Merge pull request #1019 from w1th0utnam3/sparse_serde

Implement Serde Serialize/Deserialize for nalgebra-sparse types

.github/workflows/nalgebra-ci-build.yml

@@ -38,8 +38,12 @@ jobs:
       run: cargo build --features serde-serialize
     - name: Build nalgebra-lapack
       run: cd nalgebra-lapack; cargo build;
-    - name: Build nalgebra-sparse
+    - name: Build nalgebra-sparse --no-default-features
+      run: cd nalgebra-sparse; cargo build --no-default-features;
+    - name: Build nalgebra-sparse (default features)
       run: cd nalgebra-sparse; cargo build;
+    - name: Build nalgebra-sparse --all-features
+      run: cd nalgebra-sparse; cargo build --all-features;
   # Run this on it’s own job because it alone takes a lot of time.
   # So it’s best to let it run in parallel to the other jobs.
   build-nalgebra-all-features:
@@ -71,10 +75,10 @@ jobs:
       - name: test nalgebra-sparse
         # Manifest-path is necessary because cargo otherwise won't correctly forward features
         # We increase number of proptest cases to hopefully catch more potential bugs
-        run: PROPTEST_CASES=10000 cargo test --manifest-path=nalgebra-sparse/Cargo.toml --features compare,proptest-support,io
+        run: PROPTEST_CASES=10000 cargo test --manifest-path=nalgebra-sparse/Cargo.toml --features compare,proptest-support,io,serde-serialize
       - name: test nalgebra-sparse (slow tests)
         # Unfortunately, the "slow-tests" take so much time that we need to run them with --release
-        run: PROPTEST_CASES=10000 cargo test --release --manifest-path=nalgebra-sparse/Cargo.toml --features compare,proptest-support,io,slow-tests slow
+        run: PROPTEST_CASES=10000 cargo test --release --manifest-path=nalgebra-sparse/Cargo.toml --features compare,proptest-support,io,serde-serialize,slow-tests slow
   test-nalgebra-macros:
     runs-on: ubuntu-latest
     steps:

nalgebra-sparse/Cargo.toml

@@ -15,6 +15,7 @@ license = "Apache-2.0"
 [features]
 proptest-support = ["proptest", "nalgebra/proptest-support"]
 compare = [ "matrixcompare-core" ]
+serde-serialize = [ "serde/std" ]
 
 # Enable matrix market I/O
 io      = [ "pest", "pest_derive" ]
@@ -29,12 +30,14 @@ proptest = { version = "1.0", optional = true }
 matrixcompare-core = { version = "0.1.0", optional = true }
 pest           = { version = "2", optional = true }
 pest_derive    = { version = "2", optional = true }
+serde = { version = "1.0", default-features = false, features = [ "derive" ], optional = true }
 
 [dev-dependencies]
 itertools = "0.10"
 matrixcompare = { version = "0.3.0", features = [ "proptest-support" ] }
 nalgebra = { version="0.30", path = "../", features = ["compare"] }
+serde_json = "1.0"
 
 [package.metadata.docs.rs]
 # Enable certain features when building docs for docs.rs
-features = [ "proptest-support", "compare" ]
+features = [ "proptest-support", "compare" ]

nalgebra-sparse/src/coo.rs

@@ -1,5 +1,8 @@
 //! An implementation of the COO sparse matrix format.
 
+#[cfg(feature = "serde-serialize")]
+mod coo_serde;
+
 use crate::SparseFormatError;
 
 /// A COO representation of a sparse matrix.

