htsr: Hydro-Meteorology Time-Series

Description

Functions for the management and treatment of hydrology and meteorology time-series stored in a 'Sqlite' data base.

Author(s)

Maintainer: Pierre Chevallier pierre.chevallier@mailo.com

See Also

Useful links:

• https://github.com/p-chevallier/htsr

• Report bugs at https://github.com/p-chevallier/htsr/issues

Backup a data base

Description

Back a htsr sqlite data base

Usage

d_backup(fsq)

Arguments

Value

A saved data base with extension .bak

Author(s)

P. Chevallier - Jan 2019 / Nov 2020

Compact a data base

Description

Compact htsr sqlite data base

Usage

d_compact(fsq)

Arguments

Value

New data base or overwritten data base. Note that the created data base is empty.

Author(s)

P. Chevallier - Jan 2019

Convert Hubeau station files into a htsr sqlite base

Description

Convert a Hubeau hydrological file into a htsr sqlite base. It regards the "basic" data file, which includes water level and discharge data. .

Usage

d_convert_hubeau(hubeau.dir, station.id, fsqname)

Arguments

Details

The data base is build from selected stations in the "stations.tar" file available on the data.eau.france web site. This file must be first downloaded and extracted in the folder hubeau.dir. For the extraction the R function untar() can be used. Secondly Within the hubeau.dir, the file stations/stations.csv give the full list of the available stations. One or more station ids must be chosen and included in the station.id list parameter.

The units of water level data is cm and of discharge data is m3/s.

Author(s)

P. Chevallier - Jul/Aug 2024

Convert a full Hydraccess database into a new htsr sqlite database (Windows only)

Description

Because the Hydraccess application only works into a Windows environment, this function cannot be applied on other platforms (Mas OS or Linux). Additionally, the R session must be configured in 32b (see the htsr-package vignette).

Usage

d_convert_hydraccess(fsq, db.hydraccess)

Arguments

Details

If the specified sqlite data base already exists, a confirmation is requested to overwrite it.

An 32b ODBC Microsoft driver must be configured in the "administrative tools" and installed for the hydraccess data base. The correct functioning can be verified using the sub-function u_test_rodbc (db.hydraccess), which must be successful.

Value

A new or a replaced sqlite htsr data base.

Author(s)

P. Chevallier - Nov 2018-Nov 2020

See Also

ds_inventory_station and ds_inventory_sensor for displaying the content of the sqlite data base; ds_exp_hts for extracting a time-series.

Examples

## Not run: 

d_import_hydraccess("foo.sqlite","foo.mdb")

## End(Not run)

Convert a Meteo-France csv daily basic data file into a htsr sqlite base

Description

Convert a Meteo-France csv daily data file into a htsr sqlite base. It regards the "basic" data file, which includes precipitation, temperature and wind data. For other variables the function d_convert_meteofrance_d1 shall be used with the corresponding csv file. The csv file shall be downloaded from https://meteo.data.gouv.fr/ The name of the created sqlite file is the same as the csv file with an extension .sqlite.

Usage

d_convert_meteofrance_d(fmeteo)

Arguments

Details

The sensors have an additional prefix d (as daily) in order to distinguish them from sensors with another time reference.

Author(s)

P. Chevallier - dec 2023 - jan 2024

Convert a Meteo-France csv hourly basic data file into a htsr sqlite base

Description

Convert a Meteo-France csv hourly data file into a htsr sqlite base. It regards the "basic" data file, which includes precipitation, temperature and wind data. The csv file shall be downloaded from https://meteo.data.gouv.fr/ The name of the created sqlite file is the same as the csv file with an extension .sqlite.

Usage

d_convert_meteofrance_h(fmeteo)

Arguments

Details

The sensors have an additional prefix h (as hourly) in order to distinguish them from sensors with another time reference.

Author(s)

P. Chevallier - jan 2024

Convert a weewx data base into a htsr sqlite base

Description

Convert (or update) a weewx data base into a htsr sqlite base

Usage

d_convert_weewx(
  db.weewx,
  fsq = NA,
  update = TRUE,
  tzo = "Europe/Paris",
  sta = NA,
  name_st = NA
)

Arguments

Details

If update is TRUE, sta and name_st are unnecessary. I update is FALSE and fsq is NA, fsq is named "weewx.sqlite".

Author(s)

P. Chevallier - Feb 2018 - Jul 2024

Examples

## Not run: 

d_convert_weewx("weewx.sql", "foo.sqlite")

## End(Not run)

Create a data base

Description

Create htsr sqlite data base

Usage

d_create(fsq, cr_table = TRUE, bku = TRUE)

Arguments

Details

If the data base already exists and bku is TRUE, a backup is automatically generated.

