimeInterval(self): |
|
|
848 | 850 | |
|
|
849 | 851 | timeInterval = self.ippSeconds * self.nCohInt * self.nIncohInt |
|
|
850 | 852 | |
|
|
851 | 853 | return timeInterval |
|
|
852 | 854 | |
|
|
853 | 855 | def get_ippSeconds(self): |
|
|
854 | 856 | ''' |
|
|
855 | 857 | ''' |
|
|
856 | 858 | return self.ipp_sec |
|
|
857 | 859 | |
|
|
858 | 860 | |
|
|
859 | 861 | datatime = property(getDatatime, "I'm the 'datatime' property") |
|
|
860 | 862 | nHeights = property(getNHeights, "I'm the 'nHeights' property.") |
|
|
861 | 863 | nChannels = property(getNChannels, "I'm the 'nChannel' property.") |
|
|
862 | 864 | channelIndexList = property( |
|
|
863 | 865 | getChannelIndexList, "I'm the 'channelIndexList' property.") |
|
|
864 | 866 | noise = property(getNoise, "I'm the 'nHeights' property.") |
|
|
865 | 867 | |
|
|
866 | 868 | ltctime = property(getltctime, "I'm the 'ltctime' property") |
|
|
867 | 869 | timeInterval = property(getTimeInterval, "I'm the 'timeInterval' property") |
|
|
868 | 870 | ippSeconds = property(get_ippSeconds, '') |
|
|
869 | 871 | |
|
|
870 | 872 | class Correlation(JROData): |
|
|
871 | 873 | |
|
|
872 | 874 | noise = None |
|
|
873 | 875 | SNR = None |
|
|
874 | 876 | #-------------------------------------------------- |
|
|
875 | 877 | mode = None |
|
|
876 | 878 | split = False |
|
|
877 | 879 | data_cf = None |
|
|
878 | 880 | lags = None |
|
|
879 | 881 | lagRange = None |
|
|
880 | 882 | pairsList = None |
|
|
881 | 883 | normFactor = None |
|
|
882 | 884 | #-------------------------------------------------- |
|
|
883 | 885 | # calculateVelocity = None |
|
|
884 | 886 | nLags = None |
|
|
885 | 887 | nPairs = None |
|
|
886 | 888 | nAvg = None |
|
|
887 | 889 | |
|
|
888 | 890 | def __init__(self): |
|
|
889 | 891 | ''' |
|
|
890 | 892 | Constructor |
|
|
891 | 893 | ''' |
|
|
892 | 894 | self.radarControllerHeaderObj = RadarControllerHeader() |
|
|
893 | 895 | |
|
|
894 | 896 | self.systemHeaderObj = SystemHeader() |
|
|
895 | 897 | |
|
|
896 | 898 | self.type = "Correlation" |
|
|
897 | 899 | |
|
|
898 | 900 | self.data = None |
|
|
899 | 901 | |
|
|
900 | 902 | self.dtype = None |
|
|
901 | 903 | |
|
|
902 | 904 | self.nProfiles = None |
|
|
903 | 905 | |
|
|
904 | 906 | self.heightList = None |
|
|
905 | 907 | |
|
|
906 | 908 | self.channelList = None |
|
|
907 | 909 | |
|
|
908 | 910 | self.flagNoData = True |
|
|
909 | 911 | |
|
|
910 | 912 | self.flagDiscontinuousBlock = False |
|
|
911 | 913 | |
|
|
912 | 914 | self.utctime = None |
|
|
913 | 915 | |
|
|
914 | 916 | self.timeZone = None |
|
|
915 | 917 | |
|
|
916 | 918 | self.dstFlag = None |
|
|
917 | 919 | |
|
|
918 | 920 | self.errorCount = None |
|
|
919 | 921 | |
|
|
920 | 922 | self.blocksize = None |
|
|
921 | 923 | |
|
|
922 | 924 | self.flagDecodeData = False # asumo q la data no esta decodificada |
|
|
923 | 925 | |
|
|
924 | 926 | self.flagDeflipData = False # asumo q la data no esta sin flip |
|
|
925 | 927 | |
|
|
926 | 928 | self.pairsList = None |
|
|
927 | 929 | |
|
|
928 | 930 | self.nPoints = None |
|
|
929 | 931 | |
|
|
930 | 932 | def getPairsList(self): |
|
|
931 | 933 | |
|
|
932 | 934 | return self.pairsList |
|
|
933 | 935 | |
|
|
934 | 936 | def getNoise(self, mode=2): |
|
|
935 | 937 | |
|
|
936 | 938 | indR = numpy.where(self.lagR == 0)[0][0] |
|
|
937 | 939 | indT = numpy.where(self.lagT == 0)[0][0] |
|
|
938 | 940 | |
|
|
939 | 941 | jspectra0 = self.data_corr[:, :, indR, :] |
|
|
940 | 942 | jspectra = copy.copy(jspectra0) |
|
|
941 | 943 | |
|
|
942 | 944 | num_chan = jspectra.shape[0] |
|
|
943 | 945 | num_hei = jspectra.shape[2] |
|
|
944 | 946 | |
|
|
945 | 947 | freq_dc = jspectra.shape[1] / 2 |
|
|
946 | 948 | ind_vel = numpy.array([-2, -1, 1, 2]) + freq_dc |
|
|
947 | 949 | |
|
|
948 | 950 | if ind_vel[0] < 0: |
|
|
949 | 951 | ind_vel[list(range(0, 1))] = ind_vel[list( |
|
|
950 | 952 | range(0, 1))] + self.num_prof |
|
|
951 | 953 | |
|
|
952 | 954 | if mode == 1: |
|
|
953 | 955 | jspectra[:, freq_dc, :] = ( |
|
|
954 | 956 | jspectra[:, ind_vel[1], :] + jspectra[:, ind_vel[2], :]) / 2 # CORRECCION |
|
|
955 | 957 | |
|
|
956 | 958 | if mode == 2: |
|
|
957 | 959 | |
|
|
958 | 960 | vel = numpy.array([-2, -1, 1, 2]) |
|
|
959 | 961 | xx = numpy.zeros([4, 4]) |
|
|
960 | 962 | |
|
|
961 | 963 | for fil in range(4): |
|
|
962 | 964 | xx[fil, :] = vel[fil]**numpy.asarray(list(range(4))) |
|
|
963 | 965 | |
|
|
964 | 966 | xx_inv = numpy.linalg.inv(xx) |
|
|
965 | 967 | xx_aux = xx_inv[0, :] |
|
|
966 | 968 | |
|
|
967 | 969 | for ich in range(num_chan): |
|
|
968 | 970 | yy = jspectra[ich, ind_vel, :] |
|
|
969 | 971 | jspectra[ich, freq_dc, :] = numpy.dot(xx_aux, yy) |
|
|
970 | 972 | |
|
|
971 | 973 | junkid = jspectra[ich, freq_dc, :] <= 0 |
|
|
972 | 974 | cjunkid = sum(junkid) |
|
|
973 | 975 | |
|
|
974 | 976 | if cjunkid.any(): |
|
|
975 | 977 | jspectra[ich, freq_dc, junkid.nonzero()] = ( |
|
|
976 | 978 | jspectra[ich, ind_vel[1], junkid] + jspectra[ich, ind_vel[2], junkid]) / 2 |
|
|
977 | 979 | |
|
|
978 | 980 | noise = jspectra0[:, freq_dc, :] - jspectra[:, freq_dc, :] |
|
|
979 | 981 | |
|
|
980 | 982 | return noise |
|
|
981 | 983 | |
|
|
982 | 984 | def getTimeInterval(self): |
|
|
983 | 985 | |
|
|
984 | 986 | timeInterval = self.ippSeconds * self.nCohInt * self.nProfiles |
|
|
985 | 987 | |
|
|
986 | 988 | return timeInterval |
|
|
987 | 989 | |
|
|
988 | 990 | def splitFunctions(self): |
|
|
989 | 991 | |
|
|
990 | 992 | pairsList = self.pairsList |
|
|
991 | 993 | ccf_pairs = [] |
|
|
992 | 994 | acf_pairs = [] |
|
|
993 | 995 | ccf_ind = [] |
|
|
994 | 996 | acf_ind = [] |
|
|
995 | 997 | for l in range(len(pairsList)): |
|
|
996 | 998 | chan0 = pairsList[l][0] |
|
|
997 | 999 | chan1 = pairsList[l][1] |
|
|
998 | 1000 | |
|
|
999 | 1001 | # Obteniendo pares de Autocorrelacion |
|
|
1000 | 1002 | if chan0 == chan1: |
|
|
1001 | 1003 | acf_pairs.append(chan0) |
|
|
1002 | 1004 | acf_ind.append(l) |
|
|
1003 | 1005 | else: |
|
|
1004 | 1006 | ccf_pairs.append(pairsList[l]) |
|
|
1005 | 1007 | ccf_ind.append(l) |
|
|
1006 | 1008 | |
|
|
1007 | 1009 | data_acf = self.data_cf[acf_ind] |
|
|
1008 | 1010 | data_ccf = self.data_cf[ccf_ind] |
|
|
1009 | 1011 | |
|
|
1010 | 1012 | return acf_ind, ccf_ind, acf_pairs, ccf_pairs, data_acf, data_ccf |
|
|
1011 | 1013 | |
|
|
1012 | 1014 | def getNormFactor(self): |
|
|
1013 | 1015 | acf_ind, ccf_ind, acf_pairs, ccf_pairs, data_acf, data_ccf = self.splitFunctions() |
|
|
1014 | 1016 | acf_pairs = numpy.array(acf_pairs) |
|
|
1015 | 1017 | normFactor = numpy.zeros((self.nPairs, self.nHeights)) |
|
|
1016 | 1018 | |
|
|
1017 | 1019 | for p in range(self.nPairs): |
|
|
1018 | 1020 | pair = self.pairsList[p] |
|
|
1019 | 1021 | |
|
|
1020 | 1022 | ch0 = pair[0] |
|
|
1021 | 1023 | ch1 = pair[1] |
|
|
1022 | 1024 | |
|
|
1023 | 1025 | ch0_max = numpy.max(data_acf[acf_pairs == ch0, :, :], axis=1) |
|
|
1024 | 1026 | ch1_max = numpy.max(data_acf[acf_pairs == ch1, :, :], axis=1) |
|
|
1025 | 1027 | normFactor[p, :] = numpy.sqrt(ch0_max * ch1_max) |
|
|
1026 | 1028 | |
|
|
1027 | 1029 | return normFactor |
|
|
1028 | 1030 | |
|
|
1029 | 1031 | timeInterval = property(getTimeInterval, "I'm the 'timeInterval' property") |
|
|
1030 | 1032 | normFactor = property(getNormFactor, "I'm the 'normFactor property'") |
|
|
1031 | 1033 | |
|
|
1032 | 1034 | |
|
|
1033 | 1035 | class Parameters(Spectra): |
|
|
1034 | 1036 | |
|
|
1035 | 1037 | experimentInfo = None # Information about the experiment |
|
|
1036 | 1038 | # Information from previous data |
|
|
1037 | 1039 | inputUnit = None # Type of data to be processed |
|
|
1038 | 1040 | operation = None # Type of operation to parametrize |
|
|
1039 | 1041 | # normFactor = None #Normalization Factor |
|
|
1040 | 1042 | groupList = None # List of Pairs, Groups, etc |
|
|
1041 | 1043 | # Parameters |
|
|
1042 | 1044 | data_param = None # Parameters obtained |
|
|
1043 | 1045 | data_pre = None # Data Pre Parametrization |
|
|
1044 | 1046 | data_SNR = None # Signal to Noise Ratio |
|
|
1045 | 1047 | # heightRange = None #Heights |
|
|
1046 | 1048 | abscissaList = None # Abscissa, can be velocities, lags or time |
|
|
1047 | 1049 | # noise = None #Noise Potency |
|
|
1048 | 1050 | utctimeInit = None # Initial UTC time |
|
|
1049 | 1051 | paramInterval = None # Time interval to calculate Parameters in seconds |
|
|
1050 | 1052 | useLocalTime = True |
|
|
1051 | 1053 | # Fitting |
|
|
1052 | 1054 | data_error = None # Error of the estimation |
|
|
1053 | 1055 | constants = None |
|
|
1054 | 1056 | library = None |
|
|
1055 | 1057 | # Output signal |
|
|
1056 | 1058 | outputInterval = None # Time interval to calculate output signal in seconds |
|
|
1057 | 1059 | data_output = None # Out signal |
|
|
1058 | 1060 | nAvg = None |
|
|
1059 | 1061 | noise_estimation = None |
|
|
1060 | 1062 | GauSPC = None # Fit gaussian SPC |
|
|
1061 | 1063 | |
|
|
1062 | 1064 | def __init__(self): |
|
|
1063 | 1065 | ''' |
|
|
1064 | 1066 | Constructor |
|
|
1065 | 1067 | ''' |
|
|
1066 | 1068 | self.radarControllerHeaderObj = RadarControllerHeader() |
|
|
1067 | 1069 | |
|
|
1068 | 1070 | self.systemHeaderObj = SystemHeader() |
|
|
1069 | 1071 | |
|
|
1070 | 1072 | self.type = "Parameters" |
|
|
1071 | 1073 | |
|
|
1072 | 1074 | def getTimeRange1(self, interval): |
|
|
1073 | 1075 | |
|
|
1074 | 1076 | datatime = [] |
|
|
1075 | 1077 | |
|
|
1076 | 1078 | if self.useLocalTime: |
|
|
1077 | 1079 | time1 = self.utctimeInit - self.timeZone * 60 |
|
|
1078 | 1080 | else: |
|
|
1079 | 1081 | time1 = self.utctimeInit |
|
|
1080 | 1082 | |
|
|
1081 | 1083 | datatime.append(time1) |
|
|
1082 | 1084 | datatime.append(time1 + interval) |
|
|
1083 | 1085 | datatime = numpy.array(datatime) |
|
|
1084 | 1086 | |
|
|
1085 | 1087 | return datatime |
|
|
1086 | 1088 | |
|
|
1087 | 1089 | def getTimeInterval(self): |
|
|
1088 | 1090 | |
|
|
1089 | 1091 | if hasattr(self, 'timeInterval1'): |
|
|
1090 | 1092 | return self.timeInterval1 |
|
|
1091 | 1093 | else: |
|
|
1092 | 1094 | return self.paramInterval |
|
|
1093 | 1095 | |
|
|
1094 | 1096 | def setValue(self, value): |
|
|
1095 | 1097 | |
|
|
1096 | 1098 | print("This property should not be initialized") |
|
|
1097 | 1099 | |
|
|
1098 | 1100 | return |
|
|
1099 | 1101 | |
|
|
1100 | 1102 | def getNoise(self): |
|
|
1101 | 1103 | |
|
|
1102 | 1104 | return self.spc_noise |
|
|
1103 | 1105 | |
|
|
1104 | 1106 | timeInterval = property(getTimeInterval) |
|
|
1105 | 1107 | noise = property(getNoise, setValue, "I'm the 'Noise' property.") |
|
|
1106 | 1108 | |
|
|
1107 | 1109 | |
|
|
1108 | 1110 | class PlotterData(object): |
|
|
1109 | 1111 | ''' |
|
|
1110 | 1112 | Object to hold data to be plotted |
|
|
1111 | 1113 | ''' |
|
|
1112 | 1114 | |
|
|
1113 | 1115 | MAXNUMX = 200 |
|
|
1114 | 1116 | MAXNUMY = 200 |
|
|
1115 | 1117 | |
|
|
1116 | 1118 | def __init__(self, code, throttle_value, exp_code, buffering=True, snr=False): |
|
|
1117 | 1119 | |
|
|
1118 | 1120 | self.key = code |
|
|
1119 | 1121 | self.throttle = throttle_value |
|
|
1120 | 1122 | self.exp_code = exp_code |
|
|
1121 | 1123 | self.buffering = buffering |
|
|
1122 | 1124 | self.ready = False |
|
|
1123 | 1125 | self.flagNoData = False |
|
|
1124 | 1126 | self.localtime = False |
|
|
1125 | 1127 | self.data = {} |
|
|
1126 | 1128 | self.meta = {} |
|
|
1127 | 1129 | self.__heights = [] |
|
|
1128 | 1130 | |
|
|
1129 | 1131 | if 'snr' in code: |
|
|
1130 | 1132 | self.plottypes = ['snr'] |
|
|
1131 | 1133 | elif code == 'spc': |
|
|
1132 | 1134 | self.plottypes = ['spc', 'noise', 'rti'] |
|
|
1133 | 1135 | elif code == 'cspc': |
|
|
1134 | 1136 | self.plottypes = ['cspc', 'spc', 'noise', 'rti'] |
|
|
1135 | 1137 | elif code == 'rti': |
|
|
1136 | 1138 | self.plottypes = ['noise', 'rti'] |
|
|
1137 | 1139 | else: |
|
|
1138 | 1140 | self.plottypes = [code] |
|
|
1139 | 1141 | |
|
|
1140 | 1142 | if 'snr' not in self.plottypes and snr: |
|
|
1141 | 1143 | self.plottypes.append('snr') |
|
|
1142 | 1144 | |
|
|
1143 | 1145 | for plot in self.plottypes: |
|
|
1144 | 1146 | self.data[plot] = {} |
|
|
1145 | 1147 | |
|
|
1146 | 1148 | |
|
|
1147 | 1149 | def __str__(self): |
|
|
1148 | 1150 | dum = ['{}{}'.format(key, self.shape(key)) for key in self.data] |
|
|
1149 | 1151 | return 'Data[{}][{}]'.format(';'.join(dum), len(self.times)) |
|
|
1150 | 1152 | |
|
|
1151 | 1153 | def __len__(self): |
|
|
1152 | 1154 | return len(self.data[self.key]) |
|
|
1153 | 1155 | |
|
|
1154 | 1156 | def __getitem__(self, key): |
|
|
1155 | 1157 | |
|
|
1156 | 1158 | if key not in self.data: |
|
|
1157 | 1159 | raise KeyError(log.error('Missing key: {}'.format(key))) |
|
|
1158 | 1160 | if 'spc' in key or not self.buffering: |
|
|
1159 | 1161 | ret = self.data[key][self.tm] |
|
|
1160 | 1162 | elif 'scope' in key: |
|
|
1161 | 1163 | ret = numpy.array(self.data[key][float(self.tm)]) |
|
|
1162 | 1164 | else: |
|
|
1163 | 1165 | ret = numpy.array([self.data[key][x] for x in self.times]) |
|
|
1164 | 1166 | if ret.ndim > 1: |
|
|
1165 | 1167 | ret = numpy.swapaxes(ret, 0, 1) |
|
|
1166 | 1168 | return ret |
|
|
1167 | 1169 | |
|
|
1168 | 1170 | def __contains__(self, key): |
|
|
1169 | 1171 | return key in self.data |
|
|
1170 | 1172 | |
|
|
1171 | 1173 | def setup(self): |
|
|
1172 | 1174 | ''' |
|
|
1173 | 1175 | Configure object |
|
|
1174 | 1176 | ''' |
|
|
1175 | 1177 | self.type = '' |
|
|
1176 | 1178 | self.ready = False |
|
|
1177 | 1179 | del self.data |
|
|
1178 | 1180 | self.data = {} |
|
|
1179 | 1181 | self.__heights = [] |
|
|
1180 | 1182 | self.__all_heights = set() |
|
|
1181 | 1183 | for plot in self.plottypes: |
|
|
1182 | 1184 | if 'snr' in plot: |
|
|
1183 | 1185 | plot = 'snr' |
|
|
1184 | 1186 | elif 'spc_moments' == plot: |
|
|
1185 | 1187 | plot = 'moments' |
|
|
1186 | 1188 | self.data[plot] = {} |
|
|
1187 | 1189 | |
|
|
1188 | 1190 | if 'spc' in self.data or 'rti' in self.data or 'cspc' in self.data or 'moments' in self.data: |
|
|
1189 | 1191 | self.data['noise'] = {} |
|
|
1190 | 1192 | self.data['rti'] = {} |
|
|
1191 | 1193 | if 'noise' not in self.plottypes: |
|
|
1192 | 1194 | self.plottypes.append('noise') |
|
|
1193 | 1195 | if 'rti' not in self.plottypes: |
|
|
1194 | 1196 | self.plottypes.append('rti') |
|
|
1195 | 1197 | |
|
|
1196 | 1198 | def shape(self, key): |
|
|
1197 | 1199 | ''' |
|
|
1198 | 1200 | Get the shape of the one-element data for the given key |
|
|
1199 | 1201 | ''' |
|
|
1200 | 1202 | |
|
|
1201 | 1203 | if len(self.data[key]): |
|
|
1202 | 1204 | if 'spc' in key or not self.buffering: |
|
|
1203 | 1205 | return self.data[key].shape |
|
|
1204 | 1206 | return self.data[key][self.times[0]].shape |
|
|
1205 | 1207 | return (0,) |
|
|
1206 | 1208 | |
|
|
1207 | 1209 | def update(self, dataOut, tm): |
|
|
1208 | 1210 | ''' |
|
|
1209 | 1211 | Update data object with new dataOut |
|
|
1210 | 1212 | ''' |
|
|
1211 | ||
|
|
1213 | ||
|
|
1212 | 1214 | self.profileIndex = dataOut.profileIndex |
|
|
1213 | 1215 | self.tm = tm |
|
|
1214 | 1216 | self.type = dataOut.type |
|
|
1215 | 1217 | self.parameters = getattr(dataOut, 'parameters', []) |
|
|
1216 | 1218 | |
|
|
1217 | 1219 | if hasattr(dataOut, 'meta'): |
|
|
1218 | 1220 | self.meta.update(dataOut.meta) |
|
|
1219 | 1221 | |
|
|
1220 | 1222 | if hasattr(dataOut, 'pairsList'): |
|
|
1221 | 1223 | self.pairs = dataOut.pairsList |
|
|
1222 | 1224 | |
|
|
1223 | 1225 | self.interval = dataOut.getTimeInterval() |
|
|
1224 | 1226 | self.localtime = dataOut.useLocalTime |
|
|
1225 | 1227 | if True in ['spc' in ptype for ptype in self.plottypes]: |
|
|
1226 | 1228 | self.xrange = (dataOut.getFreqRange(1)/1000., |
|
|
1227 | 1229 | dataOut.getAcfRange(1), dataOut.getVelRange(1)) |
|
|
1228 | 1230 | self.__heights.append(dataOut.heightList) |
|
|
1229 | 1231 | self.__all_heights.update(dataOut.heightList) |
|
|
1230 | 1232 | |
|
|
1231 | 1233 | for plot in self.plottypes: |
|
|
1232 | 1234 | if plot in ('spc', 'spc_moments', 'spc_cut'): |
|
|
1233 | 1235 | z = dataOut.data_spc/dataOut.normFactor |
|
|
1234 | 1236 | buffer = 10*numpy.log10(z) |
|
|
1235 | 1237 | if plot == 'cspc': |
|
|
1236 | 1238 | buffer = (dataOut.data_spc, dataOut.data_cspc) |
|
|
1237 | 1239 | if plot == 'noise': |
|
|
1238 | 1240 | buffer = 10*numpy.log10(dataOut.getNoise()/dataOut.normFactor) |
|
|
1239 | 1241 | if plot in ('rti', 'spcprofile'): |
|
|
1240 | 1242 | buffer = dataOut.getPower() |
|
|
1241 | 1243 | if plot == 'snr_db': |
|
|
1242 | 1244 | buffer = dataOut.data_SNR |
|
|
1243 | 1245 | if plot == 'snr': |
|
|
1244 | 1246 | buffer = 10*numpy.log10(dataOut.data_SNR) |
|
|
1245 | 1247 | if plot == 'dop': |
|
|
1246 | 1248 | buffer = dataOut.data_DOP |
|
|
1247 | 1249 | if plot == 'pow': |
|
|
1248 | 1250 | buffer = 10*numpy.log10(dataOut.data_POW) |
|
|
1249 | 1251 | if plot == 'width': |
|
|
1250 | 1252 | buffer = dataOut.data_WIDTH |
|
|
1251 | 1253 | if plot == 'coh': |
|
|
1252 | 1254 | buffer = dataOut.getCoherence() |
|
|
1253 | 1255 | if plot == 'phase': |
|
|
1254 | 1256 | buffer = dataOut.getCoherence(phase=True) |
|
|
1255 | 1257 | if plot == 'output': |
|
|
1256 | 1258 | buffer = dataOut.data_output |
|
|
1257 | 1259 | if plot == 'param': |
|
|
1258 | 1260 | buffer = dataOut.data_param |
|
|
1259 | 1261 | if plot == 'scope': |
|
|
1260 | 1262 | buffer = dataOut.data |
|
|
1261 | 1263 | self.flagDataAsBlock = dataOut.flagDataAsBlock |
|
|
1262 | 1264 | self.nProfiles = dataOut.nProfiles |
|
|
1263 | 1265 | if plot == 'pp_power': |
|
|
1264 |
buffer = dataOut.data |
|
|
|
1266 | buffer = dataOut.dataPP_POWER | |
|
|
1267 | self.flagDataAsBlock = dataOut.flagDataAsBlock | |
|
|
1268 | self.nProfiles = dataOut.nProfiles | |
|
|
1269 | if plot == 'pp_signal': | |
|
|
1270 | buffer = dataOut.dataPP_POW | |
|
|
1265 | 1271 | self.flagDataAsBlock = dataOut.flagDataAsBlock |
|
|
1266 | 1272 | self.nProfiles = dataOut.nProfiles |
|
|
1267 | 1273 | if plot == 'pp_velocity': |
|
|
1268 |
buffer = dataOut.data |
|
|
|
1274 | buffer = dataOut.dataPP_DOP | |
|
|
1269 | 1275 | self.flagDataAsBlock = dataOut.flagDataAsBlock |
|
|
1270 | 1276 | self.nProfiles = dataOut.nProfiles |
|
|
1271 | 1277 | if plot == 'pp_specwidth': |
|
|
1272 |
buffer = dataOut.data |
|
|
|
1278 | buffer = dataOut.dataPP_WIDTH | |
|
|
1273 | 1279 | self.flagDataAsBlock = dataOut.flagDataAsBlock |
|
|
1274 | 1280 | self.nProfiles = dataOut.nProfiles |
|
|
1275 | 1281 | |
|
|
1276 | 1282 | if plot == 'spc': |
|
|
1277 | 1283 | self.data['spc'][tm] = buffer |
|
|
1278 | 1284 | elif plot == 'cspc': |
|
|
1279 | 1285 | self.data['cspc'][tm] = buffer |
|
|
1280 | 1286 | elif plot == 'spc_moments': |
|
|
1281 | 1287 | self.data['spc'][tm] = buffer |
|
|
1282 | 1288 | self.data['moments'][tm] = dataOut.moments |
|
|
1283 | 1289 | else: |
|
|
1284 | 1290 | if self.buffering: |
|
|
1285 | 1291 | self.data[plot][tm] = buffer |
|
|
1286 | 1292 | else: |
|
|
1287 | 1293 | self.data[plot][tm] = buffer |
|
|
1288 | 1294 | |
|
|
1289 | 1295 | if dataOut.channelList is None: |
|
|
1290 | 1296 | self.channels = range(buffer.shape[0]) |
|
|
1291 | 1297 | else: |
|
|
1292 | 1298 | self.channels = dataOut.channelList |
|
|
1293 | 1299 | |
|
|
1294 | 1300 | if buffer is None: |
|
|
1295 | 1301 | self.flagNoData = True |
|
|
1296 | 1302 | raise schainpy.admin.SchainWarning('Attribute data_{} is empty'.format(self.key)) |
|
|