nalgebra-sparse/src/coo/coo_serde.rs

@@ -0,0 +1,65 @@
+use crate::coo::CooMatrix;
+use serde::{de, Deserialize, Deserializer, Serialize, Serializer};
+
+/// This is an intermediate type for (de)serializing `CooMatrix`.
+///
+/// Deserialization requires using a `try_from_*` function for validation. We could have used
+/// the `remote = "Self"` trick (https://github.com/serde-rs/serde/issues/1220) which allows
+/// to directly serialize/deserialize the original fields and combine it with validation.
+/// However, this would lead to nested serialization of the `CsMatrix` and `SparsityPattern`
+/// types. Instead, we decided that we want a more human-readable serialization format using
+/// field names like `row_indices` and `col_indices`. The easiest way to achieve this is to
+/// introduce an intermediate type. It also allows the serialization format to stay constant
+/// even if the internal layout in `nalgebra` changes.
+///
+/// We want to avoid unnecessary copies when serializing (i.e. cloning slices into owned
+/// storage). Therefore, we use generic arguments to allow using slices during serialization and
+/// owned storage (i.e. `Vec`) during deserialization. Without a major update of serde, slices
+/// and `Vec`s should always (de)serialize identically.
+#[derive(Serialize, Deserialize)]
+struct CooMatrixSerializationData<Indices, Values> {
+    nrows: usize,
+    ncols: usize,
+    row_indices: Indices,
+    col_indices: Indices,
+    values: Values,
+}
+
+impl<T> Serialize for CooMatrix<T>
+where
+    T: Serialize + Clone,
+{
+    fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>
+    where
+        S: Serializer,
+    {
+        CooMatrixSerializationData::<&[usize], &[T]> {
+            nrows: self.nrows(),
+            ncols: self.ncols(),
+            row_indices: self.row_indices(),
+            col_indices: self.col_indices(),
+            values: self.values(),
+        }
+        .serialize(serializer)
+    }
+}
+
+impl<'de, T> Deserialize<'de> for CooMatrix<T>
+where
+    T: Deserialize<'de> + Clone,
+{
+    fn deserialize<D>(deserializer: D) -> Result<CooMatrix<T>, D::Error>
+    where
+        D: Deserializer<'de>,
+    {
+        let de = CooMatrixSerializationData::<Vec<usize>, Vec<T>>::deserialize(deserializer)?;
+        CooMatrix::try_from_triplets(
+            de.nrows,
+            de.ncols,
+            de.row_indices,
+            de.col_indices,
+            de.values,
+        )
+        .map_err(|e| de::Error::custom(e))
+    }
+}

nalgebra-sparse/src/csc.rs

@@ -3,6 +3,9 @@
 //! This is the module-level documentation. See [`CscMatrix`] for the main documentation of the
 //! CSC implementation.
 
+#[cfg(feature = "serde-serialize")]
+mod csc_serde;
+
 use crate::cs::{CsLane, CsLaneIter, CsLaneIterMut, CsLaneMut, CsMatrix};
 use crate::csr::CsrMatrix;
 use crate::pattern::{SparsityPattern, SparsityPatternFormatError, SparsityPatternIter};