If cr_table is TRUE, The following tables are also created: ST (stations), SS (sensors), WL (water levels), DI (discharges), PR (Precipitations), WE (weather) and QU (quality)

Value

a new data base

Author(s)

P. Chevallier - Jan 2019

Export discharge measurements and calibrations from data base

Description

Export discharge measurements and calibrations from data base

Usage

d_exp_discalib(fsq, sta, calib = TRUE, dism = TRUE)

Arguments

Value

a list of 2 tibbles, one with the calibration table and one with the discharge measurements

Author(s)

P. Chevallier - Sep 2017 - Nov 2020

See Also

ds_exp_hts for export time-series

Import a hts file into a data base

Description

Import a hts file into a tshm sqlite base

Usage

d_imp_hts(fsq, filein, table, bku = TRUE)

Arguments

Details

The main table where the data have to be imported must be selected with one of the following abbreviation: WL (water level), DI (discharge), WE (weather), PR (precipitation) or QU (quality) If records already exist during the same interval, they are removed and replaced.

Value

Actualized data base

Author(s)

P. Chevallier - jan 2019-jan 2024

Remove hts records from a data base

Description

Remove hts records from a Sqlite base

Usage

d_rem_hts(fsq, table, sta, sen, start, end)

Arguments

Details

The main table where the data have to be removed must be selected with one the following abbreviation: WL (water level), DI (discharge), WE (weather), PR (precipitation) or QU (quality)

Value

Actualized data base

Author(s)

P. Chevallier - jan 2019 - dec 2022

Create or remove a table of a htsr sqlite base

Description

The function allows to create or remove of a tshm sqlite base. If the base doesn't exist, it is created.

Usage

d_table(fsq, table, op = "C", bku = TRUE)

Arguments

Details

Possible table names : ST (Stations), SS (Sensors), WL (Water levels), DI (Discharges), WE, (Weather), PR (Precipitations), QU (Quality)

Value

Table created or removed

Author(s)

P. Chevallier - Jan-Feb 2018

See Also

• ds_inventory_station and ds_inventory_station to list the content of the base ;

• ds_exp_hts to extract a time-series

Extraction of a time-series from htsr data base

Description

The function display a web page allowing to extract a time-series in the "hts" format.

Usage

ds_exp_hts()

Details

Complete the requested information in the left panel, then press the submit button in order to extract the file. If you want to display the plot of the extracted file, choose "line" or "bar" and press the plot button.

When the subfunction "d_exp_hts(fsq, sta,sen,rtime=FALSE,dstart=NA,dend=NA, rplot=FALSE)" is used solely it returns a tibble tstab with 4 columns Date, Value, Station, Sensor. In this last subfunction fsq is the sqlite data base; sta, the station id, sen, the sensor id; rtime, dstart and dend define a time interval; rplot, the resulted plot.

Value

The function returns a file (nomfic) with the following name: <sensor.id>_<station.id>.hts

Author(s)

P. Chevallier - Oct 2017 - Sep 2023

Inventory of a station sensors of an htsr data base

Description

The function display a web page in order to produce an inventory of the sensors for a selected station in an htsr data base.

Usage

ds_inventory_sensor()

Details

Complete the requested information in the left panel, then press the submit button. When finished press "done".

If "Output format" is "none", the results are displayed on the screen, If it is "xlsx", or "csv" (, as separator) or "csv2" (; as separator), the corresponding file with a sensor list is written.

Value

A table with the inventory of sensors of a selected station in the data base.

Author(s)

P. Chevallier - Jan 2024

Inventory of the stations of an htsr data base

Description

The function display a web page in order to produce an inventory of the stations in an htsr data base.

Usage

ds_inventory_station()

Details

Complete the requested information in the left panel, then press the submit button. When finished press "done".

If "Output format" is "none", the results are displayed on the screen, If it is "xlsx", or "csv" (, as separator) or "csv2" (; as separator), the corresponding file with a station list is written.

Value

A table with the inventory of stations in the data base.

Author(s)

P. Chevallier - Dec 2023

Create, Modify or Remove a sensor

Description

Create, Modify or Remove a sensor.

Usage

ds_sensor()

Details

If operation is Create, the fields Station, Table and Sensor are compulsory and cannot be modified afterwards.

Allowed entries for table are: WL (water levels), DI (discharges), QU (Quality), PR (precipitations), WE (weather).

If op is Create or Modify, the following text fields can be completed optionally: Nature, Description, Comment.

If op is Remove, all data corresponding to the sensor of the selected station are removed.

