def processZ(Z1, Z2, startZ, ctime, etime):
Z = []
for i in range(len(Z1)):
if abs(Z1[i] - Z2[i]) > 60000:
Z.append(0)
else:
Z.append((Z1[i] + Z2[i]) / 2)
prevZ = startZ % 16.0
trueZ = startZ
trueZVect = []
for i in range(0, len(Z)):
z = Z[i]
curZ = z * (10.0 / 40961.0)
if abs(prevZ - curZ) > 7:
if prevZ < curZ:
print("wrapped, prevZ<curZ " + str(time_now()), flush=True)
trueZ = trueZ - (Zthresh - curZ + prevZ)
else:
print("Wrapped, prevZ>curZ " + str(time_now()), flush=True)
trueZ = trueZ + (Zthresh - prevZ + curZ)
print(Z1[i])
print(Z2[i])
print(prevZ)
print(curZ)
print(ctime)
print(etime)
else:
trueZ = trueZ + (curZ - prevZ)
trueZVect.append(trueZ)
prevZ = curZ
if len(trueZVect) == 0:
trueZVect = [trueZ]
return [trueZVect, trueZVect[len(trueZVect) - 1]]
async def run(self, parsed_args, output):
# produce output four times per second
# figure out how much output will be in each block
rate = parsed_args.rate
width = parsed_args.width
data_ts = utilities.time_now()
data_ts_inc = 1 / rate * 1e6
wait_time = 1 / OUTPUT_RATE
BLOCK_SIZE = rate / OUTPUT_RATE
fraction_remaining = 0
i = 0
# print("Starting random stream: %d elements @ %0.1fHz" % (width, rate))
while not self.stop_requested:
float_block_size = BLOCK_SIZE + fraction_remaining
int_block_size = int(np.floor(float_block_size))
fraction_remaining = float_block_size - int_block_size
data = np.random.rand(int_block_size, width)
self.avg = np.average(data)
self.stddev = np.std(data)
top_ts = data_ts + int_block_size * data_ts_inc
ts = np.array(np.linspace(data_ts,
top_ts,
int_block_size,
endpoint=False),
dtype=np.uint64)
data_ts = top_ts
await output.write(np.hstack((ts[:, None], data)))
await asyncio.sleep(wait_time)
i += 1
async def test_data_write(self):
await self.node.data_delete("/archive/data1")
pipe = await self.node.data_write("/archive/data1")
blk_size = 100
nblks = 1000
time = utilities.time_now()
for i in range(nblks):
ts = np.linspace(time, time + blk_size, blk_size)
self.assertEqual(min(np.diff(ts)), 1)
data1 = np.random.random((blk_size, 1))
data2 = np.random.random((blk_size, 1))
res = np.hstack((ts[:, None], data1, data2))
time = time + blk_size + 1
await pipe.write(res)
await pipe.close()
# now read the data back
pipe = await self.node.data_read("/archive/data1", start=0)
nrows = 0
while not pipe.is_empty():
data = await pipe.read()
nrows += len(data)
pipe.consume(len(data))
self.assertEqual(blk_size * nblks, nrows)
async def run(self, parsed_args, output):
count = 0
while not self.stop_requested:
await output.write(np.array([[time_now(), count]]))
await asyncio.sleep(0.1)
count += parsed_args.step
async def _get_current_weather(self):
pipe = await self.node.data_read(self.weather_stream,
start=time_now() - 60 * 60 * 1e6)
try:
data = await pipe.read()
except EmptyPipe:
return []
pipe.consume(len(data))
await pipe.close()
return data['data'][-1]
async def ambient_weather(request):
pipe = request.app["pipe"]
keys = [
"tempf", "humidity", "hourlyrainin", "baromrelin", "windspeedmph",
"windgustmph", "winddir", "solarradiation", "uv"
]
data = [time_now()]
for key in keys:
data.append(float(request.query[key]))
await pipe.write(np.array([data]))
return web.Response(text="OK")
async def run(self, parsed_args, output):
with open(parsed_args.file, 'r') as f:
for line in f:
data = np.fromstring(line, dtype=float,
sep=parsed_args.delimiter)
if parsed_args.timestamp:
data = np.insert(data, 0, utilities.time_now())
await output.write(np.array([data]))
#TODO is this necessary?
await asyncio.sleep(0.1)
if self.stop_requested:
break
async def run(self, parsed_args, output):
while True:
await asyncio.sleep(0.5)
self.gps.update()
if not self.gps.has_fix:
print('Waiting for fix...')