nalgebra-sparse/src/csc/csc_serde.rs

@@ -0,0 +1,65 @@
+use crate::CscMatrix;
+use serde::{de, Deserialize, Deserializer, Serialize, Serializer};
+
+/// This is an intermediate type for (de)serializing `CscMatrix`.
+///
+/// Deserialization requires using a `try_from_*` function for validation. We could have used
+/// the `remote = "Self"` trick (https://github.com/serde-rs/serde/issues/1220) which allows
+/// to directly serialize/deserialize the original fields and combine it with validation.
+/// However, this would lead to nested serialization of the `CsMatrix` and `SparsityPattern`
+/// types. Instead, we decided that we want a more human-readable serialization format using
+/// field names like `col_offsets` and `row_indices`. The easiest way to achieve this is to
+/// introduce an intermediate type. It also allows the serialization format to stay constant
+/// even if the internal layout in `nalgebra` changes.
+///
+/// We want to avoid unnecessary copies when serializing (i.e. cloning slices into owned
+/// storage). Therefore, we use generic arguments to allow using slices during serialization and
+/// owned storage (i.e. `Vec`) during deserialization. Without a major update of serde, slices
+/// and `Vec`s should always (de)serialize identically.
+#[derive(Serialize, Deserialize)]
+struct CscMatrixSerializationData<Indices, Values> {
+    nrows: usize,
+    ncols: usize,
+    col_offsets: Indices,
+    row_indices: Indices,
+    values: Values,
+}
+
+impl<T> Serialize for CscMatrix<T>
+where
+    T: Serialize + Clone,
+{
+    fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>
+    where
+        S: Serializer,
+    {
+        CscMatrixSerializationData::<&[usize], &[T]> {
+            nrows: self.nrows(),
+            ncols: self.ncols(),
+            col_offsets: self.col_offsets(),
+            row_indices: self.row_indices(),
+            values: self.values(),
+        }
+        .serialize(serializer)
+    }
+}
+
+impl<'de, T> Deserialize<'de> for CscMatrix<T>
+where
+    T: Deserialize<'de> + Clone,
+{
+    fn deserialize<D>(deserializer: D) -> Result<CscMatrix<T>, D::Error>
+    where
+        D: Deserializer<'de>,
+    {
+        let de = CscMatrixSerializationData::<Vec<usize>, Vec<T>>::deserialize(deserializer)?;
+        CscMatrix::try_from_csc_data(
+            de.nrows,
+            de.ncols,
+            de.col_offsets,
+            de.row_indices,
+            de.values,
+        )
+        .map_err(|e| de::Error::custom(e))
+    }
+}

nalgebra-sparse/src/csr.rs

@@ -2,6 +2,10 @@
 //!
 //! This is the module-level documentation. See [`CsrMatrix`] for the main documentation of the
 //! CSC implementation.
+
+#[cfg(feature = "serde-serialize")]
+mod csr_serde;
+
 use crate::cs::{CsLane, CsLaneIter, CsLaneIterMut, CsLaneMut, CsMatrix};
 use crate::csc::CscMatrix;
 use crate::pattern::{SparsityPattern, SparsityPatternFormatError, SparsityPatternIter};
@@ -9,7 +13,6 @@ use crate::{SparseEntry, SparseEntryMut, SparseFormatError, SparseFormatErrorKin
 
 use nalgebra::Scalar;
 use num_traits::One;
-
 use std::iter::FromIterator;
 use std::slice::{Iter, IterMut};
 

nalgebra-sparse/src/csr/csr_serde.rs

@@ -0,0 +1,65 @@
+use crate::CsrMatrix;
+use serde::{de, Deserialize, Deserializer, Serialize, Serializer};
+
+/// This is an intermediate type for (de)serializing `CsrMatrix`.
+///
+/// Deserialization requires using a `try_from_*` function for validation. We could have used
+/// the `remote = "Self"` trick (https://github.com/serde-rs/serde/issues/1220) which allows
+/// to directly serialize/deserialize the original fields and combine it with validation.
+/// However, this would lead to nested serialization of the `CsMatrix` and `SparsityPattern`
+/// types. Instead, we decided that we want a more human-readable serialization format using
+/// field names like `row_offsets` and `cal_indices`. The easiest way to achieve this is to
+/// introduce an intermediate type. It also allows the serialization format to stay constant
+/// even if the internal layout in `nalgebra` changes.
+///
+/// We want to avoid unnecessary copies when serializing (i.e. cloning slices into owned
+/// storage). Therefore, we use generic arguments to allow using slices during serialization and
+/// owned storage (i.e. `Vec`) during deserialization. Without a major update of serde, slices
+/// and `Vec`s should always (de)serialize identically.
+#[derive(Serialize, Deserialize)]
+struct CsrMatrixSerializationData<Indices, Values> {
+    nrows: usize,
+    ncols: usize,
+    row_offsets: Indices,
+    col_indices: Indices,
+    values: Values,
+}
+
+impl<T> Serialize for CsrMatrix<T>
+where
+    T: Serialize + Clone,
+{
+    fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>
+    where
+        S: Serializer,
+    {
+        CsrMatrixSerializationData::<&[usize], &[T]> {
+            nrows: self.nrows(),
+            ncols: self.ncols(),
+            row_offsets: self.row_offsets(),
+            col_indices: self.col_indices(),
+            values: self.values(),
+        }
+        .serialize(serializer)
+    }
+}
+
+impl<'de, T> Deserialize<'de> for CsrMatrix<T>
+where
+    T: Deserialize<'de> + Clone,
+{
+    fn deserialize<D>(deserializer: D) -> Result<CsrMatrix<T>, D::Error>
+    where
+        D: Deserializer<'de>,
+    {
+        let de = CsrMatrixSerializationData::<Vec<usize>, Vec<T>>::deserialize(deserializer)?;
+        CsrMatrix::try_from_csr_data(
+            de.nrows,
+            de.ncols,
+            de.row_offsets,
+            de.col_indices,
+            de.values,
+        )
+        .map_err(|e| de::Error::custom(e))
+    }
+}

