def transmit_std():
print 'TX: Initializing standard transport TX to IP', options.ip
tx = spead.Transmitter(spead.TransportUDPtx(options.ip, 8888))
ig = spead.ItemGroup()
ig.add_item(
name='data_timestamp',
description='Timestamp in epoch ms for the current visibility sample',
shape=[1],
fmt=spead.mkfmt(('u', 64)))
ig.add_item(
name='vis_data',
description='The complex visibility spectrum for a single time dump',
shape=[channels, baselines, 2],
fmt=spead.mkfmt(('u', 32)))
# using init_val with a numpy array will use the numpy transport automatically.
for x in range(iterations):
ig['data_timestamp'] = int(time.time() * 1000)
ig['vis_data'] = np.random.normal(size=(channels, baselines,
2)).astype(np.float32)
t_heap_send = time.time()
tx.send_heap(ig.get_heap())
print "Sent data for timestamp", ig['data_timestamp'], "in", time.time(
) - t_heap_send, "s"
time.sleep(15)
tx.end()
print 'TX: Done.'
def transmit():
#print 'TX: Initializing...'
tx = spead.Transmitter(spead.TransportFile(sys.stdout))
ig = spead.ItemGroup()
ig.add_item(name='Var1', description='Description for Var1',
shape=[], fmt=spead.mkfmt(('u',32),('u',32),('u',32)),
init_val=(1,2,3))
tx.send_heap(ig.get_heap())
ig['Var1'] = (4,5,6)
tx.send_heap(ig.get_heap())
ig.add_item(name='Var2', description='Description for Var2',
shape=[100,100], fmt=spead.mkfmt(('u',32)))
data = numpy.arange(100*100); data.shape = (100,100)
ig['Var2'] = data
tx.send_heap(ig.get_heap())
tx.end()
def transmit():
print 'TX: Initializing...'
tx = spead.Transmitter(spead.TransportUDPtx('127.0.0.1', PORT, rate=1e9))
ig = spead.ItemGroup()
ig.add_item(name='Var1',
description='Description for Var1',
shape=[],
fmt=spead.mkfmt(('u', 32), ('u', 32), ('u', 32)),
init_val=(1, 2, 3))
tx.send_heap(ig.get_heap())
ig['Var1'] = (4, 5, 6)
tx.send_heap(ig.get_heap())
data = numpy.arange(100000 * 4000).astype(numpy.uint32)
data.shape = (100000, 4000)
ig.add_item(name='Var2',
description='Description for Var2',
shape=[100000, 4000],
ndarray=data)
ig['Var2'] = data
tx.send_heap(ig.get_heap())
tx.end()
print 'TX: Done.'
def transmit():
print 'TX: Initializing...'
tx = spead.Transmitter(spead.TransportFile(FILENAME,'w'))
ig = spead.ItemGroup()
ig.add_item(name='Var1', description='Description for Var1',
shape=[], fmt=spead.mkfmt(('u',32),('u',32),('u',32)),
init_val=(1,2,3))
tx.send_heap(ig.get_heap())
ig['Var1'] = (4,5,6)
tx.send_heap(ig.get_heap())
ig.add_item(name='Var2', description='Description for Var2',
shape=[DIM,DIM], fmt=spead.mkfmt(('u',32)))
data = numpy.arange(DIM*DIM); data.shape = (DIM,DIM)
ig['Var2'] = data
tx.send_heap(ig.get_heap())
tx.end()
print 'TX: Done.'
def transmit_std():
print 'TX: Initializing standard transport TX to IP', options.ip
tx = spead.Transmitter(spead.TransportUDPtx(options.ip, 8888))
ig = spead.ItemGroup()
ig.add_item(name='data_timestamp', description='Timestamp in epoch ms for the current visibility sample',
shape=[1], fmt=spead.mkfmt(('u', 64)))
ig.add_item(name='vis_data', description='The complex visibility spectrum for a single time dump',
shape=[channels, baselines, 2], fmt=spead.mkfmt(('u', 32)))
# using init_val with a numpy array will use the numpy transport automatically.
for x in range(iterations):
ig['data_timestamp'] = int(time.time() * 1000)
ig['vis_data'] = np.random.normal(size=(channels, baselines, 2)).astype(np.float32)
t_heap_send = time.time()
tx.send_heap(ig.get_heap())
print "Sent data for timestamp", ig['data_timestamp'], "in", time.time() - t_heap_send, "s"
time.sleep(15)
tx.end()
print 'TX: Done.'
def send_meta():
print 'Sending meta'
spead_ig = spead.ItemGroup()
spead_tx = spead.Transmitter(spead.TransportUDPtx('127.0.0.1', DATA_PORT))
# ndarray = numpy.dtype(numpy.int64), (4096 * 40 * 1, 1, 1)
ndarray = numpy.dtype(numpy.int32), (4096, 40, 2)
spead_ig.add_item(name='xeng_raw', id=0x1800, description='raw simulator data', ndarray=ndarray)
spead_ig.add_item(name='timestamp', id=0x1600, description='Timestamp', shape=[],
fmt=spead.mkfmt(('u', spead.ADDRSIZE)), init_val=0)
spead_tx.send_heap(spead_ig.get_heap())
def transmit():
#print 'TX: Initializing...'
