def getHistorical(years, stationID='46011', workingdirectory=None):
#
# Get historical data from ndbc
#
import numpy as np
import spectral
#
start = True
for year in years:
#
url = 'http://www.ndbc.noaa.gov/data/historical/swden/' + stationID + \
'w' + '{:4d}'.format(year) + '.txt.gz'
E, f, date = getSpectralData(url,
workingdirectory=None,
kind=0,
historical=True)
if start:
start = False
spec = E
freq = f
dates = date
else:
spec = np.concatenate((spec, E), axis=0)
dates = np.concatenate((dates, date), axis=0)
#
#
spec = spectral.spectrum1d({'E': spec, 'f': freq, 'loc': dates})
return (spec)
def getFakeData(self, spotterID, num):
#
import time
import spectral
data = dict()
datab = dict()
datab['significantWaveHeight'] = 0.
datab['peakPeriod'] = 0.
datab['meanPeriod'] = 0.
datab['direction'] = 0.
datab['peakDirection'] = 0.
datab['peakDirectionalSpread'] = 0.
datab['directionalSpread'] = 0.
data['bulk'] = datab
#
if not (self._xy) == None:
#
data['lat'] = self._xy[num, 1]
data['lon'] = self._xy[num, 0]
#
else:
#
data['lat'] = 0.
data['lon'] = 0.
#
#endif
#
data['spotterId'] = spotterID
data['name'] = 'fake'
timestamp = time.strftime("%Y-%m-%dT%H:%M:00.000Z", time.gmtime())
data['timestampStart'] = timestamp
data['timestampEnd'] = timestamp
spotter = spotres(data)
spotter.fullMessage = False
#
if not (self.fakeData == None):
#
spotter.fullMessage = True
spotter.spec = spectral.spectrum1d({
'f': self.fakeData.ff(),
'E': self.fakeData.E[num, :],
'a1': self.fakeData.a1[num, :],
'b1': self.fakeData.b1[num, :],
'a2': self.fakeData.a2[num, :],
'b2': self.fakeData.b2[num, :]
})
#
#endif
#
return (spotter)
def getSpec(self):
#
# get all the spectra from the spotters as one
# convinient spectral object. Note that for
# spotters without full message nans are returned
#
import numpy as np
import spectral
ind = self.fullSpecIndices[0]
nf = self.spotters[ind].spec.nf
f = self.spotters[ind].spec.f
nloc = len(self.spotters)
#
E = np.zeros((self.numSpot, nf)) + np.nan
a1 = np.zeros((self.numSpot, nf)) + np.nan
b1 = np.zeros((self.numSpot, nf)) + np.nan
a2 = np.zeros((self.numSpot, nf)) + np.nan
b2 = np.zeros((self.numSpot, nf)) + np.nan
j = 0
#
for index, spotter in enumerate(self.spotters):
#
if index in self.fullSpecIndices:
#
E[index, :] = spotter.spec.E
a1[index, :] = spotter.spec.a1
b1[index, :] = spotter.spec.b1
a2[index, :] = spotter.spec.a2
b2[index, :] = spotter.spec.b2
#
#endif
#
#endfor
#
spec = spectral.spectrum1d({
'E': E,
'f': f,
'a1': a1,
'b1': b1,
'a2': a2,
'b2': b2
})
return (spec)
def getData(self,
spotterID='SPOT-ST0009',
endpoint='https://wavefleet.herokuapp.com/api/latestData',
num=0):
#
import urllib.request
import json
import ndbc
import numpy as np
import h5py
import spectral
#If this is a fake, or virtual spotter, do update from fake
if self.fake:
spot = self.getFakeData(spotterID, num)
return (spot)
if spotterID[0:4].lower() == 'ndbc':
#
#
ndbcID = spotterID[4:]
spec, lat, lon, epochtime = ndbc.getLatestSpec(stationID=ndbcID)
data = {
'spec': spec,
'lat': lat,
'lon': lon,
'epochtime': epochtime,
'name': spotterID,
'spotterId': spotterID
}
spot = spotres(data)
#
elif self.matlabSpotter:
#
# This is a matlab spotter, read from dir
#
fileName = self.matlabSpotterDir + '/' + spotterID + '.mat'
dataFile = h5py.File(fileName, 'r')
time = np.array(dataFile.get('time'))[0, :]
#Convert from matlab to Unix epoch, 719529 is the number of days
#at 1/1/1970 according to matlab datenum( 1970 , 1 , 1)
time = (time - 719529) * 3600. * 24
#Find minimum index in arrays
minimumIndex = np.argmin(np.abs(self.targetTime - time))
epochtime = time[minimumIndex]
#
E = np.array(dataFile.get('E'))[:, minimumIndex]
f = np.array(dataFile.get('f'))
a1 = np.array(dataFile.get('a1'))[:, minimumIndex]
b1 = np.array(dataFile.get('b1'))[:, minimumIndex]
a2 = np.array(dataFile.get('a2'))[:, minimumIndex]
b2 = np.array(dataFile.get('b2'))[:, minimumIndex]
lat = dataFile.get('latitude')[0][0]
lon = dataFile.get('longitude')[0][0]
spec = spectral.spectrum1d({
'f': f,
'E': E,
'a1': a1,
'b1': b1,
'a2': a2,
'b2': b2
})
data = {
'spec': spec,
'lat': lat,
'lon': lon,
'epochtime': epochtime,
'name': spotterID,
'spotterId': spotterID
}
spot = spotres(data)
#
else:
#
req = urllib.request.Request(endpoint + '?spotterId=' + spotterID)
if self.token is not None:
#
req.add_header('token', self.token)
#
#endif
#
#...decode json...