nalgebra-sparse/src/pattern.rs

@@ -1,4 +1,8 @@
 //! Sparsity patterns for CSR and CSC matrices.
+
+#[cfg(feature = "serde-serialize")]
+mod pattern_serde;
+
 use crate::cs::transpose_cs;
 use crate::SparseFormatError;
 use std::error::Error;

nalgebra-sparse/src/pattern/pattern_serde.rs

@@ -0,0 +1,56 @@
+use crate::pattern::SparsityPattern;
+use serde::{de, Deserialize, Deserializer, Serialize, Serializer};
+
+/// This is an intermediate type for (de)serializing `SparsityPattern`.
+///
+/// Deserialization requires using a `try_from_*` function for validation. We could have used
+/// the `remote = "Self"` trick (https://github.com/serde-rs/serde/issues/1220) which allows
+/// to directly serialize/deserialize the original fields and combine it with validation.
+/// However, this would lead to nested serialization of the `CsMatrix` and `SparsityPattern`
+/// types. Instead, we decided that we want a more human-readable serialization format using
+/// field names like `major_offsets` and `minor_indices`. The easiest way to achieve this is to
+/// introduce an intermediate type. It also allows the serialization format to stay constant
+/// even when the internal layout in `nalgebra` changes.
+///
+/// We want to avoid unnecessary copies when serializing (i.e. cloning slices into owned
+/// storage). Therefore, we use generic arguments to allow using slices during serialization and
+/// owned storage (i.e. `Vec`) during deserialization. Without a major update of serde, slices
+/// and `Vec`s should always (de)serialize identically.
+#[derive(Serialize, Deserialize)]
+struct SparsityPatternSerializationData<Indices> {
+    major_dim: usize,
+    minor_dim: usize,
+    major_offsets: Indices,
+    minor_indices: Indices,
+}
+
+impl Serialize for SparsityPattern {
+    fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>
+    where
+        S: Serializer,
+    {
+        SparsityPatternSerializationData::<&[usize]> {
+            major_dim: self.major_dim(),
+            minor_dim: self.minor_dim(),
+            major_offsets: self.major_offsets(),
+            minor_indices: self.minor_indices(),
+        }
+        .serialize(serializer)
+    }
+}
+
+impl<'de> Deserialize<'de> for SparsityPattern {
+    fn deserialize<D>(deserializer: D) -> Result<SparsityPattern, D::Error>
+    where
+        D: Deserializer<'de>,
+    {
+        let de = SparsityPatternSerializationData::<Vec<usize>>::deserialize(deserializer)?;
+        SparsityPattern::try_from_offsets_and_indices(
+            de.major_dim,
+            de.minor_dim,
+            de.major_offsets,
+            de.minor_indices,
+        )
+        .map_err(|e| de::Error::custom(e))
+    }
+}