The data base is automatically backuped before any operation.

Value

Sensor created, modified or removed from the data base

Author(s)

P. Chevallier - Feb 2018-Sep 2023

Create, Modify or Remove a station

Description

Create, Modify or Remove a station.

Usage

ds_station()

Details

If operation is Create, the fields Id_Station, Type_Station and Name (name_st) are compulsory. The field Name can be modified afterwards.

If op is Create or Modify the following fields can be completed optionnaly: Country, Zone, Sub-zone, Large basin, Basin, Small basin, River, Longitude, Latitude, Altitude, Basin area, Manager.

If op is Modify, station type and station id cannot be modified. The sensors and data corresponding to the station are conserved.

If op is Remove, all data and sensors of the station are removed.

Value

Station created, modified ou removed from the data base

Author(s)

P. Chevallier - Jan 2018 - Sep 2023

Change Station id or Sensor id in a hts file

Description

The function changes the station and/or the sensor id of a hts file. The new file is renamed with the new ids and a prefix n_: nw_<sensor.id>_<station.id>.hts, BUT the eventual prefixes or suffixes of the original name are not conserved. The original file is not removed.

Usage

f_change_id(file, sta = NA, sen = NA, overwrite = FALSE)

Arguments

Author(s)

P. Chevallier - Nov 2017-Jan 2019

Convert an hts file in another format (xls, xlsx or csv) and vice-versa

Description

Converter in formats hts, xls, xlsx and text (csv et csv2)

Usage

f_convert(file, form_start = "hts", form_end = "xlsx")

Arguments

Details

'form_start' = csv or csv2 is for instance not accepted. It could be converted previously in xls or xlsx format.

Value

A file in the requested format with 4 columns: Date, Value, Station, Sensor

Author(s)

P. Chevallier - October 2017 - May 2022

Examples

## Not run: 
f_convert(file,  "xlsx", "hts")

## End(Not run)

Build a multivariable table file in csv format

Description

Build a multivariable table file in csv format

Usage

f_csv_multivar(files, daily = TRUE, fileo = "fileo")

Arguments

Details

The function build a cvs file with values extracted from several hts files at the same date. So, it's better to run 'h_common' before to apply 'f_csv_multivar'

If daily is TRUE, only the date is taking into account, not the time.

Value

A csv table, where the first field is a date and the next fields values

Author(s)

P. Chevallier - Jan-Feb 2022

Interpolation of daily records from a monthly time series

Description

Interpolation of daily records from a monthly time-series

Usage

f_month2day(file)

Arguments

Details

The function build and interpolated daily time-series from a monthly one. The daily values are linearly computed between two consecutive monthly values.

Value

a daily time series

Author(s)

P. Chevallier - dec 2022

Properties of a hts series

Description

The function provides the properties of a time-series, its duration and the inventory of its gaps

Usage

f_properties(file, gaps = FALSE)

Arguments

Details

If gaps = TRUE, a file is produced, with the same name of file and the extension .gap. It contents a table with the gaps of the series and allows to build a plot with the function p_gaps.

Value

Basic infos on a hts time-series

Author(s)

P. Chevallier - Jan 2019 - Oct 2021

See Also

p_gaps.

Short-cut for file.choose

Description

Short-cut for file.choose

Usage

fc()

Value

A filename

Author(s)

P. Chevallier

Add NA values within a time series

Description

Add NA values within a time series

Usage

h_addna(file, add)

Arguments

Details

The function adds records with NA in a time series at given dates. If the date already exists, the value is replaced by NA

The output file is named with a nap_ prefix.

Author(s)

P. Chevallier - November 2022

Examples

## Not run: 

f <- h_addna (f, add = c("2021-01-01 12:00:00 UTC", "2031-01-01 12:00:00 UTC"))

## End(Not run)

Adjust a time series to a statistical model

Description

Adjust a time series to a statistical model

Usage

h_adjust(file, time_unit = "year")

Arguments

Details

The function adjust a time series with a statistical model. For instance it works only with a linear model.

"year" corresponds to an average year of 365.25 days and month to an average month of 30,4575 days.

Author(s)

P. Chevallier - January 2024

Daily average over a sequence of several years

Description

Daily average over a sequence of several years

Usage

h_avday(file, start = NA, end = NA, mhy = 1, precip = FALSE, dig = 1)

Arguments

Details

The function means the values of each calendar day over a period larger than 4 years (i.e. it includes at least one Feb 29 day). The result is transfered to the last possible hydrological year of the interval.

In the special case of precipitation, where the distribution is discontinuous over time, the original values of the last hydrological year are replaced by values corrected proportionately.

