Calculate rolling average gradient from elevation data at segment level
Calculate rolling average gradient from elevation data at segment level
route_rolling_gradient(elevations, distances, lag = 1, n = 2, abs = TRUE)
elevations |
Elevations, e.g. those provided by the |
distances |
Distances, e.g. those provided by the |
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 |
Other route_funs:
route_average_gradient(),
route_rolling_average(),
route_rolling_diff(),
route_sequential_dist(),
route_slope_matrix(),
route_slope_vector()
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))
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.