#!/usr/bin/env python
# coding: utf-8

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import utide

print(utide.__version__)


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import numpy as np


def fake_tide(t, M2amp, M2phase):
    """
    Generate a minimally realistic-looking fake semidiurnal tide.
    
    t is time in hours
    phases are in radians
    
    Modified from: http://currents.soest.hawaii.edu/ocn760_4/_static/plotting.html
    """
    return M2amp * np.sin(2 * np.pi * t / 12.42 - M2phase)


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from pandas import date_range

N = 500

t = date_range(start="2016-03-29", periods=N, freq="H")

# Signal + some noise.
u = fake_tide(np.arange(N), M2amp=2, M2phase=0) + np.random.randn(N)
v = fake_tide(np.arange(N), M2amp=1, M2phase=np.pi) + np.random.randn(N)


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from utide import solve


coef = solve(
    t, u, v,
    lat=-42.5,
    nodal=False,
    trend=False,
    method='ols',
    conf_int='linear',
    Rayleigh_min=0.95,
)


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from utide import reconstruct

tide = reconstruct(t, coef)


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tide.keys()


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get_ipython().run_line_magic('matplotlib', 'inline')
import matplotlib.pyplot as plt

fig, (ax0, ax1, ax2) = plt.subplots(nrows=3, sharey=True, sharex=True, figsize=(17, 5))

ax0.plot(t, u, label='Observations', color='C0')
ax0.legend(numpoints=1, loc='lower right')

ax1.plot(t, tide['u'], alpha=0.5, label='Prediction', color='C1')
ax1.legend(numpoints=1, loc='lower right')

ax2.plot(t, u-tide['u'], alpha=0.5, label='Original time series minus Prediction', color='C2')
ax2.legend(numpoints=1, loc='lower right');


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fig, (ax0, ax1, ax2) = plt.subplots(nrows=3, sharey=True, sharex=True, figsize=(17, 5))

ax0.plot(t, v, label='Observations', color='C0')
ax0.legend(numpoints=1, loc='lower right')

ax1.plot(t, tide['v'], alpha=0.5, label='Prediction', color='C1')
ax1.legend(numpoints=1, loc='lower right')

ax2.plot(t, v-tide['v'], alpha=0.5, label='Residuals', color='C2')
ax2.legend(numpoints=1, loc='lower right');