Unify the two matrix types

diskann-benchmark/src/multi_vector/driver.rs

@@ -14,7 +14,7 @@ use diskann_benchmark_runner::{
     },
     Checker, Input,
 };
-use diskann_quantization::multi_vector::{Mat, MatRef, MaxSimKernel, Overflow, Standard};
+use diskann_quantization::multi_vector::{Mat, MatRef, MaxSimKernel, Overflow, RowMajor};
 use rand::{
     distr::{Distribution, StandardUniform},
     rngs::StdRng,
@@ -68,8 +68,8 @@ impl Input for MultiVectorTolerance {
 
 /// Random query / doc fixture for a single benchmark run.
 pub(super) struct Data<T: Copy> {
-    pub(super) queries: Mat<Standard<T>>,
-    pub(super) docs: Mat<Standard<T>>,
+    pub(super) queries: Mat<RowMajor<T>>,
+    pub(super) docs: Mat<RowMajor<T>>,
 }
 
 impl<T: Copy> Data<T>
@@ -79,11 +79,11 @@ where
     pub(super) fn new(run: &Run) -> Result<Self, Overflow> {
         let mut rng = StdRng::seed_from_u64(0x12345);
         let queries = Mat::from_fn(
-            Standard::new(run.num_query_vectors.get(), run.dim.get())?,
+            RowMajor::new(run.num_query_vectors.get(), run.dim.get())?,
             || StandardUniform.sample(&mut rng),
         );
         let docs = Mat::from_fn(
-            Standard::new(run.num_doc_vectors.get(), run.dim.get())?,
+            RowMajor::new(run.num_doc_vectors.get(), run.dim.get())?,
             || StandardUniform.sample(&mut rng),
         );
         Ok(Self { queries, docs })
@@ -96,7 +96,7 @@ where
 
 pub(super) fn run_with_kernel<T: Copy>(
     run: &Run,
-    doc: MatRef<'_, Standard<T>>,
+    doc: MatRef<'_, RowMajor<T>>,
     kernel: &dyn MaxSimKernel<T>,
 ) -> RunResult {
     let mut scores = vec![0.0f32; run.num_query_vectors.get()];

diskann-disk/src/search/pq/quantizer_preprocess.rs

@@ -22,7 +22,7 @@ pub fn quantizer_preprocess(
 ) -> ANNResult<()> {
     let table = pq_data.pq_table();
     let expected_len = table.ncenters() * table.nchunks();
-    let dst = diskann_utils::views::MutMatrixView::try_from(
+    let dst = diskann_utils::views::MatrixViewMut::try_from(
         &mut (*pq_scratch.aligned_pqtable_dist_scratch)[..expected_len],
         table.nchunks(),
         table.ncenters(),

diskann-disk/src/storage/quant/compressor.rs

@@ -4,7 +4,7 @@
  */
 
 use diskann::{utils::VectorRepr, ANNResult};
-use diskann_utils::views::{MatrixView, MutMatrixView};
+use diskann_utils::views::{MatrixView, MatrixViewMut};
 
 /// [`QuantCompressor`] defines the interface for quantizer with [`QuantDataGenerator`]
 ///
@@ -30,6 +30,6 @@ where
     type CompressorContext;
 
     fn new(context: &Self::CompressorContext) -> ANNResult<Self>;
-    fn compress(&self, vector: MatrixView<f32>, output: MutMatrixView<u8>) -> ANNResult<()>;
+    fn compress(&self, vector: MatrixView<f32>, output: MatrixViewMut<u8>) -> ANNResult<()>;
     fn compressed_bytes(&self) -> usize;
 }

diskann-disk/src/storage/quant/generator.rs

@@ -147,7 +147,7 @@ where
 
             // Wrap the data in `MatrixViews` so we do not need to manually construct view
             // in the compression loop.
-            let mut compressed_block = views::MutMatrixView::try_from(
+            let mut compressed_block = views::MatrixViewMut::try_from(
                 block_compressed_base,
                 cur_block_size,
                 compressed_size,
@@ -221,7 +221,7 @@ mod generator_tests {
         fn compress(
             &self,
             _vector: views::MatrixView<f32>,
-            mut output: views::MutMatrixView<u8>,
+            mut output: views::MatrixViewMut<u8>,
         ) -> ANNResult<()> {
             output
                 .row_iter_mut()

diskann-disk/src/storage/quant/pq/pq_generation.rs

@@ -16,7 +16,7 @@ use diskann_providers::{
     utils::{BridgeErr, RayonThreadPoolRef},
 };
 use diskann_quantization::{product::TransposedTable, CompressInto};
-use diskann_utils::views::MatrixBase;
+use diskann_utils::views::{MatrixView, MatrixViewMut};
 use diskann_vector::distance::Metric;
 use tracing::info;
 
