First commit
commit
e6a1bdda32
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import datetime
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import time
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import math
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from pylab import *
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# Brett Miller 9th October 2015.
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# This program reads Harmonics for Fort Denison as provided by BOM on the 9th October 2015
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#
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# NOT FOR DISTRIBUTION
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# the predictions from this code have been cross checked against some daily predictions but
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# not against all.
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# USE AT YOUR OWN CAUTION. NO GAURENTEE MADE THAT THESE PREDICTIONS ARE CORRECT.
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#
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# The x-tide method for calculating tides is:-
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# z(t,y,site)= MWL(site) + sum[c=1,N](nodefactor(c,y).amp(c,site).cos( speed(c).t + eqarg(c,y) - kappa(c,site) ))
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# where
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# t is the time since the beginning of the year
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# y is the year
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# site is the site of interest
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# N is the number of consituents being included
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# nodefactor is an amplitude adjustment for each constituent for each year
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# eqarg is a phase adjustment for each site for each year
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# amp is the amplitude of each constituent for the site
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# kappa is the phase adjustment for each constituent for the site
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#
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# the harmonics included below in the python code were provided directly to WRL from BOM.
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harm={}
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speed=0
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amp=1
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lag=2
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def readlinenocomm(F):
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l=F.readline()
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while l[0]=='#':
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l=F.readline()
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return l
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#
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H=open("HARMONIC","r")
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l=readlinenocomm(H)
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numconstits=int(l)
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print "Number of Constituents = ",numconstits
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# Read in the constituent speeds
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constitspeed={}
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i=0
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while i<numconstits:
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l=readlinenocomm(H)
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ll=l.split()
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constitspeed[ll[0]]=float(ll[1])
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i=i+1
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l=readlinenocomm(H)
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sy=int(l)
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l=readlinenocomm(H)
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numyears=int(l)
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# Read in the equalibrium arguements
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equalibrium_arg={}
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i=0
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while i<numconstits:
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l=readlinenocomm(H)
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ll=l.split()
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constit=ll[0]
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v=[]
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j=0
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while j<=numyears/10:
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l=readlinenocomm(H)
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ll=l.split()
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for lll in ll:
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v.append(float(lll))
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j=j+1
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equalibrium_arg[constit]=v
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i=i+1
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l=readlinenocomm(H)
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if l[0:5]<>'*END*':
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print "Error, expected end after eq args. Got: ",l
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# Read in the node factors
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l=readlinenocomm(H)
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numyears=int(l)
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node_factor={}
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i=0
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while i<numconstits:
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l=readlinenocomm(H)
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ll=l.split()
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constit=ll[0]
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v=[]
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j=0
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while j<=numyears/10:
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l=readlinenocomm(H)
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ll=l.split()
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for lll in ll:
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v.append(float(lll))
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j=j+1
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node_factor[constit]=v