Author(s)

P. Chevallier - Nov 2022

Examples

## Not run: 

f <- h_avday(f,   start=NA, end=NA, mhy=10, precip=TRUE, dig=1)

## End(Not run)

Change the time zone of a time series

Description

Change the time zone of a time series

Usage

h_changetz(file, tz1 = "UTC", tz2 = "Europe/Paris")

Arguments

Details

The output file is named with a tz prefix.

Author(s)

P. Chevallier - June 2023

Extract 2 (or more) time-series on their common period

Description

The fonction extract the data of 2 (or more) hts time-series for the common date/time records (precision of the second).

Usage

h_common(files)

Arguments

Value

hts files resulting of the operation; their names are composed as: co_<original filename>

Author(s)

P. Chevallier - Oct 2017 - Oct 2023

Examples

## Not run: 
f <- h_common(files = c("foo1.hts","foo2.hts"))

## End(Not run)

Conditional extraction of a time-series regarding another one

Description

The series to proceed is the first of the list, the conditional series the second. Only the common record dates are kept.

Usage

h_condition(files, condition)

Arguments

Details

If the condition on the file 2 value is not respected, the value of file 1 is changed as NA.

The condition has 3 options : x< ("inf"), x>= ("sup"), < x <= ("between"). In case of error or by default, "inf" is considered. In the cases "inf" and "sup", only one threshold is used (thrhd1) ; in the case "between", two thresholds are needed (thrhd1 < thrhd2).

The output file is the name of the fist file with a cd_ prefix.

Author(s)

P. Chevallier - Oct 2017-Jan 2019

Examples

## Not run: 

f <- h_condition(c(f1,f2), c("between", O, 2))

## End(Not run)

Cumul of time-series

Description

The function returns a time-series of cumulated values. If the value is negative, the absolute value is taken. It is possible to limit the computation time interval. NA values are ignored.

Usage

h_cumul(file, start = NA, end = NA)

Arguments

Details

The output file is named with a cu_ prefix.

Author(s)

P. Chevallier - Oct 2017-Jan 2019

Examples

## Not run: 

f <- h_cumul(f, start="2012-1-1", end = "2013-1-1")

## End(Not run)

Replace errors with gaps in a time-series based on neighboring values

Description

Replace errors with gaps in a time-series based on neighboring values

Usage

h_gaperr(file, nv = 1, itv0 = 43201, df)

Arguments

Details

Replace errors with gaps in a time-series based on neighboring values

Value

a time-series file with the prefix eg_

Author(s)

P. Chevallier - Nov 2019

Simple gapfilling in a time-series

Description

Simple gapfilling in a time-series

Usage

h_gapfill(file, npdt)

Arguments

Details

Replace the missing values with the linear interpolated value within the gap interval, when the time interval is less than a number of fixed time steps.

CAUTION! this operation is only possible when the time-series has a fixed time-step.

Value

a time-series file with the prefix gf_

Author(s)

P. Chevallier - Nov 2017 - Nov 2021

Remove gaps in a time-series with a time interval threshold

Description

Remove gaps in a time-series with a time interval threshold

Usage

h_gaprem_itv(file, itv0 = 43201)

Arguments

Details

Remove the missing values when the time interval between the previous and the next record is less than a fixed threshold

Value

a time-series file with the prefix gr_

Author(s)

P. Chevallier - Nov 2019

Replace values with NA conditionally or in a time interval

Description

Replace values with NA conditionally or in a time interval

Usage

h_nodata(file, threshold = NA, test = "=", start = NA, end = NA)

Arguments

Details

The function replace values with NA conditionally or introduce a gap for a given interval.

For the conditional option, the start parameter must be NA. A conditional test is applied on the values (= ; > ; >= ; < ; <=) with a fixed threshold returning NA if the test is verified.

For the gap option, the threshold parameter must be NA. All the values of the records within the interval start end are replaces by NA.

CAUTION ! At least one of both parameters threshold or start must not be NA. NA.

The output file is named with a na_ prefix.

Author(s)

P. Chevallier - Oct 2017-Jan 2019

Examples

## Not run: 

f <- h_nodata(f, threshold=10., test= "<=", start=NA)

## End(Not run)

Share the solid and liquid precipitations with a temperature criteria

Description

The precipitations are shared with a linear bevel between two temperature values

Usage

h_rainsnow(fpr, fta, ta0, ta1, sta = NA)

Arguments

Details

The two time-series must be previously restricted to the same interval of time.

The two temperature thresholds can be equal.

The temperature time-series must be complete with no gap. Gaps are allowed in the precipitation time-series.

Is the station id is NA, the station id of the file fta is used.

