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251 Commits

Author SHA1 Message Date
Alexander Karatarakis
4ba872bd75 Avoid leading underscore followed by cap in template identifiers 2021-08-04 22:41:52 +00:00
Rasmus Munk Larsen
b431024404 Don't make assumptions about NaN-propagation for pmin/pmax - it various across platforms. 
Change test to only test for NaN-propagation for pfmin/pfmax.
 2020-10-07 19:05:18 +00:00
Rasmus Munk Larsen
6964ae8d52 Change the sign operator in Eigen to return NaN for NaN arguments, not zero. 2020-07-07 01:54:04 +00:00
Felipe Attanasio
d640276d31 Added support for reverse iterators for Vectorwise operations. 2020-05-14 22:38:20 +00:00
Xiaoxiang Cao
a74a278abd Fix confusing template param name for Stride fwd decl. 2020-04-30 01:43:05 +00:00
Joel Holdsworth
d5c665742b Add absolute_difference coefficient-wise binary Array function 2020-03-19 17:45:20 +00:00
Srinivas Vasudevan
6e215cf109 Add Bessel functions to SpecialFunctions. 
- Split SpecialFunctions files in to a separate BesselFunctions file.

In particular add:
    - Modified bessel functions of the second kind k0, k1, k0e, k1e
    - Bessel functions of the first kind j0, j1
    - Bessel functions of the second kind y0, y1
 2019-09-14 12:16:47 -04:00
Srinivas Vasudevan
facdec5aa7 Add packetized versions of i0e and i1e special functions. 
- In particular refactor the i0e and i1e code so scalar and vectorized path share code.
  - Move chebevl to GenericPacketMathFunctions.


A brief benchmark with building Eigen with FMA, AVX and AVX2 flags

Before:

CPU: Intel Haswell with HyperThreading (6 cores)
Benchmark                  Time(ns)        CPU(ns)     Iterations
-----------------------------------------------------------------
BM_eigen_i0e_double/1            57.3           57.3     10000000
BM_eigen_i0e_double/8           398            398        1748554
BM_eigen_i0e_double/64         3184           3184         218961
BM_eigen_i0e_double/512       25579          25579          27330
BM_eigen_i0e_double/4k       205043         205042           3418
BM_eigen_i0e_double/32k     1646038        1646176            422
BM_eigen_i0e_double/256k   13180959       13182613             53
BM_eigen_i0e_double/1M     52684617       52706132             10
BM_eigen_i0e_float/1             28.4           28.4     24636711
BM_eigen_i0e_float/8             75.7           75.7      9207634
BM_eigen_i0e_float/64           512            512        1000000
BM_eigen_i0e_float/512         4194           4194         166359
BM_eigen_i0e_float/4k         32756          32761          21373
BM_eigen_i0e_float/32k       261133         261153           2678
BM_eigen_i0e_float/256k     2087938        2088231            333
BM_eigen_i0e_float/1M       8380409        8381234             84
BM_eigen_i1e_double/1            56.3           56.3     10000000
BM_eigen_i1e_double/8           397            397        1772376
BM_eigen_i1e_double/64         3114           3115         223881
BM_eigen_i1e_double/512       25358          25361          27761
BM_eigen_i1e_double/4k       203543         203593           3462
BM_eigen_i1e_double/32k     1613649        1613803            428
BM_eigen_i1e_double/256k   12910625       12910374             54
BM_eigen_i1e_double/1M     51723824       51723991             10
BM_eigen_i1e_float/1             28.3           28.3     24683049
BM_eigen_i1e_float/8             74.8           74.9      9366216
BM_eigen_i1e_float/64           505            505        1000000
BM_eigen_i1e_float/512         4068           4068         171690
BM_eigen_i1e_float/4k         31803          31806          21948
BM_eigen_i1e_float/32k       253637         253692           2763
BM_eigen_i1e_float/256k     2019711        2019918            346
BM_eigen_i1e_float/1M       8238681        8238713             86


After:

CPU: Intel Haswell with HyperThreading (6 cores)
Benchmark                  Time(ns)        CPU(ns)     Iterations
-----------------------------------------------------------------
BM_eigen_i0e_double/1            15.8           15.8     44097476
BM_eigen_i0e_double/8            99.3           99.3      7014884
BM_eigen_i0e_double/64          777            777         886612
BM_eigen_i0e_double/512        6180           6181         100000
BM_eigen_i0e_double/4k        48136          48140          14678
BM_eigen_i0e_double/32k      385936         385943           1801
BM_eigen_i0e_double/256k    3293324        3293551            228
BM_eigen_i0e_double/1M     12423600       12424458             57
BM_eigen_i0e_float/1             16.3           16.3     43038042
BM_eigen_i0e_float/8             30.1           30.1     23456931
BM_eigen_i0e_float/64           169            169        4132875
BM_eigen_i0e_float/512         1338           1339         516860
BM_eigen_i0e_float/4k         10191          10191          68513
BM_eigen_i0e_float/32k        81338          81337           8531
BM_eigen_i0e_float/256k      651807         651984           1000
BM_eigen_i0e_float/1M       2633821        2634187            268
BM_eigen_i1e_double/1            16.2           16.2     42352499
BM_eigen_i1e_double/8           110            110        6316524
BM_eigen_i1e_double/64          822            822         851065
BM_eigen_i1e_double/512        6480           6481         100000
BM_eigen_i1e_double/4k        51843          51843          10000
BM_eigen_i1e_double/32k      414854         414852           1680
BM_eigen_i1e_double/256k    3320001        3320568            212
BM_eigen_i1e_double/1M     13442795       13442391             53
BM_eigen_i1e_float/1             17.6           17.6     41025735
BM_eigen_i1e_float/8             35.5           35.5     19597891
BM_eigen_i1e_float/64           240            240        2924237
BM_eigen_i1e_float/512         1424           1424         485953
BM_eigen_i1e_float/4k         10722          10723          65162
BM_eigen_i1e_float/32k        86286          86297           8048
BM_eigen_i1e_float/256k      691821         691868           1000
BM_eigen_i1e_float/1M       2777336        2777747            256


This shows anywhere from a 50% to 75% improvement on these operations.

I've also benchmarked without any of these flags turned on, and got similar
performance to before (if not better).

