def parseBitStream(bits, elevation=0.0, inputDataDict=None, verbose=False):
"""
Given a sequence of bits from readRTL/readRTLFile, find all of the
valid Oregon Scientific v2.1 packets and return the data contained
within the packets as a dictionary. In the process, compute various
derived quantities (dew point, windchill, and sea level corrected
pressure).
.. note::
The sea level corrected pressure is only compute if the elevation
(in meters) is set to a non-zero value.
"""
# Setup the output dictionary
output = {}
if inputDataDict is not None:
for key, value in inputDataDict.iteritems():
output[key] = value
# Find the packets and save the output
i = 0
while i < len(bits) - 32:
## Check for a valid preamble (and its logical negation counterpart)
if sum(bits[i:i + 32:2]) == 16 and sum(bits[i + 1:i + 1 + 32:2]) == 0:
### Assume nothing
valid = False
### Packet #1
packet = bits[i + 0::2]
try:
valid, sensorName, channel, sensorData = parsePacketv21(
packet, verbose=verbose)
except IndexError:
pass
if not valid:
### Packet #2
packet = bits[i + 1::2]
try:
valid, sensorName, channel, sensorData = parsePacketv21(
packet, verbose=verbose)
except IndexError:
pass
### Data reorganization and computed quantities
if valid:
#### Dew point - indoor and output
if sensorName in ('BHTR968', 'THGR268', 'THGR968'):
sensorData['dewpoint'] = computeDewPoint(
sensorData['temperature'], sensorData['humidity'])
#### Sea level corrected barometric pressure
if sensorName in ('BHTR968', ) and elevation != 0.0:
sensorData['pressure'] = computeSeaLevelPressure(
sensorData['pressure'], elevation)
#### Disentangle the indoor temperatures from the outdoor temperatures
if sensorName == 'BHTR968':
for key in ('temperature', 'humidity', 'dewpoint'):
newKey = 'indoor%s' % key.capitalize()
sensorData[newKey] = sensorData[key]
del sensorData[key]
#### Multiplex the THGR268 values
for key in sensorData.keys():
if key in ('temperature', 'humidity', 'dewpoint'):
if sensorName == 'THGR968':
output[key] = sensorData[key]
else:
try:
output['alt%s' %
key.capitalize()][channel -
1] = sensorData[key]
except KeyError:
output['alt%s' % key.capitalize()] = [
None, None, None, None
]
output['alt%s' %
key.capitalize()][channel -
1] = sensorData[key]
else:
output[key] = sensorData[key]
i += 1
# Compute combined quantities
if 'temperature' in output.keys() and 'average' in output.keys():
output['windchill'] = computeWindchill(output['temperature'],
output['average'])
# Done
return output
def parseBitStream(bits, elevation=0.0, inputDataDict=None, verbose=False):
"""
Given a sequence of bits from readRTL/readRTLFile, find all of the
valid Oregon Scientific v2.1 packets and return the data contained
within the packets as a dictionary. In the process, compute various
derived quantities (dew point, windchill, and sea level corrected
pressure).
.. note::
The sea level corrected pressure is only compute if the elevation
(in meters) is set to a non-zero value.
"""
# Setup the output dictionary
output = {}
if inputDataDict is not None:
for key,value in inputDataDict.iteritems():
output[key] = value
# Find the packets and save the output
i = 0
while i < len(bits)-32:
## Check for a valid preamble (and its logical negation counterpart)
if sum(bits[i:i+32:2]) == 16 and sum(bits[i+1:i+1+32:2]) == 0:
### Assume nothing
valid = False
### Packet #1
packet = bits[i+0::2]
try:
valid, sensorName, channel, sensorData = parsePacketv21(packet, verbose=verbose)
except IndexError:
pass
if not valid:
### Packet #2
packet = bits[i+1::2]
try:
valid, sensorName, channel, sensorData = parsePacketv21(packet, verbose=verbose)
except IndexError:
pass
### Data reorganization and computed quantities
if valid:
#### Dew point - indoor and output
if sensorName in ('BTHGN129', 'THGN800', 'THGN800'):
sensorData['dewpoint'] = computeDewPoint(sensorData['temperature'], sensorData['humidity'])
#### Disentangle the indoor temperatures from the outdoor temperatures
if sensorName == 'BTHGN129':
for key in ('temperature', 'humidity', 'dewpoint','pressure'):
output[key] = sensorData[key]
#### Multiplex the THGN800 values
for key in sensorData.keys():
if key in ('temperature', 'humidity', 'dewpoint'):
if sensorName == 'THGN800':
output[key] = sensorData[key]
else:
try:
output['alt%s' % key.capitalize()][channel-1] = sensorData[key]
except KeyError:
output['alt%s' % key.capitalize()] = [None, None, None, None]
output['alt%s' % key.capitalize()][channel-1] = sensorData[key]
else:
output[key] = sensorData[key]
i += 1
# Compute combined quantities
if 'temperature' in output.keys() and 'average' in output.keys():
output['windchill'] = computeWindchill(output['temperature'], output['average'])
# Done
return output
def parsePacketStream(packets, elevation=0.0, inputDataDict=None):
"""
Given a sequence of two-element type,payload packets from read433,
find all of the Oregon Scientific sensor values and return the data
as a dictionary. In the process, compute various derived quantities
(dew point, windchill, and sea level correctedpressure).