1297 | 1303 | |
|
|
1298 | 1304 | def normalize_heights(self): |
|
|
1299 | 1305 | ''' |
|
|
1300 | 1306 | Ensure same-dimension of the data for different heighList |
|
|
1301 | 1307 | ''' |
|
|
1302 | 1308 | |
|
|
1303 | 1309 | H = numpy.array(list(self.__all_heights)) |
|
|
1304 | 1310 | H.sort() |
|
|
1305 | 1311 | for key in self.data: |
|
|
1306 | 1312 | shape = self.shape(key)[:-1] + H.shape |
|
|
1307 | 1313 | for tm, obj in list(self.data[key].items()): |
|
|
1308 | 1314 | h = self.__heights[self.times.tolist().index(tm)] |
|
|
1309 | 1315 | if H.size == h.size: |
|
|
1310 | 1316 | continue |
|
|
1311 | 1317 | index = numpy.where(numpy.in1d(H, h))[0] |
|
|
1312 | 1318 | dummy = numpy.zeros(shape) + numpy.nan |
|
|
1313 | 1319 | if len(shape) == 2: |
|
|
1314 | 1320 | dummy[:, index] = obj |
|
|
1315 | 1321 | else: |
|
|
1316 | 1322 | dummy[index] = obj |
|
|
1317 | 1323 | self.data[key][tm] = dummy |
|
|
1318 | 1324 | |
|
|
1319 | 1325 | self.__heights = [H for tm in self.times] |
|
|
1320 | 1326 | |
|
|
1321 | 1327 | def jsonify(self, tm, plot_name, plot_type, decimate=False): |
|
|
1322 | 1328 | ''' |
|
|
1323 | 1329 | Convert data to json |
|
|
1324 | 1330 | ''' |
|
|
1325 | 1331 | |
|
|
1326 | 1332 | dy = int(self.heights.size/self.MAXNUMY) + 1 |
|
|
1327 | 1333 | if self.key in ('spc', 'cspc'): |
|
|
1328 | 1334 | dx = int(self.data[self.key][tm].shape[1]/self.MAXNUMX) + 1 |
|
|
1329 | 1335 | data = self.roundFloats( |
|
|
1330 | 1336 | self.data[self.key][tm][::, ::dx, ::dy].tolist()) |
|
|
1331 | 1337 | else: |
|
|
1332 | 1338 | if self.key is 'noise': |
|
|
1333 | 1339 | data = [[x] for x in self.roundFloats(self.data[self.key][tm].tolist())] |
|
|
1334 | 1340 | else: |
|
|
1335 | 1341 | data = self.roundFloats(self.data[self.key][tm][::, ::dy].tolist()) |
|
|
1336 | 1342 | |
|
|
1337 | 1343 | meta = {} |
|
|
1338 | 1344 | ret = { |
|
|
1339 | 1345 | 'plot': plot_name, |
|
|
1340 | 1346 | 'code': self.exp_code, |
|
|
1341 | 1347 | 'time': float(tm), |
|
|
1342 | 1348 | 'data': data, |
|
|
1343 | 1349 | } |
|
|
1344 | 1350 | meta['type'] = plot_type |
|
|
1345 | 1351 | meta['interval'] = float(self.interval) |
|
|
1346 | 1352 | meta['localtime'] = self.localtime |
|
|
1347 | 1353 | meta['yrange'] = self.roundFloats(self.heights[::dy].tolist()) |
|
|
1348 | 1354 | if 'spc' in self.data or 'cspc' in self.data: |
|
|
1349 | 1355 | meta['xrange'] = self.roundFloats(self.xrange[2][::dx].tolist()) |
|
|
1350 | 1356 | else: |
|
|
1351 | 1357 | meta['xrange'] = [] |
|
|
1352 | 1358 | |
|
|
1353 | 1359 | meta.update(self.meta) |
|
|
1354 | 1360 | ret['metadata'] = meta |
|
|
1355 | 1361 | return json.dumps(ret) |
|
|
1356 | 1362 | |
|
|
1357 | 1363 | @property |
|
|
1358 | 1364 | def times(self): |
|
|
1359 | 1365 | ''' |
|
|
1360 | 1366 | Return the list of times of the current data |
|
|
1361 | 1367 | ''' |
|
|
1362 | 1368 | |
|
|
1363 | 1369 | ret = numpy.array([*self.data[self.key]]) |
|
|
1364 | 1370 | if self: |
|
|
1365 | 1371 | ret.sort() |
|
|
1366 | 1372 | return ret |
|
|
1367 | 1373 | |
|
|
1368 | 1374 | @property |
|
|
1369 | 1375 | def min_time(self): |
|
|
1370 | 1376 | ''' |
|
|
1371 | 1377 | Return the minimun time value |
|
|
1372 | 1378 | ''' |
|
|
1373 | 1379 | |
|
|
1374 | 1380 | return self.times[0] |
|
|
1375 | 1381 | |
|
|
1376 | 1382 | @property |
|
|
1377 | 1383 | def max_time(self): |
|
|
1378 | 1384 | ''' |
|
|
1379 | 1385 | Return the maximun time value |
|
|
1380 | 1386 | ''' |
|
|
1381 | 1387 | |
|
|
1382 | 1388 | return self.times[-1] |
|
|
1383 | 1389 | |
|
|
1384 | 1390 | @property |
|
|
1385 | 1391 | def heights(self): |
|
|
1386 | 1392 | ''' |
|
|
1387 | 1393 | Return the list of heights of the current data |
|
|
1388 | 1394 | ''' |
|
|
1389 | 1395 | |
|
|
1390 | 1396 | return numpy.array(self.__heights[-1]) |
|
|
1391 | 1397 | |
|
|
1392 | 1398 | @staticmethod |
|
|
1393 | 1399 | def roundFloats(obj): |
|
|
1394 | 1400 | if isinstance(obj, list): |
|
|
1395 | 1401 | return list(map(PlotterData.roundFloats, obj)) |
|
|
1396 | 1402 | elif isinstance(obj, float): |
|
|
1397 | 1403 | return round(obj, 2) |
| @@ -1,276 +1,302 | |||
|
|
1 | 1 | ''' |
|
|
2 | 2 | Created on Jul 9, 2014 |
|
|
3 | 3 | |
|
|
4 | 4 | @author: roj-idl71 |
|
|
5 | 5 | ''' |
|
|
6 | 6 | import os |
|
|
7 | 7 | import datetime |
|
|
8 | 8 | import numpy |
|
|
9 | 9 | |
|
|
10 | 10 | from schainpy.model.graphics.jroplot_base import Plot, plt |
|
|
11 | 11 | |
|
|
12 | 12 | |
|
|
13 | 13 | class ScopePlot(Plot): |
|
|
14 | 14 | |
|
|
15 | 15 | ''' |
|
|
16 | 16 | Plot for Scope |
|
|
17 | 17 | ''' |
|
|
18 | 18 | |
|
|
19 | 19 | CODE = 'scope' |
|
|
20 | 20 | plot_name = 'Scope' |
|
|
21 | 21 | plot_type = 'scatter' |
|
|
22 | 22 | |
|
|
23 | 23 | def setup(self): |
|
|
24 | 24 | |
|
|
25 | 25 | self.xaxis = 'Range (Km)' |
|
|
26 | 26 | self.ncols = 1 |
|
|
27 | 27 | self.nrows = 1 |
|
|
28 | 28 | self.nplots = 1 |
|
|
29 | 29 | self.ylabel = 'Intensity [dB]' |
|
|
30 | 30 | self.titles = ['Scope'] |
|
|
31 | 31 | self.colorbar = False |
|
|
32 | 32 | self.width = 6 |
|
|
33 | 33 | self.height = 4 |
|
|
34 | 34 | |
|
|
35 | 35 | def plot_iq(self, x, y, channelIndexList, thisDatetime, wintitle): |
|
|
36 | 36 | |
|
|
37 | 37 | yreal = y[channelIndexList,:].real |
|
|
38 | 38 | yimag = y[channelIndexList,:].imag |
|
|
39 | 39 | title = wintitle + " Scope: %s" %(thisDatetime.strftime("%d-%b-%Y")) |
|
|
40 | 40 | self.xlabel = "Range (Km)" |
|
|
41 | 41 | self.ylabel = "Intensity - IQ" |
|
|
42 | 42 | |
|
|
43 | 43 | self.y = yreal |
|
|
44 | 44 | self.x = x |
|
|
45 | 45 | self.xmin = min(x) |
|
|
46 | 46 | self.xmax = max(x) |
|
|
47 | 47 | |
|
|
48 | 48 | |
|
|
49 | 49 | self.titles[0] = title |
|
|
50 | 50 | |
|
|
51 | 51 | for i,ax in enumerate(self.axes): |
|
|
52 | 52 | title = "Channel %d" %(i) |
|
|
53 | 53 | if ax.firsttime: |
|
|
54 | 54 | ax.plt_r = ax.plot(x, yreal[i,:], color='b')[0] |
|
|
55 | 55 | ax.plt_i = ax.plot(x, yimag[i,:], color='r')[0] |
|
|
56 | 56 | else: |
|
|
57 | 57 | ax.plt_r.set_data(x, yreal[i,:]) |
|
|
58 | 58 | ax.plt_i.set_data(x, yimag[i,:]) |
|
|
59 | 59 | |
|
|
60 | 60 | def plot_power(self, x, y, channelIndexList, thisDatetime, wintitle): |
|
|
61 | 61 | y = y[channelIndexList,:] * numpy.conjugate(y[channelIndexList,:]) |
|
|
62 | 62 | yreal = y.real |
|
|
63 | 63 | yreal = 10*numpy.log10(yreal) |
|
|
64 | 64 | self.y = yreal |
|
|
65 | 65 | title = wintitle + " Scope: %s" %(thisDatetime.strftime("%d-%b-%Y")) |
|
|
66 | 66 | self.xlabel = "Range (Km)" |
|
|
67 | 67 | self.ylabel = "Intensity" |
|
|
68 | 68 | self.xmin = min(x) |
|
|
69 | 69 | self.xmax = max(x) |
|
|
70 | 70 | |
|
|
71 | 71 | |
|
|
72 | 72 | self.titles[0] = title |
|
|
73 | 73 | |
|
|
74 | 74 | for i,ax in enumerate(self.axes): |
|
|
75 | 75 | title = "Channel %d" %(i) |
|
|
76 | 76 | |
|
|
77 | 77 | ychannel = yreal[i,:] |
|
|
78 | 78 | |
|
|
79 | 79 | if ax.firsttime: |
|
|
80 | 80 | ax.plt_r = ax.plot(x, ychannel)[0] |
|
|
81 | 81 | else: |
|
|
82 | 82 | #pass |
|
|
83 | 83 | ax.plt_r.set_data(x, ychannel) |
|
|
84 | 84 | |
|
|
85 | 85 | def plot_weatherpower(self, x, y, channelIndexList, thisDatetime, wintitle): |
|
|
86 | 86 | |
|
|
87 | 87 | |
|
|
88 | 88 | y = y[channelIndexList,:] |
|
|
89 | 89 | yreal = y.real |
|
|
90 | 90 | yreal = 10*numpy.log10(yreal) |
|
|
91 | 91 | self.y = yreal |
|
|
92 | 92 | title = wintitle + " Scope: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) |
|
|
93 | 93 | self.xlabel = "Range (Km)" |
|
|
94 | 94 | self.ylabel = "Intensity" |
|
|
95 | 95 | self.xmin = min(x) |
|
|
96 | 96 | self.xmax = max(x) |
|
|
97 | 97 | |
|
|
98 | 98 | self.titles[0] =title |
|
|
99 | 99 | for i,ax in enumerate(self.axes): |
|
|
100 | 100 | title = "Channel %d" %(i) |
|
|
101 | 101 | |
|
|
102 | 102 | ychannel = yreal[i,:] |
|
|
103 | 103 | |
|
|
104 | 104 | if ax.firsttime: |
|
|
105 | 105 | ax.plt_r = ax.plot(x, ychannel)[0] |
|
|
106 | 106 | else: |
|
|
107 | 107 | #pass |
|
|
108 | 108 | ax.plt_r.set_data(x, ychannel) |
|
|
109 | 109 | |
|
|
110 | 110 | def plot_weathervelocity(self, x, y, channelIndexList, thisDatetime, wintitle): |
|
|
111 | 111 | |
|
|
112 | 112 | x = x[channelIndexList,:] |
|
|
113 | 113 | yreal = y |
|
|
114 | 114 | self.y = yreal |
|
|
115 | 115 | title = wintitle + " Scope: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) |
|
|
116 | 116 | self.xlabel = "Velocity (m/s)" |
|
|
117 | 117 | self.ylabel = "Range (Km)" |
|
|
118 | 118 | self.xmin = numpy.min(x) |
|
|
119 | 119 | self.xmax = numpy.max(x) |
|
|
120 | 120 | self.titles[0] =title |
|
|
121 | 121 | for i,ax in enumerate(self.axes): |
|
|
122 | 122 | title = "Channel %d" %(i) |
|
|
123 | 123 | xchannel = x[i,:] |
|
|
124 | 124 | if ax.firsttime: |
|
|
125 | 125 | ax.plt_r = ax.plot(xchannel, yreal)[0] |
|
|
126 | 126 | else: |
|
|
127 | 127 | #pass |
|
|
128 | 128 | ax.plt_r.set_data(xchannel, yreal) |
|
|
129 | 129 | |
|
|
130 | 130 | def plot_weatherspecwidth(self, x, y, channelIndexList, thisDatetime, wintitle): |
|
|
131 | 131 | |
|
|
132 | 132 | x = x[channelIndexList,:] |
|
|
133 | 133 | yreal = y |
|
|
134 | 134 | self.y = yreal |
|
|
135 | 135 | title = wintitle + " Scope: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) |
|
|
136 | 136 | self.xlabel = "width " |
|
|
137 | 137 | self.ylabel = "Range (Km)" |
|
|
138 | 138 | self.xmin = numpy.min(x) |
|
|
139 | 139 | self.xmax = numpy.max(x) |
|
|
140 | 140 | self.titles[0] =title |
|
|
141 | 141 | for i,ax in enumerate(self.axes): |
|
|
142 | 142 | title = "Channel %d" %(i) |
|
|
143 | 143 | xchannel = x[i,:] |
|
|
144 | 144 | if ax.firsttime: |
|
|
145 | 145 | ax.plt_r = ax.plot(xchannel, yreal)[0] |
|
|
146 | 146 | else: |
|
|
147 | 147 | #pass |
|
|
148 | 148 | ax.plt_r.set_data(xchannel, yreal) |
|
|
149 | 149 | |
|
|
150 | 150 | def plot(self): |
|
|
151 | 151 | if self.channels: |
|
|
152 | 152 | channels = self.channels |
|
|
153 | 153 | else: |
|
|
154 | 154 | channels = self.data.channels |
|
|
155 | 155 | |
|
|
156 | 156 | thisDatetime = datetime.datetime.utcfromtimestamp(self.data.times[-1]) |
|
|
157 | 157 | if self.CODE == "pp_power": |
|
|
158 | 158 | scope = self.data['pp_power'] |
|
|
159 | elif self.CODE == "pp_signal": | |
|
|
160 | scope = self.data["pp_signal"] | |
|
|
159 | 161 | elif self.CODE == "pp_velocity": |
|
|
160 | 162 | scope = self.data["pp_velocity"] |
|
|
161 | 163 | elif self.CODE == "pp_specwidth": |
|
|
162 | 164 | scope = self.data["pp_specwidth"] |
|
|
163 | 165 | else: |
|
|
164 | 166 | scope =self.data["scope"] |
|
|
165 | 167 | |
|
|
166 | 168 | if self.data.flagDataAsBlock: |
|
|
167 | 169 | |
|
|
168 | 170 | for i in range(self.data.nProfiles): |
|
|
169 | 171 | |
|
|
170 | 172 | wintitle1 = " [Profile = %d] " %i |
|
|
171 | 173 | if self.CODE =="scope": |
|
|
172 | 174 | if self.type == "power": |
|
|
173 | 175 | self.plot_power(self.data.heights, |
|
|
174 | 176 | scope[:,i,:], |
|
|
175 | 177 | channels, |
|
|
176 | 178 | thisDatetime, |
|
|
177 | 179 | wintitle1 |
|
|
178 | 180 | ) |
|
|
179 | 181 | |
|
|
180 | 182 | if self.type == "iq": |
|
|
181 | 183 | self.plot_iq(self.data.heights, |
|
|
182 | 184 | scope[:,i,:], |
|
|
183 | 185 | channels, |
|
|
184 | 186 | thisDatetime, |
|
|
185 | 187 | wintitle1 |
|
|
186 | 188 | ) |
|
|
187 | 189 | if self.CODE=="pp_power": |
|
|
188 | 190 | self.plot_weatherpower(self.data.heights, |
|
|
189 | 191 | scope[:,i,:], |
|
|
190 | 192 | channels, |
|
|
191 | 193 | thisDatetime, |
|
|
192 | 194 | wintitle |
|
|
193 | 195 | ) |
|
|
196 | if self.CODE=="pp_signal": | |
|
|
197 | self.plot_weatherpower(self.data.heights, | |
|
|
198 | scope[:,i,:], | |
|
|
199 | channels, | |
|
|
200 | thisDatetime, | |
|
|
201 | wintitle | |
|
|
202 | ) | |
|
|
194 | 203 | if self.CODE=="pp_velocity": |
|
|
195 | 204 | self.plot_weathervelocity(scope[:,i,:], |
|
|
196 | 205 | self.data.heights, |
|
|
197 | 206 | channels, |
|
|
198 | 207 | thisDatetime, |
|
|
199 | 208 | wintitle |
|
|
200 | 209 | ) |
|
|
201 | 210 | if self.CODE=="pp_spcwidth": |
|
|
202 | 211 | self.plot_weatherspecwidth(scope[:,i,:], |
|
|
203 | 212 | self.data.heights, |
|
|
204 | 213 | channels, |
|
|
205 | 214 | thisDatetime, |
|
|
206 | 215 | wintitle |
|
|
207 | 216 | ) |
|
|
208 | 217 | else: |
|
|
209 | 218 | wintitle = " [Profile = %d] " %self.data.profileIndex |
|
|
210 | 219 | if self.CODE== "scope": |
|
|
211 | 220 | if self.type == "power": |
|
|
212 | 221 | self.plot_power(self.data.heights, |
|
|
213 | 222 | scope, |
|
|
214 | 223 | channels, |
|
|
215 | 224 | thisDatetime, |
|
|
216 | 225 | wintitle |
|
|
217 | 226 | ) |
|
|
218 | 227 | |
|
|
219 | 228 | if self.type == "iq": |
|
|
220 | 229 | self.plot_iq(self.data.heights, |
|
|
221 | 230 | scope, |
|
|
222 | 231 | channels, |
|
|
223 | 232 | thisDatetime, |
|
|
224 | 233 | wintitle |
|
|
225 | 234 | ) |
|
|
226 | 235 | if self.CODE=="pp_power": |
|
|
227 | 236 | self.plot_weatherpower(self.data.heights, |
|
|
228 | 237 | scope, |
|
|
229 | 238 | channels, |
|
|
230 | 239 | thisDatetime, |
|
|
231 | 240 | wintitle |
|
|
232 | 241 | ) |
|
|
242 | if self.CODE=="pp_signal": | |
|
|
243 | self.plot_weatherpower(self.data.heights, | |
|
|
244 | scope, | |
|
|
245 | channels, | |
|
|
246 | thisDatetime, | |
|
|
247 | wintitle | |
|
|
248 | ) | |
|
|
233 | 249 | if self.CODE=="pp_velocity": |
|
|
234 | 250 | self.plot_weathervelocity(scope, |
|
|
235 | 251 | self.data.heights, |
|
|
236 | 252 | channels, |
|
|
237 | 253 | thisDatetime, |
|
|
238 | 254 | wintitle |
|
|
239 | 255 | ) |
|
|
240 | 256 | if self.CODE=="pp_specwidth": |
|
|
241 | 257 | self.plot_weatherspecwidth(scope, |
|
|
242 | 258 | self.data.heights, |
|
|
243 | 259 | channels, |
|
|
244 | 260 | thisDatetime, |
|
|
245 | 261 | wintitle |
|
|
246 | 262 | ) |
|
|
247 | 263 | |
|
|
248 | 264 | |
|
|
249 | 265 | |
|
|
250 | 266 | class PulsepairPowerPlot(ScopePlot): |
|
|
251 | 267 | ''' |
|
|
252 | Plot for | |
|
|
268 | Plot for P= S+N | |
|
|
253 | 269 | ''' |
|
|
254 | 270 | |
|
|
255 | 271 | CODE = 'pp_power' |
|
|
256 | 272 | plot_name = 'PulsepairPower' |
|
|
257 | 273 | plot_type = 'scatter' |
|
|
258 | 274 | buffering = False |
|
|
259 | 275 | |
|
|
260 | 276 | class PulsepairVelocityPlot(ScopePlot): |
|
|
261 | 277 | ''' |
|
|
262 | Plot for | |
|
|
278 | Plot for VELOCITY | |
|
|
263 | 279 | ''' |
|
|
264 | 280 | CODE = 'pp_velocity' |
|
|
265 | 281 | plot_name = 'PulsepairVelocity' |
|
|
266 | 282 | plot_type = 'scatter' |
|
|
267 | 283 | buffering = False |
|
|
268 | 284 | |
|
|
269 | 285 | class PulsepairSpecwidthPlot(ScopePlot): |
|
|
270 | 286 | ''' |
|
|
271 | Plot for | |
|
|
287 | Plot for WIDTH | |
|
|
272 | 288 | ''' |
|
|
273 | 289 | CODE = 'pp_specwidth' |
|
|
274 | 290 | plot_name = 'PulsepairSpecwidth' |
|
|
275 | 291 | plot_type = 'scatter' |
|
|
276 | 292 | buffering = False |
|
|
293 | ||
|
|
294 | class PulsepairSignalPlot(ScopePlot): | |
|
|
295 | ''' | |
|
|
296 | Plot for S | |
|
|
297 | ''' | |
|
|
298 | ||
|
|
299 | CODE = 'pp_signal' | |
|
|
300 | plot_name = 'PulsepairSignal' | |
|
|
301 | plot_type = 'scatter' | |
|
|
302 | buffering = False | |
| @@ -1,512 +1,519 | |||
|
|
1 | 1 | import numpy,math,random,time |
|
|
2 | 2 | #---------------1 Heredamos JRODatareader |
|
|
3 | 3 | from schainpy.model.io.jroIO_base import * |
|
|
4 | 4 | #---------------2 Heredamos las propiedades de ProcessingUnit |
|
|
5 | 5 | from schainpy.model.proc.jroproc_base import ProcessingUnit,Operation,MPDecorator |
|
|
6 | 6 | #---------------3 Importaremos las clases BascicHeader, SystemHeader, RadarControlHeader, ProcessingHeader |
|
|
7 | 7 | from schainpy.model.data.jroheaderIO import PROCFLAG, BasicHeader,SystemHeader,RadarControllerHeader, ProcessingHeader |
|
|
8 | 8 | #---------------4 Importaremos el objeto Voltge |
|
|
9 | 9 | from schainpy.model.data.jrodata import Voltage |
|
|
10 | 10 | |
|
|
11 | 11 | class SimulatorReader(JRODataReader, ProcessingUnit): |
|
|
12 | 12 | incIntFactor = 1 |
|
|
13 | 13 | nFFTPoints = 0 |
|
|
14 | 14 | FixPP_IncInt = 1 |
|
|
15 | 15 | FixRCP_IPP = 1000 |
|
|
16 | 16 | FixPP_CohInt = 1 |
|
|
17 | 17 | Tau_0 = 250 |
|
|
18 | 18 | AcqH0_0 = 70 |
|
|
19 | 19 | H0 = AcqH0_0 |
|
|
20 | 20 | AcqDH_0 = 1.25 |
|
|
21 | 21 | DH0 = AcqDH_0 |
|
|
22 | 22 | Bauds = 32 |
|
|
23 | 23 | BaudWidth = None |
|
|
24 | 24 | FixRCP_TXA = 40 |
|
|
25 | 25 | FixRCP_TXB = 70 |
|
|
26 | 26 | fAngle = 2.0*math.pi*(1/16) |
|
|
27 | 27 | DC_level = 500 |
|
|
28 | 28 | stdev = 8 |
|
|
29 | 29 | Num_Codes = 2 |
|
|
30 | 30 | #code0 = numpy.array([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]) |
|
|
31 | 31 | #code1 = numpy.array([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]) |
|
|
32 | 32 | #Dyn_snCode = numpy.array([Num_Codes,Bauds]) |
|
|
33 | 33 | Dyn_snCode = None |
|
|
34 | 34 | Samples = 200 |
|
|
35 | 35 | channels = 2 |
|
|
36 | 36 | pulses = None |
|
|
37 | 37 | Reference = None |
|
|
38 | 38 | pulse_size = None |
|
|
39 | 39 | prof_gen = None |
|
|
40 | 40 | Fdoppler = 100 |
|
|
41 | 41 | Hdoppler = 36 |
|
|
42 | 42 | Adoppler = 300 |
|
|
43 | 43 | frequency = 9345 |
|
|
44 | 44 | nTotalReadFiles = 1000 |
|
|
45 | 45 | |
|
|
46 | 46 | def __init__(self): |
|
|
47 | 47 | """ |
|
|
48 | 48 | Inicializador de la clases SimulatorReader para |
|
|
49 | 49 | generar datos de voltage simulados. |
|
|
50 | 50 | Input: |
|
|
51 | 51 | dataOut: Objeto de la clase Voltage. |
|
|
52 | 52 | Este Objeto sera utilizado apra almacenar |
|
|
53 | 53 | un perfil de datos cada vez qe se haga |
|
|
54 | 54 | un requerimiento (getData) |
|
|
55 | 55 | """ |
|
|
56 | 56 | ProcessingUnit.__init__(self) |
|
|
57 | 57 | print(" [ START ] init - Metodo Simulator Reader") |
|
|
58 | 58 | |
|
|
59 | 59 | self.isConfig = False |
|
|
60 | 60 | self.basicHeaderObj = BasicHeader(LOCALTIME) |
|
|
61 | 61 | self.systemHeaderObj = SystemHeader() |
|
|
62 | 62 | self.radarControllerHeaderObj = RadarControllerHeader() |
|
|
63 | 63 | self.processingHeaderObj = ProcessingHeader() |
|
|
64 | 64 | self.profileIndex = 2**32-1 |
|
|
65 | 65 | self.dataOut = Voltage() |
|
|
66 | 66 | #code0 = numpy.array([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]) |
|
|
67 | 67 | code0 = numpy.array([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,-1,1,1,1,-1,1]) |
|
|
68 | 68 | #code1 = numpy.array([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]) |
|
|
69 | 69 | code1 = numpy.array([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,-1,-1,1,-1]) |
|
|
70 | 70 | #self.Dyn_snCode = numpy.array([code0,code1]) |
|
|
71 | 71 | self.Dyn_snCode = None |
|
|
72 | 72 | |
|
|
73 | 73 | def set_kwargs(self, **kwargs): |
|
|
74 | 74 | for key, value in kwargs.items(): |
|
|
75 | 75 | setattr(self, key, value) |
|
|
76 | 76 | |
|
|
77 | 77 | def __hasNotDataInBuffer(self): |
|
|
78 | 78 | |
|
|
79 | 79 | if self.profileIndex >= self.processingHeaderObj.profilesPerBlock* self.nTxs: |
|
|
80 | 80 | if self.nReadBlocks>0: |
|
|
81 | 81 | tmp = self.dataOut.utctime |
|
|
82 | 82 | tmp_utc = int(self.dataOut.utctime) |
|
|
83 | 83 | tmp_milisecond = int((tmp-tmp_utc)*1000) |
|
|
84 | 84 | self.basicHeaderObj.utc = tmp_utc |
|
|
85 | 85 | self.basicHeaderObj.miliSecond= tmp_milisecond |
|
|
86 | 86 | return 1 |
|
|
87 | 87 | return 0 |
|
|
88 | 88 | |
|
|
89 | 89 | def setNextFile(self): |
|
|
90 | 90 | """Set the next file to be readed open it and parse de file header""" |