Also tested packetmath.cpp + special_functions to ensure no regressions.
 2019-09-11 18:34:02 -07:00
Srinivas Vasudevan
18ceb3413d Add ndtri function, the inverse of the normal distribution function. 2019-08-12 19:26:29 -04:00
Gael Guennebaud
b3c4344a68 bug #1676: workaround GCC's bug in c++17 mode. 2019-02-07 15:21:35 +01:00
Patrick Peltzer
15e53d5d93 PR 567: makes all dense solvers inherit SoverBase (LU,Cholesky,QR,SVD). 
This changeset also includes:
 * add HouseholderSequence::conjugateIf
 * define int as the StorageIndex type for all dense solvers
 * dedicated unit tests, including assertion checking
 * _check_solve_assertion(): this method can be implemented in derived solver classes to implement custom checks
 * CompleteOrthogonalDecompositions: add applyZOnTheLeftInPlace, fix scalar type in applyZAdjointOnTheLeftInPlace(), add missing assertions
 * Cholesky: add missing assertions
 * FullPivHouseholderQR: Corrected Scalar type in _solve_impl()
 * BDCSVD: Unambiguous return type for ternary operator
 * SVDBase: Corrected Scalar type in _solve_impl()
 2019-01-17 01:17:39 +01:00
Eugene Zhulenev
2bf1a31d81 Use void type if stl-style iterators are not supported 2018-10-10 10:31:40 -07:00
Eugene Zhulenev
c0ca8a9fa3 Compile time detection for unimplemented stl-style iterators 2018-10-09 15:28:23 -07:00
Gael Guennebaud
d92f004ab7 Simplify API by removing allCols/allRows and reusing rowwise/colwise to define iterators over rows/columns 2018-10-05 23:11:21 +02:00
Gael Guennebaud
3e64b1fc86 Move iterators to internal, improve doc, make unit test c++03 friendly 2018-10-03 15:13:15 +02:00
Gael Guennebaud
0481900e25 Add pointer-based iterator for direct-access expressions 2018-10-02 23:44:36 +02:00
Gael Guennebaud
8c38528168 Factorize RowsProxy/ColsProxy and related iterators using subVector<>(Index) 2018-10-02 14:03:26 +02:00
Gael Guennebaud
b0c66adfb1 bug #231: initial implementation of STL iterators for dense expressions 2018-10-01 23:21:37 +02:00
Gael Guennebaud
9036cda364 Cleanup intitial reshape implementation: 
- reshape -> reshaped
 - make it compatible with evaluators.
 2017-01-29 14:57:45 +01:00
Gael Guennebaud
0e89baa5d8 import yoco xiao's work on reshape 2017-01-29 14:29:31 +01:00
Gael Guennebaud
ac7e4ac9c0 Initial commit to add a generic indexed-based view of matrices. 
This version already works as a read-only expression.
Numerous refactoring, renaming, extension, tuning passes are expected...
 2017-01-06 00:01:44 +01:00
Gael Guennebaud
2f7e2614e7 bug #1232: refactor special functions as a new SpecialFunctions module, currently in unsupported/. 2016-07-08 11:13:55 +02:00
Gael Guennebaud
deb45ad4bc bug #1245: fix compilation with msvc 2016-06-24 09:52:25 +02:00
Gael Guennebaud
396d9cfb6e Generalize expr.pow(scalar), pow(expr,scalar) and pow(scalar,expr). 
Internal: scalar_pow_op (unary) is removed, and scalar_binary_pow_op is renamed scalar_pow_op.
 2016-06-14 14:10:07 +02:00
Gael Guennebaud
a8c08e8b8e Implement expr+scalar, scalar+expr, expr-scalar, and scalar-expr as binary expressions, and generalize supported scalar types. 
The following functors are now deprecated: scalar_add_op, scalar_sub_op, and scalar_rsub_op.
 2016-06-14 12:06:10 +02:00
Gael Guennebaud
64fcfd314f Implement scalar multiples and division by a scalar as a binary-expression with a constant expression. 
This slightly complexifies the type of the expressions and implies that we now have to distinguish between scalar*expr and expr*scalar to catch scalar-multiple expression (e.g., see BlasUtil.h), but this brings several advantages:
- it makes it clear on each side the scalar is applied,
- it clearly reflects that we are dealing with a binary-expression,
- the complexity of the type is hidden through macros defined at the end of Macros.h,
- distinguishing between "scalar op expr" and "expr op scalar" is important to support non commutative fields (like quaternions)
- "scalar op expr" is now fully equivalent to "ConstantExpr(scalar) op expr"
- scalar_multiple_op, scalar_quotient1_op and scalar_quotient2_op are not used anymore in officially supported modules (still used in Tensor)
 2016-06-14 11:26:57 +02:00
Gael Guennebaud
3c12e24164 Add bind1st_op and bind2nd_op helpers to turn binary functors into unary ones, and implement scalar_multiple2 and scalar_quotient2 on top of them. 2016-06-13 16:18:59 +02:00
Gael Guennebaud
7a9ef7bbb4 Add default template parameters for the second scalar type of binary functors. 
This enhences backward compatibility.
 2016-06-13 16:17:23 +02:00
Gael Guennebaud
5fdd703629 Enable mixing types in numext::pow 2016-06-10 15:58:04 +02:00
Gael Guennebaud
2e238bafb6 Big 279: enable mixing types for comparisons, min, and max. 2016-06-10 15:05:43 +02:00
Gael Guennebaud
66e99ab6a1 Relax mixing-type constraints for binary coefficient-wise operators: 
- Replace internal::scalar_product_traits<A,B> by Eigen::ScalarBinaryOpTraits<A,B,OP>
- Remove the "functor_is_product_like" helper (was pretty ugly)
- Currently, OP is not used, but it is available to the user for fine grained tuning
- Currently, only the following operators have been generalized: *,/,+,-,=,*=,/=,+=,-=
- TODO: generalize all other binray operators (comparisons,pow,etc.)
- TODO: handle "scalar op array" operators (currently only * is handled)
- TODO: move the handling of the "void" scalar type to ScalarBinaryOpTraits
 2016-06-06 15:11:41 +02:00
Eugene Brevdo
39baff850c Add TernaryFunctors and the betainc SpecialFunction. 
TernaryFunctors and their executors allow operations on 3-tuples of inputs.
API fully implemented for Arrays and Tensors based on binary functors.