tx = spead.Transmitter(spead.TransportFile(sys.stdout))
ig = spead.ItemGroup()
ig.add_item(name='Var1',
description='Description for Var1',
shape=[],
fmt=spead.mkfmt(('u', 32), ('u', 32), ('u', 32)),
init_val=(1, 2, 3))
tx.send_heap(ig.get_heap())
ig['Var1'] = (4, 5, 6)
tx.send_heap(ig.get_heap())
ig.add_item(name='Var2',
description='Description for Var2',
shape=[100, 100],
fmt=spead.mkfmt(('u', 32)))
data = numpy.arange(100 * 100)
data.shape = (100, 100)
ig['Var2'] = data
tx.send_heap(ig.get_heap())
tx.end()
def transmit():
print 'TX: Initializing...'
tx = spead.Transmitter(spead.TransportFile(FILENAME, 'w'))
ig = spead.ItemGroup()
ig.add_item(name='Var1',
description='Description for Var1',
shape=[],
fmt=spead.mkfmt(('u', 32), ('u', 32), ('u', 32)),
init_val=(1, 2, 3))
tx.send_heap(ig.get_heap())
ig['Var1'] = (4, 5, 6)
tx.send_heap(ig.get_heap())
ig.add_item(name='Var2',
description='Description for Var2',
shape=[DIM, DIM],
fmt=spead.mkfmt(('u', 32)))
data = numpy.arange(DIM * DIM)
data.shape = (DIM, DIM)
ig['Var2'] = data
tx.send_heap(ig.get_heap())
tx.end()
print 'TX: Done.'
def transmit():
print 'TX: Initializing...'
tx = spead.Transmitter(spead.TransportUDPtx('127.0.0.1', PORT, rate=1e9))
ig = spead.ItemGroup()
ig.add_item(name='Var1', description='Description for Var1',
shape=[], fmt=spead.mkfmt(('u',32),('u',32),('u',32)),
init_val=(1,2,3))
tx.send_heap(ig.get_heap())
ig['Var1'] = (4,5,6)
tx.send_heap(ig.get_heap())
data = numpy.arange(100000*4000).astype(numpy.uint32); data.shape = (100000,4000)
ig.add_item(name='Var2', description='Description for Var2',
shape=[100000,4000], ndarray=data)
ig['Var2'] = data
tx.send_heap(ig.get_heap())
tx.end()
print 'TX: Done.'
tx = spead.Transmitter(spead.TransportUDPtx('127.0.0.1', 8888, rate=1e3))
# Send N heaps
for j in range(int(sys.argv[1])):
ig = spead.ItemGroup()
# Timestamp
time = str(datetime.datetime.now().time())
ig.add_item(name='Timestamp',
description='Current time',
shape=[],
fmt=spead.mkfmt(('c', 8)),
init_val=('00:00'))
ig['Timestamp'] = time
# Beam ID
ig.add_item(name='beam id',
description='beam number',
shape=[],
fmt=spead.mkfmt(('u', 32)),
init_val=(0))
ig['beam id'] = i
# frequency
ig.add_item(
def rx_inter(self,data_port=7148, sd_ip='127.0.0.1', sd_port=7149, acc_scale=True, filename=None, **kwargs):
'''
Process SPEAD data from X engines and forward it to the SD.
'''
print 'WARNING: This function is not yet tested. YMMV.'
logger=self.logger
logger.info("Data reception on port %i."%data_port)
rx = spead.TransportUDPrx(data_port, pkt_count=1024, buffer_size=51200000)
logger.info("Sending Signal Display data to %s:%i."%(sd_ip,sd_port))
tx_sd = spead.Transmitter(spead.TransportUDPtx(sd_ip, sd_port))
ig = spead.ItemGroup()
ig_sd = spead.ItemGroup()
if filename == None:
filename=str(int(time.time())) + ".synth.h5"
logger.info("Starting file %s."%(filename))
f = h5py.File(filename, mode="w")
data_ds = None
ts_ds = None
idx = 0
dump_size = 0
datasets = {}
datasets_index = {}
# we need these bits of meta data before being able to assemble and transmit signal display data
meta_required = ['n_chans','n_bls','n_xengs','center_freq','bls_ordering','bandwidth']
meta_desired = ['n_accs']
