#>

#> ── Checking arguments ──────────────────────────────────────────────────────────

#> ✓ Segmentation with seg.var = c("x", "y")

#> ✓ Using lmin = 10

#> ✓ Using Kmax = 15

#> ✓ Using ncluster = 2:4

#> ! Argument scale.variable missing

#> Taking default value scale.variable = TRUE for segclust().

#> ℹ Argument diag.var was not provided

#> Taking default seg.var as diagnostic variables diag.var.

#> Setting diag.var = c("x", "y")

#> ℹ Argument order.var was not provided

#> Taking default diag.var[1] as ordering variable order.var.

#> Setting order.var = "x"

#>

#> ── Preparing and checking data ─────────────────────────────────────────────────

#>

#> ── Subsampling ──

#>

#> ! Subsampling automatically activated. To disable it, provide subsample = FALSE

#> ℹ Argument subsample_over was not provided

#> Taking default value for segmentation()

#> Setting subsample_over = 10000

#> ✓ nrow(x) < subsample_over, no subsample needed

#>

#> ── Scaling and final data check ──

#>

#> ✓ Rescaling variables.
#> To desactivate, use scale.variable = FALSE

#> ✓ Data have no repetition of nearly-identical values larger than lmin

#>

#> ── Running Segmentation/Clustering algorithm ───────────────────────────────────

#> ℹ Running Segmentation/Clustering with lmin = 10, Kmax = 15 and ncluster = 2:4

#> → Calculating initial segmentation without clustering

#> ✓ Initial segmentation with no cluster calculated.

#> → Calculating initial segmentation without clustering

#>

#> → Calculating initial segmentation without clustering

#> ── Segmentation/Clustering with ncluster = 2

#> → Calculating initial segmentation without clustering

#> → Calculating initial segmentation without clustering

#> → Segmentation-Clustering for ncluster = 2 and nseg = 2/15

#> → Segmentation-Clustering for ncluster = 2 and nseg = 3/15

#> → Segmentation-Clustering for ncluster = 2 and nseg = 4/15

#> → Segmentation-Clustering for ncluster = 2 and nseg = 5/15

#> → Segmentation-Clustering for ncluster = 2 and nseg = 6/15

#> → Segmentation-Clustering for ncluster = 2 and nseg = 7/15

#> → Segmentation-Clustering for ncluster = 2 and nseg = 8/15

#> → Segmentation-Clustering for ncluster = 2 and nseg = 9/15

#> → Segmentation-Clustering for ncluster = 2 and nseg = 10/15

#> → Segmentation-Clustering for ncluster = 2 and nseg = 11/15

#> → Segmentation-Clustering for ncluster = 2 and nseg = 12/15

#> → Segmentation-Clustering for ncluster = 2 and nseg = 13/15

#> → Segmentation-Clustering for ncluster = 2 and nseg = 14/15

#> → Segmentation-Clustering for ncluster = 2 and nseg = 15/15

#> ✓ Segmentation-Clustering successful for ncluster = 2 and nseg = 2:15

#> → Segmentation-Clustering for ncluster = 2 and nseg = 15/15

#> → Smoothing likelihood for ncluster = 2. This step can be lengthy.

#> ✓ Smoothing successful for ncluster = 2

#> → Smoothing likelihood for ncluster = 2. This step can be lengthy.

#> → Calculating initial segmentation without clustering

#> ✓ Segmentation/Clustering with ncluster = 2 successfully calculated.
#> BIC selected : nseg = 4

