timeIntegration: Approximate the integral of a vector of data over time
In Smisc: Sego Miscellaneous

Description Usage Arguments Details Value Author(s) Examples

Integrate a series over time by calculating the area under the "curve" of the linear interpolation of the series (akin to the Trapezoid rule). This is especially useful in calculating energy usage: kilowatt-hours, watt-seconds, etc.

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timeIntegration(data, time = names(data), lower = time[1],
  upper = time[length(time)], check.plot = FALSE, units = c("hours",
  "minutes", "seconds"))

`data`	Vector of numerical data
`time`	Vector of timestamps which correspond to `data`. These can either character or POSIXct.
`lower`	The time (character or POSIXct) of the lower bound of the integration
`upper`	The time (character or POSIXct) of the upper bound of the integration
`check.plot`	`=TRUE` makes a plot which illustrates the integration.
`units`	The units of integration, defaults to hours. It is only required to supply enough characters to uniquely complete the name.

If upper or lower does not correspond to a data point, a linear interpolation is made between the two neighboring time points to predict the resulting data value.

The approximation of the integral by joining the points in the series in a linear fashion and calculating the area under this "curve".

Landon Sego

# Some example power data
data(PowerData)

par(mfrow = c(2, 1))

# Calculate the kilowatt-minutes, display graph which shows how the
# integration is done.  This example calculates the integral using
# a contiguous subset of the data
int1 <- timeIntegration(PowerData,
                       # Convert to POSIXct in order to subtract time
                       lower = "5/6/2008 17:00:09",
                       upper = "5/6/2008 17:01:36",
                       check.plot = TRUE, units = "m")

# This example calculates the integral for all the data in 'powerData'
int2 <- timeIntegration(PowerData, check.plot = TRUE, units = "m")

# Print the outcome
pvar(int1, int2)