|
|
91 | 91 | |
|
|
92 | 92 | if (self.nReadBlocks >= self.processingHeaderObj.dataBlocksPerFile): |
|
|
93 | 93 | self.nReadFiles=self.nReadFiles+1 |
|
|
94 | 94 | if self.nReadFiles > self.nTotalReadFiles: |
|
|
95 | 95 | self.flagNoMoreFiles=1 |
|
|
96 | 96 | raise schainpy.admin.SchainWarning('No more files to read') |
|
|
97 | 97 | |
|
|
98 | 98 | print('------------------- [Opening file] ------------------------------',self.nReadFiles) |
|
|
99 | 99 | self.nReadBlocks = 0 |
|
|
100 | 100 | #if self.nReadBlocks==0: |
|
|
101 | 101 | # self.readFirstHeader() |
|
|
102 | 102 | |
|
|
103 | 103 | def __setNewBlock(self): |
|
|
104 | 104 | self.setNextFile() |
|
|
105 | 105 | if self.flagIsNewFile: |
|
|
106 | 106 | return 1 |
|
|
107 | 107 | |
|
|
108 | 108 | def readNextBlock(self): |
|
|
109 | 109 | while True: |
|
|
110 | 110 | self.__setNewBlock() |
|
|
111 | 111 | if not(self.readBlock()): |
|
|
112 | 112 | return 0 |
|
|
113 | 113 | self.getBasicHeader() |
|
|
114 | 114 | break |
|
|
115 | 115 | if self.verbose: |
|
|
116 | 116 | print("[Reading] Block No. %d/%d -> %s" %(self.nReadBlocks, |
|
|
117 | 117 | self.processingHeaderObj.dataBlocksPerFile, |
|
|
118 | 118 | self.dataOut.datatime.ctime()) ) |
|
|
119 | 119 | return 1 |
|
|
120 | 120 | |
|
|
121 | 121 | def getFirstHeader(self): |
|
|
122 | 122 | self.getBasicHeader() |
|
|
123 | 123 | self.dataOut.processingHeaderObj = self.processingHeaderObj.copy() |
|
|
124 | 124 | self.dataOut.systemHeaderObj = self.systemHeaderObj.copy() |
|
|
125 | 125 | self.dataOut.radarControllerHeaderObj = self.radarControllerHeaderObj.copy() |
|
|
126 | 126 | self.dataOut.dtype = self.dtype |
|
|
127 | 127 | |
|
|
128 | 128 | self.dataOut.nProfiles = self.processingHeaderObj.profilesPerBlock |
|
|
129 | 129 | self.dataOut.heightList = numpy.arange(self.processingHeaderObj.nHeights) * self.processingHeaderObj.deltaHeight + self.processingHeaderObj.firstHeight |
|
|
130 | 130 | self.dataOut.channelList = list(range(self.systemHeaderObj.nChannels)) |
|
|
131 | 131 | self.dataOut.nCohInt = self.processingHeaderObj.nCohInt |
|
|
132 | 132 | # asumo q la data no esta decodificada |
|
|
133 | 133 | self.dataOut.flagDecodeData = self.processingHeaderObj.flag_decode |
|
|
134 | 134 | # asumo q la data no esta sin flip |
|
|
135 | 135 | self.dataOut.flagDeflipData = self.processingHeaderObj.flag_deflip |
|
|
136 | 136 | self.dataOut.flagShiftFFT = self.processingHeaderObj.shif_fft |
|
|
137 | 137 | self.dataOut.frequency = self.frequency |
|
|
138 | 138 | |
|
|
139 | 139 | def getBasicHeader(self): |
|
|
140 | 140 | self.dataOut.utctime = self.basicHeaderObj.utc + self.basicHeaderObj.miliSecond / \ |
|
|
141 | 141 | 1000. + self.profileIndex * self.radarControllerHeaderObj.ippSeconds |
|
|
142 | 142 | |
|
|
143 | 143 | self.dataOut.flagDiscontinuousBlock = self.flagDiscontinuousBlock |
|
|
144 | 144 | self.dataOut.timeZone = self.basicHeaderObj.timeZone |
|
|
145 | 145 | self.dataOut.dstFlag = self.basicHeaderObj.dstFlag |
|
|
146 | 146 | self.dataOut.errorCount = self.basicHeaderObj.errorCount |
|
|
147 | 147 | self.dataOut.useLocalTime = self.basicHeaderObj.useLocalTime |
|
|
148 | 148 | self.dataOut.ippSeconds = self.radarControllerHeaderObj.ippSeconds / self.nTxs |
|
|
149 | 149 | |
|
|
150 | 150 | def readFirstHeader(self): |
|
|
151 | 151 | |
|
|
152 | 152 | datatype = int(numpy.log2((self.processingHeaderObj.processFlags & |
|
|
153 | 153 | PROCFLAG.DATATYPE_MASK)) - numpy.log2(PROCFLAG.DATATYPE_CHAR)) |
|
|
154 | 154 | if datatype == 0: |
|
|
155 | 155 | datatype_str = numpy.dtype([('real', '<i1'), ('imag', '<i1')]) |
|
|
156 | 156 | elif datatype == 1: |
|
|
157 | 157 | datatype_str = numpy.dtype([('real', '<i2'), ('imag', '<i2')]) |
|
|
158 | 158 | elif datatype == 2: |
|
|
159 | 159 | datatype_str = numpy.dtype([('real', '<i4'), ('imag', '<i4')]) |
|
|
160 | 160 | elif datatype == 3: |
|
|
161 | 161 | datatype_str = numpy.dtype([('real', '<i8'), ('imag', '<i8')]) |
|
|
162 | 162 | elif datatype == 4: |
|
|
163 | 163 | datatype_str = numpy.dtype([('real', '<f4'), ('imag', '<f4')]) |
|
|
164 | 164 | elif datatype == 5: |
|
|
165 | 165 | datatype_str = numpy.dtype([('real', '<f8'), ('imag', '<f8')]) |
|
|
166 | 166 | else: |
|
|
167 | 167 | raise ValueError('Data type was not defined') |
|
|
168 | 168 | |
|
|
169 | 169 | self.dtype = datatype_str |
|
|
170 | 170 | |
|
|
171 | 171 | |
|
|
172 | 172 | def set_RCH(self, expType=2, nTx=1,ipp=None, txA=0, txB=0, |
|
|
173 | 173 | nWindows=None, nHeights=None, firstHeight=None, deltaHeight=None, |
|
|
174 | 174 | numTaus=0, line6Function=0, line5Function=0, fClock=None, |
|
|
175 | 175 | prePulseBefore=0, prePulseAfter=0, |
|
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176 | 176 | codeType=0, nCode=0, nBaud=0, code=None, |
|
|
177 | 177 | flip1=0, flip2=0,Taus=0): |
|
|
178 | 178 | self.radarControllerHeaderObj.expType = expType |
|
|
179 | 179 | self.radarControllerHeaderObj.nTx = nTx |
|
|
180 | 180 | self.radarControllerHeaderObj.ipp = float(ipp) |
|
|
181 | 181 | self.radarControllerHeaderObj.txA = float(txA) |
|
|
182 | 182 | self.radarControllerHeaderObj.txB = float(txB) |
|
|
183 | 183 | self.radarControllerHeaderObj.rangeIpp = b'A\n'#ipp |
|
|
184 | 184 | self.radarControllerHeaderObj.rangeTxA = b'' |
|
|
185 | 185 | self.radarControllerHeaderObj.rangeTxB = b'' |
|
|
186 | 186 | |
|
|
187 | 187 | self.radarControllerHeaderObj.nHeights = int(nHeights) |
|
|
188 | 188 | self.radarControllerHeaderObj.firstHeight = numpy.array([firstHeight]) |
|
|
189 | 189 | self.radarControllerHeaderObj.deltaHeight = numpy.array([deltaHeight]) |
|
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190 | 190 | self.radarControllerHeaderObj.samplesWin = numpy.array([nHeights]) |
|
|
191 | 191 | |
|
|
192 | 192 | |
|
|
193 | 193 | self.radarControllerHeaderObj.nWindows = nWindows |
|
|
194 | 194 | self.radarControllerHeaderObj.numTaus = numTaus |
|
|
195 | 195 | self.radarControllerHeaderObj.codeType = codeType |
|
|
196 | 196 | self.radarControllerHeaderObj.line6Function = line6Function |
|
|
197 | 197 | self.radarControllerHeaderObj.line5Function = line5Function |
|
|
198 | 198 | #self.radarControllerHeaderObj.fClock = fClock |
|
|
199 | 199 | self.radarControllerHeaderObj.prePulseBefore= prePulseBefore |
|
|
200 | 200 | self.radarControllerHeaderObj.prePulseAfter = prePulseAfter |
|
|
201 | 201 | |
|
|
202 | 202 | self.radarControllerHeaderObj.flip1 = flip1 |
|
|
203 | 203 | self.radarControllerHeaderObj.flip2 = flip2 |
|
|
204 | 204 | |
|
|
205 | 205 | self.radarControllerHeaderObj.code_size = 0 |
|
|
206 | 206 | if self.radarControllerHeaderObj.codeType != 0: |
|
|
207 | 207 | self.radarControllerHeaderObj.nCode = nCode |
|
|
208 | 208 | self.radarControllerHeaderObj.nBaud = nBaud |
|
|
209 | 209 | self.radarControllerHeaderObj.code = code |
|
|
210 | 210 | self.radarControllerHeaderObj.code_size = int(numpy.ceil(nBaud / 32.)) * nCode * 4 |
|
|
211 | 211 | |
|
|
212 | 212 | if fClock is None and deltaHeight is not None: |
|
|
213 | 213 | self.fClock = 0.15 / (deltaHeight * 1e-6) |
|
|
214 | 214 | self.radarControllerHeaderObj.fClock = self.fClock |
|
|
215 | 215 | if numTaus==0: |
|
|
216 | 216 | self.radarControllerHeaderObj.Taus = numpy.array(0,'<f4') |
|
|
217 | 217 | else: |
|
|
218 | 218 | self.radarControllerHeaderObj.Taus = numpy.array(Taus,'<f4') |
|
|
219 | 219 | |
|
|
220 | 220 | def set_PH(self, dtype=0, blockSize=0, profilesPerBlock=0, |
|
|
221 | 221 | dataBlocksPerFile=0, nWindows=0, processFlags=0, nCohInt=0, |
|
|
222 | 222 | nIncohInt=0, totalSpectra=0, nHeights=0, firstHeight=0, |
|
|
223 | 223 | deltaHeight=0, samplesWin=0, spectraComb=0, nCode=0, |
|
|
224 | 224 | code=0, nBaud=None, shif_fft=False, flag_dc=False, |
|
|
225 | 225 | flag_cspc=False, flag_decode=False, flag_deflip=False): |
|
|
226 | 226 | |
|
|
227 | 227 | self.processingHeaderObj.dtype = dtype |
|
|
228 | 228 | self.processingHeaderObj.profilesPerBlock = profilesPerBlock |
|
|
229 | 229 | self.processingHeaderObj.dataBlocksPerFile = dataBlocksPerFile |
|
|
230 | 230 | self.processingHeaderObj.nWindows = nWindows |
|
|
231 | 231 | self.processingHeaderObj.processFlags = processFlags |
|
|
232 | 232 | self.processingHeaderObj.nCohInt = nCohInt |
|
|
233 | 233 | self.processingHeaderObj.nIncohInt = nIncohInt |
|
|
234 | 234 | self.processingHeaderObj.totalSpectra = totalSpectra |
|
|
235 | 235 | |
|
|
236 | 236 | self.processingHeaderObj.nHeights = int(nHeights) |
|
|
237 | 237 | self.processingHeaderObj.firstHeight = firstHeight#numpy.array([firstHeight])#firstHeight |
|
|
238 | 238 | self.processingHeaderObj.deltaHeight = deltaHeight#numpy.array([deltaHeight])#deltaHeight |
|
|
239 | 239 | self.processingHeaderObj.samplesWin = nHeights#numpy.array([nHeights])#nHeights |
|
|
240 | 240 | |
|
|
241 | 241 | def set_BH(self, utc = 0, miliSecond = 0, timeZone = 0): |
|
|
242 | 242 | self.basicHeaderObj.utc = utc |
|
|
243 | 243 | self.basicHeaderObj.miliSecond = miliSecond |
|
|
244 | 244 | self.basicHeaderObj.timeZone = timeZone |
|
|
245 | 245 | |
|
|
246 | 246 | def set_SH(self, nSamples=0, nProfiles=0, nChannels=0, adcResolution=14, pciDioBusWidth=32): |
|
|
247 | 247 | #self.systemHeaderObj.size = size |
|
|
248 | 248 | self.systemHeaderObj.nSamples = nSamples |
|
|
249 | 249 | self.systemHeaderObj.nProfiles = nProfiles |
|
|
250 | 250 | self.systemHeaderObj.nChannels = nChannels |
|
|
251 | 251 | self.systemHeaderObj.adcResolution = adcResolution |
|
|
252 | 252 | self.systemHeaderObj.pciDioBusWidth = pciDioBusWidth |
|
|
253 | 253 | |
|
|
254 | 254 | def init_acquisition(self): |
|
|
255 | 255 | |
|
|
256 | 256 | if self.nFFTPoints != 0: |
|
|
257 | 257 | self.incIntFactor = m_nProfilesperBlock/self.nFFTPoints |
|
|
258 | 258 | if (self.FixPP_IncInt > self.incIntFactor): |
|
|
259 | 259 | self.incIntFactor = self.FixPP_IncInt/ self.incIntFactor |
|
|
260 | 260 | elif(self.FixPP_IncInt< self.incIntFactor): |
|
|
261 | 261 | print("False alert...") |
|
|
262 | 262 | |
|
|
263 | 263 | ProfilesperBlock = self.processingHeaderObj.profilesPerBlock |
|
|
264 | 264 | |
|
|
265 | 265 | self.timeperblock =int(((self.FixRCP_IPP |
|
|
266 | 266 | *ProfilesperBlock |
|
|
267 | 267 | *self.FixPP_CohInt |
|
|
268 | 268 | *self.incIntFactor) |
|
|
269 | 269 | /150.0) |
|
|
270 | 270 | *0.9 |
|
|
271 | 271 | +0.5) |
|
|
272 | 272 | # para cada canal |
|
|
273 | 273 | self.profiles = ProfilesperBlock*self.FixPP_CohInt |
|
|
274 | 274 | self.profiles = ProfilesperBlock |
|
|
275 | 275 | self.Reference = int((self.Tau_0-self.AcqH0_0)/(self.AcqDH_0)+0.5) |
|
|
276 | 276 | self.BaudWidth = int((self.FixRCP_TXA/self.AcqDH_0)/self.Bauds + 0.5 ) |
|
|
277 | 277 | |
|
|
278 | 278 | if (self.BaudWidth==0): |
|
|
279 | 279 | self.BaudWidth=1 |
|
|
280 | 280 | |
|
|
281 | 281 | def init_pulse(self,Num_Codes=Num_Codes,Bauds=Bauds,BaudWidth=BaudWidth,Dyn_snCode=Dyn_snCode): |
|
|
282 | 282 | |
|
|
283 | 283 | Num_Codes = Num_Codes |
|
|
284 | 284 | Bauds = Bauds |
|
|
285 | 285 | BaudWidth = BaudWidth |
|
|
286 | 286 | Dyn_snCode = Dyn_snCode |
|
|
287 | 287 | |
|
|
288 | 288 | if Dyn_snCode: |
|
|
289 | 289 | print("EXISTE") |
|
|
290 | 290 | else: |
|
|
291 | 291 | print("No existe") |
|
|
292 | 292 | |
|
|
293 | 293 | if Dyn_snCode: # if Bauds: |
|
|
294 | 294 | pulses = list(range(0,Num_Codes)) |
|
|
295 | 295 | num_codes = Num_Codes |
|
|
296 | 296 | for i in range(num_codes): |
|
|
297 | 297 | pulse_size = Bauds*BaudWidth |
|
|
298 | 298 | pulses[i] = numpy.zeros(pulse_size) |
|
|
299 | 299 | for j in range(Bauds): |
|
|
300 | 300 | for k in range(BaudWidth): |
|
|
301 | 301 | pulses[i][j*BaudWidth+k] = int(Dyn_snCode[i][j]*600) |
|
|
302 | 302 | else: |
|
|
303 | 303 | print("sin code") |
|
|
304 | 304 | pulses = list(range(1)) |
|
|
305 | 305 | if self.AcqDH_0>0.149: |
|
|
306 | 306 | pulse_size = int(self.FixRCP_TXB/0.15+0.5) |
|
|
307 | 307 | else: |
|
|
308 | 308 | pulse_size = int((self.FixRCP_TXB/self.AcqDH_0)+0.5) #0.0375 |
|
|
309 | 309 | pulses[0] = numpy.ones(pulse_size) |
|
|
310 | 310 | pulses = 600*pulses[0] |
|
|
311 | 311 | |
|
|
312 | 312 | return pulses,pulse_size |
|
|
313 | 313 | |
|
|
314 | 314 | def jro_GenerateBlockOfData(self,Samples=Samples,DC_level= DC_level,stdev=stdev, |
|
|
315 | 315 | Reference= Reference,pulses= pulses, |
|
|
316 | 316 | Num_Codes= Num_Codes,pulse_size=pulse_size, |
|
|
317 | 317 | prof_gen= prof_gen,H0 = H0,DH0=DH0, |
|
|
318 | 318 | Adoppler=Adoppler,Fdoppler= Fdoppler,Hdoppler=Hdoppler): |
|
|
319 | 319 | Samples = Samples |
|
|
320 | 320 | DC_level = DC_level |
|
|
321 | 321 | stdev = stdev |
|
|
322 | 322 | m_nR = Reference |
|
|
323 | 323 | pulses = pulses |
|
|
324 | 324 | num_codes = Num_Codes |
|
|
325 | 325 | ps = pulse_size |
|
|
326 | 326 | prof_gen = prof_gen |
|
|
327 | 327 | channels = self.channels |
|
|
328 | 328 | H0 = H0 |
|
|
329 | 329 | DH0 = DH0 |
|
|
330 | 330 | ippSec = self.radarControllerHeaderObj.ippSeconds |
|
|
331 | 331 | Fdoppler = self.Fdoppler |
|
|
332 | 332 | Hdoppler = self.Hdoppler |
|
|
333 | 333 | Adoppler = self.Adoppler |
|
|
334 | 334 | |
|
|
335 | 335 | self.datablock = numpy.zeros([channels,prof_gen,Samples],dtype= numpy.complex64) |
|
|
336 | 336 | for i in range(channels): |
|
|
337 | 337 | for k in range(prof_gen): |
|
|
338 | 338 | #Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·NOISEΒ·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· |
|
|
339 | 339 | Noise_r = numpy.random.normal(DC_level,stdev,Samples) |
|
|
340 | 340 | Noise_i = numpy.random.normal(DC_level,stdev,Samples) |
|
|
341 | 341 | Noise = numpy.zeros(Samples,dtype=complex) |
|
|
342 | 342 | Noise.real = Noise_r |
|
|
343 | 343 | Noise.imag = Noise_i |
|
|
344 | 344 | #Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·PULSOSΒ·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· |
|
|
345 | 345 | Pulso = numpy.zeros(pulse_size,dtype=complex) |
|
|
346 | 346 | Pulso.real = pulses[k%num_codes] |
|
|
347 | 347 | Pulso.imag = pulses[k%num_codes] |
|
|
348 | 348 | #Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· PULSES+NOISEΒ·Β·Β·Β·Β·Β·Β·Β·Β·Β· |
|
|
349 | 349 | InBuffer = numpy.zeros(Samples,dtype=complex) |
|
|
350 | 350 | InBuffer[m_nR:m_nR+ps] = Pulso |
|
|
351 | 351 | InBuffer = InBuffer+Noise |
|
|
352 | 352 | #Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· ANGLE Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· |
|
|
353 | 353 | InBuffer.real[m_nR:m_nR+ps] = InBuffer.real[m_nR:m_nR+ps]*(math.cos( self.fAngle)*5) |
|
|
354 | 354 | InBuffer.imag[m_nR:m_nR+ps] = InBuffer.imag[m_nR:m_nR+ps]*(math.sin( self.fAngle)*5) |
|
|
355 | 355 | InBuffer=InBuffer |
|
|
356 | 356 | self.datablock[i][k]= InBuffer |
|
|
357 | 357 | |
|
|
358 | 358 | #Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·DOPPLER SIGNAL............................................... |
|
|
359 | 359 | time_vec = numpy.linspace(0,(prof_gen-1)*ippSec,int(prof_gen))+self.nReadBlocks*ippSec*prof_gen+(self.nReadFiles-1)*ippSec*prof_gen |
|
|
360 | 360 | fd = Fdoppler #+(600.0/120)*self.nReadBlocks |
|
|
361 | 361 | d_signal = Adoppler*numpy.array(numpy.exp(1.0j*2.0*math.pi*fd*time_vec),dtype=numpy.complex64) |
|
|
362 | 362 | #Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·SeΓ±al con ancho espectralΒ·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· |
|
|
363 | #specw_sig = numpy.linspace(-149,150,300) | |
|
|
364 | #w = 8 | |
|
|
365 | #A = 20 | |
|
|
366 | #specw_sig = specw_sig/w | |
|
|
367 | #specw_sig = numpy.sinc(specw_sig) | |
|
|
368 | #specw_sig = A*numpy.array(specw_sig,dtype=numpy.complex64) | |
|
|
363 | if prof_gen%2==0: | |
|
|
364 | min = int(prof_gen/2.0-1.0) | |
|
|
365 | max = int(prof_gen/2.0) | |
|
|
366 | else: | |
|
|
367 | min = int(prof_gen/2.0) | |
|
|
368 | max = int(prof_gen/2.0) | |
|
|
369 | specw_sig = numpy.linspace(-min,max,prof_gen) | |
|
|
370 | w = 4 | |
|
|
371 | A = 20 | |
|
|
372 | specw_sig = specw_sig/w | |
|
|
373 | specw_sig = numpy.sinc(specw_sig) | |
|
|
374 | specw_sig = A*numpy.array(specw_sig,dtype=numpy.complex64) | |
|
|
369 | 375 | #Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· DATABLOCK + DOPPLERΒ·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· |
|
|
370 | 376 | HD=int(Hdoppler/self.AcqDH_0) |
|
|
371 | 377 | for i in range(12): |
|
|
372 | 378 | self.datablock[0,:,HD+i]=self.datablock[0,:,HD+i]+ d_signal# RESULT |
|
|
373 | 379 | #Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· DATABLOCK + DOPPLER*Sinc(x)Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· |
|
|
374 |
|
|
|
|
375 |
|
|
|
|
376 |
|
|
|
|
377 |
|
|
|
|
380 | HD=int(Hdoppler/self.AcqDH_0) | |
|
|
381 | HD=int(HD/2) | |
|
|
382 | for i in range(12): | |
|
|
383 | self.datablock[0,:,HD+i]=self.datablock[0,:,HD+i]+ specw_sig*d_signal# RESULT | |
|
|
378 | 384 | |
|
|
379 | 385 | def readBlock(self): |
|
|
380 | 386 | |
|
|
381 | 387 | self.jro_GenerateBlockOfData(Samples= self.samples,DC_level=self.DC_level, |
|
|
382 | 388 | stdev=self.stdev,Reference= self.Reference, |
|
|
383 | 389 | pulses = self.pulses,Num_Codes=self.Num_Codes, |
|
|
384 | 390 | pulse_size=self.pulse_size,prof_gen=self.profiles, |
|
|
385 | 391 | H0=self.H0,DH0=self.DH0) |
|
|
386 | 392 | |
|
|
387 | 393 | self.profileIndex = 0 |
|
|
388 | 394 | self.flagIsNewFile = 0 |
|
|
389 | 395 | self.flagIsNewBlock = 1 |
|
|
390 | 396 | self.nTotalBlocks += 1 |
|
|
391 | 397 | self.nReadBlocks += 1 |
|
|
392 | 398 | |
|
|
393 | 399 | return 1 |
|
|
394 | 400 | |
|
|
395 | 401 | |
|
|
396 | 402 | def getData(self): |
|
|
397 | 403 | if self.flagNoMoreFiles: |
|
|
398 | 404 | self.dataOut.flagNodata = True |
|
|
399 | 405 | return 0 |
|
|
400 | 406 | self.flagDiscontinuousBlock = 0 |
|
|
401 | 407 | self.flagIsNewBlock = 0 |
|
|
402 | 408 | if self.__hasNotDataInBuffer(): # aqui es verdad |
|
|
403 | 409 | if not(self.readNextBlock()): # return 1 y por eso el if not salta a getBasic Header |
|
|
404 | 410 | return 0 |
|
|
405 | 411 | self.getFirstHeader() # atributo |
|
|
406 | 412 | |
|
|
407 | 413 | if not self.getByBlock: |
|
|
408 | 414 | self.dataOut.flagDataAsBlock = False |
|
|
409 | 415 | self.dataOut.data = self.datablock[:, self.profileIndex, :] |
|
|
410 | 416 | self.dataOut.profileIndex = self.profileIndex |
|
|
411 | 417 | self.profileIndex += 1 |
|
|
412 | 418 | else: |
|
|
413 | 419 | pass |
|
|
414 | 420 | self.dataOut.flagNoData = False |
|
|
415 | 421 | self.getBasicHeader() |
|
|
416 | 422 | self.dataOut.realtime = self.online |
|
|
417 | 423 | return self.dataOut.data |
|
|
418 | 424 | |
|
|
419 | 425 | |
|
|
420 | 426 | def setup(self,frequency=49.92e6,incIntFactor= 1, nFFTPoints = 0, FixPP_IncInt=1,FixRCP_IPP=1000, |
|
|
421 | 427 | FixPP_CohInt= 1,Tau_0= 250,AcqH0_0 = 70 ,AcqDH_0=1.25, Bauds= 32, |
|
|
422 | 428 | FixRCP_TXA = 40, FixRCP_TXB = 50, fAngle = 2.0*math.pi*(1/16),DC_level= 50, |
|
|
423 | 429 | stdev= 8,Num_Codes = 1 , Dyn_snCode = None, samples=200, |
|
|
424 |
channels=2,Fdoppler=20,Hdoppler=36,Adoppler=500, |
|
|
|
430 | channels=2,Fdoppler=20,Hdoppler=36,Adoppler=500, | |
|
|
431 | profilesPerBlock=300,dataBlocksPerFile=120,nTotalReadFiles=10000, | |
|
|
425 | 432 | **kwargs): |
|
|
426 | 433 | |
|
|
427 | 434 | self.set_kwargs(**kwargs) |
|
|
428 | 435 | self.nReadBlocks = 0 |
|
|
429 | 436 | self.nReadFiles = 1 |
|
|