@@ -119,7 +119,7 @@ where
                 context.storage_provider,
             )?;
 
-        let mut full_pivot_data_mat = diskann_utils::views::MutMatrixView::try_from(
+        let mut full_pivot_data_mat = diskann_utils::views::MatrixViewMut::try_from(
             full_pivot_data.as_mut_slice(),
             context.num_centers,
             full_dim,
@@ -146,8 +146,8 @@ where
 
     fn compress(
         &self,
-        vector: MatrixBase<&[f32]>,
-        output: MatrixBase<&mut [u8]>,
+        vector: MatrixView<'_, f32>,
+        output: MatrixViewMut<'_, u8>,
     ) -> Result<(), diskann::ANNError> {
         self.table
             .compress_into(vector, output)
@@ -175,7 +175,7 @@ mod pq_generation_tests {
     use diskann_utils::{
         io::{read_bin, write_bin},
         test_data_root,
-        views::{MatrixView, MutMatrixView},
+        views::{MatrixView, MatrixViewMut},
     };
     use diskann_vector::distance::Metric;
     use rstest::rstest;
@@ -329,7 +329,7 @@ mod pq_generation_tests {
         let mut compressed_mat = vec![0_u8; num_chunks * npts];
         let result = compressor.unwrap().compress(
             data_matrix.as_view(),
-            MutMatrixView::try_from(&mut compressed_mat, npts, num_chunks).unwrap(),
+            MatrixViewMut::try_from(&mut compressed_mat, npts, num_chunks).unwrap(),
         );
         assert!(result.is_ok());
 

diskann-garnet/src/provider.rs

@@ -499,7 +499,7 @@ impl<T: VectorRepr> GarnetProvider<T> {
             Ok(v) => v,
             Err(_) => return false,
         };
-        let view = match MatrixView::try_from(&*converted, view.nrows(), view.ncols()) {
+        let view = match MatrixView::try_from(&converted, view.nrows(), view.ncols()) {
             Ok(v) => v,
             Err(_) => return false,
         };

diskann-providers/src/model/graph/provider/determinant_diversity.rs

@@ -53,7 +53,7 @@
 
 use std::fmt;
 
-use diskann_utils::views::MutMatrixView;
+use diskann_utils::views::MatrixViewMut;
 use diskann_vector::{MathematicalValue, PureDistanceFunction, distance::InnerProduct};
 
 /// Parameters for Determinant-Diversity post-processor with validation.
@@ -199,7 +199,7 @@ struct DistanceRange {
 /// An empty candidate set, a `k` of zero, or zero-dimensional vectors yield an
 /// empty result.
 pub fn determinant_diversity(
-    candidates: MutMatrixView<'_, f32>,
+    candidates: MatrixViewMut<'_, f32>,
     distances: &[f32],
     query: &[f32],
     k: usize,
@@ -338,7 +338,7 @@ pub fn determinant_diversity(
 /// O(n * k * dim) -- for each of k pivots we touch all n residual rows of
 /// length `dim`. Memory is O(n * dim) for the contiguous residual matrix.
 fn greedy_orthogonal_select(
-    mut candidates: MutMatrixView<'_, f32>,
+    mut candidates: MatrixViewMut<'_, f32>,
     distances: &[f32],
     k: usize,
     power: f32,

diskann-providers/src/model/pq/fixed_chunk_pq_table.rs

@@ -9,7 +9,7 @@ use diskann_quantization::{
     product::{self, BasicTable},
     views::ChunkOffsetsBase,
 };
-use diskann_utils::views::{self, MatrixBase, MatrixView};
+use diskann_utils::views::{self, Matrix, MatrixView};
 use diskann_vector::{PureDistanceFunction, distance};
 use diskann_wide::ARCH;
 
@@ -133,7 +133,7 @@ impl FixedChunkPQTable {
     pub fn new(dim: usize, pq_table: Box<[f32]>, chunk_offsets: Box<[usize]>) -> ANNResult<Self> {
         let len = pq_table.len();
         let table = BasicTable::new(
-            MatrixBase::try_from(pq_table, len / dim, dim).bridge_err()?,
+            Matrix::try_from(pq_table, len / dim, dim).bridge_err()?,
             ChunkOffsetsBase::new(chunk_offsets).bridge_err()?,
         )
         .map_err(|err| ANNError::log_pq_error(diskann_quantization::error::format(&err)))?;

