def parseADCPdata(data, staInfo, ID):
basetime = datetime(1970, 1, 1)
# Find the number of bins
nz = maxList(data['"bin (count)"'])
nt = len(data['"bin (count)"']) / nz
# Get the depth data
ele = -np.array(data['"bin_distance (m)"\n'][0:nz])
# Load in the data
time = np.zeros(nt)
u = np.zeros((nt, nz))
v = np.zeros((nt, nz))
T = np.zeros(nt)
ii = 0
for tt in range(0, nt):
dt = data['date_time'][ii] - basetime
time[tt] = dt.total_seconds() / 60.0
T[tt] = data['"sea_water_temperature (C)"'][ii]
for zz in range(0, nz):
uu, vv = airsea.convertSpeedDirn(
data['"direction_of_sea_water_velocity (degree)"'][ii],
data['"sea_water_speed (cm/s)"'][ii] / 100)
u[tt, zz] = uu
v[tt, zz] = vv
ii += 1
# Insert each variable into a list
ncdict = []
# U
coords = [{'Name':'longitude','Value':staInfo[ID]['lon'],'units':'degrees East'},\
{'Name':'latitude','Value':staInfo[ID]['lat'],'units':'degrees North'},\
{'Name':'elevation','Value':ele,'units':'metres','positive':'up'},\
{'Name':'time','Value':time,'units':'minutes since 1970-01-01 00:00:00'}]
attribs = {'StationID':ID,'StationName':staInfo[ID]['name'],'Data':u,\
'coordinates':'time, elevation, latitude, longitude','long_name':'Eastward Water Velocity Component',\
'units':'m/s','coords':coords}
ncdict.append({'water_u': attribs})
# V
coords = [{'Name':'longitude','Value':staInfo[ID]['lon'],'units':'degrees East'},\
{'Name':'latitude','Value':staInfo[ID]['lat'],'units':'degrees North'},\
{'Name':'elevation','Value':ele,'units':'metres','positive':'up'},\
{'Name':'time','Value':time,'units':'minutes since 1970-01-01 00:00:00'}]
attribs = {'StationID':ID,'StationName':staInfo[ID]['name'],'Data':v,\
'coordinates':'time, elevation, latitude, longitude','long_name':'Northward Water Velocity Component',\
'units':'m/s','coords':coords}
ncdict.append({'water_v': attribs})
# T
coords = [{'Name':'longitude','Value':staInfo[ID]['lon'],'units':'degrees East'},\
{'Name':'latitude','Value':staInfo[ID]['lat'],'units':'degrees North'},\
{'Name':'elevation','Value':ele[0],'units':'metres','positive':'up'},\
{'Name':'time','Value':time,'units':'minutes since 1970-01-01 00:00:00'}]
attribs = {'StationID':ID,'StationName':staInfo[ID]['name'],'Data':T,\
'coordinates':'time, elevation, latitude, longitude','long_name':'Sea Water Temperature',\
'units':'degrees C','coords':coords}
ncdict.append({'watertemp': attribs})
return ncdict
def parseADCPdata(data,staInfo,ID):
basetime = datetime(1970,1,1)
# Find the number of bins
nz = maxList(data['"bin (count)"'])
nt = len(data['"bin (count)"'])/nz
# Get the depth data
ele = -np.array(data['"bin_distance (m)"\n'][0:nz])
# Load in the data
time = np.zeros(nt)
u = np.zeros((nt,nz))
v = np.zeros((nt,nz))
T = np.zeros(nt)
ii=0
for tt in range(0,nt):
dt = data['date_time'][ii]-basetime
time[tt] = dt.total_seconds()/60.0
T[tt]=data['"sea_water_temperature (C)"'][ii]
for zz in range(0,nz):
uu,vv=airsea.convertSpeedDirn(data['"direction_of_sea_water_velocity (degree)"'][ii],data['"sea_water_speed (cm/s)"'][ii]/100)
u[tt,zz]=uu
v[tt,zz]=vv
ii+=1
# Insert each variable into a list
ncdict = []
