bin/ipdf
data/*
src/moc_controlpanel.cpp
+src/tests/*
+tools/*
+!tools/*.ipynb
+!tools/*.py
+!src/tests/*.cpp
+!src/tests/*.h
#Makefile
ARCH := $(shell uname -m)
# TODO: stb_truetype doesn't compile with some of these warnings.
-CXX = g++ -std=gnu++0x -g -Wall -Werror -Wshadow -pedantic -rdynamic
+CXX = g++ -std=c++11 -g -Wall -Werror -Wshadow -pedantic -rdynamic
MAIN = main.o
OBJ = log.o real.o bezier.o document.o objectrenderer.o view.o screen.o graphicsbuffer.o framebuffer.o shaderprogram.o stb_truetype.o gl_core44.o path.o paranoidnumber.o quadtree.o
## Only link with things we care about
ifeq ($(QUADTREE),enabled)
- OBJ := $(OBJ) quadtree.o
+ OBJ := $(OBJ)
else
DEF := $(DEF) -DQUADTREE_DISABLED
endif
CFLAGS := $(CFLAGS) -I../contrib/iRRAM/include
endif
+
+
+ifeq ($(REALTYPE),9)
+ LIB := $(LIB) -lgmp
+endif
+
LINKOBJ = $(OBJPATHS)
# To change that you can run as `make DEFS="REALTYPE=X" tests/<target>` where X is your chosen type
# But remember to make clean first.
tests/% : tests/%.cpp ../obj/tests/%.o $(LINKOBJ)
- $(CXX) $(CFLAGS) -o $@
.test $(LINKOBJ) ../obj/
[email protected] $(LIB) $(TESTRPATH)
-include $(DEPS)
typedef enum {UNKNOWN, LINE, QUADRATIC, CUSP, LOOP, SERPENTINE} Type;
Type type;
- Bezier() = default; // Needed so we can fread/fwrite this struct... for now.
- Bezier(Real _x0, Real _y0, Real _x1, Real _y1, Real _x2, Real _y2, Real _x3, Real _y3) : x0(_x0), y0(_y0), x1(_x1), y1(_y1), x2(_x2), y2(_y2), x3(_x3), y3(_y3), type(UNKNOWN)
+ //Bezier() = default; // Needed so we can fread/fwrite this struct... for now.
+ Bezier(Real _x0=0, Real _y0=0, Real _x1=0, Real _y1=0, Real _x2=0, Real _y2=0, Real _x3=0, Real _y3=0) : x0(_x0), y0(_y0), x1(_x1), y1(_y1), x2(_x2), y2(_y2), x3(_x3), y3(_y3), type(UNKNOWN)
{
}
return type;
// From Loop-Blinn 2005, with w0 == w1 == w2 == w3 = 1
// Transformed control points: (a0 = x0, b0 = y0)
- Real a1 = (x1-x0)*3;
- Real a2 = (x0- x1*2 +x2)*3;
- Real a3 = (x3 - x0 + (x1 - x2)*3);
+ Real a1 = (x1-x0)*Real(3);
+ Real a2 = (x0- x1*Real(2) +x2)*Real(3);
+ Real a3 = (x3 - x0 + (x1 - x2)*Real(3));
- Real b1 = (y1-y0)*3;
- Real b2 = (y0- y1*2 +y2)*3;
- Real b3 = (y3 - y0 + (y1 - y2)*3);
+ Real b1 = (y1-y0)*Real(3);
+ Real b2 = (y0- y1*Real(2) +y2)*Real(3);
+ Real b3 = (y3 - y0 + (y1 - y2)*Real(3));
// d vector (d0 = 0 since all w = 1)
Real d1 = a2*b3 - a3*b2;
Real d2 = a3*b1 - a1*b3;
Real d3 = a1*b2 - a2*b1;
- if (Abs(d1+d2+d3) < 1e-6)
+ if (Abs(d1+d2+d3) < Real(1e-6))
{
type = LINE;
//Debug("LINE %s", Str().c_str());
Real delta1 = -(d1*d1);
Real delta2 = d1*d2;
Real delta3 = d1*d3 -(d2*d2);
- if (Abs(delta1+delta2+delta3) < 1e-6)
+ if (Abs(delta1+delta2+delta3) < Real(1e-6))
{
type = QUADRATIC;
return type;
}
- Real discriminant = d1*d3*4 -d2*d2;
- if (Abs(discriminant) < 1e-6)
+ Real discriminant = d1*d3*Real(4) -d2*d2;
+ if (Abs(discriminant) < Real(1e-6))
{
type = CUSP;
//Debug("CUSP %s", Str().c_str());
}
- else if (discriminant > 0)
+ else if (discriminant > Real(0))
{
type = SERPENTINE;
//Debug("SERPENTINE %s", Str().c_str());
// (So can't just use the Copy constructor on the inverse of bounds)
// Rect inverse = {-bounds.x/bounds.w, -bounds.y/bounds.h, Real(1)/bounds.w, Real(1)/bounds.h};
Bezier result;
- if (bounds.w == 0)
+ if (bounds.w == Real(0))
{
result.x0 = 0;
result.x1 = 0;
result.x3 = (x3 - bounds.x)/bounds.w;
}
- if (bounds.h == 0)
+ if (bounds.h == Real(0))
{
result.y0 = 0;
result.y1 = 0;
{
Real t1 = *it;
if (t1 == t0) continue;
- Debug(" -- t0: %f to t1: %f: %f", Double(t0), Double(t1), (t1 + t0)/Real(2));
+ Debug(" -- t0: %f to t1: %f: %f", Double(t0), Double(t1), Double((t1 + t0)/Real(2)));
Real ptx, pty;
Evaluate(ptx, pty, ((t1 + t0) / Real(2)));
if (r.PointIn(ptx, pty))
--- /dev/null
+version: 1
+creator: callgrind-3.9.0
+pid: 22889
+cmd: tests/addsub
+part: 1
+
+
+desc: I1 cache:
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+desc: LL cache:
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++1 1590
+cfi=(241) /usr/include/c++/4.9/bits/alloc_traits.h
+cfn=(4406) void std::__alloc_on_swap<std::allocator<IPDF::ParanoidNumber*> >(std::allocator<IPDF::ParanoidNumber*>&, std::allocator<IPDF::ParanoidNumber*>&)
+calls=318 490
+* 6678
+* 636
+
+fn=(4362) __gnu_cxx::__alloc_traits<std::allocator<IPDF::ParanoidNumber*> >::_S_propagate_on_copy_assign()
+145 165232
++1 247848
+
+fl=(234) /home/sam/Documents/University/2014/ipdf/code/src/tests/stresstest.h
+fn=(4346) IPDF::ParanoidNumber AddSub<IPDF::ParanoidNumber>(IPDF::ParanoidNumber const&, IPDF::ParanoidNumber const&, IPDF::ParanoidNumber const&)
+13 792
++2 396
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++1 495
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+cfn=(4264) IPDF::ParanoidNumber::ParanoidNumber(IPDF::ParanoidNumber const&)
+calls=99 +72
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+* 99
++2 24995
+cfi=(217) /home/sam/Documents/University/2014/ipdf/code/src/paranoidnumber.cpp
+cfn=(4356) IPDF::ParanoidNumber::operator+=(IPDF::ParanoidNumber const&)
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+* 17314804
++1 24995
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++2 1668835
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+cfn=(4392) IPDF::ParanoidNumber::operator-=(IPDF::ParanoidNumber const&)
+calls=333767 284
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+-2 1668835
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+* 1152580424
+* 1693830
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+cfn=(4348) IPDF::ParanoidNumber::operator<(IPDF::ParanoidNumber const&) const
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+* 169042237
+* 692529
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+cfn=(4298) IPDF::ParanoidNumber::~ParanoidNumber()
+calls=4999 -1
+* 6338732
++4 24995
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++2 1668835
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++12 495
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++2 24995
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++1 24995
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++2 1668835
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++4 24995
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++2 1668835
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+* 125532
++12 99
++1 495
+
+fl=(233) /usr/include/c++/4.9/bits/stl_construct.h
+fn=(4316) void std::_Destroy<IPDF::ParanoidNumber**, IPDF::ParanoidNumber*>(IPDF::ParanoidNumber**, IPDF::ParanoidNumber**, std::allocator<IPDF::ParanoidNumber*>&)
+148 162419772
++3 135349810
+cfn=(4318) void std::_Destroy<IPDF::ParanoidNumber**>(IPDF::ParanoidNumber**, IPDF::ParanoidNumber**)
+calls=27069962 -29
+* 487259316
++1 54139924
+
+fn=(4386) void std::_Destroy<__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >, IPDF::ParanoidNumber*>(__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >, __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >, std::allocator<IPDF::ParanoidNumber*>&)
+148 495696
++3 413080
+cfn=(4388) void std::_Destroy<__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > > >(__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >, __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >)
+calls=82616 -29
+* 1487088
++1 165232
+
+fn=(4390) void std::_Destroy_aux<true>::__destroy<__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > > >(__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >, __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >)
+112 495696
+
+fn=(4320) void std::_Destroy_aux<true>::__destroy<IPDF::ParanoidNumber**>(IPDF::ParanoidNumber**, IPDF::ParanoidNumber**)
+112 162419772
+
+fn=(4318)
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++4 135349810
+cfn=(4320)
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+* 162419772
++2 54139924
+
+fn=(4388)
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++4 413080
+cfn=(4390)
+calls=82616 -14
+* 495696
++2 165232
+
+fl=(238) /usr/include/c++/4.9/bits/stl_algobase.h
+fn=(4372) __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > > std::__copy_move_a2<false, __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >, __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > > >(__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >, __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >, __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >)
+430 660928
++4 247848
+cfn=(4374) std::_Niter_base<__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > > >::iterator_type std::__niter_base<__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > > >(__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >)
+calls=82616 278
+* 2065400
+* 330464
+cfn=(4378) std::_Niter_base<__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > > >::iterator_type std::__niter_base<__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > > >(__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >)
+calls=82616 278
+* 2065400
+* 330464
+cfn=(4378)
+calls=82616 278
+* 2065400
+* 330464
+cfn=(4382) IPDF::ParanoidNumber** std::__copy_move_a<false, IPDF::ParanoidNumber* const*, IPDF::ParanoidNumber**>(IPDF::ParanoidNumber* const*, IPDF::ParanoidNumber* const*, IPDF::ParanoidNumber**)
+calls=82616 -49
+* 2891560
+* 495696
+cfi=(232) /usr/include/c++/4.9/bits/stl_iterator.h
+cfn=(4302) __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >::__normal_iterator(IPDF::ParanoidNumber** const&)
+calls=82616 728
+* 826160
+* 82616
++1 413080
+
+fn=(4366) __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > > std::copy<__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >, __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > > >(__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >, __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >, __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >)
+456 578312
++10 247848
+cfn=(4368) std::_Miter_base<__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > > >::iterator_type std::__miter_base<__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > > >(__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >)
+calls=82616 289
+* 1239240
+* 330464
+cfn=(4368)
+calls=82616 289
+* 1239240
+* 495696
+cfn=(4372)
+calls=82616 -36
+* 12805480
++1 330464
+
+fn=(4368)
+289 660928
++1 495696
+cfi=(239) /usr/include/c++/4.9/bits/stl_iterator_base_types.h
+cfn=(4370) std::_Iter_base<__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >, false>::_S_base(__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >)
+calls=165232 -78
+* 991392
+* 330464
+
+fn=(4384) IPDF::ParanoidNumber** std::__copy_move<false, true, std::random_access_iterator_tag>::__copy_m<IPDF::ParanoidNumber*>(IPDF::ParanoidNumber* const*, IPDF::ParanoidNumber* const*, IPDF::ParanoidNumber**)
+369 495696
++7 495696
++1 165232
++2 330464
++1 165232
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++1 537250960
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+fn=(4270) std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> >::end() const
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++1 130442976
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+fn=(4394) void std::swap<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> >(std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> >&, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> >&)
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++5 1590
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++2 954
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++2 1272
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++4 32532228
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++1 97355316
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++1 81459642
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+fn=(4324) std::_Vector_base<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> >::~_Vector_base()
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++2 119284836
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++1 32532228
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+fn=(4256) std::_Vector_base<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> >::_Vector_impl::_Vector_impl()
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++1 32532228
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++1 21688152
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++1 130442976
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++1 48677658
++1 32451772
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++2 826160
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++1 97355316
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++3 21688152
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+fn=(4190) _GLOBAL__sub_I__ZN4IPDF20TransformToQuadChildERKNS_4RectENS_20QuadTreeNodeChildrenE
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+fl=(209) /home/sam/Documents/University/2014/ipdf/code/src/real.cpp
+fn=(4144) _GLOBAL__sub_I__ZN4IPDF11g_real_nameE
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++1 636
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+fl=(211) /home/sam/Documents/University/2014/ipdf/code/src/document.cpp
+fn=(4156) _GLOBAL__sub_I__ZN4pugi15xml_writer_fileC2EPv
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++1 2690132
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++1 2690132
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++1 1345066
++1 3362665
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+fn=(4186) _GLOBAL__sub_I__ZN4IPDF14ParanoidNumberD2Ev
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++8 18831617
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++3 8191857
++1 10922476
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++1 4156362
++1 5380660
++1 8070990
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++4 8070990
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++2 5380660
++2 2690330
+-2 2770908
++2 2770908
+
+fn=(4284) IPDF::ParanoidNumber::OperationFactor(IPDF::ParanoidNumber*, IPDF::Optype, IPDF::ParanoidNumber**, IPDF::Optype*)
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++3 297
++2 396
++11 297
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++5 297
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++13 297
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++1 2
++4 294
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++2 784
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++2 392
++1 588
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++4 392
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++3 392
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--- /dev/null
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+creator: callgrind-3.9.0
+pid: 30764
+cmd: tests/identitytests
+part: 1
+
+
+desc: I1 cache:
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+desc: Timerange: Basic block 0 - 24551207
+desc: Trigger: Program termination
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+cfn=(4196)
+calls=1 *
+* 93
+* 2
+
+fl=(234) /usr/include/c++/4.9/bits/stl_set.h
+fn=(4292) std::set<IPDF::ParanoidNumber*, std::less<IPDF::ParanoidNumber*>, std::allocator<IPDF::ParanoidNumber*> >::set()
+142 163748
++1 122811
+cfi=(235) /usr/include/c++/4.9/bits/stl_tree.h
+cfn=(4294) std::_Rb_tree<IPDF::ParanoidNumber*, IPDF::ParanoidNumber*, std::_Identity<IPDF::ParanoidNumber*>, std::less<IPDF::ParanoidNumber*>, std::allocator<IPDF::ParanoidNumber*> >::_Rb_tree()
+calls=40937 664
+* 2538094
+* 81874
+
+fn=(4306) std::set<IPDF::ParanoidNumber*, std::less<IPDF::ParanoidNumber*>, std::allocator<IPDF::ParanoidNumber*> >::end() const
+343 163748
++1 122811
+cfi=(235)
+cfn=(4308) std::_Rb_tree<IPDF::ParanoidNumber*, IPDF::ParanoidNumber*, std::_Identity<IPDF::ParanoidNumber*>, std::less<IPDF::ParanoidNumber*>, std::allocator<IPDF::ParanoidNumber*> >::end() const
+calls=40937 744
+* 900614
+* 81874
+
+fn=(4312) std::set<IPDF::ParanoidNumber*, std::less<IPDF::ParanoidNumber*>, std::allocator<IPDF::ParanoidNumber*> >::find(IPDF::ParanoidNumber* const&)
+701 204685
++1 204685
+cfi=(235)
+cfn=(4314) std::_Rb_tree<IPDF::ParanoidNumber*, IPDF::ParanoidNumber*, std::_Identity<IPDF::ParanoidNumber*>, std::less<IPDF::ParanoidNumber*>, std::allocator<IPDF::ParanoidNumber*> >::find(IPDF::ParanoidNumber* const&)
+calls=40937 1910
+* 5731180
+* 245622
+cfi=(235)
+cfn=(4328) std::_Rb_tree_const_iterator<IPDF::ParanoidNumber*>::_Rb_tree_const_iterator(std::_Rb_tree_iterator<IPDF::ParanoidNumber*> const&)
+calls=40937 264
+* 409370
+* 122811
+
+fn=(4400) std::set<IPDF::ParanoidNumber*, std::less<IPDF::ParanoidNumber*>, std::allocator<IPDF::ParanoidNumber*> >::~set()
+90 286552
+cfi=(235)
+cfn=(4402) std::_Rb_tree<IPDF::ParanoidNumber*, IPDF::ParanoidNumber*, std::_Identity<IPDF::ParanoidNumber*>, std::less<IPDF::ParanoidNumber*>, std::allocator<IPDF::ParanoidNumber*> >::~_Rb_tree()
+calls=40936 714
+* 13225783
+* 81872
+
+fn=(4332) std::set<IPDF::ParanoidNumber*, std::less<IPDF::ParanoidNumber*>, std::allocator<IPDF::ParanoidNumber*> >::insert(IPDF::ParanoidNumber*&&)
+508 204685
++3 122811
+cfi=(236) /usr/include/c++/4.9/bits/move.h
+cfn=(4334) std::remove_reference<IPDF::ParanoidNumber*&>::type&& std::move<IPDF::ParanoidNumber*&>(IPDF::ParanoidNumber*&)
+calls=40937 101
+* 245622
+* 204685
+cfi=(235)
+cfn=(4336) std::pair<std::_Rb_tree_iterator<IPDF::ParanoidNumber*>, bool> std::_Rb_tree<IPDF::ParanoidNumber*, IPDF::ParanoidNumber*, std::_Identity<IPDF::ParanoidNumber*>, std::less<IPDF::ParanoidNumber*>, std::allocator<IPDF::ParanoidNumber*> >::_M_insert_unique<IPDF::ParanoidNumber*>(IPDF::ParanoidNumber*&&)
+calls=40937 1489
+* 27104788
+* 81874
++1 286559
+cfi=(238) /usr/include/c++/4.9/bits/stl_pair.h
+cfn=(4394) std::pair<std::_Rb_tree_const_iterator<IPDF::ParanoidNumber*>, bool>::pair<std::_Rb_tree_iterator<IPDF::ParanoidNumber*>&, bool&, void>(std::_Rb_tree_iterator<IPDF::ParanoidNumber*>&, bool&)
+calls=40937 144
+* 1801228
+* 81874
++1 81874
+
+fl=(217)
+fn=(4444) IPDF::ParanoidNumber::OperationFactor(IPDF::ParanoidNumber*, IPDF::Optype, IPDF::ParanoidNumber**, IPDF::Optype*)
+379 170
++3 51
++1 51
+cfi=(228) /home/sam/ipdf/code/src/paranoidnumber.h
+cfn=(4446) IPDF::ParanoidNumber::Floating() const
+calls=17 133
+* 1870
+* 221
++5 51
+cfi=(228)
+cfn=(4446)
+calls=17 133
+* 1870
+* 255
++13 51
+cfi=(228)
+cfn=(4446)
+calls=17 133
+* 1870
+* 222
++1 2
++4 48
+cfi=(228)
+cfn=(4454) IPDF::ParanoidNumber::NoTerms() const
+calls=16 140
+* 736
+* 80
+cfi=(228)
+cfn=(4454)
+calls=16 140
+* 736
+* 96
++2 128
+cfi=(228)
+cfn=(4576) bool IPDF::ParanoidOp<float>(float&, float const&, IPDF::Optype)
+calls=16 45
+* 4893
+* 32
++2 64
++1 96
+cfi=(229) /usr/include/c++/4.9/bits/stl_vector.h
+cfn=(4460) std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> >::begin()
+calls=16 547
+* 352
+* 64
+cfi=(229)
+cfn=(4464) std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> >::end()
+calls=16 565
+* 368
+* 112
+cfi=(233) /usr/include/c++/4.9/bits/stl_iterator.h
+cfn=(4466) bool __gnu_cxx::operator!=<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >(__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > > const&, __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > > const&)
+calls=16 829
+* 512
+* 32
++4 64
++1 96
+cfi=(229)
+cfn=(4460)
+calls=16 547
+* 352
+* 64
+cfi=(229)
+cfn=(4464)
+calls=16 565
+* 368
+* 112
+cfi=(233)
+cfn=(4466)
+calls=16 829
+* 512
+* 32
++3 64
+cfi=(229)
+cfn=(4264) std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> >::clear()
+calls=16 1211
+* 1104
++1 64
+cfi=(229)
+cfn=(4264)
+calls=16 1211
+* 1104
++1 32
++70 85
+
+fn=(4442) IPDF::ParanoidNumber::Operation(IPDF::ParanoidNumber*, IPDF::Optype, IPDF::ParanoidNumber**, IPDF::Optype*)
+502 104448
++2 26112
++4 45696
++1 104312
+cfn=(4494) IPDF::ParanoidNumber::OperationTerm(IPDF::ParanoidNumber*, IPDF::Optype, IPDF::ParanoidNumber**, IPDF::Optype*)
+calls=13039 261
+* 35127064
+* 13038
++1 68
++1 136
+cfn=(4444)
+calls=17 379
+* 19086
+* 17
++2 26110
+
+fn=(4578) bool IPDF::TrustingOp<float>(float&, float const&, IPDF::Optype)
+134 70914
++2 23638
+cob=(4)
+cfi=(257)
+cfn=(4584)
+calls=11819 28
+* 141828
+cob=(1)
+cfi=(54)
+cfn=(228)
+calls=1 34
+* 1835
+* 11823
++1 70914
++3 70976
++1 8872
++2 23448
++1 2931
++5 128
++6 128
++1 16
++4 23638
+cob=(4)
+cfi=(258)
+cfn=(4590)
+calls=11819 28
+* 94552
+cob=(1)
+cfi=(54)
+cfn=(228)
+calls=1 34
+* 1722
+* 11823
+* 23638
++1 23638
+
+fn=(4188) __static_initialization_and_destruction_0(int, int)
+702 9
+fi=(198)
+74 2
+cob=(31)
+cfi=(157)
+cfn=(3796)
+calls=1 -74
+* 8
+* 1
+* 4
+cob=(3)
+cfi=(158)
+cfn=(2494)
+calls=1 -17
+* 66
+* 1
+fe=(217)
+702 2
+
+fn=(4304) IPDF::ParanoidNumber::SanityCheck(std::set<IPDF::ParanoidNumber*, std::less<IPDF::ParanoidNumber*>, std::allocator<IPDF::ParanoidNumber*> >&) const
+663 204685
++1 81874
++6 122811
+cfi=(234)
+cfn=(4306)
+calls=40937 343
+* 1269047
+* 327496
+cfi=(234)
+cfn=(4312)
+calls=40937 +31
+* 6918353
+* 245622
+cfi=(235)
+cfn=(4330) std::_Rb_tree_const_iterator<IPDF::ParanoidNumber*>::operator!=(std::_Rb_tree_const_iterator<IPDF::ParanoidNumber*> const&) const
+calls=40937 315
+* 491244
+* 81874
++6 286559
+cfi=(234)
+cfn=(4332)
+calls=40937 508
+* 30216000
++2 245622
+cfi=(229)
+cfn=(4280) std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> >::begin() const
+calls=40937 556
+* 1023425
+* 163748
+cfi=(229)
+cfn=(4284) std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> >::end() const
+calls=40937 574
+* 1023425
+* 286559
+cfi=(233)
+cfn=(4286) bool __gnu_cxx::operator!=<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >(__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > > const&, __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > > const&)
+calls=40937 829
+* 1309984
+* 81874
++5 245622
+cfi=(229)
+cfn=(4280)
+calls=40937 556
+* 1023425
+* 163748
+cfi=(229)
+cfn=(4284)
+calls=40937 574
+* 1023425
+* 286559
+cfi=(233)
+cfn=(4286)
+calls=40937 829
+* 1309984
+* 81874
++5 245622
+cfi=(229)
+cfn=(4280)
+calls=40937 556
+* 1023425
+* 163748
+cfi=(229)
+cfn=(4284)
+calls=40937 574
+* 1023425
+* 286559
+cfi=(233)
+cfn=(4286)
+calls=40937 829
+* 1309984
+* 81874
++6 245622
+cfi=(229)
+cfn=(4280)
+calls=40937 556
+* 1023425
+* 163748
+cfi=(229)
+cfn=(4284)
+calls=40937 574
+* 1023425
+* 286559
+cfi=(233)
+cfn=(4286)
+calls=40937 829
+* 1309977
+* 81872
++5 40936
++1 81872
+
+fn=(4440) IPDF::ParanoidNumber::operator/=(IPDF::ParanoidNumber const&)
+252 119
++1 34
+cob=(31)
+cfi=(157)
+cfn=(2642)
+calls=17 0
+* 1928
+* 17
+* 85
+cfi=(228)