nalgebra-sparse/tests/serde.rs

@@ -0,0 +1,206 @@
+#![cfg(feature = "serde-serialize")]
+//! Serialization tests
+#[cfg(any(not(feature = "proptest-support"), not(feature = "compare")))]
+compile_error!("Tests must be run with features `proptest-support` and `compare`");
+
+#[macro_use]
+pub mod common;
+
+use nalgebra_sparse::coo::CooMatrix;
+use nalgebra_sparse::csc::CscMatrix;
+use nalgebra_sparse::csr::CsrMatrix;
+use nalgebra_sparse::pattern::SparsityPattern;
+
+use proptest::prelude::*;
+use serde::{Deserialize, Serialize};
+
+use crate::common::{csc_strategy, csr_strategy};
+
+fn json_roundtrip<T: Serialize + for<'a> Deserialize<'a>>(csr: &T) -> T {
+    let serialized = serde_json::to_string(csr).unwrap();
+    let deserialized: T = serde_json::from_str(&serialized).unwrap();
+    deserialized
+}
+
+#[test]
+fn pattern_roundtrip() {
+    {
+        // A pattern with zero explicitly stored entries
+        let pattern =
+            SparsityPattern::try_from_offsets_and_indices(3, 2, vec![0, 0, 0, 0], Vec::new())
+                .unwrap();
+
+        assert_eq!(json_roundtrip(&pattern), pattern);
+    }
+
+    {
+        // Arbitrary pattern
+        let offsets = vec![0, 2, 2, 5];
+        let indices = vec![0, 5, 1, 2, 3];
+        let pattern =
+            SparsityPattern::try_from_offsets_and_indices(3, 6, offsets.clone(), indices.clone())
+                .unwrap();
+
+        assert_eq!(json_roundtrip(&pattern), pattern);
+    }
+}
+
+#[test]
+#[rustfmt::skip]
+fn pattern_deserialize_invalid() {
+    assert!(serde_json::from_str::<SparsityPattern>(r#"{"major_dim":3,"minor_dim":6,"major_offsets":[0,2,2,5],"minor_indices":[0,5,1,2,3]}"#).is_ok());
+    assert!(serde_json::from_str::<SparsityPattern>(r#"{"major_dim":0,"minor_dim":0,"major_offsets":[],"minor_indices":[]}"#).is_err());
+    assert!(serde_json::from_str::<SparsityPattern>(r#"{"major_dim":3,"minor_dim":6,"major_offsets":[0, 3, 5],"minor_indices":[0, 1, 2, 3, 5]}"#).is_err());
+    assert!(serde_json::from_str::<SparsityPattern>(r#"{"major_dim":3,"minor_dim":6,"major_offsets":[1, 2, 2, 5],"minor_indices":[0, 5, 1, 2, 3]}"#).is_err());
+    assert!(serde_json::from_str::<SparsityPattern>(r#"{"major_dim":3,"minor_dim":6,"major_offsets":[0, 2, 2, 4],"minor_indices":[0, 5, 1, 2, 3]}"#).is_err());
+    assert!(serde_json::from_str::<SparsityPattern>(r#"{"major_dim":3,"minor_dim":6,"major_offsets":[0, 2, 2],"minor_indices":[0, 5, 1, 2, 3]}"#).is_err());
+    assert!(serde_json::from_str::<SparsityPattern>(r#"{"major_dim":3,"minor_dim":6,"major_offsets":[0, 3, 2, 5],"minor_indices":[0, 1, 2, 3, 4]}"#).is_err());
+    assert!(serde_json::from_str::<SparsityPattern>(r#"{"major_dim":3,"minor_dim":6,"major_offsets":[0, 2, 2, 5],"minor_indices":[0, 2, 3, 1, 4]}"#).is_err());
