* of the returned array is that of the specified array. If the collection fits in the specified
   * array, it is returned therein. Otherwise, a new array is allocated with the runtime type of the
   * specified array and the size of the specified collection.
   *
   * <p>If the collection fits in the specified array with room to spare (i.e., the array has more

   * of the returned array is that of the specified array. If the collection fits in the specified
   * array, it is returned therein. Otherwise, a new array is allocated with the runtime type of the
   * specified array and the size of the specified collection.
   *
   * <p>If the collection fits in the specified array with room to spare (i.e., the array has more

errors.New("edwards25519: invalid field element input size") } // Bits 0:51 (bytes 0:8, bits 0:64, shift 0, mask 51). v.l0 = byteorder.LEUint64(x[0:8]) v.l0 &= maskLow51Bits // Bits 51:102 (bytes 6:14, bits 48:112, shift 3, mask 51). v.l1 = byteorder.LEUint64(x[6:14]) >> 3 v.l1 &= maskLow51Bits // Bits 102:153 (bytes 12:20, bits 96:160, shift 6, mask 51). v.l2 = byteorder.LEUint64(x[12:20]) >> 6 v.l2 &= maskLow51Bits // Bits 153:204 (bytes 19:27, bits 152:216, shift 1, mask 51). v.l3 = byteorder.LEUint64(x[19:27])...

all types in its type set must have the same underlying slice type <code>[]E</code>.
</p>

<p>
If the capacity of <code>s</code> is not large enough to fit the additional
values, <code>append</code> <a href="#Allocation">allocates</a> a new, sufficiently large underlying
array that fits both the existing slice elements and the additional values.

Cryptographic Module operates in FIPS 140-3 mode.
The possible values are:
- "off": no special support for FIPS 140-3 mode. This is the default.
- "on": the Go Cryptographic Module operates in FIPS 140-3 mode.
- "only": like "on", but cryptographic algorithms not approved by
  FIPS 140-3 return an error or panic.
For more information, see [FIPS 140-3 Compliance](/doc/security/fips140).

    // The values here look like 111...11101...010 in binary, where the initial 111...1110 takes
    // up exactly as many bits as can be represented in the significand (24 for float, 53 for
    // double). That final 0 should be rounded up to 1 because the remaining bits make that number
    // slightly nearer.
    long floatConversionTest = 0xfffffe8000000002L;
    long doubleConversionTest = 0xfffffffffffff402L;

# SHA256 checksums of snapshot zip files in this directory.
# These checksums are included in the FIPS security policy
# (validation instructions sent to the lab) and MUST NOT CHANGE.
# That is, the zip files themselves must not change.
#
# It is okay to add new zip files to the list, and it is okay to
# remove zip files from the list when they are removed from
# this directory. To update this file:
#
#	go test cmd/go/internal/fips140 -update
#

    // The values here look like 111...11101...010 in binary, where the initial 111...1110 takes
    // up exactly as many bits as can be represented in the significand (24 for float, 53 for
    // double). That final 0 should be rounded up to 1 because the remaining bits make that number
    // slightly nearer.
    long floatConversionTest = 0xfffffe8000000002L;
    long doubleConversionTest = 0xfffffffffffff402L;

      PairedStats stats = createPairedStatsOf(values.asIterable(), OTHER_MANY_VALUES);
      LinearTransformation fit = stats.leastSquaresFit();
      if (values.hasAnyNonFinite()) {
        assertLinearTransformationNaN(fit);
      } else {
        assertDiagonalLinearTransformation(
            fit,
            stats.xStats().mean(),
            stats.yStats().mean(),
            stats.xStats().populationVariance(),

      PairedStats stats = createPairedStatsOf(values.asIterable(), OTHER_MANY_VALUES);
      LinearTransformation fit = stats.leastSquaresFit();
      if (values.hasAnyNonFinite()) {
        assertLinearTransformationNaN(fit);
      } else {
        assertDiagonalLinearTransformation(
            fit,
            stats.xStats().mean(),
            stats.yStats().mean(),
            stats.xStats().populationVariance(),