Value

2 hts files, one with the liquid precipitation (prefix rn_) and one with the solid precipitation (prefix sn_).

Author(s)

P. Chevallier - Oct 2017- Feb 2019

Bind 2 time-series on consecutive periods

Description

The fonction binds the data of 2 hts time-series for consecutive date/time records (precision of the second) of the same station.

Usage

h_rbind(files, sensor = "NewS", gap = TRUE)

Arguments

Details

In the list, the files must be ordered from the oldest to the newest. If gap is TRUE, a gap is introduced between both series.

Value

hts file resulting of the operation; its names are composed as: <sensor>_<station>.hts, with the prefix na, if a gap has been introduced.

Author(s)

P. Chevallier - Mar-Nov 2020

Examples

## Not run: 

f <- h_bind(files = c("foo1.hts","foo2.hts"), sensor = "NewOne")

## End(Not run)

Replace a value by another

Description

Replace a value by another

Usage

h_replace(file, old.val, new.val)

Arguments

Details

The output file is named with a re_ prefix.

Author(s)

P. Chevallier - Oct 2017- Nov 2020

Examples

## Not run: 

f <- ts_remplace_ts(f,  NA, 0)

## End(Not run)

Restrict a series between 2 dates

Description

Restrict a series between 2 dates

Usage

h_restrict(file, start = NA, end = NA)

Arguments

Details

The output file is named with a rs_ prefix.

Author(s)

P. Chevallier - Nov 2017-Jan 2019

Rolling average of a daily time-series

Description

The function compute a rollong average of daily time-series values. NA values are removed.

Usage

h_rollav(file, ti = 7, position = "central")

Arguments

Details

The output file is named with a ro_ prefix. The computation can considers the values before and after the current time step (position = "central") or the values before the current time step. If the position is "central", the position must be an odd integer.

Author(s)

P. Chevallier - Apr 2020

Seasonal selection

Description

The function provides seasonal time-series.

Usage

h_season(file, monthstart)

Arguments

Details

2 to 4 seasons can be selected. For each season, the prefix sx_ where x is the season is added to the file name.

Value

list of file names for each seasonal time-series.

Author(s)

P. Chevallier - Oct 2017 - Mar 2020

Examples

## Not run: 

files <- h_season("foo.hts", monthstart=c(3,6,9,12))

## End(Not run)

Basic statistics of a time-series

Description

Compute the main statistic parameters of a time-series

Usage

h_stat_basic(files)

Arguments

Value

a tibble with the basic stats of the files.

Author(s)

P. Chevallier - Oct 2017 - Feb 2022

Examples

## Not run: 
simplestat <- h_stat_basic(c("foo1.hts", "foo2.hts")

## End(Not run)

Subtitute the missing values in a series by existing values of another series

Description

The series to proceed (first in file list) contents missing values or gaps to be replaced by those of the second series (second in file list).

The function only works on the common dates of both series.

Usage

h_substitute(files)

Arguments

Details

The output file is named with a sb_ prefix.

Author(s)

P. Chevallier - Feb 2017 - Mar 2020

Examples

## Not run: 

f <- h_substitute(c(f1, f2))

## End(Not run)

Weighted sum of time-series

Description

The function only works on the common period of the files without NA values. It operates weighted sums on one or several time-series. It is also possible to add a constant.

Usage

h_weightedsum(files, weights, constant = 0)

Arguments

Details

For averaging n time-series one can use n weights wit a value of 1/n and constant = 0.

Value

The function returns + n hts files with the extracted common period + 1 hts file named as the first file of the list with the prefix w_. The sensor id is automatically set to "weighted".

Author(s)

P. Chevallier - Oct 2017-Oct 2021

Examples

## Not run: 

# choose time-series f1, f2, f3
f1 <- "foo1.hts" ; f2 <- "foo2.hts" ; f3 <- "foo3.hts"
# the new f time-series contains records f[i] = f1[i] - (0.5 * f2[i]) + (0.5 * f3[i]) + 5
f <- h_weightedsum(c(f1,f2,f3), c(1,-0.5,0.5)), 5)
# the new f time-series contains records f[i] = (1.12 * f1[i]) + 3
f <- h_weightedsum(f1, 1.12, 3)

## End(Not run)

Computation of the discharges from water-levels

Description

Computes a discharge time-series from water levels data and calibration curves

Usage

h_wl_di(fsq, sta, seni, seno, dstart = NA, dend = NA, dbo = TRUE)

Arguments

Details

Calibration curves must exist in the data base.

