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56 lines
1.5 KiB
R
56 lines
1.5 KiB
R
library(prophet)
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context("Prophet stan model tests")
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rstan::expose_stan_functions(rstan::stanc(file="../..//inst/stan/prophet_logistic_growth.stan"))
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DATA <- read.csv('data.csv')
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N <- nrow(DATA)
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train <- DATA[1:floor(N / 2), ]
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future <- DATA[(ceiling(N/2) + 1):N, ]
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DATA2 <- read.csv('data2.csv')
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DATA$ds <- prophet:::set_date(DATA$ds)
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DATA2$ds <- prophet:::set_date(DATA2$ds)
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test_that("get_changepoint_matrix", {
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history <- train
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m <- prophet(history, fit = FALSE)
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out <- prophet:::setup_dataframe(m, history, initialize_scales = TRUE)
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history <- out$df
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m <- out$m
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m$history <- history
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m <- prophet:::set_changepoints(m)
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cp <- m$changepoints.t
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mat <- get_changepoint_matrix(history$t, cp, nrow(history), length(cp))
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expect_equal(nrow(mat), floor(N / 2))
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expect_equal(ncol(mat), m$n.changepoints)
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# Compare to the R implementation
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A <- matrix(0, nrow(history), length(cp))
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for (i in 1:length(cp)) {
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A[history$t >= cp[i], i] <- 1
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}
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expect_true(all(A == mat))
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})
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test_that("get_zero_changepoints", {
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history <- train
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m <- prophet(history, n.changepoints = 0, fit = FALSE)
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out <- prophet:::setup_dataframe(m, history, initialize_scales = TRUE)
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m <- out$m
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history <- out$df
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m$history <- history
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m <- prophet:::set_changepoints(m)
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cp <- m$changepoints.t
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mat <- get_changepoint_matrix(history$t, cp, nrow(history), length(cp))
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expect_equal(nrow(mat), floor(N / 2))
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expect_equal(ncol(mat), 1)
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expect_true(all(mat == 1))
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})
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