From 9c105b970b2edea62256bbf1da1b7b029e4fd133 Mon Sep 17 00:00:00 2001 From: Carlos Paniagua Date: Fri, 3 Nov 2023 00:30:11 -0400 Subject: [PATCH 1/8] feat: add distances between floe centroids to props long table --- src/tracker/tracker-funcs.jl | 25 +++++++++++++++++++++++++ 1 file changed, 25 insertions(+) diff --git a/src/tracker/tracker-funcs.jl b/src/tracker/tracker-funcs.jl index c78b2f56..ce1b4b17 100644 --- a/src/tracker/tracker-funcs.jl +++ b/src/tracker/tracker-funcs.jl @@ -497,3 +497,28 @@ function addfloemasks!(props, imgs) end return nothing end + +""" + getdist(grp, cols::Vector{Symbol}) + +Return the distances between the centroids of the floes in `grp` using data in the columns specified by `cols`. +""" +function getdist(grp, cols::Vector{Symbol}) + u, v = [v .^ 2 for v in (diff.(eachcol(grp[:, cols])))] + norm_ = sqrt.(u .+ v) + return norm_ == Float64[] ? [NaN] : vcat([NaN], norm_) +end + +""" + adddist!(props::DataFrame) + +Add a column `dist` to `props` with the distances between the centroids of the floes in `props`. + +# Arguments +- `props`: floe properties in long format +""" +function adddist!(props::DataFrame) + cols = [:row_centroid, :col_centroid] + props[!, "dist"] = vcat([getdist(grp, cols) for grp in groupby(props, :ID)]...) + return nothing +end From d58649ca5aa5cad75d3ee17ee2671aecacc05985 Mon Sep 17 00:00:00 2001 From: Carlos Paniagua Date: Fri, 3 Nov 2023 17:41:51 -0400 Subject: [PATCH 2/8] feat: add latlon to paired floes --- src/tracker/tracker-funcs.jl | 61 ++++++++++++++++++++++++++++++++-- src/tracker/tracker.jl | 64 +++++++++++++++++++++++------------- 2 files changed, 101 insertions(+), 24 deletions(-) diff --git a/src/tracker/tracker-funcs.jl b/src/tracker/tracker-funcs.jl index ce1b4b17..828a32ff 100644 --- a/src/tracker/tracker-funcs.jl +++ b/src/tracker/tracker-funcs.jl @@ -504,6 +504,7 @@ end Return the distances between the centroids of the floes in `grp` using data in the columns specified by `cols`. """ function getdist(grp, cols::Vector{Symbol}) + # Compute the square root of the sum of squares of differences between consecutive elements in specified columns of a data frame, and then prepending a NaN to the result. NaN is prepended because the first floe in a group has no previous floe to compare with. u, v = [v .^ 2 for v in (diff.(eachcol(grp[:, cols])))] norm_ = sqrt.(u .+ v) return norm_ == Float64[] ? [NaN] : vcat([NaN], norm_) @@ -517,8 +518,64 @@ Add a column `dist` to `props` with the distances between the centroids of the f # Arguments - `props`: floe properties in long format """ -function adddist!(props::DataFrame) - cols = [:row_centroid, :col_centroid] +function adddist!(props::DataFrame, cols = ["row_centroid", "col_centroid"]) + # grouping a floe `props` by the :ID, calculating a "dist" values for each group using the `getdist`` function and the :row_centroid and :col_centroid columns, and adding these "dist" values as a new column to `props`. props[!, "dist"] = vcat([getdist(grp, cols) for grp in groupby(props, :ID)]...) return nothing end + + +## LatLon functions originally from IFTPipeline.jl + +""" + convertcentroid!