If 'dbo' is TRUE, a discharge table "DI" and the sensor 'seno' must exist in the data base. The new discharge time-series overwrites the already existing data ; however, it is asked to confirm the operation. In any case the data base is previously backed up.

Value

Writes an hts file with the resulting discharges and optionally includes it in the data base.

Author(s)

P. Chevallier - Dec 2020 - Sep 2023

See Also

The functions ds_exp_hts and d_imp_htsare used for export the water levels, respectively import the discharges within the data base. The function u_exp_discalib included in p_discalib is used for loading the calibration curves.

Annual time series

Description

Annual time series

Usage

h_year(file, mhy = 1, op = "M", dig = 1)

Arguments

Details

The function computes an annual time-series using the annual mean or the annual sum of daily values. It allows the use of hydrological years. The date corresponds to the middle of the year, i.e. the 182th day.

Value

The function returns a time-series of annual values.

Author(s)

P. Chevallier - Nov 2022

hts time series with fixed timestep

Description

Computes time-series with a fixed timestep from infra-daily to monthly within a shiny web page.

Usage

hs_tstep()

Details

First of all, one must select a "starting" hts file, instantaneous or already with a fixed timestep.

Then one must choose the computing time-step and mode, between the possible choices. Note that the timezone considered is the timezone of the "starting" file.

Possible time-steps are: 5, 10 or 30 minutes, 1, 2, 3, 6 or 12 hours, 1 day, 1 month. It shall be noted that when computing the monthly time step, the daily time step is previously computed.

Possible modes are: average, sum, max or min. For monthly time step, max and min offers two options: daily max averages, respectively min, or absolute, respectively min.

In the case of a daily timestep, a shift value (in hours) allows to shift the time interval. For example if shift = 6, the date is computed from 6am until 6am the following day. The result is dated in the middle of the interval, i.e. if shift = 6; the datetime is 18.

In the case of a monthly timestep, associated additional time series can be optionally computed:

• A mean monthly climatology, taking into account or not the missing daily values with the option "remove NA". Climatology files are by convention awarded to year 2000.

• Excel files: with a calendar presentation (days in rows, months in columns, years in sheets): option caledit_j ; with the monthly means (or sums): option caledit_m.

• Missing values can be replaced by the mean of the existing values for other years: option gapfill.

• Extract year stat

The output files are written in same folder as the starting hts file.

Value

hts files at the requested timestep with a suffix giving the timestep in minutes, i.e. 1440 for the daily timestep. In the case or monthly timestep, the suffixes are: M for the current case, C for the climatology, G for the gapfilled file.

Optionally, two Excel files with values in "calendar form": one with daily data and one with monthly data, the fist one with a ad_ prefix and the second one with the am_ prefix.

Author(s)

P. Chevallier - Oct 2017 - Sep 2023

Boxplot of the 12 months of a time-series.

Description

Boxplot of the 12 months of a time-series.

Usage

p_box_month(
  file,
  title = "Title",
  axeY = "Y-axis",
  savefig = FALSE,
  fileo = "plot.png",
  width = 8,
  height = 6
)

Arguments

Value

A ggplot2 object

Author(s)

P. Chevallier - Nov 2017 -Feb 2019

Plot climatologies in hydrological year

Description

This function processes climatology hts files created with hs_tstep.

Usage

p_clim(
  files,
  type = "line",
  hydro.month = 1,
  title = "Title",
  yaxis = "Value",
  y.down = NA,
  y.up = NA,
  rpal = FALSE,
  pal = mapalette,
  legend.l = NA
)

Arguments

Details

The parameter tyoe allows to display a line graph or a bar graph.

The parameter hydro.mont fixes the starting month of the hydrological year.

The y-axis scale can be fixed with y.down and y.up.

By default, the color palette is the R one. It can be change with a color list in the pal parameter or choosing mapalette (default in pal)

Par default station_sensor ids are displayed in the legend.l list. But it can be changed entering a list of texts in legend.l,, which must have the same length as the file number.

Value

A ggplot2 object.

Author(s)

P. Chevallier - Feb 2017 - Sep 2023

Plot calibration curves water levels vs discharges

Description

Experimental function, which is for instance limited to only two calibration curves on the same plot.

The function plot the discharges measurements and the corresponding calibration curves starting.

Only the "active" discharge measurements are plotted. The parameter plotdism displays them or not.

One can zoom on a subpart of the plot using the limit values on the x and y axis.

The savefig (default = FALSE by default) parameter allows to save the result i a png, jpg or pdf file, according to the extension of fout.

