1 /*
   2  * Copyright (c) 2017, Oracle and/or its affiliates. All rights reserved.
   3  * DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
   4  *
   5  * This code is free software; you can redistribute it and/or modify it
   6  * under the terms of the GNU General Public License version 2 only, as
   7  * published by the Free Software Foundation.  Oracle designates this
   8  * particular file as subject to the "Classpath" exception as provided
   9  * by Oracle in the LICENSE file that accompanied this code.
  10  *
  11  * This code is distributed in the hope that it will be useful, but WITHOUT
  12  * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
  13  * FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General Public License
  14  * version 2 for more details (a copy is included in the LICENSE file that
  15  * accompanied this code).
  16  *
  17  * You should have received a copy of the GNU General Public License version
  18  * 2 along with this work; if not, write to the Free Software Foundation,
  19  * Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
  20  *
  21  * Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
  22  * or visit www.oracle.com if you need additional information or have
  23  * questions.
  24  */
  25 package jdk.incubator.vector;
  26 
  27 import java.nio.ByteBuffer;
  28 import java.nio.DoubleBuffer;
  29 import java.nio.ByteOrder;
  30 import java.util.Objects;
  31 import java.util.function.IntUnaryOperator;
  32 import java.util.function.Function;
  33 import java.util.concurrent.ThreadLocalRandom;
  34 
  35 import jdk.internal.misc.Unsafe;
  36 import jdk.internal.vm.annotation.ForceInline;
  37 import static jdk.incubator.vector.VectorIntrinsics.*;
  38 
  39 
  40 /**
  41  * A specialized {@link Vector} representing an ordered immutable sequence of
  42  * {@code double} values.
  43  */
  44 @SuppressWarnings("cast")
  45 public abstract class DoubleVector extends Vector<Double> {
  46 
  47     DoubleVector() {}
  48 
  49     private static final int ARRAY_SHIFT = 31 - Integer.numberOfLeadingZeros(Unsafe.ARRAY_DOUBLE_INDEX_SCALE);
  50 
  51     // Unary operator
  52 
  53     interface FUnOp {
  54         double apply(int i, double a);
  55     }
  56 
  57     abstract DoubleVector uOp(FUnOp f);
  58 
  59     abstract DoubleVector uOp(Mask<Double> m, FUnOp f);
  60 
  61     // Binary operator
  62 
  63     interface FBinOp {
  64         double apply(int i, double a, double b);
  65     }
  66 
  67     abstract DoubleVector bOp(Vector<Double> v, FBinOp f);
  68 
  69     abstract DoubleVector bOp(Vector<Double> v, Mask<Double> m, FBinOp f);
  70 
  71     // Trinary operator
  72 
  73     interface FTriOp {
  74         double apply(int i, double a, double b, double c);
  75     }
  76 
  77     abstract DoubleVector tOp(Vector<Double> v1, Vector<Double> v2, FTriOp f);
  78 
  79     abstract DoubleVector tOp(Vector<Double> v1, Vector<Double> v2, Mask<Double> m, FTriOp f);
  80 
  81     // Reduction operator
  82 
  83     abstract double rOp(double v, FBinOp f);
  84 
  85     // Binary test
  86 
  87     interface FBinTest {
  88         boolean apply(int i, double a, double b);
  89     }
  90 
  91     abstract Mask<Double> bTest(Vector<Double> v, FBinTest f);
  92 
  93     // Foreach
  94 
  95     interface FUnCon {
  96         void apply(int i, double a);
  97     }
  98 
  99     abstract void forEach(FUnCon f);
 100 
 101     abstract void forEach(Mask<Double> m, FUnCon f);
 102 
 103     // Static factories
 104 
 105     /**
 106      * Returns a vector where all lane elements are set to the default
 107      * primitive value.
 108      *
 109      * @param species species of desired vector
 110      * @return a zero vector of given species
 111      */
 112     @ForceInline
 113     @SuppressWarnings("unchecked")
 114     public static DoubleVector zero(Species<Double> species) {
 115         return VectorIntrinsics.broadcastCoerced((Class<DoubleVector>) species.boxType(), double.class, species.length(),
 116                                                  Double.doubleToLongBits(0.0f), species,
 117                                                  ((bits, s) -> ((DoubleSpecies)s).op(i -> Double.longBitsToDouble((long)bits))));
 118     }
 119 
 120     /**
 121      * Loads a vector from a byte array starting at an offset.
 122      * <p>
 123      * Bytes are composed into primitive lane elements according to the
 124      * native byte order of the underlying platform
 125      * <p>
 126      * This method behaves as if it returns the result of calling the
 127      * byte buffer, offset, and mask accepting
 128      * {@link #fromByteBuffer(Species<Double>, ByteBuffer, int, Mask) method} as follows:
 129      * <pre>{@code
 130      * return this.fromByteBuffer(ByteBuffer.wrap(a), i, this.maskAllTrue());
 131      * }</pre>
 132      *
 133      * @param species species of desired vector
 134      * @param a the byte array
 135      * @param ix the offset into the array
 136      * @return a vector loaded from a byte array
 137      * @throws IndexOutOfBoundsException if {@code i < 0} or
 138      * {@code i > a.length - (this.length() * this.elementSize() / Byte.SIZE)}
 139      */
 140     @ForceInline
 141     @SuppressWarnings("unchecked")
 142     public static DoubleVector fromByteArray(Species<Double> species, byte[] a, int ix) {
 143         Objects.requireNonNull(a);
 144         ix = VectorIntrinsics.checkIndex(ix, a.length, species.bitSize() / Byte.SIZE);
 145         return VectorIntrinsics.load((Class<DoubleVector>) species.boxType(), double.class, species.length(),
 146                                      a, ((long) ix) + Unsafe.ARRAY_BYTE_BASE_OFFSET,
 147                                      a, ix, species,
 148                                      (c, idx, s) -> {
 149                                          ByteBuffer bbc = ByteBuffer.wrap(c, idx, a.length - idx).order(ByteOrder.nativeOrder());
 150                                          DoubleBuffer tb = bbc.asDoubleBuffer();
 151                                          return ((DoubleSpecies)s).op(i -> tb.get());
 152                                      });
 153     }
 154 
 155     /**
 156      * Loads a vector from a byte array starting at an offset and using a
 157      * mask.
 158      * <p>
 159      * Bytes are composed into primitive lane elements according to the
 160      * native byte order of the underlying platform.
 161      * <p>
 162      * This method behaves as if it returns the result of calling the
 163      * byte buffer, offset, and mask accepting
 164      * {@link #fromByteBuffer(Species<Double>, ByteBuffer, int, Mask) method} as follows:
 165      * <pre>{@code
 166      * return this.fromByteBuffer(ByteBuffer.wrap(a), i, m);
 167      * }</pre>
 168      *
 169      * @param species species of desired vector
 170      * @param a the byte array
 171      * @param ix the offset into the array
 172      * @param m the mask
 173      * @return a vector loaded from a byte array
 174      * @throws IndexOutOfBoundsException if {@code i < 0} or
 175      * {@code i > a.length - (this.length() * this.elementSize() / Byte.SIZE)}
 176      * @throws IndexOutOfBoundsException if the offset is {@code < 0},
 177      * or {@code > a.length},
 178      * for any vector lane index {@code N} where the mask at lane {@code N}
 179      * is set
 180      * {@code i >= a.length - (N * this.elementSize() / Byte.SIZE)}
 181      */
 182     @ForceInline
 183     public static DoubleVector fromByteArray(Species<Double> species, byte[] a, int ix, Mask<Double> m) {
 184         return zero(species).blend(fromByteArray(species, a, ix), m);
 185     }
 186 
 187     /**
 188      * Loads a vector from an array starting at offset.
 189      * <p>
 190      * For each vector lane, where {@code N} is the vector lane index, the
 191      * array element at index {@code i + N} is placed into the
 192      * resulting vector at lane index {@code N}.
 193      *
 194      * @param species species of desired vector
 195      * @param a the array
 196      * @param i the offset into the array
 197      * @return the vector loaded from an array
 198      * @throws IndexOutOfBoundsException if {@code i < 0}, or
 199      * {@code i > a.length - this.length()}
 200      */
 201     @ForceInline
 202     @SuppressWarnings("unchecked")
 203     public static DoubleVector fromArray(Species<Double> species, double[] a, int i){
 204         Objects.requireNonNull(a);
 205         i = VectorIntrinsics.checkIndex(i, a.length, species.length());
 206         return VectorIntrinsics.load((Class<DoubleVector>) species.boxType(), double.class, species.length(),
 207                                      a, (((long) i) << ARRAY_SHIFT) + Unsafe.ARRAY_DOUBLE_BASE_OFFSET,
 208                                      a, i, species,
 209                                      (c, idx, s) -> ((DoubleSpecies)s).op(n -> c[idx + n]));
 210     }
 211 
 212 
 213     /**
 214      * Loads a vector from an array starting at offset and using a mask.
 215      * <p>
 216      * For each vector lane, where {@code N} is the vector lane index,
 217      * if the mask lane at index {@code N} is set then the array element at
 218      * index {@code i + N} is placed into the resulting vector at lane index
 219      * {@code N}, otherwise the default element value is placed into the
 220      * resulting vector at lane index {@code N}.
 221      *
 222      * @param species species of desired vector
 223      * @param a the array
 224      * @param i the offset into the array
 225      * @param m the mask
 226      * @return the vector loaded from an array
 227      * @throws IndexOutOfBoundsException if {@code i < 0}, or
 228      * for any vector lane index {@code N} where the mask at lane {@code N}
 229      * is set {@code i > a.length - N}
 230      */
 231     @ForceInline
 232     public static DoubleVector fromArray(Species<Double> species, double[] a, int i, Mask<Double> m) {
 233         return zero(species).blend(fromArray(species, a, i), m);
 234     }
 235 
 236     /**
 237      * Loads a vector from an array using indexes obtained from an index
 238      * map.
 239      * <p>
 240      * For each vector lane, where {@code N} is the vector lane index, the
 241      * array element at index {@code i + indexMap[j + N]} is placed into the
 242      * resulting vector at lane index {@code N}.