(propdf, latlondata, colstodrop) + +Convert the centroid coordinates from row and column to latitude and longitude dropping unwanted columns specified in `colstodrop` for the output data structure. Addionally, add columns `x` and `y` with the pixel coordinates of the centroid. +""" +function convertcentroid!(propdf, latlondata, colstodrop) + latitude, longitude = [ + [latlondata[c][x, y] for + (x, y) in zip(propdf.row_centroid, propdf.col_centroid)] for + c in ["latitude", "longitude"] + ] + + x, y = [ + [latlondata[c][z] for z in V] for + (c, V) in zip(["Y", "X"], [propdf.row_centroid, propdf.col_centroid]) + ] + + propdf.latitude = latitude + propdf.longitude = longitude + propdf.x = x + propdf.y = y + dropcols!(propdf, colstodrop) + return nothing +end + +""" + converttounits!(propdf, latlondata, colstodrop) + +Convert the floe properties from pixels to kilometers and square kilometers where appropiate. Also drop the columns specified in `colstodrop`. +""" +function converttounits!(propdf, latlondata, colstodrop) + if nrow(propdf) == 0 + dropcols!(propdf, colstodrop) + return nothing + end + convertcentroid!(propdf, latlondata, colstodrop) + x = latlondata["X"] + dx = abs(x[2] - x[1]) + convertarea(area) = area * dx^2 / 1e6 + convertlength(length) = length * dx / 1e3 + propdf.area .= convertarea(propdf.area) + propdf.convex_area .= convertarea(propdf.convex_area) + propdf.minor_axis_length .= convertlength(propdf.minor_axis_length) + propdf.major_axis_length .= convertlength(propdf.major_axis_length) + propdf.perimeter .= convertlength(propdf.perimeter) + return nothing +end + +function dropcols!(df, colstodrop) + select!(df, Not(colstodrop)) + return nothing +end diff --git a/src/tracker/tracker.jl b/src/tracker/tracker.jl index 0f71225d..76e369d8 100644 --- a/src/tracker/tracker.jl +++ b/src/tracker/tracker.jl @@ -118,8 +118,11 @@ function pairfloes( sort!(tracked) _pairs = tracked.data + # Concatenate horizontally props1, props2, tracked, and add dist as the last column for each item in _pairs + _pairs = [hcat(hcat(p.props1, p.props2, makeunique=true), p.ratios[:, ["area_under", "corr"]]) for p in _pairs] + # Make a dict with keys in _pairs[i].props2.uuid and values in _pairs[i-1].props1.uuid - mappings = [Dict(pair.props2.uuid .=> pair.props1.uuid) for pair in _pairs] + mappings = [Dict(zip(p.uuid_1, p.uuid)) for p in _pairs] # Convert mappings to functions funcsfrommappings = [x -> get(mapping, x, x) for mapping in mappings] @@ -127,37 +130,54 @@ function pairfloes( # Compose functions in reverse order to push uuids forward mapuuid = foldr((f, g) -> x -> f(g(x)), funcsfrommappings) - for prop in props[2:end] - prop.uuid = mapuuid.(prop.uuid) - end + # Apply mapuuid to uuid_1 in each set of props in _pairs => get consolidated uuids + [prop.uuid_0 = mapuuid.(prop.uuid_1) for prop in _pairs] - # Collect all unique uuids in props[i] to label as simple ints starting from 1 - uuids = unique([uuid for prop in props for uuid in prop.uuid]) + + propsvert = vcat(_pairs...) + DataFrames.sort!(propsvert, [:uuid_0, :passtime]) + rightcolnames = vcat([name for name in names(propsvert) if all([!(name in ["uuid_1", "psi_1", "mask_1"]), endswith(name, "_1")])], ["uuid_0"]) + leftcolnames = [split(name, "_1")[1] for name in rightcolnames] + matchcolnames = ["area_under", "corr", "uuid_0", "passtime", "passtime_1",] - # create mapping from uuids to index - uuid2index = Dict(uuid => i for (i, uuid) in enumerate(uuids)) + leftdf = propsvert[:, leftcolnames] + rightdf = propsvert[:, rightcolnames] + matchdf = propsvert[:, matchcolnames] + rename!