await asyncio.sleep(1)
continue
await output.write(np.array([[time_now(),
self.gps.latitude,
self.gps.longitude]]))
print("data")
async def run(self, parsed_args, output):
data = 100 * np.sin(np.arange(0, 2 * np.pi, 2 * np.pi / rows))
data.shape = (rows, 1)
ts_inc = 1 / rows * (1 / freq) * 1e6 # microseconds
data_ts = time_now()
while not self.stop_requested:
top_ts = data_ts + 100 * ts_inc
ts = np.array(np.linspace(data_ts, top_ts, rows, endpoint=False),
dtype=np.uint64)
ts.shape = (rows, 1)
ts_data = np.hstack((ts, data))
await output.write(ts_data)
data_ts = top_ts
await asyncio.sleep(1 / freq)
raise ValueError("Intentional Exception")
async def run(self, parsed_args, output):
start_ts = time_now()
# run 5 times per second
period = 1
samples_per_period = np.round(parsed_args.rate * period)
while True:
end_ts = start_ts + period * 1e6
ts = np.linspace(start_ts,
end_ts,
samples_per_period,
endpoint=False)
vals = np.linspace(0, 33, samples_per_period)
start_ts = end_ts
chunk = np.hstack((ts[:, None], vals[:, None]))
await output.write(chunk)
await asyncio.sleep(period)
async def run(self, parsed_args, output):
while True:
req = requests.get("http://api.openweathermap.org/data/2.5/" +
"weather?" +
"id=%s&units=imperial&" % parsed_args.city_id +
"APPID=%s" % parsed_args.api_key)
resp = req.json()
temp = resp['main']['temp']
pressure = resp['main']['pressure'] * 0.02953 # convert to inHg
humidity = resp['main']['humidity']
windspeed = resp['wind']['speed']
winddir = resp['wind']['deg']
ts = time_now()
await output.write(
np.array([[ts, temp, humidity, pressure, windspeed, winddir]]))
await asyncio.sleep(60) # every minute
async def run(self, parsed_args, output):
start_ts = time_now()
period = 1
samples_per_period = np.round(parsed_args.rate * period)
while True:
try:
end_ts = start_ts + period * 1e6
ts = np.linspace(start_ts, end_ts,
samples_per_period, endpoint=False)
vals = np.linspace(0, 33, samples_per_period)
start_ts = end_ts
chunk = np.hstack((ts[:, None], vals[:, None]))
# simulate an error
if np.random.rand() < ERROR_PROBABILITY:
raise ValueError
await output.write(chunk)
except ValueError:
logging.error("simulated data interruption")
await output.close_interval()
await asyncio.sleep(period)
async def _get_power_data(self):
one_day = 24 * 60 * 60 * 1e6
one_week = 7 * one_day
time_window = one_day
pipe = await self.node.data_read(self.power_stream,
start=time_now() - time_window,
max_rows=1000)
power_data = []
offset = _utc_offset().total_seconds() * 1e3
while True:
try:
data = await pipe.read(flatten=True)
except EmptyPipe:
break
pipe.consume(len(data))
power_data += [[(d[0] / 1e3) + offset, (d[1] + d[8]) / 1e3]
for d in data]
if pipe.end_of_interval:
power_data.append(None)
await pipe.close()
return power_data
async def run(self, parsed_args, output):
aq_device = None
ctr_device = None
descriptor_index = 0
interface_type = InterfaceType.USB
low_encoder = 0
encoder_count = 5
sample_rate = 1000.0 # 1000 # Hz
samples_per_channel = 10000 # 10000
scan_options = ScanOption.CONTINUOUS
scan_flags = CInScanFlag.DEFAULT
encoder_type = CounterMeasurementType.ENCODER
encoder_mode = CounterMeasurementMode.ENCODER_X4
edge_detection = CounterEdgeDetection.RISING_EDGE
tick_size = CounterTickSize.TICK_20ns
debounce_mode = CounterDebounceMode.TRIGGER_AFTER_STABLE
debounce_time = CounterDebounceTime.DEBOUNCE_7500ns
config_flags = CConfigScanFlag.DEFAULT
daq_device = None
try:
# Get descriptors for all of the available DAQ devices.
devices = get_daq_device_inventory(interface_type)
number_of_devices = len(devices)
if number_of_devices == 0:
raise ValueError('Error: No DAQ devices found')
# Create the DAQ device object associated with the specified descriptor index.
daq_device = DaqDevice(devices[descriptor_index])
# Get the CtrDevice object and verify that it is valid.
ctr_device = daq_device.get_ctr_device()
if ctr_device is None:
raise ValueError(
'Error: The DAQ device does not support counters')