meta = {}
sd_frame = None
sd_slots = None
timestamp = None
# log the latest timestamp for which we've stored data
currentTimestamp = -1
# iterate through SPEAD heaps returned by the SPEAD receiver.
for heap in spead.iterheaps(rx):
ig.update(heap)
logger.debug("PROCESSING HEAP idx(%i) cnt(%i) @ %.4f" % (idx, heap.heap_cnt, time.time()))
for name in ig.keys():
item = ig.get_item(name)
# the item is not marked as changed and we already have a record for it, continue
if not item._changed and datasets.has_key(name):
continue
logger.debug("PROCESSING KEY %s @ %.4f" % (name, time.time()))
if name in meta_desired:
meta[name] = ig[name]
if name in meta_required:
meta[name] = ig[name]
meta_required.pop(meta_required.index(name))
if len(meta_required) == 0:
sd_frame = np.zeros((meta['n_chans'],meta['n_bls'],2),dtype=np.float32)
logger.info("Got all required metadata. Initialised sd frame to shape %s"%(str(sd_frame.shape)))
meta_required = ['n_chans','bandwidth','n_bls','n_xengs','center_freq','bls_ordering']
ig_sd = spead.ItemGroup()
for meta_item in meta_required:
ig_sd.add_item(
name=ig.get_item(meta_item).name,
id=ig.get_item(meta_item).id,
description=ig.get_item(meta_item).description,
#shape=ig.get_item(meta_item).shape,
#fmt=ig.get_item(meta_item).format,
init_val=ig.get_item(meta_item).get_value())
tx_sd.send_heap(ig_sd.get_heap())
sd_slots = np.zeros(meta['n_xengs'])
if not datasets.has_key(name):
# check to see if we have encountered this type before
shape = ig[name].shape if item.shape == -1 else item.shape
dtype = np.dtype(type(ig[name])) if shape == [] else item.dtype
if dtype is None: dtype = ig[name].dtype
# if we can't get a dtype from the descriptor, try and get one from the value
logger.info("Creating dataset for %s (%s,%s)."%(str(name),str(shape),str(dtype)))
f.create_dataset(name,[1] + ([] if list(shape) == [1] else list(shape)), maxshape=[None] + ([] if list(shape) == [1] else list(shape)), dtype=dtype)
dump_size += np.multiply.reduce(shape) * dtype.itemsize
datasets[name] = f[name]
datasets_index[name] = 0
# if we built from an empty descriptor
if not item._changed:
continue
else:
logger.info("Adding %s to dataset. New size is %i."%(name,datasets_index[name]+1))
f[name].resize(datasets_index[name]+1, axis=0)
# now we store this x engine's data for sending sd data.
if sd_frame is not None and name.startswith("xeng_raw"):
xeng_id = int(name[8:])
sd_frame[xeng_id::meta['n_xengs']] = ig[name]
logger.debug('Received data for Xeng %i @ %.4f' % (xeng_id, time.time()))
# we got a timestamp.
if sd_frame is not None and name.startswith("timestamp"):
xeng_id = int(name[9:])
timestamp = ig['sync_time'] + (ig[name] / ig['scale_factor_timestamp']) #in seconds since unix epoch
localTime = time.time()
print "Decoded timestamp for Xeng", xeng_id, ":", timestamp, " (", time.ctime(timestamp),") @ %.4f" % localTime, " ", time.ctime(localTime), "diff(", localTime-timestamp, ")"
# is this timestamp in the past?
if currentTimestamp > timestamp:
errorString = "Timestamp %.2f (%s) is earlier than the current timestamp %.2f (%s). Ignoring..." % (timestamp, time.ctime(timestamp), currentTimestamp, time.ctime(currentTimestamp))
logger.warning(errorString)
continue
# is this a new timestamp before a complete set?
if (timestamp > currentTimestamp) and sd_slots.any():
errorString = "New timestamp %.2f from Xeng%i before previous set %.2f sent" % (timestamp, xeng_id, currentTimestamp)
logger.warning(errorString)
sd_slots = np.zeros(meta['n_xengs'])
sd_frame = np.zeros((ig['n_chans'],ig['n_bls'],2),dtype=sd_frame.dtype)
currentTimestamp = -1
continue
# is this new timestamp in the past for this X engine?
if timestamp <= sd_slots[xeng_id]:
errorString = 'Xeng%i already on timestamp %.2f but got %.2f now, THIS SHOULD NOT HAPPEN' % (xeng_id, sd_slots[xeng_id], timestamp)
logger.error(errorString)
raise RuntimeError(errorString)
