Description
Return exp(entropy × ln(base)) for effectiveAlphabetSize.
Entropy summarizes uncertainty under a specified probability model and logarithm convention. Support indicators, one-symbol terms, and exponentiated entropies are components with different meanings.
Return exp(entropy × ln(base)) for effectiveAlphabetSize.
When to use this tool
Use Information: Entropy Effective Alphabet Size when you need one explicitly scoped entropy or support calculation.
How to use the tool and how it works
- Enter entropy, base. Use the units and conventions below.
- Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
- Read result. Expand result to inspect the returned fields.
Require nonnegative entropy and base > 1. Return exp(entropy × ln(base)) for effectiveAlphabetSize.1
| Input field | Meaning and units | Accepted input |
|---|---|---|
| entropy | Entropy | Required. Finite number. |
| base | Numeric base or source quantity interpreted under the specific calculation above. | Required. Finite number. |
| Output field | Interpretation | Returned shape |
|---|---|---|
| result | Result | Required. Object. |
| result.effectiveAlphabetSize | Effective Alphabet Size | Calculated result member: number. |
{
"input": {
"entropy": 3,
"base": 2
},
"output": {
"result": {
"effectiveAlphabetSize": 8
}
}
}Limitations and assumptions
- The exponentiated Shannon-style entropy is an effective count and can be fractional; actual support size and distribution validity are not supplied.
- Outputs are nested inside result. Inputs must satisfy both the field types and the cross-field conditions above. Invalid input causes an error; a successful false flag or documented placeholder is a different result.
- Numeric calculations use binary floating point unless exact decimal-integer arithmetic is explicitly stated. No hidden measurement tolerance or decimal rounding is added; nonfinite or out-of-contract results are rejected. Numeric signed-zero results are exported as zero.
Alternative or Complementary methods
Validate and align complete probability distributions before aggregating terms or interpreting an uncertainty estimate.
References
Similar or alternative tools
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