hydroTSM (version 0.7-0)

(sub)daily2monthly: (sub)Daily -> Monthly

Description

Generic function for transforming a DAILY (sub-daily or weekly) regular time series into a MONTHLY one

Usage

daily2monthly(x, ...)
subdaily2monthly(x, ...)
# S3 method for default
daily2monthly(x, FUN, na.rm=TRUE, na.rm.max=0, ...)
# S3 method for zoo
daily2monthly(x, FUN, na.rm=TRUE, na.rm.max=0, ...)
# S3 method for data.frame
daily2monthly(x, FUN, na.rm=TRUE, na.rm.max=0, dates=1, 
        date.fmt = "%Y-%m-%d", out.type = "data.frame", out.fmt="numeric", 
        verbose=TRUE, ...)
# S3 method for matrix
daily2monthly(x, FUN, na.rm=TRUE, na.rm.max=0, dates=1, 
        date.fmt = "%Y-%m-%d", out.type = "data.frame", out.fmt="numeric", 
        verbose=TRUE, ...)

Value

a zoo object with monthly time frequency

Arguments

x

zoo, data.frame or matrix object, with (sub)daily time series.
Measurements at several gauging stations can be stored in a data.frame or matrix object, and in that case, each column of x represents the time series measured in each gauging station, and the column names of x have to correspond to the ID of each station (starting by a letter).

FUN

Function that have to be applied for transforming from daily to monthly time step (e.g., for precipitation FUN=sum and for temperature and streamflow ts FUN=mean).

FUN MUST accept the na.rm argument, because na.rm is passed to FUN.

na.rm

Logical. Should missing values be removed?
-) TRUE : the monthly values are computed only for months with a percentage of missing values less than na.rm.max
-) FALSE: if there is AT LEAST one NA within a month, the corresponing monthly values in the output object will be NA.

na.rm.max

Numeric in [0, 1]. It is used to define the maximum percentage of missing values allowed in each month to keep the monthly aggregated value in the output object of this function. In other words, if the percentage of missing values in a given month is larger or equal than na.rm.max the corresponding monthly value will be NA.

dates

numeric, factor or Date object indicating how to obtain the dates for each gauging station
If dates is a number (default), it indicates the index of the column in x that stores the dates
If dates is a factor, it is converted into Date class, using the date format specified by date.fmt
If dates is already of Date class, the code verifies that the number of days on it be equal to the number of elements in x

date.fmt

character indicating the format in which the dates are stored in dates, e.g. %Y-%m-%d. See format in as.Date.
ONLY required when class(dates)=="factor" or class(dates)=="numeric".

out.type

Character that defines the desired type of output. Valid values are:
-) data.frame: a data.frame, with as many columns as stations are included in x, and row names indicating the month and year for each value.
-) db : a data.frame, with 4 columns will be produced.
The first column (StationID) stores the ID of the station,
The second column (Year) stores the year
The third column (Month) stores the Month
The fourth column (Value) stores the numerical values corresponding to the values specified in the three previous columns.

out.fmt

OPTIONAL. Only used when x is a matrix or data.frame object /cr character, for selecting if the result will be a matrix/data.frame or a zoo object. Valid values are: numeric, zoo.

verbose

logical; if TRUE, progress messages are printed

...

arguments additional to na.rm passed to FUN.

Author

Mauricio Zambrano-Bigiarini,

See Also

cmv, subhourly2hourly, daily2annual, subdaily2daily, monthlyfunction, hydroplot, vector2zoo, izoo2rzoo, as.Date

Examples

######################
## Ex1: Computation of monthly values, removing any missing value in 'x'

# Loading the DAILY precipitation data at SanMartino
data(SanMartinoPPts)
x <- SanMartinoPPts

# Subsetting 'x' to its first three months (Jan/1921 - Mar/1921)
x <- window(x, end="1921-03-31")

## Transforming into NA the 10% of values in 'x'
set.seed(10) # for reproducible results
n           <- length(x)
n.nas       <- round(0.1*n, 0)
na.index    <- sample(1:n, n.nas)
x[na.index] <- NA

## Agreggating from Daily to Monthly, removing any missing value in 'x'
m <- daily2monthly(x, FUN=sum, na.rm=TRUE)

######################
## Ex2: Computation of monthly values only when the percentage of NAs in each
#       month is lower than a user-defined percentage (10% in this example).

# Loading the DAILY precipitation data at SanMartino
data(SanMartinoPPts)
x <- SanMartinoPPts

# Subsetting 'x' to its first three months (Jan/1921 - Mar/1921)
x <- window(x, end="1921-03-31")

## Transforming into NA the 10% of values in 'x'
set.seed(10) # for reproducible results
n           <- length(x)
n.nas       <- round(0.1*n, 0)
na.index    <- sample(1:n, n.nas)
x[na.index] <- NA

## Daily to monthly, only for months with less than 10% of missing values
m2 <- daily2monthly(x, FUN=sum, na.rm=TRUE, na.rm.max=0.1)

# Verifying that the second and third month of 'x' had 10% or more of missing values
cmv(x, tscale="month")

######################
## Ex3: Loading the HOURLY streamflows for the station Karamea at Gorge
data(KarameaAtGorgeQts)
x <- KarameaAtGorgeQts

# Sub-daily to monthly ts
subdaily2monthly(x, FUN=mean, na.rm=TRUE)