430 | 437 | print('------------------- [Opening file: ] ------------------------------',self.nReadFiles) |
|
|
431 | 438 | |
|
|
432 | 439 | tmp = time.time() |
|
|
433 | 440 | tmp_utc = int(tmp) |
|
|
434 | 441 | tmp_milisecond = int((tmp-tmp_utc)*1000) |
|
|
435 | 442 | print(" SETUP -basicHeaderObj.utc",datetime.datetime.utcfromtimestamp(tmp)) |
|
|
436 | 443 | if Dyn_snCode is None: |
|
|
437 | 444 | Num_Codes=1 |
|
|
438 | 445 | Bauds =1 |
|
|
439 | 446 | |
|
|
440 | 447 | |
|
|
441 | 448 | |
|
|
442 | 449 | self.set_BH(utc= tmp_utc,miliSecond= tmp_milisecond,timeZone=300 ) |
|
|
443 | 450 | self.set_RCH( expType=0, nTx=150,ipp=FixRCP_IPP, txA=FixRCP_TXA, txB= FixRCP_TXB, |
|
|
444 | 451 | nWindows=1 , nHeights=samples, firstHeight=AcqH0_0, deltaHeight=AcqDH_0, |
|
|
445 | 452 | numTaus=1, line6Function=0, line5Function=0, fClock=None, |
|
|
446 | 453 | prePulseBefore=0, prePulseAfter=0, |
|
|
447 | 454 | codeType=0, nCode=Num_Codes, nBaud=32, code=Dyn_snCode, |
|
|
448 | 455 | flip1=0, flip2=0,Taus=Tau_0) |
|
|
449 | 456 | |
|
|
450 |
self.set_PH(dtype=0, blockSize=0, profilesPerBlock= |
|
|
|
451 |
dataBlocksPerFile= |
|
|
|
457 | self.set_PH(dtype=0, blockSize=0, profilesPerBlock=profilesPerBlock, | |
|
|
458 | dataBlocksPerFile=dataBlocksPerFile, nWindows=1, processFlags=numpy.array([1024]), nCohInt=1, | |
|
|
452 | 459 | nIncohInt=1, totalSpectra=0, nHeights=samples, firstHeight=AcqH0_0, |
|
|
453 | 460 | deltaHeight=AcqDH_0, samplesWin=samples, spectraComb=0, nCode=0, |
|
|
454 | 461 | code=0, nBaud=None, shif_fft=False, flag_dc=False, |
|
|
455 | 462 | flag_cspc=False, flag_decode=False, flag_deflip=False) |
|
|
456 | 463 | |
|
|
457 |
self.set_SH(nSamples=samples, nProfiles= |
|
|
|
464 | self.set_SH(nSamples=samples, nProfiles=profilesPerBlock, nChannels=channels) | |
|
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458 | 465 | |
|
|
459 | 466 | self.readFirstHeader() |
|
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460 | 467 | |
|
|
461 | 468 | self.frequency = frequency |
|
|
462 | 469 | self.incIntFactor = incIntFactor |
|
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463 | 470 | self.nFFTPoints = nFFTPoints |
|
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464 | 471 | self.FixPP_IncInt = FixPP_IncInt |
|
|
465 | 472 | self.FixRCP_IPP = FixRCP_IPP |
|
|
466 | 473 | self.FixPP_CohInt = FixPP_CohInt |
|
|
467 | 474 | self.Tau_0 = Tau_0 |
|
|
468 | 475 | self.AcqH0_0 = AcqH0_0 |
|
|
469 | 476 | self.H0 = AcqH0_0 |
|
|
470 | 477 | self.AcqDH_0 = AcqDH_0 |
|
|
471 | 478 | self.DH0 = AcqDH_0 |
|
|
472 | 479 | self.Bauds = Bauds |
|
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473 | 480 | self.FixRCP_TXA = FixRCP_TXA |
|
|
474 | 481 | self.FixRCP_TXB = FixRCP_TXB |
|
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475 | 482 | self.fAngle = fAngle |
|
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476 | 483 | self.DC_level = DC_level |
|
|
477 | 484 | self.stdev = stdev |
|
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478 | 485 | self.Num_Codes = Num_Codes |
|
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479 | 486 | self.Dyn_snCode = Dyn_snCode |
|
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480 | 487 | self.samples = samples |
|
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481 | 488 | self.channels = channels |
|
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482 | 489 | self.profiles = None |
|
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483 | 490 | self.m_nReference = None |
|
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484 | 491 | self.Baudwidth = None |
|
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485 | 492 | self.Fdoppler = Fdoppler |
|
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486 | 493 | self.Hdoppler = Hdoppler |
|
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487 | 494 | self.Adoppler = Adoppler |
|
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488 | 495 | self.nTotalReadFiles = int(nTotalReadFiles) |
|
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489 | 496 | |
|
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490 | 497 | print("IPP ", self.FixRCP_IPP) |
|
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491 | 498 | print("Tau_0 ",self.Tau_0) |
|
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492 | 499 | print("AcqH0_0",self.AcqH0_0) |
|
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493 | 500 | print("samples,window ",self.samples) |
|
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494 | 501 | print("AcqDH_0",AcqDH_0) |
|
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495 | 502 | print("FixRCP_TXA",self.FixRCP_TXA) |
|
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496 | 503 | print("FixRCP_TXB",self.FixRCP_TXB) |
|
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497 | 504 | print("Dyn_snCode",Dyn_snCode) |
|
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498 | 505 | print("Fdoppler", Fdoppler) |
|
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499 | 506 | print("Hdoppler",Hdoppler) |
|
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500 | 507 | print("Vdopplermax",Fdoppler*(3.0e8/self.frequency)/2.0) |
|
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501 | 508 | print("nTotalReadFiles", nTotalReadFiles) |
|
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502 | 509 | |
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503 | 510 | self.init_acquisition() |
|
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504 | 511 | self.pulses,self.pulse_size=self.init_pulse(Num_Codes=self.Num_Codes,Bauds=self.Bauds,BaudWidth=self.BaudWidth,Dyn_snCode=Dyn_snCode) |
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505 | 512 | print(" [ END ] - SETUP metodo") |
|
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506 | 513 | return |
|
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507 | 514 | |
|
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508 | 515 | def run(self,**kwargs): # metodo propio |
|
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509 | 516 | if not(self.isConfig): |
|
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510 | 517 | self.setup(**kwargs) |
|
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511 | 518 | self.isConfig = True |
|
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512 | 519 | self.getData() |
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1 | NO CONTENT: modified file | |
| The requested commit or file is too big and content was truncated. Show full diff | |||
| @@ -1,1604 +1,1627 | |||
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1 | 1 | import sys |
|
|
2 | 2 | import numpy,math |
|
|
3 | 3 | from scipy import interpolate |
|
|
4 | 4 | from schainpy.model.proc.jroproc_base import ProcessingUnit, Operation, MPDecorator |
|
|
5 | from schainpy.model.data.jrodata import Voltage | |
|
|
5 | from schainpy.model.data.jrodata import Voltage,hildebrand_sekhon | |
|
|
6 | 6 | from schainpy.utils import log |
|
|
7 | 7 | from time import time |
|
|
8 | 8 | |
|
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9 | 9 | |
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10 | 10 | |
|
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11 | 11 | class VoltageProc(ProcessingUnit): |
|
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12 | 12 | |
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13 | 13 | def __init__(self): |
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14 | 14 | |
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15 | 15 | ProcessingUnit.__init__(self) |
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16 | 16 | |
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17 | 17 | self.dataOut = Voltage() |
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18 | 18 | self.flip = 1 |
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19 | 19 | self.setupReq = False |
|
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20 | 20 | |
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21 | 21 | def run(self): |
|
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22 | 22 | |
|
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23 | 23 | if self.dataIn.type == 'AMISR': |
|
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24 | 24 | self.__updateObjFromAmisrInput() |
|
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25 | 25 | |
|
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26 | 26 | if self.dataIn.type == 'Voltage': |
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27 | 27 | self.dataOut.copy(self.dataIn) |
|
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28 | 28 | |
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29 | 29 | def __updateObjFromAmisrInput(self): |
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30 | 30 | |
|
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31 | 31 | self.dataOut.timeZone = self.dataIn.timeZone |
|
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32 | 32 | self.dataOut.dstFlag = self.dataIn.dstFlag |
|
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33 | 33 | self.dataOut.errorCount = self.dataIn.errorCount |
|
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34 | 34 | self.dataOut.useLocalTime = self.dataIn.useLocalTime |
|
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35 | 35 | |
|
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36 | 36 | self.dataOut.flagNoData = self.dataIn.flagNoData |
|
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37 | 37 | self.dataOut.data = self.dataIn.data |
|
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38 | 38 | self.dataOut.utctime = self.dataIn.utctime |
|
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39 | 39 | self.dataOut.channelList = self.dataIn.channelList |
|
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40 | 40 | #self.dataOut.timeInterval = self.dataIn.timeInterval |
|
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41 | 41 | self.dataOut.heightList = self.dataIn.heightList |
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42 | 42 | self.dataOut.nProfiles = self.dataIn.nProfiles |
|
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43 | 43 | |
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44 | 44 | self.dataOut.nCohInt = self.dataIn.nCohInt |
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45 | 45 | self.dataOut.ippSeconds = self.dataIn.ippSeconds |
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46 | 46 | self.dataOut.frequency = self.dataIn.frequency |
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47 | 47 | |
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48 | 48 | self.dataOut.azimuth = self.dataIn.azimuth |
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49 | 49 | self.dataOut.zenith = self.dataIn.zenith |
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50 | 50 | |
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51 | 51 | self.dataOut.beam.codeList = self.dataIn.beam.codeList |
|
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52 | 52 | self.dataOut.beam.azimuthList = self.dataIn.beam.azimuthList |
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53 | 53 | self.dataOut.beam.zenithList = self.dataIn.beam.zenithList |
|
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54 | 54 | |
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55 | 55 | |
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56 | 56 | class selectChannels(Operation): |
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57 | 57 | |
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58 | 58 | def run(self, dataOut, channelList): |
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59 | 59 | |
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60 | 60 | channelIndexList = [] |
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61 | 61 | self.dataOut = dataOut |
|
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62 | 62 | for channel in channelList: |
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63 | 63 | if channel not in self.dataOut.channelList: |
|
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64 | 64 | raise ValueError("Channel %d is not in %s" %(channel, str(self.dataOut.channelList))) |
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65 | 65 | |
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66 | 66 | index = self.dataOut.channelList.index(channel) |
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67 | 67 | channelIndexList.append(index) |
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68 | 68 | self.selectChannelsByIndex(channelIndexList) |
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69 | 69 | return self.dataOut |
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70 | 70 | |
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71 | 71 | def selectChannelsByIndex(self, channelIndexList): |
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72 | 72 | """ |
|
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73 | 73 | Selecciona un bloque de datos en base a canales segun el channelIndexList |
|
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74 | 74 | |
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75 | 75 | Input: |
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76 | 76 | channelIndexList : lista sencilla de canales a seleccionar por ej. [2,3,7] |
|
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77 | 77 | |
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78 | 78 | Affected: |
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79 | 79 | self.dataOut.data |
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80 | 80 | self.dataOut.channelIndexList |
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81 | 81 | self.dataOut.nChannels |
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82 | 82 | self.dataOut.m_ProcessingHeader.totalSpectra |
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83 | 83 | self.dataOut.systemHeaderObj.numChannels |
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84 | 84 | self.dataOut.m_ProcessingHeader.blockSize |
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85 | 85 | |
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86 | 86 | Return: |
|
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87 | 87 | None |
|
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88 | 88 | """ |
|
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89 | 89 | |
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90 | 90 | for channelIndex in channelIndexList: |
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91 | 91 | if channelIndex not in self.dataOut.channelIndexList: |
|
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92 | 92 | raise ValueError("The value %d in channelIndexList is not valid" %channelIndex) |
|
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93 | 93 | |
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94 | 94 | if self.dataOut.type == 'Voltage': |
|
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95 | 95 | if self.dataOut.flagDataAsBlock: |
|
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96 | 96 | """ |
|
|
97 | 97 | Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis] |
|
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98 | 98 | """ |
|
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99 | 99 | data = self.dataOut.data[channelIndexList,:,:] |
|
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100 | 100 | else: |
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101 | 101 | data = self.dataOut.data[channelIndexList,:] |
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102 | 102 | |
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103 | 103 | self.dataOut.data = data |
|
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104 | 104 | # self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList] |
|
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105 | 105 | self.dataOut.channelList = range(len(channelIndexList)) |
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106 | 106 | |
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107 | 107 | elif self.dataOut.type == 'Spectra': |
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108 | 108 | data_spc = self.dataOut.data_spc[channelIndexList, :] |
|
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109 | 109 | data_dc = self.dataOut.data_dc[channelIndexList, :] |
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110 | 110 | |
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111 | 111 | self.dataOut.data_spc = data_spc |
|
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112 | 112 | self.dataOut.data_dc = data_dc |
|
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113 | 113 | |
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114 | 114 | # self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList] |
|
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115 | 115 | self.dataOut.channelList = range(len(channelIndexList)) |
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116 | 116 | self.__selectPairsByChannel(channelIndexList) |
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117 | 117 | |
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118 | 118 | return 1 |
|
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119 | 119 | |
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120 | 120 | def __selectPairsByChannel(self, channelList=None): |
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121 | 121 | |
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122 | 122 | if channelList == None: |
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123 | 123 | return |
|
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124 | 124 | |
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125 | 125 | pairsIndexListSelected = [] |
|
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126 | 126 | for pairIndex in self.dataOut.pairsIndexList: |
|
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127 | 127 | # First pair |
|
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128 | 128 | if self.dataOut.pairsList[pairIndex][0] not in channelList: |
|
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129 | 129 | continue |
|
|
130 | 130 | # Second pair |
|
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131 | 131 | if self.dataOut.pairsList[pairIndex][1] not in channelList: |
|
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132 | 132 | continue |
|
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133 | 133 | |
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134 | 134 | pairsIndexListSelected.append(pairIndex) |
|
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135 | 135 | |
|
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136 | 136 | if not pairsIndexListSelected: |
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137 | 137 | self.dataOut.data_cspc = None |
|
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138 | 138 | self.dataOut.pairsList = [] |
|
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139 | 139 | return |
|
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140 | 140 | |
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141 | 141 | self.dataOut.data_cspc = self.dataOut.data_cspc[pairsIndexListSelected] |
|