diskann-providers/src/model/pq/pq_construction.rs

@@ -25,7 +25,7 @@ use diskann_quantization::{
 };
 use diskann_utils::{
     io::Metadata,
-    views::{MatrixView, MutMatrixView},
+    views::{MatrixView, MatrixViewMut},
 };
 use rand::{Rng, distr::Distribution};
 use rayon::prelude::*;
@@ -293,7 +293,7 @@ pub fn move_train_data_by_centroid(
 /// # Panics
 ///
 /// Panics if `y.len() != x.ncols()`.
-pub fn accum_row_inplace<T>(mut x: MutMatrixView<T>, y: &[T])
+pub fn accum_row_inplace<T>(mut x: MatrixViewMut<T>, y: &[T])
 where
     T: Copy + std::ops::AddAssign,
 {
@@ -362,7 +362,7 @@ where
     // Instead of subtracting the center from each data set component, we instead
     // add it to each center.
     let mut full_pivot_data_mat =
-        MutMatrixView::try_from(full_pivot_data.as_mut_slice(), num_centers, full_dim)
+        MatrixViewMut::try_from(full_pivot_data.as_mut_slice(), num_centers, full_dim)
             .bridge_err()?;
     accum_row_inplace(full_pivot_data_mat.as_mut_view(), centroid.as_slice());
 
@@ -430,7 +430,7 @@ where
         // Wrap the data in `MatrixViews` so we do not need to manually construct view
         // in the compression loop.
         let mut compressed_block =
-            MutMatrixView::try_from(&mut block_compressed_base, cur_block_size, num_pq_chunks)
+            MatrixViewMut::try_from(&mut block_compressed_base, cur_block_size, num_pq_chunks)
                 .bridge_err()?;
         let base_block = MatrixView::try_from(block_data, cur_block_size, full_dim).bridge_err()?;
 

diskann-providers/src/model/pq/views.rs

@@ -106,7 +106,7 @@ mod tests {
         let data = vec![0; ncols * nrows];
 
         test_error(|| {
-            views::MatrixView::try_from(&*data, nrows, ncols + 1)
+            views::MatrixView::try_from(&data, nrows, ncols + 1)
                 .bridge_err()
                 .unwrap_err()
         });

diskann-providers/src/storage/pq_storage.rs

@@ -523,7 +523,7 @@ mod pq_storage_tests {
     #[test]
     fn write_read_roundtrip_with_legacy_centroid() {
         use crate::model::pq::accum_row_inplace;
-        use diskann_utils::views::MutMatrixView;
+        use diskann_utils::views::MatrixViewMut;
 
         let storage_provider = VirtualStorageProvider::new_memory();
         let pivot_path = "/roundtrip_legacy_centroid_pivots.bin";
@@ -563,7 +563,7 @@ mod pq_storage_tests {
 
         // Fold the centroid into the pivots — this is what production callers do.
         let mut pivot_mat =
-            MutMatrixView::try_from(loaded_pivots.as_mut_slice(), num_centers, dim).unwrap();
+            MatrixViewMut::try_from(loaded_pivots.as_mut_slice(), num_centers, dim).unwrap();
         accum_row_inplace(pivot_mat.as_mut_view(), &loaded_centroid);
 
         // Each pivot row should have the centroid added element-wise.

diskann-quantization/src/algorithms/kmeans/lloyds.rs

@@ -9,7 +9,7 @@ use super::common::square_norm;
 use crate::multi_vector::{BlockTransposed, BlockTransposedRef};
 use diskann_utils::{
     strided::StridedView,
-    views::{Matrix, MatrixView, MutMatrixView},
+    views::{Matrix, MatrixView, MatrixViewMut},
 };
 
 ////////////////////////////////
@@ -342,7 +342,7 @@ fn update((d0, i0): (f32s, u32s), (d1, i1): (f32s, u32s)) -> (f32s, u32s) {
 // Update Step //
 /////////////////
 
-fn update_centroids(mut centers: MutMatrixView<'_, f32>, data: StridedView<'_, f32>, map: &[u32]) {
+fn update_centroids(mut centers: MatrixViewMut<'_, f32>, data: StridedView<'_, f32>, map: &[u32]) {
     let mut sums = Matrix::<f64>::new(0.0, centers.nrows(), centers.ncols());
     let mut counts: Vec<u32> = vec![0; centers.nrows()];
     data.row_iter().zip(map.iter()).for_each(|(row, &center)| {
@@ -373,7 +373,7 @@ pub(crate) fn lloyds_inner(
     data: StridedView<'_, f32>,
     square_norms: &[f32],
     transpose: BlockTransposedRef<'_, f32, 16>,
-    mut centers: MutMatrixView<'_, f32>,
+    mut centers: MatrixViewMut<'_, f32>,
     max_reps: usize,
 ) -> (Vec<u32>, f32) {
     // Check our requirements.
@@ -440,7 +440,7 @@ pub(crate) fn lloyds_inner(
 /// dimension.
 pub fn lloyds(
     data: MatrixView<'_, f32>,
-    centers: MutMatrixView<'_, f32>,
+    centers: MatrixViewMut<'_, f32>,
     max_reps: usize,
 ) -> (Vec<u32>, f32) {
     assert_eq!(