+    assert!(serde_json::from_str::<SparsityPattern>(r#"{"major_dim":3,"minor_dim":6,"major_offsets":[0, 2, 2, 5],"minor_indices":[0, 6, 1, 2, 3]}"#).is_err());
+    assert!(serde_json::from_str::<SparsityPattern>(r#"{"major_dim":3,"minor_dim":6,"major_offsets":[0, 2, 2, 5],"minor_indices":[0, 5, 2, 2, 3]}"#).is_err());
+}
+
+#[test]
+fn coo_roundtrip() {
+    {
+        // A COO matrix without entries
+        let matrix =
+            CooMatrix::<i32>::try_from_triplets(3, 2, Vec::new(), Vec::new(), Vec::new()).unwrap();
+
+        assert_eq!(json_roundtrip(&matrix), matrix);
+    }
+
+    {
+        // Arbitrary COO matrix, no duplicates
+        let i = vec![0, 1, 0, 0, 2];
+        let j = vec![0, 2, 1, 3, 3];
+        let v = vec![2, 3, 7, 3, 1];
+        let matrix =
+            CooMatrix::<i32>::try_from_triplets(3, 5, i.clone(), j.clone(), v.clone()).unwrap();
+
+        assert_eq!(json_roundtrip(&matrix), matrix);
+    }
+}
+
+#[test]
+fn coo_deserialize_invalid() {
+    // Valid matrix: {"nrows":3,"ncols":5,"row_indices":[0,1,0,0,2],"col_indices":[0,2,1,3,3],"values":[2,3,7,3,1]}
+    assert!(serde_json::from_str::<CooMatrix<i32>>(r#"{"nrows":3,"ncols":5,"row_indices":[0,1,0,0,2],"col_indices":[0,2,1,3,3],"values":[2,3,7,3,1]}"#).is_ok());
+    assert!(serde_json::from_str::<CooMatrix<i32>>(r#"{"nrows":0,"ncols":0,"row_indices":[0,1,0,0,2],"col_indices":[0,2,1,3,3],"values":[2,3,7,3,4]}"#).is_err());
+    assert!(serde_json::from_str::<CooMatrix<i32>>(r#"{"nrows":-3,"ncols":5,"row_indices":[0,1,0,0,2],"col_indices":[0,2,1,3,3],"values":[2,3,7,3,4]}"#).is_err());
+    assert!(serde_json::from_str::<CooMatrix<i32>>(r#"{"nrows":3,"ncols":5,"row_indices":[0,1,0,0,2],"col_indices":[0,2,1,3,3],"values":[2,3,7,3]}"#).is_err());
+    assert!(serde_json::from_str::<CooMatrix<i32>>(r#"{"nrows":3,"ncols":5,"row_indices":[0,1,0,0,2],"col_indices":[0,2,1,3,3],"values":[2,3,7,3,4,5]}"#).is_err());
+    assert!(serde_json::from_str::<CooMatrix<i32>>(r#"{"nrows":3,"ncols":5,"row_indices":[0,1,0,0,2],"col_indices":[0,2,1,8,3],"values":[2,3,7,3,4]}"#).is_err());
+    assert!(serde_json::from_str::<CooMatrix<i32>>(r#"{"nrows":3,"ncols":5,"row_indices":[0,1,0,0],"col_indices":[0,2,1,8,3],"values":[2,3,7,3,4]}"#).is_err());
+    assert!(serde_json::from_str::<CooMatrix<i32>>(r#"{"nrows":3,"ncols":5,"row_indices":[0,10,0,0,2],"col_indices":[0,2,1,3,3],"values":[2,3,7,3,4]}"#).is_err());
+    assert!(serde_json::from_str::<CooMatrix<i32>>(r#"{"nrows":3,"ncols":5,"row_indices":[0,1,0,0,2],"col_indices":[0,2,1,30,3],"values":[2,3,7,3,4]}"#).is_err());
+}
+
+#[test]
+fn coo_deserialize_duplicates() {
+    assert_eq!(
+        serde_json::from_str::<CooMatrix<i32>>(
+            r#"{"nrows":3,"ncols":5,"row_indices":[0,1,0,0,2,0,1],"col_indices":[0,2,1,3,3,0,2],"values":[2,3,7,3,1,5,6]}"#