Usage

p_discalib(
  fsq,
  sta,
  sen = "IH",
  plotcalib = TRUE,
  plotdism = TRUE,
  title = "Title",
  savefig = FALSE,
  width = 8,
  height = 6,
  fout = "plot.png",
  limx = FALSE,
  limy = FALSE,
  xinf = NA,
  xsup = NA,
  yinf = NA,
  ysup = NA
)

Arguments

Author(s)

P. Chevallier - Sep 2017 - Dec 2020

Plot of data inventory

Description

This function plot an inventory of the data from one or several station(s)-sensor(s). It is based on the .gap files provided by the function f_properties. It allows to highlight the gaps in time-series.

Usage

p_gaps(files, title = "Inventory", BW = FALSE, margin = 0.1)

Arguments

Details

The inventories are represented with lines displayed bottom-up in the order of the files list. They are labeled with the station_sensor ids.

Colors are the default colors of ggplot2. For a black & white plot, precise BW = TRUE

The margin value is a reserved space for writing the label at the end of each line. Default value is 0.1 of the difference between the minimum and the maximum date. It shall be adjusted following the length of the labels.

Value

A ggplot2 object

Author(s)

P. Chevallier - Nov 2017 - Sep 2023

See Also

f_properties.

Plot the hypsometry curve of one or more basins

Description

Plot the hypsometry curve of one or more basins

Usage

p_hypso(
  file,
  abbrev,
  prop = FALSE,
  range = 50,
  fact = 5,
  title = "Title",
  savefig = FALSE,
  width = 8,
  height = 6,
  fileo = "plot.png"
)

Arguments

Value

An object of ggplot2 class

Author(s)

P. Chevallier - Sep 2017- Jun 2023

Scatter plot of 2 or more time-series

Description

The reference time-series is the first of the list. The scatter plot regards only the common dates of the series. In addition to the plot, a linear function is adjusted forcing or not the interception by the origin.

Usage

p_scatter(
  files,
  intercept.zero = FALSE,
  remove.zero = FALSE,
  lg.axis = c(NA, NA),
  title = "Title"
)

Arguments

Value

a table named "result" with 5 columns : variable name, size of the sample, correlation coefficient, regression line slope, interception

Author(s)

P. Chevallier - Oct 2017-Apr 2023

Examples

## Not run: 

result <- p_scatter(files = c("foo1.RData","foo2.RData"),
          intercept.zero = TRUE)

## End(Not run)

Plot wind roses

Description

Plot wind roses

Usage

p_wind(
  fsq,
  sta,
  swd,
  swv,
  ws.int = 0.5,
  angle = 45,
  grid.line = 10,
  type = "default",
  breaks = 5,
  offset = 5,
  paddle = FALSE,
  key.position = "right"
)

Arguments

Details

For a detailed description of all parameters see windRose

Value

A wind rose plot

Author(s)

P. Chevallier - Dec 2019 - Sep 2023

See Also

windRose

Plot hts files

Description

This function allows to plot one or several time series files using a shiny web page

Usage

ps_plothts()

Details

When launched, a shiny window is open. Follow the instructions, divided in 5 steps.

1. Select hts files (8 max) pressing "File select". They must be located in the same folder. When done, press "Enter file settings"

2. For each file, if needed, use the "Edit" tab to configure label, line.type, line.with, point.shape and point.size. (The values follows the ggplot2 package conventions). When done, press "Save file settings"

3. Configure the general layout of the file, entering Title and y-Axis label and choosing a color palette. Several options are available: set y-Axis scale, set time interval, point plot(*), display normalized values, draw a trend line, or display the plot as horizontal facets. When done, press "Save plot settings"

4. Pressing "Plot" displays the graph. You can chose a line or bar graph. When the graph is finalized, check the box "save plot". Three formats are allowed: .png, .jpeg or pdf. The resolution is 300 dpi. Then, press "Save plot settings". The plot is saved in the folder of the selected files.

5. When finished, press "Done".

Items 2 and 3 can be performed and repeated in any order. Once they have been validated once, item 4 can be executed as often as desired.

(*) When point plot is selected, the points overlay the line (point plot doesn't work with bar). If you want only the points on the plot, configure "line.type" and "line.width" = 0.

Author(s)

P. Chevallier - Apr 2015 - Sep 2023

Compute an index of community

Description

Compute an index of community

Arguments

Details

the function compute an index, which the number of apparition of the same datetime in a time-series

Value

vector of indexes

Author(s)

P. Chevallier - Apr - Oct 2023

Compute values in a time-series with a fixed timestep

Description

Compute values in a time-series with a fixed timestep

Arguments

Details

iop = 1 for sum; 0 for mean; -2 for min and +2 for max

Value

vector of values with fixed timestep

Author(s)

P. Chevallier - June / Oct 2023

Compute atmospheric pressure, function of altitude

Description

Compute atmospheric pressure, function of altitude

Usage

w_atmp_alt(f_atmp, f_temp, alt)

Arguments

Details

The function computes an atmospheric pressure time-series at a given altitude, based on a known atmospheric pressure time-series at the sea level. It also needs the air temperature time-series at the sea level for the same times.

