Merge branch 'main' of github.com:vlang/vsl into feature/new-lapack

* 'main' of github.com:vlang/vsl:
  fix kmeans.v (#199)
  Update maximum dimension checks in HDF5 file functions

inout/h5/hdf5_nix.c.v

@@ -227,7 +227,7 @@ pub fn open_file(filename string) !Hdf5File {
 
 // read_dataset1d reads a 1-d numeric array (vector) from a named HDF5 dataset in an HDF5 file.
 //   Replaces the value of the array.
-//   Maximum dimension is math.max_i32 or less (this is checked).
+//   Maximum dimension is max_i32 or less (this is checked).
 pub fn (f &Hdf5File) read_dataset1d[T](dset_name string, mut dataset []T) {
 	mut rank := 0
 	mut class_id := Hdf5ClassT(0)
@@ -242,7 +242,7 @@ pub fn (f &Hdf5File) read_dataset1d[T](dset_name string, mut dataset []T) {
 		&class_id, &type_size)
 	assert errc >= 0
 	assert curdims[0] > 0
-	assert curdims[0] < math.max_i32
+	assert curdims[0] < max_i32
 
 	dtype := hdftype(dataset[0])
 	// note: V dims are int while hdf5 dims are u64
@@ -257,8 +257,8 @@ pub fn (f &Hdf5File) read_dataset1d[T](dset_name string, mut dataset []T) {
 
 // read_dataset2d reads a 2-d numeric array from a named HDF5 dataset in an HDF5 file.
 //   Replaces the value of the array.
-//   Maximum of any dimension is math.max_i32 or less (this is checked).
-//   Maximum total elements is also math.max_i32.
+//   Maximum of any dimension is max_i32 or less (this is checked).
+//   Maximum total elements is also max_i32.
 pub fn (f &Hdf5File) read_dataset2d[T](dset_name string, mut dataset [][]T) {
 	mut rank := 0
 	mut class_id := Hdf5ClassT(0)
@@ -274,8 +274,8 @@ pub fn (f &Hdf5File) read_dataset2d[T](dset_name string, mut dataset [][]T) {
 	assert errc >= 0
 	assert curdims[0] > 0
 	assert curdims[1] > 0
-	assert curdims[0] < math.max_i32
-	assert curdims[1] < math.max_i32
+	assert curdims[0] < max_i32
+	assert curdims[1] < max_i32
 
 	dtype := hdftype(dataset[0][0])
 	mut y := make1type[T](int(curdims[0] * curdims[1]))
@@ -291,8 +291,8 @@ pub fn (f &Hdf5File) read_dataset2d[T](dset_name string, mut dataset [][]T) {
 
 // read_dataset3d reads a 3-d numeric array from a named HDF5 dataset in an HDF5 file.
 //   Replaces the value of the array with correctly dimensioned array.
-//   Maximum of any dimension is math.max_i32 or less (this is checked).
-//   Maximum total elements is also math.max_i32.
+//   Maximum of any dimension is max_i32 or less (this is checked).
+//   Maximum total elements is also max_i32.
 pub fn (f &Hdf5File) read_dataset3d[T](dset_name string, mut dataset [][][]T) {
 	mut rank := 0
 	mut class_id := Hdf5ClassT(0)
@@ -309,9 +309,9 @@ pub fn (f &Hdf5File) read_dataset3d[T](dset_name string, mut dataset [][][]T) {
 	assert curdims[0] > 0
 	assert curdims[1] > 0
 	assert curdims[2] > 0
-	assert curdims[0] < math.max_i32
-	assert curdims[1] < math.max_i32
-	assert curdims[2] < math.max_i32
+	assert curdims[0] < max_i32
+	assert curdims[1] < max_i32
+	assert curdims[2] < max_i32
 
 	dtype := hdftype(dataset[0][0][0])
 	mut y := make1type[T](int(curdims[0] * curdims[1] * curdims[2]))
@@ -584,7 +584,7 @@ pub fn (f &Hdf5File) read_attribute[T](dset_name string, attr_name string, mut a
 
 // read_attribute1d reads a 1-d numeric array (vector) from a named HDF5 dataset and named attribute in an HDF5 file.
 //   Replaces the value of the given array.
-//   Maximum dimension is math.max_i32 or less (this is checked).
+//   Maximum dimension is max_i32 or less (this is checked).
 pub fn (f &Hdf5File) read_attribute1d[T](dset_name string, attr_name string, mut attr_value []T) !bool {
 	mut rank := 0
 	mut class_id := Hdf5ClassT(0)
@@ -603,8 +603,8 @@ pub fn (f &Hdf5File) read_attribute1d[T](dset_name string, attr_name string, mut
 		&class_id, &type_size)
 	assert errc >= 0
 	assert curdims[0] > 0
-	assert curdims[0] <= math.max_i32
-	if curdims[0] > math.max_i32 {
+	assert curdims[0] <= max_i32
+	if curdims[0] > max_i32 {
 		return false
 	}
 

ml/kmeans.v

@@ -34,7 +34,7 @@ pub fn Kmeans.new(mut data Data[f64], nb_classes int, name string) &Kmeans {
 
 	// bins
 	ndiv := [10, 10] // TODO: make this a parameter
-	bins := gm.Bins.new(stat.min_x, stat.max_x, ndiv) // TODO: make sure minx and maxx are 2D or 3D; i.e. nb_features ≤ 2
+	mut bins := gm.Bins.new(stat.min_x, stat.max_x, ndiv) // TODO: make sure minx and maxx are 2D or 3D; i.e. nb_features ≤ 2
 	mut o := Kmeans{
 		name: name
 		data: data

prime/prime_test.v

@@ -17,10 +17,10 @@ fn test_is_prime() {
 	// true
 	assert is_prime(7_691)
 	assert is_prime(524_287)
-	assert is_prime(int(math.max_i32))
+	assert is_prime(int(max_i32))
 
 	// false
-	assert is_prime(int(math.max_i32) - 1) == false
+	assert is_prime(int(max_i32) - 1) == false
 }
 
 fn test_prime_sieve() {