<jupyter_start><jupyter_text>Single constituenty = A cos (at + α)for all constituents?The formula for that calculation is: h = Ho + Sum{ƒH cos[at + (Vo+u) - K]}The terms of the equation are defined as:h = height of tide at any time t.Ho = mean height of water level above datum used for prediction.H = mean amplitude of any constituent A.ƒ = factor for reducing mean amplitude H to year of prediction.a = speed of constituent A.t = time reckoned from some initial epoch such as beginning of year of predictions. (Vo+u) = value of equilibrium argument of constituent A when t = 0.K = epoch of constituent A.<jupyter_code>import numpy as np
import os
import matplotlib.pyplot as plt
import pandas as pd
odf = pd.read_csv('/Users/catherinej/Downloads/CO-OPS_8512354_wl (2).csv', parse_dates=[['Date', 'Time (GMT)']])
idf = pd.read_csv('/Users/catherinej/Downloads/CO-OPS_8512451_wl (1).csv',parse_dates=[['Date', 'Time (GMT)']])
odf.head()
plt.figure(figsize=(20,16))
ax = odf.plot(x = 'Date_Time (GMT)', y='Verified (ft)')
idf.plot(x='Date_Time (GMT)', y='Verified (ft)', ax=ax)
ax.set_xlim(pd.Timestamp('2013-09-23 07:15:00'), pd.Timestamp('2013-09-23 9:30:00'))

ax.xaxis.grid(True, which='minor')
tc = pd.read_csv('/Users/catherinej/Downloads/tide_constituents.csv')
#h = H0 + sum(fHcos(at + V0+u) - K)
tc.head()
tc.Speed[0]
for i in tc.Con:
    y = A * np.cos(tc.Speed[i]*tc. + alpha)
Single constituent
y = A cos (at + α)

for all constituents?

The formula for that calculation is: h = Ho + Sum{ƒH cos[at + (Vo+u) - K]}

The terms of the equation are defined as:

h = height of tide at any time t.

Ho = mean height of water level above datum used for prediction.

H = mean amplitude of any constituent A.

ƒ = factor for reducing mean amplitude H to year of prediction.

a = speed of constituent A.

t = time reckoned from some initial epoch such as beginning of year of predictions. (Vo+u) = value of equilibrium argument of constituent A when t = 0.

K = epoch of constituent A.<jupyter_output><empty_output>
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