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import numpy
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import sys
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import zmq
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import time
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import h5py
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import os
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path = "/home/alex/Downloads/pedestal"
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ext = ".hdf5"
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port = "5556"
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if len(sys.argv) > 1:
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port = sys.argv[1]
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int(port)
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if len(sys.argv) > 2:
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port1 = sys.argv[2]
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int(port1)
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# Socket to talk to server
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context = zmq.Context()
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socket = context.socket(zmq.SUB)
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print("Collecting updates from weather server...")
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socket.connect("tcp://localhost:%s" % port)
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if len(sys.argv) > 2:
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socket.connect("tcp://localhost:%s" % port1)
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# Subscribe to zipcode, default is NYC,10001
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topicfilter = "10001"
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socket.setsockopt_string(zmq.SUBSCRIBE, topicfilter)
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# Process 5 updates
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total_value = 0
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count = -1
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azi = []
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elev = []
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time0 = []
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# for update_nbr in range(250):
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while(True):
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string = socket.recv()
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topic, ang_elev, ang_elev_dec, ang_azi, ang_azi_dec, seconds, seconds_dec = string.split()
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ang_azi = float(ang_azi) + 1e-3 * float(ang_azi_dec)
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ang_elev = float(ang_elev) + 1e-3 * float(ang_elev_dec)
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seconds = float(seconds) + 1e-6 * float(seconds_dec)
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azi.append(ang_azi)
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elev.append(ang_elev)
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time0.append(seconds)
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count += 1
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if count == 100:
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timetuple = time.localtime()
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epoc = time.mktime(timetuple)
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# print(epoc)
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fullpath = path + ("/" if path[-1] != "/" else "")
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if not os.path.exists(fullpath):
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os.mkdir(fullpath)
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azi_array = numpy.array(azi)
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elev_array = numpy.array(elev)
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time0_array = numpy.array(time0)
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pedestal_array = numpy.array([azi, elev, time0])
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count = 0
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azi = []
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elev = []
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time0 = []
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# print(pedestal_array[0])
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# print(pedestal_array[1])
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meta = 'PE'
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filex = "%s%4.4d%3.3d%10.4d%s" % (meta, timetuple.tm_year, timetuple.tm_yday, epoc, ext)
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filename = os.path.join(fullpath, filex)
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fp = h5py.File(filename, 'w')
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# print("Escribiendo HDF5...",epoc)
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# ·················· Data·....······································
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grp = fp.create_group("Data")
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dset = grp.create_dataset("azimuth" , data=pedestal_array[0])
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dset = grp.create_dataset("elevacion", data=pedestal_array[1])
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dset = grp.create_dataset("utc" , data=pedestal_array[2])
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# ·················· Metadata·······································
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grp = fp.create_group("Metadata")
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dset = grp.create_dataset("utctimeInit", data=pedestal_array[2][0])
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timeInterval = pedestal_array[2][1] - pedestal_array[2][0]
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dset = grp.create_dataset("timeInterval", data=timeInterval)
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fp.close()
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# print ("Average messagedata value for topic '%s' was %dF" % ( topicfilter,total_value / update_nbr))
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