# update our info on which integrations we have
sd_slots[xeng_id] = timestamp
currentTimestamp = timestamp
# do we have integration data and timestamps for all the xengines? If so, send the SD frame.
if timestamp is not None and sd_frame is not None and sd_slots is not None and sd_slots.all():
ig_sd = spead.ItemGroup()
# make sure we have the right dtype for the sd data
ig_sd.add_item(name=('sd_data'), id=(0x3501), description="Combined raw data from all x engines.", ndarray=(sd_frame.dtype,sd_frame.shape))
ig_sd.add_item(name=('sd_timestamp'), id=0x3502, description='Timestamp of this sd frame in centiseconds since epoch (40 bit limitation).', shape=[], fmt=spead.mkfmt(('u',spead.ADDRSIZE)))
t_it = ig_sd.get_item('sd_data')
logger.info("Added SD frame with shape %s, dtype %s" % (str(t_it.shape),str(t_it.dtype)))
scale_factor=(meta['n_accs'] if meta.has_key('n_accs') else 1)
logger.info("Sending signal display frame with timestamp %i (%s). %s. @ %.4f" % (timestamp, time.ctime(timestamp), "Unscaled" if not acc_scale else "Scaled by %i" % (scale_factor), time.time()))
ig_sd['sd_data'] = sd_frame.astype(np.float32) if not acc_scale else (sd_frame / float(scale_factor)).astype(np.float32)
ig_sd['sd_timestamp'] = int(timestamp * 100)
tx_sd.send_heap(ig_sd.get_heap())
# reset the arrays that hold integration data
sd_slots = np.zeros(meta['n_xengs'])
sd_frame = np.zeros((ig['n_chans'],ig['n_bls'],2),dtype=sd_frame.dtype)
timestamp = None
f[name][datasets_index[name]] = ig[name]
datasets_index[name] += 1
item._changed = False
idx+=1
logger.info("Got a SPEAD end-of-stream marker. Closing File.")
f.flush()
f.close()
rx.stop()
sd_frame = None
sd_slots = None
ig_sd = None
def spead_issue_meta(self):
"""
All FxCorrelators issued SPEAD in the same way, with tweakings that are
implemented by the child class.
:return: <nothing>
"""
if self.meta_destination is None:
logging.info('SPEAD meta destination is still unset, NOT sending '
'metadata at this time.')
return
# make a new SPEAD transmitter
del self.spead_tx, self.spead_meta_ig
self.spead_tx = spead.Transmitter(spead.TransportUDPtx(*self.meta_destination))
# update the multicast socket option to use a TTL of 2,
# in order to traverse the L3 network on site.
ttl_bin = struct.pack('@i', 2)
self.spead_tx.t._udp_out.setsockopt(socket.IPPROTO_IP, socket.IP_MULTICAST_TTL, ttl_bin)
#mcast_interface = self.configd['xengine']['multicast_interface_address']
#self.spead_tx.t._udp_out.setsockopt(socket.SOL_IP, socket.IP_MULTICAST_IF,
# socket.inet_aton(mcast_interface))
# self.spead_tx.t._udp_out.setsockopt(socket.SOL_IP, socket.IP_ADD_MEMBERSHIP,
# socket.inet_aton(txip_str) + socket.inet_aton(mcast_interface))
# make the item group we're going to use
self.spead_meta_ig = spead.ItemGroup()
self.spead_meta_ig.add_item(name='adc_sample_rate', id=0x1007,
description='The expected ADC sample rate (samples '
'per second) of incoming data.',
shape=[], fmt=spead.mkfmt(('u', 64)),
init_val=self.sample_rate_hz)
self.spead_meta_ig.add_item(name='n_bls', id=0x1008,
description='Number of baselines in the data product.',
shape=[], fmt=spead.mkfmt(('u', spead.ADDRSIZE)),
init_val=len(self.xops.get_baseline_order()))
self.spead_meta_ig.add_item(name='n_chans', id=0x1009,
description='Number of frequency channels in '
'an integration.',
shape=[], fmt=spead.mkfmt(('u', spead.ADDRSIZE)),
init_val=self.n_chans)
self.spead_meta_ig.add_item(name='n_ants', id=0x100A,
description='The number of antennas in the system.',
shape=[], fmt=spead.mkfmt(('u', spead.ADDRSIZE)),
init_val=self.n_antennas)
self.spead_meta_ig.add_item(name='n_xengs', id=0x100B,
description='The number of x-engines in the system.',
shape=[], fmt=spead.mkfmt(('u', spead.ADDRSIZE)),
init_val=(len(self.xhosts) * self.x_per_fpga))
self.spead_meta_ig.add_item(name='bls_ordering', id=0x100C,
description='The baseline ordering in the output '
'data product.',
shape=[], fmt=spead.mkfmt(('u', spead.ADDRSIZE)),
init_val=numpy.array(
[baseline for baseline in self.xops.get_baseline_order()]))
# spead_ig.add_item(name='crosspol_ordering', id=0x100D,
# description='',
# shape=[], fmt=spead.mkfmt(('u', spead.ADDRSIZE)),
# init_val=)
metalist = numpy.array(self._spead_meta_get_labelling())
self.spead_meta_ig.add_item(name='input_labelling', id=0x100E,
description='input labels and numbers',
init_val=metalist)