# U
coords = [{'Name':'longitude','Value':staInfo[ID]['lon'],'units':'degrees East'},\
{'Name':'latitude','Value':staInfo[ID]['lat'],'units':'degrees North'},\
{'Name':'elevation','Value':ele,'units':'metres','positive':'up'},\
{'Name':'time','Value':time,'units':'minutes since 1970-01-01 00:00:00'}]
attribs = {'StationID':ID,'StationName':staInfo[ID]['name'],'Data':u,\
'coordinates':'time, elevation, latitude, longitude','long_name':'Eastward Water Velocity Component',\
'units':'m/s','coords':coords}
ncdict.append({'water_u':attribs})
# V
coords = [{'Name':'longitude','Value':staInfo[ID]['lon'],'units':'degrees East'},\
{'Name':'latitude','Value':staInfo[ID]['lat'],'units':'degrees North'},\
{'Name':'elevation','Value':ele,'units':'metres','positive':'up'},\
{'Name':'time','Value':time,'units':'minutes since 1970-01-01 00:00:00'}]
attribs = {'StationID':ID,'StationName':staInfo[ID]['name'],'Data':v,\
'coordinates':'time, elevation, latitude, longitude','long_name':'Northward Water Velocity Component',\
'units':'m/s','coords':coords}
ncdict.append({'water_v':attribs})
# T
coords = [{'Name':'longitude','Value':staInfo[ID]['lon'],'units':'degrees East'},\
{'Name':'latitude','Value':staInfo[ID]['lat'],'units':'degrees North'},\
{'Name':'elevation','Value':ele[0],'units':'metres','positive':'up'},\
{'Name':'time','Value':time,'units':'minutes since 1970-01-01 00:00:00'}]
attribs = {'StationID':ID,'StationName':staInfo[ID]['name'],'Data':T,\
'coordinates':'time, elevation, latitude, longitude','long_name':'Sea Water Temperature',\
'units':'degrees C','coords':coords}
ncdict.append({'watertemp':attribs})
return ncdict
def ishData2struct(gzfile, station_id, station_name):
"""
Convert the data into a useful structure array (dictionary)
"""
### Input Variables
#gzfile = './rawdata/722420-12923-2012.gz'
#station_id = '722420-12923'
#station_name = 'test'
###
print 'Reading ISH gz file: %s...' % gzfile
ishdata = readRawGZdata(gzfile)
# Create the base structure (dictionary)
station = {}
station['StationName'] = station_name
station['StationID'] = station_id
station['Latitude'] = []
station['Longitude'] = []
station['Tair'] = {
'Data': [],
'Time': [],
'Units': 'Celsius',
'Longname': 'Air Temperature',
'Height': [],
'TimeUnits': 'minutes since 1970-01-01 00:00:00'
}
station['Pair'] = {
'Data': [],
'Time': [],
'Units': 'hPa',
'Longname': 'Air Pressure',
'Height': [],
'TimeUnits': 'minutes since 1970-01-01 00:00:00'
}
station['Uwind'] = {
'Data': [],
'Time': [],
'Units': 'm s-1',
'Longname': 'Eastward wind velocity component',
'Height': [],
'TimeUnits': 'minutes since 1970-01-01 00:00:00'
}
station['Vwind'] = {
'Data': [],
'Time': [],
'Units': 'm s-1',
'Longname': 'Northward wind velocity component',
'Height': [],
'TimeUnits': 'minutes since 1970-01-01 00:00:00'
}
station['RH'] = {
'Data': [],
'Time': [],
'Units': 'percent',
'Longname': 'Relative Humidity',
'Height': [],
'TimeUnits': 'minutes since 1970-01-01 00:00:00'
}
station['cloud'] = {
'Data': [],
'Time': [],
'Units': 'dimensionless',
'Longname': 'Cloud cover fraction',
'TimeUnits': 'minutes since 1970-01-01 00:00:00'