diskann-quantization/src/algorithms/kmeans/plusplus.rs

@@ -7,7 +7,7 @@ use std::{collections::HashSet, fmt};
 
 use diskann_utils::{
     strided::StridedView,
-    views::{MatrixView, MutMatrixView},
+    views::{MatrixView, MatrixViewMut},
 };
 use diskann_wide::{SIMDMulAdd, SIMDPartialOrd, SIMDSelect, SIMDVector};
 use rand::{
@@ -379,7 +379,7 @@ impl KMeansPlusPlusError {
 }
 
 pub(crate) fn kmeans_plusplus_into_inner<const N: usize>(
-    mut points: MutMatrixView<'_, f32>,
+    mut points: MatrixViewMut<'_, f32>,
     data: StridedView<'_, f32>,
     transpose: BlockTransposedRef<'_, f32, N>,
     norms: &[f32],
@@ -498,7 +498,7 @@ where
 }
 
 pub fn kmeans_plusplus_into(
-    centers: MutMatrixView<'_, f32>,
+    centers: MatrixViewMut<'_, f32>,
     data: MatrixView<'_, f32>,
     rng: &mut dyn RngCore,
 ) -> Result<(), KMeansPlusPlusError> {
@@ -581,7 +581,7 @@ mod tests {
     /// ...
     /// K-1, K,   K+1, K+3 ... N+K-2
     /// ```
-    fn set_default_values(mut x: MutMatrixView<'_, f32>) {
+    fn set_default_values(mut x: MatrixViewMut<'_, f32>) {
         for (i, row) in x.row_iter_mut().enumerate() {
             for (j, r) in row.iter_mut().enumerate() {
                 *r = (i + j) as f32;

diskann-quantization/src/lib.rs

@@ -216,7 +216,6 @@ mod tests {
         t.pass("tests/compile-fail/bootstrap/bootstrap.rs");
         t.compile_fail("tests/compile-fail/*.rs");
         t.compile_fail("tests/compile-fail/error/*.rs");
-        t.compile_fail("tests/compile-fail/multi/*.rs");
     }
 }
 

diskann-quantization/src/minmax/multi/max_sim.rs

@@ -144,7 +144,7 @@ mod tests {
     use crate::algorithms::transforms::NullTransform;
     use crate::bits::{Representation, Unsigned};
     use crate::minmax::{Data, MinMaxQuantizer};
-    use crate::multi_vector::{Defaulted, Mat, Standard};
+    use crate::multi_vector::{Mat, RowMajor};
     use crate::num::Positive;
     use diskann_utils::ReborrowMut;
     use std::num::NonZeroUsize;
@@ -202,9 +202,9 @@ mod tests {
     where
         Unsigned: Representation<NBITS>,
     {
-        let input_mat = MatRef::new(Standard::<f32>::new(n, dim).unwrap(), input).unwrap();
+        let input_mat = MatRef::from_repr(RowMajor::<f32>::new(n, dim).unwrap(), input).unwrap();
         let mut output: Mat<MinMaxMeta<NBITS>> =
-            Mat::new(MinMaxMeta::new(n, dim), Defaulted).unwrap();
+            Mat::from_default(MinMaxMeta::new(n, dim)).unwrap();
         quantizer
             .compress_into(input_mat, output.reborrow_mut())
             .unwrap();
@@ -301,10 +301,10 @@ mod tests {
         let query_data = vec![0u8; 2 * row_bytes];
         let doc_data = vec![0u8; 3 * row_bytes];
 
-        let query: QueryMatRef<_> = MatRef::new(MinMaxMeta::<8>::new(2, dim), &query_data)
+        let query: QueryMatRef<_> = MatRef::from_repr(MinMaxMeta::<8>::new(2, dim), &query_data)
             .unwrap()
             .into();
-        let doc = MatRef::new(MinMaxMeta::<8>::new(3, dim), &doc_data).unwrap();
+        let doc = MatRef::from_repr(MinMaxMeta::<8>::new(3, dim), &doc_data).unwrap();
 
         let mut scores = vec![0.0f32; 5]; // Wrong size
         MaxSim::new(&mut scores).evaluate(query, doc);