 243      *
 244      * @param species species of desired vector
 245      * @param a the array
 246      * @param i the offset into the array, may be negative if relative
 247      * indexes in the index map compensate to produce a value within the
 248      * array bounds
 249      * @param indexMap the index map
 250      * @param j the offset into the index map
 251      * @return the vector loaded from an array
 252      * @throws IndexOutOfBoundsException if {@code j < 0}, or
 253      * {@code j > indexMap.length - this.length()},
 254      * or for any vector lane index {@code N} the result of
 255      * {@code i + indexMap[j + N]} is {@code < 0} or {@code >= a.length}
 256      */
 257     @ForceInline
 258     @SuppressWarnings("unchecked")
 259     public static DoubleVector fromArray(Species<Double> species, double[] a, int i, int[] indexMap, int j) {
 260         Objects.requireNonNull(a);
 261         Objects.requireNonNull(indexMap);
 262 
 263         if (species.length() == 1) {
 264           return DoubleVector.fromArray(species, a, i + indexMap[j]);
 265         }
 266 
 267         // Index vector: vix[0:n] = k -> i + indexMap[j + k]
 268         IntVector vix = IntVector.fromArray(IntVector.species(species.indexShape()), indexMap, j).add(i);
 269 
 270         vix = VectorIntrinsics.checkIndex(vix, a.length);
 271 
 272         return VectorIntrinsics.loadWithMap((Class<DoubleVector>) species.boxType(), double.class, species.length(),
 273                                             IntVector.species(species.indexShape()).boxType(), a, Unsafe.ARRAY_DOUBLE_BASE_OFFSET, vix,
 274                                             a, i, indexMap, j, species,
 275                                             (double[] c, int idx, int[] iMap, int idy, Species<Double> s) ->
 276                                                 ((DoubleSpecies)s).op(n -> c[idx + iMap[idy+n]]));
 277         }
 278 
 279     /**
 280      * Loads a vector from an array using indexes obtained from an index
 281      * map and using a mask.
 282      * <p>
 283      * For each vector lane, where {@code N} is the vector lane index,
 284      * if the mask lane at index {@code N} is set then the array element at
 285      * index {@code i + indexMap[j + N]} is placed into the resulting vector
 286      * at lane index {@code N}.
 287      *
 288      * @param species species of desired vector
 289      * @param a the array
 290      * @param i the offset into the array, may be negative if relative
 291      * indexes in the index map compensate to produce a value within the
 292      * array bounds
 293      * @param m the mask
 294      * @param indexMap the index map
 295      * @param j the offset into the index map
 296      * @return the vector loaded from an array
 297      * @throws IndexOutOfBoundsException if {@code j < 0}, or
 298      * {@code j > indexMap.length - this.length()},
 299      * or for any vector lane index {@code N} where the mask at lane
 300      * {@code N} is set the result of {@code i + indexMap[j + N]} is
 301      * {@code < 0} or {@code >= a.length}
 302      */
 303     @ForceInline
 304     @SuppressWarnings("unchecked")
 305     public static DoubleVector fromArray(Species<Double> species, double[] a, int i, Mask<Double> m, int[] indexMap, int j) {
 306         // @@@ This can result in out of bounds errors for unset mask lanes
 307         return zero(species).blend(fromArray(species, a, i, indexMap, j), m);
 308     }
 309 
 310 
 311     /**
 312      * Loads a vector from a {@link ByteBuffer byte buffer} starting at an
 313      * offset into the byte buffer.
 314      * <p>
 315      * Bytes are composed into primitive lane elements according to the
 316      * native byte order of the underlying platform.
 317      * <p>
 318      * This method behaves as if it returns the result of calling the
 319      * byte buffer, offset, and mask accepting
 320      * {@link #fromByteBuffer(Species<Double>, ByteBuffer, int, Mask)} method} as follows:
 321      * <pre>{@code
 322      *   return this.fromByteBuffer(b, i, this.maskAllTrue())
 323      * }</pre>
 324      *
 325      * @param species species of desired vector
 326      * @param bb the byte buffer
 327      * @param ix the offset into the byte buffer
 328      * @return a vector loaded from a byte buffer
 329      * @throws IndexOutOfBoundsException if the offset is {@code < 0},
 330      * or {@code > b.limit()},
 331      * or if there are fewer than
 332      * {@code this.length() * this.elementSize() / Byte.SIZE} bytes
 333      * remaining in the byte buffer from the given offset
 334      */
 335     @ForceInline
 336     @SuppressWarnings("unchecked")
 337     public static DoubleVector fromByteBuffer(Species<Double> species, ByteBuffer bb, int ix) {
 338         if (bb.order() != ByteOrder.nativeOrder()) {
 339             throw new IllegalArgumentException();
 340         }
 341         ix = VectorIntrinsics.checkIndex(ix, bb.limit(), species.bitSize() / Byte.SIZE);
 342         return VectorIntrinsics.load((Class<DoubleVector>) species.boxType(), double.class, species.length(),
 343                                      U.getReference(bb, BYTE_BUFFER_HB), U.getLong(bb, BUFFER_ADDRESS) + ix,
 344                                      bb, ix, species,
 345                                      (c, idx, s) -> {
 346                                          ByteBuffer bbc = c.duplicate().position(idx).order(ByteOrder.nativeOrder());
 347                                          DoubleBuffer tb = bbc.asDoubleBuffer();
 348                                          return ((DoubleSpecies)s).op(i -> tb.get());
 349                                      });
 350     }
 351 
 352     /**
 353      * Loads a vector from a {@link ByteBuffer byte buffer} starting at an
 354      * offset into the byte buffer and using a mask.
 355      * <p>
 356      * This method behaves as if the byte buffer is viewed as a primitive
 357      * {@link java.nio.Buffer buffer} for the primitive element type,
 358      * according to the native byte order of the underlying platform, and
 359      * the returned vector is loaded with a mask from a primitive array
 360      * obtained from the primitive buffer.
 361      * The following pseudocode expresses the behaviour, where
 362      * {@coce EBuffer} is the primitive buffer type, {@code e} is the
 363      * primitive element type, and {@code ESpecies<S>} is the primitive
 364      * species for {@code e}:
 365      * <pre>{@code
 366      * EBuffer eb = b.duplicate().
 367      *     order(ByteOrder.nativeOrder()).position(i).
 368      *     asEBuffer();
 369      * e[] es = new e[this.length()];
 370      * for (int n = 0; n < t.length; n++) {
 371      *     if (m.isSet(n))
 372      *         es[n] = eb.get(n);
 373      * }
 374      * Vector<E> r = ((ESpecies<S>)this).fromArray(es, 0, m);
 375      * }</pre>
 376      *
 377      * @param species species of desired vector
 378      * @param bb the byte buffer
 379      * @param ix the offset into the byte buffer
 380      * @param m the mask
 381      * @return a vector loaded from a byte buffer
 382      * @throws IndexOutOfBoundsException if the offset is {@code < 0},
 383      * or {@code > b.limit()},
 384      * for any vector lane index {@code N} where the mask at lane {@code N}
 385      * is set
 386      * {@code i >= b.limit() - (N * this.elementSize() / Byte.SIZE)}
 387      */
 388     @ForceInline
 389     public static DoubleVector fromByteBuffer(Species<Double> species, ByteBuffer bb, int ix, Mask<Double> m) {
 390         return zero(species).blend(fromByteBuffer(species, bb, ix), m);
 391     }
 392 
 393     /**
 394      * Returns a vector where all lane elements are set to the primitive
 395      * value {@code e}.
 396      *
 397      * @param s species of the desired vector
 398      * @param e the value
 399      * @return a vector of vector where all lane elements are set to
 400      * the primitive value {@code e}
 401      */
 402     @ForceInline
 403     @SuppressWarnings("unchecked")
 404     public static DoubleVector broadcast(Species<Double> s, double e) {
 405         return VectorIntrinsics.broadcastCoerced(
 406             (Class<DoubleVector>) s.boxType(), double.class, s.length(),
 407             Double.doubleToLongBits(e), s,
 408             ((bits, sp) -> ((DoubleSpecies)sp).op(i -> Double.longBitsToDouble((long)bits))));
 409     }
 410 
 411     /**
 412      * Returns a vector where each lane element is set to a given
 413      * primitive value.
 414      * <p>
 415      * For each vector lane, where {@code N} is the vector lane index, the
 416      * the primitive value at index {@code N} is placed into the resulting
 417      * vector at lane index {@code N}.
 418      *
 419      * @param s species of the desired vector
 420      * @param es the given primitive values
 421      * @return a vector where each lane element is set to a given primitive
 422      * value
 423      * @throws IndexOutOfBoundsException if {@code es.length < this.length()}
 424      */
 425     @ForceInline
 426     @SuppressWarnings("unchecked")
 427     public static DoubleVector scalars(Species<Double> s, double... es) {
 428         Objects.requireNonNull(es);
 429         int ix = VectorIntrinsics.checkIndex(0, es.length, s.length());
 430         return VectorIntrinsics.load((Class<DoubleVector>) s.boxType(), double.class, s.length(),
 431                                      es, Unsafe.ARRAY_DOUBLE_BASE_OFFSET,
 432                                      es, ix, s,
 433                                      (c, idx, sp) -> ((DoubleSpecies)sp).op(n -> c[idx + n]));
 434     }
 435 
 436     /**
 437      * Returns a vector where the first lane element is set to the primtive
 438      * value {@code e}, all other lane elements are set to the default
 439      * value.
 440      *
 441      * @param s species of the desired vector
 442      * @param e the value
 443      * @return a vector where the first lane element is set to the primitive
 444      * value {@code e}
 445      */
 446     @ForceInline
 447     public static final DoubleVector single(Species<Double> s, double e) {
 448         return zero(s).with(0, e);
 449     }
 450 
 451     /**
 452      * Returns a vector where each lane element is set to a randomly
 453      * generated primitive value.