In order to verify that both time-series correspond, it is strongly recommended to run previously the function h_common.

Value

An hts file with the suffixe _<alt>

Author(s)

P. Chevallier - Nov 2021 / Nov 2022

Compute the potential evapotranspiration with several methods

Description

ETP calculation

Usage

w_etp(
  method = c("Turc", "Penman-Monteith", "Priestley-Taylor", "Makkink",
    "Heargraves-Samani"),
  freq = c("day", "month"),
  f_temp,
  f_relh = NA,
  f_radg = NA,
  f_radn = NA,
  f_atmp = NA,
  f_wvel = NA,
  f_tmin = NA,
  f_tmax = NA,
  lat = NA,
  alt = NA,
  albedo = NA,
  z = NA
)

Arguments

Details

f_temp and f_relh are mandatory in all cases.

For the Turc method, f_radg is needed.

For the Penman-Monteith method, f_atmp, f_wvel, h and z are needed. If f_radn is not avalaible, lat, f_tmin and ftmax are also needed.

The Turc method only works with a monthly frequence.

Value

An hts files resulting of the operation with a name composed as:

<J or M><EtpTu>_<Station_id>.hts for the Turc method,

<J or M><EtpPM>_<Station_id>.hts for the Penman-Monteith method,

<J or M><EtpPT>_<Station_id>.hts for the Priestley-Taylor method

<J or M><EtpMa>_<Station_id>.hts for the Makkink method

<J or M><EtpHS>_<Station_id>.hts for the Heargraves-Samani method

Author(s)

P. Chevallier - April 2020-Nov2022

Source

Hingray, B., Picouet, C., Musy A., Hydrologie, une science pour l'ingénieur, Presses Plolytechniques et Universitaires Romandes, 2008,

Allen, R.G., L.S. Pereira, D. Raes, and M. Smith. 1998. Crop Evapotranspiration. Guidelines for Computing Crop Water Requirements. FAO Irrigation and Drainage Paper 56. 300p

Er-Raki, S., A. Chehbouni, S. Khabba, V. Simonneaux, L. Jarlan, A. Ouldbba, J. C. Rodriguez, and R. Allen. 2010. “Assessment of Reference Evapotranspiration Methods in Semi-Arid Regions: Can Weather Forecast Data Be Used as Alternate of Ground Meteorological Parameters?” Journal of Arid Environments 74 (12): 1587–96. https://doi.org/10.1016/j.jaridenv.2010.07.002.

Convert specific humidity to relative humidity

Description

Convert specific humidity to relative humidity

Usage

w_spechum2relhum(f_spechum, f_temp, f_atm)

Arguments

Details

Converting specific humidity into relative humidity. from Bolton 1980 The computation of Equivalent Potential Temperature

Value

a file of relative humidity, ratio of actual water mixing ratio to saturation mixing ratio

Author(s)

P. Chevallier - Nov 2022

Source

David LeBauer - 2014

from Bolton 1980 The computation of Equivalent Potential Temperature

https://earthscience.stackexchange.com/questions/2360/how-do-i-convert-specific-humidity-to-relative-humidity

Compute temperature, function of altitude

Description

Compute temperature, function of altitude

Usage

w_temp_alt(file, alt0 = 0, alt, grad = -0.0065)

Arguments

Details

The function computes an air temperature time-series at a given altitude, based on a known air temperature time-series at a known altitude.

Value

An hts file with the suffix _<alt>

Author(s)

P. Chevallier - Nov 2021

Coordinate utility

Description

Convert numeric coordinates in character coordinates

Usage

z_coord(ncoord = NA, ccoord = NA, type)

Arguments

Details

Only one of both parameters ncoord (numeric) and ccoord (character) must be filled, the other one remaining NA. The type of coordinate (Lat or Lon) is compulsory.

The character coordinate must be organized in one string with 4 fields (degrees, minutes, seconds, direction) separated with blanks (space or tab). Within each field, no blanks are allowed to share the numeric value and the unit character. For the unit character, the only following letters are allowed: letter d/m/s. For direction, the only the following letters are allowed: N/n/W/w/S/s/E/e.

Example: "25d 18m 56.2s S"

Value

Coordinates in characters

Author(s)

P. Chevallier - Jan 2019 / Nov 2020