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i=i+1
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l=readlinenocomm(H)
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if l[0:5]<>'*END*':
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print "Error, expected end after node factors. Got: ",l
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harm['sa']=[0.0410686,0.04,44.3373]
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harm['ssa']=[0.0821373,0.0233,140.8642]
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harm['Mm']=[0.5443747,0.0022,163.3925]
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harm['MSF']=[1.0158958,0.0019,73.4003]
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harm['MF']=[1.0980331,0.0025,203.8471]
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harm['2Q1']=[12.8542862,0.0036,9.8664]
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harm['SIGMA1']=[12.9271398,0.0043,16.6066]
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harm['Q1']=[13.3986609,0.023,52.3723]
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harm['RHO1']=[13.4715145,0.0043,55.9113]
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harm['O1']=[13.9430356,0.0963,79.6431]
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harm['MP1']=[14.0251729,0.001,45.9175]
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harm['M1']=[14.4920521,0.0044,99.5325]
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harm['CHI1']=[14.5695476,0.0013,102.4847]
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harm['PI1']=[14.9178647,0.0028,125.9361]
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harm['P1']=[14.9589314,0.0439,115.4037]
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harm['S1']=[15,0.0033,129.8967]
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harm['K1']=[15.0410686,0.148,119.6599]
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harm['PSI1']=[15.0821353,0.002,11.0025]
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harm['PHI1']=[15.1232059,0.0015,103.8567]
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harm['THETA1']=[15.5125897,0.0017,137.3796]
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harm['J1']=[15.5854433,0.0096,142.7051]
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harm['SO1']=[16.0569644,0.0017,173.2765]
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harm['OO1']=[16.1391017,0.0062,180.0375]
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harm['OQ2']=[27.3416964,0.0006,75.4143]
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harm['MNS2']=[27.4238337,0.0061,193.1893]
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harm['2N2']=[27.8953548,0.0205,199.6233]
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harm['MEU2']=[27.9682084,0.021,212.8684]
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harm['N2']=[28.4397295,0.1127,223.5144]
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harm['NEU2']=[28.5125831,0.0206,223.5377]
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harm['OP2']=[28.9019669,0.0024,128.4082]
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harm['M2']=[28.9841042,0.5022,237.061]
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harm['MKS2']=[29.0662415,0.0014,313.3572]
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harm['LAMDA2']=[29.4556253,0.0058,224.4572]
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harm['L2']=[29.5284789,0.0135,243.1576]
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harm['T2']=[29.9589333,0.0073,281.2802]
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harm['S2']=[30,0.1247,260.7625]
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harm['R2']=[30.0410667,0.0022,206.1633]
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harm['K2']=[30.0821373,0.0373,250.3219]
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harm['MSN2']=[30.5443747,0.0016,124.387]
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harm['KJ2']=[30.626512,0.0023,62.9849]
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harm['2SM2']=[31.0158958,0.0019,145.4123]
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harm['MO3']=[42.9271398,0.0004,148.654]
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harm['M3']=[43.4761563,0.0023,327.537]
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harm['SO3']=[43.9430356,0.0002,307.6915]
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harm['MK3']=[44.0251729,0.0005,248.2678]
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harm['SK3']=[45.0410686,0.0016,113.2852]
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harm['MN4']=[57.4238337,0.001,90.6269]
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harm['M4']=[57.9682084,0.0031,114.2894]
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harm['SN4']=[58.4397295,0.0003,103.5135]
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harm['MS4']=[58.9841042,0.0014,183.7788]
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harm['MK4']=[59.0662415,0.0004,196.3685]
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harm['S4']=[60,0.0006,299.9646]
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harm['SK4']=[60.0821373,0.0002,45.1703]
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harm['2MN6']=[86.407938,0.0009,6.8059]
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harm['M6']=[86.9523127,0.002,52.2368]
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harm['MSN6']=[87.4238337,0.0007,64.4301]
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harm['2MS6']=[87.9682084,0.0025,114.6867]
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harm['2MK6']=[88.0503457,0.0007,131.372]
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harm['2SM6']=[88.9841042,0.0003,157.8974]
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harm['MSK6']=[89.0662415,0.0003,204.7339]
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harm['2MN2S2']=[26.4079379,0.0003,1.3443]
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harm['3M(SK)2']=[26.8701753,0.0005,3.6145]
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harm['3M2S2']=[26.9523127,0.0008,78.7665]
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harm['MNK2S2']=[27.505971,0.0001,225.556]
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harm['SNK2']=[28.3575922,0.0003,218.9001]
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harm['2SK2']=[29.9178627,0.0011,321.0943]
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harm['MQ3']=[42.3827651,0.0004,43.8537]
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harm['2MP3']=[43.009277,0.0001,134.0684]
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harm['2MQ3']=[44.5695475,0.0001,329.7593]
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harm['3MK4']=[56.8701754,0,39.731]
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harm['3MS4']=[56.9523127,0.0001,97.9154]