 454      *
 455      * The semantics are equivalent to calling
 456      * {@link ThreadLocalRandom#nextDouble()}
 457      *
 458      * @param s species of the desired vector
 459      * @return a vector where each lane elements is set to a randomly
 460      * generated primitive value
 461      */
 462     public static DoubleVector random(Species<Double> s) {
 463         ThreadLocalRandom r = ThreadLocalRandom.current();
 464         return ((DoubleSpecies)s).op(i -> r.nextDouble());
 465     }
 466 
 467     // Ops
 468 
 469     @Override
 470     public abstract DoubleVector add(Vector<Double> v);
 471 
 472     /**
 473      * Adds this vector to the broadcast of an input scalar.
 474      * <p>
 475      * This is a vector binary operation where the primitive addition operation
 476      * ({@code +}) is applied to lane elements.
 477      *
 478      * @param s the input scalar
 479      * @return the result of adding this vector to the broadcast of an input
 480      * scalar
 481      */
 482     public abstract DoubleVector add(double s);
 483 
 484     @Override
 485     public abstract DoubleVector add(Vector<Double> v, Mask<Double> m);
 486 
 487     /**
 488      * Adds this vector to broadcast of an input scalar,
 489      * selecting lane elements controlled by a mask.
 490      * <p>
 491      * This is a vector binary operation where the primitive addition operation
 492      * ({@code +}) is applied to lane elements.
 493      *
 494      * @param s the input scalar
 495      * @param m the mask controlling lane selection
 496      * @return the result of adding this vector to the broadcast of an input
 497      * scalar
 498      */
 499     public abstract DoubleVector add(double s, Mask<Double> m);
 500 
 501     @Override
 502     public abstract DoubleVector sub(Vector<Double> v);
 503 
 504     /**
 505      * Subtracts the broadcast of an input scalar from this vector.
 506      * <p>
 507      * This is a vector binary operation where the primitive subtraction
 508      * operation ({@code -}) is applied to lane elements.
 509      *
 510      * @param s the input scalar
 511      * @return the result of subtracting the broadcast of an input
 512      * scalar from this vector
 513      */
 514     public abstract DoubleVector sub(double s);
 515 
 516     @Override
 517     public abstract DoubleVector sub(Vector<Double> v, Mask<Double> m);
 518 
 519     /**
 520      * Subtracts the broadcast of an input scalar from this vector, selecting
 521      * lane elements controlled by a mask.
 522      * <p>
 523      * This is a vector binary operation where the primitive subtraction
 524      * operation ({@code -}) is applied to lane elements.
 525      *
 526      * @param s the input scalar
 527      * @param m the mask controlling lane selection
 528      * @return the result of subtracting the broadcast of an input
 529      * scalar from this vector
 530      */
 531     public abstract DoubleVector sub(double s, Mask<Double> m);
 532 
 533     @Override
 534     public abstract DoubleVector mul(Vector<Double> v);
 535 
 536     /**
 537      * Multiplies this vector with the broadcast of an input scalar.
 538      * <p>
 539      * This is a vector binary operation where the primitive multiplication
 540      * operation ({@code *}) is applied to lane elements.
 541      *
 542      * @param s the input scalar
 543      * @return the result of multiplying this vector with the broadcast of an
 544      * input scalar
 545      */
 546     public abstract DoubleVector mul(double s);
 547 
 548     @Override
 549     public abstract DoubleVector mul(Vector<Double> v, Mask<Double> m);
 550 
 551     /**
 552      * Multiplies this vector with the broadcast of an input scalar, selecting
 553      * lane elements controlled by a mask.
 554      * <p>
 555      * This is a vector binary operation where the primitive multiplication
 556      * operation ({@code *}) is applied to lane elements.
 557      *
 558      * @param s the input scalar
 559      * @param m the mask controlling lane selection
 560      * @return the result of multiplying this vector with the broadcast of an
 561      * input scalar
 562      */
 563     public abstract DoubleVector mul(double s, Mask<Double> m);
 564 
 565     @Override
 566     public abstract DoubleVector neg();
 567 
 568     @Override
 569     public abstract DoubleVector neg(Mask<Double> m);
 570 
 571     @Override
 572     public abstract DoubleVector abs();
 573 
 574     @Override
 575     public abstract DoubleVector abs(Mask<Double> m);
 576 
 577     @Override
 578     public abstract DoubleVector min(Vector<Double> v);
 579 
 580     @Override
 581     public abstract DoubleVector min(Vector<Double> v, Mask<Double> m);
 582 
 583     /**
 584      * Returns the minimum of this vector and the broadcast of an input scalar.
 585      * <p>
 586      * This is a vector binary operation where the operation
 587      * {@code (a, b) -> Math.min(a, b)} is applied to lane elements.
 588      *
 589      * @param s the input scalar
 590      * @return the minimum of this vector and the broadcast of an input scalar
 591      */
 592     public abstract DoubleVector min(double s);
 593 
 594     @Override
 595     public abstract DoubleVector max(Vector<Double> v);
 596 
 597     @Override
 598     public abstract DoubleVector max(Vector<Double> v, Mask<Double> m);
 599 
 600     /**
 601      * Returns the maximum of this vector and the broadcast of an input scalar.
 602      * <p>
 603      * This is a vector binary operation where the operation
 604      * {@code (a, b) -> Math.max(a, b)} is applied to lane elements.
 605      *
 606      * @param s the input scalar
 607      * @return the maximum of this vector and the broadcast of an input scalar
 608      */
 609     public abstract DoubleVector max(double s);
 610 
 611     @Override
 612     public abstract Mask<Double> equal(Vector<Double> v);
 613 
 614     /**
 615      * Tests if this vector is equal to the broadcast of an input scalar.
 616      * <p>
 617      * This is a vector binary test operation where the primitive equals
 618      * operation ({@code ==}) is applied to lane elements.
 619      *
 620      * @param s the input scalar
 621      * @return the result mask of testing if this vector is equal to the
 622      * broadcast of an input scalar
 623      */
 624     public abstract Mask<Double> equal(double s);
 625 
 626     @Override
 627     public abstract Mask<Double> notEqual(Vector<Double> v);
 628 
 629     /**
 630      * Tests if this vector is not equal to the broadcast of an input scalar.
 631      * <p>
 632      * This is a vector binary test operation where the primitive not equals
 633      * operation ({@code !=}) is applied to lane elements.
 634      *
 635      * @param s the input scalar
 636      * @return the result mask of testing if this vector is not equal to the
 637      * broadcast of an input scalar
 638      */
 639     public abstract Mask<Double> notEqual(double s);
 640 
 641     @Override
 642     public abstract Mask<Double> lessThan(Vector<Double> v);
 643 
 644     /**
 645      * Tests if this vector is less than the broadcast of an input scalar.
 646      * <p>
 647      * This is a vector binary test operation where the primitive less than
 648      * operation ({@code <}) is applied to lane elements.
 649      *
 650      * @param s the input scalar
 651      * @return the mask result of testing if this vector is less than the
 652      * broadcast of an input scalar
 653      */
 654     public abstract Mask<Double> lessThan(double s);
 655 
 656     @Override
 657     public abstract Mask<Double> lessThanEq(Vector<Double> v);
 658 
 659     /**
 660      * Tests if this vector is less or equal to the broadcast of an input scalar.
 661      * <p>
 662      * This is a vector binary test operation where the primitive less than
 663      * or equal to operation ({@code <=}) is applied to lane elements.
 664      *
 665      * @param s the input scalar
 666      * @return the mask result of testing if this vector is less than or equal
 667      * to the broadcast of an input scalar
 668      */
 669     public abstract Mask<Double> lessThanEq(double s);
 670 
 671     @Override
 672     public abstract Mask<Double> greaterThan(Vector<Double> v);
 673 
 674     /**
 675      * Tests if this vector is greater than the broadcast of an input scalar.
 676      * <p>
 677      * This is a vector binary test operation where the primitive greater than
 678      * operation ({@code >}) is applied to lane elements.
 679      *
 680      * @param s the input scalar
 681      * @return the mask result of testing if this vector is greater than the
 682      * broadcast of an input scalar
 683      */
 684     public abstract Mask<Double> greaterThan(double s);
 685 
 686     @Override
 687     public abstract Mask<Double> greaterThanEq(Vector<Double> v);
 688 
 689     /**
 690      * Tests if this vector is greater than or equal to the broadcast of an
 691      * input scalar.
 692      * <p>
 693      * This is a vector binary test operation where the primitive greater than
 694      * or equal to operation ({@code >=}) is applied to lane elements.
 695      *
 696      * @param s the input scalar
 697      * @return the mask result of testing if this vector is greater than or
 698      * equal to the broadcast of an input scalar
 699      */
 700     public abstract Mask<Double> greaterThanEq(double s);
 701 
 702     @Override
 703     public abstract DoubleVector blend(Vector<Double> v, Mask<Double> m);
 704 
 705     /**
 706      * Blends the lane elements of this vector with those of the broadcast of an
 707      * input scalar, selecting lanes controlled by a mask.
 708      * <p>
 709      * For each lane of the mask, at lane index {@code N}, if the mask lane
 710      * is set then the lane element at {@code N} from the input vector is
 711      * selected and placed into the resulting vector at {@code N},
 712      * otherwise the the lane element at {@code N} from this input vector is
 713      * selected and placed into the resulting vector at {@code N}.
 714      *
 715      * @param s the input scalar
 716      * @param m the mask controlling lane selection
 717      * @return the result of blending the lane elements of this vector with
 718      * those of the broadcast of an input scalar
 719      */
 720     public abstract DoubleVector blend(double s, Mask<Double> m);
 721 
 722     @Override
 723     public abstract DoubleVector rearrange(Vector<Double> v,
 724                                                       Shuffle<Double> s, Mask<Double> m);
 725 
 726     @Override
 727     public abstract DoubleVector rearrange(Shuffle<Double> m);
 728 
 729     @Override
 730     public abstract DoubleVector reshape(Species<Double> s);
 731 
 732     @Override
 733     public abstract DoubleVector rotateEL(int i);
 734 
 735     @Override
 736     public abstract DoubleVector rotateER(int i);
 737 
 738     @Override
 739     public abstract DoubleVector shiftEL(int i);
 740 
 741     @Override
 742     public abstract DoubleVector shiftER(int i);
 743 
 744     /**
 745      * Divides this vector by an input vector.