# spead_ig.add_item(name='n_bengs', id=0x100F,
# description='',
# shape=[], fmt=spead.mkfmt(('u', spead.ADDRSIZE)),
# init_val=)
self.spead_meta_ig.add_item(name='center_freq', id=0x1011,
description='The on-sky centre-frequency.',
shape=[], fmt=spead.mkfmt(('f', 64)),
init_val=int(self.configd['fengine']['true_cf']))
self.spead_meta_ig.add_item(name='bandwidth', id=0x1013,
description='The input (analogue) bandwidth of '
'the system.',
shape=[], fmt=spead.mkfmt(('f', 64)),
init_val=int(self.configd['fengine']['bandwidth']))
self.spead_meta_ig.add_item(name='n_accs', id=0x1015,
description='The number of spectra that are '
'accumulated per X-engine dump.',
shape=[], fmt=spead.mkfmt(('u', spead.ADDRSIZE)),
init_val=self.accumulation_len * self.xeng_accumulation_len)
self.spead_meta_ig.add_item(name='int_time', id=0x1016,
description='The time per integration, in seconds.',
shape=[], fmt=spead.mkfmt(('f', 64)),
init_val=self.xops.get_acc_time())
# spead_ig.add_item(name='coarse_chans', id=0x1017,
# description='',
# shape=[], fmt=spead.mkfmt(('u', spead.ADDRSIZE)),
# init_val=)
#
# spead_ig.add_item(name='current_coarse_chan', id=0x1018,
# description='',
# shape=[], fmt=spead.mkfmt(('u', spead.ADDRSIZE)),
# init_val=)
#
# spead_ig.add_item(name='fft_shift_fine', id=0x101C,
# description='',
# shape=[], fmt=spead.mkfmt(('u', spead.ADDRSIZE)),
# init_val=)
#
# spead_ig.add_item(name='fft_shift_coarse', id=0x101D,
# description='',
# shape=[], fmt=spead.mkfmt(('u', spead.ADDRSIZE)),
# init_val=)
self.spead_meta_ig.add_item(name='fft_shift', id=0x101E,
description='The FFT bitshift pattern. F-engine correlator internals.',
shape=[], fmt=spead.mkfmt(('u', spead.ADDRSIZE)),
init_val=int(self.configd['fengine']['fft_shift']))
self.spead_meta_ig.add_item(name='xeng_acc_len', id=0x101F,
description='Number of spectra accumulated inside X engine. '
'Determines minimum integration time and '
'user-configurable integration time stepsize. '
'X-engine correlator internals.',
shape=[], fmt=spead.mkfmt(('u', spead.ADDRSIZE)),
init_val=self.xeng_accumulation_len)
quant_bits = int(self.configd['fengine']['quant_format'].split('.')[0])
self.spead_meta_ig.add_item(name='requant_bits', id=0x1020,
description='Number of bits after requantisation in the '
'F engines (post FFT and any '
'phasing stages).',
shape=[], fmt=spead.mkfmt(('u', spead.ADDRSIZE)),
init_val=quant_bits)
pkt_len = int(self.configd['fengine']['10gbe_pkt_len'])
self.spead_meta_ig.add_item(name='feng_pkt_len', id=0x1021,
description='Payload size of 10GbE packet exchange between '
'F and X engines in 64 bit words. Usually equal '
'to the number of spectra accumulated inside X '
'engine. F-engine correlator internals.',
shape=[], fmt=spead.mkfmt(('u', spead.ADDRSIZE)),
init_val=pkt_len)
# port = int(self.configd['xengine']['output_destination_port'])
# spead_ig.add_item(name='rx_udp_port', id=0x1022,
# description='Destination UDP port for X engine output.',
# shape=[], fmt=spead.mkfmt(('u', spead.ADDRSIZE)),
# init_val=port)
port = int(self.configd['fengine']['10gbe_port'])
self.spead_meta_ig.add_item(name='feng_udp_port', id=0x1023,
description='Port for F-engines 10Gbe links in the system.',
shape=[], fmt=spead.mkfmt(('u', spead.ADDRSIZE)),
init_val=port)
# ip = self.configd['xengine']['output_destination_ip']
# spead_ig.add_item(name='rx_udp_ip_str', id=0x1024,
# description='Destination UDP IP for X engine output.',
# shape=[-1], fmt=spead.STR_FMT,
# init_val=ip)
ip = struct.unpack('>I', socket.inet_aton(self.configd['fengine']['10gbe_start_ip']))[0]
self.spead_meta_ig.add_item(name='feng_start_ip', id=0x1025,
description='Start IP address for F-engines in the system.',
shape=[], fmt=spead.mkfmt(('u', spead.ADDRSIZE)),
init_val=ip)
self.spead_meta_ig.add_item(name='xeng_rate', id=0x1026,
description='Target clock rate of processing engines (xeng).',
shape=[], fmt=spead.mkfmt(('u', spead.ADDRSIZE)),
init_val=self.xeng_clk)
self.spead_meta_ig.add_item(name='sync_time', id=0x1027,
description='The time at which the digitisers were synchronised. '
'Seconds since the Unix Epoch.',
shape=[], fmt=spead.mkfmt(('u', spead.ADDRSIZE)),
init_val=self.synchronisation_epoch)
# spead_ig.add_item(name='n_stokes', id=0x1040,
# description='',
# shape=[], fmt=spead.mkfmt(('u', spead.ADDRSIZE)),
# init_val=)
x_per_fpga = int(self.configd['xengine']['x_per_fpga'])
self.spead_meta_ig.add_item(name='x_per_fpga', id=0x1041,
description='Number of X engines per FPGA host.',