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142 | 142 | self.dataOut.pairsList = [self.dataOut.pairsList[i] |
|
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143 | 143 | for i in pairsIndexListSelected] |
|
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144 | 144 | |
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145 | 145 | return |
|
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146 | 146 | |
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147 | 147 | class selectHeights(Operation): |
|
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148 | 148 | |
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149 | 149 | def run(self, dataOut, minHei=None, maxHei=None): |
|
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150 | 150 | """ |
|
|
151 | 151 | Selecciona un bloque de datos en base a un grupo de valores de alturas segun el rango |
|
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152 | 152 | minHei <= height <= maxHei |
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153 | 153 | |
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154 | 154 | Input: |
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155 | 155 | minHei : valor minimo de altura a considerar |
|
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156 | 156 | maxHei : valor maximo de altura a considerar |
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157 | 157 | |
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158 | 158 | Affected: |
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159 | 159 | Indirectamente son cambiados varios valores a travez del metodo selectHeightsByIndex |
|
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160 | 160 | |
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161 | 161 | Return: |
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162 | 162 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 |
|
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163 | 163 | """ |
|
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164 | 164 | |
|
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165 | 165 | self.dataOut = dataOut |
|
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166 | 166 | |
|
|
167 | 167 | if minHei == None: |
|
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168 | 168 | minHei = self.dataOut.heightList[0] |
|
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169 | 169 | |
|
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170 | 170 | if maxHei == None: |
|
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171 | 171 | maxHei = self.dataOut.heightList[-1] |
|
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172 | 172 | |
|
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173 | 173 | if (minHei < self.dataOut.heightList[0]): |
|
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174 | 174 | minHei = self.dataOut.heightList[0] |
|
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175 | 175 | |
|
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176 | 176 | if (maxHei > self.dataOut.heightList[-1]): |
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177 | 177 | maxHei = self.dataOut.heightList[-1] |
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178 | 178 | |
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179 | 179 | minIndex = 0 |
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180 | 180 | maxIndex = 0 |
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181 | 181 | heights = self.dataOut.heightList |
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182 | 182 | |
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183 | 183 | inda = numpy.where(heights >= minHei) |
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184 | 184 | indb = numpy.where(heights <= maxHei) |
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185 | 185 | |
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186 | 186 | try: |
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187 | 187 | minIndex = inda[0][0] |
|
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188 | 188 | except: |
|
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189 | 189 | minIndex = 0 |
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190 | 190 | |
|
|
191 | 191 | try: |
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192 | 192 | maxIndex = indb[0][-1] |
|
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193 | 193 | except: |
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194 | 194 | maxIndex = len(heights) |
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195 | 195 | |
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196 | 196 | self.selectHeightsByIndex(minIndex, maxIndex) |
|
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197 | 197 | |
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198 | 198 | return self.dataOut |
|
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199 | 199 | |
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200 | 200 | def selectHeightsByIndex(self, minIndex, maxIndex): |
|
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201 | 201 | """ |
|
|
202 | 202 | Selecciona un bloque de datos en base a un grupo indices de alturas segun el rango |
|
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203 | 203 | minIndex <= index <= maxIndex |
|
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204 | 204 | |
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205 | 205 | Input: |
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206 | 206 | minIndex : valor de indice minimo de altura a considerar |
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207 | 207 | maxIndex : valor de indice maximo de altura a considerar |
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208 | 208 | |
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209 | 209 | Affected: |
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210 | 210 | self.dataOut.data |
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211 | 211 | self.dataOut.heightList |
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212 | 212 | |
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213 | 213 | Return: |
|
|
214 | 214 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 |
|
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215 | 215 | """ |
|
|
216 | 216 | |
|
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217 | 217 | if self.dataOut.type == 'Voltage': |
|
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218 | 218 | if (minIndex < 0) or (minIndex > maxIndex): |
|
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219 | 219 | raise ValueError("Height index range (%d,%d) is not valid" % (minIndex, maxIndex)) |
|
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220 | 220 | |
|
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221 | 221 | if (maxIndex >= self.dataOut.nHeights): |
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222 | 222 | maxIndex = self.dataOut.nHeights |
|
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223 | 223 | |
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|
224 | 224 | #voltage |
|
|
225 | 225 | if self.dataOut.flagDataAsBlock: |
|
|
226 | 226 | """ |
|
|
227 | 227 | Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis] |
|
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228 | 228 | """ |
|
|
229 | 229 | data = self.dataOut.data[:,:, minIndex:maxIndex] |
|
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230 | 230 | else: |
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|
231 | 231 | data = self.dataOut.data[:, minIndex:maxIndex] |
|
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232 | 232 | |
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233 | 233 | # firstHeight = self.dataOut.heightList[minIndex] |
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234 | 234 | |
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235 | 235 | self.dataOut.data = data |
|
|
236 | 236 | self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex] |
|
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237 | 237 | |
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238 | 238 | if self.dataOut.nHeights <= 1: |
|
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239 | 239 | raise ValueError("selectHeights: Too few heights. Current number of heights is %d" %(self.dataOut.nHeights)) |
|
|
240 | 240 | elif self.dataOut.type == 'Spectra': |
|
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241 | 241 | if (minIndex < 0) or (minIndex > maxIndex): |
|
|
242 | 242 | raise ValueError("Error selecting heights: Index range (%d,%d) is not valid" % ( |
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243 | 243 | minIndex, maxIndex)) |
|
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244 | 244 | |
|
|
245 | 245 | if (maxIndex >= self.dataOut.nHeights): |
|
|
246 | 246 | maxIndex = self.dataOut.nHeights - 1 |
|
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247 | 247 | |
|
|
248 | 248 | # Spectra |
|
|
249 | 249 | data_spc = self.dataOut.data_spc[:, :, minIndex:maxIndex + 1] |
|
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250 | 250 | |
|
|
251 | 251 | data_cspc = None |
|
|
252 | 252 | if self.dataOut.data_cspc is not None: |
|
|
253 | 253 | data_cspc = self.dataOut.data_cspc[:, :, minIndex:maxIndex + 1] |
|
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254 | 254 | |
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|
255 | 255 | data_dc = None |
|
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256 | 256 | if self.dataOut.data_dc is not None: |
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257 | 257 | data_dc = self.dataOut.data_dc[:, minIndex:maxIndex + 1] |
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258 | 258 | |
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259 | 259 | self.dataOut.data_spc = data_spc |
|
|
260 | 260 | self.dataOut.data_cspc = data_cspc |
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|
261 | 261 | self.dataOut.data_dc = data_dc |
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262 | 262 | |
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|
263 | 263 | self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex + 1] |
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264 | 264 | |
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|
265 | 265 | return 1 |
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266 | 266 | |
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267 | 267 | |
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268 | 268 | class filterByHeights(Operation): |
|
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269 | 269 | |
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270 | 270 | def run(self, dataOut, window): |
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271 | 271 | |
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|
272 | 272 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
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273 | 273 | |
|
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274 | 274 | if window == None: |
|
|
275 | 275 | window = (dataOut.radarControllerHeaderObj.txA/dataOut.radarControllerHeaderObj.nBaud) / deltaHeight |
|
|
276 | 276 | |
|
|
277 | 277 | newdelta = deltaHeight * window |
|
|
278 | 278 | r = dataOut.nHeights % window |
|
|
279 | 279 | newheights = (dataOut.nHeights-r)/window |
|
|
280 | 280 | |
|
|
281 | 281 | if newheights <= 1: |
|
|
282 | 282 | raise ValueError("filterByHeights: Too few heights. Current number of heights is %d and window is %d" %(dataOut.nHeights, window)) |
|
|
283 | 283 | |
|
|
284 | 284 | if dataOut.flagDataAsBlock: |
|
|
285 | 285 | """ |
|
|
286 | 286 | Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis] |
|
|
287 | 287 | """ |
|
|
288 | 288 | buffer = dataOut.data[:, :, 0:int(dataOut.nHeights-r)] |
|
|
289 | 289 | buffer = buffer.reshape(dataOut.nChannels, dataOut.nProfiles, int(dataOut.nHeights/window), window) |
|
|
290 | 290 | buffer = numpy.sum(buffer,3) |
|
|
291 | 291 | |
|
|
292 | 292 | else: |
|
|
293 | 293 | buffer = dataOut.data[:,0:int(dataOut.nHeights-r)] |
|
|
294 | 294 | buffer = buffer.reshape(dataOut.nChannels,int(dataOut.nHeights/window),int(window)) |
|
|
295 | 295 | buffer = numpy.sum(buffer,2) |
|
|
296 | 296 | |
|
|
297 | 297 | dataOut.data = buffer |
|
|
298 | 298 | dataOut.heightList = dataOut.heightList[0] + numpy.arange( newheights )*newdelta |
|
|
299 | 299 | dataOut.windowOfFilter = window |
|
|
300 | 300 | |
|
|
301 | 301 | return dataOut |
|
|
302 | 302 | |
|
|
303 | 303 | |
|
|
304 | 304 | class setH0(Operation): |
|
|
305 | 305 | |
|
|
306 | 306 | def run(self, dataOut, h0, deltaHeight = None): |
|
|
307 | 307 | |
|
|
308 | 308 | if not deltaHeight: |
|
|
309 | 309 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
|
310 | 310 | |
|
|
311 | 311 | nHeights = dataOut.nHeights |
|
|
312 | 312 | |
|
|
313 | 313 | newHeiRange = h0 + numpy.arange(nHeights)*deltaHeight |
|
|
314 | 314 | |
|
|
315 | 315 | dataOut.heightList = newHeiRange |
|
|
316 | 316 | |
|
|
317 | 317 | return dataOut |
|
|
318 | 318 | |
|
|
319 | 319 | |
|
|
320 | 320 | class deFlip(Operation): |
|
|
321 | 321 | |
|
|
322 | 322 | def run(self, dataOut, channelList = []): |
|
|
323 | 323 | |
|
|
324 | 324 | data = dataOut.data.copy() |
|
|
325 | 325 | |
|
|
326 | 326 | if dataOut.flagDataAsBlock: |
|
|
327 | 327 | flip = self.flip |
|
|
328 | 328 | profileList = list(range(dataOut.nProfiles)) |
|
|
329 | 329 | |
|
|
330 | 330 | if not channelList: |
|
|
331 | 331 | for thisProfile in profileList: |
|
|
332 | 332 | data[:,thisProfile,:] = data[:,thisProfile,:]*flip |
|
|
333 | 333 | flip *= -1.0 |
|
|
334 | 334 | else: |
|
|
335 | 335 | for thisChannel in channelList: |
|
|
336 | 336 | if thisChannel not in dataOut.channelList: |
|
|
337 | 337 | continue |
|
|
338 | 338 | |
|
|
339 | 339 | for thisProfile in profileList: |
|
|
340 | 340 | data[thisChannel,thisProfile,:] = data[thisChannel,thisProfile,:]*flip |
|
|
341 | 341 | flip *= -1.0 |
|
|
342 | 342 | |
|
|
343 | 343 | self.flip = flip |
|
|
344 | 344 | |
|
|
345 | 345 | else: |
|
|
346 | 346 | if not channelList: |
|
|
347 | 347 | data[:,:] = data[:,:]*self.flip |
|
|
348 | 348 | else: |
|
|
349 | 349 | for thisChannel in channelList: |
|
|
350 | 350 | if thisChannel not in dataOut.channelList: |
|
|
351 | 351 | continue |
|
|
352 | 352 | |
|
|
353 | 353 | data[thisChannel,:] = data[thisChannel,:]*self.flip |
|
|
354 | 354 | |
|
|
355 | 355 | self.flip *= -1. |
|
|
356 | 356 | |
|
|
357 | 357 | dataOut.data = data |
|
|
358 | 358 | |
|
|
359 | 359 | return dataOut |
|
|
360 | 360 | |
|
|
361 | 361 | |
|
|
362 | 362 | class setAttribute(Operation): |
|
|
363 | 363 | ''' |
|
|
364 | 364 | Set an arbitrary attribute(s) to dataOut |
|
|
365 | 365 | ''' |
|
|
366 | 366 | |
|
|
367 | 367 | def __init__(self): |
|
|
368 | 368 | |
|
|
369 | 369 | Operation.__init__(self) |
|
|
370 | 370 | self._ready = False |
|
|
371 | 371 | |
|
|
372 | 372 | def run(self, dataOut, **kwargs): |
|
|
373 | 373 | |
|
|
374 | 374 | for key, value in kwargs.items(): |
|
|
375 | 375 | setattr(dataOut, key, value) |
|
|
376 | 376 | |
|
|
377 | 377 | return dataOut |
|
|
378 | 378 | |
|
|
379 | 379 | |
|
|
380 | 380 | @MPDecorator |
|
|
381 | 381 | class printAttribute(Operation): |
|
|
382 | 382 | ''' |
|
|
383 | 383 | Print an arbitrary attribute of dataOut |
|
|
384 | 384 | ''' |
|
|
385 | 385 | |
|
|
386 | 386 | def __init__(self): |
|
|
387 | 387 | |
|
|
388 | 388 | Operation.__init__(self) |
|
|
389 | 389 | |
|
|
390 | 390 | def run(self, dataOut, attributes): |
|
|
391 | 391 | |
|
|
392 | 392 | for attr in attributes: |
|
|
393 | 393 | if hasattr(dataOut, attr): |
|
|
394 | 394 | log.log(getattr(dataOut, attr), attr) |
|
|
395 | 395 | |
|
|
396 | 396 | |
|
|
397 | 397 | class interpolateHeights(Operation): |
|
|
398 | 398 | |
|
|
399 | 399 | def run(self, dataOut, topLim, botLim): |
|
|
400 | 400 | #69 al 72 para julia |
|
|
401 | 401 | #82-84 para meteoros |
|
|
402 | 402 | if len(numpy.shape(dataOut.data))==2: |
|
|
403 | 403 | sampInterp = (dataOut.data[:,botLim-1] + dataOut.data[:,topLim+1])/2 |
|
|
404 | 404 | sampInterp = numpy.transpose(numpy.tile(sampInterp,(topLim-botLim + 1,1))) |
|
|
405 | 405 | #dataOut.data[:,botLim:limSup+1] = sampInterp |
|
|
406 | 406 | dataOut.data[:,botLim:topLim+1] = sampInterp |
|
|
407 | 407 | else: |
|
|
408 | 408 | nHeights = dataOut.data.shape[2] |
|
|
409 | 409 | x = numpy.hstack((numpy.arange(botLim),numpy.arange(topLim+1,nHeights))) |
|
|
410 | 410 | y = dataOut.data[:,:,list(range(botLim))+list(range(topLim+1,nHeights))] |
|
|
411 | 411 | f = interpolate.interp1d(x, y, axis = 2) |
|
|
412 | 412 | xnew = numpy.arange(botLim,topLim+1) |
|
|
413 | 413 | ynew = f(xnew) |
|
|
414 | 414 | dataOut.data[:,:,botLim:topLim+1] = ynew |
|
|
415 | 415 | |
|
|
416 | 416 | return dataOut |
|
|
417 | 417 | |
|
|
418 | 418 | |
|
|
419 | 419 | class CohInt(Operation): |
|
|
420 | 420 | |
|
|
421 | 421 | isConfig = False |
|
|
422 | 422 | __profIndex = 0 |
|
|
423 | 423 | __byTime = False |
|
|
424 | 424 | __initime = None |
|
|
425 | 425 | __lastdatatime = None |
|
|
426 | 426 | __integrationtime = None |
|
|
427 | 427 | __buffer = None |
|
|
428 | 428 | __bufferStride = [] |
|
|
429 | 429 | __dataReady = False |
|
|
430 | 430 | __profIndexStride = 0 |
|
|
431 | 431 | __dataToPutStride = False |
|
|
432 | 432 | n = None |
|
|
433 | 433 | |
|
|
434 | 434 | def __init__(self, **kwargs): |
|
|
435 | 435 | |
|
|
436 | 436 | Operation.__init__(self, **kwargs) |
|
|
437 | 437 | |
|
|
438 | 438 | def setup(self, n=None, timeInterval=None, stride=None, overlapping=False, byblock=False): |
|
|
439 | 439 | """ |
|
|
440 | 440 | Set the parameters of the integration class. |
|
|
441 | 441 | |
|
|
442 | 442 | Inputs: |
|
|
443 | 443 | |
|
|
444 | 444 | n : Number of coherent integrations |
|
|
445 | 445 | timeInterval : Time of integration. If the parameter "n" is selected this one does not work |
|
|
446 | 446 | overlapping : |
|
|
447 | 447 | """ |
|
|
448 | 448 | |
|
|
449 | 449 | self.__initime = None |
|
|
450 | 450 | self.__lastdatatime = 0 |
|
|
451 | 451 | self.__buffer = None |
|
|
452 | 452 | self.__dataReady = False |
|
|
453 | 453 | self.byblock = byblock |
|
|
454 | 454 | self.stride = stride |
|
|
455 | 455 | |
|
|
456 | 456 | if n == None and timeInterval == None: |
|
|
457 | 457 | raise ValueError("n or timeInterval should be specified ...") |
|
|
458 | 458 | |
|
|
459 | 459 | if n != None: |
|
|
460 | 460 | self.n = n |
|
|
461 | 461 | self.__byTime = False |
|
|
462 | 462 | else: |
|
|
463 | 463 | self.__integrationtime = timeInterval #* 60. #if (type(timeInterval)!=integer) -> change this line |
|
|
464 | 464 | self.n = 9999 |
|
|
465 | 465 | self.__byTime = True |
|
|
466 | 466 | |
|
|
467 | 467 | if overlapping: |
|
|
468 | 468 | self.__withOverlapping = True |
|
|
469 | 469 | self.__buffer = None |
|
|
470 | 470 | else: |
|
|
471 | 471 | self.__withOverlapping = False |
|
|
472 | 472 | self.__buffer = 0 |
|
|
473 | 473 | |
|
|
474 | 474 | self.__profIndex = 0 |
|
|
475 | 475 | |
|
|
476 | 476 | def putData(self, data): |
|
|
477 | 477 | |
|
|
478 | 478 | """ |
|
|
479 | 479 | Add a profile to the __buffer and increase in one the __profileIndex |
|
|
480 | 480 | |
|
|
481 | 481 | """ |
|
|
482 | 482 | |
|
|
