diff --git a/src/RQADeforestation.jl b/src/RQADeforestation.jl
index c409457..9587b48 100644
--- a/src/RQADeforestation.jl
+++ b/src/RQADeforestation.jl
@@ -15,7 +15,6 @@ include("metrics.jl")
 include("auxil.jl")
 include("rqatrend.jl")
 include("analysis.jl")  # TODO what is still needed from analysis now that rqatrend is in its own file?
-include("timestats.jl")
 include("main.jl")
 
 end
\ No newline at end of file
diff --git a/src/analysis.jl b/src/analysis.jl
index b1c8131..da2853d 100644
--- a/src/analysis.jl
+++ b/src/analysis.jl
@@ -35,83 +35,16 @@ countvalid(cube; path=tempname() * ".zarr") = mapCube(countvalid, cube; indims=I
         Y(range(1, 5, length=15)),
     )
     mock_data = allowmissing(rand(30, 10, 15))
-    mock_data[1:10,1,1] .= missing
-    mock_data[:, 2,1] .= missing
-    mock_data[[1,5,9], 2,2] .= missing
+    mock_data[1:10, 1, 1] .= missing
+    mock_data[:, 2, 1] .= missing
+    mock_data[[1, 5, 9], 2, 2] .= missing
     mock_props = Dict()
     mock_cube = YAXArray(mock_axes, mock_data, mock_props)
 
     mock_count = RQADeforestation.countvalid(mock_cube)
     @test mock_count.axes == (mock_cube.X, mock_cube.Y)
-    @test mock_count[1,1] == 20
-    @test mock_count[1,2] == 30
-    @test mock_count[2,2] == 27
-    @test mock_count[2,1] == 0
-end
-
-"""
-rqatrend(xout, xin, thresh)
-
-Compute the RQA trend metric for the non-missing time steps of xin, and save it to xout. 
-`thresh` specifies the epsilon threshold of the Recurrence Plot computation
-"""
-function rqatrend_recurrenceanalysis(pix_trend, pix, thresh=2)
-    ts = collect(skipmissing(pix))
-    tau_pix = tau_recurrence(ts, thresh)
-    pix_trend .= RA._trend(tau_pix)
-end
-
-function rqatrend_matrix(pix_trend, pix, thresh=2)
-    #replace!(pix, -9999 => missing)
-    ts = collect(skipmissing(pix))
-    rm = RecurrenceMatrix(ts, thresh)
-    pix_trend .= RA.trend(rm)
-end
-
-#=
-"""
-    rqatrend_shuffle(cube; thresh=2, path=tempname() * ".zarr", numshuffle=300)
-Compute the RQA trend metric for shuffled time series of the data cube `cube` with the epsilon threshold `thresh` for `numshuffle` tries and save it into `path`.
-"""
-function rqatrend_shuffle(cube; thresh=2, path=tempname() * ".zarr", numshuffle=300)
-    # This should be made a random shuffle
-    # TODO this looks completely broken
-    sg = surrogenerator(collect(eachindex(water[overlap])), BlockShuffle(7, shift=true))
-end
-=#
-
-
-"""
-    anti_diagonal_density(ts, thresh, metric)
-Compute the average density of the diagonals perpendicular to the main diagonal for data series `ts`.
-Uses the threshold `thresh` and `metric` for the computation of the similarities.
-"""
-function anti_diagonal_density(ts::AbstractVector, thresh, metric=Euclidean())
-    n = length(ts)
-    ad_densities = zeros(2 * n - 3)
-    for col in 1:n
-        for row in 1:(col-1)
-            d = evaluate(metric, ts[col], ts[row])
-            #@show row, col, d
-            ad_densities[col+row-2] += d <= thresh
-        end
-    end
-    half = div(n, 2)
-    maxdensities = collect(Iterators.flatten([(n, n) for n in 1:half-1]))
-    diagonallengths = [maxdensities..., half, reverse(maxdensities)...]
-    ad_densities ./ diagonallengths
-end
-
-"""
-Compute the forest masking thresholding and clustering of the rqadata in one step
-"""
-function inner_postprocessing(rqadata, forestmask; threshold=-1.28, clustersize=30)
-    @time rqamasked = rqadata .* forestmask
-    @time rqathresh = map(rqamasked) do x
-        if !ismissing(x)
-            x > threshold ? zero(Float32) : one(Float32)
-        else
-            x
-        end
-    end
+    @test mock_count[1, 1] == 20
+    @test mock_count[1, 2] == 30
+    @test mock_count[2, 2] == 27
+    @test mock_count[2, 1] == 0
 end
\ No newline at end of file
diff --git a/src/timestats.jl b/src/timestats.jl
deleted file mode 100644
index 5591845..0000000
--- a/src/timestats.jl
+++ /dev/null
@@ -1,37 +0,0 @@
-using Statistics
-using StatsBase
-
-function timestats(cube; path=tempname())
-
-    indims = InDims("Time")
-    funcs = ["Mean", "5th Quantile", "25th Quantile", "Median", "75th Quantile", "95th Quantile",
-        "Standard Deviation",
-        "Minimum", "Maximum",
-        "Skewness", "Kurtosis", "Median Absolute Deviation"]
-
-    stataxis = CategoricalAxis("Stats", funcs)
-    od = OutDims(stataxis, path=path)
-    stats = mapCube(ctimestats!, cube, indims=indims, outdims=od)
-end
-
-function ctimestats!(xout, xin)
-    x = collect(skipmissing(xin))
-    ts = x[.!isnan.(x)]
-    #    m = mean(ts)
-    #    T = eltype(m)
-    #stats = Vector{T}(undef,12)
-    if isempty(ts)
-        xout .= NaN
-    else
-        xout[1] = mean(ts)
-        xout[2:6] .= quantile(ts, [0.05, 0.25, 0.5, 0.75, 0.95])
-        xout[7] = std(ts)
-        xout[2] = minimum(ts)
-        xout[3] = maximum(ts)
-        #       stats[10] = skewness(ts)
-        #      stats[11] = kurtosis(ts)
-        #     stats[12] = mad(ts, normalize=true)
-    end
-    #xout .=stats
-    nothing
-end
\ No newline at end of file
diff --git a/test/Artifacts.toml b/test/Artifacts.toml
index 9ba9b91..db39948 100644
--- a/test/Artifacts.toml
+++ b/test/Artifacts.toml
@@ -2,5 +2,5 @@
 git-tree-sha1 = "1dc9d7aa975de4f5ecc652f34d6bbee706fcb7bd"
 
     [[rqatestdata.download]]
-    url = "https://github.com/meggart/RQADeforestationTestData/archive/refs/tags/v2.0.tar.gz"
+    url = "https://github.com/EarthyScience/RQADeforestationTestData/archive/refs/tags/v2.0.tar.gz"
     sha256 = "38a3e66a0505ed9d22c6e065627039089a421b0b143ac4c8d78aac45dd3dd497"