| Type: | Package |
| Title: | Analysis and Prediction of Tides |
| Version: | 0.0.5 |
| Maintainer: | Moritz Mueller-Navarra <muellernavarra@gmail.com> |
| Description: | Tidal analysis of evenly spaced observed time series (time step 1 to 60 min) with or without shorter gaps using the harmonic representation of inequalities. The analysis should preferably cover an observation period of at least 19 years. For shorter periods low frequency constituents are not taken into account, in accordance with the Rayleigh-Criterion. The main objective of this package is to synthesize or predict a tidal time series. |
| License: | GPL-3 |
| LazyData: | TRUE |
| Imports: | chron (≥ 2.3-56), data.table (≥ 1.14.0), fields (≥ 11.6) |
| Depends: | R (≥ 4.0.0) |
| RoxygenNote: | 7.1.1 |
| Suggests: | testthat (≥ 3.0.1) |
| Config/testthat/edition: | 3 |
| NeedsCompilation: | no |
| Packaged: | 2021-06-28 16:39:37 UTC; Moritz |
| Author: | Moritz Mueller-Navarra [aut, cre], Sylvin Mueller-Navarra [aut] ((2019) <https://doi.org/10.5194/os-15-1363-2019>), Andreas Boesch [ctb] ((2019) <https://doi.org/10.5194/os-15-1363-2019>) |
| Repository: | CRAN |
| Date/Publication: | 2021-06-28 16:50:02 UTC |
Builds the design matrix
Description
Builds the xdesign.matrix by calling Funcs. For internal use.
Usage
BuildDesign(tdiffa, numma, numme)
Arguments
tdiffa |
The difference in days as double which stems from the analysis period. |
numma |
The transit number (start). |
numme |
The transit number (end). |
Value
Returns a matrix
Builds a TideCurve model
Description
Builds a TideCurve model of class "tidecurve".
Usage
BuildTC(
dataInput = NULL,
otz = 1,
astime,
asdate,
aedate,
aetime,
km = -1,
mindt = 30,
keep_data = FALSE
)
Arguments
dataInput |
A data frame with the columns observation_date, observation_time and height. See attached data for correct formats. |
otz |
The time zone of the observations |
astime |
A string indicating the time you want the analysis to start with. Format: "hh:mm:ss" |
asdate |
A string indication the date you want the analysis to start with. Format: "yyyy/mm/dd". |
aedate |
A string indication the date you want the analysis to end with. Format: "yyyy/mm/dd". |
aetime |
A string indicating the time you want the analysis to end with. Format: "hh:mm:ss". |
km |
The number of nodes between two consecutive mean moon transits. Shall be less or equal to: round(1440 [min] / time step [min]) Example: Time step 5 min: Use km = 288 or even smaller. Leave on default (km = -1) and supply mindt, when unsure. |
mindt |
Observation time step in [min]. Default is 30. |
keep_data |
Indicating whether you want to keep the data for computing residuals later. Default is FALSE which keeps the model footprint small. |
Value
A model of class tidecurve, which is a list.
References
Examples
## Not run: BuildTC(dataInput = tideObservation, asdate = "2015/12/06",
astime = "00:00:00", aedate = "2015/12/31",
aetime = "23:30:00")
## End(Not run)
Returns predictor vector for design matrix
Description
Returns predictor vector for design matrix from 39 astronomical angular velocities.
Usage
Funcs(tdiff, xi)
Arguments
tdiff |
Length of input time series. |
xi |
Transit index |
Value
A list with the selected angular velocities, their ranks and the predictor vector (Values between -1, 1).
Computes the residuum between the observed data and the synthesis
Description
This function computes the residuum of the computed lunar and solar synthesis and the observed data
Usage
ResCurve(tcData, obsData)
Arguments
tcData |
The results from TideCurve or BuildTC + SynTC. Warning: The synthesis period must overlap with the analysis period. Must be a data.table object. Please see examples. |
obsData |
The observation data with the columns observation_date, observation_time and height. See attached data for correct formats. |
Value
A list with two data.tables with the joined data input and the computed difference between the observed data and the synthesis (res)
Examples
## Not run:
#Using TideCurve
tc <- TideCurve(dataInput = tideObservation, asdate = "2015/12/06",
astime = "00:00:00", aedate = "2015/12/31",
aetime = "23:30:00", ssdate = "2015/12/17",
sstime = "00:00:00", sedate = "2015/12/31",
setime = "23:30:00")
res_tc <- ResCurve(tc, tideObservation)
#Using BuildTC and SynTC
your_model <- BuildTC(dataInput = tideObservation, asdate = "2015/12/06",
astime = "00:00:00", aedate = "2016/12/31",
aetime = "23:30:00", keep_data = TRUE)
syn_tc <- SynTC(tmodel = your_model, ssdate = "2015/12/17", sstime = "00:00:00",
sedate = "2015/12/31", setime = "23:30:00")
syn_tc$data_matrix <- your_model$data_matrix
res_tc_n <- ResCurve(syn_tc, tideObservation)
## End(Not run)
Synthesizes a tide curve
Description
Synthesizes a tide curve; model built with BuildTC().