483 | 483 | if not self.__withOverlapping: |
|
|
484 | 484 | self.__buffer += data.copy() |
|
|
485 | 485 | self.__profIndex += 1 |
|
|
486 | 486 | return |
|
|
487 | 487 | |
|
|
488 | 488 | #Overlapping data |
|
|
489 | 489 | nChannels, nHeis = data.shape |
|
|
490 | 490 | data = numpy.reshape(data, (1, nChannels, nHeis)) |
|
|
491 | 491 | |
|
|
492 | 492 | #If the buffer is empty then it takes the data value |
|
|
493 | 493 | if self.__buffer is None: |
|
|
494 | 494 | self.__buffer = data |
|
|
495 | 495 | self.__profIndex += 1 |
|
|
496 | 496 | return |
|
|
497 | 497 | |
|
|
498 | 498 | #If the buffer length is lower than n then stakcing the data value |
|
|
499 | 499 | if self.__profIndex < self.n: |
|
|
500 | 500 | self.__buffer = numpy.vstack((self.__buffer, data)) |
|
|
501 | 501 | self.__profIndex += 1 |
|
|
502 | 502 | return |
|
|
503 | 503 | |
|
|
504 | 504 | #If the buffer length is equal to n then replacing the last buffer value with the data value |
|
|
505 | 505 | self.__buffer = numpy.roll(self.__buffer, -1, axis=0) |
|
|
506 | 506 | self.__buffer[self.n-1] = data |
|
|
507 | 507 | self.__profIndex = self.n |
|
|
508 | 508 | return |
|
|
509 | 509 | |
|
|
510 | 510 | |
|
|
511 | 511 | def pushData(self): |
|
|
512 | 512 | """ |
|
|
513 | 513 | Return the sum of the last profiles and the profiles used in the sum. |
|
|
514 | 514 | |
|
|
515 | 515 | Affected: |
|
|
516 | 516 | |
|
|
517 | 517 | self.__profileIndex |
|
|
518 | 518 | |
|
|
519 | 519 | """ |
|
|
520 | 520 | |
|
|
521 | 521 | if not self.__withOverlapping: |
|
|
522 | 522 | data = self.__buffer |
|
|
523 | 523 | n = self.__profIndex |
|
|
524 | 524 | |
|
|
525 | 525 | self.__buffer = 0 |
|
|
526 | 526 | self.__profIndex = 0 |
|
|
527 | 527 | |
|
|
528 | 528 | return data, n |
|
|
529 | 529 | |
|
|
530 | 530 | #Integration with Overlapping |
|
|
531 | 531 | data = numpy.sum(self.__buffer, axis=0) |
|
|
532 | 532 | # print data |
|
|
533 | 533 | # raise |
|
|
534 | 534 | n = self.__profIndex |
|
|
535 | 535 | |
|
|
536 | 536 | return data, n |
|
|
537 | 537 | |
|
|
538 | 538 | def byProfiles(self, data): |
|
|
539 | 539 | |
|
|
540 | 540 | self.__dataReady = False |
|
|
541 | 541 | avgdata = None |
|
|
542 | 542 | # n = None |
|
|
543 | 543 | # print data |
|
|
544 | 544 | # raise |
|
|
545 | 545 | self.putData(data) |
|
|
546 | 546 | |
|
|
547 | 547 | if self.__profIndex == self.n: |
|
|
548 | 548 | avgdata, n = self.pushData() |
|
|
549 | 549 | self.__dataReady = True |
|
|
550 | 550 | |
|
|
551 | 551 | return avgdata |
|
|
552 | 552 | |
|
|
553 | 553 | def byTime(self, data, datatime): |
|
|
554 | 554 | |
|
|
555 | 555 | self.__dataReady = False |
|
|
556 | 556 | avgdata = None |
|
|
557 | 557 | n = None |
|
|
558 | 558 | |
|
|
559 | 559 | self.putData(data) |
|
|
560 | 560 | |
|
|
561 | 561 | if (datatime - self.__initime) >= self.__integrationtime: |
|
|
562 | 562 | avgdata, n = self.pushData() |
|
|
563 | 563 | self.n = n |
|
|
564 | 564 | self.__dataReady = True |
|
|
565 | 565 | |
|
|
566 | 566 | return avgdata |
|
|
567 | 567 | |
|
|
568 | 568 | def integrateByStride(self, data, datatime): |
|
|
569 | 569 | # print data |
|
|
570 | 570 | if self.__profIndex == 0: |
|
|
571 | 571 | self.__buffer = [[data.copy(), datatime]] |
|
|
572 | 572 | else: |
|
|
573 | 573 | self.__buffer.append([data.copy(),datatime]) |
|
|
574 | 574 | self.__profIndex += 1 |
|
|
575 | 575 | self.__dataReady = False |
|
|
576 | 576 | |
|
|
577 | 577 | if self.__profIndex == self.n * self.stride : |
|
|
578 | 578 | self.__dataToPutStride = True |
|
|
579 | 579 | self.__profIndexStride = 0 |
|
|
580 | 580 | self.__profIndex = 0 |
|
|
581 | 581 | self.__bufferStride = [] |
|
|
582 | 582 | for i in range(self.stride): |
|
|
583 | 583 | current = self.__buffer[i::self.stride] |
|
|
584 | 584 | data = numpy.sum([t[0] for t in current], axis=0) |
|
|
585 | 585 | avgdatatime = numpy.average([t[1] for t in current]) |
|
|
586 | 586 | # print data |
|
|
587 | 587 | self.__bufferStride.append((data, avgdatatime)) |
|
|
588 | 588 | |
|
|
589 | 589 | if self.__dataToPutStride: |
|
|
590 | 590 | self.__dataReady = True |
|
|
591 | 591 | self.__profIndexStride += 1 |
|
|
592 | 592 | if self.__profIndexStride == self.stride: |
|
|
593 | 593 | self.__dataToPutStride = False |
|
|
594 | 594 | # print self.__bufferStride[self.__profIndexStride - 1] |
|
|
595 | 595 | # raise |
|
|
596 | 596 | return self.__bufferStride[self.__profIndexStride - 1] |
|
|
597 | 597 | |
|
|
598 | 598 | |
|
|
599 | 599 | return None, None |
|
|
600 | 600 | |
|
|
601 | 601 | def integrate(self, data, datatime=None): |
|
|
602 | 602 | |
|
|
603 | 603 | if self.__initime == None: |
|
|
604 | 604 | self.__initime = datatime |
|
|
605 | 605 | |
|
|
606 | 606 | if self.__byTime: |
|
|
607 | 607 | avgdata = self.byTime(data, datatime) |
|
|
608 | 608 | else: |
|
|
609 | 609 | avgdata = self.byProfiles(data) |
|
|
610 | 610 | |
|
|
611 | 611 | |
|
|
612 | 612 | self.__lastdatatime = datatime |
|
|
613 | 613 | |
|
|
614 | 614 | if avgdata is None: |
|
|
615 | 615 | return None, None |
|
|
616 | 616 | |
|
|
617 | 617 | avgdatatime = self.__initime |
|
|
618 | 618 | |
|
|
619 | 619 | deltatime = datatime - self.__lastdatatime |
|
|
620 | 620 | |
|
|
621 | 621 | if not self.__withOverlapping: |
|
|
622 | 622 | self.__initime = datatime |
|
|
623 | 623 | else: |
|
|
624 | 624 | self.__initime += deltatime |
|
|
625 | 625 | |
|
|
626 | 626 | return avgdata, avgdatatime |
|
|
627 | 627 | |
|
|
628 | 628 | def integrateByBlock(self, dataOut): |
|
|
629 | 629 | |
|
|
630 | 630 | times = int(dataOut.data.shape[1]/self.n) |
|
|
631 | 631 | avgdata = numpy.zeros((dataOut.nChannels, times, dataOut.nHeights), dtype=numpy.complex) |
|
|
632 | 632 | |
|
|
633 | 633 | id_min = 0 |
|
|
634 | 634 | id_max = self.n |
|
|
635 | 635 | |
|
|
636 | 636 | for i in range(times): |
|
|
637 | 637 | junk = dataOut.data[:,id_min:id_max,:] |
|
|
638 | 638 | avgdata[:,i,:] = junk.sum(axis=1) |
|
|
639 | 639 | id_min += self.n |
|
|
640 | 640 | id_max += self.n |
|
|
641 | 641 | |
|
|
642 | 642 | timeInterval = dataOut.ippSeconds*self.n |
|
|
643 | 643 | avgdatatime = (times - 1) * timeInterval + dataOut.utctime |
|
|
644 | 644 | self.__dataReady = True |
|
|
645 | 645 | return avgdata, avgdatatime |
|
|
646 | 646 | |
|
|
647 | 647 | def run(self, dataOut, n=None, timeInterval=None, stride=None, overlapping=False, byblock=False, **kwargs): |
|
|
648 | 648 | |
|
|
649 | 649 | if not self.isConfig: |
|
|
650 | 650 | self.setup(n=n, stride=stride, timeInterval=timeInterval, overlapping=overlapping, byblock=byblock, **kwargs) |
|
|
651 | 651 | self.isConfig = True |
|
|
652 | 652 | |
|
|
653 | 653 | if dataOut.flagDataAsBlock: |
|
|
654 | 654 | """ |
|
|
655 | 655 | Si la data es leida por bloques, dimension = [nChannels, nProfiles, nHeis] |
|
|
656 | 656 | """ |
|
|
657 | 657 | avgdata, avgdatatime = self.integrateByBlock(dataOut) |
|
|
658 | 658 | dataOut.nProfiles /= self.n |
|
|
659 | 659 | else: |
|
|
660 | 660 | if stride is None: |
|
|
661 | 661 | avgdata, avgdatatime = self.integrate(dataOut.data, dataOut.utctime) |
|
|
662 | 662 | else: |
|
|
663 | 663 | avgdata, avgdatatime = self.integrateByStride(dataOut.data, dataOut.utctime) |
|
|
664 | 664 | |
|
|
665 | 665 | |
|
|
666 | 666 | # dataOut.timeInterval *= n |
|
|
667 | 667 | dataOut.flagNoData = True |
|
|
668 | 668 | |
|
|
669 | 669 | if self.__dataReady: |
|
|
670 | 670 | dataOut.data = avgdata |
|
|
671 | 671 | if not dataOut.flagCohInt: |
|
|
672 | 672 | dataOut.nCohInt *= self.n |
|
|
673 | 673 | dataOut.flagCohInt = True |
|
|
674 | 674 | dataOut.utctime = avgdatatime |
|
|
675 | 675 | # print avgdata, avgdatatime |
|
|
676 | 676 | # raise |
|
|
677 | 677 | # dataOut.timeInterval = dataOut.ippSeconds * dataOut.nCohInt |
|
|
678 | 678 | dataOut.flagNoData = False |
|
|
679 | 679 | return dataOut |
|
|
680 | 680 | |
|
|
681 | 681 | class Decoder(Operation): |
|
|
682 | 682 | |
|
|
683 | 683 | isConfig = False |
|
|
684 | 684 | __profIndex = 0 |
|
|
685 | 685 | |
|
|
686 | 686 | code = None |
|
|
687 | 687 | |
|
|
688 | 688 | nCode = None |
|
|
689 | 689 | nBaud = None |
|
|
690 | 690 | |
|
|
691 | 691 | def __init__(self, **kwargs): |
|
|
692 | 692 | |
|
|
693 | 693 | Operation.__init__(self, **kwargs) |
|
|
694 | 694 | |
|
|
695 | 695 | self.times = None |
|
|
696 | 696 | self.osamp = None |
|
|
697 | 697 | # self.__setValues = False |
|
|
698 | 698 | self.isConfig = False |
|
|
699 | 699 | self.setupReq = False |
|
|
700 | 700 | def setup(self, code, osamp, dataOut): |
|
|
701 | 701 | |
|
|
702 | 702 | self.__profIndex = 0 |
|
|
703 | 703 | |
|
|
704 | 704 | self.code = code |
|
|
705 | 705 | |
|
|
706 | 706 | self.nCode = len(code) |
|
|
707 | 707 | self.nBaud = len(code[0]) |
|
|
708 | 708 | |
|
|
709 | 709 | if (osamp != None) and (osamp >1): |
|
|
710 | 710 | self.osamp = osamp |
|
|
711 | 711 | self.code = numpy.repeat(code, repeats=self.osamp, axis=1) |
|
|
712 | 712 | self.nBaud = self.nBaud*self.osamp |
|
|
713 | 713 | |
|
|
714 | 714 | self.__nChannels = dataOut.nChannels |
|
|
715 | 715 | self.__nProfiles = dataOut.nProfiles |
|
|
716 | 716 | self.__nHeis = dataOut.nHeights |
|
|
717 | 717 | |
|
|
718 | 718 | if self.__nHeis < self.nBaud: |
|
|
719 | 719 | raise ValueError('Number of heights (%d) should be greater than number of bauds (%d)' %(self.__nHeis, self.nBaud)) |
|
|
720 | 720 | |
|
|
721 | 721 | #Frequency |
|
|
722 | 722 | __codeBuffer = numpy.zeros((self.nCode, self.__nHeis), dtype=numpy.complex) |
|
|
723 | 723 | |
|
|
724 | 724 | __codeBuffer[:,0:self.nBaud] = self.code |
|
|
725 | 725 | |
|
|
726 | 726 | self.fft_code = numpy.conj(numpy.fft.fft(__codeBuffer, axis=1)) |
|
|
727 | 727 | |
|
|
728 | 728 | if dataOut.flagDataAsBlock: |
|
|
729 | 729 | |
|
|
730 | 730 | self.ndatadec = self.__nHeis #- self.nBaud + 1 |
|
|
731 | 731 | |
|
|
732 | 732 | self.datadecTime = numpy.zeros((self.__nChannels, self.__nProfiles, self.ndatadec), dtype=numpy.complex) |
|
|
733 | 733 | |
|
|
734 | 734 | else: |
|
|
735 | 735 | |
|
|
736 | 736 | #Time |
|
|
737 | 737 | self.ndatadec = self.__nHeis #- self.nBaud + 1 |
|
|
738 | 738 | |
|
|
739 | 739 | self.datadecTime = numpy.zeros((self.__nChannels, self.ndatadec), dtype=numpy.complex) |
|
|
740 | 740 | |
|
|
741 | 741 | def __convolutionInFreq(self, data): |
|
|
742 | 742 | |
|
|
743 | 743 | fft_code = self.fft_code[self.__profIndex].reshape(1,-1) |
|
|
744 | 744 | |
|
|
745 | 745 | fft_data = numpy.fft.fft(data, axis=1) |
|
|
746 | 746 | |
|
|
747 | 747 | conv = fft_data*fft_code |
|
|
748 | 748 | |
|
|
749 | 749 | data = numpy.fft.ifft(conv,axis=1) |
|
|
750 | 750 | |
|
|
751 | 751 | return data |
|
|
752 | 752 | |
|
|
753 | 753 | def __convolutionInFreqOpt(self, data): |
|
|
754 | 754 | |
|
|
755 | 755 | raise NotImplementedError |
|
|
756 | 756 | |
|
|
757 | 757 | def __convolutionInTime(self, data): |
|
|
758 | 758 | |
|
|
759 | 759 | code = self.code[self.__profIndex] |
|
|
760 | 760 | for i in range(self.__nChannels): |
|
|
761 | 761 | self.datadecTime[i,:] = numpy.correlate(data[i,:], code, mode='full')[self.nBaud-1:] |
|
|
762 | 762 | |
|
|
763 | 763 | return self.datadecTime |
|
|
764 | 764 | |
|
|
765 | 765 | def __convolutionByBlockInTime(self, data): |
|
|
766 | 766 | |
|
|
767 | 767 | repetitions = int(self.__nProfiles / self.nCode) |
|
|
768 | 768 | junk = numpy.lib.stride_tricks.as_strided(self.code, (repetitions, self.code.size), (0, self.code.itemsize)) |
|
|
769 | 769 | junk = junk.flatten() |
|
|
770 | 770 | code_block = numpy.reshape(junk, (self.nCode*repetitions, self.nBaud)) |
|
|
771 | 771 | profilesList = range(self.__nProfiles) |
|
|
772 | 772 | |
|
|
773 | 773 | for i in range(self.__nChannels): |
|
|
774 | 774 | for j in profilesList: |
|
|
775 | 775 | self.datadecTime[i,j,:] = numpy.correlate(data[i,j,:], code_block[j,:], mode='full')[self.nBaud-1:] |
|
|
776 | 776 | return self.datadecTime |
|
|
777 | 777 | |
|
|
778 | 778 | def __convolutionByBlockInFreq(self, data): |
|
|
779 | 779 | |
|
|
780 | 780 | raise NotImplementedError("Decoder by frequency fro Blocks not implemented") |
|
|
781 | 781 | |
|
|
782 | 782 | |
|
|
783 | 783 | fft_code = self.fft_code[self.__profIndex].reshape(1,-1) |
|
|
784 | 784 | |
|
|
785 | 785 | fft_data = numpy.fft.fft(data, axis=2) |
|
|
786 | 786 | |
|
|
787 | 787 | conv = fft_data*fft_code |
|
|
788 | 788 | |
|
|
789 | 789 | data = numpy.fft.ifft(conv,axis=2) |
|
|
790 | 790 | |
|
|
791 | 791 | return data |
|
|
792 | 792 | |
|
|
793 | 793 | |
|
|
794 | 794 | def run(self, dataOut, code=None, nCode=None, nBaud=None, mode = 0, osamp=None, times=None): |
|
|
795 | 795 | |
|
|
796 | 796 | if dataOut.flagDecodeData: |
|
|
797 | 797 | print("This data is already decoded, recoding again ...") |
|
|
798 | 798 | |
|
|
799 | 799 | if not self.isConfig: |
|
|
800 | 800 | |
|
|
801 | 801 | if code is None: |
|
|
802 | 802 | if dataOut.code is None: |
|
|
803 | 803 | raise ValueError("Code could not be read from %s instance. Enter a value in Code parameter" %dataOut.type) |
|
|
804 | 804 | |
|
|
805 | 805 | code = dataOut.code |
|
|
806 | 806 | else: |
|
|
807 | 807 | code = numpy.array(code).reshape(nCode,nBaud) |
|
|
808 | 808 | self.setup(code, osamp, dataOut) |
|
|
809 | 809 | |
|
|
810 | 810 | self.isConfig = True |
|
|
811 | 811 | |
|
|
812 | 812 | if mode == 3: |
|
|
813 | 813 | sys.stderr.write("Decoder Warning: mode=%d is not valid, using mode=0\n" %mode) |
|
|
814 | 814 | |
|
|
815 | 815 | if times != None: |
|
|
816 | 816 | sys.stderr.write("Decoder Warning: Argument 'times' in not used anymore\n") |
|
|
817 | 817 | |
|
|
818 | 818 | if self.code is None: |
|
|
819 | 819 | print("Fail decoding: Code is not defined.") |
|
|
820 | 820 | return |
|
|
821 | 821 | |
|
|
822 | 822 | self.__nProfiles = dataOut.nProfiles |
|
|
823 | 823 | datadec = None |
|
|
824 | 824 | |
|
|
825 | 825 | if mode == 3: |
|
|
826 | 826 | mode = 0 |
|
|
827 | 827 | |
|
|
828 | 828 | if dataOut.flagDataAsBlock: |
|
|
829 | 829 | """ |
|
|
830 | 830 | Decoding when data have been read as block, |
|
|
831 | 831 | """ |
|
|
832 | 832 | |
|
|
833 | 833 | if mode == 0: |
|
|
834 | 834 | datadec = self.__convolutionByBlockInTime(dataOut.data) |
|
|
835 | 835 | if mode == 1: |
|
|
836 | 836 | datadec = self.__convolutionByBlockInFreq(dataOut.data) |
|
|
837 | 837 | else: |
|
|
838 | 838 | """ |
|
|
839 | 839 | Decoding when data have been read profile by profile |
|
|
840 | 840 | """ |
|
|
841 | 841 | if mode == 0: |
|
|
842 | 842 | datadec = self.__convolutionInTime(dataOut.data) |
|
|
843 | 843 | |
|
|
844 | 844 | if mode == 1: |
|
|
845 | 845 | datadec = self.__convolutionInFreq(dataOut.data) |
|
|
846 | 846 | |
|
|
847 | 847 | if mode == 2: |
|
|
848 | 848 | datadec = self.__convolutionInFreqOpt(dataOut.data) |
|
|
849 | 849 | |
|
|
850 | 850 | if datadec is None: |
|
|
851 | 851 | raise ValueError("Codification mode selected is not valid: mode=%d. Try selecting 0 or 1" %mode) |
|
|
852 | 852 | |
|
|
853 | 853 | dataOut.code = self.code |
|
|
854 | 854 | dataOut.nCode = self.nCode |
|
|
855 | 855 | dataOut.nBaud = self.nBaud |
|
|
856 | 856 | |
|
|
857 | 857 | dataOut.data = datadec |
|
|
858 | 858 | |
|
|
859 | 859 | dataOut.heightList = dataOut.heightList[0:datadec.shape[-1]] |
|
|
860 | 860 | |
|
|
861 | 861 | dataOut.flagDecodeData = True #asumo q la data esta decodificada |
|
|
862 | 862 | |
|
|
863 | 863 | if self.__profIndex == self.nCode-1: |
|
|
864 | 864 | self.__profIndex = 0 |
|
|
865 | 865 | return dataOut |
|
|
866 | 866 | |
|
|
867 | 867 | self.__profIndex += 1 |
|
|
868 | 868 | |
|
|
869 | 869 | return dataOut |
|
|
870 | 870 | # dataOut.flagDeflipData = True #asumo q la data no esta sin flip |
|
|
871 | 871 | |
|
|
872 | 872 | |
|
|
873 | 873 | class ProfileConcat(Operation): |
|
|
874 | 874 | |
|
|
875 | 875 | isConfig = False |
|
|
876 | 876 | buffer = None |
|
|
877 | 877 | |
|
|
878 | 878 | def __init__(self, **kwargs): |
|
|
879 | 879 | |
|
|
880 | 880 | Operation.__init__(self, **kwargs) |
|
|
881 | 881 | self.profileIndex = 0 |
|
|
882 | 882 | |
|
|
883 | 883 | def reset(self): |
|
|
884 | 884 | self.buffer = numpy.zeros_like(self.buffer) |
|
|
885 | 885 | self.start_index = 0 |
|
|
886 | 886 | self.times = 1 |
|
|
887 | 887 | |
|
|
888 | 888 | def setup(self, data, m, n=1): |
|
|
889 | 889 | self.buffer = numpy.zeros((data.shape[0],data.shape[1]*m),dtype=type(data[0,0])) |
|
|
890 | 890 | self.nHeights = data.shape[1]#.nHeights |
|
|
891 | 891 | self.start_index = 0 |
|
|
892 | 892 | self.times = 1 |
|
|
893 | 893 | |
|
|
894 | 894 | def concat(self, data): |
|
|
895 | 895 | |
|
|
896 | 896 | self.buffer[:,self.start_index:self.nHeights*self.times] = data.copy() |
|
|
897 | 897 | self.start_index = self.start_index + self.nHeights |
|
|
898 | 898 | |
|
|
899 | 899 | def run(self, dataOut, m): |
|
|
900 | 900 | dataOut.flagNoData = True |
|
|
901 | 901 | |
|
|
902 | 902 | if not self.isConfig: |
|
|
903 | 903 | self.setup(dataOut.data, m, 1) |
|
|
904 | 904 | self.isConfig = True |
|
|
905 | 905 | |
|
|
906 | 906 | if dataOut.flagDataAsBlock: |
|
|
907 | 907 | raise ValueError("ProfileConcat can only be used when voltage have been read profile by profile, getBlock = False") |
|
|
908 | 908 | |
|
|
909 | 909 | else: |
|
|
910 | 910 | self.concat(dataOut.data) |
|
|
911 | 911 | self.times += 1 |
|
|
912 | 912 | if self.times > m: |
|
|
913 | 913 | dataOut.data = self.buffer |
|
|
914 | 914 | self.reset() |
|
|
915 | 915 | dataOut.flagNoData = False |
|
|
916 | 916 | # se deben actualizar mas propiedades del header y del objeto dataOut, por ejemplo, las alturas |
|
|
917 | 917 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
|
918 | 918 | xf = dataOut.heightList[0] + dataOut.nHeights * deltaHeight * m |
|
|
919 | 919 | dataOut.heightList = numpy.arange(dataOut.heightList[0], xf, deltaHeight) |
|
|
920 | 920 | dataOut.ippSeconds *= m |
|
|
921 | 921 | return dataOut |
|
|
922 | 922 | |
|
|
923 | 923 | class ProfileSelector(Operation): |
|
|
924 | 924 | |
|
|
925 | 925 | profileIndex = None |
|
|
926 | 926 | # Tamanho total de los perfiles |
|
|
927 | 927 | nProfiles = None |
|
|
928 | 928 | |
|
|
929 | 929 | def __init__(self, **kwargs): |
|
|
930 | 930 | |
|
|
931 | 931 | Operation.__init__(self, **kwargs) |
|
|
932 | 932 | self.profileIndex = 0 |
|
|
933 | 933 | |
|
|
934 | 934 | def incProfileIndex(self): |
|
|
935 | 935 | |
|
|
936 | 936 | self.profileIndex += 1 |
|
|
937 | 937 | |
|
|
938 | 938 | if self.profileIndex >= self.nProfiles: |
|
|
939 | 939 | self.profileIndex = 0 |
|
|
940 | 940 | |
|
|
941 | 941 | def isThisProfileInRange(self, profileIndex, minIndex, maxIndex): |
|
|
942 | 942 | |
|
|
943 | 943 | if profileIndex < minIndex: |
|
|
944 | 944 | return False |
|
|
945 | 945 | |
|
|
946 | 946 | if profileIndex > maxIndex: |
|
|
947 | 947 | return False |
|
|
948 | 948 | |
|
|
949 | 949 | return True |
|
|
950 | 950 | |
|
|
951 | 951 | def isThisProfileInList(self, profileIndex, profileList): |
|
|
952 | 952 | |
|
|
953 | 953 | if profileIndex not in profileList: |
|
|
954 | 954 | return False |
|
|
955 | 955 | |
|
|
956 | 956 | return True |
|
|
957 | 957 | |
|
|
958 | 958 | def run(self, dataOut, profileList=None, profileRangeList=None, beam=None, byblock=False, rangeList = None, nProfiles=None): |
|
|
959 | 959 | |
|
|
960 | 960 | """ |
|
|