+cfn=(4278) IPDF::ParanoidNumber::ParanoidNumber(IPDF::ParanoidNumber const&)
+calls=17 88
+* 48790
+* 119
+cfn=(4442)
+calls=17 502
+* 19579
+* 119
+cfn=(4458) IPDF::ParanoidNumber::~ParanoidNumber()
+calls=17 15
+* 17799
++1 68
+cfn=(4482) IPDF::ParanoidNumber::Simplify(IPDF::Optype)
+calls=17 533
+* 2227
++1 68
+cfn=(4482)
+calls=17 533
+* 2227
++1 34
++1 85
+
+fn=(4492) IPDF::ParanoidNumber::operator+=(IPDF::ParanoidNumber const&)
+224 68425
++3 19550
+cob=(31)
+cfi=(157)
+cfn=(2642)
+calls=9775 0
+* 1055700
+* 9775
+* 48875
+cfi=(228)
+cfn=(4278)
+calls=9775 88
+* 28054250
+* 68425
+cfn=(4442)
+calls=9775 502
+* 26831840
+* 68418
+cfn=(4458)
+calls=9774 15
+* 10233378
++1 39096
+cfn=(4482)
+calls=9774 533
+* 1280394
++1 39096
+cfn=(4482)
+calls=9774 533
+* 1280394
++1 19548
++1 48870
+
+fn=(4494)
+261 117351
++1 39117
+cfi=(228)
+cfn=(4290) IPDF::ParanoidNumber::SanityCheck() const
+calls=13039 115
+* 23678470
+* 39114
++6 39114
++1 39114
+cfi=(228)
+cfn=(4446)
+calls=13038 133
+* 1434180
+* 170184
++2 2760
++1 1380
++2 399
++1 399
+cfi=(229)
+cfn=(4530) void std::swap<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> >(std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> >&, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> >&)
+calls=57 1559
+* 13338
++3 1380
++2 63480
+cfi=(243) /usr/include/c++/4.9/bits/vector.tcc
+cfn=(4496) std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> >::operator=(std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > const&)
+calls=2760 167
+* 1272360
++1 33120
+cfi=(229)
+cfn=(4264)
+calls=2760 1211
+* 190440
+-3 9660
++7 1380
++2 37044
+cfi=(228)
+cfn=(4446)
+calls=12348 133
+* 1358280
+* 161069
++1 1090
++4 35409
+cfi=(228)
+cfn=(4448) IPDF::ParanoidNumber::NoFactors() const
+calls=11803 139
+* 542938
++1 23606
+-1 35409
+cfi=(228)
+cfn=(4448)
+calls=11803 139
+* 542938
+* 23606
++1 23606
+-1 23606
++3 94424
+cfi=(228)
+cfn=(4576)
+calls=11803 45
+* 885225
+* 23606
++2 47212
++1 70818
+cfi=(229)
+cfn=(4460)
+calls=11803 547
+* 259666
+* 47212
+cfi=(229)
+cfn=(4464)
+calls=11803 565
+* 271469
+* 82621
+cfi=(233)
+cfn=(4466)
+calls=11803 829
+* 377696
+* 23606
++4 47212
++1 17586
+cfi=(229)
+cfn=(4460)
+calls=2931 547
+* 64482
+-1 8872
++1 53232
+cfi=(229)
+cfn=(4460)
+calls=8872 547
+* 195184
+* 47212
+cfi=(229)
+cfn=(4464)
+calls=11803 565
+* 271469
+* 82621
+cfi=(233)
+cfn=(4466)
+calls=11803 829
+* 377696
+* 23606
++3 47212
+cfi=(229)
+cfn=(4264)
+calls=11803 1211
+* 814407
++1 47212
+cfi=(229)
+cfn=(4264)
+calls=11803 1211
+* 814407
++2 23606
++67 52152
+
+fn=(4186)
+702 5
+cfn=(4188)
+calls=1 *
+* 93
+* 2
+
+fn=(4490)
+614 71170
++1 42702
+cfi=(228)
+cfn=(4290)
+calls=14234 115
+* 25848944
+* 42702
++9 42702
++1 85404
+cfi=(229)
+cfn=(4280)
+calls=14234 -69
+* 355850
+* 56936
+cfi=(229)
+cfn=(4284)
+calls=14234 -51
+* 355850
+* 99638
+cfi=(233)
+cfn=(4286)
+calls=14234 829
+* 455488
+* 28468
++4 85404
+cfi=(229)
+cfn=(4280)
+calls=14234 -73
+* 355850
+* 56936
+cfi=(229)
+cfn=(4284)
+calls=14234 -55
+* 355850
+* 99638
+cfi=(233)
+cfn=(4286)
+calls=14234 829
+* 455488
+* 28468
++4 85404
+cfi=(229)
+cfn=(4280)
+calls=14234 -77
+* 355850
+* 56936
+cfi=(229)
+cfn=(4284)
+calls=14234 -59
+* 355850
+* 99638
+cfi=(233)
+cfn=(4286)
+calls=14234 829
+* 455488
+* 28468
++2 85404
+cfi=(229)
+cfn=(4280)
+calls=14234 -79
+* 355850
+* 56936
+cfi=(229)
+cfn=(4284)
+calls=14234 -61
+* 355850
+* 99638
+cfi=(233)
+cfn=(4286)
+calls=14234 829
+* 455488
+* 28468
++2 56936
++2 56936
+
+fn=(4458)
+15 4795
++2 2055
++1 1370
++2 38360
+cfi=(229)
+cfn=(4460)
+calls=2740 547
+* 60280
+* 10960
+cfi=(229)
+cfn=(4464)
+calls=2740 565
+* 63020
+* 19180
+cfi=(233)
+cfn=(4466)
+calls=2740 829
+* 87680
+* 5480
+-2 9590
+-3 26030
+cfi=(229)
+cfn=(4470) std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> >::~vector()
+calls=2740 423
+* 312360
+* 2740
++8 4795
+-8 52220
++8 39165
+cfn=(4459) IPDF::ParanoidNumber::~ParanoidNumber()'2
+calls=13055 -8
+* 12363085
+* 39165
+cob=(31)
+cfi=(157)
+cfn=(4428)
+calls=13055 -23
+* 1135785
+* 13055
+* 26110
+
+fn=(4459)
+15 91385
++2 39165
++1 26110
++2 731080
+cfi=(229)
+cfn=(4460)
+calls=52220 547
+* 1148840
+* 208880
+cfi=(229)
+cfn=(4464)
+calls=52220 565
+* 1201060
+* 365540
+cfi=(233)
+cfn=(4466)
+calls=52220 829
+* 1671040
+* 104440
+-2 182770
+-3 496090
+cfi=(229)
+cfn=(4470)
+calls=52220 423
+* 5953080
+* 52220
++8 91385
+
+fn=(4482)
+533 182770
++2 78330
+cfi=(228)
+cfn=(4446)
+calls=26110 133
+* 2872100
+* 52220
++1 52220
++64 52220
++1 130550
+
+fn=(4528) IPDF::ParanoidNumber::operator-=(IPDF::ParanoidNumber const&)
+235 22848
++1 6528
+cob=(31)
+cfi=(157)
+cfn=(2642)
+calls=3264 0
+* 352512
+* 3264
+* 16320
+cfi=(228)
+cfn=(4278)
+calls=3264 88
+* 9367680
+* 22848
+cfn=(4442)
+calls=3264 502
+* 8614668
+* 22848
+cfn=(4458)
+calls=3264 15
+* 3417408
++1 13056
+cfn=(4482)
+calls=3264 533
+* 427584
++1 13056
+cfn=(4482)
+calls=3264 533
+* 427584
++1 6528
++1 16320
+
+fl=(236)
+fn=(4334)
+101 122811
++1 122811
+
+fn=(4392) bool&& std::forward<bool>(std::remove_reference<bool>::type&)
+76 122811
++1 122811
+
+fn=(4348) IPDF::ParanoidNumber*&& std::forward<IPDF::ParanoidNumber*>(std::remove_reference<IPDF::ParanoidNumber*>::type&)
+76 736866
++1 736866
+
+fn=(4398) bool& std::forward<bool&>(std::remove_reference<bool&>::type&)
+76 122811
++1 122811
+
+fn=(4390) std::_Rb_tree_iterator<IPDF::ParanoidNumber*>&& std::forward<std::_Rb_tree_iterator<IPDF::ParanoidNumber*> >(std::remove_reference<std::_Rb_tree_iterator<IPDF::ParanoidNumber*> >::type&)
+76 122811
++1 122811
+
+fn=(4538) std::remove_reference<IPDF::ParanoidNumber**&>::type&& std::move<IPDF::ParanoidNumber**&>(IPDF::ParanoidNumber**&)
+101 1539
++1 1539
+
+fn=(4346) std::_Rb_tree_node<IPDF::ParanoidNumber*>*& std::forward<std::_Rb_tree_node<IPDF::ParanoidNumber*>*&>(std::remove_reference<std::_Rb_tree_node<IPDF::ParanoidNumber*>*&>::type&)
+76 245622
++1 245622
+
+fn=(4536) void std::swap<IPDF::ParanoidNumber**>(IPDF::ParanoidNumber**&, IPDF::ParanoidNumber**&)
+166 855
++9 513
+cfn=(4538)
+calls=171 -74
+* 1026
+* 342
++1 513
+cfn=(4538)
+calls=171 -75
+* 1026
+* 513
++1 513
+cfn=(4538)
+calls=171 -76
+* 1026
+* 513
++1 342
+
+fn=(4396) std::_Rb_tree_iterator<IPDF::ParanoidNumber*>& std::forward<std::_Rb_tree_iterator<IPDF::ParanoidNumber*>&>(std::remove_reference<std::_Rb_tree_iterator<IPDF::ParanoidNumber*>&>::type&)
+76 122811
++1 122811
+
+fl=(210)
+fn=(4148)
+422 5
+cfn=(4150) __static_initialization_and_destruction_0(int, int)
+calls=1 *
+* 1773
+* 2
+
+fn=(4150)
+422 9
+fi=(198)
+74 2
+cob=(31)
+cfi=(157)
+cfn=(3796)
+calls=1 -74
+* 8
+* 1
+* 4
+cob=(3)
+cfi=(158)
+cfn=(2494)
+calls=1 -17
+* 1746
+* 1
+fe=(210)
+422 2
+
+fl=(215)
+fn=(4178)
+524 5
+cfn=(4180) __static_initialization_and_destruction_0(int, int)
+calls=1 *
+* 93
+* 2
+
+fn=(4180)
+524 9
+fi=(198)
+74 2
+cob=(31)
+cfi=(157)
+cfn=(3796)
+calls=1 -74
+* 8
+* 1
+* 4
+cob=(3)
+cfi=(158)
+cfn=(2494)
+calls=1 -17
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+* 1
+fe=(215)
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+
+fl=(238)
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++1 122811
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+fn=(4394)
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+* 409370
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+* 245622
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+
+fn=(4344) std::pair<std::_Rb_tree_node_base*, std::_Rb_tree_node_base*>::pair<std::_Rb_tree_node<IPDF::ParanoidNumber*>*&, std::_Rb_tree_node<IPDF::ParanoidNumber*>*&, void>(std::_Rb_tree_node<IPDF::ParanoidNumber*>*&, std::_Rb_tree_node<IPDF::ParanoidNumber*>*&)
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++1 122811
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+* 245622
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+
+fl=(230) /usr/include/c++/4.9/bits/allocator.h
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+121 286552
+cfi=(231) /usr/include/c++/4.9/ext/new_allocator.h
+cfn=(4438) __gnu_cxx::new_allocator<std::_Rb_tree_node<IPDF::ParanoidNumber*> >::~new_allocator()
+calls=40936 -35
+* 204680
+* 81872
+
+fn=(4478) std::allocator<IPDF::ParanoidNumber*>::~allocator()
+121 384720
+cfi=(231)
+cfn=(4480) __gnu_cxx::new_allocator<IPDF::ParanoidNumber*>::~new_allocator()
+calls=54960 -35
+* 274800
+* 109920
+
+fn=(4298) std::allocator<std::_Rb_tree_node<IPDF::ParanoidNumber*> >::allocator()
+113 286559
+cfi=(231)
+cfn=(4300) __gnu_cxx::new_allocator<std::_Rb_tree_node<IPDF::ParanoidNumber*> >::new_allocator()
+calls=40937 -34
+* 204685
+* 81874
+
+fn=(4258) std::allocator<IPDF::ParanoidNumber*>::allocator()
+113 384972
+cfi=(231)
+cfn=(4260) __gnu_cxx::new_allocator<IPDF::ParanoidNumber*>::new_allocator()
+calls=54996 -34
+* 274980
+* 109992
+
+fl=(228)
+fn=(4276) IPDF::ParanoidNumber::operator/(IPDF::ParanoidNumber const&) const
+189 119
++2 85
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+calls=17 88
+* 56739
++1 85
+cfi=(217)
+cfn=(4440)
+calls=17 +60
+* 93298
++1 17
++1 85
+
+fn=(4486) IPDF::ParanoidNumber::operator<(IPDF::ParanoidNumber const&) const
+157 56872
+cfn=(4488) IPDF::ParanoidNumber::ToDouble() const
+calls=7109 -27
+* 16009468
+* 28436
+cfn=(4488)
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+* 28436
+
+fn=(4290)
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++2 122811
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+* 13594207
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++1 163744
+
+fn=(4454)
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+0 206316
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+0 670527
+0 309474
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+0 670527
+0 309474
+
+fn=(4262) IPDF::ParanoidNumber::Construct()
+107 54996
++2 27498
++1 659952
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+-1 192486
++2 41247
++1 27498
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+
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++2 154641
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+* 206188
++1 103094
+
+fn=(4250) IPDF::ParanoidNumber::ParanoidNumber(float)
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+cfi=(229)
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++2 255
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++1 425
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++2 35457
++1 23638
++3 23638
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++1 27328
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+-2 191296
++8 40992
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++1 68320
+
+fn=(4488)
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+
+fl=(231)
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+
+fn=(4416) void __gnu_cxx::new_allocator<std::_Rb_tree_node<IPDF::ParanoidNumber*> >::destroy<IPDF::ParanoidNumber*>(IPDF::ParanoidNumber**)
+124 245616
+
+fn=(4300)
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+
+fn=(4360) __gnu_cxx::new_allocator<std::_Rb_tree_node<IPDF::ParanoidNumber*> >::allocate(unsigned long, void const*)
+99 245622
++2 122811
+cfn=(4362) __gnu_cxx::new_allocator<std::_Rb_tree_node<IPDF::ParanoidNumber*> >::max_size() const
+calls=40937 +12
+* 245622
+* 163748
++3 286559
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+calls=40937 0
+* 4421202
+cob=(1)
+cfi=(54)
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+calls=1 -70
+* 1482
+* 40941
++1 81874
+
+fn=(4380) _ZN9__gnu_cxx13new_allocatorISt13_Rb_tree_nodeIPN4IPDF14ParanoidNumberEEE9constructIS4_IS4_EEEvPT_DpOT0_
+119 286559
++1 122811
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+* 245622
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+cfn=(4368) operator new(unsigned long, void*)
+calls=40937 +27
+* 286559
+* 286559
+
+fn=(4422) __gnu_cxx::new_allocator<std::_Rb_tree_node<IPDF::ParanoidNumber*> >::deallocate(std::_Rb_tree_node<IPDF::ParanoidNumber*>*, unsigned long)
+109 245616
++1 122808
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+* 81872
+
+fn=(4260)
+79 274980
+
+fn=(4362)
+113 122811
++1 122811
+
+fn=(4480)
+86 274800
+
+fl=(241) /usr/include/c++/4.9/ext/aligned_buffer.h
+fn=(4372) __gnu_cxx::__aligned_buffer<IPDF::ParanoidNumber*>::_M_ptr()
+63 327492
++1 245619
+cfn=(4374) __gnu_cxx::__aligned_buffer<IPDF::ParanoidNumber*>::_M_addr()
+calls=81873 -13
+* 491238
+* 163746
+
+fn=(4374)
+51 245619
++2 81873
++1 163746
+
+fl=(211)
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+cfn=(4158) __static_initialization_and_destruction_0(int, int)
+calls=1 *
+* 213
+* 2
+
+fn=(4158)
+1026 9
+fi=(198)
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+cob=(31)
+cfi=(157)
+cfn=(3796)
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+* 8
+* 1
+* 4
+cob=(3)
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+cfn=(2494)
+calls=1 -17
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+calls=1 10138
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+calls=1 57
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+* 1
+fe=(211)
+1026 2
+
+fl=(243)
+fn=(4496)
+167 24840
++3 8280
++3 2760
+cfi=(244) /usr/include/c++/4.9/ext/alloc_traits.h
+cfn=(4498) __gnu_cxx::__alloc_traits<std::allocator<IPDF::ParanoidNumber*> >::_S_propagate_on_copy_assign()
+calls=2760 -28
+* 13800
+* 5520
++18 8280
+cfi=(229)
+cfn=(4450)
+calls=2760 654
+* 35880
+* 2760
++1 8280
+cfi=(229)
+cfn=(4500) std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> >::capacity() const
+calls=2760 734
+* 35880
+* 11040
++12 8280
+cfi=(229)
+cfn=(4450)
+calls=2760 654
+* 35880
+* 11040
++3 8280
+cfi=(229)
+cfn=(4268) std::_Vector_base<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> >::_M_get_Tp_allocator()
+calls=2760 -94
+* 16560
+* 11040
+cfi=(229)
+cfn=(4464)
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+cfn=(4280)
+calls=2760 556
+* 69000
+* 11040
+cfi=(245) /usr/include/c++/4.9/bits/stl_algobase.h
+cfn=(4502) __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > > std::copy<__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >, __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > > >(__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >, __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >, __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >)
+calls=2760 456
+* 576840
+-1 11040
+cfi=(232) /usr/include/c++/4.9/bits/stl_construct.h
+cfn=(4522) void std::_Destroy<__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >, IPDF::ParanoidNumber*>(__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >, __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >, std::allocator<IPDF::ParanoidNumber*>&)
+calls=2760 -58
+* 85560
+* 2760
++12 19320
++2 2760
++1 19320
+
+fl=(197)
+fn=(3788) __static_initialization_and_destruction_0(int, int)
+151 9
+fi=(198)
+-77 2
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+cfn=(3796)
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+cob=(1)
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+cfi=(158)
+cfn=(2494)
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+cob=(1)
+cfi=(54)
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+calls=1 -40
+* 2113
+* 5
+fe=(197)
++77 2
+
+fn=(4212)
+46 24
++10 12
++1 26
++2 4
++3 12
+cob=(3)
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+cfn=(3418)
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+* 1898
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++3 4
++5 20
++15 2
++1 2
++8 28
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++3 6
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+fn=(3786)
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+* 136751
+* 2
+
+fl=(220)
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++1 1
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+* 7538
++1 7
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+calls=1 +35
+* 2361
++2 1
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+cfn=(4244)
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+* 31
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+* 1799
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++1 1
++1 2
++2 2
++2 17
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+cfn=(4244)
+calls=17 +10
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+* 17
++1 85
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+* 150428
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+cfi=(228)
+cfn=(4250)
+calls=17 +58
+* 10081
+* 102
+cfi=(242) /home/sam/ipdf/code/src/tests/stresstest.h
+cfn=(4484) IPDF::ParanoidNumber AddSub<IPDF::ParanoidNumber>(IPDF::ParanoidNumber const&, IPDF::ParanoidNumber const&, IPDF::ParanoidNumber const&)
+calls=17 -7
+* 126434371
+* 48
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+cfn=(4458)
+calls=16 -5
+* 15152
+* 48
+cfi=(217)
+cfn=(4458)
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++1 16
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+* 16
++1 48
++1 96
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++2 48
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+* 15152
+-8 50
+-2 2
+
+fn=(4198)
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+cfn=(4200) __static_initialization_and_destruction_0(int, int)
+calls=1 *
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+
+fn=(4200)
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+fe=(220)
+-31 2
+
+fl=(246) /usr/include/c++/4.9/bits/stl_iterator_base_types.h
+fn=(4506) std::_Iter_base<__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >, false>::_S_base(__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >)
+212 16560
++1 16560
+
+fn=(4512) std::_Iter_base<__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >, true>::_S_base(__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >)
+220 11040
++1 8280
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+cfn=(4468) __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >::base() const
+calls=2760 793
+* 16560
+* 8280
+
+fn=(4516) std::_Iter_base<__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >, true>::_S_base(__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >)
+220 22080
++1 16560
+cfi=(233)
+cfn=(4288) __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >::base() const
+calls=5520 793
+* 33120
+* 16560
+
+fl=(242)
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++2 68
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+-7 705
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+cfn=(4458)
+calls=16 -1
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++12 80
+cfi=(228)
+cfn=(4278)
+calls=16 +60
+* 45920
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++2 685
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++1 685
+cfi=(228)
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++2 7605
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+-2 7605
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++4 685
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+* 393190
+* 137
++2 7605
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+calls=1521 235
+* 10550115
+-2 7605
+cfi=(217)
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+* 10847509
+* 8290
+cfi=(228)
+cfn=(4486)
+calls=1658 157
+* 7494160
+* 3727
+cfi=(217)
+cfn=(4458)
+calls=137 -20
+* 129739
+-7 685
+cfi=(217)
+cfn=(4492)
+calls=137 224
+* 982986
+* 765
+cfi=(228)
+cfn=(4486)
+calls=153 157
+* 691560
+* 354
+cfi=(217)
+cfn=(4458)
+calls=16 -13
+* 15152
++12 16
++1 80
+
+fl=(218)
+fn=(4192) __static_initialization_and_destruction_0(int, int)
+200 9
+fi=(198)
+74 2
+cob=(31)
+cfi=(157)
+cfn=(3796)
+calls=1 -74
+* 8
+* 1
+* 4
+cob=(3)
+cfi=(158)
+cfn=(2494)
+calls=1 -17
+* 66
+* 1
+fe=(218)
+200 2
+
+fn=(4190)
+200 5
+cfn=(4192)
+calls=1 *
+* 93
+* 2
+
+fl=(244)
+fn=(4540) __gnu_cxx::__alloc_traits<std::allocator<IPDF::ParanoidNumber*> >::_S_on_swap(std::allocator<IPDF::ParanoidNumber*>&, std::allocator<IPDF::ParanoidNumber*>&)
+142 285
++1 285
+cfi=(239) /usr/include/c++/4.9/bits/alloc_traits.h
+cfn=(4542) void std::__alloc_on_swap<std::allocator<IPDF::ParanoidNumber*> >(std::allocator<IPDF::ParanoidNumber*>&, std::allocator<IPDF::ParanoidNumber*>&)
+calls=57 490
+* 1197
+* 114
+
+fn=(4498)
+145 5520
++1 8280
+
+fl=(239)
+fn=(4420) std::allocator_traits<std::allocator<std::_Rb_tree_node<IPDF::ParanoidNumber*> > >::deallocate(std::allocator<std::_Rb_tree_node<IPDF::ParanoidNumber*> >&, std::_Rb_tree_node<IPDF::ParanoidNumber*>*, unsigned long)
+382 245616
++1 245616
+cfi=(231)
+cfn=(4422)
+calls=40936 109
+* 4056119
+* 81872
+
+fn=(4544) void std::__do_alloc_on_swap<std::allocator<IPDF::ParanoidNumber*> >(std::allocator<IPDF::ParanoidNumber*>&, std::allocator<IPDF::ParanoidNumber*>&, std::integral_constant<bool, false>)
+486 228
++1 114
+
+fn=(4378) _ZNSt16allocator_traitsISaISt13_Rb_tree_nodeIPN4IPDF14ParanoidNumberEEEE12_S_constructIS3_IS3_EEENSt9enable_ifIXsrSt6__and_IINS6_18__construct_helperIT_IDpT0_EE4typeEEE5valueEvE4typeERS5_PSB_DpOSC_
+252 245622
++1 122811
+cfi=(236)
+cfn=(4348)
+calls=40937 76
+* 245622
+* 245622
+cfi=(231)
+cfn=(4380)
+calls=40937 119
+* 1432795
+* 81874
+
+fn=(4414) std::enable_if<std::__and_<std::allocator_traits<std::allocator<std::_Rb_tree_node<IPDF::ParanoidNumber*> > >::__destroy_helper<IPDF::ParanoidNumber*>::type>::value, void>::type std::allocator_traits<std::allocator<std::_Rb_tree_node<IPDF::ParanoidNumber*> > >::_S_destroy<IPDF::ParanoidNumber*>(std::allocator<std::_Rb_tree_node<IPDF::ParanoidNumber*> >&, IPDF::ParanoidNumber**)
+281 204680
++1 204680
+cfi=(231)
+cfn=(4416)
+calls=40936 124
+* 245616
+* 81872
+
+fn=(4376) _ZNSt16allocator_traitsISaISt13_Rb_tree_nodeIPN4IPDF14ParanoidNumberEEEE9constructIS3_IS3_EEEDTcl12_S_constructfp_fp0_spcl7forwardIT0_Efp1_EEERS5_PT_DpOS8_
+397 245622
++2 122811
+cfi=(236)
+cfn=(4348)
+calls=40937 76
+* 245622
+* 245622
+cfn=(4378)
+calls=40937 252
+* 2374346
+* 81874
+
+fn=(4358) std::allocator_traits<std::allocator<std::_Rb_tree_node<IPDF::ParanoidNumber*> > >::allocate(std::allocator<std::_Rb_tree_node<IPDF::ParanoidNumber*> >&, unsigned long)
+356 204685
++1 245622
+cfi=(231)
+cfn=(4360)
+calls=40937 99
+* 5609861
+* 81874
+
+fn=(4542)
+490 285
++4 399
+cfn=(4544)
+calls=57 -8
+* 342
+* 57
++1 114
+
+fn=(4412) void std::allocator_traits<std::allocator<std::_Rb_tree_node<IPDF::ParanoidNumber*> > >::destroy<IPDF::ParanoidNumber*>(std::allocator<std::_Rb_tree_node<IPDF::ParanoidNumber*> >&, IPDF::ParanoidNumber**)
+410 204680
++1 204680
+cfn=(4414)
+calls=40936 281
+* 736848
+* 81872
+
+fl=(237) /usr/include/c++/4.9/bits/stl_function.h
+fn=(4338) std::_Identity<IPDF::ParanoidNumber*>::operator()(IPDF::ParanoidNumber*&) const