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harm['2MSK4']=[57.8860711,0.0002,283.9222]
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harm['3MK5']=[71.9112441,0.0002,182.3575]
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harm['M5']=[72.4602605,0,24.2117]
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harm['3MO5']=[73.0092771,0.0005,264.7303]
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harm['2(MN)S6']=[84.8476674,0,129.7631]
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harm['3MNS6']=[85.3920422,0.0001,260.1927]
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harm['4MK6']=[85.8542795,0.0001,332.2482]
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harm['4MS6']=[85.9364168,0.0001,249.9087]
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harm['2MSNK6']=[86.3258006,0,280.3885]
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harm['2MNU6']=[86.4807915,0.0003,28.4884]
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harm['3MSK6']=[86.8701754,0.0001,222.0912]
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harm['4MN6']=[87.4966873,0.0003,292.3403]
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harm['3MSN6']=[88.5125832,0.0006,338.3166]
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harm['MKL6']=[88.5947204,0.0001,176.1921]
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harm['2MN8']=[114.8476674,0.0001,219.9735]
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harm['3MN8']=[115.3920422,0.0002,245.3801]
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harm['M8']=[115.9364168,0.0002,284.0175]
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harm['2MSN8']=[116.4079379,0.0002,203.8838]
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harm['3MS8']=[116.9523127,0.0001,280.466]
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harm['3MK8']=[117.03445,0.0001,286.3325]
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harm['MSNK8']=[117.505971,0,219.0404]
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harm['2MS8']=[117.9682084,0.0002,188.3974]
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harm['2MSK8']=[118.0503457,0.0001,195.8549]
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harm['4MS10']=[145.9364168,0.0002,293.7057]
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harm['3M2S10']=[146.9523127,0.0002,307.5005]
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harm['4MSN12']=[174.3761463,0.0001,110.9933]
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harm['5MS12']=[174.920521,0,180.6601]
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harm['4M2S12']=[175.9364168,0,108.791]
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harm['SP3']=[44.9589314,0.0019,112.6443]
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harm['S3']=[45,0.0012,23.4633]
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harm['MA2']=[28.9430375,0.0039,117.2716]
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harm['Ma2']=[29.0251709,0.0027,150.6304]
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harm['MSV2']=[30.4715211,0,98.718]
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harm['SKM2']=[31.0980331,0.0008,156.4092]
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harm['2MNS4']=[56.407938,0.0001,26.7109]
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harm['MV4']=[57.4966873,0.0003,94.1175]
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harm['3MN4']=[58.5125832,0.0003,339.4208]
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harm['2MSN4']=[59.5284789,0.0001,264.4342]
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harm['NA2']=[28.3986628,0.0004,16.9727]
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harm['MSO5']=[72.9271398,0.0001,247.7639]
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harm['MSK5']=[74.0251729,0.0002,189.3859]
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MSL=0.9952
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# Now do the maths
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start_time=datetime.datetime(2016,07,29,0,0,0)
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end_time=datetime.datetime(2016,07,30,0,0,0)
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time_step=datetime.timedelta(minutes=15)
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x=[]
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y=[]
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F=open("tide.out","w")
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t=start_time
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while (t<end_time):
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offset = t - datetime.datetime(t.year,1,1,0,0,0)
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yr=t.year-sy
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t1=(offset.days) * 24.0 + offset.seconds / 3600.0
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z=MSL
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for constit in harm.keys():
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if constit in node_factor:
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nf=node_factor[constit][yr]
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ea=equalibrium_arg[constit][yr]
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else:
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nf=1.0
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ea=0.0
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z=z+nf*harm[constit][amp]*math.cos((harm[constit][speed]*t1 + ea - harm[constit][lag]) * (2*3.1415927 / 360.0))
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# print t,z
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F.write("%s,%s\n" % (t,z))
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x.append(t)
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y.append(z)
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t=t+time_step
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F.close
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plt.figure()
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plot(x,y,c='g',label='Sample')
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plt.gcf().autofmt_xdate()
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show()
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@ -0,0 +1,132 @@
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Noofjobs 1 &fd1985-2012
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(I4,7X,24F5.2)
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(1X///I3,I4,3X,24F5.2)
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(2I5,12(F6.4,F5.2))
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1.0 1
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Port A0 .995year##vday%%%fstd%%%endd***doc112oth 0step 10 .9622 ?