961 | 961 | ProfileSelector: |
|
|
962 | 962 | |
|
|
963 | 963 | Inputs: |
|
|
964 | 964 | profileList : Index of profiles selected. Example: profileList = (0,1,2,7,8) |
|
|
965 | 965 | |
|
|
966 | 966 | profileRangeList : Minimum and maximum profile indexes. Example: profileRangeList = (4, 30) |
|
|
967 | 967 | |
|
|
968 | 968 | rangeList : List of profile ranges. Example: rangeList = ((4, 30), (32, 64), (128, 256)) |
|
|
969 | 969 | |
|
|
970 | 970 | """ |
|
|
971 | 971 | |
|
|
972 | 972 | if rangeList is not None: |
|
|
973 | 973 | if type(rangeList[0]) not in (tuple, list): |
|
|
974 | 974 | rangeList = [rangeList] |
|
|
975 | 975 | |
|
|
976 | 976 | dataOut.flagNoData = True |
|
|
977 | 977 | |
|
|
978 | 978 | if dataOut.flagDataAsBlock: |
|
|
979 | 979 | """ |
|
|
980 | 980 | data dimension = [nChannels, nProfiles, nHeis] |
|
|
981 | 981 | """ |
|
|
982 | 982 | if profileList != None: |
|
|
983 | 983 | dataOut.data = dataOut.data[:,profileList,:] |
|
|
984 | 984 | |
|
|
985 | 985 | if profileRangeList != None: |
|
|
986 | 986 | minIndex = profileRangeList[0] |
|
|
987 | 987 | maxIndex = profileRangeList[1] |
|
|
988 | 988 | profileList = list(range(minIndex, maxIndex+1)) |
|
|
989 | 989 | |
|
|
990 | 990 | dataOut.data = dataOut.data[:,minIndex:maxIndex+1,:] |
|
|
991 | 991 | |
|
|
992 | 992 | if rangeList != None: |
|
|
993 | 993 | |
|
|
994 | 994 | profileList = [] |
|
|
995 | 995 | |
|
|
996 | 996 | for thisRange in rangeList: |
|
|
997 | 997 | minIndex = thisRange[0] |
|
|
998 | 998 | maxIndex = thisRange[1] |
|
|
999 | 999 | |
|
|
1000 | 1000 | profileList.extend(list(range(minIndex, maxIndex+1))) |
|
|
1001 | 1001 | |
|
|
1002 | 1002 | dataOut.data = dataOut.data[:,profileList,:] |
|
|
1003 | 1003 | |
|
|
1004 | 1004 | dataOut.nProfiles = len(profileList) |
|
|
1005 | 1005 | dataOut.profileIndex = dataOut.nProfiles - 1 |
|
|
1006 | 1006 | dataOut.flagNoData = False |
|
|
1007 | 1007 | |
|
|
1008 | 1008 | return dataOut |
|
|
1009 | 1009 | |
|
|
1010 | 1010 | """ |
|
|
1011 | 1011 | data dimension = [nChannels, nHeis] |
|
|
1012 | 1012 | """ |
|
|
1013 | 1013 | |
|
|
1014 | 1014 | if profileList != None: |
|
|
1015 | 1015 | |
|
|
1016 | 1016 | if self.isThisProfileInList(dataOut.profileIndex, profileList): |
|
|
1017 | 1017 | |
|
|
1018 | 1018 | self.nProfiles = len(profileList) |
|
|
1019 | 1019 | dataOut.nProfiles = self.nProfiles |
|
|
1020 | 1020 | dataOut.profileIndex = self.profileIndex |
|
|
1021 | 1021 | dataOut.flagNoData = False |
|
|
1022 | 1022 | |
|
|
1023 | 1023 | self.incProfileIndex() |
|
|
1024 | 1024 | return dataOut |
|
|
1025 | 1025 | |
|
|
1026 | 1026 | if profileRangeList != None: |
|
|
1027 | 1027 | |
|
|
1028 | 1028 | minIndex = profileRangeList[0] |
|
|
1029 | 1029 | maxIndex = profileRangeList[1] |
|
|
1030 | 1030 | |
|
|
1031 | 1031 | if self.isThisProfileInRange(dataOut.profileIndex, minIndex, maxIndex): |
|
|
1032 | 1032 | |
|
|
1033 | 1033 | self.nProfiles = maxIndex - minIndex + 1 |
|
|
1034 | 1034 | dataOut.nProfiles = self.nProfiles |
|
|
1035 | 1035 | dataOut.profileIndex = self.profileIndex |
|
|
1036 | 1036 | dataOut.flagNoData = False |
|
|
1037 | 1037 | |
|
|
1038 | 1038 | self.incProfileIndex() |
|
|
1039 | 1039 | return dataOut |
|
|
1040 | 1040 | |
|
|
1041 | 1041 | if rangeList != None: |
|
|
1042 | 1042 | |
|
|
1043 | 1043 | nProfiles = 0 |
|
|
1044 | 1044 | |
|
|
1045 | 1045 | for thisRange in rangeList: |
|
|
1046 | 1046 | minIndex = thisRange[0] |
|
|
1047 | 1047 | maxIndex = thisRange[1] |
|
|
1048 | 1048 | |
|
|
1049 | 1049 | nProfiles += maxIndex - minIndex + 1 |
|
|
1050 | 1050 | |
|
|
1051 | 1051 | for thisRange in rangeList: |
|
|
1052 | 1052 | |
|
|
1053 | 1053 | minIndex = thisRange[0] |
|
|
1054 | 1054 | maxIndex = thisRange[1] |
|
|
1055 | 1055 | |
|
|
1056 | 1056 | if self.isThisProfileInRange(dataOut.profileIndex, minIndex, maxIndex): |
|
|
1057 | 1057 | |
|
|
1058 | 1058 | self.nProfiles = nProfiles |
|
|
1059 | 1059 | dataOut.nProfiles = self.nProfiles |
|
|
1060 | 1060 | dataOut.profileIndex = self.profileIndex |
|
|
1061 | 1061 | dataOut.flagNoData = False |
|
|
1062 | 1062 | |
|
|
1063 | 1063 | self.incProfileIndex() |
|
|
1064 | 1064 | |
|
|
1065 | 1065 | break |
|
|
1066 | 1066 | |
|
|
1067 | 1067 | return dataOut |
|
|
1068 | 1068 | |
|
|
1069 | 1069 | |
|
|
1070 | 1070 | if beam != None: #beam is only for AMISR data |
|
|
1071 | 1071 | if self.isThisProfileInList(dataOut.profileIndex, dataOut.beamRangeDict[beam]): |
|
|
1072 | 1072 | dataOut.flagNoData = False |
|
|
1073 | 1073 | dataOut.profileIndex = self.profileIndex |
|
|
1074 | 1074 | |
|
|
1075 | 1075 | self.incProfileIndex() |
|
|
1076 | 1076 | |
|
|
1077 | 1077 | return dataOut |
|
|
1078 | 1078 | |
|
|
1079 | 1079 | raise ValueError("ProfileSelector needs profileList, profileRangeList or rangeList parameter") |
|
|
1080 | 1080 | |
|
|
1081 | 1081 | |
|
|
1082 | 1082 | class Reshaper(Operation): |
|
|
1083 | 1083 | |
|
|
1084 | 1084 | def __init__(self, **kwargs): |
|
|
1085 | 1085 | |
|
|
1086 | 1086 | Operation.__init__(self, **kwargs) |
|
|
1087 | 1087 | |
|
|
1088 | 1088 | self.__buffer = None |
|
|
1089 | 1089 | self.__nitems = 0 |
|
|
1090 | 1090 | |
|
|
1091 | 1091 | def __appendProfile(self, dataOut, nTxs): |
|
|
1092 | 1092 | |
|
|
1093 | 1093 | if self.__buffer is None: |
|
|
1094 | 1094 | shape = (dataOut.nChannels, int(dataOut.nHeights/nTxs) ) |
|
|
1095 | 1095 | self.__buffer = numpy.empty(shape, dtype = dataOut.data.dtype) |
|
|
1096 | 1096 | |
|
|
1097 | 1097 | ini = dataOut.nHeights * self.__nitems |
|
|
1098 | 1098 | end = ini + dataOut.nHeights |
|
|
1099 | 1099 | |
|
|
1100 | 1100 | self.__buffer[:, ini:end] = dataOut.data |
|
|
1101 | 1101 | |
|
|
1102 | 1102 | self.__nitems += 1 |
|
|
1103 | 1103 | |
|
|
1104 | 1104 | return int(self.__nitems*nTxs) |
|
|
1105 | 1105 | |
|
|
1106 | 1106 | def __getBuffer(self): |
|
|
1107 | 1107 | |
|
|
1108 | 1108 | if self.__nitems == int(1./self.__nTxs): |
|
|
1109 | 1109 | |
|
|
1110 | 1110 | self.__nitems = 0 |
|
|
1111 | 1111 | |
|
|
1112 | 1112 | return self.__buffer.copy() |
|
|
1113 | 1113 | |
|
|
1114 | 1114 | return None |
|
|
1115 | 1115 | |
|
|
1116 | 1116 | def __checkInputs(self, dataOut, shape, nTxs): |
|
|
1117 | 1117 | |
|
|
1118 | 1118 | if shape is None and nTxs is None: |
|
|
1119 | 1119 | raise ValueError("Reshaper: shape of factor should be defined") |
|
|
1120 | 1120 | |
|
|
1121 | 1121 | if nTxs: |
|
|
1122 | 1122 | if nTxs < 0: |
|
|
1123 | 1123 | raise ValueError("nTxs should be greater than 0") |
|
|
1124 | 1124 | |
|
|
1125 | 1125 | if nTxs < 1 and dataOut.nProfiles % (1./nTxs) != 0: |
|
|
1126 | 1126 | raise ValueError("nProfiles= %d is not divisibled by (1./nTxs) = %f" %(dataOut.nProfiles, (1./nTxs))) |
|
|
1127 | 1127 | |
|
|
1128 | 1128 | shape = [dataOut.nChannels, dataOut.nProfiles*nTxs, dataOut.nHeights/nTxs] |
|
|
1129 | 1129 | |
|
|
1130 | 1130 | return shape, nTxs |
|
|
1131 | 1131 | |
|
|
1132 | 1132 | if len(shape) != 2 and len(shape) != 3: |
|
|
1133 | 1133 | raise ValueError("shape dimension should be equal to 2 or 3. shape = (nProfiles, nHeis) or (nChannels, nProfiles, nHeis). Actually shape = (%d, %d, %d)" %(dataOut.nChannels, dataOut.nProfiles, dataOut.nHeights)) |
|
|
1134 | 1134 | |
|
|
1135 | 1135 | if len(shape) == 2: |
|
|
1136 | 1136 | shape_tuple = [dataOut.nChannels] |
|
|
1137 | 1137 | shape_tuple.extend(shape) |
|
|
1138 | 1138 | else: |
|
|
1139 | 1139 | shape_tuple = list(shape) |
|
|
1140 | 1140 | |
|
|
1141 | 1141 | nTxs = 1.0*shape_tuple[1]/dataOut.nProfiles |
|
|
1142 | 1142 | |
|
|
1143 | 1143 | return shape_tuple, nTxs |
|
|
1144 | 1144 | |
|
|
1145 | 1145 | def run(self, dataOut, shape=None, nTxs=None): |
|
|
1146 | 1146 | |
|
|
1147 | 1147 | shape_tuple, self.__nTxs = self.__checkInputs(dataOut, shape, nTxs) |
|
|
1148 | 1148 | |
|
|
1149 | 1149 | dataOut.flagNoData = True |
|
|
1150 | 1150 | profileIndex = None |
|
|
1151 | 1151 | |
|
|
1152 | 1152 | if dataOut.flagDataAsBlock: |
|
|
1153 | 1153 | |
|
|
1154 | 1154 | dataOut.data = numpy.reshape(dataOut.data, shape_tuple) |
|
|
1155 | 1155 | dataOut.flagNoData = False |
|
|
1156 | 1156 | |
|
|
1157 | 1157 | profileIndex = int(dataOut.nProfiles*self.__nTxs) - 1 |
|
|
1158 | 1158 | |
|
|
1159 | 1159 | else: |
|
|
1160 | 1160 | |
|
|
1161 | 1161 | if self.__nTxs < 1: |
|
|
1162 | 1162 | |
|
|
1163 | 1163 | self.__appendProfile(dataOut, self.__nTxs) |
|
|
1164 | 1164 | new_data = self.__getBuffer() |
|
|
1165 | 1165 | |
|
|
1166 | 1166 | if new_data is not None: |
|
|
1167 | 1167 | dataOut.data = new_data |
|
|
1168 | 1168 | dataOut.flagNoData = False |
|
|
1169 | 1169 | |
|
|
1170 | 1170 | profileIndex = dataOut.profileIndex*nTxs |
|
|
1171 | 1171 | |
|
|
1172 | 1172 | else: |
|
|
1173 | 1173 | raise ValueError("nTxs should be greater than 0 and lower than 1, or use VoltageReader(..., getblock=True)") |
|
|
1174 | 1174 | |
|
|
1175 | 1175 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
|
1176 | 1176 | |
|
|
1177 | 1177 | dataOut.heightList = numpy.arange(dataOut.nHeights/self.__nTxs) * deltaHeight + dataOut.heightList[0] |
|
|
1178 | 1178 | |
|
|
1179 | 1179 | dataOut.nProfiles = int(dataOut.nProfiles*self.__nTxs) |
|
|
1180 | 1180 | |
|
|
1181 | 1181 | dataOut.profileIndex = profileIndex |
|
|
1182 | 1182 | |
|
|
1183 | 1183 | dataOut.ippSeconds /= self.__nTxs |
|
|
1184 | 1184 | |
|
|
1185 | 1185 | return dataOut |
|
|
1186 | 1186 | |
|
|
1187 | 1187 | class SplitProfiles(Operation): |
|
|
1188 | 1188 | |
|
|
1189 | 1189 | def __init__(self, **kwargs): |
|
|
1190 | 1190 | |
|
|
1191 | 1191 | Operation.__init__(self, **kwargs) |
|
|
1192 | 1192 | |
|
|
1193 | 1193 | def run(self, dataOut, n): |
|
|
1194 | 1194 | |
|
|
1195 | 1195 | dataOut.flagNoData = True |
|
|
1196 | 1196 | profileIndex = None |
|
|
1197 | 1197 | |
|
|
1198 | 1198 | if dataOut.flagDataAsBlock: |
|
|
1199 | 1199 | |
|
|
1200 | 1200 | #nchannels, nprofiles, nsamples |
|
|
1201 | 1201 | shape = dataOut.data.shape |
|
|
1202 | 1202 | |
|
|
1203 | 1203 | if shape[2] % n != 0: |
|
|
1204 | 1204 | raise ValueError("Could not split the data, n=%d has to be multiple of %d" %(n, shape[2])) |
|
|
1205 | 1205 | |
|
|
1206 | 1206 | new_shape = shape[0], shape[1]*n, int(shape[2]/n) |
|
|
1207 | 1207 | |
|
|
1208 | 1208 | dataOut.data = numpy.reshape(dataOut.data, new_shape) |
|
|
1209 | 1209 | dataOut.flagNoData = False |
|
|
1210 | 1210 | |
|
|
1211 | 1211 | profileIndex = int(dataOut.nProfiles/n) - 1 |
|
|
1212 | 1212 | |
|
|
1213 | 1213 | else: |
|
|
1214 | 1214 | |
|
|
1215 | 1215 | raise ValueError("Could not split the data when is read Profile by Profile. Use VoltageReader(..., getblock=True)") |
|
|
1216 | 1216 | |
|
|
1217 | 1217 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
|
1218 | 1218 | |
|
|
1219 | 1219 | dataOut.heightList = numpy.arange(dataOut.nHeights/n) * deltaHeight + dataOut.heightList[0] |
|
|
1220 | 1220 | |
|
|
1221 | 1221 | dataOut.nProfiles = int(dataOut.nProfiles*n) |
|
|
1222 | 1222 | |
|
|
1223 | 1223 | dataOut.profileIndex = profileIndex |
|
|
1224 | 1224 | |
|
|
1225 | 1225 | dataOut.ippSeconds /= n |
|
|
1226 | 1226 | |
|
|
1227 | 1227 | return dataOut |
|
|
1228 | 1228 | |
|
|
1229 | 1229 | class CombineProfiles(Operation): |
|
|
1230 | 1230 | def __init__(self, **kwargs): |
|
|
1231 | 1231 | |
|
|
1232 | 1232 | Operation.__init__(self, **kwargs) |
|
|
1233 | 1233 | |
|
|
1234 | 1234 | self.__remData = None |
|
|
1235 | 1235 | self.__profileIndex = 0 |
|
|
1236 | 1236 | |
|
|
1237 | 1237 | def run(self, dataOut, n): |
|
|
1238 | 1238 | |
|
|
1239 | 1239 | dataOut.flagNoData = True |
|
|
1240 | 1240 | profileIndex = None |
|
|
1241 | 1241 | |
|
|
1242 | 1242 | if dataOut.flagDataAsBlock: |
|
|
1243 | 1243 | |
|
|
1244 | 1244 | #nchannels, nprofiles, nsamples |
|
|
1245 | 1245 | shape = dataOut.data.shape |
|
|
1246 | 1246 | new_shape = shape[0], shape[1]/n, shape[2]*n |
|
|
1247 | 1247 | |
|
|
1248 | 1248 | if shape[1] % n != 0: |
|
|
1249 | 1249 | raise ValueError("Could not split the data, n=%d has to be multiple of %d" %(n, shape[1])) |
|
|
1250 | 1250 | |
|
|
1251 | 1251 | dataOut.data = numpy.reshape(dataOut.data, new_shape) |
|
|
1252 | 1252 | dataOut.flagNoData = False |
|
|
1253 | 1253 | |
|
|
1254 | 1254 | profileIndex = int(dataOut.nProfiles*n) - 1 |
|
|
1255 | 1255 | |
|
|
1256 | 1256 | else: |
|
|
1257 | 1257 | |
|
|
1258 | 1258 | #nchannels, nsamples |
|
|
1259 | 1259 | if self.__remData is None: |
|
|
1260 | 1260 | newData = dataOut.data |
|
|
1261 | 1261 | else: |
|
|
1262 | 1262 | newData = numpy.concatenate((self.__remData, dataOut.data), axis=1) |
|
|
1263 | 1263 | |
|
|
1264 | 1264 | self.__profileIndex += 1 |
|
|
1265 | 1265 | |
|
|
1266 | 1266 | if self.__profileIndex < n: |
|
|
1267 | 1267 | self.__remData = newData |
|
|
1268 | 1268 | #continue |
|
|
1269 | 1269 | return |
|
|
1270 | 1270 | |
|
|
1271 | 1271 | self.__profileIndex = 0 |
|
|
1272 | 1272 | self.__remData = None |
|
|
1273 | 1273 | |
|
|
1274 | 1274 | dataOut.data = newData |
|
|
1275 | 1275 | dataOut.flagNoData = False |
|
|
1276 | 1276 | |
|
|
1277 | 1277 | profileIndex = dataOut.profileIndex/n |
|
|
1278 | 1278 | |
|
|
1279 | 1279 | |
|
|
1280 | 1280 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
|
1281 | 1281 | |
|
|
1282 | 1282 | dataOut.heightList = numpy.arange(dataOut.nHeights*n) * deltaHeight + dataOut.heightList[0] |
|
|
1283 | 1283 | |
|
|
1284 | 1284 | dataOut.nProfiles = int(dataOut.nProfiles/n) |
|
|
1285 | 1285 | |
|
|
1286 | 1286 | dataOut.profileIndex = profileIndex |
|
|
1287 | 1287 | |
|
|
1288 | 1288 | dataOut.ippSeconds *= n |
|
|
1289 | 1289 | |
|
|
1290 | 1290 | return dataOut |
|
|
1291 | 1291 | |
|
|
1292 | 1292 | class PulsePairVoltage(Operation): |
|
|
1293 | 1293 | ''' |
|
|
1294 | 1294 | Function PulsePair(Signal Power, Velocity) |
|
|
1295 | 1295 | The real component of Lag[0] provides Intensity Information |
|
|
1296 | 1296 | The imag component of Lag[1] Phase provides Velocity Information |
|
|
1297 | 1297 | |
|
|
1298 | 1298 | Configuration Parameters: |
|
|
1299 | 1299 | nPRF = Number of Several PRF |
|
|
1300 | 1300 | theta = Degree Azimuth angel Boundaries |
|
|
1301 | 1301 | |
|
|
1302 | 1302 | Input: |
|
|
1303 | 1303 | self.dataOut |
|
|
1304 | 1304 | lag[N] |
|
|
1305 | 1305 | Affected: |
|
|
1306 | 1306 | self.dataOut.spc |
|
|
1307 | 1307 | ''' |
|
|
1308 | 1308 | isConfig = False |
|
|
1309 | 1309 | __profIndex = 0 |
|
|
1310 | 1310 | __initime = None |
|
|
1311 | 1311 | __lastdatatime = None |
|
|
1312 | 1312 | __buffer = None |
|
|
1313 | 1313 | noise = None |
|
|
1314 | 1314 | __dataReady = False |
|
|
1315 | 1315 | n = None |
|
|
1316 | 1316 | __nch = 0 |
|
|
1317 | 1317 | __nHeis = 0 |
|
|
1318 | 1318 | removeDC = False |
|
|
1319 | 1319 | ipp = None |
|
|
1320 | 1320 | lambda_ = 0 |
|
|
1321 | 1321 | |
|
|
1322 | 1322 | def __init__(self,**kwargs): |
|
|
1323 | 1323 | Operation.__init__(self,**kwargs) |
|
|
1324 | 1324 | |
|
|
1325 | 1325 | def setup(self, dataOut, n = None, removeDC=False): |
|
|
1326 | 1326 | ''' |
|
|
1327 | 1327 | n= Numero de PRF's de entrada |
|
|
1328 | 1328 | ''' |
|
|
1329 | 1329 | self.__initime = None |
|
|
1330 | 1330 | self.__lastdatatime = 0 |
|
|
1331 | 1331 | self.__dataReady = False |
|
|
1332 | 1332 | self.__buffer = 0 |
|
|
1333 | 1333 | self.__profIndex = 0 |
|
|
1334 | 1334 | self.noise = None |
|
|
1335 | 1335 | self.__nch = dataOut.nChannels |
|
|
1336 | 1336 | self.__nHeis = dataOut.nHeights |
|
|
1337 | 1337 | self.removeDC = removeDC |
|
|
1338 | 1338 | self.lambda_ = 3.0e8/(9345.0e6) |
|
|
1339 | 1339 | self.ippSec = dataOut.ippSeconds |
|
|
1340 | 1340 | self.nCohInt = dataOut.nCohInt |
|
|
1341 | 1341 | print("IPPseconds",dataOut.ippSeconds) |
|
|
1342 | 1342 | |
|
|
1343 | 1343 | print("ELVALOR DE n es:", n) |
|
|
1344 | 1344 | if n == None: |
|
|
1345 | 1345 | raise ValueError("n should be specified.") |
|
|
1346 | 1346 | |
|
|
1347 | 1347 | if n != None: |
|
|
1348 | 1348 | if n<2: |
|
|
1349 | 1349 | raise ValueError("n should be greater than 2") |
|
|
1350 | 1350 | |
|
|
1351 | 1351 | self.n = n |
|
|
1352 | 1352 | self.__nProf = n |
|
|
1353 | 1353 | |
|
|
1354 | 1354 | self.__buffer = numpy.zeros((dataOut.nChannels, |
|
|
1355 | 1355 | n, |
|
|
1356 | 1356 | dataOut.nHeights), |
|
|
1357 | 1357 | dtype='complex') |
|
|
1358 | #self.noise = numpy.zeros([self.__nch,self.__nHeis]) | |
|
|
1359 | #for i in range(self.__nch): | |
|
|
1360 | # self.noise[i]=dataOut.getNoise(channel=i) | |
|
|
1361 | 1358 | |
|
|
1362 | 1359 | def putData(self,data): |
|
|
1363 | 1360 | ''' |
|
|
1364 | 1361 | Add a profile to he __buffer and increase in one the __profiel Index |
|
|
1365 | 1362 | ''' |
|
|
1366 | 1363 | self.__buffer[:,self.__profIndex,:]= data |
|
|
1367 | 1364 | self.__profIndex += 1 |
|
|
1368 | 1365 | return |
|
|
1369 | 1366 | |
|
|
1370 | 1367 | def pushData(self,dataOut): |
|
|
1371 | 1368 | ''' |
|
|
1372 | 1369 | Return the PULSEPAIR and the profiles used in the operation |
|
|
1373 | 1370 | Affected : self.__profileIndex |
|
|
1374 | 1371 | ''' |
|
|
1372 | #Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· Remove DCΒ·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· | |
|
|
1375 | 1373 | if self.removeDC==True: |
|
|
1376 | 1374 | mean = numpy.mean(self.__buffer,1) |
|
|
1377 | 1375 | tmp = mean.reshape(self.__nch,1,self.__nHeis) |
|
|
1378 | 1376 | dc= numpy.tile(tmp,[1,self.__nProf,1]) |
|
|
1379 | 1377 | self.__buffer = self.__buffer - dc |
|
|
1378 | #Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Calculo de Potencia Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· | |
|
|
1379 | pair0 = self.__buffer*numpy.conj(self.__buffer) | |
|
|
1380 | pair0 = pair0.real | |
|
|
1381 | lag_0 = numpy.sum(pair0,1) | |
|
|
1382 | #Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Calculo de Ruido x canalΒ·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· | |
|
|
1383 | self.noise = numpy.zeros(self.__nch) | |
|
|
1384 | for i in range(self.__nch): | |
|
|
1385 | daux = numpy.sort(pair0[i,:,:],axis= None) | |
|
|
1386 | self.noise[i]=hildebrand_sekhon( daux ,self.nCohInt) | |
|
|
1387 | ||
|
|
1388 | self.noise = self.noise.reshape(self.__nch,1) | |
|
|
1389 | self.noise = numpy.tile(self.noise,[1,self.__nHeis]) | |
|
|
1390 | noise_buffer = self.noise.reshape(self.__nch,1,self.__nHeis) | |
|
|
1391 | noise_buffer = numpy.tile(noise_buffer,[1,self.__nProf,1]) | |
|
|
1392 | #Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· Potencia recibida= P , Potencia senal = S , Ruido= NΒ·Β· | |
|
|
1393 | #Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· P= S+N ,P=lag_0/N Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· | |
|
|
1394 | #Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· Power Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· | |
|
|
1395 | data_power = lag_0/(self.n*self.nCohInt) | |
|
|
1396 | #------------------ Senal Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· | |
|
|
1397 | data_intensity = pair0 - noise_buffer | |
|
|
1398 | data_intensity = numpy.sum(data_intensity,axis=1)*(self.n*self.nCohInt)#*self.nCohInt) | |
|
|
1399 | #data_intensity = (lag_0-self.noise*self.n)*(self.n*self.nCohInt) | |
|
|
1400 | for i in range(self.__nch): | |
|
|
1401 | for j in range(self.__nHeis): | |
|
|
1402 | if data_intensity[i][j] < 0: | |
|
|