+        ).unwrap(),
+        CooMatrix::<i32>::try_from_triplets(
+            3,
+            5,
+            vec![0, 1, 0, 0, 2, 0, 1],
+            vec![0, 2, 1, 3, 3, 0, 2],
+            vec![2, 3, 7, 3, 1, 5, 6]
+        )
+        .unwrap()
+    );
+}
+
+#[test]
+fn csc_roundtrip() {
+    {
+        // A CSC matrix with zero explicitly stored entries
+        let offsets = vec![0, 0, 0, 0];
+        let indices = vec![];
+        let values = Vec::<i32>::new();
+        let matrix = CscMatrix::try_from_csc_data(2, 3, offsets, indices, values).unwrap();
+
+        assert_eq!(json_roundtrip(&matrix), matrix);
+    }
+
+    {
+        // An arbitrary CSC matrix
+        let offsets = vec![0, 2, 2, 5];
+        let indices = vec![0, 5, 1, 2, 3];
+        let values = vec![0, 1, 2, 3, 4];
+        let matrix =
+            CscMatrix::try_from_csc_data(6, 3, offsets.clone(), indices.clone(), values.clone())
+                .unwrap();
+
+        assert_eq!(json_roundtrip(&matrix), matrix);
+    }
+}
+
+#[test]
+fn csc_deserialize_invalid() {
+    // Valid matrix: {"nrows":6,"ncols":3,"col_offsets":[0,2,2,5],"row_indices":[0,5,1,2,3],"values":[0,1,2,3,4]}
+    assert!(serde_json::from_str::<CscMatrix<i32>>(r#"{"nrows":6,"ncols":3,"col_offsets":[0,2,2,5],"row_indices":[0,5,1,2,3],"values":[0,1,2,3,4]}"#).is_ok());
+    assert!(serde_json::from_str::<CscMatrix<i32>>(r#"{"nrows":0,"ncols":0,"col_offsets":[0,2,2,5],"row_indices":[0,5,1,2,3],"values":[0,1,2,3,4]}"#).is_err());
+    assert!(serde_json::from_str::<CscMatrix<i32>>(r#"{"nrows":-6,"ncols":3,"col_offsets":[0,2,2,5],"row_indices":[0,5,1,2,3],"values":[0,1,2,3,4]}"#).is_err());
+    assert!(serde_json::from_str::<CscMatrix<i32>>(r#"{"nrows":6,"ncols":3,"col_offsets":[0,2,2,5],"row_indices":[0,5,1,2,3],"values":[0,1,2,3]}"#).is_err());
+    assert!(serde_json::from_str::<CscMatrix<i32>>(r#"{"nrows":6,"ncols":3,"col_offsets":[0,2,2,5],"row_indices":[0,5,1,2,3],"values":[0,1,2,3,4,5]}"#).is_err());
+    assert!(serde_json::from_str::<CscMatrix<i32>>(r#"{"nrows":6,"ncols":3,"col_offsets":[0,2,2,5],"row_indices":[0,5,1,8,3],"values":[0,1,2,3,4]}"#).is_err());
+    assert!(serde_json::from_str::<CscMatrix<i32>>(r#"{"nrows":6,"ncols":3,"col_offsets":[0,2,2,5],"row_indices":[0,5,1,2,3,1,1],"values":[0,1,2,3,4]}"#).is_err());
+    // The following actually panics ('range end index 10 out of range for slice of length 5', nalgebra-sparse\src\pattern.rs:156:38)
+    //assert!(serde_json::from_str::<CscMatrix<i32>>(r#"{"nrows":6,"ncols":3,"col_offsets":[0,10,2,5],"row_indices":[0,5,1,2,3],"values":[0,1,2,3,4]}"#).is_err());
+    assert!(serde_json::from_str::<CscMatrix<i32>>(r#"{"nrows":3,"ncols":6,"row_offsets":[0,2,2,5],"col_indices":[0,5,1,2,3],"values":[0,1,2,3,4]}"#).is_err());
+}