 746      * <p>
 747      * This is a vector binary operation where the primitive division
 748      * operation ({@code /}) is applied to lane elements.
 749      *
 750      * @param v the input vector
 751      * @return the result of dividing this vector by the input vector
 752      */
 753     public abstract DoubleVector div(Vector<Double> v);
 754 
 755     /**
 756      * Divides this vector by the broadcast of an input scalar.
 757      * <p>
 758      * This is a vector binary operation where the primitive division
 759      * operation ({@code /}) is applied to lane elements.
 760      *
 761      * @param s the input scalar
 762      * @return the result of dividing this vector by the broadcast of an input
 763      * scalar
 764      */
 765     public abstract DoubleVector div(double s);
 766 
 767     /**
 768      * Divides this vector by an input vector, selecting lane elements
 769      * controlled by a mask.
 770      * <p>
 771      * This is a vector binary operation where the primitive division
 772      * operation ({@code /}) is applied to lane elements.
 773      *
 774      * @param v the input vector
 775      * @param m the mask controlling lane selection
 776      * @return the result of dividing this vector by the input vector
 777      */
 778     public abstract DoubleVector div(Vector<Double> v, Mask<Double> m);
 779 
 780     /**
 781      * Divides this vector by the broadcast of an input scalar, selecting lane
 782      * elements controlled by a mask.
 783      * <p>
 784      * This is a vector binary operation where the primitive division
 785      * operation ({@code /}) is applied to lane elements.
 786      *
 787      * @param s the input scalar
 788      * @param m the mask controlling lane selection
 789      * @return the result of dividing this vector by the broadcast of an input
 790      * scalar
 791      */
 792     public abstract DoubleVector div(double s, Mask<Double> m);
 793 
 794     /**
 795      * Calculates the square root of this vector.
 796      * <p>
 797      * This is a vector unary operation where the {@link Math#sqrt} operation
 798      * is applied to lane elements.
 799      *
 800      * @return the square root of this vector
 801      */
 802     public abstract DoubleVector sqrt();
 803 
 804     /**
 805      * Calculates the square root of this vector, selecting lane elements
 806      * controlled by a mask.
 807      * <p>
 808      * This is a vector unary operation where the {@link Math#sqrt} operation
 809      * is applied to lane elements.
 810      *
 811      * @param m the mask controlling lane selection
 812      * @return the square root of this vector
 813      */
 814     public DoubleVector sqrt(Mask<Double> m) {
 815         return uOp(m, (i, a) -> (double) Math.sqrt((double) a));
 816     }
 817 
 818     /**
 819      * Calculates the trigonometric tangent of this vector.
 820      * <p>
 821      * This is a vector unary operation with same semantic definition as
 822      * {@link Math#tan} operation applied to lane elements.
 823      * The implementation is not required to return same
 824      * results as {@link Math#tan}, but adheres to rounding, monotonicity,
 825      * and special case semantics as defined in the {@link Math#tan}
 826      * specifications. The computed result will be within 1 ulp of the
 827      * exact result.
 828      *
 829      * @return the tangent of this vector
 830      */
 831     public DoubleVector tan() {
 832         return uOp((i, a) -> (double) Math.tan((double) a));
 833     }
 834 
 835     /**
 836      * Calculates the trigonometric tangent of this vector, selecting lane
 837      * elements controlled by a mask.
 838      * <p>
 839      * Semantics for rounding, monotonicity, and special cases are
 840      * described in {@link DoubleVector#tan}
 841      *
 842      * @param m the mask controlling lane selection
 843      * @return the tangent of this vector
 844      */
 845     public DoubleVector tan(Mask<Double> m) {
 846         return uOp(m, (i, a) -> (double) Math.tan((double) a));
 847     }
 848 
 849     /**
 850      * Calculates the hyperbolic tangent of this vector.
 851      * <p>
 852      * This is a vector unary operation with same semantic definition as
 853      * {@link Math#tanh} operation applied to lane elements.
 854      * The implementation is not required to return same
 855      * results as {@link Math#tanh}, but adheres to rounding, monotonicity,
 856      * and special case semantics as defined in the {@link Math#tanh}
 857      * specifications. The computed result will be within 2.5 ulps of the
 858      * exact result.
 859      *
 860      * @return the hyperbolic tangent of this vector
 861      */
 862     public DoubleVector tanh() {
 863         return uOp((i, a) -> (double) Math.tanh((double) a));
 864     }
 865 
 866     /**
 867      * Calculates the hyperbolic tangent of this vector, selecting lane elements
 868      * controlled by a mask.
 869      * <p>
 870      * Semantics for rounding, monotonicity, and special cases are
 871      * described in {@link DoubleVector#tanh}
 872      *
 873      * @param m the mask controlling lane selection
 874      * @return the hyperbolic tangent of this vector
 875      */
 876     public DoubleVector tanh(Mask<Double> m) {
 877         return uOp(m, (i, a) -> (double) Math.tanh((double) a));
 878     }
 879 
 880     /**
 881      * Calculates the trigonometric sine of this vector.
 882      * <p>
 883      * This is a vector unary operation with same semantic definition as
 884      * {@link Math#sin} operation applied to lane elements.
 885      * The implementation is not required to return same
 886      * results as {@link Math#sin}, but adheres to rounding, monotonicity,
 887      * and special case semantics as defined in the {@link Math#sin}
 888      * specifications. The computed result will be within 1 ulp of the
 889      * exact result.
 890      *
 891      * @return the sine of this vector
 892      */
 893     public DoubleVector sin() {
 894         return uOp((i, a) -> (double) Math.sin((double) a));
 895     }
 896 
 897     /**
 898      * Calculates the trigonometric sine of this vector, selecting lane elements
 899      * controlled by a mask.
 900      * <p>
 901      * Semantics for rounding, monotonicity, and special cases are
 902      * described in {@link DoubleVector#sin}
 903      *
 904      * @param m the mask controlling lane selection
 905      * @return the sine of this vector
 906      */
 907     public DoubleVector sin(Mask<Double> m) {
 908         return uOp(m, (i, a) -> (double) Math.sin((double) a));
 909     }
 910 
 911     /**
 912      * Calculates the hyperbolic sine of this vector.
 913      * <p>
 914      * This is a vector unary operation with same semantic definition as
 915      * {@link Math#sinh} operation applied to lane elements.
 916      * The implementation is not required to return same
 917      * results as  {@link Math#sinh}, but adheres to rounding, monotonicity,
 918      * and special case semantics as defined in the {@link Math#sinh}
 919      * specifications. The computed result will be within 2.5 ulps of the
 920      * exact result.
 921      *
 922      * @return the hyperbolic sine of this vector
 923      */
 924     public DoubleVector sinh() {
 925         return uOp((i, a) -> (double) Math.sinh((double) a));
 926     }
 927 
 928     /**
 929      * Calculates the hyperbolic sine of this vector, selecting lane elements
 930      * controlled by a mask.
 931      * <p>
 932      * Semantics for rounding, monotonicity, and special cases are
 933      * described in {@link DoubleVector#sinh}
 934      *
 935      * @param m the mask controlling lane selection
 936      * @return the hyperbolic sine of this vector
 937      */
 938     public DoubleVector sinh(Mask<Double> m) {
 939         return uOp(m, (i, a) -> (double) Math.sinh((double) a));
 940     }
 941 
 942     /**
 943      * Calculates the trigonometric cosine of this vector.
 944      * <p>
 945      * This is a vector unary operation with same semantic definition as
 946      * {@link Math#cos} operation applied to lane elements.
 947      * The implementation is not required to return same
 948      * results as {@link Math#cos}, but adheres to rounding, monotonicity,
 949      * and special case semantics as defined in the {@link Math#cos}
 950      * specifications. The computed result will be within 1 ulp of the
 951      * exact result.
 952      *
 953      * @return the cosine of this vector
 954      */
 955     public DoubleVector cos() {
 956         return uOp((i, a) -> (double) Math.cos((double) a));
 957     }
 958 
 959     /**
 960      * Calculates the trigonometric cosine of this vector, selecting lane
 961      * elements controlled by a mask.
 962      * <p>
 963      * Semantics for rounding, monotonicity, and special cases are
 964      * described in {@link DoubleVector#cos}
 965      *
 966      * @param m the mask controlling lane selection
 967      * @return the cosine of this vector
 968      */
 969     public DoubleVector cos(Mask<Double> m) {
 970         return uOp(m, (i, a) -> (double) Math.cos((double) a));
 971     }
 972 
 973     /**
 974      * Calculates the hyperbolic cosine of this vector.
 975      * <p>
 976      * This is a vector unary operation with same semantic definition as
 977      * {@link Math#cosh} operation applied to lane elements.
 978      * The implementation is not required to return same
 979      * results as {@link Math#cosh}, but adheres to rounding, monotonicity,
 980      * and special case semantics as defined in the {@link Math#cosh}
 981      * specifications. The computed result will be within 2.5 ulps of the
 982      * exact result.
 983      *
 984      * @return the hyperbolic cosine of this vector
 985      */
 986     public DoubleVector cosh() {
 987         return uOp((i, a) -> (double) Math.cosh((double) a));
 988     }
 989 
 990     /**
 991      * Calculates the hyperbolic cosine of this vector, selecting lane elements
 992      * controlled by a mask.
 993      * <p>
 994      * Semantics for rounding, monotonicity, and special cases are
 995      * described in {@link DoubleVector#cosh}
 996      *
 997      * @param m the mask controlling lane selection
 998      * @return the hyperbolic cosine of this vector
 999      */
1000     public DoubleVector cosh(Mask<Double> m) {
1001         return uOp(m, (i, a) -> (double) Math.cosh((double) a));
1002     }
1003 
1004     /**
1005      * Calculates the arc sine of this vector.
1006      * <p>
1007      * This is a vector unary operation with same semantic definition as
1008      * {@link Math#asin} operation applied to lane elements.
1009      * The implementation is not required to return same
1010      * results as {@link Math#asin}, but adheres to rounding, monotonicity,
1011      * and special case semantics as defined in the {@link Math#asin}
1012      * specifications. The computed result will be within 1 ulp of the
1013      * exact result.
