route_rolling_gradient: Calculate rolling average gradient from elevation data at...

In ropensci/stplanr: Sustainable Transport Planning

Calculate rolling average gradient from elevation data at segment level

Description

Calculate rolling average gradient from elevation data at segment level

Usage

route_rolling_gradient(elevations, distances, lag = 1, n = 2, abs = TRUE)

Arguments

elevations	Elevations, e.g. those provided by the cyclestreets package
distances	Distances, e.g. those provided by the cyclestreets package
lag	The window size of the smoothing function. The default, 3, will take the mean of values before, after and including each value.
n	The window size of the smoothing function. The default, 3, will take the mean of values before, after and including each value.
abs	Should the absolute (always positive) change be returned? True by default

See Also

Other route_funs: route_average_gradient(), route_rolling_average(), route_rolling_diff(), route_sequential_dist(), route_slope_matrix(), route_slope_vector()

Examples

r1 <- od_data_routes[od_data_routes$route_number == 2, ]
y <- r1$elevations
distances <- r1$distances
route_rolling_gradient(y, distances)
route_rolling_gradient(y, distances, abs = FALSE)
route_rolling_gradient(y, distances, n = 3)
route_rolling_gradient(y, distances, n = 4)
r1$elevations_diff_1 <- route_rolling_diff(y, lag = 1)
r1$rolling_gradient <- route_rolling_gradient(y, distances, n = 2)
r1$rolling_gradient3 <- route_rolling_gradient(y, distances, n = 3)
r1$rolling_gradient4 <- route_rolling_gradient(y, distances, n = 4)
d <- cumsum(r1$distances) - r1$distances / 2
diff_above_mean <- r1$elevations_diff_1 + mean(y)
par(mfrow = c(2, 1))
plot(c(0, cumsum(r1$distances)), c(y, y[length(y)]), ylim = c(80, 130))
lines(c(0, cumsum(r1$distances)), c(y, y[length(y)]))
points(d, diff_above_mean)
abline(h = mean(y))
rg <- r1$rolling_gradient
rg[is.na(rg)] <- 0
plot(c(0, d), c(0, rg), ylim = c(0, 0.2))
points(c(0, d), c(0, r1$rolling_gradient3), col = "blue")
points(c(0, d), c(0, r1$rolling_gradient4), col = "grey")
par(mfrow = c(1, 1))

ropensci/stplanr documentation built on May 5, 2024, 5:49 p.m.