Numeric Functions

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Summary

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README.md

Public entries: Python and R. Passing coverage requires an installed inventory.

Goal: apply CEIL, FLOOR, TRUNC, EXP, and MOD to carried values, and choose the largest, the smallest, and the first present of the carried whole numbers.

Input: subject-level records carrying AVAL as a decimal number and BVAL and CVAL as whole numbers, each copied to the output unchanged (a blank stays blank).

Variables:

CEILVAL holds the smallest whole number at or above AVAL; blank when AVAL is blank.
FLOORVAL holds the largest whole number at or below AVAL; blank when AVAL is blank.
TRUNCVAL holds AVAL with its fraction cut away toward zero, so a negative value with a fraction moves up, not down; blank when AVAL is blank.
EXPVAL holds the constant e raised to AVAL; blank when AVAL is blank.
MODVAL holds the remainder of BVAL divided by three, with the sign of BVAL; blank when BVAL is blank.
GREATESTVAL holds the largest among BVAL, CVAL, and zero, skipping blanks; the zero means it is never blank.
LEASTVAL holds the smallest among BVAL, CVAL, and zero, skipping blanks; the zero means it is never blank.
COALESCEVAL holds CVAL when present and otherwise BVAL; blank when both are blank.

Note: a blank input gives a blank result, except that the largest-or-smallest choice skips blanks and the first-present choice moves to the next value.

YAML specification

1 spec file

spec.yaml

Edit103 lines

1yamaa: "1.0"2type: spec3model: ADaM4domain: ADSL5keys: [STUDYID, USUBJID]6input:7  SOURCE: input/adsl.csv89output:10  path: adsl.csv11  columns: [STUDYID, USUBJID, AVAL, BVAL, CVAL, CEILVAL, FLOORVAL,12    TRUNCVAL, EXPVAL, MODVAL, GREATESTVAL, LEASTVAL, COALESCEVAL]1314columns:15  - name: STUDYID16    type: str17    label: Study Identifier18    derivation: SOURCE.STUDYID1920  - name: USUBJID21    type: str22    label: Unique Subject Identifier23    derivation: SOURCE.USUBJID2425  - name: AVAL26    type: float27    label: Analysis Value28    derivation: SOURCE.AVAL2930  - name: BVAL31    type: int32    label: Secondary Analysis Value33    derivation: SOURCE.BVAL3435  - name: CVAL36    type: int37    label: Tertiary Analysis Value38    derivation: SOURCE.CVAL3940  # Zero joins the largest and smallest choices below as a column, because41  # their sources are variables rather than literals. It stays out of the42  # output.43  - name: ZERO44    type: int45    label: Zero46    derivation: 04748  - name: CEILVAL49    type: int50    label: Ceiling of Analysis Value51    derivation: "CEIL(AVAL)"5253  - name: FLOORVAL54    type: int55    label: Floor of Analysis Value56    derivation: "FLOOR(AVAL)"5758  # Toward zero: -2.7 gives -2, where FLOOR gives -3.59  - name: TRUNCVAL60    type: int61    label: Truncation of Analysis Value62    derivation: "TRUNC(AVAL)"6364  - name: EXPVAL65    type: float66    label: Exponential of Analysis Value67    derivation: "EXP(AVAL)"6869  # The remainder takes the sign of BVAL, so -7 gives -1 rather than 2.70  - name: MODVAL71    type: int72    label: Remainder of Secondary Value Divided by Three73    derivation: "MOD(BVAL, 3)"7475  # Greatest and least skip missing sources, so with ZERO among them76  # neither result is ever missing.77  - name: GREATESTVAL78    type: int79    label: Largest of Secondary, Tertiary, and Zero80    derivation:81      greatest:82        sources: [BVAL, CVAL, ZERO]8384  - name: LEASTVAL85    type: int86    label: Smallest of Secondary, Tertiary, and Zero87    derivation:88      least:89        sources: [BVAL, CVAL, ZERO]9091  # First_available returns the first present source, or missing when92  # every source is missing.93  - name: COALESCEVAL94    type: int95    label: First Present Value Among Tertiary and Secondary96    derivation:97      first_available:98        sources: [CVAL, BVAL]99100verifications:101  - row_count:102      min: 5103      max: 5