}
station['rain'] = {
'Data': [],
'Time': [],
'Units': 'kg m2 s-1',
'Longname': 'rain fall rate',
'TimeUnits': 'minutes since 1970-01-01 00:00:00'
}
# Loop through the ishdata
ii = 0
basetime = datetime(1970, 1, 1)
for dd in ishdata:
if ii == 0:
station['Latitude'] = dd['lat']
station['Longitude'] = dd['lon']
# Convert the time to a suitable time format
t = datetime.strptime(dd['yyyymmdd'] + dd['hhmm'], '%Y%m%d%H%M')
dt = t - basetime
tobs = dt.total_seconds() / 60.0
# tobs = (t.toordinal()-basetime.toordinal())*1440.0
# Check for missing values here
# Append the required data fields
station['Tair']['Data'].append(dd['airtemp'])
station['Tair']['Time'].append(tobs)
if ii == 0:
station['Tair']['Height'] = dd['ele']
station['Pair']['Data'].append(dd['airpres'])
station['Pair']['Time'].append(tobs)
if ii == 0:
station['Pair']['Height'] = dd['ele']
if np.size(dd['windspd']) == np.size(dd['winddir']):
spd = dd['windspd']
if spd >= 999: spd = np.NaN
dirn = dd['winddir']
if dirn >= 999: dirn = np.NaN
# Note the flip of direction to go to cartesian vectors
theta = np.mod(dirn - 180, 360)
[Uwind, Vwind] = airsea.convertSpeedDirn(theta, spd)
station['Uwind']['Data'].append(Uwind)
station['Uwind']['Time'].append(tobs)
if ii == 0:
station['Uwind']['Height'] = dd['ele']
station['Vwind']['Data'].append(Vwind)
station['Vwind']['Time'].append(tobs)
if ii == 0:
station['Vwind']['Height'] = dd['ele']
rh = returnHumidity(dd)
if np.size(rh) > 0:
station['RH']['Data'].append(rh)
station['RH']['Time'].append(tobs)
if ii == 0:
station['RH']['Height'] = dd['ele']
rain = returnRainfall(dd)
if np.size(rain) > 0:
station['rain']['Data'].append(rain)
station['rain']['Time'].append(tobs)
cloud = returnCloudCover(dd)
if np.size(cloud) > 0:
station['cloud']['Data'].append(cloud)
station['cloud']['Time'].append(tobs)
# Print a summary
print 'File Summary:'
print 'No. of Tair observations - %d' % len(station['Tair']['Data'])
print 'No. of Pair observations - %d' % len(station['Pair']['Data'])
print 'No. of Uwind observations - %d' % len(station['Uwind']['Data'])
print 'No. of Vwind observations - %d' % len(station['Vwind']['Data'])
print 'No. of RH observations - %d' % len(station['RH']['Data'])
print 'No. of rain observations - %d' % len(station['rain']['Data'])
print 'No. of cloud observations - %d' % len(station['cloud']['Data'])
print '############# File read successfully################\n'
return station
def ishData2struct(gzfile,station_id,station_name):
"""
Convert the data into a useful structure array (dictionary)
"""
### Input Variables
#gzfile = './rawdata/722420-12923-2012.gz'
#station_id = '722420-12923'
#station_name = 'test'
###
print 'Reading ISH gz file: %s...' % gzfile
ishdata = readRawGZdata(gzfile)
# Create the base structure (dictionary)
station={}
station['StationName']=station_name
station['StationID']=station_id
station['Latitude']=[]
station['Longitude']=[]
station['Tair'] = {'Data':[],'Time':[],'Units':'Celsius','Longname':'Air Temperature','Height':[],'TimeUnits':'minutes since 1970-01-01 00:00:00'}