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AUSTRALIA, EAST COAST - SYDNEY (FORT DENISON) 4335115114 -1000 60370
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1 0.0410686 0.0400 44.3373 sa
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2 0.0821373 0.0233 140.8642 ssa
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3 0.5443747 0.0022 163.3925 Mm
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4 1.0158958 0.0019 73.4003 Msf
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5 1.0980331 0.0025 203.8471 Mf
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6 12.8542862 0.0036 9.8664 2Q1
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7 12.9271398 0.0043 16.6066 SIGMA1
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8 13.3986609 0.0230 52.3723 Q1
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9 13.4715145 0.0043 55.9113 RHO1
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10 13.9430356 0.0963 79.6431 O1
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11 14.0251729 0.0010 45.9175 MP1
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12 14.4920521 0.0044 99.5325 M1
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13 14.5695476 0.0013 102.4847 CHI1
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14 14.9178647 0.0028 125.9361 PI1
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15 14.9589314 0.0439 115.4037 P1
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16 15.0000000 0.0033 129.8967 S1
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17 15.0410686 0.1480 119.6599 K1
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18 15.0821353 0.0020 11.0025 PSI1
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19 15.1232059 0.0015 103.8567 PHI1
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20 15.5125897 0.0017 137.3796 THETA1
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21 15.5854433 0.0096 142.7051 J1
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22 16.0569644 0.0017 173.2765 SO1
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23 16.1391017 0.0062 180.0375 OO1
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24 27.3416964 0.0006 75.4143 OQ2
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25 27.4238337 0.0061 193.1893 MNS2
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26 27.8953548 0.0205 199.6233 2N2
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27 27.9682084 0.0210 212.8684 MEU2
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28 28.4397295 0.1127 223.5144 N2
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29 28.5125831 0.0206 223.5377 NEU2
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30 28.9019669 0.0024 128.4082 OP2
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31 28.9841042 0.5022 237.0610 M2
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32 29.0662415 0.0014 313.3572 MKS2
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33 29.4556253 0.0058 224.4572 LAMDA2
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34 29.5284789 0.0135 243.1576 L2
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35 29.9589333 0.0073 281.2802 T2
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36 30.0000000 0.1247 260.7625 S2
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37 30.0410667 0.0022 206.1633 R2
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38 30.0821373 0.0373 250.3219 K2
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39 30.5443747 0.0016 124.3870 MSN2
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40 30.6265120 0.0023 62.9849 KJ2
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41 31.0158958 0.0019 145.4123 2SM2
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42 42.9271398 0.0004 148.6540 MO3
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43 43.4761563 0.0023 327.5370 M3
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44 43.9430356 0.0002 307.6915 SO3
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45 44.0251729 0.0005 248.2678 MK3
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46 45.0410686 0.0016 113.2852 SK3
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47 57.4238337 0.0010 90.6269 MN4
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48 57.9682084 0.0031 114.2894 M4
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49 58.4397295 0.0003 103.5135 SN4
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50 58.9841042 0.0014 183.7788 MS4
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51 59.0662415 0.0004 196.3685 MK4
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52 60.0000000 0.0006 299.9646 S4
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53 60.0821373 0.0002 45.1703 SK4
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54 86.4079380 0.0009 6.8059 2MN6