# Verify that the specified device supports hardware pacing for counters.
ctr_info = ctr_device.get_info()
if not ctr_info.has_pacer():
raise ValueError(
'Error: The specified DAQ device does not support hardware paced counter input'
)
# Establish a connection to the DAQ device.
descriptor = daq_device.get_descriptor()
daq_device.connect()
# Get the encoder counter channels.
encoder_counters = get_supported_encoder_counters(ctr_info)
if len(encoder_counters) == 0:
raise ValueError(
'Error: The specified DAQ device does not support encoder channels'
)
# Verify that the low_encoder number is valid.
first_encoder = encoder_counters[0]
if low_encoder < first_encoder:
low_encoder = first_encoder
if low_encoder > first_encoder + len(encoder_counters) - 1:
low_encoder = first_encoder
# Verify that the encoder count is valid.
if encoder_count > len(encoder_counters):
encoder_count = len(encoder_counters)
# Set the high_encoder channel.
high_encoder = low_encoder + encoder_count - 1
if high_encoder > first_encoder + len(encoder_counters) - 1:
high_encoder = first_encoder + len(encoder_counters) - 1
# update the actual number of encoders being used
encoder_count = high_encoder - low_encoder + 1
# Clear the counter, and configure the counter as an encoder.
for encoder in range(low_encoder, high_encoder + 1):
ctr_device.c_config_scan(encoder, encoder_type, encoder_mode,
edge_detection, tick_size,
debounce_mode, debounce_time,
config_flags)
# Allocate a buffer to receive the data.
data = create_int_buffer(encoder_count, samples_per_channel)
# Start the scan
ctr_device.c_in_scan(low_encoder, high_encoder,
samples_per_channel, sample_rate,
scan_options, scan_flags, data)
# prev_samples_per_channel = 0
# cur_samples_per_channel = 0
prev_index = 0
XVect = []
YVect = []
ZVect = []
EVect = []
AllVect = []
startX = 0.0
startY = 0.0
startZ = 0.0
startE = 0.0
# newZ = []
prev_index = 0
start_time = time_now()
cur_time = start_time + 1
while not self.stop_requested:
status, transfer_status = ctr_device.get_scan_status()
# not sure if can await the above line
index = transfer_status.current_index
# print(index)
# edge starting condition
if index == -1:
AllVect = [0.0, 0.0, 0.0, 0.0, 0.0]
# normal condition
else:
# has not looped around
if prev_index < index:
AllVect = data[prev_index:index]
# has wrapped around
else:
AllVect = data[prev_index:] + data[0:index]
prev_index = index
# print(AllVect)
XVect = AllVect[3::5]
YVect = AllVect[1::5]
Z1Vect = AllVect[0::5]
Z2Vect = AllVect[2::5]
EVect = AllVect[4::5]
end_time = cur_time + (len(XVect) -
1) * 1e3 # cur_time is in us
[XVect, startX] = processX(XVect, startX)
[YVect, startY] = processY(YVect, startY)
[EVect, startE] = processE(EVect, startE)
[ZVect, startZ] = processZ(Z1Vect, Z2Vect, startZ, cur_time,
end_time)
Xarray = np.array(XVect)
Yarray = np.array(YVect)
Zarray = np.array(ZVect)
Earray = np.array(EVect) * -1 #invert for positive extrusion
Xarray = np.vstack(Xarray)
Yarray = np.vstack(Yarray)
Zarray = np.vstack(Zarray)
Earray = np.vstack(Earray)
time_array = np.linspace(cur_time, end_time, len(XVect))
time_array = np.vstack(time_array)
# print("before all output")
All_Output = np.hstack(
(time_array, Xarray, Yarray, Zarray, Earray))
# print("after all output")
# print(All_Output)
await output.write(np.array(All_Output))
# print("after writing")
# print(len(YVect))
# for i in range(len(YVect)):
# print(str(YVect[i])+ "\t"+str(newY[i]))
await asyncio.sleep(1)
cur_time = end_time + 1e3
if status != ScanStatus.RUNNING:
break
# except (ValueError, NameError, SyntaxError):
# break
# print("next while loop cycle")
except ValueError as e:
print(str(e))
except Exception as e:
raise e
finally:
if daq_device:
if ctr_device:
ctr_device.scan_stop()
if daq_device.is_connected():
daq_device.disconnect()
daq_device.release()
async def run(self, parsed_args, output):
while True:
value = np.random.rand() # data from sensor
await output.write(np.array([[time_now(), value]]))
await asyncio.sleep(1)