response = urllib.request.urlopen(req)
data = json.loads(response.read().decode('utf-8'))
#
#... and return a spot datatype
print(data)
spot = spotres(data['data'])
#
#endif
return (spot)
def __init__(self, data):
#
import time
import calendar
import spectral
import numpy as np
if not 'spec' in data:
#
self.Hsig = data['waves'][0]['significantWaveHeight']
self.Tp = data['bulk']['peakPeriod']
self.Tm01 = data['bulk']['meanPeriod']
self.peakDir = data['bulk']['peakDirection']
self.peakSprd = data['bulk']['peakDirectionalSpread']
self.Dir = data['bulk']['direction']
self.dirSprd = data['bulk']['directionalSpread']
self.lat = data['lat']
self.lon = data['lon']
self.id = data['spotterId']
self.name = data['name']
self.updatetime = [data['timestampStart'], data['timestampEnd']]
self.epochtimes = [
calendar.timegm(time.strptime(x, '%Y-%m-%dT%H:%M:%S.%fZ'))
for x in self.updatetime
]
self.epochtime = int(
(self.epochtimes[0] + self.epochtimes[1]) // 2)
self.fullMessage = False
self.spec = None
if 'frequencyData' in data:
#
data = data['frequencyData']
#
if 'f' in data:
#
self.fullMessage = True
# adhoc conversion to densities based on full messsage format
# hardcoded now - should disappear once full message returns
# densities
f = data['f']
df = np.ones(39)
df[0:33] = 0.009765625
df[33:38] = 3 * 0.009765625
df[38] = 0.751953125 - 0.517578125
E = data['Szz'] / df / 1000000
var = {
'f': data['f'],
'E': E,
'a1': data['a1'],
'a2': data['a2'],
'b1': data['b1'],
'b2': data['b2']
}
self.spec = spectral.spectrum1d(var)
#
#end if
#
#end if
#
else:
#
self.Hsig = data['spec'].Hm0()
self.Tp = data['spec'].Tp()
self.Tm01 = data['spec'].Tm0n()
self.peakDir = 270. - data['spec'].peakDir() * 180. / np.pi
if self.peakDir < 0.:
self.peakDir = self.peakDir + 360.
if self.peakDir > 360.:
self.peakDir = self.peakDir - 360.
self.peakSprd = data['spec'].peakSprd() * 180. / np.pi
self.Dir = 270. - data['spec'].bulkDir() * 180. / np.pi
#
if self.Dir < 0.:
#
self.Dir = self.Dir + 360.
#
#
if self.Dir > 360.:
#
self.Dir = self.Dir - 360.
#
#
self.dirSprd = data['spec'].bulkSprd() * 180. / np.pi
self.lat = data['lat']
self.lon = data['lon']
self.id = data['spotterId']
self.name = data['name']
self.updatetime = ['0', '0']
self.epochtimes = [data['epochtime'], data['epochtime']]
self.epochtime = data['epochtime']
if not np.any(np.isnan(data['spec'].E)):
self.fullMessage = True
else:
self.fullMessage = False
self.spec = data['spec']
def getSpec(stationID='46011',
workingdirectory=None,
epochtime=None,
historical=False):
import code
import numpy as np
import urllib.request
import pandas as pd
import calendar
import time
import os
from datetime import datetime
from pytz import timezone
import spectral
global baseurl
files = ['.data_spec', '.swdir', '.swdir2', '.swr1', '.swr2']
kind = [0, 1, 1, 1, 1]
data = []
for index, file in enumerate(files):
#
url = baseurl + stationID + file
[tmp, freq, dates] = getSpectralData(url,
workingdirectory=workingdirectory,
kind=kind[index])
data.append(tmp)
#
#
# Convert to lhs moments - see http://www.ndbc.noaa.gov/measdes.shtml
#
angle1 = (270 - data[1]) * np.pi / 180.
angle2 = (540 - 2 * data[2]) * np.pi / 180.
msk = data[3] == 999.0
msk = data[4] == 999.0
data[3][msk] = 0.
data[4][msk] = 0.
#D(f,A) = (1/PI)*(0.5+R1*COS(A-ALPHA1)+R2*COS(2*(A-ALPHA2))).
R1 = data[3]
R2 = data[4]
E = data[0]
a1 = R1 * np.cos(angle1)
b1 = R1 * np.sin(angle1)
a2 = R2 * np.cos(angle2)
b2 = R2 * np.sin(angle2)
spec = spectral.spectrum1d({
'E': E,
'f': freq,
'loc': dates,
'a1': a1,
'b1': b1,
'a2': a2,
'b2': b2
})
if epochtime is not None:
#
if epochtime < 0:
#
epochtime = dates[0]
#
#
spec = spec.interpLoc(epochtime)
else:
#
epochtime = dates
#
#
lat, lon = getStationInfo(stationID, workingDirectory=workingdirectory)
return (spec, lat, lon, epochtime)