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55 86.9523127 0.0020 52.2368 M6
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56 87.4238337 0.0007 64.4301 MSN6
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57 87.9682084 0.0025 114.6867 2MS6
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58 88.0503457 0.0007 131.3720 2MK6
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59 88.9841042 0.0003 157.8974 2SM6
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60 89.0662415 0.0003 204.7339 MSK6
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61 26.4079379 0.0003 1.3443 2MN2S2
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62 26.8701753 0.0005 3.6145 3M(SK)2
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63 26.9523127 0.0008 78.7665 3M2S2
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64 27.5059710 0.0001 225.5560 MNK2S2
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65 28.3575922 0.0003 218.9001 SNK2
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66 29.9178627 0.0011 321.0943 2SK2
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68 42.3827651 0.0004 43.8537 MQ3
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69 43.0092770 0.0001 134.0684 2MP3
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70 44.5695475 0.0001 329.7593 2MQ3
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71 56.8701754 0.0000 39.7310 3MK4
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72 56.9523127 0.0001 97.9154 3MS4
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73 57.8860711 0.0002 283.9222 2MSK4
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74 71.9112441 0.0002 182.3575 3MK5
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75 72.4602605 0.0000 24.2117 M5
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76 73.0092771 0.0005 264.7303 3MO5
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77 84.8476674 0.0000 129.7631 2(MN)S6
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78 85.3920422 0.0001 260.1927 3MNS6
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79 85.8542795 0.0001 332.2482 4MK6
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80 85.9364168 0.0001 249.9087 4MS6
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81 86.3258006 0.0000 280.3885 2MSNK6
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82 86.4807915 0.0003 28.4884 2MNU6
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83 86.8701754 0.0001 222.0912 3MSK6
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84 87.4966873 0.0003 292.3403 4MN6
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85 88.5125832 0.0006 338.3166 3MSN6
|
||||
86 88.5947204 0.0001 176.1921 MKL6
|
||||
87 114.8476674 0.0001 219.9735 2MN8
|
||||
88 115.3920422 0.0002 245.3801 3MN8
|
||||
89 115.9364168 0.0002 284.0175 M8
|
||||
90 116.4079379 0.0002 203.8838 2MSN8
|
||||
91 116.9523127 0.0001 280.4660 3MS8
|
||||
92 117.0344500 0.0001 286.3325 3MK8
|
||||
93 117.5059710 0.0000 219.0404 MSNK8
|
||||
94 117.9682084 0.0002 188.3974 2MS8
|
||||
95 118.0503457 0.0001 195.8549 2MSK8
|
||||
96 145.9364168 0.0002 293.7057 4MS10
|
||||
97 146.9523127 0.0002 307.5005 3M2S10
|
||||
98 174.3761463 0.0001 110.9933 4MSN12
|
||||
99 174.9205210 0.0000 180.6601 5MS12
|
||||
100 175.9364168 0.0000 108.7910 4M2S12
|
||||
101 44.9589314 0.0019 112.6443 SP3
|
||||
102 45.0000000 0.0012 23.4633 S3
|
||||
103 28.9430375 0.0039 117.2716 MA2
|
||||
104 29.0251709 0.0027 150.6304 Ma2
|
||||
105 30.4715211 0.0000 98.7180 MSV2
|
||||
106 31.0980331 0.0008 156.4092 SKM2
|
||||
107 56.4079380 0.0001 26.7109 2MNS4
|
||||
108 57.4966873 0.0003 94.1175 MV4
|
||||
109 58.5125832 0.0003 339.4208 3MN4
|
||||
110 59.5284789 0.0001 264.4342 2MSN4
|
||||
111 28.3986628 0.0004 16.9727 NA2
|
||||
113 72.9271398 0.0001 247.7639 MSO5
|
||||
114 74.0251729 0.0002 189.3859 MSK5
|
||||
116 0.0000000 0.9952 0.0000 A0
|
||||
FORT DENISON - 1985 TO 2012 ANALYSIS Time zone -1000
|
||||
Hourly sea levels in metres from 1-Jan-1985 to 31-Dec-2012
|
||||
There are 46 gaps of 24(9),11,8,22(3),95,1,1,23,49,4,7,48,27,38,13,21,48,
|
||||
98,125,75,25,27,23,67,96,98,96,20,28,121,7,17,26,1047,25 and 51 hours
|
||||
Analysis of 24-Jun-13 for 112 constituents on 10113 days of data
|
||||
Sa and Ssa from a long period analysis (96.7 years) of Fort Denison (1914-2012)
|
||||
(1985-2012 analysis gave Sa=0.0384/59.5695 and Ssa=0.0191/143.8045)
|
||||
Sample Correlation Coefficient is 0.9767
|
||||
Standard Devn of the Residuals is 0.0877
|
||||
Zero Frequency Level is 0.9622m above TGZ, which is 6.647m below PM 101
|
||||
For 2015 predictions use Zero Frequency Level plus 16.5 years x 2.0mm/year trend
|
||||
Mean sea level is 0.995m above tide gauge zero for 2015 predictions
|
||||
Loading…
Reference in New Issue