1014      *
1015      * @return the arc sine of this vector
1016      */
1017     public DoubleVector asin() {
1018         return uOp((i, a) -> (double) Math.asin((double) a));
1019     }
1020 
1021     /**
1022      * Calculates the arc sine of this vector, selecting lane elements
1023      * controlled by a mask.
1024      * <p>
1025      * Semantics for rounding, monotonicity, and special cases are
1026      * described in {@link DoubleVector#asin}
1027      *
1028      * @param m the mask controlling lane selection
1029      * @return the arc sine of this vector
1030      */
1031     public DoubleVector asin(Mask<Double> m) {
1032         return uOp(m, (i, a) -> (double) Math.asin((double) a));
1033     }
1034 
1035     /**
1036      * Calculates the arc cosine of this vector.
1037      * <p>
1038      * This is a vector unary operation with same semantic definition as
1039      * {@link Math#acos} operation applied to lane elements.
1040      * The implementation is not required to return same
1041      * results as {@link Math#acos}, but adheres to rounding, monotonicity,
1042      * and special case semantics as defined in the {@link Math#acos}
1043      * specifications. The computed result will be within 1 ulp of the
1044      * exact result.
1045      *
1046      * @return the arc cosine of this vector
1047      */
1048     public DoubleVector acos() {
1049         return uOp((i, a) -> (double) Math.acos((double) a));
1050     }
1051 
1052     /**
1053      * Calculates the arc cosine of this vector, selecting lane elements
1054      * controlled by a mask.
1055      * <p>
1056      * Semantics for rounding, monotonicity, and special cases are
1057      * described in {@link DoubleVector#acos}
1058      *
1059      * @param m the mask controlling lane selection
1060      * @return the arc cosine of this vector
1061      */
1062     public DoubleVector acos(Mask<Double> m) {
1063         return uOp(m, (i, a) -> (double) Math.acos((double) a));
1064     }
1065 
1066     /**
1067      * Calculates the arc tangent of this vector.
1068      * <p>
1069      * This is a vector unary operation with same semantic definition as
1070      * {@link Math#atan} operation applied to lane elements.
1071      * The implementation is not required to return same
1072      * results as {@link Math#atan}, but adheres to rounding, monotonicity,
1073      * and special case semantics as defined in the {@link Math#atan}
1074      * specifications. The computed result will be within 1 ulp of the
1075      * exact result.
1076      *
1077      * @return the arc tangent of this vector
1078      */
1079     public DoubleVector atan() {
1080         return uOp((i, a) -> (double) Math.atan((double) a));
1081     }
1082 
1083     /**
1084      * Calculates the arc tangent of this vector, selecting lane elements
1085      * controlled by a mask.
1086      * <p>
1087      * Semantics for rounding, monotonicity, and special cases are
1088      * described in {@link DoubleVector#atan}
1089      *
1090      * @param m the mask controlling lane selection
1091      * @return the arc tangent of this vector
1092      */
1093     public DoubleVector atan(Mask<Double> m) {
1094         return uOp(m, (i, a) -> (double) Math.atan((double) a));
1095     }
1096 
1097     /**
1098      * Calculates the arc tangent of this vector divided by an input vector.
1099      * <p>
1100      * This is a vector binary operation with same semantic definition as
1101      * {@link Math#atan2} operation applied to lane elements.
1102      * The implementation is not required to return same
1103      * results as {@link Math#atan2}, but adheres to rounding, monotonicity,
1104      * and special case semantics as defined in the {@link Math#atan2}
1105      * specifications. The computed result will be within 2 ulps of the
1106      * exact result.
1107      *
1108      * @param v the input vector
1109      * @return the arc tangent of this vector divided by the input vector
1110      */
1111     public DoubleVector atan2(Vector<Double> v) {
1112         return bOp(v, (i, a, b) -> (double) Math.atan2((double) a, (double) b));
1113     }
1114 
1115     /**
1116      * Calculates the arc tangent of this vector divided by the broadcast of an
1117      * an input scalar.
1118      * <p>
1119      * This is a vector binary operation with same semantic definition as
1120      * {@link Math#atan2} operation applied to lane elements.
1121      * The implementation is not required to return same
1122      * results as {@link Math#atan2}, but adheres to rounding, monotonicity,
1123      * and special case semantics as defined in the {@link Math#atan2}
1124      * specifications. The computed result will be within 1 ulp of the
1125      * exact result.
1126      *
1127      * @param s the input scalar
1128      * @return the arc tangent of this vector over the input vector
1129      */
1130     public abstract DoubleVector atan2(double s);
1131 
1132     /**
1133      * Calculates the arc tangent of this vector divided by an input vector,
1134      * selecting lane elements controlled by a mask.
1135      * <p>
1136      * Semantics for rounding, monotonicity, and special cases are
1137      * described in {@link DoubleVector#atan2}
1138      *
1139      * @param v the input vector
1140      * @param m the mask controlling lane selection
1141      * @return the arc tangent of this vector divided by the input vector
1142      */
1143     public DoubleVector atan2(Vector<Double> v, Mask<Double> m) {
1144         return bOp(v, m, (i, a, b) -> (double) Math.atan2((double) a, (double) b));
1145     }
1146 
1147     /**
1148      * Calculates the arc tangent of this vector divided by the broadcast of an
1149      * an input scalar, selecting lane elements controlled by a mask.
1150      * <p>
1151      * Semantics for rounding, monotonicity, and special cases are
1152      * described in {@link DoubleVector#atan2}
1153      *
1154      * @param s the input scalar
1155      * @param m the mask controlling lane selection
1156      * @return the arc tangent of this vector over the input vector
1157      */
1158     public abstract DoubleVector atan2(double s, Mask<Double> m);
1159 
1160     /**
1161      * Calculates the cube root of this vector.
1162      * <p>
1163      * This is a vector unary operation with same semantic definition as
1164      * {@link Math#cbrt} operation applied to lane elements.
1165      * The implementation is not required to return same
1166      * results as {@link Math#cbrt}, but adheres to rounding, monotonicity,
1167      * and special case semantics as defined in the {@link Math#cbrt}
1168      * specifications. The computed result will be within 1 ulp of the
1169      * exact result.
1170      *
1171      * @return the cube root of this vector
1172      */
1173     public DoubleVector cbrt() {
1174         return uOp((i, a) -> (double) Math.cbrt((double) a));
1175     }
1176 
1177     /**
1178      * Calculates the cube root of this vector, selecting lane elements
1179      * controlled by a mask.
1180      * <p>
1181      * Semantics for rounding, monotonicity, and special cases are
1182      * described in {@link DoubleVector#cbrt}
1183      *
1184      * @param m the mask controlling lane selection
1185      * @return the cube root of this vector
1186      */
1187     public DoubleVector cbrt(Mask<Double> m) {
1188         return uOp(m, (i, a) -> (double) Math.cbrt((double) a));
1189     }
1190 
1191     /**
1192      * Calculates the natural logarithm of this vector.
1193      * <p>
1194      * This is a vector unary operation with same semantic definition as
1195      * {@link Math#log} operation applied to lane elements.
1196      * The implementation is not required to return same
1197      * results as {@link Math#log}, but adheres to rounding, monotonicity,
1198      * and special case semantics as defined in the {@link Math#log}
1199      * specifications. The computed result will be within 1 ulp of the
1200      * exact result.
1201      *
1202      * @return the natural logarithm of this vector
1203      */
1204     public DoubleVector log() {
1205         return uOp((i, a) -> (double) Math.log((double) a));
1206     }
1207 
1208     /**
1209      * Calculates the natural logarithm of this vector, selecting lane elements
1210      * controlled by a mask.
1211      * <p>
1212      * Semantics for rounding, monotonicity, and special cases are
1213      * described in {@link DoubleVector#log}
1214      *
1215      * @param m the mask controlling lane selection
1216      * @return the natural logarithm of this vector
1217      */
1218     public DoubleVector log(Mask<Double> m) {
1219         return uOp(m, (i, a) -> (double) Math.log((double) a));
1220     }
1221 
1222     /**
1223      * Calculates the base 10 logarithm of this vector.
1224      * <p>
1225      * This is a vector unary operation with same semantic definition as
1226      * {@link Math#log10} operation applied to lane elements.
1227      * The implementation is not required to return same
1228      * results as {@link Math#log10}, but adheres to rounding, monotonicity,
1229      * and special case semantics as defined in the {@link Math#log10}
1230      * specifications. The computed result will be within 1 ulp of the
1231      * exact result.
1232      *
1233      * @return the base 10 logarithm of this vector
1234      */
1235     public DoubleVector log10() {
1236         return uOp((i, a) -> (double) Math.log10((double) a));
1237     }
1238 
1239     /**
1240      * Calculates the base 10 logarithm of this vector, selecting lane elements
1241      * controlled by a mask.
1242      * <p>
1243      * Semantics for rounding, monotonicity, and special cases are
1244      * described in {@link DoubleVector#log10}
1245      *
1246      * @param m the mask controlling lane selection
1247      * @return the base 10 logarithm of this vector
1248      */
1249     public DoubleVector log10(Mask<Double> m) {
1250         return uOp(m, (i, a) -> (double) Math.log10((double) a));
1251     }
1252 
1253     /**
1254      * Calculates the natural logarithm of the sum of this vector and the
1255      * broadcast of {@code 1}.
1256      * <p>
1257      * This is a vector unary operation with same semantic definition as
1258      * {@link Math#log1p} operation applied to lane elements.
1259      * The implementation is not required to return same
1260      * results as  {@link Math#log1p}, but adheres to rounding, monotonicity,
1261      * and special case semantics as defined in the {@link Math#log1p}
1262      * specifications. The computed result will be within 1 ulp of the
1263      * exact result.
1264      *
1265      * @return the natural logarithm of the sum of this vector and the broadcast
1266      * of {@code 1}
1267      */
1268     public DoubleVector log1p() {
1269         return uOp((i, a) -> (double) Math.log1p((double) a));
1270     }
1271 
1272     /**
1273      * Calculates the natural logarithm of the sum of this vector and the
1274      * broadcast of {@code 1}, selecting lane elements controlled by a mask.
