1use super::{
  2    super::{RpoDigest, Vec, ZERO},
  3    Felt, MmrError, MmrProof, Rpo256, Word,
  4};
  5
  6// MMR PEAKS
  7// ================================================================================================
  8
  9#[derive(Debug, Clone, PartialEq)]
 10#[cfg_attr(feature = "serde", derive(serde::Deserialize, serde::Serialize))]
 11pub struct MmrPeaks {
 12    /// The number of leaves is used to differentiate MMRs that have the same number of peaks. This
 13    /// happens because the number of peaks goes up-and-down as the structure is used causing
 14    /// existing trees to be merged and new ones to be created. As an example, every time the MMR
 15    /// has a power-of-two number of leaves there is a single peak.
 16    ///
 17    /// Every tree in the MMR forest has a distinct power-of-two size, this means only the right-
 18    /// most tree can have an odd number of elements (e.g. `1`). Additionally this means that the
 19    /// bits in `num_leaves` conveniently encode the size of each individual tree.
 20    ///
 21    /// Examples:
 22    ///
 23    ///    - With 5 leaves, the binary `0b101`. The number of set bits is equal the number
 24    ///      of peaks, in this case there are 2 peaks. The 0-indexed least-significant position of
 25    ///      the bit determines the number of elements of a tree, so the rightmost tree has `2**0`
 26    ///      elements and the left most has `2**2`.
 27    ///    - With 12 leaves, the binary is `0b1100`, this case also has 2 peaks, the
 28    ///      leftmost tree has `2**3=8` elements, and the right most has `2**2=4` elements.
 29    num_leaves: usize,
 30
 31    /// All the peaks of every tree in the MMR forest. The peaks are always ordered by number of
 32    /// leaves, starting from the peak with most children, to the one with least.
 33    ///
 34    /// Invariant: The length of `peaks` must be equal to the number of true bits in `num_leaves`.
 35    peaks: Vec<RpoDigest>,
 36}
 37
 38impl MmrPeaks {
 39    pub fn new(num_leaves: usize, peaks: Vec<RpoDigest>) -> Result<Self, MmrError> {
 40        if num_leaves.count_ones() as usize != peaks.len() {
 41            return Err(MmrError::InvalidPeaks);
 42        }
 43
 44        Ok(Self { num_leaves, peaks })
 45    }
 46
 47    // ACCESSORS
 48    // --------------------------------------------------------------------------------------------
 49
 50    /// Returns a count of the MMR's leaves.
 51    pub fn num_leaves(&self) -> usize {
 52        self.num_leaves
 53    }
 54
 55    /// Returns the current peaks of the MMR.
 56    pub fn peaks(&self) -> &[RpoDigest] {
 57        &self.peaks
 58    }
 59
 60    /// Returns the current num_leaves and peaks of the MMR.
 61    pub fn into_parts(self) -> (usize, Vec<RpoDigest>) {
 62        (self.num_leaves, self.peaks)
 63    }
 64
 65    /// Hashes the peaks.
 66    ///
 67    /// The procedure will:
 68    /// - Flatten and pad the peaks to a vector of Felts.
 69    /// - Hash the vector of Felts.
 70    pub fn hash_peaks(&self) -> RpoDigest {
 71        Rpo256::hash_elements(&self.flatten_and_pad_peaks())
 72    }
 73
 74    pub fn verify(&self, value: RpoDigest, opening: MmrProof) -> bool {
 75        let root = &self.peaks[opening.peak_index()];
 76        opening.merkle_path.verify(opening.relative_pos() as u64, value, root)
 77    }
 78
 79    /// Flattens and pads the peaks to make hashing inside of the Miden VM easier.
 80    ///
 81    /// The procedure will:
 82    /// - Flatten the vector of Words into a vector of Felts.
 83    /// - Pad the peaks with ZERO to an even number of words, this removes the need to handle RPO
 84    ///   padding.
 85    /// - Pad the peaks to a minimum length of 16 words, which reduces the constant cost of
 86    ///   hashing.
 87    pub fn flatten_and_pad_peaks(&self) -> Vec<Felt> {
 88        let num_peaks = self.peaks.len();
 89
 90        // To achieve the padding rules above we calculate the length of the final vector.
 91        // This is calculated as the number of field elements. Each peak is 4 field elements.
 92        // The length is calculated as follows:
 93        // - If there are less than 16 peaks, the data is padded to 16 peaks and as such requires
 94        //   64 field elements.
 95        // - If there are more than 16 peaks and the number of peaks is odd, the data is padded to
 96        //   an even number of peaks and as such requires `(num_peaks + 1) * 4` field elements.
 97        // - If there are more than 16 peaks and the number of peaks is even, the data is not padded
 98        //   and as such requires `num_peaks * 4` field elements.
 99        let len = if num_peaks < 16 {
100            64
101        } else if num_peaks % 2 == 1 {
102            (num_peaks + 1) * 4
103        } else {
104            num_peaks * 4
105        };
106
107        let mut elements = Vec::with_capacity(len);
108        elements.extend_from_slice(
109            &self
110                .peaks
111                .as_slice()
112                .iter()
113                .map(|digest| digest.into())
114                .collect::<Vec<Word>>()
115                .concat(),
116        );
117        elements.resize(len, ZERO);
118        elements
119    }
120}