+826 163748
++1 122811
+
+fl=(214)
+fn=(4176) __static_initialization_and_destruction_0(int, int)
+526 9
+fi=(198)
+74 2
+cob=(31)
+cfi=(157)
+cfn=(3796)
+calls=1 -74
+* 8
+* 1
+* 4
+cob=(3)
+cfi=(158)
+cfn=(2494)
+calls=1 -17
+* 66
+* 1
+fe=(214)
+526 2
+
+fn=(4174)
+526 5
+cfn=(4176)
+calls=1 *
+* 93
+* 2
+
+fl=(209)
+fn=(4144)
+30 5
+cfn=(4146) __static_initialization_and_destruction_0(int, int)
+calls=1 *
+* 93
+* 2
+
+fn=(4146)
+30 9
+fi=(198)
++44 2
+cob=(31)
+cfi=(157)
+cfn=(3796)
+calls=1 -74
+* 8
+* 1
+* 4
+cob=(3)
+cfi=(158)
+cfn=(2494)
+calls=1 -17
+* 66
+* 1
+fe=(209)
+-44 2
+
+fl=(213)
+fn=(4170)
+583 5
+cfn=(4172) __static_initialization_and_destruction_0(int, int)
+calls=1 *
+* 93
+* 2
+
+fn=(4172)
+583 9
+fi=(198)
+74 2
+cob=(31)
+cfi=(157)
+cfn=(3796)
+calls=1 -74
+* 8
+* 1
+* 4
+cob=(3)
+cfi=(158)
+cfn=(2494)
+calls=1 -17
+* 66
+* 1
+fe=(213)
+583 2
+
+fl=(233)
+fn=(4466)
+829 471588
++3 235794
+cfn=(4468)
+calls=78598 -39
+* 471588
+* 314392
+cfn=(4468)
+calls=78598 -39
+* 471588
+* 550186
+
+fn=(4288)
+793 1668600
++1 1668600
+
+fn=(4282) __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >::__normal_iterator(IPDF::ParanoidNumber* const* const&)
+728 2224800
++1 3337200
+
+fn=(4462) __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >::__normal_iterator(IPDF::ParanoidNumber** const&)
+728 661904
++1 992856
+
+fn=(4468)
+793 479868
++1 479868
+
+fn=(4286)
+829 1652040
++3 826020
+cfn=(4288)
+calls=275340 -39
+* 1652040
+* 1101360
+cfn=(4288)
+calls=275340 -39
+* 1652040
+* 1927373
+
+fl=(229)
+fn=(4252)
+253 219984
++4 164988
+cfn=(4254) std::_Vector_base<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> >::_Vector_base()
+calls=54996 124
+* 2089848
+* 109992
+
+fn=(4264)
+1211 325576
++1 488364
+cfn=(4266) std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> >::_M_erase_at_end(IPDF::ParanoidNumber**)
+calls=81394 1436
+* 4639458
+* 162788
+
+fn=(4268)
+113 417684
++1 417684
+
+fn=(4472) std::_Vector_base<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> >::~_Vector_base()
+159 219840
++2 604560
+-1 219840
+cfn=(4474) std::_Vector_base<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> >::_M_deallocate(IPDF::ParanoidNumber**, unsigned long)
+calls=54960 +14
+* 549600
++1 164880
+cfn=(4476) std::_Vector_base<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> >::_Vector_impl::~_Vector_impl()
+calls=54960 -82
+* 1264080
+* 109920
+
+fn=(4256) std::_Vector_base<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> >::_Vector_impl::_Vector_impl()
+86 219984
++1 164988
+cfi=(230)
+cfn=(4258)
+calls=54996 +26
+* 769944
+* 329976
++1 109992
+
+fn=(4534) std::_Vector_base<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> >::_Vector_impl::_M_swap_data(std::_Vector_base<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> >::_Vector_impl&)
+101 285
++2 285
+cfi=(236)
+cfn=(4536)
+calls=57 +63
+* 2394
++1 399
+cfi=(236)
+cfn=(4536)
+calls=57 +62
+* 2394
++1 399
+cfi=(236)
+cfn=(4536)
+calls=57 +61
+* 2394
++1 114
+
+fn=(4266)
+1436 406970
++2 244182
+cfn=(4268)
+calls=81394 113
+* 488364
+* 569758
+cfi=(232)
+cfn=(4270) void std::_Destroy<IPDF::ParanoidNumber**, IPDF::ParanoidNumber*>(IPDF::ParanoidNumber**, IPDF::ParanoidNumber**, std::allocator<IPDF::ParanoidNumber*>&)
+calls=81394 148
+* 2523214
++1 244182
++1 162788
+
+fn=(4284)
+574 1112400
++1 2224800
+cfi=(233)
+cfn=(4282)
+calls=278100 728
+* 2781000
+* 834300
+
+fn=(4460)
+547 325432
++1 406790
+cfi=(233)
+cfn=(4462)
+calls=81358 728
+* 813580
+* 244074
+
+fn=(4254)
+124 219984
++1 164988
+cfn=(4256)
+calls=54996 -39
+* 1594884
+* 109992
+
+fn=(4450)
+654 776952
++1 2589840
+
+fn=(4464)
+565 325432
++1 488148
+cfi=(233)
+cfn=(4462)
+calls=81358 728
+* 813580
+* 244074
+
+fn=(4476)
+79 384720
+cfi=(230)
+cfn=(4478)
+calls=54960 +42
+* 769440
+* 109920
+
+fn=(4280)
+556 1112400
++1 2224800
+cfi=(233)
+cfn=(4282)
+calls=278100 728
+* 2781000
+* 834300
+
+fn=(4470)
+423 219840
++2 164880
+cfn=(4268)
+calls=54960 113
+* 329760
+* 274800
+-1 164880
+cfi=(232)
+cfn=(4270)
+calls=54960 148
+* 1703760
++1 164880
+cfn=(4472)
+calls=54960 159
+* 3132720
+* 109920
+
+fn=(4474)
+174 329760
++3 109920
++2 109920
+
+fn=(4500)
+734 8280
++2 27600
+
+fn=(4530)
+1559 285
++1 285
+cfn=(4532) std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> >::swap(std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> >&)
+calls=57 1194
+* 12654
+* 114
+
+fn=(4532)
+1194 342
++5 285
+cfn=(4534)
+calls=57 101
+* 8664
++2 171
+cfn=(4268)
+calls=57 113
+* 342
+* 57
+-1 171
+cfn=(4268)
+calls=57 113
+* 342
+* 171
+cfi=(244)
+cfn=(4540)
+calls=57 142
+* 1881
++2 228
+
+fl=(240)
+fn=(4368)
+147 573118
+
+fl=(245)
+fn=(4502)
+456 19320
++10 8280
+cfn=(4504) std::_Miter_base<__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > > >::iterator_type std::__miter_base<__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > > >(__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >)
+calls=2760 289
+* 41400
+* 11040
+cfn=(4504)
+calls=2760 289
+* 41400
+* 16560
+cfn=(4508) __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > > std::__copy_move_a2<false, __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >, __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > > >(__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >, __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >, __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >)
+calls=2760 -36
+* 427800
++1 11040
+
+fn=(4504)
+289 22080
++1 16560
+cfi=(246)
+cfn=(4506)
+calls=5520 -78
+* 33120
+* 11040
+
+fn=(4520) IPDF::ParanoidNumber** std::__copy_move<false, true, std::random_access_iterator_tag>::__copy_m<IPDF::ParanoidNumber*>(IPDF::ParanoidNumber* const*, IPDF::ParanoidNumber* const*, IPDF::ParanoidNumber**)
+369 16560
++7 16560
++1 5520
++2 11040
++1 5520
+
+fn=(4510) std::_Niter_base<__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > > >::iterator_type std::__niter_base<__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > > >(__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >)
+278 11040
++1 8280
+cfi=(246)
+cfn=(4512)
+calls=2760 -59
+* 44160
+* 5520
+
+fn=(4514) std::_Niter_base<__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > > >::iterator_type std::__niter_base<__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > > >(__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >)
+278 22080
++1 16560
+cfi=(246)
+cfn=(4516)
+calls=5520 -59
+* 88320
+* 11040
+
+fn=(4518) IPDF::ParanoidNumber** std::__copy_move_a<false, IPDF::ParanoidNumber* const*, IPDF::ParanoidNumber**>(IPDF::ParanoidNumber* const*, IPDF::ParanoidNumber* const*, IPDF::ParanoidNumber**)
+385 16560
++8 2760
++3 16560
+cfn=(4520)
+calls=2760 -27
+* 55200
++1 5520
+
+fn=(4508)
+430 22080
++4 8280
+cfn=(4510)
+calls=2760 278
+* 69000
+* 11040
+cfn=(4514)
+calls=2760 278
+* 69000
+* 11040
+cfn=(4514)
+calls=2760 278
+* 69000
+* 11040
+cfn=(4518)
+calls=2760 -49
+* 96600
+* 16560
+cfi=(233)
+cfn=(4462)
+calls=2760 728
+* 27600
+* 2760
++1 13800
+
+fl=(235)
+fn=(4314)
+1910 245622
++3 122811
+cfn=(4316) std::_Rb_tree<IPDF::ParanoidNumber*, IPDF::ParanoidNumber*, std::_Identity<IPDF::ParanoidNumber*>, std::less<IPDF::ParanoidNumber*>, std::allocator<IPDF::ParanoidNumber*> >::_M_end()
+calls=40937 528
+* 286559
+* 163748
+cfn=(4318) std::_Rb_tree<IPDF::ParanoidNumber*, IPDF::ParanoidNumber*, std::_Identity<IPDF::ParanoidNumber*>, std::less<IPDF::ParanoidNumber*>, std::allocator<IPDF::ParanoidNumber*> >::_M_begin()
+calls=40937 517
+* 286559
+* 286559
+cfn=(4320) std::_Rb_tree<IPDF::ParanoidNumber*, IPDF::ParanoidNumber*, std::_Identity<IPDF::ParanoidNumber*>, std::less<IPDF::ParanoidNumber*>, std::allocator<IPDF::ParanoidNumber*> >::_M_lower_bound(std::_Rb_tree_node<IPDF::ParanoidNumber*>*, std::_Rb_tree_node<IPDF::ParanoidNumber*>*, IPDF::ParanoidNumber* const&)
+calls=40937 1256
+* 1105299
+* 40937
++1 122811
+cfn=(4324) std::_Rb_tree<IPDF::ParanoidNumber*, IPDF::ParanoidNumber*, std::_Identity<IPDF::ParanoidNumber*>, std::less<IPDF::ParanoidNumber*>, std::allocator<IPDF::ParanoidNumber*> >::end()
+calls=40937 740
+* 900614
+* 40937
++2 40937
+-2 204685
+cfn=(4326) std::_Rb_tree_iterator<IPDF::ParanoidNumber*>::operator==(std::_Rb_tree_iterator<IPDF::ParanoidNumber*> const&) const
+calls=40937 231
+* 491244
++2 204685
+cfn=(4324)
+calls=40937 740
+* 900614
+* 40937
+-2 81874
++3 163748
+
+fn=(4350) std::_Rb_tree_iterator<IPDF::ParanoidNumber*> std::_Rb_tree<IPDF::ParanoidNumber*, IPDF::ParanoidNumber*, std::_Identity<IPDF::ParanoidNumber*>, std::less<IPDF::ParanoidNumber*>, std::allocator<IPDF::ParanoidNumber*> >::_M_insert_<IPDF::ParanoidNumber*>(std::_Rb_tree_node_base*, std::_Rb_tree_node_base*, IPDF::ParanoidNumber*&&)
+1132 368433
++9 122811
+-2 122811
+cfn=(4316)
+calls=40937 528
+* 286559
++2 204685
+-1 40937
++1 40937
++2 122811
+cfi=(236)
+cfn=(4348)
+calls=40937 76
+* 245622
+* 204685
+cfn=(4352) std::_Rb_tree_node<IPDF::ParanoidNumber*>* std::_Rb_tree<IPDF::ParanoidNumber*, IPDF::ParanoidNumber*, std::_Identity<IPDF::ParanoidNumber*>, std::less<IPDF::ParanoidNumber*>, std::allocator<IPDF::ParanoidNumber*> >::_M_create_node<IPDF::ParanoidNumber*>(IPDF::ParanoidNumber*&&)
+calls=40937 415
+* 13510702
+* 40937
++3 122811
+-1 163748
+cob=(31)
+cfi=(157)
+cfn=(4386)
+calls=40937 0
+* 1228110
+cob=(1)
+cfi=(54)
+cfn=(228)
+calls=1 34
+* 2998
+* 40941
++2 204685
++1 204685
+cfn=(4322) std::_Rb_tree_iterator<IPDF::ParanoidNumber*>::_Rb_tree_iterator(std::_Rb_tree_node<IPDF::ParanoidNumber*>*)
+calls=40937 189
+* 368433
+* 81874
++1 204685
+
+fn=(4408) std::_Rb_tree<IPDF::ParanoidNumber*, IPDF::ParanoidNumber*, std::_Identity<IPDF::ParanoidNumber*>, std::less<IPDF::ParanoidNumber*>, std::allocator<IPDF::ParanoidNumber*> >::_S_left(std::_Rb_tree_node_base*)
+544 122808
++1 163744
+
+fn=(4330)
+315 163748
++1 327496
+
+fn=(4336)
+1489 204685
++9 204685
+cfi=(237)
+cfn=(4338)
+calls=40937 826
+* 286559
+* 204685
+cfn=(4340) std::_Rb_tree<IPDF::ParanoidNumber*, IPDF::ParanoidNumber*, std::_Identity<IPDF::ParanoidNumber*>, std::less<IPDF::ParanoidNumber*>, std::allocator<IPDF::ParanoidNumber*> >::_M_get_insert_unique_pos(IPDF::ParanoidNumber* const&)
+calls=40937 -63
+* 5567432
+* 81874
++2 122811
++3 40937
+-1 122811
+cfi=(236)
+cfn=(4348)
+calls=40937 76
+* 245622
+* 122811
++1 122811
+cfn=(4350)
+calls=40937 1132
+* 17934900
+* 286559
+cfi=(238)
+cfn=(4388)
+calls=40937 144
+* 1350921
+* 122811
++3 81874
+
+fn=(4356) std::_Rb_tree<IPDF::ParanoidNumber*, IPDF::ParanoidNumber*, std::_Identity<IPDF::ParanoidNumber*>, std::less<IPDF::ParanoidNumber*>, std::allocator<IPDF::ParanoidNumber*> >::_M_get_Node_allocator()
+371 491238
++1 491238
+
+fn=(4406) std::_Rb_tree<IPDF::ParanoidNumber*, IPDF::ParanoidNumber*, std::_Identity<IPDF::ParanoidNumber*>, std::less<IPDF::ParanoidNumber*>, std::allocator<IPDF::ParanoidNumber*> >::_S_right(std::_Rb_tree_node_base*)
+552 122808
++1 163744
+
+fn=(4318)
+517 368430
++1 491240
+
+fn=(4302) std::_Rb_tree<IPDF::ParanoidNumber*, IPDF::ParanoidNumber*, std::_Identity<IPDF::ParanoidNumber*>, std::less<IPDF::ParanoidNumber*>, std::allocator<IPDF::ParanoidNumber*> >::_Rb_tree_impl<std::less<IPDF::ParanoidNumber*>, true>::_M_initialize()
+480 122811
++2 81874
++1 81874
++1 163748
++1 163748
++1 81874
+
+fn=(4308)
+744 163748
++3 245622
+cfn=(4310) std::_Rb_tree_const_iterator<IPDF::ParanoidNumber*>::_Rb_tree_const_iterator(std::_Rb_tree_node<IPDF::ParanoidNumber*> const*)
+calls=40937 261
+* 368433
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++1 81874
+
+fn=(4320)
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++4 122811
++5 204685
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++1 81874
+
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++4 122811
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++1 122811
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++1 40937
++1 163748
++6 204685
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++1 81874
++2 122811
+cfn=(4342) std::_Rb_tree<IPDF::ParanoidNumber*, IPDF::ParanoidNumber*, std::_Identity<IPDF::ParanoidNumber*>, std::less<IPDF::ParanoidNumber*>, std::allocator<IPDF::ParanoidNumber*> >::begin()
+calls=40937 726
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++1 245622
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++7 81874
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++1 81874
+
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++1 491244
+
+fn=(4354) std::_Rb_tree<IPDF::ParanoidNumber*, IPDF::ParanoidNumber*, std::_Identity<IPDF::ParanoidNumber*>, std::less<IPDF::ParanoidNumber*>, std::allocator<IPDF::ParanoidNumber*> >::_M_get_node()
+384 163748
++1 122811
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+
+fn=(4402)
+714 163744
++1 122808
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+calls=40936 517
+* 286552
+* 204680
+cfn=(4404) std::_Rb_tree<IPDF::ParanoidNumber*, IPDF::ParanoidNumber*, std::_Identity<IPDF::ParanoidNumber*>, std::less<IPDF::ParanoidNumber*>, std::allocator<IPDF::ParanoidNumber*> >::_M_erase(std::_Rb_tree_node<IPDF::ParanoidNumber*>*)
+calls=40936 1239
+* 11301791
+* 122808
+cfn=(4434) std::_Rb_tree<IPDF::ParanoidNumber*, IPDF::ParanoidNumber*, std::_Identity<IPDF::ParanoidNumber*>, std::less<IPDF::ParanoidNumber*>, std::allocator<IPDF::ParanoidNumber*> >::_Rb_tree_impl<std::less<IPDF::ParanoidNumber*>, true>::~_Rb_tree_impl()
+calls=40936 455
+* 941528
+* 81872
+
+fn=(4410) std::_Rb_tree<IPDF::ParanoidNumber*, IPDF::ParanoidNumber*, std::_Identity<IPDF::ParanoidNumber*>, std::less<IPDF::ParanoidNumber*>, std::allocator<IPDF::ParanoidNumber*> >::_M_destroy_node(std::_Rb_tree_node<IPDF::ParanoidNumber*>*)
+434 245616
++2 122808
+cfn=(4370) std::_Rb_tree_node<IPDF::ParanoidNumber*>::_M_valptr()
+calls=40936 150
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+cfn=(4356)
+calls=40936 -65
+* 245616
+* 122808
+cfi=(239)
+cfn=(4412)
+calls=40936 -26
+* 1228080
++2 204680
+cfn=(4418) std::_Rb_tree<IPDF::ParanoidNumber*, IPDF::ParanoidNumber*, std::_Identity<IPDF::ParanoidNumber*>, std::less<IPDF::ParanoidNumber*>, std::allocator<IPDF::ParanoidNumber*> >::_M_put_node(std::_Rb_tree_node<IPDF::ParanoidNumber*>*)
+calls=40936 -50
+* 5529815
++1 163744
+
+fn=(4434)
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+
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+
+fn=(4404)
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++4 40936
++2 122808
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+cfn=(4405) std::_Rb_tree<IPDF::ParanoidNumber*, IPDF::ParanoidNumber*, std::_Identity<IPDF::ParanoidNumber*>, std::less<IPDF::ParanoidNumber*>, std::allocator<IPDF::ParanoidNumber*> >::_M_erase(std::_Rb_tree_node<IPDF::ParanoidNumber*>*)'2
+calls=40936 -6
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++1 122808
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++1 204680
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++7 81872
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+
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+
+fn=(4294)
+664 286559
+cfn=(4296) std::_Rb_tree<IPDF::ParanoidNumber*, IPDF::ParanoidNumber*, std::_Identity<IPDF::ParanoidNumber*>, std::less<IPDF::ParanoidNumber*>, std::allocator<IPDF::ParanoidNumber*> >::_Rb_tree_impl<std::less<IPDF::ParanoidNumber*>, true>::_Rb_tree_impl()
+calls=40937 461
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+
+fn=(4296)
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++2 122811
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++1 122811
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+
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+
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+
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+
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+
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++9 81874
++1 204685
+
+fl=(232)
+fn=(4524) void std::_Destroy<__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > > >(__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >, __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >)
+122 13800
++4 13800
+cfn=(4526) void std::_Destroy_aux<true>::__destroy<__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > > >(__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >, __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >)
+calls=2760 -14
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++2 5520
+
+fn=(4270)
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++3 681770
+cfn=(4272) void std::_Destroy<IPDF::ParanoidNumber**>(IPDF::ParanoidNumber**, IPDF::ParanoidNumber**)
+calls=136354 -29
+* 2454372
++1 272708
+
+fn=(4274) void std::_Destroy_aux<true>::__destroy<IPDF::ParanoidNumber**>(IPDF::ParanoidNumber**, IPDF::ParanoidNumber**)
+112 818124
+
+fn=(4272)
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++4 681770
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++2 272708
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+
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--- /dev/null
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+
+desc: I1 cache:
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++4 10597996
++1 3973314
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+-1 1987280
++1 11923680
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++3 10597996
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++1 10597996
+cfi=(229)
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++2 5298998
++71 5380264
+
+fn=(4284) IPDF::ParanoidNumber::OperationFactor(IPDF::ParanoidNumber*, IPDF::Optype, IPDF::ParanoidNumber**, IPDF::Optype*)
+495 990
++4 297
++3 396
++11 297
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++5 297
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++13 297
+cfi=(228)
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++1 2
++4 294
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++2 784
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++2 392
++1 588
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++4 392
++1 588
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++3 392
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++1 392
+cfi=(229)
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++1 196
++77 495
+
+fn=(4340)
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++2 16141386
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+calls=5380462 138
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++1 10760924
++77 10760924
++1 26902310
+
+fn=(4276) IPDF::ParanoidNumber::operator/=(IPDF::ParanoidNumber const&)
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++1 198
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+calls=99 0
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++1 396
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++1 396
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++1 198
++1 495
+
+fn=(4186)
+905 5
+cfn=(4188)
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+
+fn=(4282)
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++2 5380462
++4 9415858
++1 21521056
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++1 396
++1 792
+cfn=(4284)
+calls=99 495
+* 96972
+* 99
++2 5380462
+
+fn=(4348) IPDF::ParanoidNumber::Digit() const
+764 10922476
++4 8191857
++2 10922476
+cfi=(235)
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+calls=2730619 619
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++1 4156362
++4 5380660
++1 8070990
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+* 33629125
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+* 33629125
+* 9416155
+cfi=(232)
+cfn=(4272) bool __gnu_cxx::operator!=<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >(__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > > const&, __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > > const&)
+calls=1345165 +53
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++4 8070990
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++4 8070990
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++2 8070990
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++2 5380660
++2 2690330
+-2 2770908
++2 2770908
+
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++3 247848
++3 82616
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+calls=82616 -28
+* 413080
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++18 247848
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++12 247848
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++3 247848
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+* 2065400
+* 330464
+cfi=(229)
+cfn=(4266)
+calls=82616 556
+* 2065400
+* 330464
+cfi=(238) /usr/include/c++/4.9/bits/stl_algobase.h
+cfn=(4362) __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > > std::copy<__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >, __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > > >(__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >, __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >, __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >)
+calls=82616 456
+* 17266744
+-1 330464
+cfi=(233)
+cfn=(4382) void std::_Destroy<__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >, IPDF::ParanoidNumber*>(__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >, __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >, std::allocator<IPDF::ParanoidNumber*>&)
+calls=82616 -58
+* 2561096
+* 82616
++12 578312
++2 82616
++1 578312
+
+fl=(216)
+fn=(4184) __static_initialization_and_destruction_0(int, int)
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+fe=(216)
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+
+fn=(4182)
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+cfn=(4184)
+calls=1 *
+* 93
+* 2
+
+fl=(241) /usr/include/c++/4.9/bits/alloc_traits.h
+fn=(4408) void std::__do_alloc_on_swap<std::allocator<IPDF::ParanoidNumber*> >(std::allocator<IPDF::ParanoidNumber*>&, std::allocator<IPDF::ParanoidNumber*>&, std::integral_constant<bool, false>)
+486 1272
++1 636
+
+fn=(4406) void std::__alloc_on_swap<std::allocator<IPDF::ParanoidNumber*> >(std::allocator<IPDF::ParanoidNumber*>&, std::allocator<IPDF::ParanoidNumber*>&)
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++4 2226
+cfn=(4408)
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+* 318
++1 636
+
+fl=(224) /home/sam/Documents/University/2014/ipdf/code/src/real.h
+fn=(4210) IPDF::DebugRealInfo()
+181 13
+cfi=(197)
+cfn=(4212) LogEx(int, char const*, char const*, int, ...)
