Geology Dunham Carbonate Classification Lookup

Screen depositional texture/mud/grain-support evidence under caller Dunham criteria; not identification by grain size alone. Independently declared positive evidence requirements; overlapping/unknown classes retained. Caller independently establishes matching units, evidence, method edition and applicability; output is not compliance, diagnosis, work-safety approval, geological identity or validated hazard prediction.

Description

Dunham carbonate classification relies on independently observed depositional texture and an adopted interpretation.

Dunham carbonate classification relies on independently observed depositional texture and an adopted interpretation.^[1]

A caller-defined positive-evidence rule table preserves missing evidence instead of fabricating a rock class from an incomplete observation. Use this tool to calculate dunham carbonate classification lookup from the supplied measurements and assumptions.

When to use Geology Dunham Carbonate Classification Lookup

Use this tool to calculate dunham carbonate classification lookup from the supplied measurements and assumptions. Establish the measurement units, sampled interval, calibration or model edition and geological assumptions before entering data.

How to use Geology Dunham Carbonate Classification Lookup and understand its results

Establish the measurement units, sampled interval, calibration or model edition and geological assumptions before entering data.
Enter callerDunhamFabricClassIds, callerDunhamFabricRequiredEvidence, observedDunhamFabricEvidence, knownDunhamFabricEvidenceFlags, using the field meanings and rules below, then run the tool.
Read compatibleCallerClasses, fullyWitnessedCallerClasses. Interpret the fields using their units, signs and evidence conventions below.
If input validation fails, correct the reported field and run again. Before applying the result, check reference scope, model assumptions and any missing evidence or placeholder values.

Input field	Meaning	Value type	Requirement
callerDunhamFabricClassIds	Caller dunham fabric class ids	list of string	Required
callerDunhamFabricRequiredEvidence	Caller dunham fabric required evidence	list of list of number	Required
observedDunhamFabricEvidence	Observed dunham fabric evidence	list of number	Required
knownDunhamFabricEvidenceFlags	Known dunham fabric evidence flags; binary 1=known, 0=unknown, in the order described below	list of number	Required

Supply nonempty unique class IDs and a rectangular binary requirement matrix with one row per class and one column per observed feature. Every class must require at least one positive feature. Supply aligned binary observation and known-flag lists. A requirement 0 ignores its column; a requirement 1 permits a class only if the feature is unknown or observed present. Fully witnessed classes require every required feature to be known present. Return all compatible and fully witnessed caller classes in caller order; unknown evidence can leave several candidates, and known absent required evidence excludes a class. The rubric is supplied rather than installed.

compatible={class:each required column is unknown or present}; witnessed={class:each required column is known present}

Use the exact units, boundary rules, ordering and missing-evidence conventions above.

Output field	Meaning	Value type
compatibleCallerClasses	Every supplied class whose required features are unknown or known present	list of string
fullyWitnessedCallerClasses	Every supplied class with all required features known present	list of string

json

{
  "input": {
    "callerDunhamFabricClassIds": [
      "a",
      "b"
    ],
    "callerDunhamFabricRequiredEvidence": [
      [
        1,
        0
      ],
      [
        0,
        1
      ]
    ],
    "observedDunhamFabricEvidence": [
      1,
      0
    ],
    "knownDunhamFabricEvidenceFlags": [
      1,
      0
    ]
  },
  "output": {
    "compatibleCallerClasses": [
      "a",
      "b"
    ],
    "fullyWitnessedCallerClasses": [
      "a"
    ]
  }
}

Limitations and assumptions

A caller-defined positive-evidence rule table preserves missing evidence instead of fabricating a rock class from an incomplete observation. Interpretation depends on the units, sampling scope and exact model described above.

All listed fields require explicit values. Unexpected fields, incorrect types, nonfinite numbers and sparse evidence arrays fail validation; the specific bounds and alignment requirements are stated above. Extremely large inputs or outputs can also be rejected. An input error is distinct from a successful result reporting false, no matches or missing evidence.

Alternative or Complementary methods

Use Geology TAS Classification Lookup for this related task: A total-alkali–silica classification uses composition coordinates and an adopted set of class boundaries.

Use Geology QAPF Classification Lookup when its separate inputs and assumptions fit the question: QAPF classification uses independently determined mineral proportions and a specified classification diagram.

References

Geology Dunham Carbonate Classification Lookup — tool.io

Similar or alternative tools

Geology TAS Classification Lookup
A total-alkali–silica classification uses composition coordinates and an adopted set of class boundaries.
Geology QAPF Classification Lookup
QAPF classification uses independently determined mineral proportions and a specified classification diagram.