1275      * <p>
1276      * Semantics for rounding, monotonicity, and special cases are
1277      * described in {@link DoubleVector#log1p}
1278      *
1279      * @param m the mask controlling lane selection
1280      * @return the natural logarithm of the sum of this vector and the broadcast
1281      * of {@code 1}
1282      */
1283     public DoubleVector log1p(Mask<Double> m) {
1284         return uOp(m, (i, a) -> (double) Math.log1p((double) a));
1285     }
1286 
1287     /**
1288      * Calculates this vector raised to the power of an input vector.
1289      * <p>
1290      * This is a vector binary operation with same semantic definition as
1291      * {@link Math#pow} operation applied to lane elements.
1292      * The implementation is not required to return same
1293      * results as {@link Math#pow}, but adheres to rounding, monotonicity,
1294      * and special case semantics as defined in the {@link Math#pow}
1295      * specifications. The computed result will be within 1 ulp of the
1296      * exact result.
1297      *
1298      * @param v the input vector
1299      * @return this vector raised to the power of an input vector
1300      */
1301     public DoubleVector pow(Vector<Double> v) {
1302         return bOp(v, (i, a, b) -> (double) Math.pow((double) a, (double) b));
1303     }
1304 
1305     /**
1306      * Calculates this vector raised to the power of the broadcast of an input
1307      * scalar.
1308      * <p>
1309      * This is a vector binary operation with same semantic definition as
1310      * {@link Math#pow} operation applied to lane elements.
1311      * The implementation is not required to return same
1312      * results as {@link Math#pow}, but adheres to rounding, monotonicity,
1313      * and special case semantics as defined in the {@link Math#pow}
1314      * specifications. The computed result will be within 1 ulp of the
1315      * exact result.
1316      *
1317      * @param s the input scalar
1318      * @return this vector raised to the power of the broadcast of an input
1319      * scalar.
1320      */
1321     public abstract DoubleVector pow(double s);
1322 
1323     /**
1324      * Calculates this vector raised to the power of an input vector, selecting
1325      * lane elements controlled by a mask.
1326      * <p>
1327      * Semantics for rounding, monotonicity, and special cases are
1328      * described in {@link DoubleVector#pow}
1329      *
1330      * @param v the input vector
1331      * @param m the mask controlling lane selection
1332      * @return this vector raised to the power of an input vector
1333      */
1334     public DoubleVector pow(Vector<Double> v, Mask<Double> m) {
1335         return bOp(v, m, (i, a, b) -> (double) Math.pow((double) a, (double) b));
1336     }
1337 
1338     /**
1339      * Calculates this vector raised to the power of the broadcast of an input
1340      * scalar, selecting lane elements controlled by a mask.
1341      * <p>
1342      * Semantics for rounding, monotonicity, and special cases are
1343      * described in {@link DoubleVector#pow}
1344      *
1345      * @param s the input scalar
1346      * @param m the mask controlling lane selection
1347      * @return this vector raised to the power of the broadcast of an input
1348      * scalar.
1349      */
1350     public abstract DoubleVector pow(double s, Mask<Double> m);
1351 
1352     /**
1353      * Calculates the broadcast of Euler's number {@code e} raised to the power
1354      * of this vector.
1355      * <p>
1356      * This is a vector unary operation with same semantic definition as
1357      * {@link Math#exp} operation applied to lane elements.
1358      * The implementation is not required to return same
1359      * results as {@link Math#exp}, but adheres to rounding, monotonicity,
1360      * and special case semantics as defined in the {@link Math#exp}
1361      * specifications. The computed result will be within 1 ulp of the
1362      * exact result.
1363      *
1364      * @return the broadcast of Euler's number {@code e} raised to the power of
1365      * this vector
1366      */
1367     public DoubleVector exp() {
1368         return uOp((i, a) -> (double) Math.exp((double) a));
1369     }
1370 
1371     /**
1372      * Calculates the broadcast of Euler's number {@code e} raised to the power
1373      * of this vector, selecting lane elements controlled by a mask.
1374      * <p>
1375      * Semantics for rounding, monotonicity, and special cases are
1376      * described in {@link DoubleVector#exp}
1377      *
1378      * @param m the mask controlling lane selection
1379      * @return the broadcast of Euler's number {@code e} raised to the power of
1380      * this vector
1381      */
1382     public DoubleVector exp(Mask<Double> m) {
1383         return uOp(m, (i, a) -> (double) Math.exp((double) a));
1384     }
1385 
1386     /**
1387      * Calculates the broadcast of Euler's number {@code e} raised to the power
1388      * of this vector minus the broadcast of {@code -1}.
1389      * More specifically as if the following (ignoring any differences in
1390      * numerical accuracy):
1391      * <pre>{@code
1392      *   this.exp().sub(this.species().broadcast(1))
1393      * }</pre>
1394      * <p>
1395      * This is a vector unary operation with same semantic definition as
1396      * {@link Math#expm1} operation applied to lane elements.
1397      * The implementation is not required to return same
1398      * results as {@link Math#expm1}, but adheres to rounding, monotonicity,
1399      * and special case semantics as defined in the {@link Math#expm1}
1400      * specifications. The computed result will be within 1 ulp of the
1401      * exact result.
1402      *
1403      * @return the broadcast of Euler's number {@code e} raised to the power of
1404      * this vector minus the broadcast of {@code -1}
1405      */
1406     public DoubleVector expm1() {
1407         return uOp((i, a) -> (double) Math.expm1((double) a));
1408     }
1409 
1410     /**
1411      * Calculates the broadcast of Euler's number {@code e} raised to the power
1412      * of this vector minus the broadcast of {@code -1}, selecting lane elements
1413      * controlled by a mask
1414      * More specifically as if the following (ignoring any differences in
1415      * numerical accuracy):
1416      * <pre>{@code
1417      *   this.exp(m).sub(this.species().broadcast(1), m)
1418      * }</pre>
1419      * <p>
1420      * Semantics for rounding, monotonicity, and special cases are
1421      * described in {@link DoubleVector#expm1}
1422      *
1423      * @param m the mask controlling lane selection
1424      * @return the broadcast of Euler's number {@code e} raised to the power of
1425      * this vector minus the broadcast of {@code -1}
1426      */
1427     public DoubleVector expm1(Mask<Double> m) {
1428         return uOp(m, (i, a) -> (double) Math.expm1((double) a));
1429     }
1430 
1431     /**
1432      * Calculates the product of this vector and a first input vector summed
1433      * with a second input vector.
1434      * More specifically as if the following (ignoring any differences in
1435      * numerical accuracy):
1436      * <pre>{@code
1437      *   this.mul(v1).add(v2)
1438      * }</pre>
1439      * <p>
1440      * This is a vector ternary operation where the {@link Math#fma} operation
1441      * is applied to lane elements.
1442      *
1443      * @param v1 the first input vector
1444      * @param v2 the second input vector
1445      * @return the product of this vector and the first input vector summed with
1446      * the second input vector
1447      */
1448     public abstract DoubleVector fma(Vector<Double> v1, Vector<Double> v2);
1449 
1450     /**
1451      * Calculates the product of this vector and the broadcast of a first input
1452      * scalar summed with the broadcast of a second input scalar.
1453      * More specifically as if the following:
1454      * <pre>{@code
1455      *   this.fma(this.species().broadcast(s1), this.species().broadcast(s2))
1456      * }</pre>
1457      * <p>
1458      * This is a vector ternary operation where the {@link Math#fma} operation
1459      * is applied to lane elements.
1460      *
1461      * @param s1 the first input scalar
1462      * @param s2 the second input scalar
1463      * @return the product of this vector and the broadcast of a first input
1464      * scalar summed with the broadcast of a second input scalar
1465      */
1466     public abstract DoubleVector fma(double s1, double s2);
1467 
1468     /**
1469      * Calculates the product of this vector and a first input vector summed
1470      * with a second input vector, selecting lane elements controlled by a mask.
1471      * More specifically as if the following (ignoring any differences in
1472      * numerical accuracy):
1473      * <pre>{@code
1474      *   this.mul(v1, m).add(v2, m)
1475      * }</pre>
1476      * <p>
1477      * This is a vector ternary operation where the {@link Math#fma} operation
1478      * is applied to lane elements.
1479      *
1480      * @param v1 the first input vector
1481      * @param v2 the second input vector
1482      * @param m the mask controlling lane selection
1483      * @return the product of this vector and the first input vector summed with
1484      * the second input vector
1485      */
1486     public DoubleVector fma(Vector<Double> v1, Vector<Double> v2, Mask<Double> m) {
1487         return tOp(v1, v2, m, (i, a, b, c) -> Math.fma(a, b, c));
1488     }
1489 
1490     /**
1491      * Calculates the product of this vector and the broadcast of a first input
1492      * scalar summed with the broadcast of a second input scalar, selecting lane
1493      * elements controlled by a mask
1494      * More specifically as if the following:
1495      * <pre>{@code
1496      *   this.fma(this.species().broadcast(s1), this.species().broadcast(s2), m)
1497      * }</pre>
1498      * <p>
1499      * This is a vector ternary operation where the {@link Math#fma} operation
1500      * is applied to lane elements.
1501      *
1502      * @param s1 the first input scalar
1503      * @param s2 the second input scalar
1504      * @param m the mask controlling lane selection
1505      * @return the product of this vector and the broadcast of a first input
1506      * scalar summed with the broadcast of a second input scalar
1507      */
1508     public abstract DoubleVector fma(double s1, double s2, Mask<Double> m);
1509 
1510     /**
1511      * Calculates square root of the sum of the squares of this vector and an
1512      * input vector.
1513      * More specifically as if the following (ignoring any differences in
1514      * numerical accuracy):
1515      * <pre>{@code
1516      *   this.mul(this).add(v.mul(v)).sqrt()
1517      * }</pre>
1518      * <p>
1519      * This is a vector binary operation with same semantic definition as
1520      * {@link Math#hypot} operation applied to lane elements.
1521      * The implementation is not required to return same
1522      * results as {@link Math#hypot}, but adheres to rounding, monotonicity,
1523      * and special case semantics as defined in the {@link Math#hypot}
1524      * specifications. The computed result will be within 1 ulp of the
1525      * exact result.