+calls=1 46
+* 7546
+* 3
+
+fn=(4410) IPDF::Double(IPDF::ParanoidNumber const&)
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++1 1
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++1 7
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++2 1
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++1 2
++2 2
++2 99
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++1 495
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+calls=99 +63
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+cfi=(234) /home/sam/Documents/University/2014/ipdf/code/src/tests/stresstest.h
+cfn=(4342) IPDF::ParanoidNumber AddSub<IPDF::ParanoidNumber>(IPDF::ParanoidNumber const&, IPDF::ParanoidNumber const&, IPDF::ParanoidNumber const&)
+calls=99 -7
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++1 297
++1 594
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++2 297
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+-2 5
++12 1
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++2 6
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+fn=(4198)
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+fl=(239) /usr/include/c++/4.9/bits/stl_iterator_base_types.h
+fn=(4366) std::_Iter_base<__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >, false>::_S_base(__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >)
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++1 495696
+
+fn=(4372) std::_Iter_base<__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >, true>::_S_base(__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >)
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++1 247848
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+* 495696
+* 247848
+
+fn=(4376) std::_Iter_base<__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >, true>::_S_base(__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >)
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++1 495696
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+* 991392
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+fl=(237)
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++1 247848
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+fn=(4212)
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++4 10842096
++3 10842096
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+-2 40657860
++9 13552620
+
+fn=(4346) IPDF::ParanoidNumber::ToDouble() const
+135 19113640
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+* 626626942
+* 13652600
+
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++3 990
++3 1485
++2 2475
+
+fn=(4344) IPDF::ParanoidNumber::operator<(IPDF::ParanoidNumber const&) const
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+
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+
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++2 7948791
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++3 5299194
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+fn=(4368) __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > > std::__copy_move_a2<false, __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >, __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > > >(__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >, __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >, __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >)
+430 660928
++4 247848
+cfn=(4370) std::_Niter_base<__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > > >::iterator_type std::__niter_base<__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > > >(__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >)
+calls=82616 278
+* 2065400
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+cfn=(4374) std::_Niter_base<__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > > >::iterator_type std::__niter_base<__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > > >(__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber* const*, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >)
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++1 413080
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+fn=(4380) IPDF::ParanoidNumber** std::__copy_move<false, true, std::random_access_iterator_tag>::__copy_m<IPDF::ParanoidNumber*>(IPDF::ParanoidNumber* const*, IPDF::ParanoidNumber* const*, IPDF::ParanoidNumber**)
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++1 8586
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++1 32451772
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+cfn=(4384) void std::_Destroy<__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > > >(__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >, __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >)
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+fn=(4386) void std::_Destroy_aux<true>::__destroy<__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > > >(__gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >, __gnu_cxx::__normal_iterator<IPDF::ParanoidNumber**, std::vector<IPDF::ParanoidNumber*, std::allocator<IPDF::ParanoidNumber*> > >)
+112 495696
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+fn=(4318) void std::_Destroy_aux<true>::__destroy<IPDF::ParanoidNumber**>(IPDF::ParanoidNumber**, IPDF::ParanoidNumber**)
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+0 9
+0 3
+
+fn=(4806)
+0 10
+cfn=(4810)
+calls=1 0
+0 4244
+0 2
+cob=(31)
+cfi=(157)
+cfn=(4334)
+calls=1 0
+0 91
+0 1
+0 7
+
+fn=(4858)
+0 10
+cfn=(4862)
+calls=1 0
+0 1532
+0 2
+cob=(31)
+cfi=(157)
+cfn=(4334)
+calls=1 0
+0 122
+0 1
+0 7
+
+fn=(2702)
+0 21
+cob=(31)
+cfi=(157)
+cfn=(2642)
+calls=3 0
+0 592
+0 3
+0 12
+cfn=(2704)
+calls=3 0
+0 36
+0 15
+
+fn=(2836)
+0 26
+cfn=(2838)
+calls=2 0
+0 374
+0 30
+cfn=(2860)
+calls=2 0
+0 9111
+0 1188
+cob=(3)
+cfi=(133)
+cfn=(984)
+calls=1 180
+0 24
+cob=(1)
+cfi=(54)
+cfn=(228)
+calls=1 34
+0 1967
+0 5
+0 16
+cfn=(3002)
+calls=2 0
+0 5120
+0 18
+cfn=(3044)
+calls=2 0
+0 82
+0 30
+cfn=(2992)
+calls=2 0
+0 40
+0 22
+cfn=(3052) 0x0000000000188ed0
+calls=2 0
+0 2848
+0 54
+cfn=(3082)
+calls=2 0
+0 112
+0 10
+cfn=(3042)
+calls=2 0
+0 94
+0 4
+
+fn=(2890)
+0 1508
+cfn=(2910)
+calls=4 0
+0 9270
+0 16
+cfn=(2990)
+calls=4 0
+0 164
+0 20
+
+fn=(2590)
+0 17
+
+fn=(2598)
+0 8
+cob=(3)
+cfi=(158)
+cfn=(2494)
+calls=1 57
+0 66
+cob=(1)
+cfi=(54)
+cfn=(228)
+calls=1 34
+0 2113
+0 5
+
+fn=(2606)
+0 4
+cob=(3)
+cfi=(158)
+cfn=(2494)
+calls=1 57
+0 66
+0 1
+
+fn=(2672)
+0 30
+cfn=(2674)
+calls=10 0
+0 2476
+0 141
+cfn=(2700)
+calls=1 0
+0 435
+
+fn=(2718)
+0 108
+
+fn=(2720)
+0 66
+cfn=(2726)
+calls=1 0
+0 2203
+0 12
+cob=(3)
+cfi=(132)
+cfn=(890)
+calls=1 25
+0 17
+cob=(1)
+cfi=(54)
+cfn=(228)
+calls=1 34
+0 2020
+0 5
+0 119
+cfn=(2746)
+calls=5 0
+0 2089
+0 17
+
+fn=(2974)
+0 2392
+
+fn=(3052)
+0 56
+cfn=(2716)
+calls=2 0
+0 80
+0 10
+cfn=(3058)
+calls=2 0
+0 2641
+0 61
+
+fn=(4712)
+0 3
+cob=(31)
+cfi=(157)
+cfn=(4334)
+calls=3 0
+0 269
+cob=(1)
+cfi=(54)
+cfn=(228)
+calls=1 34
+0 1620
+0 7
+
+fn=(4812)
+0 10
+cob=(5)
+cfi=(264)
+cfn=(4818)
+calls=2 30
+0 62
+cob=(1)
+cfi=(54)
+cfn=(228)
+calls=1 34
+0 1950
+0 6
+0 8
+cfn=(3018)
+calls=2 0
+0 6
+0 4
+cob=(5)
+cfi=(265)
+cfn=(4824)
+calls=2 29
+0 20
+cob=(1)
+cfi=(54)
+cfn=(228)
+calls=1 34
+0 1756
+0 6
+0 8
+cfn=(3018)
+calls=2 0
+0 6
+0 6
+cob=(31)
+cfi=(157)
+cfn=(4334)
+calls=2 0
+0 178
+0 2
+
+ob=(21)
+fl=(129)
+fn=(828)
+176 3
++1 3
++1 3
+
+ob=(27)
+fl=(153)
+fn=(2390)
+0 6
+
+fn=(5026)
+0 15
+cob=(3)
+cfi=(260)
+cfn=(4534)
+calls=1 31
+0 268
+cob=(1)
+cfi=(54)
+cfn=(228)
+calls=1 34
+0 2074
+0 5
+0 1
+
+fn=(2402)
+0 12
+
+ob=(32)
+fl=(159)
+fn=(4850)
+0 6
+cfn=(3110)
+calls=2 0
+0 225
+
+ob=(27)
+fl=(153)
+fn=(2396)
+0 6
+
+ob=(32)
+fl=(159)
+fn=(4912)
+0 6
+
+ob=(30)
+fl=(156)
+fn=(2448)
+0 17
+
+fn=(4958)
+0 8
+cob=(3)
+cfi=(260)
+cfn=(4534)
+calls=1 31
+0 268
+cob=(1)
+cfi=(54)
+cfn=(228)
+calls=1 34
+0 2074
+0 5
+0 1
+cfn=(4972) 0x0000000000002f10
+calls=1 0
+0 9
+0 3
+
+fn=(2442) 0x0000000000002ab0
+0 75
+
+fn=(2436)
+0 32
+cfn=(2438) 0x0000000000002bc0
+calls=1 0
+0 20
+0 13
+cfn=(2438)
+calls=1 0
+0 20
+0 34
+cfn=(2442)
+calls=1 0
+0 75
+0 10
+
+fn=(2438)
+0 40
+
+fn=(4972)
+0 9
+
+totals: 9121026185
m_screen_cpu_rendering = new QAction("&CPU Rendering", this);
m_screen_cpu_rendering->setCheckable(true);
m_screen_gpu_rendering->setToolTip("Uses the CPU for Rendering");
+
+ m_screen_lazy_rendering = new QAction("&Lazy Rendering", this);
+ m_screen_lazy_rendering->setCheckable(true);
screen->addAction(m_screen_gpu_rendering);
screen->addAction(m_screen_cpu_rendering);
+ screen->addAction(m_screen_lazy_rendering);
+ connect(m_screen_lazy_rendering, SIGNAL(triggered()), this, SLOT(ToggleLazyRendering()));
+
connect(m_screen_gpu_rendering, SIGNAL(triggered()), this, SLOT(SetGPURendering()));
connect(m_screen_cpu_rendering, SIGNAL(triggered()), this, SLOT(SetCPURendering()));
m_screen_gpu_rendering->setChecked(using_gpu_rendering);
m_screen_cpu_rendering->setChecked(!using_gpu_rendering);
m_screen_show_debug->setChecked(m_screen.DebugFontShown());
+ m_screen_lazy_rendering->setChecked(m_view.UsingLazyRendering());
m_view_show_bezier_bounds->setChecked(m_view.ShowingBezierBounds());
m_view_show_bezier_type->setChecked(m_view.ShowingBezierType());
UpdateAll();
}
+void ControlPanel::ToggleLazyRendering()
+{
+ bool state = m_view.UsingLazyRendering();
+ m_view.SetLazyRendering(!state);
+ UpdateAll();
+}
+
void ControlPanel::ToggleScreenDebugFont()
{
bool state = m_screen.DebugFontShown();
void ControlPanel::InsertSVGIntoDocument()
{
Rect bounds(m_view.GetBounds());
+ bounds.x += bounds.w/Real(2);
+ bounds.y += bounds.h/Real(2);
+
bounds.w /= Real(m_screen.ViewportWidth());
bounds.h /= Real(m_screen.ViewportHeight());
if (filename == "")
return;
+ #ifdef TRANSFORM_OBJECTS_NOT_VIEW
+ Rect bounds(0,0,1,1);
+ #else
Rect bounds(m_view.GetBounds());
+ #endif
+ bounds.x += bounds.w/Real(2);
+ bounds.y += bounds.h/Real(2);
+
bounds.w /= Real(m_screen.ViewportWidth());
bounds.h /= Real(m_screen.ViewportHeight());
private slots:
void SetGPURendering();
void SetCPURendering();
+ void ToggleLazyRendering();
void ToggleShowBezierBounds();
void ToggleShowBezierType();
void ToggleShowFillBounds();
QAction * m_screen_gpu_rendering;
QAction * m_screen_cpu_rendering;
QAction * m_screen_show_debug;
+ QAction * m_screen_lazy_rendering;
QAction * m_document_set_font;
QAction * m_document_insert_text;
QAction * m_view_show_fill_points;
QAction * m_view_enable_shading;
-
QTextEdit * m_text_edit;
QPushButton * m_ok_button;
Bezier data = bezier.ToRelative(bounds); // Relative
if (data.ToAbsolute(bounds) != bezier)
{
- Warn("%s != %s", data.ToAbsolute(Rect(0,0,1,1)).Str().c_str(),
+ Warn("%s != %s", data.ToAbsolute(bounds).Str().c_str(),
bezier.Str().c_str());
Warn("ToAbsolute on ToRelative does not give original Bezier");
}
{
string token("");
while (GetToken(d, token, i, delims) == ",");
- x = strtod(token.c_str(),NULL);
+ x = RealFromStr(token);
if (GetToken(d, token, i, delims) != ",")
{
Fatal("Expected \",\" seperating x,y pair");
}
- y = strtod(GetToken(d, token, i, delims).c_str(),NULL);
+ y = RealFromStr(GetToken(d,token,i,delims));
}
static bool GetKeyValuePair(const string & d, string & key, string & value, unsigned & i, const string & delims = "()[],{}<>;:=")
}
else if (command == "scale")
{
- delta.a = (strtod(GetToken(s,token,i).c_str(), NULL));
+ delta.a = RealFromStr(GetToken(s,token,i));
GetToken(s, token, i);
if (token == ",")
{
- delta.d = (strtod(GetToken(s,token,i).c_str(), NULL));
+ delta.d = RealFromStr(GetToken(s,token,i));
assert(GetToken(s, token, i) == ")");
}
else
c = {255,255,255,255};
else if (colour_str.size() == 7 && colour_str[0] == '#')
{
- Debug("Parse colour string: \"%s\"", colour_str.c_str());
+ //Debug("Parse colour string: \"%s\"", colour_str.c_str());
char comp[3] = {colour_str[1], colour_str[2], '\0'};
c.r = strtoul(comp, NULL, 16);
comp[0] = colour_str[3]; comp[1] = colour_str[4];
comp[0] = colour_str[5]; comp[1] = colour_str[6];
c.b = strtoul(comp, NULL, 16);
c.a = 255;
- Debug("Colour is: %u, %u, %u, %u", c.r, c.g, c.b, c.a);
+ //Debug("Colour is: %u, %u, %u, %u", c.r, c.g, c.b, c.a);
}
return c;
}
{
//Debug("Parse node <%s>", root.name());
-
+
+ // Centre the SVGs
+ if (strcmp(root.name(),"svg") == 0)
+ {
+ Real ww = RealFromStr(root.attribute("width").as_string());
+ Real hh = RealFromStr(root.attribute("height").as_string());
+ parent_transform.e -= parent_transform.a * ww/Real(2);
+ parent_transform.f -= parent_transform.d * hh/Real(2);
+ }
+
for (pugi::xml_node child = root.first_child(); child; child = child.next_sibling())
{
SVGMatrix transform(parent_transform);
//Debug("Path data attribute is \"%s\"", d.c_str());
bool closed = false;
pair<unsigned, unsigned> range = ParseSVGPathData(d, transform, closed);
- if (true)//(closed)
+ if (true && range.first < m_count && range.second < m_count)//(closed)
{
string colour_str("");
input.close();
// a c e, b d f
- SVGMatrix transform = {bounds.w, 0,bounds.x, 0,bounds.h,bounds.y};
+ SVGMatrix transform = {bounds.w,0 ,bounds.x, 0,bounds.h,bounds.y};
ParseSVGNode(doc_xml, transform);
}
if (command == "m" || command == "M")
{
//Debug("Construct moveto command");
- Real dx = Real(strtod(GetToken(d,token,i,delims).c_str(),NULL));
+ Real dx = RealFromStr(GetToken(d,token,i,delims));
assert(GetToken(d,token,i,delims) == ",");
- Real dy = Real(strtod(GetToken(d,token,i,delims).c_str(),NULL));
+ Real dy = RealFromStr(GetToken(d,token,i,delims));
x[0] = (relative) ? x[0] + dx : dx;
y[0] = (relative) ? y[0] + dy : dy;
else if (command == "c" || command == "C" || command == "q" || command == "Q")
{
//Debug("Construct curveto command");
- Real dx = Real(strtod(GetToken(d,token,i,delims).c_str(),NULL));
+ Real dx = RealFromStr(GetToken(d,token,i,delims));
assert(GetToken(d,token,i,delims) == ",");
- Real dy = Real(strtod(GetToken(d,token,i,delims).c_str(),NULL));
+ Real dy = RealFromStr(GetToken(d,token,i,delims));
x[1] = (relative) ? x[0] + dx : dx;
y[1] = (relative) ? y[0] + dy : dy;
- dx = Real(strtod(GetToken(d,token,i,delims).c_str(),NULL));
+ dx = RealFromStr(GetToken(d,token,i,delims));
assert(GetToken(d,token,i,delims) == ",");
- dy = Real(strtod(GetToken(d,token,i,delims).c_str(),NULL));
+ dy = RealFromStr(GetToken(d,token,i,delims));
x[2] = (relative) ? x[0] + dx : dx;
y[2] = (relative) ? y[0] + dy : dy;
if (command != "q" && command != "Q")
{
- dx = Real(strtod(GetToken(d,token,i,delims).c_str(),NULL));
+ dx = RealFromStr(GetToken(d,token,i,delims));
assert(GetToken(d,token,i,delims) == ",");
- dy = Real(strtod(GetToken(d,token,i,delims).c_str(),NULL));
+ dy = RealFromStr(GetToken(d,token,i,delims));
x[3] = (relative) ? x[0] + dx : dx;
y[3] = (relative) ? y[0] + dy : dy;
}
{
//Debug("Construct lineto command, relative %d", relative);
- Real dx = Real(strtod(GetToken(d,token,i,delims).c_str(),NULL));
- Real dy;
+ Real dx = RealFromStr(GetToken(d,token,i,delims));
+ Real dy = 0;
if (command == "l" || command == "L")
{
assert(GetToken(d,token,i,delims) == ",");
- dy = Real(strtod(GetToken(d,token,i,delims).c_str(),NULL));
+ dy = RealFromStr(GetToken(d,token,i,delims));
}
else if (command == "v" || command == "V")
{
stbtt_FreeShape(font, instructions);
}
+
+void Document::TransformObjectBounds(const SVGMatrix & transform)
+{
+ for (unsigned i = 0; i < m_count; ++i)
+ {
+ TransformXYPair(m_objects.bounds[i].x, m_objects.bounds[i].y, transform);
+ m_objects.bounds[i].w *= transform.a;
+ m_objects.bounds[i].h *= transform.d;
+ }
+}
+
+void Document::TranslateObjects(const Real & dx, const Real & dy)
+{
+ for (unsigned i = 0; i < m_count; ++i)
+ {
+ m_objects.bounds[i].x += dx;
+ m_objects.bounds[i].y += dy;
+ }
+}
+
+void Document::ScaleObjectsAboutPoint(const Real & x, const Real & y, const Real & scale_amount)
+{
+ for (unsigned i = 0; i < m_count; ++i)
+ {
+ m_objects.bounds[i].w /= scale_amount;
+ m_objects.bounds[i].h /= scale_amount;
+ //m_objects.bounds[i].x = x + (m_objects.bounds[i].x-x)/scale_amount;
+ //m_objects.bounds[i].y = y + (m_objects.bounds[i].y-x)/scale_amount;
+ m_objects.bounds[i].x -= x;
+ m_objects.bounds[i].x /= scale_amount;
+ m_objects.bounds[i].x += x;
+
+ m_objects.bounds[i].y -= y;
+ m_objects.bounds[i].y /= scale_amount;
+ m_objects.bounds[i].y += y;
+
+ }
+
+}
void AddText(const std::string & text, Real scale, Real x, Real y);
void AddFontGlyphAtPoint(stbtt_fontinfo *font, int character, Real scale, Real x, Real y);
-
+
+ void TransformObjectBounds(const SVGMatrix & transform);
+ void TranslateObjects(const Real & x, const Real & y);
+ void ScaleObjectsAboutPoint(const Real & x, const Real & y, const Real & scale_amount);
+
#ifndef QUADTREE_DISABLED
inline const QuadTree& GetQuadTree() { if (m_quadtree.root_id == QUADTREE_EMPTY) { GenBaseQuadtree(); } return m_quadtree; }
QuadTreeIndex GenQuadChild(QuadTreeIndex parent, QuadTreeNodeChildren type);
--- /dev/null
+/**
+ * @file gmpint.h
+ * @brief Wraps to GMP mpq_t type using inlines
+ */
+
+#ifndef _GMPRAT_H
+#define _GMPRAT_H
+
+#include <gmp.h>
+#include <string>
+
+class Gmprat
+{
+ public:
+ Gmprat(double d=0) {mpq_init(m_op); mpq_set_d(m_op, d);}
+ //Gmprat(int64_t p = 0, int64_t q = 1) {mpq_init(m_op); mpq_set_si(m_op, p, q);}
+ //Gmprat(const std::string & str, int base=10) {mpq_init_set_str(m_op, str.c_str(), base);}
+ Gmprat(const Gmprat & cpy) {mpq_init(m_op); mpq_set(m_op, cpy.m_op);}
+ virtual ~Gmprat() {mpq_clear(m_op);}
+
+ //operator int64_t() const {return mpq_get_si(m_op);}
+ //operator uint64_t() const {return mpq_get_ui(m_op);}
+ //operator double() const {return mpq_get_d(m_op);}
+ double ToDouble() const {return mpq_get_d(m_op);}
+ std::string Str(int base = 10) const
+ {
+ //TODO: Make less hacky, if we care.
+ char * buff = mpq_get_str(NULL, 10, m_op);
+ std::string result(buff);
+ free(buff);
+ return result;
+ }
+
+ Gmprat & operator=(const Gmprat & equ) {mpq_set(m_op, equ.m_op); return *this;}
+ Gmprat & operator+=(const Gmprat & add) {mpq_add(m_op, m_op, add.m_op); return *this;}
+ Gmprat & operator-=(const Gmprat & sub) {mpq_sub(m_op, m_op, sub.m_op); return *this;}
+ Gmprat & operator*=(const Gmprat & mul) {mpq_mul(m_op, m_op, mul.m_op); return *this;}
+ Gmprat & operator/=(const Gmprat & div) {mpq_div(m_op, m_op, div.m_op); return *this;}
+
+ Gmprat operator+(const Gmprat & add) const {Gmprat a(*this); a += add; return a;}
+ Gmprat operator-(const Gmprat & sub) const {Gmprat a(*this); a -= sub; return a;}
+ Gmprat operator*(const Gmprat & mul) const {Gmprat a(*this); a *= mul; return a;}
+ Gmprat operator/(const Gmprat & div) const {Gmprat a(*this); a /= div; return a;}
+ //Gmprat operator%(const Gmprat & div) const {Gmprat a(*this); mpq_mod(a.m_op, a.m_op, div.m_op); return a;}
+ Gmprat operator-() const {return (Gmprat(0L)-*this);}
+
+
+ bool operator==(const Gmprat & cmp) const {return mpq_cmp(m_op, cmp.m_op) == 0;}
+ bool operator!=(const Gmprat & cmp) const {return mpq_cmp(m_op, cmp.m_op) != 0;}
+ bool operator<(const Gmprat & cmp) const {return mpq_cmp(m_op, cmp.m_op) < 0;}
+ bool operator>(const Gmprat & cmp) const {return mpq_cmp(m_op, cmp.m_op) > 0;}
+ bool operator<=(const Gmprat & cmp) const {return mpq_cmp(m_op, cmp.m_op) <= 0;}
+ bool operator>=(const Gmprat & cmp) const {return mpq_cmp(m_op, cmp.m_op) >= 0;}
+
+ Gmprat Abs() const {Gmprat a(*this); mpq_abs(a.m_op, a.m_op); return a;}
+
+
+ private:
+ mpq_t m_op;
+};
+
+
+
+
+#endif //_GMPRAT_H
+
inline Real Random(Real max=1, Real min=0)
{
- return min + (max-min) * (Real(rand() % (int)1e6) / Real(1e6));
+ return min + (max-min) * (Real(rand() % (int)100) / Real(100));
}
typedef unsigned ObjectID;
#define _GNU_SOURCE
#endif
#include <fenv.h>
+#include <signal.h>
+bool ignore_sigfpe = false;
+
+void sigfpe_handler(int sig)
+{
+ if (!ignore_sigfpe)
+ Fatal("Floating point exception!");
+ exit(EXIT_SUCCESS);
+}
int main(int argc, char ** argv)
{
+ signal(SIGFPE, sigfpe_handler);
#if REALTYPE == REAL_IRRAM
iRRAM_initialize(argc,argv);
#endif
// We want to crash if we ever get a NaN.
feenableexcept(FE_DIVBYZERO | FE_INVALID | FE_OVERFLOW);
- Debug("Compiled with REAL = %d => \"%s\" sizeof(Real) == %d bytes", REALTYPE, g_real_name[REALTYPE], sizeof(Real));
+ DebugRealInfo();
Document doc("","fonts/ComicSans.ttf");
srand(time(NULL));
Colour c(0,0,0,1);
- const char * input_bmp = NULL;
+
const char * output_bmp = NULL;
const char * input_filename = NULL;
+ const char * input_text = NULL;
float b[4] = {0,0,1,1};
+ int max_frames = -1;
+ bool hide_control_panel = false;
+ bool lazy_rendering = true;
+ bool window_visible = true;
+ bool gpu_transform = true;
+ bool gpu_rendering = true;
+
+
int i = 0;
while (++i < argc)
{
{
case 'o':
mode = OUTPUT_TO_BMP;
- if (++i >= argc)
- Fatal("No input argument following -o switch");
- input_bmp = argv[i];
if (++i >= argc)
Fatal("No output argument following -o switch");
output_bmp = argv[i];
-
+ hide_control_panel = true;
break;
case 'b':
{
i += 4;
break;
}
+ case 't':
+ {
+ if (++i >= argc)
+ Fatal("No text input following -t switch");
+ input_text = argv[i];
+ Debug("Insert text: %s", input_text);
+ break;
+ }
+
+ case 'r':
+ {
+ if (++i >= argc)
+ Fatal("Expected \"gpu\" or \"cpu\" after -r switch");
+ if (strcmp(argv[i], "gpu") == 0)
+ {
+ gpu_rendering = true;
+ }
+ else if (strcmp(argv[i], "cpu") == 0)
+ {
+ gpu_rendering = false;
+ }
+ else
+ {
+ Fatal("Expected \"gpu\" or \"cpu\" after -r switch, not \"%s\"", argv[i]);
+ }
+ break;
+ }
+
+ case 'T':
+ {
+ if (++i >= argc)
+ Fatal("Expected \"gpu\" or \"cpu\" after -T switch");
+ if (strcmp(argv[i], "gpu") == 0)
+ {
+ gpu_transform = true;
+ }
+ else if (strcmp(argv[i], "cpu") == 0)
+ {
+ gpu_transform = false;
+ }
+ else
+ {
+ Fatal("Expected \"gpu\" or \"cpu\" after -T switch, not \"%s\"", argv[i]);
+ }
+ break;
+ }
+
+
+ case 'l':
+ lazy_rendering = !lazy_rendering;
+ break;
+
+ case 'f':
+ if (++i >= argc)
+ Fatal("No frame number following -f switch");
+ max_frames = strtol(argv[i], NULL, 10);
+ hide_control_panel = true;
+ break;
+
+ case 'q':
+ hide_control_panel = true;
+ break;
+
+ case 'Q':
+ hide_control_panel = true;
+ window_visible = !window_visible;
+ break;
}
}
+ Rect bounds(b[0],b[1],b[2],b[3]);
+ Screen scr(window_visible);
+ View view(doc,scr, bounds);
+
+ view.SetLazyRendering(lazy_rendering);
+ view.SetGPURendering(gpu_rendering);
+ view.SetGPUTransform(gpu_transform);
+
if (input_filename != NULL)
{
- doc.LoadSVG(input_filename, Rect(0,0,Real(1)/Real(800),Real(1)/Real(600)));
+ #ifdef TRANSFORM_OBJECTS_NOT_VIEW
+ doc.LoadSVG(input_filename, Rect(Real(1)/Real(2),Real(1)/Real(2),Real(1)/Real(800),Real(1)/Real(600)));
+ #else
+ doc.LoadSVG(input_filename, Rect(bounds.x+bounds.w/Real(2),bounds.y+bounds.h/Real(2),bounds.w/Real(800),bounds.h/Real(600)));
+ #endif
}
- else
+ else if (input_text != NULL)
+ {
+ doc.AddText(input_text, bounds.h/Real(2), bounds.x, bounds.y+bounds.h/Real(2));
+ }
+ else
{
doc.Add(RECT_OUTLINE, Rect(0,0,0,0),0); // hack to stop segfault if document is empty (:S)
}
- Debug("Start!");
- Rect bounds(b[0],b[1],b[2],b[3]);
-
- Screen scr;
- View view(doc,scr, bounds);
+
#ifndef CONTROLPANEL_DISABLED
+ if (!scr.Valid()) hide_control_panel = true;
+ SDL_Thread * cp_thread = NULL;
+ if (!hide_control_panel)
+ {
ControlPanel::RunArgs args = {argc, argv, view, doc, scr};
- SDL_Thread * cp_thread = SDL_CreateThread(ControlPanel::Run, "ControlPanel", &args);
+ cp_thread = SDL_CreateThread(ControlPanel::Run, "ControlPanel", &args);
if (cp_thread == NULL)
{
Error("Couldn't create ControlPanel thread: %s", SDL_GetError());
}
- #endif //CONTROLPANEL_DISABLED
+ }
+ #else //CONTROLPANEL_DISABLED
+ Debug("No control panel, hide_control_panel is %d", hide_control_panel);
+ #endif
if (mode == LOOP)
- MainLoop(doc, scr, view);
- else if (mode == OUTPUT_TO_BMP) //TODO: Remove this shit
- OverlayBMP(doc, input_bmp, output_bmp, bounds, c);
+ MainLoop(doc, scr, view, max_frames);
+ else if (mode == OUTPUT_TO_BMP)
+ {
+ view.SaveBMP(output_bmp);
+ }
#ifndef CONTROLPANEL_DISABLED
-
if (cp_thread != NULL)
{
int cp_return;
Debug("ControlPanel thread returned %d", cp_return);
}
#endif //CONTROLPANEL_DISABLED
+
+ ignore_sigfpe = true;
return 0;
}
}
if (buttons)
{
- #if REALTYPE == REAL_RATIONAL
- view->Translate(Real(oldx, scr->ViewportWidth()) -Real(x,scr->ViewportWidth()), Real(oldy, scr->ViewportHeight()) - Real(y,scr->ViewportHeight()));
- #else
- view->Translate(Real(oldx-x)/Real(scr->ViewportWidth()), Real(oldy-y)/Real(scr->ViewportHeight()));
- #endif
+ view->Translate(Real(oldx-x)/Real(scr->ViewportWidth()), Real(oldy-y)/Real(scr->ViewportHeight()));
}
else
{
if (wheel)
{
- #if REALTYPE == REAL_RATIONAL
- view->ScaleAroundPoint(Real(x,scr->ViewportWidth()), Real(y,scr->ViewportHeight()), Real(20-wheel, 20));
- #else
- view->ScaleAroundPoint(Real(x)/Real(scr->ViewportWidth()),Real(y)/Real(scr->ViewportHeight()), Real(expf(-wheel/20.f)));
- #endif
-
+ view->ScaleAroundPoint(Real(x)/Real(scr->ViewportWidth()),Real(y)/Real(scr->ViewportHeight()), Real(expf(-wheel/20.f)));
}
}
-inline void MainLoop(Document & doc, Screen & scr, View & view)
+inline void MainLoop(Document & doc, Screen & scr, View & view, int max_frames = -1)
{
// order is important... segfaults occur when screen (which inits GL) is not constructed first -_-
double data_rate = 0; // period between data output to stdout (if <= 0 there will be no output)
uint64_t data_points = 0;
setbuf(stdout, NULL);
- while (scr.PumpEvents())
+ int frame_number = 0;
+ while (scr.PumpEvents() && (max_frames < 0 || frame_number++ < max_frames))
{
real_clock_prev = real_clock_now;
++frames;
data_points++;
}
scr.DebugFontPrintF("Rendered frame %lu\n", (uint64_t)frames);
- scr.DebugFontPrintF("[CPU] Render took %lf ms (%lf FPS) (total %lf s, avg FPS %lf)\n", cpu_frame*1e3, 1.0/cpu_frame, total_cpu_time,frames/total_cpu_time);
- scr.DebugFontPrintF("[GPU] Render took %lf ms (%lf FPS) (total %lf s, avg FPS %lf)\n", gpu_frame*1e3, 1.0/gpu_frame, total_gpu_time, frames/total_gpu_time);
- scr.DebugFontPrintF("[REALTIME] Render+Present+Cruft took %lf ms (%lf FPS) (total %lf s, avg FPS %lf)\n", real_frame*1e3, 1.0/real_frame, total_real_time,frames/total_real_time);
+ scr.DebugFontPrintF("Lazy Rendering = %d\n", view.UsingLazyRendering());
+ if (cpu_frame > 0 && total_cpu_time > 0)
+ scr.DebugFontPrintF("[CPU] Render took %lf ms (%lf FPS) (total %lf s, avg FPS %lf)\n", cpu_frame*1e3, 1.0/cpu_frame, total_cpu_time,frames/total_cpu_time);
+ if (gpu_frame > 0 && total_gpu_time > 0)
+ scr.DebugFontPrintF("[GPU] Render took %lf ms (%lf FPS) (total %lf s, avg FPS %lf)\n", gpu_frame*1e3, 1.0/gpu_frame, total_gpu_time, frames/total_gpu_time);
+ if (real_frame > 0 && total_real_time > 0)
+ scr.DebugFontPrintF("[REALTIME] Render+Present+Cruft took %lf ms (%lf FPS) (total %lf s, avg FPS %lf)\n", real_frame*1e3, 1.0/real_frame, total_real_time,frames/total_real_time);
+
scr.DebugFontPrintF("View bounds: %s\n", view.GetBounds().Str().c_str());
scr.DebugFontPrintF("type of Real == %s\n", g_real_name[REALTYPE]);
- #if REALTYPE == REAL_MPFRCPP
- scr.DebugFontPrintf("Precision: %s\nRounding: %s\n");
- #endif
+ //#if REALTYPE == REAL_MPFRCPP
+ // scr.DebugFontPrintf("Precision: %s\nRounding: %s\n");
+ //#endif
+ #ifdef TRANSFORM_OBJECTS_NOT_VIEW
+ scr.DebugFontPrint("Doing cumulative coordinate transforms on Objects.\n");
+ #else
if (view.UsingGPUTransform())
{
scr.DebugFontPrint("Doing coordinate transform on the GPU.\n");
{
scr.DebugFontPrint("Doing coordinate transform on the CPU.\n");
}
+ #endif
if (view.UsingGPURendering())
{
scr.DebugFontPrint("Doing rendering using GPU.\n");
const char * vert_glsl_file, const char * frag_glsl_file, const char * geom_glsl_file)
: m_type(type), m_shader_program(), m_indexes(), m_buffer_builder(NULL)
{
- m_shader_program.InitialiseShaders(vert_glsl_file, frag_glsl_file, geom_glsl_file);
- m_shader_program.Use();
- glUniform4f(m_shader_program.GetUniformLocation("colour"), 0,0,0,1); //TODO: Allow different colours
+ if (vert_glsl_file != NULL && frag_glsl_file != NULL && geom_glsl_file != NULL)
+ {
+ m_shader_program.InitialiseShaders(vert_glsl_file, frag_glsl_file, geom_glsl_file);
+ m_shader_program.Use();
+ glUniform4f(m_shader_program.GetUniformLocation("colour"), 0,0,0,1); //TODO: Allow different colours
+ }
}
/**
ObjectRenderer::RenderLineOnCPU(pix_bounds.x+pix_bounds.w, pix_bounds.y, pix_bounds.x+pix_bounds.w, pix_bounds.y+pix_bounds.h, target, Colour(0,255,0,0));
}
- unsigned blen = min(max(2U, (unsigned)Int64(Real(target.w)/view.GetBounds().w)),
- min((unsigned)(pix_bounds.w+pix_bounds.h)/4 + 1, 100U));
+ unsigned blen = target.w;//min(max(2U, (unsigned)Int64(Real(target.w)/view.GetBounds().w)),
+ //min((unsigned)(pix_bounds.w+pix_bounds.h)/4 + 1, 100U));
// DeCasteljau Divide the Bezier
queue<Bezier> divisions;
{
public:
/** Construct the ObjectRenderer **/
- ObjectRenderer(const ObjectType & type, const char * vert_glsl_file, const char * frag_glsl_file, const char * geom_glsl_file = "");
+ ObjectRenderer(const ObjectType & type, const char * vert_glsl_file="", const char * frag_glsl_file="", const char * geom_glsl_file = "");
virtual ~ObjectRenderer() {}
/**
// do nothing on GPU
virtual void RenderUsingGPU(unsigned first_obj_id, unsigned last_obj_id) {}
};
+
+ class FakeRenderer : public ObjectRenderer
+ {
+ public:
+ FakeRenderer() : ObjectRenderer(PATH,NULL,NULL,NULL) {}
+ ~FakeRenderer() {}
+ virtual void RenderUsingCPU(Objects & objects, const View & view, const CPURenderTarget & target, unsigned first_obj_id, unsigned last_obj_id) {}
+ virtual void RenderUsingGPU(unsigned first_obj_id, unsigned last_obj_id) {}
+ };
}
#include <sstream>
#include <fenv.h>
#include "log.h"
+#include <cassert>
#include <iostream>
+// here be many copy paste bugs
+
using namespace std;
namespace IPDF
{
-int64_t ParanoidNumber::g_count = 0;
-ParanoidNumber::ParanoidNumber(const char * str) : m_value(0), m_op(ADD), m_next_term(NULL), m_next_factor(NULL)
+
+#ifdef PARANOID_USE_ARENA
+ParanoidNumber::Arena ParanoidNumber::g_arena;
+#endif //PARANOID_USE_ARENA
+
+ParanoidNumber::~ParanoidNumber()
+{
+ for (int i = 0; i < NOP; ++i)
+ {
+ for (auto n : m_next[i])
+ delete n;
+ }
+}
+
+ParanoidNumber::ParanoidNumber(const string & str) : m_value(0), m_next()
{
+ #ifdef PARANOID_SIZE_LIMIT
+ m_size = 0;
+ #endif
+ #ifdef PARANOID_CACHE_RESULTS
+ m_cached_result = NAN;
+ #endif
+
int dp = 0;
int end = 0;
+ bool negate = str[0] == '-';
+ if (negate)
+ {
+ dp++;
+ end++;
+ }
while (str[dp] != '\0' && str[dp] != '.')
