Correct bit * byte and bit * float script comparisons

docs/reference/vectors/vector-functions.asciidoc

@@ -336,6 +336,10 @@ When using `bit` vectors, not all the vector functions are available. The suppor
 this is the sum of the bitwise AND of the two vectors. If providing `float[]` or `byte[]`, who has `dims` number of elements, as a query vector, the `dotProduct` is
 the sum of the floating point values using the stored `bit` vector as a mask.
 
+NOTE: When comparing `floats` and `bytes` with `bit` vectors, the `bit` vector is treated as a mask in big-endian order.
+For example, if the `bit` vector is `10100001` (e.g. the single byte value `161`) and its compared
+with array of values `[1, 2, 3, 4, 5, 6, 7, 8]` the `dotProduct` will be `1 + 3 + 8 = 16`.
+
 Here is an example of using dot-product with bit vectors.
 
 [source,console]

libs/simdvec/src/main/java/org/elasticsearch/simdvec/ESVectorUtil.java

@@ -51,6 +51,8 @@ public static long ipByteBinByte(byte[] q, byte[] d) {
     /**
      * Compute the inner product of two vectors, where the query vector is a byte vector and the document vector is a bit vector.
      * This will return the sum of the query vector values using the document vector as a mask.
+     * When comparing the bits with the bytes, they are done in "big endian" order. For example, if the byte vector
+     * is [1, 2, 3, 4, 5, 6, 7, 8] and the bit vector is [0b10000000], the inner product will be 1.0.
      * @param q the query vector
      * @param d the document vector
      * @return the inner product of the two vectors
@@ -63,9 +65,9 @@ public static int ipByteBit(byte[] q, byte[] d) {
         // now combine the two vectors, summing the byte dimensions where the bit in d is `1`
         for (int i = 0; i < d.length; i++) {
             byte mask = d[i];
-            for (int j = 0; j < Byte.SIZE; j++) {
+            for (int j = Byte.SIZE - 1; j >= 0; j--) {
                 if ((mask & (1 << j)) != 0) {
-                    result += q[i * Byte.SIZE + j];
+                    result += q[i * Byte.SIZE + Byte.SIZE - 1 - j];
                 }
             }
         }
@@ -75,6 +77,8 @@ public static int ipByteBit(byte[] q, byte[] d) {
     /**
      * Compute the inner product of two vectors, where the query vector is a float vector and the document vector is a bit vector.
      * This will return the sum of the query vector values using the document vector as a mask.
+     * When comparing the bits with the floats, they are done in "big endian" order. For example, if the float vector
+     * is [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0] and the bit vector is [0b10000000], the inner product will be 1.0.
      * @param q the query vector
      * @param d the document vector
      * @return the inner product of the two vectors
@@ -86,9 +90,9 @@ public static float ipFloatBit(float[] q, byte[] d) {
         float result = 0;
         for (int i = 0; i < d.length; i++) {
             byte mask = d[i];
-            for (int j = 0; j < Byte.SIZE; j++) {
+            for (int j = Byte.SIZE - 1; j >= 0; j--) {
                 if ((mask & (1 << j)) != 0) {
-                    result += q[i * Byte.SIZE + j];
+                    result += q[i * Byte.SIZE + Byte.SIZE - 1 - j];
                 }
             }
         }

libs/simdvec/src/test/java/org/elasticsearch/simdvec/ESVectorUtilTests.java

@@ -21,6 +21,22 @@ public class ESVectorUtilTests extends BaseVectorizationTests {
     static final ESVectorizationProvider defaultedProvider = BaseVectorizationTests.defaultProvider();
     static final ESVectorizationProvider defOrPanamaProvider = BaseVectorizationTests.maybePanamaProvider();
 
+    public void testIpByteBit() {
+        byte[] q = new byte[16];
+        byte[] d = new byte[] { (byte) Integer.parseInt("01100010", 2), (byte) Integer.parseInt("10100111", 2) };
+        random().nextBytes(q);
+        int expected = q[1] + q[2] + q[6] + q[8] + q[10] + q[13] + q[14] + q[15];
+        assertEquals(expected, ESVectorUtil.ipByteBit(q, d));
+    }
+
+    public void testIpFloatBit() {
+        float[] q = new float[16];
+        byte[] d = new byte[] { (byte) Integer.parseInt("01100010", 2), (byte) Integer.parseInt("10100111", 2) };
+        random().nextFloat();
+        float expected = q[1] + q[2] + q[6] + q[8] + q[10] + q[13] + q[14] + q[15];
+        assertEquals(expected, ESVectorUtil.ipFloatBit(q, d), 1e-6);
+    }
+
     public void testBitAndCount() {
         testBasicBitAndImpl(ESVectorUtil::andBitCountLong);
     }