shape=[], fmt=spead.mkfmt(('u', spead.ADDRSIZE)),
init_val=x_per_fpga)
# n_ants_per_xaui = 1
# spead_ig.add_item(name='n_ants_per_xaui', id=0x1042,
# description='',
# shape=[], fmt=spead.mkfmt(('u', spead.ADDRSIZE)),
# init_val=n_ants_per_xaui)
# spead_ig.add_item(name='ddc_mix_freq', id=0x1043,
# description='',
# shape=[],fmt=spead.mkfmt(('f', 64)),
# init_val=)
# spead_ig.add_item(name='ddc_bandwidth', id=0x1044,
# description='',
# shape=[],fmt=spead.mkfmt(('f', 64)),
# init_val=)
sample_bits = int(self.configd['fengine']['sample_bits'])
self.spead_meta_ig.add_item(name='adc_bits', id=0x1045,
description='How many bits per ADC sample.',
shape=[], fmt=spead.mkfmt(('u', spead.ADDRSIZE)),
init_val=sample_bits)
self.spead_meta_ig.add_item(name='scale_factor_timestamp', id=0x1046,
description='Timestamp scaling factor. Divide the SPEAD '
'data packet timestamp by this number to get '
'back to seconds since last sync.',
shape=[], fmt=spead.mkfmt(('f', 64)),
init_val=self.sample_rate_hz)
self.spead_meta_ig.add_item(name='xeng_out_bits_per_sample', id=0x1048,
description='The number of bits per value of the xeng '
'accumulator output. Note this is for a '
'single value, not the combined complex size.',
shape=[], fmt=spead.mkfmt(('u', spead.ADDRSIZE)),
init_val=self.xeng_outbits)
self.spead_meta_ig.add_item(name='f_per_fpga', id=0x1049,
description='Number of F engines per FPGA host.',
shape=[], fmt=spead.mkfmt(('u', spead.ADDRSIZE)),
init_val=self.f_per_fpga)
# spead_ig.add_item(name='rf_gain_MyAntStr ', id=0x1200+inputN,
# description='',
# shape=[], fmt=spead.mkfmt(('f', 64)),
# init_val=)
# 0x1400 +++
self.fops.eq_update_metadata()
# spead_ig.add_item(name='eq_coef_MyAntStr', id=0x1400+inputN,
# description='',
# shape=[], fmt=spead.mkfmt(('u', 32)),
# init_val=)
# ndarray = numpy.dtype(numpy.int64), (4096 * 40 * 1, 1, 1)
self.spead_meta_ig.add_item(name='timestamp', id=0x1600,
description='Timestamp of start of this integration. uint counting multiples '
'of ADC samples since last sync (sync_time, id=0x1027). Divide this '
'number by timestamp_scale (id=0x1046) to get back to seconds since '
'last sync when this integration was actually started.',
shape=[], fmt=spead.mkfmt(('u', spead.ADDRSIZE)))
self.spead_meta_ig.add_item(name='flags_xeng_raw', id=0x1601,
description='Flags associated with xeng_raw data output.'
'bit 34 - corruption or data missing during integration '
'bit 33 - overrange in data path '
'bit 32 - noise diode on during integration '
'bits 0 - 31 reserved for internal debugging',
shape=[], fmt=spead.mkfmt(('u', spead.ADDRSIZE)))
ndarray = numpy.dtype(numpy.int32), (self.n_chans, len(self.xops.get_baseline_order()), 2)
self.spead_meta_ig.add_item(name='xeng_raw', id=0x1800,
description='Raw data for %i xengines in the system. This item represents a '
'full spectrum (all frequency channels) assembled from lowest '
'frequency to highest frequency. Each frequency channel contains '
'the data for all baselines (n_bls given by SPEAD ID 0x100b). '
'Each value is a complex number -- two (real and imaginary) '
'unsigned integers.' % len(self.xhosts * self.x_per_fpga),
ndarray=ndarray)
# TODO hard-coded !!!!!!! :(
# self.spead_ig.add_item(name=("xeng_raw"),id=0x1800,
# description="Raw data for %i xengines in the system. This
# item represents a full spectrum (all frequency channels) assembled from lowest frequency
# to highest frequency. Each frequency channel contains the data for all baselines
# (n_bls given by SPEAD ID 0x100B). Each value is a complex number -- two
# (real and imaginary) unsigned integers."%(32),
# ndarray=(numpy.dtype(numpy.int32),(4096,((4*(4+1))/2)*4,2)))
# spead_ig.add_item(name='beamweight_MyAntStr', id=0x2000+inputN,
# description='',
# shape=[], fmt=spead.mkfmt(('u', 32)),
# init_val=)
# spead_ig.add_item(name='incoherent_sum', id=0x3000,
# description='',
# shape=[], fmt=spead.mkfmt(('u', 32)),
# init_val=)
# spead_ig.add_item(name='n_inputs', id=0x3100,
# description='',
# shape=[], fmt=spead.mkfmt(('u', spead.ADDRSIZE)),
# init_val=)
# spead_ig.add_item(name='digitiser_id', id=0x3101,
# description='',
# shape=[], fmt=spead.mkfmt(('u', spead.ADDRSIZE)),
# init_val=)
# spead_ig.add_item(name='digitiser_status', id=0x3102,
# description='',
# shape=[], fmt=spead.mkfmt(('u', spead.ADDRSIZE)),
# init_val=)
# spead_ig.add_item(name='pld_len', id=0x3103,
# description='',
# shape=[], fmt=spead.mkfmt(('u', spead.ADDRSIZE)),