{
++dp;
}
while (str[end] != '\0')
++end;
-
ParanoidNumber m(1);
- for (int i = dp-1; i >= 0; --i)
+ for (int i = dp-1; i >= negate; --i)
{
ParanoidNumber b(str[i]-'0');
b*=m;
- //Debug("m is %s", m.Str().c_str());
- //Debug("Add %s", b.Str().c_str());
this->operator+=(b);
- //Debug("Now at %s", Str().c_str());
m*=10;
}
ParanoidNumber n(1);
{
n/=10;
ParanoidNumber b(str[i]-'0');
- //Debug("%s * %s", b.Str().c_str(), n.Str().c_str());
b*=n;
- //Debug("b -> %s", b.Str().c_str());
- //Debug("Add %s", b.Str().c_str());
this->operator+=(b);
- //Debug("Now at %s", Str().c_str());
-
}
- //Debug("Constructed {%s} from %s (%f)", Str().c_str(), str, ToDouble());
+
+ if (negate)
+ Negate();
+
+ #ifdef PARANOID_COMPARE_EPSILON
+ double d = strtod(str.c_str(), NULL);
+ CompareForSanity(d, d);
+ #endif
}
ParanoidNumber & ParanoidNumber::operator=(const ParanoidNumber & a)
{
- //TODO: Optimise
- delete m_next_term;
- delete m_next_factor;
- m_op = a.m_op;
- if (a.m_next_term != NULL)
- {
- m_next_term = new ParanoidNumber(*(a.m_next_term));
- }
- if (a.m_next_factor != NULL)
+ //assert(this != NULL);
+
+ #ifdef PARANOID_SIZE_LIMIT
+ m_size = a.m_size;
+ #endif
+
+ m_value = a.m_value;
+ #ifdef PARANOID_CACHE_RESULT
+ m_cached_result = a.m_cached_result;
+ #endif
+ for (int i = 0; i < NOP; ++i)
{
- m_next_factor = new ParanoidNumber(*(a.m_next_factor));
+ for (auto n : m_next[i])
+ delete n;
+ m_next[i].clear();
+ for (auto n : a.m_next[i])
+ m_next[i].push_back(new ParanoidNumber(*n));
}
+ #ifdef PARANOID_COMPARE_EPSILON
+ CompareForSanity(a.Digit(),a.Digit());
+ #endif
return *this;
}
-ParanoidNumber & ParanoidNumber::operator+=(const ParanoidNumber & a)
+
+string ParanoidNumber::Str() const
{
- if (m_next_factor == NULL && a.Floating())
+
+ //assert(this != NULL);
+ string result("");
+ stringstream s;
+ s << (double)m_value;
+ result += s.str();
+ for (auto mul : m_next[MULTIPLY])
{
- if (ParanoidOp<digit_t>(m_value, a.m_value, ADD))
- {
- Simplify();
- return *this;
- }
+ result += "*";
+ if (!mul->Floating())
+ result += "(" + mul->Str() + ")";
+ else
+ result += mul->Str();
}
- ParanoidNumber * nt = m_next_term;
- ParanoidNumber * nf = m_next_factor;
+ for (auto div : m_next[DIVIDE])
+ {
+ result += "/";
+ if (!div->Floating())
+ result += "(" + div->Str() + ")";
+ else
+ result += div->Str();
+ }
- ParanoidNumber ca(a);
- if (m_next_factor != NULL)
+ for (auto add : m_next[ADD])
{
- if (m_next_factor->m_op == MULTIPLY)
- ca /= (*m_next_factor);
+ result += "+";
+ if (!add->Floating())
+ result += "(" + add->Str() + ")";
else
- ca *= (*m_next_factor);
-
- if (ca.Floating())
- {
- m_next_factor = NULL;
- m_next_term = NULL;
- operator+=(ca);
- m_next_factor = nf;
- m_next_term = nt;
- Simplify();
- return *this;
- }
-
+ result += add->Str();
+ }
+ for (auto sub : m_next[SUBTRACT])
+ {
+ result += "-";
+ if (!sub->Floating())
+ result += "(" + sub->Str() + ")";
+ else
+ result += sub->Str();
}
- m_next_term = new ParanoidNumber(a, ADD);
- ParanoidNumber * t = m_next_term;
- while (t->m_next_term != NULL)
- t = t->m_next_term;
- t->m_next_term = nt;
- //Debug("Simplify {%s} after add", Str().c_str());
- Simplify();
- return *this;
+
+ return result;
}
-ParanoidNumber & ParanoidNumber::operator-=(const ParanoidNumber & a)
+template <>
+bool TrustingOp<float>(float & a, const float & b, Optype op)
{
- // this = v + t + (a)
- // -> v + (a) + t
- if (m_next_factor == NULL && a.Floating())
+
+
+ feclearexcept(FE_ALL_EXCEPT);
+ switch (op)
{
- if (ParanoidOp<digit_t>(m_value, a.m_value, ADD))
- {
- Simplify();
- return *this;
- }
+ case ADD:
+ a += b;
+ break;
+ case SUBTRACT:
+ a -= b;
+ break;
+ case MULTIPLY:
+ a *= b;
+ break;
+ case DIVIDE:
+ if (b == 0)
+ {
+ a = (a >= 0) ? INFINITY : -INFINITY;
+ return false;
+ }
+
+ a /= b;
+ break;
+ case NOP:
+ break;
}
+ return !fetestexcept(FE_ALL_EXCEPT);
+}
+
+template <>
+bool TrustingOp<double>(double & a, const double & b, Optype op)
+{
+ feclearexcept(FE_ALL_EXCEPT);
+ switch (op)
+ {
+ case ADD:
+ a += b;
+ break;
+ case SUBTRACT:
+ a -= b;
+ break;
+ case MULTIPLY:
+ a *= b;
+ break;
+ case DIVIDE:
+ if (b == 0)
+ {
+ a = (a >= 0) ? INFINITY : -INFINITY;
+ return false;
+ }
+ a /= b;
+ break;
+ case NOP:
+ break;
+ }
+ return !fetestexcept(FE_ALL_EXCEPT);
+}
+
+
+
+template <>
+bool TrustingOp<long double>(long double & a, const long double & b, Optype op)
+{
- ParanoidNumber * nt = m_next_term;
- ParanoidNumber * nf = m_next_factor;
- ParanoidNumber ca(a, SUBTRACT);
- if (m_next_factor != NULL)
+ feclearexcept(FE_ALL_EXCEPT);
+ switch (op)
{
- if (m_next_factor->m_op == MULTIPLY)
- ca /= (*m_next_factor);
- else
- ca *= (*m_next_factor);
+ case ADD:
+ a += b;
+ break;
+ case SUBTRACT:
+ a -= b;
+ break;
+ case MULTIPLY:
+ a *= b;
+ break;
+ case DIVIDE:
+ if (b == 0)
+ {
+ a = (a >= 0) ? INFINITY : -INFINITY;
+ return false;
+ }
- if (ca.Floating())
- {
- m_next_factor = NULL;
- m_next_term = NULL;
- operator-=(ca);
- m_next_factor = nf;
- m_next_term = nt;
- Simplify();
- return *this;
- }
-
+ a /= b;
+ break;
+ case NOP:
+ break;
}
-
- m_next_term = new ParanoidNumber(a,SUBTRACT);
- ParanoidNumber * t = m_next_term;
- while (t->m_next_term != NULL)
+ return !fetestexcept(FE_ALL_EXCEPT);
+}
+
+
+template <>
+bool TrustingOp<int8_t>(int8_t & a, const int8_t & b, Optype op)
+{
+ int16_t sa(a);
+ bool exact = true;
+ switch (op)
{
- t->m_op = SUBTRACT;
- t = t->m_next_term;
+ case ADD:
+ sa += b;
+ exact = (abs(sa) <= 127);
+ break;
+ case SUBTRACT:
+ sa -= b;
+ exact = (abs(sa) <= 127);
+ break;
+ case MULTIPLY:
+ sa *= b;
+ exact = (abs(sa) <= 127);
+ break;
+ case DIVIDE:
+ exact = (b != 0 && sa > b && sa % b == 0);
+ sa /= b;
+ break;
+ case NOP:
+ break;
}
- t->m_op = SUBTRACT;
- //Debug("next term {%s}", m_next_term->Str().c_str());
- t->m_next_term = nt;
- //Debug("Simplify {%s} after sub", Str().c_str());
- Simplify();
+ a = (int8_t)(sa);
+ return exact;
+}
+
+
+ParanoidNumber & ParanoidNumber::operator+=(const digit_t & a)
+{
+ #ifdef PARANOID_COMPARE_EPSILON
+ digit_t compare = Digit();
+ compare += a;
+ #endif
+ delete Operation(new ParanoidNumber(a), ADD);
+ Simplify(SUBTRACT);
+ Simplify(ADD);
+ #ifdef PARANOID_COMPARE_EPSILON
+ CompareForSanity(compare, a);
+ #endif
return *this;
}
-ParanoidNumber & ParanoidNumber::operator*=(const ParanoidNumber & a)
+
+ParanoidNumber & ParanoidNumber::operator-=(const digit_t & a)
{
+ #ifdef PARANOID_COMPARE_EPSILON
+ digit_t compare = Digit();
+ compare -= a;
+ #endif
+ delete Operation(new ParanoidNumber(a), SUBTRACT);
+ Simplify(ADD);
+ Simplify(SUBTRACT);
+ #ifdef PARANOID_COMPARE_EPSILON
+ CompareForSanity(compare, a);
+ #endif
+ return *this;
+}
- //if (m_value == 0)
- // return *this;
- //Debug("{%s} *= {%s}", Str().c_str(), a.Str().c_str());
- // this = (vf + t) * (a)
- if (a.Floating() && ParanoidOp<digit_t>(m_value, a.m_value, MULTIPLY))
- {
- if (m_next_term != NULL)
- m_next_term->operator*=(a);
- Simplify();
- return *this;
- }
-
- ParanoidNumber * t = this;
- while (t->m_next_factor != NULL)
- t = t->m_next_factor;
- t->m_next_factor = new ParanoidNumber(a, MULTIPLY);
+ParanoidNumber & ParanoidNumber::operator*=(const digit_t & a)
+{
+ #ifdef PARANOID_COMPARE_EPSILON
+ digit_t compare = Digit();
+ compare *= a;
+ #endif
+ delete Operation(new ParanoidNumber(a), MULTIPLY);
+ Simplify(DIVIDE);
+ Simplify(MULTIPLY);
+ #ifdef PARANOID_COMPARE_EPSILON
+ CompareForSanity(compare, a);
+ #endif
+ return *this;
+}
- if (m_next_term != NULL)
- m_next_term->operator*=(a);
- //Debug("Simplify {%s}", Str().c_str());
- Simplify();
- //Debug("Simplified to {%s}", Str().c_str());
+ParanoidNumber & ParanoidNumber::operator/=(const digit_t & a)
+{
+ #ifdef PARANOID_COMPARE_EPSILON
+ digit_t compare = Digit();
+ compare /= a;
+ #endif
+ delete Operation(new ParanoidNumber(a), DIVIDE);
+ Simplify(MULTIPLY);
+ Simplify(DIVIDE);
+ #ifdef PARANOID_COMPARE_EPSILON
+ CompareForSanity(compare, a);
+ #endif
+ return *this;
+}
+
+
+ParanoidNumber & ParanoidNumber::operator+=(const ParanoidNumber & a)
+{
+ #ifdef PARANOID_COMPARE_EPSILON
+ digit_t compare = Digit();
+ compare += a.Digit();
+ #endif
+ delete Operation(new ParanoidNumber(a), ADD);
+ Simplify(SUBTRACT);
+ Simplify(ADD);
+ #ifdef PARANOID_COMPARE_EPSILON
+ CompareForSanity(compare, a.Digit());
+ #endif
+ return *this;
+}
+
+
+ParanoidNumber & ParanoidNumber::operator-=(const ParanoidNumber & a)
+{
+ #ifdef PARANOID_COMPARE_EPSILON
+ digit_t compare = Digit();
+ compare -= a.Digit();
+ #endif
+ delete Operation(new ParanoidNumber(a), SUBTRACT);
+ Simplify(ADD);
+ Simplify(SUBTRACT);
+ #ifdef PARANOID_COMPARE_EPSILON
+ CompareForSanity(compare, a.Digit());
+ #endif
+ return *this;
+}
+
+ParanoidNumber & ParanoidNumber::operator*=(const ParanoidNumber & a)
+{
+ #ifdef PARANOID_COMPARE_EPSILON
+ digit_t compare = Digit();
+ compare *= a.Digit();
+ #endif
+ delete Operation(new ParanoidNumber(a), MULTIPLY);
+ Simplify(DIVIDE);
+ Simplify(MULTIPLY);
+ #ifdef PARANOID_COMPARE_EPSILON
+ CompareForSanity(compare, a.Digit());
+ #endif
return *this;
}
ParanoidNumber & ParanoidNumber::operator/=(const ParanoidNumber & a)
{
+ #ifdef PARANOID_COMPARE_EPSILON
+ digit_t compare = Digit();
+ compare /= a.Digit();
+ #endif
+ delete Operation(new ParanoidNumber(a), DIVIDE);
+ Simplify(MULTIPLY);
+ Simplify(DIVIDE);
+ #ifdef PARANOID_COMPARE_EPSILON
+ CompareForSanity(compare, a.Digit());
+ #endif
+ return *this;
+}
+
+ParanoidNumber & ParanoidNumber::operator=(const digit_t & a)
+{
+
+ for (int i = 0; i < NOP; ++i)
+ {
+ for (auto n : m_next[i])
+ delete n;
+ m_next[i].clear();
+ }
+ m_value = a;
+ #ifdef PARANOID_CACHE_RESULT
+ m_cached_result = a;
+ #endif
+
+ #ifdef PARANOID_COMPARE_EPSILON
+ CompareForSanity(a,a);
+ #endif
+
+ return *this;
+}
+
+// a + b
+ParanoidNumber * ParanoidNumber::OperationTerm(ParanoidNumber * b, Optype op, ParanoidNumber ** merge_point, Optype * merge_op)
+{
+ ////assert(b->SanityCheck());
+ #ifdef PARANOID_CACHE_RESULTS
+ m_cached_result = NAN;
+ #endif
+ #ifdef PARANOID_SIZE_LIMIT
+ if (m_size >= PARANOID_SIZE_LIMIT)
+ {
+ this->operator=(this->Digit());
+ if (op == ADD)
+ m_value += b->Digit();
+ else
+ m_value -= b->Digit();
+ m_size = 0;
+ Debug("Cut off %p", this);
+ return b;
+ }
+ //Debug("At size limit %d", m_size);
+ #endif
+
+
+ if (Floating() && m_value == 0) // 0 + b = b
+ {
+ m_value = b->m_value;
+ if (op == SUBTRACT)
+ {
+ m_value = -m_value;
+ swap(b->m_next[ADD], b->m_next[SUBTRACT]);
+ }
+
+ for (int i = 0; i < NOP; ++i)
+ {
+ m_next[i] = b->m_next[i];
+ b->m_next[i].clear();
+ }
+
+ //assert(SanityCheck());
+ return b;
+ }
+ if (b->Floating() && b->m_value == 0) // a + 0 = a
+ return b;
+
+ if ((NoFactors() && b->NoFactors())
+ || (GetFactors() == b->GetFactors()))
+ {
+ if (ParanoidOp<digit_t>(m_value, b->m_value, op))
+ {
+ Optype addop = (op == ADD) ? ADD : SUBTRACT;
+ for (auto add : b->m_next[ADD])
+ {
+ delete (OperationTerm(add, addop));
+ }
+ Optype subop = (op == ADD) ? SUBTRACT : ADD;
+ for (auto sub : b->m_next[SUBTRACT])
+ delete (OperationTerm(sub, subop));
+
+ b->m_next[ADD].clear();
+ b->m_next[SUBTRACT].clear();
+ //assert(SanityCheck());
+ return b;
+ }
+ }
+
+
+
+ bool parent = (merge_point == NULL);
+ ParanoidNumber * merge = this;
+ Optype mop = op;
+ //assert(mop != NOP); // silence compiler warning
+ if (parent)
+ {
+ merge_point = &merge;
+ merge_op = &mop;
+ }
+ else
+ {
+ merge = *merge_point;
+ mop = *merge_op;
+ }
+
+ Optype invop = InverseOp(op); // inverse of p
+ Optype fwd = op;
+ Optype rev = invop;
+ if (op == SUBTRACT)
+ {
+ fwd = ADD;
+ rev = SUBTRACT;
+ }
+
+ for (auto prev : m_next[invop])
+ {
+ if (prev->OperationTerm(b, rev, merge_point, merge_op) == b)
+ {
+ //assert(SanityCheck());
+ return b;
+ }
- if (a.Floating() && ParanoidOp<digit_t>(m_value, a.m_value, DIVIDE))
+ }
+ for (auto next : m_next[op])
{
- if (m_next_term != NULL)
- m_next_term->operator/=(a);
- Simplify();
- return *this;
+ if (next->OperationTerm(b, fwd, merge_point, merge_op) == b)
+ {
+ //assert(SanityCheck());
+ return b;
+ }
}
- //Debug("Called %s /= %s", Str().c_str(), a.Str().c_str());
- // this = (vf + t) * (a)
- ParanoidNumber * t = this;
- while (t->m_next_factor != NULL)
+
+
+
+ if (parent)
+ {
+ //merge->m_next[*merge_op].push_back(b);
+ m_next[op].push_back(b);
+ #ifdef PARANOID_SIZE_LIMIT
+ m_size += 1+b->m_size;
+ #endif
+ }
+ else
{
- t = t->m_next_factor;
+ if (m_next[op].size() == 0)
+ {
+ *merge_point = this;
+ *merge_op = op;
+ }
}
- t->m_next_factor = new ParanoidNumber(a, DIVIDE);
- if (m_next_term != NULL)
- m_next_term->operator/=(a);
+ //assert(SanityCheck());
- Simplify();
- return *this;
+ return NULL;
}
+ParanoidNumber * ParanoidNumber::OperationFactor(ParanoidNumber * b, Optype op, ParanoidNumber ** merge_point, Optype * merge_op)
+{
+ #ifdef PARANOID_CACHE_RESULTS
+ m_cached_result = NAN;
+ #endif
+ #ifdef PARANOID_SIZE_LIMIT
+ if (m_size >= PARANOID_SIZE_LIMIT)
+ {
+ this->operator=(this->Digit());
+ if (op == MULTIPLY)
+ m_value *= b->Digit();
+ else
+ m_value /= b->Digit();
+ m_size = 0;
+
+ Debug("Cut off %p", this);
+ return b;
+
+ }
+ #endif
-
-void ParanoidNumber::SimplifyTerms()
-{
-
- //Debug("Simplify {%s}", Str().c_str());
- if (m_next_term == NULL)
+ if (Floating() && m_value == 0)
{
- //Debug("No terms!");
- return;
+ return b;
}
-
- for (ParanoidNumber * a = this; a != NULL; a = a->m_next_term)
+
+ if (Floating() && m_value == 1 && op == MULTIPLY)
{
- ParanoidNumber * b = a->m_next_term;
- if (a->m_next_factor != NULL && !a->m_next_factor->Floating())
+ m_value = b->m_value;
+ for (int i = 0; i < NOP; ++i)
{
- continue;
+ for (auto n : m_next[i])
+ delete (n);
+ m_next[i].clear();
+ swap(m_next[i], b->m_next[i]);
}
+ //assert(SanityCheck());
+ return b;
+ }
+ if (b->Floating() && b->m_value == 1)
+ return b;
+ if (b->Floating() && b->m_value == 0 && op == MULTIPLY)
+ {
+ operator=(*b);
+ return b;
+ }
+
- ParanoidNumber * bprev = a;
- while (b != NULL)
+ if (NoTerms() && b->NoTerms())
+ {
+ if (ParanoidOp<digit_t>(m_value, b->m_value, op))
{
- //Debug("Simplify factors of %s", b->Str().c_str());
- b->SimplifyFactors();
- if (b->m_next_factor != NULL && !b->m_next_factor->Floating())
- {
- bprev = b;
- b = b->m_next_term;
- continue;
- }
-
- bool simplify = false;
- if (a->m_next_factor != NULL || b->m_next_factor != NULL)
+ Optype mulop = (op == MULTIPLY) ? MULTIPLY : DIVIDE;
+ for (auto mul : b->m_next[MULTIPLY])
{
- digit_t aa(a->Head<digit_t>());
- digit_t ab = (a->m_next_factor != NULL) ? a->m_next_factor->Head<digit_t>() : 1;
- digit_t bc(b->Head<digit_t>());
- digit_t bd = (b->m_next_factor != NULL) ? b->m_next_factor->Head<digit_t>() : 1;
- Optype aop = (a->m_next_factor != NULL) ? a->m_next_factor->m_op : DIVIDE;
- Optype cop = (b->m_next_factor != NULL) ? b->m_next_factor->m_op : DIVIDE;
- simplify = CombineTerms<digit_t>(aa, aop, ab, bc, cop, bd);
- if (simplify)
- {
- a->m_value = aa;
- if (a->m_next_factor != NULL)
- a->m_next_factor->m_value = ab;
- else if (ab != 1)
- {
- a->m_next_factor = b->m_next_factor;
- b->m_next_factor = NULL;
- a->m_next_factor->m_value = ab;
- }
- }
+ delete(OperationFactor(mul, mulop));
}
- else
+ Optype divop = (op == MULTIPLY) ? DIVIDE : MULTIPLY;
+ for (auto div : b->m_next[DIVIDE])
+ delete(OperationFactor(div, divop));
+
+ b->m_next[DIVIDE].clear();
+ b->m_next[MULTIPLY].clear();
+ return b;
+ }
+ }
+
+
+ bool parent = (merge_point == NULL);
+ ParanoidNumber * merge = this;
+ Optype mop = op;
+ if (parent)
+ {
+ merge_point = &merge;
+ merge_op = &mop;
+ }
+ else
+ {
+ merge = *merge_point;
+ mop = *merge_op;
+ }
+
+ Optype invop = InverseOp(op); // inverse of p
+ Optype fwd = op;
+ Optype rev = invop;
+ if (op == DIVIDE)
+ {
+ fwd = MULTIPLY;
+ rev = DIVIDE;
+ }
+
+ ParanoidNumber * cpy_b = new ParanoidNumber(*b);
+ for (auto prev : m_next[invop])
+ {
+ if (prev->OperationFactor(b, rev, merge_point, merge_op) == b)
+ {
+ for (auto add : m_next[ADD])
+ delete(add->OperationFactor(new ParanoidNumber(*cpy_b), op));
+ for (auto sub : m_next[SUBTRACT])
+ delete(sub->OperationFactor(new ParanoidNumber(*cpy_b), op));
+
+ delete(cpy_b);
+ return b;
+ }
+ }
+ for (auto next : m_next[op])
+ {
+ if (next->OperationFactor(b, fwd, merge_point, merge_op) == b)
+ {
+ for (auto add : m_next[ADD])
{
- simplify = ParanoidOp<digit_t>(a->m_value, b->Head<digit_t>(), ADD);
+ delete(add->OperationFactor(new ParanoidNumber(*cpy_b), op));
}
- if (simplify)
+ for (auto sub : m_next[SUBTRACT])
{
- bprev->m_next_term = b->m_next_term;
- b->m_next_term = NULL;
- delete b;
- b = bprev;
+ delete(sub->OperationFactor(new ParanoidNumber(*cpy_b), op));
}
-
- bprev = b;
- b = b->m_next_term;
+ delete(cpy_b);
+ return b;
}
}
+
+ if (parent)
+ {
+ //assert(b != NULL);
+ m_next[op].push_back(b);
+ for (auto add : m_next[ADD])
+ delete(add->OperationFactor(new ParanoidNumber(*cpy_b), op));
+ for (auto sub : m_next[SUBTRACT])
+ delete(sub->OperationFactor(new ParanoidNumber(*cpy_b), op));
+
+ #ifdef PARANOID_SIZE_LIMIT
+ m_size += 1+b->m_size;
+ #endif
+ }
+ //assert(SanityCheck());
+
+
+
+ return NULL;
+}
+
+
+
+/**
+ * Performs the operation on a with argument b (a += b, a -= b, a *= b, a /= b)
+ * @returns b if b can safely be deleted
+ * @returns NULL if b has been merged with a
+ * append indicates that b should be merged
+ */
+ParanoidNumber * ParanoidNumber::Operation(ParanoidNumber * b, Optype op, ParanoidNumber ** merge_point, Optype * merge_op)
+{
+
+ if (b == NULL)
+ return NULL;
+
+
+ if (op == SUBTRACT || op == ADD)
+ return OperationTerm(b, op, merge_point, merge_op);
+ if (op == MULTIPLY || op == DIVIDE)
+ return OperationFactor(b, op, merge_point, merge_op);
+ return b;
}
-void ParanoidNumber::SimplifyFactors()
-{
- //Debug("Simplify {%s}", Str().c_str());
- if (m_next_factor == NULL)
+
+string ParanoidNumber::PStr() const
+{
+ stringstream s;
+ for (int i = 0; i < NOP; ++i)
{
- //Debug("No factors!");
- return;
+ Optype f = Optype(i);
+ s << this;
+ for (auto n : m_next[f])
+ {
+ s << OpChar(f) << n->PStr();
+ }
}
+ return s.str();
+}
- for (ParanoidNumber * a = this; a != NULL; a = a->m_next_factor)
+bool ParanoidNumber::Simplify(Optype op)
+{
+
+ if (Floating())
+ return false;
+
+ //assert(SanityCheck());
+ vector<ParanoidNumber*> next;
+ next.clear();
+ swap(m_next[op], next);
+ m_next[op].clear();
+ //assert(m_next[op].size() == 0);
+ //assert(SanityCheck());
+ Optype fwd = op;
+ if (op == DIVIDE)
+ fwd = MULTIPLY;
+ else if (op == SUBTRACT)
+ fwd = ADD;
+
+
+ vector<ParanoidNumber*> hold[2];
+ if (op == MULTIPLY || op == DIVIDE)
{
- if ((a->m_op != ADD || a->m_op != SUBTRACT) && a->m_next_term != NULL)
+ swap(m_next[ADD], hold[0]);
+ swap(m_next[SUBTRACT], hold[1]);
+ }
+
+ for (vector<ParanoidNumber*>::iterator n = next.begin(); n != next.end(); ++n)
+ {
+ if (*n == NULL)
continue;
-
- ParanoidNumber * bprev = a;
- ParanoidNumber * b = a->m_next_factor;
- while (b != NULL)
+ for (vector<ParanoidNumber*>::iterator m = n; m != next.end(); ++m)
{
- b->SimplifyTerms();
- if (b->m_next_term != NULL)
- {
- bprev = b;
- b = b->m_next_factor;
+ if ((*m) == (*n))
continue;
- }
-
- Optype op = b->m_op;
- if (a->m_op == DIVIDE)
+ if (*m == NULL)
+ continue;
+
+ ParanoidNumber * parent = this;
+ Optype mop = op;
+ ParanoidNumber * result = (*n)->Operation(*m, fwd, &parent, &mop);
+ if (result != NULL)
{
- op = (b->m_op == DIVIDE) ? MULTIPLY : DIVIDE;
- }
-
- if (ParanoidOp<digit_t>(a->m_value, b->m_value, op))
- {
-
- bprev->m_next_factor = b->m_next_factor;
- b->m_next_factor = NULL;
- delete b;
- b = bprev;
+ #ifdef PARANOID_SIZE_LIMIT
+ m_size -= (1+result->m_size);
+ #endif
+ *m = NULL;
+ delete(result);
}
- bprev = b;
- b = b->m_next_factor;
}
}
+
+
+
+ for (auto n : next)
+ {
+ if (n != NULL)
+ {
+ #ifdef PARANOID_SIZE_LIMIT
+ if (Operation(n, op) == n)
+ {
+ m_size -= (1+n->m_size);
+ delete n;
+ }
+ #else
+ delete(Operation(n, op));
+ #endif
+ }
+ }
+
+ if (op == MULTIPLY || op == DIVIDE)
+ {
+ swap(m_next[ADD], hold[0]);
+ swap(m_next[SUBTRACT], hold[1]);
+ }
+
+ set<ParanoidNumber*> s;
+ //if (!SanityCheck(s))
+ //{
+ // Error("Simplify broke Sanity");
+ //}
+ return (next.size() > m_next[op].size());
}
-void ParanoidNumber::Simplify()
+bool ParanoidNumber::FullSimplify()
{
- SimplifyFactors();
- SimplifyTerms();
+ bool result = false;
+ result |= Simplify(MULTIPLY);
+ result |= Simplify(DIVIDE);
+ result |= Simplify(ADD);
+ result |= Simplify(SUBTRACT);
+ return result;
}
-string ParanoidNumber::Str() const
+ParanoidNumber::digit_t ParanoidNumber::Digit() const
{
- string result("");
- stringstream s;
- s << (double)m_value;
+
+ // Get around the absurd requirement that const correctness be observed.