Ported the cephes betainc function (regularized incomplete beta
integral) to Eigen, with support for CPU and GPU, floats, doubles, and
half types.

Added unit tests in array.cpp and cxx11_tensor_cuda.cu


Collapsed revision
* Merged helper methods for betainc across floats and doubles.
* Added TensorGlobalFunctions with betainc().  Removed betainc() from TensorBase.
* Clean up CwiseTernaryOp checks, change igamma_helper to cephes_helper.
* betainc: merge incbcf and incbd into incbeta_cfe.  and more cleanup.
* Update TernaryOp and SpecialFunctions (betainc) based on review comments.
 2016-06-02 17:04:19 -07:00
Eugene Brevdo
73220d2bb0 Resolve bad merge. 2016-03-08 17:28:21 -08:00
Rasmus Munk Larsen
d904c8ac8f Implement complete orthogonal decomposition in Eigen. 2016-02-06 16:32:00 -08:00
Gael Guennebaud
659fc9c159 Remove dead code 2016-02-04 09:55:09 +01:00
Gael Guennebaud
1bc207c528 backout changeset d4a9e61569 
: the extended SparseView is not needed anymore
 2016-01-30 14:43:21 +01:00
Gael Guennebaud
d4a9e61569 Extend SparseView to allow keeping explicit zeros. This is equivalent to sparseView(1,-1) but faster because the test is removed at compile-time. 2016-01-29 22:07:56 +01:00
Gael Guennebaud
0bb12fa614 Add LU::transpose().solve() and LU::adjoint().solve() API. 2015-12-01 14:38:47 +01:00
Mark Borgerding
7ddcf97da7 added scalar_sign_op (both real,complex) 2015-11-24 17:15:07 -05:00
Gael Guennebaud
902750826b Add support for dense.cwiseProduct(sparse) 
This also fixes a regression regarding (dense*sparse).diagonal()
 2015-11-04 17:42:07 +01:00
Gael Guennebaud
527fc4bc86 Fix ambiguous instantiation issues of product_evaluator. 2015-10-14 10:14:47 +02:00
Gael Guennebaud
98ff17eb9e Add special path for matrix<complex>/real. 
This also fixes underflow issues when scaling complex matrices through complex/complex operator.
 2015-06-26 16:08:15 +02:00
Gael Guennebaud
a5a7b68b76 Fix ambiguous instanciation using clean class-level SFINAE in product_evaluator 2015-06-19 17:25:13 +02:00
Gael Guennebaud
6fc5438205 Remove a few deprecated internal expressions 2015-06-19 17:06:12 +02:00
Gael Guennebaud
321a2cbe3d Add missing forward declaration of AlignedBox 2015-06-15 15:01:20 +02:00
Benoit Jacob
051d5325cc Abandon blocking size lookup table approach. Not performing as well in real world as in microbenchmark. 2015-05-19 11:03:59 -04:00
Benoit Steiner
d3f7915aeb Pulled latest update from the eigen main codebase 2015-03-24 13:12:14 -07:00
Benoit Jacob
e56aabf205 Refactor computeProductBlockingSizes to make room for the possibility of using lookup tables 2015-03-15 18:05:12 -04:00
Benoit Steiner
f41b1f1666 Added support for fast reciprocal square root computation. 2015-02-26 09:42:41 -08:00
Gael Guennebaud
ee06f78679 Introduce unified macros to identify compiler, OS, and architecture. They are all defined in util/Macros.h and prefixed with EIGEN_COMP_, EIGEN_OS_, and EIGEN_ARCH_ respectively. 2014-11-04 21:58:52 +01:00