stplanr (version 0.6.0)

route_rolling_gradient: 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

# NOT RUN {
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))
# }