+ #ifdef PARANOID_CACHE_RESULTS
+ digit_t & result = ((ParanoidNumber*)(this))->m_cached_result;
- if (m_next_factor != NULL)
- {
- result += s.str();
- result += OpChar(m_next_factor->m_op);
- if (m_next_factor->m_next_term != NULL)
- result += "(" + m_next_factor->Str() + ")";
- else
- result += m_next_factor->Str();
- }
- else
+ if (!isnan(float(result))) // le sigh ambiguous function compiler warnings
+ return result;
+ #else
+ digit_t result;
+ #endif
+ result = m_value;
+ for (auto mul : m_next[MULTIPLY])
{
- result += s.str();
+ result *= mul->Digit();
}
-
- if (m_next_term != NULL)
+ for (auto div : m_next[DIVIDE])
{
- result += " ";
- result += OpChar(m_next_term->m_op);
- result += m_next_term->Str();
+ result /= div->Digit();
}
+ for (auto add : m_next[ADD])
+ result += add->Digit();
+ for (auto sub : m_next[SUBTRACT])
+ result -= sub->Digit();
return result;
+
}
-template <>
-bool TrustingOp<float>(float & a, const float & b, Optype op)
+ParanoidNumber::digit_t ParanoidNumber::GetFactors() const
{
- feclearexcept(FE_ALL_EXCEPT);
- switch (op)
+ digit_t value = 1;
+ for (auto mul : m_next[MULTIPLY])
+ value *= mul->Digit();
+ for (auto div : m_next[DIVIDE])
+ value /= div->Digit();
+ return value;
+}
+
+
+ParanoidNumber::digit_t ParanoidNumber::GetTerms() const
+{
+ digit_t value = 0;
+ for (auto add : m_next[ADD])
+ value += add->Digit();
+ for (auto sub : m_next[SUBTRACT])
+ value -= sub->Digit();
+ return value;
+}
+
+bool ParanoidNumber::SanityCheck(set<ParanoidNumber*> & visited) const
+{
+ if (this == NULL)
{
- case ADD:
- a += b;
- break;
- case SUBTRACT:
- a -= b;
- break;
- case MULTIPLY:
- a *= b;
- break;
- case DIVIDE:
- a /= b;
- break;
+ Error("NULL pointer in tree");
+ return false;
}
- return !fetestexcept(FE_ALL_EXCEPT);
+
+ if (visited.find((ParanoidNumber*)this) != visited.end())
+ {
+ Error("I think I've seen this tree before...");
+ return false;
+ }
+
+ visited.insert((ParanoidNumber*)this);
+
+ for (auto add : m_next[ADD])
+ {
+ if (!add->SanityCheck(visited))
+ return false;
+ }
+ for (auto sub : m_next[SUBTRACT])
+ {
+ if (!sub->SanityCheck(visited))
+ return false;
+ }
+ for (auto mul : m_next[MULTIPLY])
+ {
+ if (!mul->SanityCheck(visited))
+ return false;
+ }
+
+ for (auto div : m_next[DIVIDE])
+ {
+ if (!div->SanityCheck(visited))
+ return false;
+ if (div->Digit() == 0)
+ {
+ Error("Divide by zero");
+ return false;
+ }
+ }
+ return true;
}
-template <>
-bool TrustingOp<double>(double & a, const double & b, Optype op)
+void ParanoidNumber::Negate()
{
- feclearexcept(FE_ALL_EXCEPT);
- switch (op)
+ swap(m_next[ADD], m_next[SUBTRACT]);
+ m_value = -m_value;
+}
+
+#ifdef PARANOID_USE_ARENA
+
+void * ParanoidNumber::operator new(size_t s)
+{
+ return g_arena.allocate(s);
+}
+
+void ParanoidNumber::operator delete(void * p)
+{
+ g_arena.deallocate(p);
+}
+
+ParanoidNumber::Arena::Arena(int64_t block_size) : m_block_size(block_size), m_spare(NULL)
+{
+ m_blocks.push_back({malloc(block_size*sizeof(ParanoidNumber)),0});
+}
+
+ParanoidNumber::Arena::~Arena()
+{
+ for (auto block : m_blocks)
{
- case ADD:
- a += b;
- break;
- case SUBTRACT:
- a -= b;
- break;
- case MULTIPLY:
- a *= b;
- break;
- case DIVIDE:
- a /= b;
- break;
+ free(block.memory);
}
- return !fetestexcept(FE_ALL_EXCEPT);
+ m_blocks.clear();
}
-template <>
-bool TrustingOp<int8_t>(int8_t & a, const int8_t & b, Optype op)
+void * ParanoidNumber::Arena::allocate(size_t s)
{
- int16_t sa(a);
- bool exact = true;
- switch (op)
+ if (m_spare != NULL)
{
- case ADD:
- sa += b;
- exact = (abs(sa) <= 127);
- break;
- case SUBTRACT:
- sa -= b;
- exact = (abs(sa) <= 127);
- break;
- case MULTIPLY:
- sa *= b;
- exact = (abs(sa) <= 127);
- break;
- case DIVIDE:
- exact = (b != 0 && sa > b && sa % b == 0);
- sa /= b;
- break;
+ void * result = m_spare;
+ m_spare = NULL;
+ return result;
}
- a = (int8_t)(sa);
- return exact;
+
+ Block & b = m_blocks.back();
+ void * result = (ParanoidNumber*)(b.memory) + (b.used++);
+ if (b.used >= m_block_size)
+ {
+ m_block_size *= 2;
+ Debug("Add block of size %d", m_block_size);
+ m_blocks.push_back({malloc(m_block_size*sizeof(ParanoidNumber)), 0});
+ }
+ return result;
+}
+
+void ParanoidNumber::Arena::deallocate(void * p)
+{
+ m_spare = p;
}
+#endif //PARANOID_USE_ARENA
}
#include <string>
#include "log.h"
#include <fenv.h>
+#include <vector>
+#include <cmath>
+#include <cassert> // it's going to be ok
+#include <set>
-#define PARANOID_DIGIT_T float // we could theoretically replace this with a template
+#define PARANOID_DIGIT_T double // we could theoretically replace this with a template
// but let's not do that...
+
+
+//#define PARANOID_CACHE_RESULTS
+
+//#define PARANOID_USE_ARENA
+#define PARANOID_SIZE_LIMIT 1
+
+
+// Define to compare all ops against double ops and check within epsilon
+#define PARANOID_COMPARE_EPSILON 1e-6
+#define CompareForSanity(...) ParanoidNumber::CompareForSanityEx(__func__, __FILE__, __LINE__, __VA_ARGS__)
namespace IPDF
{
- typedef enum {ADD, SUBTRACT, MULTIPLY, DIVIDE} Optype;
+ typedef enum {ADD, SUBTRACT, MULTIPLY, DIVIDE, NOP} Optype;
+ inline Optype InverseOp(Optype op)
+ {
+ return ((op == ADD) ? SUBTRACT :
+ (op == SUBTRACT) ? ADD :
+ (op == MULTIPLY) ? DIVIDE :
+ (op == DIVIDE) ? MULTIPLY :
+ (op == NOP) ? NOP : NOP);
+ }
+
+
+ inline char OpChar(int op)
+ {
+ static char opch[] = {'+','-','*','/'};
+ return (op < NOP && op >= 0) ? opch[op] : '?';
+ }
+
/** Performs an operation, returning if the result was exact **/
// NOTE: DIFFERENT to ParanoidOp (although that wraps to this...)
}
return false;
}
-
-
template <> bool TrustingOp<float>(float & a, const float & b, Optype op);
template <> bool TrustingOp<double>(double & a, const double & b, Optype op);
template <> bool TrustingOp<int8_t>(int8_t & a, const int8_t & b, Optype op);
- // Attempt to comine two terms: a*b + c*d or a/b + c/d
- template <class T> bool CombineTerms(T & aa, Optype aop, T & bb, T & cc, Optype cop, T & dd)
- {
- T a(aa); T b(bb); T c(cc); T d(dd);
- if (aop == MULTIPLY && cop == MULTIPLY) // a*b + c*d
- {
-
- if ((ParanoidOp<T>(c, b, DIVIDE) || ParanoidOp(d, b, DIVIDE))
- && TrustingOp<T>(c, d, MULTIPLY) && TrustingOp<T>(a,c,ADD)
- && TrustingOp<T>(a, b, MULTIPLY)) // (a + (cd)/b) * b
- {
- aa = a;
- bb = 1;
- cc = 1;
- dd = 1;
- return true;
- }
- if ((ParanoidOp<T>(a, d, DIVIDE) || ParanoidOp(b, d, DIVIDE))
- && TrustingOp<T>(a, b, MULTIPLY) && TrustingOp<T>(a,c,ADD)
- && TrustingOp<T>(a, d, MULTIPLY)) // ((ab)/d + c)*d
- {
- aa = a;
- bb = 1;
- cc = 1;
- dd = 1;
- return true;
- }
- return false;
- }
- else if (aop == DIVIDE && cop == DIVIDE)
- {
-
-
- if (TrustingOp<T>(a, d, MULTIPLY) && TrustingOp<T>(c, b, MULTIPLY)
- && TrustingOp<T>(a, c, ADD) && TrustingOp<T>(b, d, MULTIPLY))
- {
- cc = 1;
- dd = 1;
- if (ParanoidOp<T>(a, b, DIVIDE))
- {
- aa = a;
- bb = 1;
- return true;
- }
- aa = a;
- bb = b;
- return true;
- }
- return false;
- }
- return false;
- }
-
+ /**
+ * A ParanoidNumber
+ * Idea: Perform regular floating point arithmetic but rearrange operations to only ever use exact results
+ * Memory Usage: O(all of it)
+ * CPU Usage: O(all of it)
+ * Accuracy: O(gives better result for 0.3+0.3+0.3, gives same result for everything else, or worse result)
+ *
+ * The ParanoidNumber basically stores 4 linked lists which can be split into two "dimensions"
+ * 1. Terms to ADD and terms to SUBTRACT
+ * 2. Factors to MULTIPLY and DIVIDE
+ * Because ADD and SUBTRACT are inverse operations and MULTIPLY and DIVIDE are inverse operations
+ * See paranoidnumber.cpp and the ParanoidNumber::Operation function
+ */
class ParanoidNumber
{
public:
typedef PARANOID_DIGIT_T digit_t;
- ParanoidNumber(digit_t value=0, Optype type = ADD) : m_value(value), m_op(type), m_next_term(NULL), m_next_factor(NULL)
+ ParanoidNumber(PARANOID_DIGIT_T value=0) : m_value(value), m_next()
{
- Construct();
+ #ifdef PARANOID_SIZE_LIMIT
+ m_size = 0;
+ #endif
+ #ifdef PARANOID_CACHE_RESULTS
+ m_cached_result = value;
+ #endif
}
- ParanoidNumber(const ParanoidNumber & cpy) : m_value(cpy.m_value), m_op(cpy.m_op), m_next_term(NULL), m_next_factor(NULL)
+ ParanoidNumber(const ParanoidNumber & cpy) : m_value(cpy.m_value), m_next()
{
- if (cpy.m_next_term != NULL)
- {
- m_next_term = new ParanoidNumber(*(cpy.m_next_term));
- }
- if (cpy.m_next_factor != NULL)
+
+ #ifdef PARANOID_SIZE_LIMIT
+ m_size = cpy.m_size;
+ #endif
+ #ifdef PARANOID_CACHE_RESULTS
+ m_cached_result = cpy.m_cached_result;
+ #endif
+ for (int i = 0; i < NOP; ++i)
{
- m_next_factor = new ParanoidNumber(*(cpy.m_next_factor));
+ for (auto next : cpy.m_next[i])
+ {
+ if (next != NULL) // why would this ever be null
+ m_next[i].push_back(new ParanoidNumber(*next)); // famous last words...
+ }
}
- Construct();
+ #ifdef PARANOID_COMPARE_EPSILON
+ CompareForSanity(cpy.Digit(), cpy.Digit());
+ #endif
+ //assert(SanityCheck());
}
- ParanoidNumber(const ParanoidNumber & cpy, Optype type) : ParanoidNumber(cpy)
- {
- m_op = type;
- }
+ //ParanoidNumber(const char * str);
+ ParanoidNumber(const std::string & str);// : ParanoidNumber(str.c_str()) {}
- ParanoidNumber(const char * str);
- ParanoidNumber(const std::string & str) : ParanoidNumber(str.c_str()) {Construct();}
+ virtual ~ParanoidNumber();
+
- virtual ~ParanoidNumber()
+ bool SanityCheck(std::set<ParanoidNumber*> & visited) const;
+ bool SanityCheck() const
{
- if (m_next_term != NULL)
- delete m_next_term;
- if (m_next_factor != NULL)
- delete m_next_factor;
- g_count--;
+ std::set<ParanoidNumber*> s;
+ return SanityCheck(s);
}
- inline void Construct() {g_count++;}
-
-
template <class T> T Convert() const;
- template <class T> T AddTerms() const;
- template <class T> T MultiplyFactors() const;
- template <class T> T Head() const {return (m_op == SUBTRACT) ? T(-m_value) : T(m_value);}
+ digit_t GetFactors() const;
+ digit_t GetTerms() const;
+
+ // This function is declared const purely to trick the compiler.
+ // It is not actually const, and therefore, none of the other functions that call it are const either.
+ digit_t Digit() const;
-
+ // Like this one. It isn't const.
+ double ToDouble() const {return (double)Digit();}
+ // This one is probably const.
+ bool Floating() const
+ {
+ return NoFactors() && NoTerms();
+ }
+ bool Sunken() const {return !Floating();} // I could not resist...
- double ToDouble() const {return Convert<double>();}
- float ToFloat() const {return Convert<float>();}
- digit_t Digit() const {return Convert<digit_t>();}
+ bool NoFactors() const {return (m_next[MULTIPLY].size() == 0 && m_next[DIVIDE].size() == 0);}
+ bool NoTerms() const {return (m_next[ADD].size() == 0 && m_next[SUBTRACT].size() == 0);}
- bool Floating() const {return (m_next_term == NULL && m_next_factor == NULL);}
- bool Sunken() const {return !Floating();} // I could not resist...
ParanoidNumber & operator+=(const ParanoidNumber & a);
ParanoidNumber & operator-=(const ParanoidNumber & a);
ParanoidNumber & operator/=(const ParanoidNumber & a);
ParanoidNumber & operator=(const ParanoidNumber & a);
+ ParanoidNumber & operator+=(const digit_t & a);
+ ParanoidNumber & operator-=(const digit_t & a);
+ ParanoidNumber & operator*=(const digit_t & a);
+ ParanoidNumber & operator/=(const digit_t & a);
+ ParanoidNumber & operator=(const digit_t & a);
+
+
+ ParanoidNumber * OperationTerm(ParanoidNumber * b, Optype op, ParanoidNumber ** merge_point = NULL, Optype * mop = NULL);
+ ParanoidNumber * OperationFactor(ParanoidNumber * b, Optype op, ParanoidNumber ** merge_point = NULL, Optype * mop = NULL);
+ ParanoidNumber * TrivialOp(ParanoidNumber * b, Optype op);
+ ParanoidNumber * Operation(ParanoidNumber * b, Optype op, ParanoidNumber ** merge_point = NULL, Optype * mop = NULL);
+ bool Simplify(Optype op);
+ bool FullSimplify();
+
+
+ // None of these are actually const
+ bool operator<(const ParanoidNumber & a) const {return Digit() < a.Digit();}
+ bool operator<=(const ParanoidNumber & a) const {return Digit() <= a.Digit();}
+ bool operator>(const ParanoidNumber & a) const {return Digit() > a.Digit();}
+ bool operator>=(const ParanoidNumber & a) const {return Digit() >= a.Digit();}
+ bool operator==(const ParanoidNumber & a) const {return Digit() == a.Digit();}
+ bool operator!=(const ParanoidNumber & a) const {return Digit() != a.Digit();}
+
+ ParanoidNumber operator-() const
+ {
+ ParanoidNumber neg(*this);
+ neg.Negate();
+ #ifdef PARANOID_COMPARE_EPSILON
+ neg.CompareForSanity(-Digit(), Digit());
+ #endif
+ return neg;
+ }
+
+ void Negate();
- bool operator<(const ParanoidNumber & a) const {return ToDouble() < a.ToDouble();}
- bool operator<=(const ParanoidNumber & a) const {return this->operator<(a) || this->operator==(a);}
- bool operator>(const ParanoidNumber & a) const {return !(this->operator<=(a));}
- bool operator>=(const ParanoidNumber & a) const {return !(this->operator<(a));}
- bool operator==(const ParanoidNumber & a) const {return ToDouble() == a.ToDouble();}
- bool operator!=(const ParanoidNumber & a) const {return !(this->operator==(a));}
ParanoidNumber operator+(const ParanoidNumber & a) const
{
ParanoidNumber result(*this);
result += a;
+ #ifdef PARANOID_COMPARE_EPSILON
+ result.CompareForSanity(Digit()+a.Digit(), a.Digit());
+ #endif
return result;
}
ParanoidNumber operator-(const ParanoidNumber & a) const
{
ParanoidNumber result(*this);
result -= a;
+ #ifdef PARANOID_COMPARE_EPSILON
+ result.CompareForSanity(Digit()-a.Digit(), a.Digit());
+ #endif
return result;
}
ParanoidNumber operator*(const ParanoidNumber & a) const
{
ParanoidNumber result(*this);
result *= a;
+ #ifdef PARANOID_COMPARE_EPSILON
+ result.CompareForSanity(Digit()*a.Digit(), a.Digit());
+ #endif
return result;
}
ParanoidNumber operator/(const ParanoidNumber & a) const
{
ParanoidNumber result(*this);
result /= a;
+ #ifdef PARANOID_COMPARE_EPSILON
+ result.CompareForSanity(Digit()/a.Digit(), a.Digit());
+ #endif
return result;
}
std::string Str() const;
- static char OpChar(Optype op)
+
+ inline void CompareForSanityEx(const char * func, const char * file, int line, const digit_t & compare, const digit_t & arg, const digit_t & eps = PARANOID_COMPARE_EPSILON)
{
- static char opch[] = {'+','-','*','/'};
- return opch[(int)op];
+ if (!SanityCheck())
+ Fatal("This is insane!");
+ if (fabs(Digit() - compare) > eps)
+ {
+ Error("Called via %s(%lf) (%s:%d)", func, arg, file, line);
+ Error("Failed: %s", Str().c_str());
+ Fatal("This: %.30lf vs Expected: %.30lf", Digit(), compare);
+ }
}
-
- static int64_t Paranoia() {return g_count;}
+
+
+ std::string PStr() const;
+
+ #ifdef PARANOID_USE_ARENA
+ void * operator new(size_t byes);
+ void operator delete(void * p);
+ #endif //PARANOID_USE_ARENA
private:
- static int64_t g_count;
+
void Simplify();
void SimplifyTerms();
void SimplifyFactors();
+ digit_t m_value;
+ #ifdef PARANOID_CACHE_RESULTS
+ digit_t m_cached_result;
+ #endif
+ std::vector<ParanoidNumber*> m_next[4];
+ #ifdef PARANOID_SIZE_LIMIT
+ int64_t m_size;
+ #endif //PARANOID_SIZE_LIMIT
- digit_t m_value;
- Optype m_op;
- ParanoidNumber * m_next_term;
- ParanoidNumber * m_next_factor;
+ #ifdef PARANOID_USE_ARENA
+ class Arena
+ {
+ public:
+ Arena(int64_t block_size = 10000000);
+ ~Arena();
+
+ void * allocate(size_t bytes);
+ void deallocate(void * p);
+
+ private:
+ struct Block
+ {
+ void * memory;
+ int64_t used;
+ };
+
+ std::vector<Block> m_blocks;
+ int64_t m_block_size;
+
+ void * m_spare;
+
+ };
+
+ static Arena g_arena;
+ #endif //PARANOID_USE_ARENA
+
+
};
+
+
+
template <class T>
-T ParanoidNumber::AddTerms() const
+T ParanoidNumber::Convert() const
{
- T value(0);
- for (ParanoidNumber * a = m_next_term; a != NULL; a = a->m_next_term)
+ #ifdef PARANOID_CACHE_RESULTS
+ if (!isnan((float(m_cached_result))))
+ return (T)m_cached_result;
+ #endif
+ T value(m_value);
+ for (auto mul : m_next[MULTIPLY])
{
- value += a->Head<T>() * a->MultiplyFactors<T>();
+ value *= mul->Convert<T>();
}
- return value;
-}
-
-template <class T>
-T ParanoidNumber::MultiplyFactors() const
-{
- T value(1);
- for (ParanoidNumber * a = m_next_factor; a != NULL; a = a->m_next_factor)
+ for (auto div : m_next[DIVIDE])
{
- if (a->m_op == DIVIDE)
- value /= (a->Head<T>() + a->AddTerms<T>());
- else
- value *= (a->Head<T>() + a->AddTerms<T>());
+ value /= div->Convert<T>();
}
+ for (auto add : m_next[ADD])
+ value += add->Convert<T>();
+ for (auto sub : m_next[SUBTRACT])
+ value -= sub->Convert<T>();
return value;
}
-template <class T>
-T ParanoidNumber::Convert() const
-{
- return Head<T>() * MultiplyFactors<T>() + AddTerms<T>();
-}
-
-
-
}
#endif //_PARANOIDNUMBER_H
// Find the bounds coordinates
// and identify the top left and bottom right objects
- unsigned left;
- unsigned right;
- unsigned top;
- unsigned bottom;
+ unsigned left = m_start;
+ unsigned right = m_start;
+ unsigned top = m_start;
+ unsigned bottom = m_start;
for (unsigned i = m_start; i <= m_end; ++i)
{
+ if (i >= objects.bounds.size())
+ break;
const Rect & objb = objects.bounds[i];
if (i == m_start || objb.x < xmin)
double ToDouble() const
{
T num = P, denom = Q;
- while (Tabs(num) > T(1e10))
+ while (Tabs(num) > T(1e10) || Tabs(denom) > T(1e10))
{
num /= T(16);
denom /= T(16);
"Rational<int64_t>",
"Rational<Arbint>",
"mpfrc++ real",
- "iRRAM REAL"
+ "iRRAM REAL",
+ "ParanoidNumber",
+ "GMPrat"
};
#if REALTYPE == REAL_RATIONAL_ARBINT
#define REAL_RATIONAL_ARBINT 5
#define REAL_MPFRCPP 6
#define REAL_IRRAM 7
+#define REAL_PARANOIDNUMBER 8
+#define REAL_GMPRAT 9
#ifndef REALTYPE
#error "REALTYPE was not defined!"