1526      *
1527      * @param v the input vector
1528      * @return square root of the sum of the squares of this vector and an input
1529      * vector
1530      */
1531     public DoubleVector hypot(Vector<Double> v) {
1532         return bOp(v, (i, a, b) -> (double) Math.hypot((double) a, (double) b));
1533     }
1534 
1535     /**
1536      * Calculates square root of the sum of the squares of this vector and the
1537      * broadcast of an input scalar.
1538      * More specifically as if the following (ignoring any differences in
1539      * numerical accuracy):
1540      * <pre>{@code
1541      *   this.mul(this).add(this.species().broadcast(v * v)).sqrt()
1542      * }</pre>
1543      * <p>
1544      * This is a vector binary operation with same semantic definition as
1545      * {@link Math#hypot} operation applied to lane elements.
1546      * The implementation is not required to return same
1547      * results as {@link Math#hypot}, but adheres to rounding, monotonicity,
1548      * and special case semantics as defined in the {@link Math#hypot}
1549      * specifications. The computed result will be within 1 ulp of the
1550      * exact result.
1551      *
1552      * @param s the input scalar
1553      * @return square root of the sum of the squares of this vector and the
1554      * broadcast of an input scalar
1555      */
1556     public abstract DoubleVector hypot(double s);
1557 
1558     /**
1559      * Calculates square root of the sum of the squares of this vector and an
1560      * input vector, selecting lane elements controlled by a mask.
1561      * More specifically as if the following (ignoring any differences in
1562      * numerical accuracy):
1563      * <pre>{@code
1564      *   this.mul(this, m).add(v.mul(v), m).sqrt(m)
1565      * }</pre>
1566      * <p>
1567      * Semantics for rounding, monotonicity, and special cases are
1568      * described in {@link DoubleVector#hypot}
1569      *
1570      * @param v the input vector
1571      * @param m the mask controlling lane selection
1572      * @return square root of the sum of the squares of this vector and an input
1573      * vector
1574      */
1575     public DoubleVector hypot(Vector<Double> v, Mask<Double> m) {
1576         return bOp(v, m, (i, a, b) -> (double) Math.hypot((double) a, (double) b));
1577     }
1578 
1579     /**
1580      * Calculates square root of the sum of the squares of this vector and the
1581      * broadcast of an input scalar, selecting lane elements controlled by a
1582      * mask.
1583      * More specifically as if the following (ignoring any differences in
1584      * numerical accuracy):
1585      * <pre>{@code
1586      *   this.mul(this, m).add(this.species().broadcast(v * v), m).sqrt(m)
1587      * }</pre>
1588      * <p>
1589      * Semantics for rounding, monotonicity, and special cases are
1590      * described in {@link DoubleVector#hypot}
1591      *
1592      * @param s the input scalar
1593      * @param m the mask controlling lane selection
1594      * @return square root of the sum of the squares of this vector and the
1595      * broadcast of an input scalar
1596      */
1597     public abstract DoubleVector hypot(double s, Mask<Double> m);
1598 
1599 
1600     @Override
1601     public abstract void intoByteArray(byte[] a, int ix);
1602 
1603     @Override
1604     public abstract void intoByteArray(byte[] a, int ix, Mask<Double> m);
1605 
1606     @Override
1607     public abstract void intoByteBuffer(ByteBuffer bb, int ix);
1608 
1609     @Override
1610     public abstract void intoByteBuffer(ByteBuffer bb, int ix, Mask<Double> m);
1611 
1612 
1613     // Type specific horizontal reductions
1614     /**
1615      * Adds all lane elements of this vector.
1616      * <p>
1617      * This is a vector reduction operation where the addition
1618      * operation ({@code +}) is applied to lane elements,
1619      * and the identity value is {@code 0.0}.
1620      *
1621      * <p>The value of a floating-point sum is a function both of the input values as well
1622      * as the order of addition operations. The order of addition operations of this method
1623      * is intentionally not defined to allow for JVM to generate optimal machine
1624      * code for the underlying platform at runtime. If the platform supports a vector
1625      * instruction to add all values in the vector, or if there is some other efficient machine
1626      * code sequence, then the JVM has the option of generating this machine code. Otherwise,
1627      * the default implementation of adding vectors sequentially from left to right is used.
1628      * For this reason, the output of this method may vary for the same input values.
1629      *
1630      * @return the addition of all the lane elements of this vector
1631      */
1632     public abstract double addAll();
1633 
1634     /**
1635      * Adds all lane elements of this vector, selecting lane elements
1636      * controlled by a mask.
1637      * <p>
1638      * This is a vector reduction operation where the addition
1639      * operation ({@code +}) is applied to lane elements,
1640      * and the identity value is {@code 0.0}.
1641      *
1642      * <p>The value of a floating-point sum is a function both of the input values as well
1643      * as the order of addition operations. The order of addition operations of this method
1644      * is intentionally not defined to allow for JVM to generate optimal machine
1645      * code for the underlying platform at runtime. If the platform supports a vector
1646      * instruction to add all values in the vector, or if there is some other efficient machine
1647      * code sequence, then the JVM has the option of generating this machine code. Otherwise,
1648      * the default implementation of adding vectors sequentially from left to right is used.
1649      * For this reason, the output of this method may vary on the same input values.
1650      *
1651      * @param m the mask controlling lane selection
1652      * @return the addition of the selected lane elements of this vector
1653      */
1654     public abstract double addAll(Mask<Double> m);
1655 
1656     /**
1657      * Multiplies all lane elements of this vector.
1658      * <p>
1659      * This is a vector reduction operation where the
1660      * multiplication operation ({@code *}) is applied to lane elements,
1661      * and the identity value is {@code 1.0}.
1662      *
1663      * <p>The order of multiplication operations of this method
1664      * is intentionally not defined to allow for JVM to generate optimal machine
1665      * code for the underlying platform at runtime. If the platform supports a vector
1666      * instruction to multiply all values in the vector, or if there is some other efficient machine
1667      * code sequence, then the JVM has the option of generating this machine code. Otherwise,
1668      * the default implementation of multiplying vectors sequentially from left to right is used.
1669      * For this reason, the output of this method may vary on the same input values.
1670      *
1671      * @return the multiplication of all the lane elements of this vector
1672      */
1673     public abstract double mulAll();
1674 
1675     /**
1676      * Multiplies all lane elements of this vector, selecting lane elements
1677      * controlled by a mask.
1678      * <p>
1679      * This is a vector reduction operation where the
1680      * multiplication operation ({@code *}) is applied to lane elements,
1681      * and the identity value is {@code 1.0}.
1682      *
1683      * <p>The order of multiplication operations of this method
1684      * is intentionally not defined to allow for JVM to generate optimal machine
1685      * code for the underlying platform at runtime. If the platform supports a vector
1686      * instruction to multiply all values in the vector, or if there is some other efficient machine
1687      * code sequence, then the JVM has the option of generating this machine code. Otherwise,
1688      * the default implementation of multiplying vectors sequentially from left to right is used.
1689      * For this reason, the output of this method may vary on the same input values.
1690      *
1691      * @param m the mask controlling lane selection
1692      * @return the multiplication of all the lane elements of this vector
1693      */
1694     public abstract double mulAll(Mask<Double> m);
1695 
1696     /**
1697      * Returns the minimum lane element of this vector.
1698      * <p>
1699      * This is an associative vector reduction operation where the operation
1700      * {@code (a, b) -> Math.min(a, b)} is applied to lane elements,
1701      * and the identity value is
1702      * {@link Double#POSITIVE_INFINITY}.
1703      *
1704      * @return the minimum lane element of this vector
1705      */
1706     public abstract double minAll();
1707 
1708     /**
1709      * Returns the minimum lane element of this vector, selecting lane elements
1710      * controlled by a mask.
1711      * <p>
1712      * This is an associative vector reduction operation where the operation
1713      * {@code (a, b) -> Math.min(a, b)} is applied to lane elements,
1714      * and the identity value is
1715      * {@link Double#POSITIVE_INFINITY}.
1716      *
1717      * @param m the mask controlling lane selection
1718      * @return the minimum lane element of this vector
1719      */
1720     public abstract double minAll(Mask<Double> m);
1721 
1722     /**
1723      * Returns the maximum lane element of this vector.
1724      * <p>
1725      * This is an associative vector reduction operation where the operation
1726      * {@code (a, b) -> Math.max(a, b)} is applied to lane elements,
1727      * and the identity value is
1728      * {@link Double#NEGATIVE_INFINITY}.
1729      *
1730      * @return the maximum lane element of this vector
1731      */
1732     public abstract double maxAll();
1733 
1734     /**
1735      * Returns the maximum lane element of this vector, selecting lane elements
1736      * controlled by a mask.
1737      * <p>
1738      * This is an associative vector reduction operation where the operation
1739      * {@code (a, b) -> Math.max(a, b)} is applied to lane elements,
1740      * and the identity value is
1741      * {@link Double#NEGATIVE_INFINITY}.
1742      *
1743      * @param m the mask controlling lane selection
1744      * @return the maximum lane element of this vector
1745      */
1746     public abstract double maxAll(Mask<Double> m);
1747 
1748 
1749     // Type specific accessors
1750 
1751     /**
1752      * Gets the lane element at lane index {@code i}
1753      *
1754      * @param i the lane index
1755      * @return the lane element at lane index {@code i}
1756      * @throws IllegalArgumentException if the index is is out of range
1757      * ({@code < 0 || >= length()})
1758      */
1759     public abstract double get(int i);
1760 
1761     /**
1762      * Replaces the lane element of this vector at lane index {@code i} with
1763      * value {@code e}.
1764      * <p>
1765      * This is a cross-lane operation and behaves as if it returns the result
1766      * of blending this vector with an input vector that is the result of
1767      * broadcasting {@code e} and a mask that has only one lane set at lane
1768      * index {@code i}.
1769      *
1770      * @param i the lane index of the lane element to be replaced
1771      * @param e the value to be placed
1772      * @return the result of replacing the lane element of this vector at lane
1773      * index {@code i} with value {@code e}.
