helix · Calculate Shannon entropy: H

Read the equation

This relation defines Shannon entropy: H in the source section “helix · Calculate Shannon entropy: H”. Uses logarithmic scaling; its base and the positivity of its argument matter. Its interpretation depends on the source’s stated variables and conditions; this record does not assign an unprovided physical or cognitive meaning to them.

Terms & definitions

The recovered passage does not supply a separate symbol table. Read the source context for the notation used in this version; familiar letters may carry different meanings in other builds.

How it works

1. Read Shannon entropy: H as the quantity being defined or updated by this relation.

2. Uses logarithmic scaling; its base and the positivity of its argument matter.

3. Use this version’s variable definitions and update order. The same symbol may be assigned a different meaning in another build.

Assumptions & limits

• This source expression was recovered from the pinned code revision. Its presence does not establish that the associated program was built, run, or scientifically validated.

Original context

    for (size_t i = 0; i < size; ++i) {
        size_t bin = static_cast<size_t>(((data[i] - min_val) / range) * (NUM_BINS - 1));
        bin = std::min(bin, NUM_BINS - 1);
        histogram[bin]++;
    }

    // Calculate Shannon entropy: H = -Σ p_i * log2(p_i)
    double entropy = 0.0;
    for (size_t i = 0; i < NUM_BINS; ++i) {
        if (histogram[i] > 0) {
            double p_i = static_cast<double>(histogram[i]) / static_cast<double>(size);
            entropy -= p_i * std::log2(p_i);
        }
    }

    // Normalize to [0,1]
    return entropy / std::log2(static_cast<double>(NUM_BINS));

Calculate Shannon entropy: H = -Σ p_i * log2(p_i)

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