#include "../contrib/iRRAM/include/iRRAM/lib.h"
#endif
+#if REALTYPE == REAL_PARANOIDNUMBER
+ #include "paranoidnumber.h"
+#endif
+
+#if REALTYPE == REAL_GMPRAT
+ #include "gmprat.h"
+#endif
+
namespace IPDF
{
extern const char * g_real_name[];
#if REALTYPE == REAL_SINGLE
typedef float Real;
+ inline Real RealFromStr(const char * str) {return strtof(str, NULL);}
#elif REALTYPE == REAL_DOUBLE
typedef double Real;
+ inline Real RealFromStr(const char * str) {return strtod(str, NULL);}
#elif REALTYPE == REAL_LONG_DOUBLE
typedef long double Real;
+ inline Real RealFromStr(const char * str) {return strtold(str, NULL);}
#elif REALTYPE == REAL_VFPU
typedef VFPU::VFloat Real;
inline float Float(const Real & r) {return r.m_value;}
inline double Double(const Real & r) {return r.m_value;}
+ inline Real RealFromStr(const char * str) {return Real(strtod(str, NULL));}
#elif REALTYPE == REAL_RATIONAL
typedef Rational<int64_t> Real;
inline float Float(const Real & r) {return (float)r.ToDouble();}
inline double Double(const Real & r) {return r.ToDouble();}
+ inline Real RealFromStr(const char * str) {return Real(strtod(str, NULL));}
#elif REALTYPE == REAL_RATIONAL_ARBINT
- #define ARBINT Gmpint // Set to Gmpint or Arbint here
+ #define ARBINT Arbint // Set to Gmpint or Arbint here
typedef Rational<ARBINT> Real;
inline float Float(const Real & r) {return (float)r.ToDouble();}
inline double Double(const Real & r) {return r.ToDouble();}
inline int64_t Int64(const Real & r) {return r.ToInt64();}
inline Rational<ARBINT> Sqrt(const Rational<ARBINT> & r) {return r.Sqrt();}
+ inline Real RealFromStr(const char * str) {return Real(strtod(str, NULL));}
#elif REALTYPE == REAL_MPFRCPP
typedef mpfr::mpreal Real;
inline double Double(const Real & r) {return r.toDouble();}
inline int64_t Int64(const Real & r) {return r.toLong();}
inline Real Sqrt(const Real & r) {return mpfr::sqrt(r, mpfr::mpreal::get_default_rnd());}
inline Real Abs(const Real & r) {return mpfr::abs(r, mpfr::mpreal::get_default_rnd());}
+ inline Real RealFromStr(const char * str) {return Real(strtod(str, NULL));}
#elif REALTYPE == REAL_IRRAM
typedef iRRAM::REAL Real;
inline double Double(const Real & r) {return r.as_double(53);}
inline float Float(const Real & r) {return r.as_double(53);}
inline int64_t Int64(const Real & r) {return (int64_t)r.as_double(53);}
inline Real Sqrt(const Real & r) {return iRRAM::sqrt(r);}
+ inline Real RealFromStr(const char * str) {return Real(strtod(str, NULL));}
+#elif REALTYPE == REAL_PARANOIDNUMBER
+ typedef ParanoidNumber Real;
+ inline double Double(const Real & r) {return r.Digit();}
+ inline float Float(const Real & r) {return r.Digit();}
+ inline int64_t Int64(const Real & r) {return (int64_t)r.Digit();}
+ inline Real Sqrt(const Real & r) {return Real(sqrt(r.Digit()));}
+ inline Real RealFromStr(const char * str) {return Real(str);}
+ inline Real Abs(const Real & a) {return Real(fabs(a.Digit()));}
+#elif REALTYPE == REAL_GMPRAT
+ typedef Gmprat Real;
+ inline double Double(const Real & r) {return r.ToDouble();}
+ inline float Float(const Real & r) {return (float)(r.ToDouble());}
+ inline int64_t Int64(const Real & r) {return (int64_t)r.ToDouble();}
+ inline Real Sqrt(const Real & r) {return Real(sqrt(r.ToDouble()));}
+ inline Real RealFromStr(const char * str) {return Real(strtod(str, NULL));}
+ inline Real Abs(const Real & a) {return (a > Real(0)) ? a : Real(0)-a;}
+
#else
#error "Type of Real unspecified."
#endif //REALTYPE
{
Real x;
Real y;
- Vec2() : x(0), y(0) {}
+ Vec2() : x(0.0), y(0.0) {}
Vec2(Real _x, Real _y) : x(_x), y(_y) {}
Vec2(const std::pair<Real, Real> & p) : x(p.first), y(p.second) {}
#if REALTYPE != REAL_IRRAM
};
+ //TODO: Make sure there is actually a RealFromStr(const char * str) function
+ // Or this will recurse infinitely
+ // (If you remove this it will also break).
+ inline Real RealFromStr(const std::string & str) {return RealFromStr(str.c_str());}
+ inline void DebugRealInfo() {Debug("Compiled with REAL = %d => \"%s\" sizeof(Real) == %d bytes", REALTYPE, g_real_name[REALTYPE], sizeof(Real));}
}
struct Rect
{
Real x; Real y; Real w; Real h;
- Rect() = default; // Needed so we can fread/fwrite this struct
- Rect(Real _x, Real _y, Real _w, Real _h) : x(_x), y(_y), w(_w), h(_h) {}
+ //Rect() = default; // Needed so we can fread/fwrite this struct
+ Rect(Real _x=0, Real _y=0, Real _w=1, Real _h=1) : x(_x), y(_y), w(_w), h(_h) {}
std::string Str() const
{
std::stringstream s;
}
-Screen::Screen()
+Screen::Screen(bool visible)
{
SDL_Init(SDL_INIT_VIDEO);
+ uint32_t flags = SDL_WINDOW_OPENGL | SDL_WINDOW_RESIZABLE;
+ if (!visible)
+ flags |= SDL_WINDOW_HIDDEN;
+
m_window = SDL_CreateWindow("IPDF", SDL_WINDOWPOS_UNDEFINED, SDL_WINDOWPOS_UNDEFINED,
- 800, 600, SDL_WINDOW_OPENGL | SDL_WINDOW_RESIZABLE);
+ 800, 600, flags);
if (!m_window)
{
- Fatal("Couldn't create window!");
+ Error("Couldn't create window!");
+ return;
}
SDL_GL_SetAttribute(SDL_GL_CONTEXT_MAJOR_VERSION, 3);
// Why is this so horribly broken?
if (ogl_IsVersionGEQ(3,0))
{
- Fatal("We require OpenGL 3.1, but you have version %d.%d!",ogl_GetMajorVersion(), ogl_GetMinorVersion());
+ Error("We require OpenGL 3.1, but you have version %d.%d!",ogl_GetMajorVersion(), ogl_GetMinorVersion());
}
if (!SDL_GL_ExtensionSupported("GL_ARB_shading_language_420pack"))
{
- Fatal("Your system does not support the ARB_shading_language_420pack extension, which is required.");
+ Error("Your system does not support the ARB_shading_language_420pack extension, which is required.");
}
if (!SDL_GL_ExtensionSupported("GL_ARB_explicit_attrib_location"))
{
- Fatal("Your system does not support the ARB_explicit_attrib_location extension, which is required.");
+ Error("Your system does not support the ARB_explicit_attrib_location extension, which is required.");
}
m_frame_begin_time = SDL_GetPerformanceCounter();
Screen::~Screen()
{
+ if (!Valid())
+ return;
SDL_GL_DeleteContext(m_gl_context);
SDL_DestroyWindow(m_window);
SDL_Quit();
void Screen::Clear(float r, float g, float b, float a)
{
+ if (!Valid())
+ return;
glClearColor(r,g,b,a);
glClear(GL_COLOR_BUFFER_BIT);
DebugFontClear();
bool Screen::PumpEvents()
{
+ if (!Valid())
+ return true;
+
SDL_Event evt;
while (SDL_PollEvent(&evt))
void Screen::Present()
{
+ if (!Valid())
+ return;
if (m_debug_font_atlas)
DebugFontFlush();
m_last_frame_time = SDL_GetPerformanceCounter() - m_frame_begin_time;
double Screen::GetLastFrameTimeGPU() const
{
- if (!m_last_frame_gpu_timer)
+ if (!Valid() || !m_last_frame_gpu_timer)
return 0;
uint64_t frame_time_ns;
glGetQueryObjectui64v(m_last_frame_gpu_timer, GL_QUERY_RESULT, &frame_time_ns);
void Screen::ScreenShot(const char * filename) const
{
+ if (!Valid()) return;
Debug("Attempting to save BMP to file %s", filename);
int w = ViewportWidth();
*/
void Screen::RenderBMP(const char * filename) const
{
+ if (!Valid()) return;
if (access(filename, R_OK) == -1)
{
Error("No such file \"%s\" - Nothing to render - You might have done this deliberately?", filename);
void Screen::DebugFontInit(const char *name, float font_size)
{
+ if (!Valid()) return;
+
unsigned char font_atlas_data[1024*1024];
FILE *font_file = fopen(name, "rb");
fseek(font_file, 0, SEEK_END);
void Screen::DebugFontClear()
{
+ if (!Valid()) return;
m_debug_font_x = m_debug_font_y = 0;
if (!m_debug_font_atlas) return;
DebugFontPrint("\n");
void Screen::DebugFontFlush()
{
+ if (!Valid()) return;
glPushDebugGroup(GL_DEBUG_SOURCE_APPLICATION, 40, -1, "Screen::DebugFontFlush()");
glEnable(GL_BLEND);
void Screen::DebugFontPrint(const char* str)
{
+ if (!Valid()) return;
if (!m_debug_font_atlas || !m_show_debug_font) return;
glPushDebugGroup(GL_DEBUG_SOURCE_APPLICATION, 41, -1, "Screen::DebugFontPrint()");
class Screen
{
public:
- Screen();
+ Screen(bool visible = true);
~Screen();
// 'Pumps' the system event queue.
void ShowDebugFont(bool show = true) {m_show_debug_font = show;}
bool DebugFontShown() const {return m_show_debug_font;}
+
+ bool Valid() const {return m_window != NULL;}
private:
void ResizeViewport(int width, int height);
void DebugFontFlush();
--- /dev/null
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\ No newline at end of file
--- /dev/null
+#include "stresstest.h"
+#include "real.h"
+#include "progressbar.h"
+
+using namespace std;
+using namespace IPDF;
+
+int main(int argc, char ** argv)
+{
+ DebugRealInfo();
+ Debug("Repeated Adds and Subtracts - Should give zero");
+
+ clock_t first_clock = clock();
+ clock_t elapsed = 0;
+ for (int i = 1; i < 2; ++i)
+ {
+ for (int j = 1; j < 100; ++j)
+ {
+ clock_t start = clock();
+ Real result = AddSub<Real>(0, i, Real(1)/Real(j));
+ clock_t end = clock();
+ elapsed += end - start;
+ printf("%d\t%d\t%.30lf\t%li\t%li\n", i, j, Double(result), end-start, elapsed);
+
+ }
+ }
+ Debug("AddSub Total Time: %li", clock() - first_clock);
+
+}
+
--- /dev/null
+/**
+ * Get diff of bmps
+ */
+
+#include <SDL.h>
+#include <cassert>
+#include "ipdf.h"
+
+using namespace std;
+using namespace IPDF;
+
+
+int main(int argc, char ** argv)
+{
+ SDL_Surface * orig = SDL_LoadBMP(argv[1]);
+ SDL_Surface * diff = SDL_LoadBMP(argv[2]);
+
+ assert(orig->w == diff->w && orig->h == diff->h);
+ int w = diff->w;
+ int h = diff->h;
+
+ uint8_t * a = (uint8_t*)orig->pixels;
+ uint8_t * b = (uint8_t*)diff->pixels;
+
+ int total_diff = 0;
+
+ int mean_dist = 0;
+ int count_a = 0;
+ int count_b = 0;
+ for (int x = 0; x < w; ++x)
+ {
+ for (int y = 0; y < h; ++y)
+ {
+ if (a[4*(x + w*y)] == 0)
+ ++count_a;
+ if (b[4*(x + w*y)] == 0)
+ ++count_b;
+
+ if (a[4*(x + w*y)] != b[4*(x + w*y)] && b[4*(x+w*y)] == 0)
+ {
+ total_diff++;
+ //
+
+ int r = 1;
+ for (r=1; r+x < w; ++r)
+ {
+ if (a[4*(x+r + w*y)] == 0)
+ break;
+ }
+ int l = 1;
+ for (l=1; x-l >= 0; ++l)
+ {
+ if (a[4*(x-l + w*y)] == 0)
+ break;
+ }
+ int u = 1;
+ for (u=1; y-u >= 0; ++u)
+ {
+ if (a[4*(x + w*(y-u))] == 0)
+ break;
+ }
+
+ int d = 1;
+ for (d=1; y+d < h; ++d)
+ {
+ if (a[4*(x + w*(y+d))] == 0)
+ break;
+ }
+
+ mean_dist += min(min(d,u), min(r,l));
+ }
+ }
+ }
+ printf("%d\t%d\t%d\t%lf\n", count_a, count_b, total_diff, (double)mean_dist / (double)count_b);
+}
--- /dev/null
+#include "stresstest.h"
+#include "real.h"
+#include "progressbar.h"
+
+using namespace std;
+using namespace IPDF;
+
+int main(int argc, char ** argv)
+{
+ DebugRealInfo();
+
+ Debug("Repeated Multiplications and Divisions - Should give one");
+ first_clock = clock();
+ elapsed = 0;
+ for (int i = 1; i < 2; ++i)
+ {
+ for (int j = 1; j < 100; ++j)
+ {
+ clock_t start = clock();
+ Real result = MulDiv<Real>(1, i, Real(1)/Real(j));
+ clock_t end = clock();
+ printf("%d\t%d\t%.30lf\t%li\t%li\n", i, j, Double(result), end-start, elapsed);
+ }
+ }
+ Debug("MulDiv Total time: %li", clock() - first_clock);
+
+}
+
float fa = da;
while (cin.good())
{
+ Debug("a is {%s} \"%.40lf\"", a.Str().c_str(), a.ToDouble());
char op;
cin >> op;
token = "";
token += c;
c = cin.get();
}
- Debug("String is %s", token.c_str());
+
+ //Debug("String is \"%s\"", token.c_str());
float fb = strtof(token.c_str(), NULL);
double db = strtod(token.c_str(), NULL);
ParanoidNumber b(token.c_str());
- Debug("b is {%s} %lf", b.Str().c_str(), b.ToDouble());
+
+ Debug("b is {%s} \"%lf\"", b.Str().c_str(), b.ToDouble());
+ Debug("db is %lf", db);
switch (op)
{
case '+':
break;
}
- Debug("a is: %s", a.Str().c_str());
- Debug("a as double: %.40f\n", a.ToDouble());
- Debug("a as float: %.40f\n", a.ToFloat());
- Debug("a as int64_t: %ld\n", a.Convert<int64_t>());
- Debug("floats give: %.40f\n", fa);
- Debug("double gives: %.40f\n", da);
+ Debug("a is: {%s}", a.Str().c_str());
+ Debug("a as double: %.40lf", a.ToDouble());
+ //Debug("a as float: %.40f", a.ToFloat());
+ //Debug("a as int64_t: %ld", a.Convert<int64_t>());
+ //Debug("floats give: %.40f", fa);
+ Debug("double gives: %.40lf", da);
}
using namespace std;
using namespace IPDF;
-string RandomNumberAsString(int max_digits = 12)
+string RandomNumberAsString(int max_digits = 3)
{
string result("");
int digits = 1+(rand() % max_digits);
return result;
}
-bool CloseEnough(double d, ParanoidNumber & p)
+bool CloseEnough(long double d, ParanoidNumber & p, long double eps = 1e-6)
{
double pd = p.ToDouble();
if (d == 0)
- return fabs(pd) <= 1e-6;
- return fabs((fabs(pd - d) / d)) <= 1e-6;
+ return fabs(pd) <= eps;
+ return fabs((fabs(pd - d) / d)) <= eps;
+}
+
+void TestOp(ParanoidNumber & p, double & d, Optype op, const double amount)
+{
+ string p0str(p.Str());
+ double p0 = p.ToDouble();
+ switch (op)
+ {
+ case ADD:
+ p += amount;
+ d += amount;
+ break;
+ case SUBTRACT:
+ p -= amount;
+ d -= amount;
+ break;
+ case MULTIPLY:
+ p *= amount;
+ d *= amount;
+ break;
+ case DIVIDE:
+ p /= amount;
+ d /= amount;
+ break;
+ default:
+ break;
+ }
+ if (false)//(!CloseEnough(d, p))
+ {
+ Debug("%.40lf %c= %.40lf failed", p0, OpChar(op), amount);
+ Debug("%.40lf vs %.40lf", p.ToDouble(), d);
+ Debug("Before: {%s}\n", p0str.c_str());
+ Debug("After: {%s}\n", p.Str().c_str());
+ Fatal(":-(");
+ }
+
+}
+
+void TestAddSubIntegers(int max=100)
+{
+ Debug("Test add/sub integers 0 -> %i", max);
+ ParanoidNumber p;
+ double d(0);
+ for (int a = 0; a < max; ++a)
+ {
+ TestOp(p, d, ADD, a);
+ for (int b = 0; b < max; ++b)
+ {
+ TestOp(p, d, SUBTRACT, b);
+ }
+ for (int b = 0; b < max; ++b)
+ {
+ TestOp(p, d, ADD, b);
+ }
+ }
+ for (int a = 0; a < max; ++a)
+ {
+ TestOp(p, d, SUBTRACT, a);
+ for (int b = 0; b < max; ++b)
+ {
+ TestOp(p, d, ADD, b);
+ }
+ for (int b = 0; b < max; ++b)
+ {
+ TestOp(p, d, SUBTRACT, b);
+ }
+ }
+ Debug("PN Yields: %.40lf", p.ToDouble());
+ Debug("Doubles Yield: %.40lf", d);
+ Debug("Complete!");
+
+}
+
+void TestMulDivIntegers(int max=50)
+{
+ Debug("Test mul/div integers 1 -> %i", max);
+ ParanoidNumber p(1.0);
+ double d(1.0);
+ for (int a = 1; a < max; ++a)
+ {
+ TestOp(p, d, MULTIPLY, a);
+ for (int b = 1; b < max; ++b)
+ {
+ TestOp(p, d, DIVIDE, b);
+ }
+ for (int b = 1; b < max; ++b)
+ {
+ TestOp(p, d, MULTIPLY, b);
+ }
+ }
+ for (int a = 1; a < max; ++a)
+ {
+ TestOp(p, d, DIVIDE, a);
+ for (int b = 1; b < max; ++b)
+ {
+ TestOp(p, d, MULTIPLY, b);
+ }
+ for (int b = 1; b < max; ++b)
+ {
+ TestOp(p, d, DIVIDE, b);
+ }
+ }
+ Debug("PN Yields: %.40lf", p.ToDouble());
+ Debug("PN is: %s", p.Str().c_str());
+
+ Debug("Doubles Yield: %.40lf", d);
+ Debug("Complete!");
+
+}
+
+void TestRandomisedOps(int test_cases = 1000, int ops_per_case = 1, int max_digits = 4)
+{
+ Debug("Test %i*%i randomised ops (max digits = %i)", test_cases, ops_per_case, max_digits);
+ long double eps = 1; //* (1e4*ops_per_case);
+ for (int i = 0; i < test_cases; ++i)
+ {
+ string s = RandomNumberAsString(max_digits);
+ ParanoidNumber a(s);
+
+ double da(a.ToDouble());
+ for (int j = 1; j <= ops_per_case; ++j)
+ {
+ double da2(a.ToDouble());
+ s = RandomNumberAsString(max_digits);
+ ParanoidNumber b(s);
+ double db(b.ToDouble());
+
+
+
+ Optype op = Optype(rand() % 4);
+
+ ParanoidNumber a_before(a);
+
+
+ switch (op)
+ {
+ case ADD:
+ a += b;
+ da += db;
+ da2 += db;
+ break;
+ case SUBTRACT:
+ a -= b;
+ da -= db;
+ da2 -= db;
+ break;
+ case MULTIPLY:
+ a *= b;
+ da *= db;
+ da2 *= db;
+ break;
+ case DIVIDE:
+ if (db == 0)
+ {
+ --i;
+ }
+ else
+ {
+ a /= b;
+ da /= db;
+ da2 /= db;
+ }
+ break;
+ case NOP:
+ break;
+ }
+ if (!CloseEnough(da2, a, eps))
+ {
+ Error("{%s} %c= {%s}", a_before.Str().c_str(), OpChar(op), b.Str().c_str());
+ Error("{%s}", a.Str().c_str());
+ Error("double Yields: %.40lf", da);
+ Error("PN Yields: %.40lf", a.ToDouble());
+ Fatal("Failed on case %i", i*ops_per_case + j-1);
+ }
+ }
+ if (!CloseEnough(da, a, eps))
+ {
+ Warn("double Yields: %.40lf", da);
+ Warn("PN Yields: %.40lf", a.ToDouble());
+ }
+ if (i == test_cases - 1)
+ {
+ Debug("double: %.40lf", da);
+ Debug("PN: %.40lf", a.ToDouble());
+ }
+ }
+
+
}
#define TEST_CASES 1000
int main(int argc, char ** argv)
{
- srand(time(NULL));
+ TestAddSubIntegers(100);
+ TestMulDivIntegers(100);
+ for (int i = 1; i <= 100; ++i)
+ TestRandomisedOps(1000, i);
+ return 0;
+ srand(0);//time(NULL)); //always test off same set
string number(RandomNumberAsString());
ParanoidNumber a(number);
+
float fa = strtof(number.c_str(), NULL);
double da = strtod(number.c_str(), NULL);
double diff = 0;
long double lda = strtold(number.c_str(), NULL);
-
+ Debug("a is %s", a.Str().c_str());
if (fabs(a.ToDouble() - da) > 1e-6)
{
Error("double %lf, pn %lf {%s}", da, a.ToDouble(), a.Str().c_str());
Fatal("Didn't construct correctly off %s", number.c_str());
+
}
char opch[] = {'+','-','*','/'};
break;
}
diff = 100.0*(fabs(a.ToDouble() - da) / da);
- if (!CloseEnough(da, a))
+ if (!CloseEnough(lda, a))
{
Error("Op %i: ParanoidNumber probably doesn't work", i);
Error("Operation: %lf %c %lf", oldda, opch[op], db);
Error("As PN: %lf %c %lf", olda.ToDouble(), opch[op], b.ToDouble());
+ Error("PN String before: %s", olda.Str().c_str());
Error("PN String: %s", a.Str().c_str());
- Error("Diff is %.40lf", diff);
Error("LONG double gives %.40llf", lda);
- Fatal("%.40lf, expected aboout %.40lf", a.ToDouble(), da);
-
+ Error("%.40llf, expected aboout %.40llf", a.Convert<long double>(), lda);
+ a = da;
}
static double g_totalerror = 0;
-bool NotEqual(double a, double b, double threshold=1e-1)
+bool NotEqual(double a, double b, double threshold=1e-4)
{
double error = fabs(a-b);
g_totalerror += error;
int main(int argc, char ** argv)
{
srand(time(NULL));
+ DebugRealInfo();
unsigned failures = 0;
+ Real acumulate(0);
+ double dacumulate = 0;
for (unsigned i = 0; i < TEST_CASES; ++i)
{
//Debug("Test %u of %u", i, TEST_CASES);
{
failures++;
Warn("a /= b = %f should be %f, a before op was %f", Double(a), da, Double(abeforeop));
+ }
+ if (NotEqual(Double(a*0.0 + 1.0), da*0.0 + 1.0))
+ {
+ failures++;
+ Warn("a * 0 = %f should be %f, a before op was %f", Double(a), da, Double(abeforeop));
}
+
+ if (NotEqual(Double(a=b), da=db))
+ {
+ failures++;
+ Warn("a = b = %f should be %f, a before op was %f", Double(a), da, Double(abeforeop));
+ }
+
+ if (NotEqual(Double(-a), -da))
+ {
+ failures++;
+ Warn("-a = %f should be %f, a before op was %f", Double(-a), -da, Double(abeforeop));
+ }
+
+ if (NotEqual(Double(Sqrt(a)), Sqrt(da)))
+ {
+ failures++;
+ Warn("Sqrt(a) = %f should be %f, a before op was %f", Double(Sqrt(a)), Sqrt(da), Double(abeforeop));
+ }
+
+ if (NotEqual(Double(a), da))
+ {
+ failures++;
+ Warn("a = %f, should be %f, a before ops was %f", Double(a), da, Double(abeforeop));
+ }
+
+ switch (rand() % 4)
+ {
+ case 0:
+ acumulate += a;
+ dacumulate += da;
+ break;
+ case 1:
+ acumulate -= a;
+ dacumulate -= da;
+ break;
+ case 2:
+ acumulate *= a;
+ dacumulate *= da;
+ break;
+ case 3:
+ acumulate /= a;
+ dacumulate /= da;
+ break;
+ }
+ if (NotEqual(Double(acumulate), dacumulate))
+ {
+ Warn("Accumulated result %.30lf vs %.30lf is wrong", Double(acumulate), dacumulate);
+ failures++;
+ }
if (failures > old_failures)
{
Debug("\tStrings are a = %s, b = %s, aa = %s, bb = %s", a.Str().c_str(), b.Str().c_str(), aa.Str().c_str(), bb.Str().c_str());
#endif
}
+
}
- Debug("Completed %u test cases with total of %u operations, %u failures", TEST_CASES, 12*TEST_CASES, failures);
+ Debug("Completed %u test cases with total of %u operations, %u failures", TEST_CASES, 18*TEST_CASES, failures);
Debug("Total accumulated difference between Real and Double operations was %f", g_totalerror);
+ Debug("Real: %.40lf", Double(acumulate));
+ Debug("Doub: %.40lf", dacumulate);
+ Debug("Diff: %.40lf", Double(acumulate) - dacumulate);
}
--- /dev/null
+#include "stresstest.h"
+#include "real.h"
+#include "progressbar.h"
+
+using namespace std;
+using namespace IPDF;
+
+int main(int argc, char ** argv)
+{
+ Debug("Repeated Adds and Subtracts - Should give zero");
+
+ for (int i = 1; i < 100; ++i)
+ {
+ for (int j = 1; j < 100; ++j)
+ {
+ Real result = AddSub(0, i, Real(1)/Real(j));
+ if (result != Real(0))
+ Warn("Result of %lf != %lf (zero)", Double(result), 0.0);
+
+ printf("%d\t%lf\t%lf", i, Real(1)/Real(j), Double(result));
+ }
+ }
+
+ Debug("Repeated Multiplications and Divisions - Should give one");
+ for (int i = 1; i < 100; ++i)
+ {
+ for (int j = 1; j < 100; ++j)
+ {
+ Real result = MulDiv(1, i, Real(1)/Real(j));
+ if (result != Real(1))
+ Warn("Result of %lf != %lf (one)", Double(result), 1.0);
+
+ printf("%d\t%lf\t%lf", i, Real(1)/Real(j), Double(result));
+ }
+ }
+
+}
+
--- /dev/null
+#ifndef _REALOPS_H
+#define _REALOPS_H
+
+// Test real operations
+
+#include <cstdlib>
+
+/**
+ * Test adding and subtracting values in a range
+ * This is an identity; the result should be zero.