# init_val=)
# spead_ig.add_item(name='raw_data_MyAntStr', id=0x3300+inputN,
# description='',
# shape=[], fmt=spead.mkfmt(('u', spead.ADDRSIZE)),
# init_val=)
# spead_ig.add_item(name='Reserved for SP-CAM meta-data', id=0x7000-0x7fff,
# description='',
# shape=[], fmt=spead.mkfmt(('u', spead.ADDRSIZE)),
# init_val=)
# spead_ig.add_item(name='feng_id', id=0xf101,
# description='',
# shape=[], fmt=spead.mkfmt(('u', spead.ADDRSIZE)),
# init_val=)
# spead_ig.add_item(name='feng_status', id=0xf102,
# description='',
# shape=[], fmt=spead.mkfmt(('u', spead.ADDRSIZE)),
# init_val=)
# spead_ig.add_item(name='frequency', id=0xf103,
# description='',
# shape=[], fmt=spead.mkfmt(('u', spead.ADDRSIZE)),
# init_val=)
# spead_ig.add_item(name='raw_freq_MyAntStr', id=0xf300+inputN,
# description='',
# shape=[], fmt=spead.mkfmt(('u', spead.ADDRSIZE)),
# init_val=)
# spead_ig.add_item(name='bf_MyBeamName', id=0xb000+beamN,
# description='',
# shape=[], fmt=spead.mkfmt(('u', spead.ADDRSIZE)),
# init_val=)
self.spead_tx.send_heap(self.spead_meta_ig.get_heap())
self.logger.info('Issued SPEAD data descriptor to %s:%i.' % (self.meta_destination[0],
self.meta_destination[1]))
def rx_inter(self,data_port=7148, sd_ip='127.0.0.1', sd_port=7149, acc_scale=True, filename=None, **kwargs):
'''
Process SPEAD data from X engines and forward it to the SD.
'''
print 'WARNING: This function is not yet tested. YMMV.'
logger=self.logger
logger.info("Data reception on port %i."%data_port)
rx = spead.TransportUDPrx(data_port, pkt_count=1024, buffer_size=51200000)
logger.info("Sending Signal Display data to %s:%i."%(sd_ip,sd_port))
tx_sd = spead.Transmitter(spead.TransportUDPtx(sd_ip, sd_port))
ig = spead.ItemGroup()
ig_sd = spead.ItemGroup()
if filename == None:
filename=str(int(time.time())) + ".synth.h5"
logger.info("Starting file %s."%(filename))
f = h5py.File(filename, mode="w")
data_ds = None
ts_ds = None
idx = 0
dump_size = 0
datasets = {}
datasets_index = {}
# we need these bits of meta data before being able to assemble and transmit signal display data
meta_required = ['n_chans','n_bls','n_xengs','center_freq','bls_ordering','bandwidth']
meta_desired = ['n_accs']
meta = {}
sd_frame = None
sd_slots = None
timestamp = None
# log the latest timestamp for which we've stored data
currentTimestamp = -1
# iterate through SPEAD heaps returned by the SPEAD receiver.
for heap in spead.iterheaps(rx):
ig.update(heap)
logger.debug("PROCESSING HEAP idx(%i) cnt(%i) @ %.4f" % (idx, heap.heap_cnt, time.time()))
for name in ig.keys():
item = ig.get_item(name)
# the item is not marked as changed and we already have a record for it, continue
if not item._changed and datasets.has_key(name):
continue
logger.debug("PROCESSING KEY %s @ %.4f" % (name, time.time()))
if name in meta_desired:
meta[name] = ig[name]
if name in meta_required:
meta[name] = ig[name]
meta_required.pop(meta_required.index(name))
if len(meta_required) == 0:
sd_frame = np.zeros((meta['n_chans'],meta['n_bls'],2),dtype=np.float32)
logger.info("Got all required metadata. Initialised sd frame to shape %s"%(str(sd_frame.shape)))
meta_required = ['n_chans','bandwidth','n_bls','n_xengs','center_freq','bls_ordering']
ig_sd = spead.ItemGroup()
for meta_item in meta_required:
ig_sd.add_item(
name=ig.get_item(meta_item).name,
id=ig.get_item(meta_item).id,
description=ig.get_item(meta_item).description,
#shape=ig.get_item(meta_item).shape,
#fmt=ig.get_item(meta_item).format,
init_val=ig.get_item(meta_item).get_value())
tx_sd.send_heap(ig_sd.get_heap())
sd_slots = np.zeros(meta['n_xengs'])
if not datasets.has_key(name):
# check to see if we have encountered this type before
shape = ig[name].shape if item.shape == -1 else item.shape
dtype = np.dtype(type(ig[name])) if shape == [] else item.dtype
if dtype is None: dtype = ig[name].dtype
# if we can't get a dtype from the descriptor, try and get one from the value
logger.info("Creating dataset for %s (%s,%s)."%(str(name),str(shape),str(dtype)))
f.create_dataset(name,[1] + ([] if list(shape) == [1] else list(shape)), maxshape=[None] + ([] if list(shape) == [1] else list(shape)), dtype=dtype)
dump_size += np.multiply.reduce(shape) * dtype.itemsize
datasets[name] = f[name]
datasets_index[name] = 0
# if we built from an empty descriptor
if not item._changed:
continue
else:
logger.info("Adding %s to dataset. New size is %i."%(name,datasets_index[name]+1))
f[name].resize(datasets_index[name]+1, axis=0)