(rightdf, Dict(zip(rightcolnames, leftcolnames))) - # apply the uuid2index mapping to props - for prop in props - prop.uuid .= [uuid2index[uuid] for uuid in prop.uuid] - end + df = vcat(leftdf, rightdf) - # Merge all props into one long DataFrame - propsvert = vcat(props...) + # sort by uuid_0, passtime and keep unique rows + df = DataFrames.sort!(df, [:uuid_0, :passtime]) |> unique + + + df = leftjoin(df, matchdf, on=[:uuid_0, :passtime]) + DataFrames.sort!(df, [:uuid_0, :passtime]) - # rename uuid to ID - rename!(propsvert, :uuid => :ID) + # create mapping from uuids to index as ID + uuids = unique(df.uuid_0) + uuid2index = Dict(uuid => i for (i, uuid) in enumerate(uuids)) + df.ID = [uuid2index[uuid] for uuid in df.uuid_0] + df = df[:, [name for name in names(df) if name != "uuid_0"]] - # 2. Sort propsvert by uuid and then by passtime - DataFrames.sort!(propsvert, [:ID, :passtime]) + # list ID, passtime as first columns drop passtime_1 + df = df[:, vcat(["ID", "passtime"], [name for name in names(df) if !(name in ["ID", "passtime"])])] + df = df[:, names(df)[1:end-1]] + return df +end - # 3. Move ID, passtime columns to the front - propsvert = propsvert[:, unique(["ID", "passtime", names(propsvert)...])] +""" + addlatlon(pairedfloesdf::DataFrame, refimage::AbstractString) - return (props = propsvert[:, names(propsvert)[1:15]], trackdata = _pairs) +Add columns `latitude`, `longitude`, and pixel coordinates `x`, `y` to `pairedfloesdf` +""" +function addlatlon(pairedfloesdf::DataFrame, refimage::AbstractString) + latlondata = getlatlon(refimage) + colstodrop = [:row_centroid, :col_centroid, :min_row, :min_col, :max_row, :max_col] + converttounits!(pairedfloesdf, latlondata, colstodrop) + return pairedfloesdf end - """ add_passtimes!(props, passtimes) From 46db2ea00d09f621d6268988dac18596fa5aaf4c Mon Sep 17 00:00:00 2001 From: Carlos Paniagua Date: Fri, 3 Nov 2023 21:08:45 -0400 Subject: [PATCH 3/8] feat: update addlatlon --- src/tracker/tracker.jl | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/tracker/tracker.jl b/src/tracker/tracker.jl index 76e369d8..c9453ce2 100644 --- a/src/tracker/tracker.jl +++ b/src/tracker/tracker.jl @@ -171,11 +171,11 @@ end Add columns `latitude`, `longitude`, and pixel coordinates `x`, `y` to `pairedfloesdf` """ -function addlatlon(pairedfloesdf::DataFrame, refimage::AbstractString) +function addlatlon!(pairedfloesdf::DataFrame, refimage::AbstractString) latlondata = getlatlon(refimage) colstodrop = [:row_centroid, :col_centroid, :min_row, :min_col, :max_row, :max_col] converttounits!