Merge pull request #231 from mrc-ide/gh-230

Allow just one entry in the particle filter data

.lintr

@@ -1,4 +1,5 @@
 linters: with_defaults(
+    indentation_linter = NULL,
     object_length_linter = NULL,
     object_usage_linter = NULL,
     todo_comment_linter = NULL,

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: mcstate
 Title: Monte Carlo Methods for State Space Models
-Version: 0.9.16
+Version: 0.9.17
 Authors@R: c(person("Rich", "FitzJohn", role = c("aut", "cre"),
                     email = "rich.fitzjohn@gmail.com"),
              person("Marc", "Baguelin", role = "aut"),

R/particle_filter_data.R

@@ -143,13 +143,6 @@ particle_filter_data <- function(data, time, rate, initial_time = NULL,
     }
   }
 
-  ## I am not entirely sure why we require two time windows and not
-  ## one - it's possible this is a hangover an earlier version where
-  ## the first line was the start time?
-  if (length(model_time_end) < 2) {
-    stop("Expected at least two time windows")
-  }
-
   if (!is_continuous && any(model_time_end < 0)) {
     stop("All times must be non-negative")
   }

tests/testthat/test-particle-filter-data.R

@@ -113,13 +113,14 @@ test_that("particle filter can offset initial data", {
 })
 
 
-test_that("require more than one observation", {
+test_that("allow only one observation", {
   d <- data.frame(hour = 1:2, a = 2:3, b = 3:4)
-  expect_error(
-    particle_filter_data(d[1, ], "hour", 10, 0),
-    "Expected at least two time windows")
-  expect_silent(
-    particle_filter_data(d, "hour", 10, 0))
+  df1 <- particle_filter_data(d[1, ], "hour", 10, 0)
+  df2 <- particle_filter_data(d[1:2, ], "hour", 10, 0)
+
+  expect_equal(names(df1), names(df2))
+  expect_equal(df1[, ], df2[1, ])
+  expect_equal(nrow(df1), 1)
 })
 
 

tests/testthat/test-particle-filter.R

@@ -1742,3 +1742,35 @@ test_that("filter works with irregular data", {
 
   expect_equal(ll2, ll1)
 })
+
+
+test_that("filter works with single data point", {
+  dat <- example_sir()
+
+  set.seed(1)
+  d <- dat$data_raw[1:3, ]
+  d$incidence[1:2] <- NA
+
+  df1 <- particle_filter_data(d, "day", 4, 0)
+  df2 <- particle_filter_data(d[-1, ], "day", 4, 0)
+  df3 <- particle_filter_data(d[-(1:2), ], "day", 4, 0)
+
+  n_particles <- 42
+  set.seed(1)
+  p1 <- particle_filter$new(df1, dat$model, n_particles, dat$compare,
+                            index = dat$index, seed = 1L)
+  ll1 <- p1$run(list())
+
+  set.seed(1)
+  p2 <- particle_filter$new(df2, dat$model, n_particles, dat$compare,
+                            index = dat$index, seed = 1L)
+  ll2 <- p2$run(list())
+
+  set.seed(1)
+  p3 <- particle_filter$new(df3, dat$model, n_particles, dat$compare,
+                            index = dat$index, seed = 1L)
+  ll3 <- p3$run(list())
+
+  expect_equal(ll2, ll1)
+  expect_equal(ll3, ll1)
+})