# now we store this x engine's data for sending sd data.
if sd_frame is not None and name.startswith("xeng_raw"):
xeng_id = int(name[8:])
sd_frame[xeng_id::meta['n_xengs']] = ig[name]
logger.debug('Received data for Xeng %i @ %.4f' % (xeng_id, time.time()))
# we got a timestamp.
if sd_frame is not None and name.startswith("timestamp"):
xeng_id = int(name[9:])
timestamp = ig['sync_time'] + (ig[name] / ig['scale_factor_timestamp']) #in seconds since unix epoch
localTime = time.time()
print "Decoded timestamp for Xeng", xeng_id, ":", timestamp, " (", time.ctime(timestamp),") @ %.4f" % localTime, " ", time.ctime(localTime), "diff(", localTime-timestamp, ")"
# is this timestamp in the past?
if currentTimestamp > timestamp:
errorString = "Timestamp %.2f (%s) is earlier than the current timestamp %.2f (%s). Ignoring..." % (timestamp, time.ctime(timestamp), currentTimestamp, time.ctime(currentTimestamp))
logger.warning(errorString)
continue
# is this a new timestamp before a complete set?
if (timestamp > currentTimestamp) and sd_slots.any():
errorString = "New timestamp %.2f from Xeng%i before previous set %.2f sent" % (timestamp, xeng_id, currentTimestamp)
logger.warning(errorString)
sd_slots = np.zeros(meta['n_xengs'])
sd_frame = np.zeros((ig['n_chans'],ig['n_bls'],2),dtype=sd_frame.dtype)
currentTimestamp = -1
continue
# is this new timestamp in the past for this X engine?
if timestamp <= sd_slots[xeng_id]:
errorString = 'Xeng%i already on timestamp %.2f but got %.2f now, THIS SHOULD NOT HAPPEN' % (xeng_id, sd_slots[xeng_id], timestamp)
logger.error(errorString)
raise RuntimeError(errorString)
# update our info on which integrations we have
sd_slots[xeng_id] = timestamp
currentTimestamp = timestamp
# do we have integration data and timestamps for all the xengines? If so, send the SD frame.
if timestamp is not None and sd_frame is not None and sd_slots is not None and sd_slots.all():
ig_sd = spead.ItemGroup()
# make sure we have the right dtype for the sd data
ig_sd.add_item(name=('sd_data'), id=(0x3501), description="Combined raw data from all x engines.", ndarray=(sd_frame.dtype,sd_frame.shape))
ig_sd.add_item(name=('sd_timestamp'), id=0x3502, description='Timestamp of this sd frame in centiseconds since epoch (40 bit limitation).', shape=[], fmt=spead.mkfmt(('u',spead.ADDRSIZE)))
t_it = ig_sd.get_item('sd_data')
logger.info("Added SD frame with shape %s, dtype %s" % (str(t_it.shape),str(t_it.dtype)))
scale_factor=(meta['n_accs'] if meta.has_key('n_accs') else 1)
logger.info("Sending signal display frame with timestamp %i (%s). %s. @ %.4f" % (timestamp, time.ctime(timestamp), "Unscaled" if not acc_scale else "Scaled by %i" % (scale_factor), time.time()))
ig_sd['sd_data'] = sd_frame.astype(np.float32) if not acc_scale else (sd_frame / float(scale_factor)).astype(np.float32)
ig_sd['sd_timestamp'] = int(timestamp * 100)
tx_sd.send_heap(ig_sd.get_heap())
# reset the arrays that hold integration data
sd_slots = np.zeros(meta['n_xengs'])
sd_frame = np.zeros((ig['n_chans'],ig['n_bls'],2),dtype=sd_frame.dtype)
timestamp = None
f[name][datasets_index[name]] = ig[name]
datasets_index[name] += 1
item._changed = False
idx+=1
logger.info("Got a SPEAD end-of-stream marker. Closing File.")
f.flush()
f.close()
rx.stop()
sd_frame = None
sd_slots = None
ig_sd = None