(pairedfloesdf, latlondata, colstodrop) - return pairedfloesdf + return nothing end """ From d728a5502507f344c96bf1ad0f3271bcaf021f55 Mon Sep 17 00:00:00 2001 From: Carlos Paniagua Date: Fri, 3 Nov 2023 22:02:22 -0400 Subject: [PATCH 4/8] test: add tests for extra tracker features --- src/IceFloeTracker.jl | 1 + src/tracker/tracker.jl | 21 +++++++++++++++++- test/test-matchcorr.jl | 23 ++++++++++++-------- test/test_inputs/tracker/latlondatatest.dat | Bin 0 -> 3213634 bytes 4 files changed, 35 insertions(+), 10 deletions(-) create mode 100644 test/test_inputs/tracker/latlondatatest.dat diff --git a/src/IceFloeTracker.jl b/src/IceFloeTracker.jl index 4dfe5327..93cebba6 100644 --- a/src/IceFloeTracker.jl +++ b/src/IceFloeTracker.jl @@ -46,6 +46,7 @@ using HDF5 export HDF5, PyCall export DataFrames, DataFrame, nrow, Not, select! export Dates, Time, Date, DateTime, @dateformat_str +export addlatlon!, getlatlon include("utils.jl") include("persist.jl") diff --git a/src/tracker/tracker.jl b/src/tracker/tracker.jl index c9453ce2..bda2173d 100644 --- a/src/tracker/tracker.jl +++ b/src/tracker/tracker.jl @@ -169,7 +169,11 @@ end """ addlatlon(pairedfloesdf::DataFrame, refimage::AbstractString) -Add columns `latitude`, `longitude`, and pixel coordinates `x`, `y` to `pairedfloesdf` +Add columns `latitude`, `longitude`, and pixel coordinates `x`, `y` to `pairedfloesdf`. + +# Arguments +- `pairedfloesdf`: dataframe containing floe tracking data. +- `refimage`: path to reference image. """ function addlatlon!(pairedfloesdf::DataFrame, refimage::AbstractString) latlondata = getlatlon(refimage) @@ -178,6 +182,21 @@ function addlatlon!(pairedfloesdf::DataFrame, refimage::AbstractString) return nothing end +""" + addlatlon!(pairedfloesdf::DataFrame, latlondata::AbstractDict) + +Add columns `latitude`, `longitude`, and pixel coordinates `x`, `y` to `pairedfloesdf`. + +# Arguments +- `pairedfloesdf`: dataframe containing floe tracking data. +- `latlondata`: dictionary containing latitude and longitude data. +""" +function addlatlon!(pairedfloesdf::DataFrame, latlondata::AbstractDict) + colstodrop = [:row_centroid, :col_centroid, :min_row, :min_col, :max_row, :max_col] + converttounits!(pairedfloesdf, latlondata, colstodrop) + return nothing +end + """ add_passtimes!(props, passtimes) diff --git a/test/test-matchcorr.jl b/test/test-matchcorr.jl index 71aad356..4d2ec048 100644 --- a/test/test-matchcorr.jl +++ b/test/test-matchcorr.jl @@ -37,32 +37,37 @@ # Load data data = deserialize(joinpath(path, "tracker_test_data.dat")) passtimes = deserialize(joinpath(path, "passtimes.dat")) + latlondata = deserialize(joinpath(path, "latlondatatest.dat")) # Filtering out small floes. Algorithm performs poorly on small, amorphous floes as they seem to look similar (too `blobby`) to each other for (i, prop) in enumerate(data.props) data.props[i] = prop[prop[:, :area].>=350, :] end - _pairs, _ = IceFloeTracker.pairfloes( + _pairs = IceFloeTracker.pairfloes( data.imgs, data.props, passtimes, dt, condition_thresholds, mc_thresholds ) - @test maximum(_pairs.ID) == 10 + IceFloeTracker.addlatlon!(_pairs, latlondata) + + + + @test maximum(_pairs.ID) == 6 @test names(_pairs) == ["ID", "passtime", "area", - "min_row", - "min_col", - "max_row", - "max_col", - "row_centroid", - "col_centroid", "convex_area", "major_axis_length", "minor_axis_length", "orientation", "perimeter", - "mask"] + "area_under", + "corr", + "latitude", + "longitude", + "x", + "y"] @test issorted(_pairs, :ID) + @test all([issorted(grp, :passtime) for grp in groupby(_pairs, :ID)]) end end diff --git a/test/test_inputs/tracker/latlondatatest.dat b/test/test_inputs/tracker/latlondatatest.dat new file mode 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