1403 | data_intensity[i][j] = numpy.min(numpy.absolute(data_intensity[i][j])) | |
|
|
1380 | 1404 | |
|
|
1381 | lag_0 = numpy.sum(self.__buffer*numpy.conj(self.__buffer),1) | |
|
|
1382 | data_intensity = lag_0/(self.n*self.nCohInt)#*self.nCohInt) | |
|
|
1383 | ||
|
|
1405 | #Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· Calculo de Frecuencia y Velocidad dopplerΒ·Β·Β·Β·Β·Β·Β·Β· | |
|
|
1384 | 1406 | pair1 = self.__buffer[:,:-1,:]*numpy.conjugate(self.__buffer[:,1:,:]) |
|
|
1385 | 1407 | lag_1 = numpy.sum(pair1,1) |
|
|
1386 | #angle = numpy.angle(numpy.sum(pair1,1))*180/(math.pi) | |
|
|
1387 | data_velocity = (-1.0*self.lambda_/(4*math.pi*self.ippSec))*numpy.angle(lag_1)#self.ippSec*self.nCohInt | |
|
|
1408 | data_freq = (-1/(2.0*math.pi*self.ippSec*self.nCohInt))*numpy.angle(lag_1) | |
|
|
1409 | data_velocity = (self.lambda_/2.0)*data_freq | |
|
|
1388 | 1410 | |
|
|
1389 | self.noise = numpy.zeros([self.__nch,self.__nHeis]) | |
|
|
1390 | for i in range(self.__nch): | |
|
|
1391 | self.noise[i]=dataOut.getNoise(channel=i) | |
|
|
1411 | #Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· Potencia promedio estimada de la SenalΒ·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· | |
|
|
1412 | lag_0 = lag_0/self.n | |
|
|
1413 | S = lag_0-self.noise | |
|
|
1392 | 1414 | |
|
|
1393 | lag_0 = lag_0.real/(self.n) | |
|
|
1415 | #Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· Frecuencia Doppler promedio Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· | |
|
|
1394 | 1416 | lag_1 = lag_1/(self.n-1) |
|
|
1395 | 1417 | R1 = numpy.abs(lag_1) |
|
|
1396 | S = (lag_0-self.noise) | |
|
|
1397 | 1418 | |
|
|
1419 | #Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· Calculo del SNRΒ·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· | |
|
|
1398 | 1420 | data_snrPP = S/self.noise |
|
|
1399 | data_snrPP = numpy.where(data_snrPP<0,1,data_snrPP) | |
|
|
1421 | for i in range(self.__nch): | |
|
|
1422 | for j in range(self.__nHeis): | |
|
|
1423 | if data_snrPP[i][j] < 1.e-20: | |
|
|
1424 | data_snrPP[i][j] = 1.e-20 | |
|
|
1400 | 1425 | |
|
|
1426 | #Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· Calculo del ancho espectral Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β·Β· | |
|
|
1401 | 1427 | L = S/R1 |
|
|
1402 | 1428 | L = numpy.where(L<0,1,L) |
|
|
1403 | 1429 | L = numpy.log(L) |
|
|
1404 | ||
|
|
1405 | 1430 | tmp = numpy.sqrt(numpy.absolute(L)) |
|
|
1406 | ||
|
|
1407 | data_specwidth = (self.lambda_/(2*math.sqrt(2)*math.pi*self.ippSec))*tmp*numpy.sign(L) | |
|
|
1408 | #data_specwidth = (self.lambda_/(2*math.sqrt(2)*math.pi*self.ippSec))*k | |
|
|
1431 | data_specwidth = (self.lambda_/(2*math.sqrt(2)*math.pi*self.ippSec*self.nCohInt))*tmp*numpy.sign(L) | |
|
|
1409 | 1432 | n = self.__profIndex |
|
|
1410 | 1433 | |
|
|
1411 | 1434 | self.__buffer = numpy.zeros((self.__nch, self.__nProf,self.__nHeis), dtype='complex') |
|
|
1412 | 1435 | self.__profIndex = 0 |
|
|
1413 | return data_intensity,data_velocity,data_snrPP,data_specwidth,n | |
|
|
1436 | return data_power,data_intensity,data_velocity,data_snrPP,data_specwidth,n | |
|
|
1437 | ||
|
|
1414 | 1438 | |
|
|
1415 | 1439 | def pulsePairbyProfiles(self,dataOut): |
|
|
1416 | 1440 | |
|
|
1417 | 1441 | self.__dataReady = False |
|
|
1442 | data_power = None | |
|
|
1418 | 1443 | data_intensity = None |
|
|
1419 | 1444 | data_velocity = None |
|
|
1420 | 1445 | data_specwidth = None |
|
|
1421 | 1446 | data_snrPP = None |
|
|
1422 | 1447 | self.putData(data=dataOut.data) |
|
|
1423 | 1448 | if self.__profIndex == self.n: |
|
|
1424 | #self.noise = numpy.zeros([self.__nch,self.__nHeis]) | |
|
|
1425 | #for i in range(self.__nch): | |
|
|
1426 | # self.noise[i]=data.getNoise(channel=i) | |
|
|
1427 | #print(self.noise.shape) | |
|
|
1428 | data_intensity, data_velocity,data_snrPP,data_specwidth, n = self.pushData(dataOut=dataOut) | |
|
|
1449 | data_power,data_intensity, data_velocity,data_snrPP,data_specwidth, n = self.pushData(dataOut=dataOut) | |
|
|
1429 | 1450 | self.__dataReady = True |
|
|
1430 | 1451 | |
|
|
1431 | return data_intensity, data_velocity,data_snrPP,data_specwidth | |
|
|
1452 | return data_power, data_intensity, data_velocity, data_snrPP, data_specwidth | |
|
|
1453 | ||
|
|
1432 | 1454 | |
|
|
1433 | 1455 | def pulsePairOp(self, dataOut, datatime= None): |
|
|
1434 | 1456 | |
|
|
1435 | 1457 | if self.__initime == None: |
|
|
1436 | 1458 | self.__initime = datatime |
|
|
1437 | #print("hola") | |
|
|
1438 | data_intensity, data_velocity,data_snrPP,data_specwidth = self.pulsePairbyProfiles(dataOut) | |
|
|
1459 | data_power, data_intensity, data_velocity, data_snrPP, data_specwidth = self.pulsePairbyProfiles(dataOut) | |
|
|
1439 | 1460 | self.__lastdatatime = datatime |
|
|
1440 | 1461 | |
|
|
1441 |
if data_ |
|
|
|
1442 | return None, None,None,None,None | |
|
|
1462 | if data_power is None: | |
|
|
1463 | return None, None, None,None,None,None | |
|
|
1443 | 1464 | |
|
|
1444 | 1465 | avgdatatime = self.__initime |
|
|
1445 | 1466 | deltatime = datatime - self.__lastdatatime |
|
|
1446 | 1467 | self.__initime = datatime |
|
|
1447 | 1468 | |
|
|
1448 | return data_intensity, data_velocity,data_snrPP,data_specwidth,avgdatatime | |
|
|
1469 | return data_power, data_intensity, data_velocity, data_snrPP, data_specwidth, avgdatatime | |
|
|
1449 | 1470 | |
|
|
1450 | 1471 | def run(self, dataOut,n = None,removeDC= False, overlapping= False,**kwargs): |
|
|
1451 | 1472 | |
|
|
1452 | 1473 | if not self.isConfig: |
|
|
1453 | 1474 | self.setup(dataOut = dataOut, n = n , removeDC=removeDC , **kwargs) |
|
|
1454 | 1475 | self.isConfig = True |
|
|
1455 | data_intensity, data_velocity,data_snrPP,data_specwidth, avgdatatime = self.pulsePairOp(dataOut, dataOut.utctime) | |
|
|
1476 | data_power, data_intensity, data_velocity,data_snrPP,data_specwidth, avgdatatime = self.pulsePairOp(dataOut, dataOut.utctime) | |
|
|
1456 | 1477 | dataOut.flagNoData = True |
|
|
1457 | 1478 | |
|
|
1458 | 1479 | if self.__dataReady: |
|
|
1459 | 1480 | dataOut.nCohInt *= self.n |
|
|
1460 |
dataOut.data |
|
|
|
1461 |
dataOut.data |
|
|
|
1462 |
dataOut.data |
|
|
|
1463 |
dataOut.data |
|
|
|
1481 | dataOut.dataPP_POW = data_intensity # S | |
|
|
1482 | dataOut.dataPP_POWER = data_power # P | |
|
|
1483 | dataOut.dataPP_DOP = data_velocity | |
|
|
1484 | dataOut.dataPP_SNR = data_snrPP | |
|
|
1485 | dataOut.dataPP_WIDTH = data_specwidth | |
|
|
1464 | 1486 | dataOut.PRFbyAngle = self.n #numero de PRF*cada angulo rotado que equivale a un tiempo. |
|
|
1465 | 1487 | dataOut.utctime = avgdatatime |
|
|
1466 | 1488 | dataOut.flagNoData = False |
|
|
1467 | 1489 | return dataOut |
|
|
1468 | 1490 | |
|
|
1469 | 1491 | |
|
|
1492 | ||
|
|
1470 | 1493 | # import collections |
|
|
1471 | 1494 | # from scipy.stats import mode |
|
|
1472 | 1495 | # |
|
|
1473 | 1496 | # class Synchronize(Operation): |
|
|
1474 | 1497 | # |
|
|
1475 | 1498 | # isConfig = False |
|
|
1476 | 1499 | # __profIndex = 0 |
|
|
1477 | 1500 | # |
|
|
1478 | 1501 | # def __init__(self, **kwargs): |
|
|
1479 | 1502 | # |
|
|
1480 | 1503 | # Operation.__init__(self, **kwargs) |
|
|
1481 | 1504 | # # self.isConfig = False |
|
|
1482 | 1505 | # self.__powBuffer = None |
|
|
1483 | 1506 | # self.__startIndex = 0 |
|
|
1484 | 1507 | # self.__pulseFound = False |
|
|
1485 | 1508 | # |
|
|
1486 | 1509 | # def __findTxPulse(self, dataOut, channel=0, pulse_with = None): |
|
|
1487 | 1510 | # |
|
|
1488 | 1511 | # #Read data |
|
|
1489 | 1512 | # |
|
|
1490 | 1513 | # powerdB = dataOut.getPower(channel = channel) |
|
|
1491 | 1514 | # noisedB = dataOut.getNoise(channel = channel)[0] |
|
|
1492 | 1515 | # |
|
|
1493 | 1516 | # self.__powBuffer.extend(powerdB.flatten()) |
|
|
1494 | 1517 | # |
|
|
1495 | 1518 | # dataArray = numpy.array(self.__powBuffer) |
|
|
1496 | 1519 | # |
|
|
1497 | 1520 | # filteredPower = numpy.correlate(dataArray, dataArray[0:self.__nSamples], "same") |
|
|
1498 | 1521 | # |
|
|
1499 | 1522 | # maxValue = numpy.nanmax(filteredPower) |
|
|
1500 | 1523 | # |
|
|
1501 | 1524 | # if maxValue < noisedB + 10: |
|
|
1502 | 1525 | # #No se encuentra ningun pulso de transmision |
|
|
1503 | 1526 | # return None |
|
|
1504 | 1527 | # |
|
|
1505 | 1528 | # maxValuesIndex = numpy.where(filteredPower > maxValue - 0.1*abs(maxValue))[0] |
|
|
1506 | 1529 | # |
|
|
1507 | 1530 | # if len(maxValuesIndex) < 2: |
|
|
1508 | 1531 | # #Solo se encontro un solo pulso de transmision de un baudio, esperando por el siguiente TX |
|
|
1509 | 1532 | # return None |
|
|
1510 | 1533 | # |
|
|
1511 | 1534 | # phasedMaxValuesIndex = maxValuesIndex - self.__nSamples |
|
|
1512 | 1535 | # |
|
|
1513 | 1536 | # #Seleccionar solo valores con un espaciamiento de nSamples |
|
|
1514 | 1537 | # pulseIndex = numpy.intersect1d(maxValuesIndex, phasedMaxValuesIndex) |
|
|
1515 | 1538 | # |
|
|
1516 | 1539 | # if len(pulseIndex) < 2: |
|
|
1517 | 1540 | # #Solo se encontro un pulso de transmision con ancho mayor a 1 |
|
|
1518 | 1541 | # return None |
|
|
1519 | 1542 | # |
|
|
1520 | 1543 | # spacing = pulseIndex[1:] - pulseIndex[:-1] |
|
|
1521 | 1544 | # |
|
|
1522 | 1545 | # #remover senales que se distancien menos de 10 unidades o muestras |
|
|
1523 | 1546 | # #(No deberian existir IPP menor a 10 unidades) |
|
|
1524 | 1547 | # |
|
|
1525 | 1548 | # realIndex = numpy.where(spacing > 10 )[0] |
|
|
1526 | 1549 | # |
|
|
1527 | 1550 | # if len(realIndex) < 2: |
|
|
1528 | 1551 | # #Solo se encontro un pulso de transmision con ancho mayor a 1 |
|
|
1529 | 1552 | # return None |
|
|
1530 | 1553 | # |
|
|
1531 | 1554 | # #Eliminar pulsos anchos (deja solo la diferencia entre IPPs) |
|
|
1532 | 1555 | # realPulseIndex = pulseIndex[realIndex] |
|
|
1533 | 1556 | # |
|
|
1534 | 1557 | # period = mode(realPulseIndex[1:] - realPulseIndex[:-1])[0][0] |
|
|
1535 | 1558 | # |
|
|
1536 | 1559 | # print "IPP = %d samples" %period |
|
|
1537 | 1560 | # |
|
|
1538 | 1561 | # self.__newNSamples = dataOut.nHeights #int(period) |
|
|
1539 | 1562 | # self.__startIndex = int(realPulseIndex[0]) |
|
|
1540 | 1563 | # |
|
|
1541 | 1564 | # return 1 |
|
|
1542 | 1565 | # |
|
|
1543 | 1566 | # |
|
|
1544 | 1567 | # def setup(self, nSamples, nChannels, buffer_size = 4): |
|
|
1545 | 1568 | # |
|
|
1546 | 1569 | # self.__powBuffer = collections.deque(numpy.zeros( buffer_size*nSamples,dtype=numpy.float), |
|
|
1547 | 1570 | # maxlen = buffer_size*nSamples) |
|
|
1548 | 1571 | # |
|
|
1549 | 1572 | # bufferList = [] |
|
|
1550 | 1573 | # |
|
|
1551 | 1574 | # for i in range(nChannels): |
|
|
1552 | 1575 | # bufferByChannel = collections.deque(numpy.zeros( buffer_size*nSamples, dtype=numpy.complex) + numpy.NAN, |
|
|
1553 | 1576 | # maxlen = buffer_size*nSamples) |
|
|
1554 | 1577 | # |
|
|
1555 | 1578 | # bufferList.append(bufferByChannel) |
|
|
1556 | 1579 | # |
|
|
1557 | 1580 | # self.__nSamples = nSamples |
|
|
1558 | 1581 | # self.__nChannels = nChannels |
|
|
1559 | 1582 | # self.__bufferList = bufferList |
|
|
1560 | 1583 | # |
|
|
1561 | 1584 | # def run(self, dataOut, channel = 0): |
|
|
1562 | 1585 | # |
|
|
1563 | 1586 | # if not self.isConfig: |
|
|
1564 | 1587 | # nSamples = dataOut.nHeights |
|
|
1565 | 1588 | # nChannels = dataOut.nChannels |
|
|
1566 | 1589 | # self.setup(nSamples, nChannels) |
|
|
1567 | 1590 | # self.isConfig = True |
|
|
1568 | 1591 | # |
|
|
1569 | 1592 | # #Append new data to internal buffer |
|
|
1570 | 1593 | # for thisChannel in range(self.__nChannels): |
|
|
1571 | 1594 | # bufferByChannel = self.__bufferList[thisChannel] |
|
|
1572 | 1595 | # bufferByChannel.extend(dataOut.data[thisChannel]) |
|
|
1573 | 1596 | # |
|
|
1574 | 1597 | # if self.__pulseFound: |
|
|
1575 | 1598 | # self.__startIndex -= self.__nSamples |
|
|
1576 | 1599 | # |
|
|
1577 | 1600 | # #Finding Tx Pulse |
|
|
1578 | 1601 | # if not self.__pulseFound: |
|
|
1579 | 1602 | # indexFound = self.__findTxPulse(dataOut, channel) |
|
|
1580 | 1603 | # |
|
|
1581 | 1604 | # if indexFound == None: |
|
|
1582 | 1605 | # dataOut.flagNoData = True |
|
|
1583 | 1606 | # return |
|
|
1584 | 1607 | # |
|
|
1585 | 1608 | # self.__arrayBuffer = numpy.zeros((self.__nChannels, self.__newNSamples), dtype = numpy.complex) |
|
|
1586 | 1609 | # self.__pulseFound = True |
|
|
1587 | 1610 | # self.__startIndex = indexFound |
|
|
1588 | 1611 | # |
|
|
1589 | 1612 | # #If pulse was found ... |
|
|
1590 | 1613 | # for thisChannel in range(self.__nChannels): |
|
|
1591 | 1614 | # bufferByChannel = self.__bufferList[thisChannel] |
|
|
1592 | 1615 | # #print self.__startIndex |
|
|
1593 | 1616 | # x = numpy.array(bufferByChannel) |
|
|
1594 | 1617 | # self.__arrayBuffer[thisChannel] = x[self.__startIndex:self.__startIndex+self.__newNSamples] |
|
|
1595 | 1618 | # |
|
|
1596 | 1619 | # deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
|
1597 | 1620 | # dataOut.heightList = numpy.arange(self.__newNSamples)*deltaHeight |
|
|
1598 | 1621 | # # dataOut.ippSeconds = (self.__newNSamples / deltaHeight)/1e6 |
|
|
1599 | 1622 | # |
|
|
1600 | 1623 | # dataOut.data = self.__arrayBuffer |
|
|
1601 | 1624 | # |
|
|
1602 | 1625 | # self.__startIndex += self.__newNSamples |
|
|
1603 | 1626 | # |
|
|
1604 | 1627 | # return |
| @@ -1,49 +1,73 | |||
|
|
1 | 1 | import os,sys |
|
|
2 | 2 | import datetime |
|
|
3 | 3 | import time |
|
|
4 | 4 | from schainpy.controller import Project |
|
|
5 | 5 | path = '/home/alex/Downloads/NEW_WR2/spc16removeDC' |
|
|
6 | 6 | figpath = path |
|
|
7 | 7 | desc = "Simulator Test" |
|
|
8 | 8 | |
|
|
9 | 9 | controllerObj = Project() |
|
|
10 | 10 | |
|
|
11 | 11 | controllerObj.setup(id='10',name='Test Simulator',description=desc) |
|
|
12 | 12 | |
|
|
13 | 13 | readUnitConfObj = controllerObj.addReadUnit(datatype='SimulatorReader', |
|
|
14 | 14 | frequency=9.345e9, |
|
|
15 | 15 | FixRCP_IPP= 60, |
|
|
16 | 16 | Tau_0 = 30, |
|
|
17 | 17 | AcqH0_0=0, |
|
|
18 | 18 | samples=330, |
|
|
19 | 19 | AcqDH_0=0.15, |
|
|
20 | 20 | FixRCP_TXA=0.15, |
|
|
21 | 21 | FixRCP_TXB=0.15, |
|
|
22 | 22 | Fdoppler=600.0, |
|
|
23 | 23 | Hdoppler=36, |
|
|
24 | 24 | Adoppler=300,#300 |
|
|
25 | 25 | delay=0, |
|
|
26 | 26 | online=0, |
|
|
27 | 27 | walk=0, |
|
|
28 |
|
|
|
|
29 | ||
|
|
28 | profilesPerBlock=625, | |
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29 | dataBlocksPerFile=100)#,#nTotalReadFiles=2) | |
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30 | ''' | |
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31 | readUnitConfObj = controllerObj.addReadUnit(datatype='VoltageReader', | |
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32 | path=path, | |
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33 | startDate="2020/01/01", #"2020/01/01",#today, | |
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34 | endDate= "2020/12/01", #"2020/12/30",#today, | |
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35 | startTime='00:00:00', | |
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36 | endTime='23:59:59', | |
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37 | delay=0, | |
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38 | #set=0, | |
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39 | online=0, | |
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40 | walk=1) | |
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41 | ''' | |
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30 | 42 | opObj11 = readUnitConfObj.addOperation(name='printInfo') |
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31 | 43 | |
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32 | 44 | procUnitConfObjA = controllerObj.addProcUnit(datatype='VoltageProc', inputId=readUnitConfObj.getId()) |
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33 | 45 | #opObj11 = procUnitConfObjA.addOperation(name='CohInt', optype='other') |
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34 | 46 | #opObj11.addParameter(name='n', value='10', format='int') |
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35 | 47 | |
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36 | 48 | #opObj10 = procUnitConfObjA.addOperation(name='selectChannels') |
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37 | 49 | #opObj10.addParameter(name='channelList', value=[0]) |
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38 | 50 | opObj11 = procUnitConfObjA.addOperation(name='PulsePairVoltage', optype='other') |
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39 |
opObj11.addParameter(name='n', value=' |
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51 | opObj11.addParameter(name='n', value='625', format='int')#10 | |
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40 | 52 | opObj11.addParameter(name='removeDC', value=1, format='int') |
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41 | 53 | |
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42 | 54 | #opObj11 = procUnitConfObjA.addOperation(name='PulsepairPowerPlot', optype='other') |
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55 | #opObj11 = procUnitConfObjA.addOperation(name='PulsepairSignalPlot', optype='other') | |
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56 | ||
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43 | 57 | |
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44 | opObj11 = procUnitConfObjA.addOperation(name='PulsepairVelocityPlot', optype='other') | |
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58 | #opObj11 = procUnitConfObjA.addOperation(name='PulsepairVelocityPlot', optype='other') | |
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45 | 59 | #opObj11.addParameter(name='xmax', value=8) |
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46 | 60 | |
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47 | opObj11 = procUnitConfObjA.addOperation(name='PulsepairSpecwidthPlot', optype='other') | |
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61 | #opObj11 = procUnitConfObjA.addOperation(name='PulsepairSpecwidthPlot', optype='other') | |
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62 | ||
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63 | procUnitConfObjB= controllerObj.addProcUnit(datatype='ParametersProc',inputId=procUnitConfObjA.getId()) | |
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64 | ||
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65 | ||
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66 | opObj10 = procUnitConfObjB.addOperation(name='ParameterWriter') | |
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67 | opObj10.addParameter(name='path',value=figpath) | |
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68 | #opObj10.addParameter(name='mode',value=0) | |
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69 | opObj10.addParameter(name='blocksPerFile',value='100',format='int') | |
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70 | opObj10.addParameter(name='metadataList',value='utctimeInit,timeInterval',format='list') | |
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71 | opObj10.addParameter(name='dataList',value='dataPP_POW,dataPP_DOP,dataPP_SNR,dataPP_WIDTH')#,format='list' | |
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48 | 72 | |
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49 | 73 | controllerObj.start() |
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