1774      * @throws IllegalArgumentException if the index is is out of range
1775      * ({@code < 0 || >= length()})
1776      */
1777     public abstract DoubleVector with(int i, double e);
1778 
1779     // Type specific extractors
1780 
1781     /**
1782      * Returns an array containing the lane elements of this vector.
1783      * <p>
1784      * This method behaves as if it {@link #intoArray(double[], int)} stores}
1785      * this vector into an allocated array and returns the array as follows:
1786      * <pre>{@code
1787      *   double[] a = new double[this.length()];
1788      *   this.intoArray(a, 0);
1789      *   return a;
1790      * }</pre>
1791      *
1792      * @return an array containing the the lane elements of this vector
1793      */
1794     @ForceInline
1795     public final double[] toArray() {
1796         double[] a = new double[species().length()];
1797         intoArray(a, 0);
1798         return a;
1799     }
1800 
1801     /**
1802      * Stores this vector into an array starting at offset.
1803      * <p>
1804      * For each vector lane, where {@code N} is the vector lane index,
1805      * the lane element at index {@code N} is stored into the array at index
1806      * {@code i + N}.
1807      *
1808      * @param a the array
1809      * @param i the offset into the array
1810      * @throws IndexOutOfBoundsException if {@code i < 0}, or
1811      * {@code i > a.length - this.length()}
1812      */
1813     public abstract void intoArray(double[] a, int i);
1814 
1815     /**
1816      * Stores this vector into an array starting at offset and using a mask.
1817      * <p>
1818      * For each vector lane, where {@code N} is the vector lane index,
1819      * if the mask lane at index {@code N} is set then the lane element at
1820      * index {@code N} is stored into the array index {@code i + N}.
1821      *
1822      * @param a the array
1823      * @param i the offset into the array
1824      * @param m the mask
1825      * @throws IndexOutOfBoundsException if {@code i < 0}, or
1826      * for any vector lane index {@code N} where the mask at lane {@code N}
1827      * is set {@code i >= a.length - N}
1828      */
1829     public abstract void intoArray(double[] a, int i, Mask<Double> m);
1830 
1831     /**
1832      * Stores this vector into an array using indexes obtained from an index
1833      * map.
1834      * <p>
1835      * For each vector lane, where {@code N} is the vector lane index, the
1836      * lane element at index {@code N} is stored into the array at index
1837      * {@code i + indexMap[j + N]}.
1838      *
1839      * @param a the array
1840      * @param i the offset into the array, may be negative if relative
1841      * indexes in the index map compensate to produce a value within the
1842      * array bounds
1843      * @param indexMap the index map
1844      * @param j the offset into the index map
1845      * @throws IndexOutOfBoundsException if {@code j < 0}, or
1846      * {@code j > indexMap.length - this.length()},
1847      * or for any vector lane index {@code N} the result of
1848      * {@code i + indexMap[j + N]} is {@code < 0} or {@code >= a.length}
1849      */
1850     public abstract void intoArray(double[] a, int i, int[] indexMap, int j);
1851 
1852     /**
1853      * Stores this vector into an array using indexes obtained from an index
1854      * map and using a mask.
1855      * <p>
1856      * For each vector lane, where {@code N} is the vector lane index,
1857      * if the mask lane at index {@code N} is set then the lane element at
1858      * index {@code N} is stored into the array at index
1859      * {@code i + indexMap[j + N]}.
1860      *
1861      * @param a the array
1862      * @param i the offset into the array, may be negative if relative
1863      * indexes in the index map compensate to produce a value within the
1864      * array bounds
1865      * @param m the mask
1866      * @param indexMap the index map
1867      * @param j the offset into the index map
1868      * @throws IndexOutOfBoundsException if {@code j < 0}, or
1869      * {@code j > indexMap.length - this.length()},
1870      * or for any vector lane index {@code N} where the mask at lane
1871      * {@code N} is set the result of {@code i + indexMap[j + N]} is
1872      * {@code < 0} or {@code >= a.length}
1873      */
1874     public abstract void intoArray(double[] a, int i, Mask<Double> m, int[] indexMap, int j);
1875     // Species
1876 
1877     @Override
1878     public abstract Species<Double> species();
1879 
1880     /**
1881      * Class representing {@link DoubleVector}'s of the same {@link Shape Shape}.
1882      */
1883     static final class DoubleSpecies extends AbstractSpecies<Double> {
1884         final Function<double[], DoubleVector> vectorFactory;
1885 
1886         private DoubleSpecies(Shape shape,
1887                           Class<?> boxType,
1888                           Class<?> maskType,
1889                           Function<double[], DoubleVector> vectorFactory,
1890                           Function<boolean[], Mask<Double>> maskFactory,
1891                           Function<IntUnaryOperator, Shuffle<Double>> shuffleFromArrayFactory,
1892                           fShuffleFromArray<Double> shuffleFromOpFactory) {
1893             super(shape, double.class, Double.SIZE, boxType, maskType, maskFactory,
1894                   shuffleFromArrayFactory, shuffleFromOpFactory);
1895             this.vectorFactory = vectorFactory;
1896         }
1897 
1898         interface FOp {
1899             double apply(int i);
1900         }
1901 
1902         interface FOpm {
1903             boolean apply(int i);
1904         }
1905 
1906         DoubleVector op(FOp f) {
1907             double[] res = new double[length()];
1908             for (int i = 0; i < length(); i++) {
1909                 res[i] = f.apply(i);
1910             }
1911             return vectorFactory.apply(res);
1912         }
1913 
1914         DoubleVector op(Mask<Double> o, FOp f) {
1915             double[] res = new double[length()];
1916             boolean[] mbits = ((AbstractMask<Double>)o).getBits();
1917             for (int i = 0; i < length(); i++) {
1918                 if (mbits[i]) {
1919                     res[i] = f.apply(i);
1920                 }
1921             }
1922             return vectorFactory.apply(res);
1923         }
1924     }
1925 
1926     /**
1927      * Finds the preferred species for an element type of {@code double}.
1928      * <p>
1929      * A preferred species is a species chosen by the platform that has a
1930      * shape of maximal bit size.  A preferred species for different element
1931      * types will have the same shape, and therefore vectors, masks, and
1932      * shuffles created from such species will be shape compatible.
1933      *
1934      * @return the preferred species for an element type of {@code double}
1935      */
1936     private static DoubleSpecies preferredSpecies() {
1937         return (DoubleSpecies) Species.ofPreferred(double.class);
1938     }
1939 
1940     /**
1941      * Finds a species for an element type of {@code double} and shape.
1942      *
1943      * @param s the shape
1944      * @return a species for an element type of {@code double} and shape
1945      * @throws IllegalArgumentException if no such species exists for the shape
1946      */
1947     static DoubleSpecies species(Shape s) {
1948         Objects.requireNonNull(s);
1949         switch (s) {
1950             case S_64_BIT: return (DoubleSpecies) SPECIES_64;
1951             case S_128_BIT: return (DoubleSpecies) SPECIES_128;
1952             case S_256_BIT: return (DoubleSpecies) SPECIES_256;
1953             case S_512_BIT: return (DoubleSpecies) SPECIES_512;
1954             case S_Max_BIT: return (DoubleSpecies) SPECIES_MAX;
1955             default: throw new IllegalArgumentException("Bad shape: " + s);
1956         }
1957     }
1958 
1959     /** Species representing {@link DoubleVector}s of {@link Shape#S_64_BIT Shape.S_64_BIT}. */
1960     public static final Species<Double> SPECIES_64 = new DoubleSpecies(Shape.S_64_BIT, Double64Vector.class, Double64Vector.Double64Mask.class,
1961                                                                      Double64Vector::new, Double64Vector.Double64Mask::new,
1962                                                                      Double64Vector.Double64Shuffle::new, Double64Vector.Double64Shuffle::new);
1963 
1964     /** Species representing {@link DoubleVector}s of {@link Shape#S_128_BIT Shape.S_128_BIT}. */
1965     public static final Species<Double> SPECIES_128 = new DoubleSpecies(Shape.S_128_BIT, Double128Vector.class, Double128Vector.Double128Mask.class,
1966                                                                       Double128Vector::new, Double128Vector.Double128Mask::new,
1967                                                                       Double128Vector.Double128Shuffle::new, Double128Vector.Double128Shuffle::new);
1968 
1969     /** Species representing {@link DoubleVector}s of {@link Shape#S_256_BIT Shape.S_256_BIT}. */
1970     public static final Species<Double> SPECIES_256 = new DoubleSpecies(Shape.S_256_BIT, Double256Vector.class, Double256Vector.Double256Mask.class,
1971                                                                       Double256Vector::new, Double256Vector.Double256Mask::new,
1972                                                                       Double256Vector.Double256Shuffle::new, Double256Vector.Double256Shuffle::new);
1973 
1974     /** Species representing {@link DoubleVector}s of {@link Shape#S_512_BIT Shape.S_512_BIT}. */
1975     public static final Species<Double> SPECIES_512 = new DoubleSpecies(Shape.S_512_BIT, Double512Vector.class, Double512Vector.Double512Mask.class,
1976                                                                       Double512Vector::new, Double512Vector.Double512Mask::new,
1977                                                                       Double512Vector.Double512Shuffle::new, Double512Vector.Double512Shuffle::new);
1978 
1979     /** Species representing {@link DoubleVector}s of {@link Shape#S_Max_BIT Shape.S_Max_BIT}. */
1980     public static final Species<Double> SPECIES_MAX = new DoubleSpecies(Shape.S_Max_BIT, DoubleMaxVector.class, DoubleMaxVector.DoubleMaxMask.class,
1981                                                                       DoubleMaxVector::new, DoubleMaxVector.DoubleMaxMask::new,
1982                                                                       DoubleMaxVector.DoubleMaxShuffle::new, DoubleMaxVector.DoubleMaxShuffle::new);
1983 
1984     /**
1985      * Preferred species for {@link DoubleVector}s.
1986      * A preferred species is a species of maximal bit size for the platform.
1987      */
1988     public static final Species<Double> SPECIES_PREFERRED = (Species<Double>) preferredSpecies();
1989 }