#> → Calculating initial segmentation without clustering

#>

#> → Calculating initial segmentation without clustering

#> ── Segmentation/Clustering with ncluster = 3

#> → Calculating initial segmentation without clustering

#> → Calculating initial segmentation without clustering

#> → Segmentation-Clustering for ncluster = 3 and nseg = 3/15

#> → Segmentation-Clustering for ncluster = 3 and nseg = 4/15

#> → Segmentation-Clustering for ncluster = 3 and nseg = 5/15

#> → Segmentation-Clustering for ncluster = 3 and nseg = 6/15

#> → Segmentation-Clustering for ncluster = 3 and nseg = 7/15

#> → Segmentation-Clustering for ncluster = 3 and nseg = 8/15

#> → Segmentation-Clustering for ncluster = 3 and nseg = 9/15

#> → Segmentation-Clustering for ncluster = 3 and nseg = 10/15

#> → Segmentation-Clustering for ncluster = 3 and nseg = 11/15

#> → Segmentation-Clustering for ncluster = 3 and nseg = 12/15

#> → Segmentation-Clustering for ncluster = 3 and nseg = 13/15

#> → Segmentation-Clustering for ncluster = 3 and nseg = 14/15

#> → Segmentation-Clustering for ncluster = 3 and nseg = 15/15

#> ✓ Segmentation-Clustering successful for ncluster = 3 and nseg = 3:15

#> → Segmentation-Clustering for ncluster = 3 and nseg = 15/15

#> → Smoothing likelihood for ncluster = 3. This step can be lengthy.

#> ✓ Smoothing successful for ncluster = 3

#> → Smoothing likelihood for ncluster = 3. This step can be lengthy.

#> → Calculating initial segmentation without clustering

#> ✓ Segmentation/Clustering with ncluster = 3 successfully calculated.
#> BIC selected : nseg = 6

#> → Calculating initial segmentation without clustering

#>

#> → Calculating initial segmentation without clustering

#> ── Segmentation/Clustering with ncluster = 4

#> → Calculating initial segmentation without clustering

#> → Calculating initial segmentation without clustering

#> → Segmentation-Clustering for ncluster = 4 and nseg = 4/15

#> → Segmentation-Clustering for ncluster = 4 and nseg = 5/15

#> → Segmentation-Clustering for ncluster = 4 and nseg = 6/15

#> → Segmentation-Clustering for ncluster = 4 and nseg = 7/15

#> → Segmentation-Clustering for ncluster = 4 and nseg = 8/15

#> → Segmentation-Clustering for ncluster = 4 and nseg = 9/15

#> → Segmentation-Clustering for ncluster = 4 and nseg = 10/15

#> → Segmentation-Clustering for ncluster = 4 and nseg = 11/15

#> → Segmentation-Clustering for ncluster = 4 and nseg = 12/15

#> → Segmentation-Clustering for ncluster = 4 and nseg = 13/15

#> → Segmentation-Clustering for ncluster = 4 and nseg = 14/15

#> → Segmentation-Clustering for ncluster = 4 and nseg = 15/15

#> ✓ Segmentation-Clustering successful for ncluster = 4 and nseg = 4:15

#> → Segmentation-Clustering for ncluster = 4 and nseg = 15/15

#> → Smoothing likelihood for ncluster = 4. This step can be lengthy.

#> ✓ Smoothing successful for ncluster = 4

#> → Smoothing likelihood for ncluster = 4. This step can be lengthy.

#> → Calculating initial segmentation without clustering

#> ✓ Segmentation/Clustering with ncluster = 4 successfully calculated.
#> BIC selected : nseg = 6

#> → Calculating initial segmentation without clustering

#>

#> ── Segmentation/Clustering results ─────────────────────────────────────────────

#> ✓ Best segmentation/clustering estimated with 3 clusters and 6 segments according to BIC

#> → Number of cluster should preferentially be selected according to biological
#> knowledge. Exploring the BIC plot with plot_BIC() can also provide advice to
#> select the number of clusters.

#> → Once number of clusters is selected, the number of segment cab be selected
#> according to BIC.

#> → Results of the segmentation/clustering may further be explored with plot()
#> and segmap()

#> ℹ Argument order missing.

#> Ordering cluster with variable x for segmentation/clustering. To disable, use
#> order = FALSE

#> ! Argument ncluster was not provided. Selecting values with BIC

#> ℹ BIC-selected number of class : ncluster = 3
#> BIC-selected number of segment : nseg = 6

#> ℹ Argument order missing.

#> Ordering cluster with variable x for segmentation/clustering. To disable, use
#> order = FALSE

#> ! Argument ncluster was not provided. Selecting values with BIC

#> ℹ BIC-selected number of class : ncluster = 3
#> BIC-selected number of segment : nseg = 6