Inputs

Under review1 source file

input/adsl.csv

Edit5 rows

input/adsl.csv
STUDYID	AVAL	BVAL	CVAL
CATH	2.3	7	5
CATH	-2.7	-7	—
CATH	2.0	10	3
CATH	—	5	8
CATH	0.5	—	—

Expected output

Under review5 expected rows

expected/adsl.csv

Edit5 rows

expected/adsl.csv
STUDYID	AVAL	BVAL	CVAL	CEILVAL	FLOORVAL	TRUNCVAL	EXPVAL	MODVAL	GREATESTVAL	LEASTVAL	COALESCEVAL
CATH	2.3	7	5	3	2	2	9.974182454814718	1	7	0	5
CATH	-2.7	-7	—	-2	-3	-2	0.06720551273974976	-1	0	-7	-7
CATH	2	10	3	2	2	2	7.38905609893065	1	10	0	3
CATH	—	5	8	—	—	—	—	2	8	0	8
CATH	0.5	—	—	1	0	0	1.6487212707001282	—	0	0	—

Shaded columns are derived— = missing value

Human review and assessment

Dataset Name	Variable Name	Variable Label	Type	Computational Method	Origin
ADSL	STUDYID	Study Identifier	character	Copy value from SOURCE.STUDYID.	Predecessor
ADSL	USUBJID	Unique Subject Identifier	character	Copy value from SOURCE.USUBJID.	Predecessor
ADSL	AVAL	Analysis Value	numeric	Copy value from SOURCE.AVAL.	Predecessor
ADSL	BVAL	Secondary Analysis Value	numeric	Copy value from SOURCE.BVAL.	Predecessor
ADSL	CVAL	Tertiary Analysis Value	numeric	Copy value from SOURCE.CVAL.	Predecessor
ADSL	CEILVAL	Ceiling of Analysis Value	numeric	Compute CEIL(AVAL).	Derived
ADSL	FLOORVAL	Floor of Analysis Value	numeric	Compute FLOOR(AVAL).	Derived
ADSL	TRUNCVAL	Truncation of Analysis Value	numeric	Compute TRUNC(AVAL).	Derived
ADSL	EXPVAL	Exponential of Analysis Value	numeric	Compute EXP(AVAL).	Derived
ADSL	MODVAL	Remainder of Secondary Value Divided by Three	numeric	Compute MOD(BVAL, 3).	Derived
ADSL	GREATESTVAL	Largest of Secondary, Tertiary, and Zero	numeric	Greatest of BVAL, CVAL and ZERO.	Derived
ADSL	LEASTVAL	Smallest of Secondary, Tertiary, and Zero	numeric	Least of BVAL, CVAL and ZERO.	Derived
ADSL	COALESCEVAL	First Present Value Among Tertiary and Secondary	numeric	First non-missing of CVAL and BVAL.	Derived

Version	Date	Author	Description
1.7	2026-10-20	yamaa docs build	Read a specification in the 1.0 surface as its 0.5 counterpart; state that missing values stay missing where a mapping declares no missing handler, and leave out a declared missing answer that restates a handler's default
1.6	2026-10-17	yamaa docs build	Describe collected date parts written as ISO 8601 date text and times of day counted in seconds since midnight
1.5	2026-10-17	yamaa docs build	Name collected precision in words instead of letter codes; state imputation fallbacks, minimum source precision, bounds ignored outside the collected period, and invalid text with no handler as an error; describe date and datetime shifts, imputation flag codes, and partial text giving no date part
1.4	2026-10-15	yamaa docs build	State datetime precision codes through the hour and minute, and complete only the time parts a collected datetime lacks
1.3	2026-09-29	yamaa docs build	Show study codelist names, external dictionaries, and ISO 8601 formats in variable rows; list the document's codelist values and metadata
1.2	2026-09-29	yamaa docs build	Classify ADaM copies from a declared input as Predecessor and recodes as Derived, and SDTM recodes of locally derived columns as Derived
1.1	2026-09-29	yamaa docs build	Resolve lookups into the donor record they select, and give every derivation shape a plain-language rule instead of its raw YAML
1.0		yamaa docs build	Initial generation from spec.yaml

R

Edit3 lines

1library(yamaa)23yamaa_spec("spec.yaml")$run()$output

Python

Edit3 lines

1import yamaa23yamaa.spec("spec.yaml").run().output

input/adsl.csv

expected/adsl.csv

Your review

Mapping spec

yamaa code

R

Python