feat: update for new IFT.pairfloes features

Includes latlon data in output data structure which requires a path to a reference geotiff image with these data.

Project.toml

@@ -18,7 +18,7 @@ TOML = "fa267f1f-6049-4f14-aa54-33bafae1ed76"
 ArgParse = "1.1.4"
 Folds = "0.2.8"  
 HDF5 = "0.16.15"
-IceFloeTracker = "0.3.0"
+IceFloeTracker = "0.4"
 LoggingExtras = "1.0.1"
 PyCall = "1.96.1"
 Pkg = "1.9.0"

src/cli-config.jl

@@ -81,8 +81,8 @@ function mkclitrack!(settings)
         help = "Path to object with satellite pass times"
         required = true
 
-        "--deltat"
-        help = "Path to object with time deltas between consecutive images"
+        "--latlon"
+        help = "Path to geotiff image with latitude/longitude data"
         required = true
 
         "--output", "-o"

src/track-docstring.jl

@@ -2,7 +2,7 @@
 Pair floes in the floe library using an equivalent implementation as in the MATLAB script `final_2020.m` from https://github.com/WilhelmusLab/ice-floe-tracker/blob/main/existing_code/final_2020.m.
 
 # Arguments
-- `indir`: path to directory containing the floe library (cropped floe masks for registration and correlation), extracted features from segmented images, and overpass elapsed times `delta_t`.
+- `indir`: path to directory containing the floe library (cropped floe masks for registration and correlation), extracted features from segmented images, and satellite overpass times.
 - `condition_thresholds`: 3-tuple of thresholds (each a named tuple) for deciding whether to match floe `i` from day `k` to floe j from day `k+1`.
 - `mc_thresholds`: thresholds for area mismatch and psi-s shape correlation and goodness of a match. 
 

src/tracker.jl

@@ -2,7 +2,7 @@
     track(
     imgsdir::String,
     propsdir::String,
-    timedeltasdir::String,
+    passtimesdir::String,
     paramsdir::String,
     outdir::String,
 )
@@ -11,13 +11,13 @@ $(include("track-docstring.jl"))
 """
 function track(; args...)
     condition_thresholds, mc_thresholds = get_thresholds(; args...)
-    vals = values(args)
+    vals = NamedTuple{Tuple(keys(args))}(values(args)) # convert to NamedTuple
     imgs = deserialize(joinpath(vals.imgs, "segmented_floes.jls"))
     props = deserialize(joinpath(vals.props, "floe_props.jls"))
     passtimes = deserialize(joinpath(vals.passtimes, "passtimes.jls"))
-    deltat = deserialize(joinpath(vals.deltat, "timedeltas.jls"))
-    labeledfloes, tracked = pairfloes(imgs, props, passtimes, deltat, condition_thresholds, mc_thresholds)
-    [serialize(joinpath(vals.output, name), obj) for (name, obj) in zip(["labeled_floes.jls", "track_data.jls"], [labeledfloes, tracked])]
+    latlon = vals.latlon
+    labeledfloes = IceFloeTracker.pairfloes(imgs, props, passtimes, latlon, condition_thresholds, mc_thresholds)
+    serialize(joinpath(vals.output, "labeled_floes.jls"), labeledfloes)
     return nothing
 end
 

test/_test-track.jl

@@ -7,19 +7,19 @@ end
 IFTPipeline.mkclitrack!(settings)
 
 params_path = "../config/sample-tracker-params.toml"
-
+latlonrefimage = "test_inputs/NE_Greenland_truecolor.2020162.aqua.250m.tiff"
 data_path = "test_inputs/tracker/"
 temp = mkpath(joinpath(@__DIR__, "__temp__"))
 cliparams = [
-    "track",
+    "track", # command
     "--imgs",
     temp,
     "--props",
     temp,
     "--passtimes",
     temp,
-    "--deltat",
-    temp,
+    "--latlon",
+    latlonrefimage,
     "--output",
     temp,
     "--params",
@@ -36,14 +36,13 @@ end
 
 serialize(joinpath(temp, "segmented_floes.jls"), obj.imgs)
 serialize(joinpath(temp, "floe_props.jls"), obj.props)
-serialize(joinpath(temp, "timedeltas.jls"), [15.0, 20.0])
 serialize(joinpath(temp, "passtimes.jls"), passtimes)
 
 argsparam = parse_args(cliparams, settings; as_symbols=true)
 cmd = argsparam[:_COMMAND_]
 IFTPipeline.track(; argsparam[cmd]...)
 tracked = deserialize(joinpath(temp, "labeled_floes.jls"))
 @test isfile(joinpath(temp, "labeled_floes.jls"))
-@test nrow(tracked) == 22
-@test maximum(tracked.ID) == 10
+@test nrow(tracked) == 18
+@test maximum(tracked.ID) == 6
 @test "passtime" in names(tracked)