.. note::
The sea level corrected pressure is only compute if the elevation
(in meters) is set to a non-zero value.
"""
# Setup the output dictionary
output = {}
if inputDataDict is not None:
for key,value in inputDataDict.iteritems():
output[key] = value
# Parse the packet payload and save the output
gspd = []
gdir = []
for pType,pPayload in packets:
if pType == 'OSV2':
valid, sensorName, channel, sensorData = parsePacketv21(pPayload)
else:
continue
## Data reorganization and computed quantities
if valid:
### Gust tracker
if sensorName == 'WGR968':
gspd.append( sensorData['gust'] )
gdir.append( sensorData['direction'] )
### Dew point - indoor and output
if sensorName in ('BHTR968', 'THGR268', 'THGR968'):
sensorData['dewpoint'] = computeDewPoint(sensorData['temperature'], sensorData['humidity'])
### Sea level corrected barometric pressure
if sensorName in ('BHTR968',) and elevation != 0.0:
sensorData['pressure'] = computeSeaLevelPressure(sensorData['pressure'], elevation)
### Disentangle the indoor temperatures from the outdoor temperatures
if sensorName == 'BHTR968':
for key in ('temperature', 'humidity', 'dewpoint'):
newKey = 'indoor%s' % key.capitalize()
sensorData[newKey] = sensorData[key]
del sensorData[key]
### Multiplex the THGR268 values
for key in sensorData.keys():
if key in ('temperature', 'humidity', 'dewpoint'):
if sensorName == 'THGR968':
output[key] = sensorData[key]
else:
try:
output['alt%s' % key.capitalize()][channel-1] = sensorData[key]
except KeyError:
output['alt%s' % key.capitalize()] = [None, None, None, None]
output['alt%s' % key.capitalize()][channel-1] = sensorData[key]
else:
output[key] = sensorData[key]
# Compute combined quantities
## Maximum gust observed
if len(gspd) > 0:
best = gspd.index( max(gspd) )
output['gust'] = gspd[best]
output['gustDirection'] = gdir[best]
## Windchill
if 'temperature' in output.keys() and 'average' in output.keys():
output['windchill'] = computeWindchill(output['temperature'], output['average'])
# Done
return output
def parsePacketStream(packets, elevation=0.0, inputDataDict=None):
"""
Given a sequence of two-element type,payload packets from read433,
find all of the Oregon Scientific sensor values and return the data
as a dictionary. In the process, compute various derived quantities
(dew point, windchill, and sea level correctedpressure).
.. note::
The sea level corrected pressure is only compute if the elevation
(in meters) is set to a non-zero value.
"""
# Setup the output dictionary
output = {}
if inputDataDict is not None:
for key,value in inputDataDict.iteritems():
output[key] = value
# Parse the packet payload and save the output
gspd = []
gdir = []
for pType,pPayload in packets:
if pType == 'OSV2':
valid, sensorName, channel, sensorData = parsePacketv21(pPayload)
else:
continue
## Data reorganization and computed quantities
if valid:
### Gust tracker
if sensorName == 'WGR968':
gspd.append( sensorData['gust'] )
gdir.append( sensorData['direction'] )
### Dew point - indoor and output
if sensorName in ('BHTR968', 'THGR268', 'THGR968'):
sensorData['dewpoint'] = computeDewPoint(sensorData['temperature'], sensorData['humidity'])
### Sea level corrected barometric pressure
if sensorName in ('BHTR968',) and elevation != 0.0:
sensorData['pressure'] = computeSeaLevelPressure(sensorData['pressure'], elevation)
### Disentangle the indoor temperatures from the outdoor temperatures
if sensorName == 'BHTR968':
for key in ('temperature', 'humidity', 'dewpoint'):
newKey = 'indoor%s' % key.capitalize()
sensorData[newKey] = sensorData[key]
del sensorData[key]
### Multiplex the THGR268 values
for key in sensorData.keys():
if key in ('temperature', 'humidity', 'dewpoint'):
if sensorName == 'THGR968':
output[key] = sensorData[key]
else:
try:
output['alt%s' % key.capitalize()][channel-1] = sensorData[key]
except KeyError:
output['alt%s' % key.capitalize()] = [None, None, None, None]
output['alt%s' % key.capitalize()][channel-1] = sensorData[key]
else:
output[key] = sensorData[key]
# Compute combined quantities
## Maximum gust observed
if len(gspd) > 0:
best = gspd.index( max(gspd) )
output['gust'] = gspd[best]
output['gustDirection'] = gdir[best]
## Windchill
if 'temperature' in output.keys() and 'average' in output.keys():
output['windchill'] = computeWindchill(output['temperature'], output['average'])
# Done
return output
