Tidetable tutorial

Tutorial for processing tabulated tide gauge data.

Tidal highs and lows can be scraped from a website such as:
https://www.ntslf.org/tides/tidepred?port=Liverpool

and format them into a csv file:

LIVERPOOL (GLADSTONE DOCK) TZ: UT(GMT)/BST Units: METRES Datum: Chart Datum
01/10/2020 06:29 1.65
01/10/2020 11:54 9.01
01/10/2020 18:36 1.87

The data can be used in the following demonstration.

import coast
import numpy as np

/usr/share/miniconda/envs/coast/lib/python3.10/site-packages/pydap/lib.py:5: DeprecationWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html
/usr/share/miniconda/envs/coast/lib/python3.10/site-packages/pkg_resources/__init__.py:2871: DeprecationWarning: Deprecated call to `pkg_resources.declare_namespace('pydap')`.
Implementing implicit namespace packages (as specified in PEP 420) is preferred to `pkg_resources.declare_namespace`. See https://setuptools.pypa.io/en/latest/references/keywords.html#keyword-namespace-packages
/usr/share/miniconda/envs/coast/lib/python3.10/site-packages/pkg_resources/__init__.py:2871: DeprecationWarning: Deprecated call to `pkg_resources.declare_namespace('pydap.responses')`.
Implementing implicit namespace packages (as specified in PEP 420) is preferred to `pkg_resources.declare_namespace`. See https://setuptools.pypa.io/en/latest/references/keywords.html#keyword-namespace-packages
/usr/share/miniconda/envs/coast/lib/python3.10/site-packages/pkg_resources/__init__.py:2350: DeprecationWarning: Deprecated call to `pkg_resources.declare_namespace('pydap')`.
Implementing implicit namespace packages (as specified in PEP 420) is preferred to `pkg_resources.declare_namespace`. See https://setuptools.pypa.io/en/latest/references/keywords.html#keyword-namespace-packages
/usr/share/miniconda/envs/coast/lib/python3.10/site-packages/pkg_resources/__init__.py:2871: DeprecationWarning: Deprecated call to `pkg_resources.declare_namespace('pydap.handlers')`.
Implementing implicit namespace packages (as specified in PEP 420) is preferred to `pkg_resources.declare_namespace`. See https://setuptools.pypa.io/en/latest/references/keywords.html#keyword-namespace-packages
/usr/share/miniconda/envs/coast/lib/python3.10/site-packages/pkg_resources/__init__.py:2350: DeprecationWarning: Deprecated call to `pkg_resources.declare_namespace('pydap')`.
Implementing implicit namespace packages (as specified in PEP 420) is preferred to `pkg_resources.declare_namespace`. See https://setuptools.pypa.io/en/latest/references/keywords.html#keyword-namespace-packages
/usr/share/miniconda/envs/coast/lib/python3.10/site-packages/pkg_resources/__init__.py:2871: DeprecationWarning: Deprecated call to `pkg_resources.declare_namespace('pydap.tests')`.
Implementing implicit namespace packages (as specified in PEP 420) is preferred to `pkg_resources.declare_namespace`. See https://setuptools.pypa.io/en/latest/references/keywords.html#keyword-namespace-packages
/usr/share/miniconda/envs/coast/lib/python3.10/site-packages/pkg_resources/__init__.py:2350: DeprecationWarning: Deprecated call to `pkg_resources.declare_namespace('pydap')`.
Implementing implicit namespace packages (as specified in PEP 420) is preferred to `pkg_resources.declare_namespace`. See https://setuptools.pypa.io/en/latest/references/keywords.html#keyword-namespace-packages
/usr/share/miniconda/envs/coast/lib/python3.10/site-packages/pkg_resources/__init__.py:2871: DeprecationWarning: Deprecated call to `pkg_resources.declare_namespace('sphinxcontrib')`.
Implementing implicit namespace packages (as specified in PEP 420) is preferred to `pkg_resources.declare_namespace`. See https://setuptools.pypa.io/en/latest/references/keywords.html#keyword-namespace-packages

Load and plot High and Low Water data.

print("load and plot HLW data")
filnam = "./example_files/Gladstone_2020-10_HLW.txt"

load and plot HLW data

Set the start and end dates.

date_start = np.datetime64("2020-10-12 23:59")
date_end = np.datetime64("2020-10-14 00:01")

Initiate a TideGauge object, if a filename is passed it assumes it is a GESLA type object.

tg = coast.Tidegauge()

Tidegauge object at 0x556642be7980 initialised

Specify the data read as a High Low Water dataset.

tg.read_hlw(filnam, date_start, date_end)

Show dataset. If timezone is specified then it is presented as requested, otherwise uses UTC.

print("Try the TideGauge.show() method:")
tg.show(timezone="Europe/London")

Try the TideGauge.show() method:

Do a basic plot of these points.

tg.dataset.plot.scatter(x="time", y="ssh")

<matplotlib.collections.PathCollection at 0x7f0b9ef31b10>

There is a method to locate HLW events around an approximate date and time. First state the time of interest.

time_guess = np.datetime64("2020-10-13 12:48")

Then recover all the HLW events in a +/- window, of specified size (iteger hrs). The default winsize = 2 (hrs).

HLW = tg.get_tide_table_times(np.datetime64("2020-10-13 12:48"), method="window", winsize=24)

Alternatively recover the closest HLW event to the input timestamp.

HLW = tg.get_tide_table_times(np.datetime64("2020-10-13 12:48"), method="nearest_1")

Or the nearest two events to the input timestamp.

HLW = tg.get_tide_table_times(np.datetime64("2020-10-13 12:48"), method="nearest_2")

Extract the Low Tide value.

print("Try the TideGauge.get_tidetabletimes() methods:")
print("LT:", HLW[np.argmin(HLW.data)].values, "m at", HLW[np.argmin(HLW.data)].time.values)

Try the TideGauge.get_tidetabletimes() methods:
LT: 2.83 m at 2020-10-13T14:36:00.000000000

Extract the High Tide value.

print("HT:", HLW[np.argmax(HLW.data)].values, "m at", HLW[np.argmax(HLW.data)].time.values)

HT: 8.01 m at 2020-10-13T07:59:00.000000000

Or use the the nearest High Tide method to get High Tide.

HT = tg.get_tide_table_times(np.datetime64("2020-10-13 12:48"), method="nearest_HW")
print("HT:", HT.values, "m at", HT.time.values)

HT: 8.01 m at 2020-10-13T07:59:00.000000000

The get_tidetabletimes() method can take extra paremeters such as a window size, an integer number of hours to seek either side of the guess.

HLW = tg.get_tide_table_times(np.datetime64("2020-10-13 12:48"), winsize=2, method="nearest_1")


HLW = tg.get_tide_table_times(np.datetime64("2020-10-13 12:48"), winsize=1, method="nearest_1")