45 `grouped_ppp()`

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Note

The examples in Chapter 45 require

library(groupedHyperframe)

The function grouped_ppp() creates a grouped hyper data frame (Chapter 25) with one-and-only-one ppp-hypercolumn, from a data frame.

In Listing 3.1, the argument formula takes form of <marks> ~ <variable.of.interest> | <group>, specifically,

the point-pattern marks, e.g., a numeric mark hladr and a multi-type mark phenotype, on the left-hand-side
the additional predictors and/or endpoints for downstream analysis, e.g., OS, gender and age, before the | separator on the right-hand-side.
the (nested) grouping structure, e.g., image_id nested in patient_id, after the | separator on the right-hand-side.

Listing 45.1 shows the use of the dot symbol . to denote the remaining variables except for those mentioned in the marks and the nested grouping structure.

Listing 45.1: Advanced: function grouped_ppp(formula = <marks> ~ . | <group>)

wrobel_lung |>
   grouped_ppp(formula = hladr + phenotype ~ ., by = ~ patient_id/image_id)
# Hypercolumn(s) dapi created!
# Grouped Hyper Data Frame: ~patient_id
# 
# 3 patient_id
# 
#    gender    OS age    patient_id          image_id      dapi  ppp.
# 1       M   176  84 #03 2-080-378 [36953,13765].im3 (numeric) (ppp)
# 2       M   176  84 #03 2-080-378 [39206,15250].im3 (numeric) (ppp)
# 3       M   176  84 #03 2-080-378 [40242,17359].im3 (numeric) (ppp)
# 4       M   176  84 #03 2-080-378 [40863,16444].im3 (numeric) (ppp)
# 5       F 3488+  85 #01 0-889-121 [40864,18015].im3 (numeric) (ppp)
# ✂️ --- output truncated --- ✂️