+
+#[test]
+fn csr_roundtrip() {
+    {
+        // A CSR matrix with zero explicitly stored entries
+        let offsets = vec![0, 0, 0, 0];
+        let indices = vec![];
+        let values = Vec::<i32>::new();
+        let matrix = CsrMatrix::try_from_csr_data(3, 2, offsets, indices, values).unwrap();
+
+        assert_eq!(json_roundtrip(&matrix), matrix);
+    }
+
+    {
+        // An arbitrary CSR matrix
+        let offsets = vec![0, 2, 2, 5];
+        let indices = vec![0, 5, 1, 2, 3];
+        let values = vec![0, 1, 2, 3, 4];
+        let matrix =
+            CsrMatrix::try_from_csr_data(3, 6, offsets.clone(), indices.clone(), values.clone())
+                .unwrap();
+
+        assert_eq!(json_roundtrip(&matrix), matrix);
+    }
+}
+
+#[test]
+fn csr_deserialize_invalid() {
+    // Valid matrix: {"nrows":3,"ncols":6,"row_offsets":[0,2,2,5],"col_indices":[0,5,1,2,3],"values":[0,1,2,3,4]}
+    assert!(serde_json::from_str::<CsrMatrix<i32>>(r#"{"nrows":3,"ncols":6,"row_offsets":[0,2,2,5],"col_indices":[0,5,1,2,3],"values":[0,1,2,3,4]}"#).is_ok());
+    assert!(serde_json::from_str::<CsrMatrix<i32>>(r#"{"nrows":0,"ncols":0,"row_offsets":[0,2,2,5],"col_indices":[0,5,1,2,3],"values":[0,1,2,3,4]}"#).is_err());
+    assert!(serde_json::from_str::<CsrMatrix<i32>>(r#"{"nrows":-3,"ncols":6,"row_offsets":[0,2,2,5],"col_indices":[0,5,1,2,3],"values":[0,1,2,3,4]}"#).is_err());
+    assert!(serde_json::from_str::<CsrMatrix<i32>>(r#"{"nrows":3,"ncols":6,"row_offsets":[0,2,2,5],"col_indices":[0,5,1,2,3],"values":[0,1,2,3]}"#).is_err());
+    assert!(serde_json::from_str::<CsrMatrix<i32>>(r#"{"nrows":3,"ncols":6,"row_offsets":[0,2,2,5],"col_indices":[0,5,1,2,3],"values":[0,1,2,3,4,5]}"#).is_err());
+    assert!(serde_json::from_str::<CsrMatrix<i32>>(r#"{"nrows":3,"ncols":6,"row_offsets":[0,2,2,5],"col_indices":[0,5,1,8,3],"values":[0,1,2,3,4]}"#).is_err());
+    assert!(serde_json::from_str::<CsrMatrix<i32>>(r#"{"nrows":3,"ncols":6,"row_offsets":[0,2,2,5],"col_indices":[0,5,1,2,3,1,1],"values":[0,1,2,3,4]}"#).is_err());
+    // The following actually panics ('range end index 10 out of range for slice of length 5', nalgebra-sparse\src\pattern.rs:156:38)
+    //assert!(serde_json::from_str::<CsrMatrix<i32>>(r#"{"nrows":3,"ncols":6,"row_offsets":[0,10,2,5],"col_indices":[0,5,1,2,3],"values":[0,1,2,3,4]}"#).is_err());
+    assert!(serde_json::from_str::<CsrMatrix<i32>>(r#"{"nrows":6,"ncols":3,"col_offsets":[0,2,2,5],"row_indices":[0,5,1,2,3],"values":[0,1,2,3,4]}"#).is_err());
+}
+
+proptest! {
+    #[test]
+    fn csc_roundtrip_proptest(csc in csc_strategy()) {
+        prop_assert_eq!(json_roundtrip(&csc), csc);
+    }
+
+    #[test]
+    fn csr_roundtrip_proptest(csr in csr_strategy()) {
+        prop_assert_eq!(json_roundtrip(&csr), csr);
+    }
+}