Usage
SynTC(tmodel = NULL, ssdate, sstime, sedate, setime, solar_syn = TRUE)
Arguments
tmodel |
The model you built with BuildTC(). Please see examples. |
ssdate |
Synthesis start date. This indicates the date you want your tide curve to start with. |
sstime |
Synthesis start time. The starting time for your tide table. |
sedate |
Synthesis end date. |
setime |
Synthesis end time. |
solar_syn |
Compute a solar synthesis? Default is TRUE. |
Value
Returns a list with two elements, which are of class data.table and data.frame.
synthesis.lunar |
The lunar synthesis data as a data.table object in UTC. |
tide.curve |
The solar tide curve as a data.table or NULL object (time zone of the observations). |
References
Examples
## Not run: SynTC(tmodel = your_model, ssdate = "2015/12/17", sstime = "00:00:00",
sedate = "2015/12/31", setime = "23:30:00")
## End(Not run)
Computes tide curves
Description
Takes a data frame as input with three columns (see example dataset) and returns a tide curve. Internally the analysis is carried out in lunar days. One mean lunar day lasts 1.0350501 mean solar days. Therefore the analysis time period should start one lunar day after the first observation and end one lunar day before the last observation.
Usage
TideCurve(
dataInput,
otz = 1,
km = -1,
mindt = 30,
asdate,
astime,
aedate,
aetime,
ssdate,
sstime,
sedate,
setime
)
Arguments
dataInput |
A data frame with the columns observation_date, observation_time and height. See attached data for correct formats. |
otz |
The time zone of the observations |
km |
The number of nodes between two consecutive mean moon transits. Shall be less or equal to: round(1440 [min] / time step [min]) Example: Time step 5 min: Use km = 288 or even smaller. Leave on default (km = -1) and supply mindt, when unsure. |
mindt |
Observation time step in [min]. Default is 30. |
asdate |
A string indication the date you want the analysis to start with. Format: "yyyy/mm/dd". |
astime |
A string indicating the time you want the analysis to start with. Format: "hh:mm:ss" |
aedate |
A string indication the date you want the analysis to end with. Format: "yyyy/mm/dd". |
aetime |
A string indicating the time you want the analysis to end with. Format: "hh:mm:ss" |
ssdate |
Synthesis start date. This indicates the date you want your tide curve to start with. Format: See above |
sstime |
Synthesis start time. The starting time for your tide table. Format: See above |
sedate |
Synthesis end date. Format: See above |
setime |
Synthesis end time. Format: See above |
Value
Returns a list with elements of the analysis, fitting and the tidal curve for given data
synthesis.lunar |
The lunar synthesis data as a data.table object in UTC |
data.matrix |
The data needed for analysis |
tide.curve |
The solar tide curve as a data.table object (provided time zone) |
lm.coeff |
Coefficients for the km fitted linear models used in the synthesis as a list of 1-row matrices |
diff.analyse |
Time in days spanning the analysis |
References
Godin, Gabriel (1972) The Analysis of Tides. Toronto, 264pp
Examples
## Not run: TideCurve(dataInput = tideObservation, asdate = "2015/12/06",
astime = "00:00:00", aedate = "2015/12/31",
aetime = "23:30:00", ssdate = "2015/12/17",
sstime = "00:00:00", sedate = "2015/12/31",
setime = "23:30:00")
## End(Not run)
Sample file of high and low water times and heights
Description
A sample dataset containing observation date, time and height of high and low water
Usage
tideObservation
Format
A data frame with 10267 rows and 3 variables
- observation_date
date of observation, character value in "yyyy/mm/dd" format
- observation_time
time of observation, character value in "hh:mm:ss" format
- height
observed value, numeric value