station['Pair'] = {'Data':[],'Time':[],'Units':'hPa','Longname':'Air Pressure','Height':[],'TimeUnits':'minutes since 1970-01-01 00:00:00'}
station['Uwind'] = {'Data':[],'Time':[],'Units':'m s-1','Longname':'Eastward wind velocity component','Height':[],'TimeUnits':'minutes since 1970-01-01 00:00:00'}
station['Vwind'] = {'Data':[],'Time':[],'Units':'m s-1','Longname':'Northward wind velocity component','Height':[],'TimeUnits':'minutes since 1970-01-01 00:00:00'}
station['RH'] = {'Data':[],'Time':[],'Units':'percent','Longname':'Relative Humidity','Height':[],'TimeUnits':'minutes since 1970-01-01 00:00:00'}
station['cloud'] = {'Data':[],'Time':[],'Units':'dimensionless','Longname':'Cloud cover fraction','TimeUnits':'minutes since 1970-01-01 00:00:00'}
station['rain'] = {'Data':[],'Time':[],'Units':'kg m2 s-1','Longname':'rain fall rate','TimeUnits':'minutes since 1970-01-01 00:00:00'}
# Loop through the ishdata
ii=0
basetime = datetime(1970,1,1)
for dd in ishdata:
if ii == 0:
station['Latitude'] = dd['lat']
station['Longitude'] = dd['lon']
# Convert the time to a suitable time format
t = datetime.strptime(dd['yyyymmdd']+dd['hhmm'],'%Y%m%d%H%M')
dt = t-basetime
tobs = dt.total_seconds()/60.0
# tobs = (t.toordinal()-basetime.toordinal())*1440.0
# Check for missing values here
# Append the required data fields
station['Tair']['Data'].append(dd['airtemp'])
station['Tair']['Time'].append(tobs)
if ii == 0:
station['Tair']['Height'] = dd['ele']
station['Pair']['Data'].append(dd['airpres'])
station['Pair']['Time'].append(tobs)
if ii == 0:
station['Pair']['Height'] = dd['ele']
if np.size(dd['windspd']) == np.size(dd['winddir']):
spd=dd['windspd']
if spd >= 999: spd=np.NaN
dirn=dd['winddir']
if dirn >= 999: dirn=np.NaN
# Note the flip of direction to go to cartesian vectors
theta = np.mod(dirn-180,360)
[Uwind,Vwind] = airsea.convertSpeedDirn(theta,spd)
station['Uwind']['Data'].append(Uwind)
station['Uwind']['Time'].append(tobs)
if ii == 0:
station['Uwind']['Height'] = dd['ele']
station['Vwind']['Data'].append(Vwind)
station['Vwind']['Time'].append(tobs)
if ii == 0:
station['Vwind']['Height'] = dd['ele']
rh = returnHumidity(dd)
if np.size(rh) > 0:
station['RH']['Data'].append(rh)
station['RH']['Time'].append(tobs)
if ii == 0:
station['RH']['Height'] = dd['ele']
rain = returnRainfall(dd)
if np.size(rain) > 0:
station['rain']['Data'].append(rain)
station['rain']['Time'].append(tobs)
cloud = returnCloudCover(dd)
if np.size(cloud) > 0:
station['cloud']['Data'].append(cloud)
station['cloud']['Time'].append(tobs)
# Print a summary
print 'File Summary:'
print 'No. of Tair observations - %d' % len(station['Tair']['Data'])
print 'No. of Pair observations - %d' % len(station['Pair']['Data'])
print 'No. of Uwind observations - %d' % len(station['Uwind']['Data'])
print 'No. of Vwind observations - %d' % len(station['Vwind']['Data'])
print 'No. of RH observations - %d' % len(station['RH']['Data'])
print 'No. of rain observations - %d' % len(station['rain']['Data'])
print 'No. of cloud observations - %d' % len(station['cloud']['Data'])
print '############# File read successfully################\n'
return station