+ */
+template <class T>
+T AddSub(const T & start, const T & end, const T & delta = T(1))
+{
+ T result = 0;
+ for (T a = start; a < end; a += delta)
+ {
+ result += a;
+ for (T b = start; b < end; b += delta)
+ {
+ result -= b;
+ }
+ for (T b = start; b < end; b += delta)
+ {
+ result += b;
+ }
+ }
+ for (T a = start; a < end; a += delta)
+ {
+ result -= a;
+ for (T b = start; b < end; b += delta)
+ {
+ result += b;
+ }
+ for (T b = start; b < end; b += delta)
+ {
+ result -= b;
+ }
+ }
+ return result;
+}
+
+template <class T>
+T MulDiv(const T & start, const T & end, const T & delta = T(1))
+{
+ T result = 1;
+ for (T a = start; a < end; a += delta)
+ {
+ result *= a;
+ for (T b = start; b < end; b += delta)
+ {
+ result /= b;
+ }
+ for (T b = start; b < end; b += delta)
+ {
+ result *= b;
+ }
+ }
+ for (T a = start; a < end; a += delta)
+ {
+ result /= a;
+ for (T b = start; b < end; b += delta)
+ {
+ result *= b;
+ }
+ for (T b = start; b < end; b += delta)
+ {
+ result /= b;
+ }
+ }
+ return result;
+}
+
+
+
+template <class T>
+void RandomOp(T & a, int recurses=0, const T & max = 1e-6, const T & min = 1e-15)
+{
+ T b;
+ if (recurses > 0)
+ b = (min + (rand() % (int64_t)(max)));
+ else
+ b = RandomOps(recurses-1, max, min);
+ switch (rand() % 4)
+ {
+ case 0:
+ a += b;
+ break;
+ case 1:
+ a -= b;
+ break;
+ case 2:
+ a *= b;
+ break;
+ case 3:
+ a /= b;
+ break;
+ }
+}
+
+/**
+ * Test replying repeated operations randomly
+ */
+template <class T>
+T RandomOps(int ops, int recurses=0, const T & min = 1e-15 ,const T & max = 1e-6)
+{
+ T a = (min + (rand() % (int64_t)(max)));
+
+
+
+ for (int i = 0; i < ops; ++i)
+ {
+ RandomOp(a, recurses, min, max);
+ }
+ return a;
+}
+
+
+/**
+ * Test multiplying and dividing values in a range
+ * Such that the result is one
+ */
+template <class T>
+T RandomOp(const T & start, const T & end, const T & delta = T(1))
+{
+ T result = 1;
+ for (T a = start; a < end; a += delta)
+ {
+ result *= a;
+ for (T b = start; b < end; b += delta)
+ {
+ result /= b;
+ }
+ for (T b = start; b < end; b += delta)
+ {
+ result *= b;
+ }
+ }
+ for (T a = start; a < end; a += a)
+ {
+ result /= a;
+ for (T b = start; b < end; b += delta)
+ {
+ result *= b;
+ }
+ for (T b = start; b < end; b += delta)
+ {
+ result /= b;
+ }
+ }
+ return result;
+}
+
+
+#endif //_REALOPS_H
m_render_dirty(true), m_document(document), m_screen(screen), m_cached_display(), m_bounds(bounds), m_colour(colour), m_bounds_ubo(),
m_objbounds_vbo(), m_object_renderers(NUMBER_OF_OBJECT_TYPES), m_cpu_rendering_pixels(NULL),
m_perform_shading(USE_SHADING), m_show_bezier_bounds(false), m_show_bezier_type(false),
- m_show_fill_points(false), m_show_fill_bounds(false)
+ m_show_fill_points(false), m_show_fill_bounds(false), m_lazy_rendering(true)
{
Debug("View Created - Bounds => {%s}", m_bounds.Str().c_str());
screen.SetView(this); // oh dear...
+
+
// Create ObjectRenderers - new's match delete's in View::~View
//TODO: Don't forget to put new renderers here or things will be segfaultastic
- m_object_renderers[RECT_FILLED] = new RectFilledRenderer();
- m_object_renderers[RECT_OUTLINE] = new RectOutlineRenderer();
- m_object_renderers[CIRCLE_FILLED] = new CircleFilledRenderer();
- m_object_renderers[BEZIER] = new BezierRenderer();
- m_object_renderers[PATH] = new PathRenderer();
+ if (screen.Valid())
+ {
+ m_object_renderers[RECT_FILLED] = new RectFilledRenderer();
+ m_object_renderers[RECT_OUTLINE] = new RectOutlineRenderer();
+ m_object_renderers[CIRCLE_FILLED] = new CircleFilledRenderer();
+ m_object_renderers[BEZIER] = new BezierRenderer();
+ m_object_renderers[PATH] = new PathRenderer();
+ }
+ else
+ {
+ for (int i = RECT_FILLED; i <= PATH; ++i)
+ m_object_renderers[i] = new FakeRenderer();
+ }
// To add rendering for a new type of object;
// 1. Add enum to ObjectType in ipdf.h
*/
void View::Translate(Real x, Real y)
{
+ if (!m_use_gpu_transform)
+ m_buffer_dirty = true;
+ m_bounds_dirty = true;
+ #ifdef TRANSFORM_OBJECTS_NOT_VIEW
+ m_document.TranslateObjects(-x, -y);
+ #endif
x *= m_bounds.w;
y *= m_bounds.h;
m_bounds.x += x;
m_bounds.y += y;
//Debug("View Bounds => %s", m_bounds.Str().c_str());
- if (!m_use_gpu_transform)
- m_buffer_dirty = true;
- m_bounds_dirty = true;
+
+
}
/**
*/
void View::ScaleAroundPoint(Real x, Real y, Real scale_amount)
{
+
+ // (x0, y0, w, h) -> (x*w - (x*w - x0)*s, y*h - (y*h - y0)*s, w*s, h*s)
// x and y are coordinates in the window
// Convert to local coords.
+ if (!m_use_gpu_transform)
+ m_buffer_dirty = true;
+ m_bounds_dirty = true;
+
+
+ #ifdef TRANSFORM_OBJECTS_NOT_VIEW
+ m_document.ScaleObjectsAboutPoint(x, y, scale_amount);
+ #endif
x *= m_bounds.w;
y *= m_bounds.h;
x += m_bounds.x;
m_bounds.w *= scale_amount;
m_bounds.h *= scale_amount;
//Debug("Scale at {%s, %s} by %s View Bounds => %s", x.Str().c_str(), y.Str().c_str(), scale_amount.Str().c_str(), m_bounds.Str().c_str());
- if (!m_use_gpu_transform)
- m_buffer_dirty = true;
- m_bounds_dirty = true;
+
+
}
/**
*/
Rect View::TransformToViewCoords(const Rect& inp) const
{
+ #ifdef TRANSFORM_OBJECTS_NOT_VIEW
+ return inp;
+ #endif
Rect out;
out.x = (inp.x - m_bounds.x) / m_bounds.w;
out.y = (inp.y - m_bounds.y) / m_bounds.h;
*/
void View::Render(int width, int height)
{
+ if (!m_screen.Valid()) return;
glPushDebugGroup(GL_DEBUG_SOURCE_APPLICATION,42,-1, "Beginning View::Render()");
// View dimensions have changed (ie: Window was resized)
int prev_width = m_cached_display.GetWidth();
}
// View bounds have not changed; blit the FrameBuffer as it is
- if (!m_bounds_dirty)
+ if (!m_bounds_dirty && m_lazy_rendering)
{
m_cached_display.UnBind();
m_cached_display.Blit();
m_cached_display.Clear();
#ifndef QUADTREE_DISABLED
- if (m_bounds_dirty)
+ if (m_bounds_dirty || !m_lazy_rendering)
{
if ( (m_bounds.x > 1.0 || m_bounds.x < 0.0 || m_bounds.y > 1.0 || m_bounds.y < 0.0 || m_bounds.w > 1.0 || m_bounds.h > 1.0))
{
if (m_render_dirty) // document has changed
PrepareRender();
- if (m_buffer_dirty || m_bounds_dirty) // object bounds have changed
- UpdateObjBoundsVBO(first_obj, last_obj);
+ if (m_buffer_dirty || m_bounds_dirty || !m_lazy_rendering) // object bounds have changed
+ {
+ if (m_use_gpu_rendering)
+ UpdateObjBoundsVBO(first_obj, last_obj);
+ }
if (m_use_gpu_transform)
{
+ #ifdef TRANSFORM_OBJECTS_NOT_VIEW
+ GLfloat glbounds[] = {0.0f, 0.0f, 1.0f, 1.0f,
+ 0.0f, 0.0f, float(width), float(height)};
+ #else
GLfloat glbounds[] = {static_cast<GLfloat>(Float(m_bounds.x)), static_cast<GLfloat>(Float(m_bounds.y)), static_cast<GLfloat>(Float(m_bounds.w)), static_cast<GLfloat>(Float(m_bounds.h)),
0.0, 0.0, static_cast<GLfloat>(width), static_cast<GLfloat>(height)};
+ #endif
m_bounds_ubo.Upload(sizeof(float)*8, glbounds);
}
else
{
Debug("Recreate buffers with %u objects", m_document.ObjectCount());
// Prepare bounds vbo
- m_bounds_ubo.Invalidate();
- m_bounds_ubo.SetType(GraphicsBuffer::BufferTypeUniform);
- m_bounds_ubo.SetUsage(GraphicsBuffer::BufferUsageStreamDraw);
- m_bounds_ubo.SetName("m_bounds_ubo: Screen bounds.");
+ if (UsingGPURendering())
+ {
+ m_bounds_ubo.Invalidate();
+ m_bounds_ubo.SetType(GraphicsBuffer::BufferTypeUniform);
+ m_bounds_ubo.SetUsage(GraphicsBuffer::BufferUsageStreamDraw);
+ m_bounds_ubo.SetName("m_bounds_ubo: Screen bounds.");
+ }
// Instead of having each ObjectRenderer go through the whole document
// we initialise them, go through the document once adding to the appropriate Renderers
//Debug("Object of type %d", type);
}
+
// Finish the buffers
for (unsigned i = 0; i < m_object_renderers.size(); ++i)
{
m_object_renderers[i]->FinaliseBuffers();
}
- dynamic_cast<BezierRenderer*>(m_object_renderers[BEZIER])->PrepareBezierGPUBuffer(m_document.m_objects);
+ if (UsingGPURendering())
+ dynamic_cast<BezierRenderer*>(m_object_renderers[BEZIER])->PrepareBezierGPUBuffer(m_document.m_objects);
m_render_dirty = false;
}
+
+void View::SaveCPUBMP(const char * filename)
+{
+ bool prev = UsingGPURendering();
+ SetGPURendering(false);
+ Render(800, 600);
+ ObjectRenderer::SaveBMP({m_cpu_rendering_pixels, 800, 600}, filename);
+ SetGPURendering(prev);
+}
+
+void View::SaveGPUBMP(const char * filename)
+{
+ bool prev = UsingGPURendering();
+ SetGPURendering(true);
+ Render(800,600);
+ m_screen.ScreenShot(filename);
+ SetGPURendering(prev);
+}
#define USE_GPU_RENDERING true
#define USE_SHADING !(USE_GPU_RENDERING) && true
+#define TRANSFORM_OBJECTS_NOT_VIEW
+
namespace IPDF
{
class Screen;
const bool UsingGPURendering() const { return m_use_gpu_rendering; } // whether GPU shaders are used or CPU rendering
void ToggleGPUTransform() { m_use_gpu_transform = (!m_use_gpu_transform); m_bounds_dirty = true; m_buffer_dirty = true; }
void ToggleGPURendering() { m_use_gpu_rendering = (!m_use_gpu_rendering); m_bounds_dirty = true; m_buffer_dirty = true; }
+ void SetGPUTransform(bool state) {m_use_gpu_transform = state; m_bounds_dirty = true; m_buffer_dirty = true;}
void SetGPURendering(bool state) {m_use_gpu_rendering = state; m_bounds_dirty = true; m_buffer_dirty = true;}
void ForceBoundsDirty() {m_bounds_dirty = true;}
void ForceBufferDirty() {m_buffer_dirty = true;}
void ForceRenderDirty() {m_render_dirty = true;}
+
+ void SetLazyRendering(bool state = true) {m_lazy_rendering = state;}
+ bool UsingLazyRendering() const {return m_lazy_rendering;}
+
+ void SaveBMP(const char * filename) {if (UsingGPURendering()) SaveGPUBMP(filename); else SaveCPUBMP(filename);}
+
+ void SaveCPUBMP(const char * filename);
+ void SaveGPUBMP(const char * filename);
private:
struct GPUObjBounds
bool m_show_bezier_type;
bool m_show_fill_points;
bool m_show_fill_bounds;
+
+ bool m_lazy_rendering;// don't redraw frames unless we need to
#ifndef QUADTREE_DISABLED
--- /dev/null
+{
+ "metadata": {
+ "name": ""
+ },
+ "nbformat": 3,
+ "nbformat_minor": 0,
+ "worksheets": [
+ {
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Test the performance of numerical operations"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "%pylab inline"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "Populating the interactive namespace from numpy and matplotlib\n"
+ ]
+ }
+ ],
+ "prompt_number": 1
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "from common import *"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [],
+ "prompt_number": 14
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "for b in [\"single\", \"double\", \"GMPrat\", \"ParanoidNumber\"]:\n",
+ " os.system(\"make -C %s clean\" % options[\"ipdf_src\"])\n",
+ " os.system(\"make -C %s REALTYPE=%d tests/identitytests\" % (options[\"ipdf_src\"], options[\"real_names\"].index(b)))\n",
+ " os.system(\"mv %s/tests/identitytests %s/identity-%s\" % (options[\"ipdf_src\"], options[\"local_bin\"], b))\n",
+ " display(\"Built %s\" % b)"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "metadata": {},
+ "output_type": "display_data",
+ "text": [
+ "'Built single'"
+ ]
+ },
+ {
+ "metadata": {},
+ "output_type": "display_data",
+ "text": [
+ "'Built double'"
+ ]
+ },
+ {
+ "metadata": {},
+ "output_type": "display_data",
+ "text": [
+ "'Built GMPrat'"
+ ]
+ },
+ {
+ "metadata": {},
+ "output_type": "display_data",
+ "text": [
+ "'Built ParanoidNumber'"
+ ]
+ }
+ ],
+ "prompt_number": 26
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "def IdentityTest(real):\n",
+ " start = time.time()\n",
+ " display(\"%s starts at %d\" % (b, start))\n",
+ " p = subprocess.Popen(\"./identity-%s\" % real, bufsize=0, stdin=subprocess.PIPE, \\\n",
+ " stdout=subprocess.PIPE, stderr=subprocess.PIPE, shell=True)\n",
+ " p.wait()\n",
+ " display(\"%s completed, took %d\" % (real,time.time() - start))\n",
+ " "
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [],
+ "prompt_number": 30
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "import threading"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [],
+ "prompt_number": 31
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "for b in [\"single\", \"double\", \"GMPrat\", \"ParanoidNumber\"]:\n",
+ " threading.Thread(target=IdentityTest, args=(b,)).start()"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "metadata": {},
+ "output_type": "display_data",
+ "text": [
+ "'double starts at 1411243678'"
+ ]
+ },
+ {
+ "metadata": {},
+ "output_type": "display_data",
+ "text": [
+ "'GMPrat starts at 1411243678'"
+ ]
+ },
+ {
+ "metadata": {},
+ "output_type": "display_data",
+ "text": [
+ "'ParanoidNumber starts at 1411243678'"
+ ]
+ }
+ ],
+ "prompt_number": 33
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [],
+ "language": "python",
+ "metadata": {},
+ "outputs": []
+ }
+ ],
+ "metadata": {}
+ }
+ ]
+}
\ No newline at end of file
--- /dev/null
+{
+ "metadata": {
+ "name": ""
+ },
+ "nbformat": 3,
+ "nbformat_minor": 0,
+ "worksheets": [
+ {
+ "cells": [
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "%pylab inline"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "Populating the interactive namespace from numpy and matplotlib\n"
+ ]
+ }
+ ],
+ "prompt_number": 1
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "from common import *"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [],
+ "prompt_number": 2
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Compile programs\n",
+ "\n",
+ "Build for each type of real, then save a local copy of the executable."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "def build(real_type, quadtree=False, controlpanel=False):\n",
+ " global options\n",
+ " real_name = \"\"\n",
+ " if (type(real_type) == str):\n",
+ " quadtree = \"enabled\" if (real_type.split(\"-\")[-1] == \"qtree\") else quadtree\n",
+ " real_type = real_type.split(\"-\")[0]\n",
+ " real_name = real_type\n",
+ " real_type = options[\"real_names\"].index(real_type)\n",
+ " else:\n",
+ " real_name = options[\"real_names\"][real_type]\n",
+ " \n",
+ " quadtree = \"enabled\" if quadtree else \"disabled\"\n",
+ " controlpanel = \"enabled\" if controlpanel else \"disabled\"\n",
+ " if (os.system(\"make -C %s clean\" % options[\"ipdf_src\"]) != 0):\n",
+ " raise Exception(\"Make clean failed.\")\n",
+ " if (os.system(\"make -C %s REALTYPE=%d QUADTREE=%s CONTROLPANEL=%s\" % (options[\"ipdf_src\"], real_type, quadtree, controlpanel)) != 0):\n",
+ " raise Exception(\"Make failed.\")\n",
+ " \n",
+ " q = \"-qtree\" if quadtree == \"enabled\" else \"\"\n",
+ " os.rename(options[\"ipdf_bin\"], options[\"local_bin\"]+real_name+q)"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [],
+ "prompt_number": 4
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "p = ProgressBar(len(options[\"tobuild\"]))\n",
+ "p.animate(0)\n",
+ "for (i,b) in enumerate(options[\"tobuild\"]): #options[\"real_names\"]:\n",
+ " if b in options[\"ignore\"]:\n",
+ " continue\n",
+ " try:\n",
+ " build(b, False, False)\n",
+ " options[\"built\"] += [b]\n",
+ " #display(\"Built %s\" % b)\n",
+ " except:\n",
+ " display(\"Failed to build %s\" % b)\n",
+ " p.animate(i+1)\n"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "\r",
+ "[ 0% ]"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ " \r",
+ "[************* 33% ] 1 of 3 complete"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ " \r",
+ "[*****************67%***** ] 2 of 3 complete"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ " \r",
+ "[****************100%******************] 3 of 3 complete"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "\n"
+ ]
+ }
+ ],
+ "prompt_number": 5
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "options[\"built\"]"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "metadata": {},
+ "output_type": "pyout",
+ "prompt_number": 6,
+ "text": [
+ "['single', 'double', 'GMPrat']"
+ ]
+ }
+ ],
+ "prompt_number": 6
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Time to render frames\n",
+ "\n",
+ "Compare CPU and GPU frame rates for test image and fixed bounds"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "def time_vs_frames(exec_name, bounds = [0.,0.,1.,1.], min_frames=0, \\\n",
+ " max_frames=100, step=10,test_image=\"svg-tests/rabbit_simple.svg\"):\n",
+ " binname = options[\"local_bin\"]+exec_name\n",
+ " data = []\n",
+ " p = ProgressBar(sum(xrange(min_frames, max_frames, step)))\n",
+ " display(\"Time VS Frames for %s\" % exec_name)\n",
+ " p.animate(0)\n",
+ " i = 0\n",
+ " for frames in xrange(min_frames, max_frames+step, step):\n",
+ " pt = [frames]\n",
+ " # -l means to turn off lazy rendering\n",
+ " # -Q means don't show the window\n",
+ " cmd = binname + \" -l -Q -b %s %s %s %s -f %d %s\" % tuple(map(str, bounds) + [frames, test_image])\n",
+ " \n",
+ " # Everything on GPU\n",
+ " start = time.time()\n",
+ " os.system(cmd + \" -r gpu -T gpu\")\n",
+ " end = time.time()\n",
+ " pt += [(end - start)]\n",
+ " \n",
+ " # Everything on CPU\n",
+ " start = time.time()\n",
+ " os.system(cmd + \" -r cpu -T cpu\")\n",
+ " end = time.time()\n",
+ " pt += [(end - start)]\n",
+ " \n",
+ " data += [pt]\n",
+ " i += frames\n",
+ " p.animate(i)\n",
+ " \n",
+ " return asarray(data)"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [],
+ "prompt_number": 7
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "def plot_time_vs_frames(tf, new_figure=True):\n",
+ " if new_figure:\n",
+ " figure(figsize=(9,7))\n",
+ " yscale('linear')\n",
+ " xscale('linear')\n",
+ " legend([\"GPU\", \"CPU\"])\n",
+ " xlabel(\"Frames\")\n",
+ " ylabel(\"Time To Render\")\n",
+ " title(\"Quick, to the TARDIS of Infinite Precision!\") \n",
+ " \n",
+ " plot(tf[:,0], tf[:,1], 'o-')\n",
+ " plot(tf[:,0], tf[:,2], 'x-')\n",
+ " "
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [],
+ "prompt_number": 8
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "for p in options[\"built\"]:\n",
+ " plot_time_vs_frames(time_vs_frames(p, bounds=[0.5,0.5,1e-14,1e-14]), False)"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "metadata": {},
+ "output_type": "display_data",
+ "text": [
+ "'Time VS Frames for single'"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "\r",
+ "[ 0% ]"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ " \r",
+ "[ 0% ] 1 of 450 complete"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ " \r",
+ "[ 0% ] 1 of 450 complete"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ " \r",
+ "[* 2% ] 11 of 450 complete"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ " \r",
+ "[*** 7% ] 31 of 450 complete"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ " \r",
+ "[***** 14% ] 61 of 450 complete"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ " \r",
+ "[******** 22% ] 101 of 450 complete"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ " \r",
+ "[************* 34% ] 151 of 450 complete"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ " \r",
+ "[*****************47% ] 211 of 450 complete"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ " \r",
+ "[*****************62%**** ] 281 of 450 complete"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ " \r",
+ "[*****************80%********** ] 361 of 450 complete"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ " \r",
+ "[****************100%******************] 451 of 450 complete"
+ ]
+ },
+ {
+ "metadata": {},
+ "output_type": "display_data",
+ "text": [
+ "'Time VS Frames for double'"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ " \r",
+ "[ 0% ]"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ " \r",
+ "[ 0% ] 1 of 450 complete"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ " \r",
+ "[ 0% ] 1 of 450 complete"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ " \r",
+ "[* 2% ] 11 of 450 complete"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ " \r",
+ "[*** 7% ] 31 of 450 complete"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ " \r",
+ "[***** 14% ] 61 of 450 complete"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ " \r",
+ "[******** 22% ] 101 of 450 complete"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ " \r",
+ "[************* 34% ] 151 of 450 complete"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ " \r",
+ "[*****************47% ] 211 of 450 complete"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ " \r",
+ "[*****************62%**** ] 281 of 450 complete"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ " \r",
+ "[*****************80%********** ] 361 of 450 complete"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ " \r",
+ "[****************100%******************] 451 of 450 complete"
+ ]
+ },
+ {
+ "metadata": {},
+ "output_type": "display_data",
+ "text": [
+ "'Time VS Frames for GMPrat'"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ " \r",
+ "[ 0% ]"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ " \r",
+ "[ 0% ] 1 of 450 complete"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ " \r",
+ "[ 0% ] 1 of 450 complete"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ " \r",
+ "[* 2% ] 11 of 450 complete"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ " \r",
+ "[*** 7% ] 31 of 450 complete"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ " \r",
+ "[***** 14% ] 61 of 450 complete"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ " \r",
+ "[******** 22% ] 101 of 450 complete"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ " \r",
+ "[************* 34% ] 151 of 450 complete"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ " \r",
+ "[*****************47% ] 211 of 450 complete"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ " \r",
+ "[*****************62%**** ] 281 of 450 complete"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ " \r",
+ "[*****************80%********** ] 361 of 450 complete"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ " \r",
+ "[****************100%******************] 451 of 450 complete"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "\n"
+ ]
+ },
+ {
+ "metadata": {},
+ "output_type": "display_data",
+ "png": 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CnJwnUas3MnTom/j6Xtkr4VFZmXxs7vSBPnNBSGft2TOekJD/olBc3uY2aXV1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\nOSW7FwiaM81qw7IqVqen811mJkf698fexoaCkgIOXj9I9JV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+ "text": [
+ "<matplotlib.figure.Figure at 0x7f252628efd0>"
+ ]
+ }
+ ],
+ "prompt_number": 9
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Precision of rendering\n",
+ "\n",
+ "Compare images"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "def rgb2gray(rgb):\n",
+ " return np.dot(rgb[...,:3], [0.299/256., 0.587/256., 0.144/256.])"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [],
+ "prompt_number": 10
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "def bmpdiff(img1, img2):\n",
+ " p = subprocess.Popen(\"./bmpdiff %s %s\" % (img1, img2), bufsize=0, stdin=subprocess.PIPE, \\\n",
+ " stdout=subprocess.PIPE, stderr=subprocess.PIPE, shell=True)\n",
+ " out = p.stdout.readlines()\n",
+ " if len(out) != 1:\n",
+ " raise Exception(\"bmpdiff %s %s failed: %s \" % (img1, img2, str(map(lambda e : e.strip(\"\\n\"),p.stderr.readlines()))))\n",
+ " result = map(float, out[0].strip(\" \\r\\n\").split(\"\\t\"))\n",
+ " for i in xrange(len(result)):\n",
+ " if isnan(result[i]):\n",
+ " result[i] = 0\n",
+ " return result"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [],
+ "prompt_number": 11
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "def precision_vs_zoom(exec_name, xy, start_dims, end_dims, steps, test_image=\"svg-tests/rabbit_simple.svg\", show_outputs=False):\n",
+ " binname = options[\"local_bin\"]+exec_name\n",
+ " data = []\n",
+ " bounds = [xy[0], xy[1], start_dims[0], start_dims[1]]\n",
+ " dw = float(end_dims[0] - start_dims[0])/float(steps)\n",
+ " dh = float(end_dims[1] - start_dims[1])/float(steps)\n",
+ " p = ProgressBar(steps)\n",
+ " display(\"Precision vs Zoom of \\\"%s\\\" using %s\" % (test_image, exec_name))\n",
+ " p.animate(0)\n",
+ " im = None\n",
+ " figure(figsize=(10,10))\n",
+ " for i in xrange(steps+1):\n",
+ " \n",
+ " cmd = binname + \" -l -b %s %s %s %s %s\" % tuple(map(str, bounds) + [test_image])\n",
+ " \n",
+ " # Don't show the windows\n",
+ " os.system(cmd + \" -Q -r gpu -T gpu -o gpu%d.bmp\" % i)\n",
+ " os.system(cmd + \" -Q -r cpu -T cpu -o cpu%d.bmp\" % i)\n",
+ " \n",
+ " pt = [i]\n",
+ " pt += bounds\n",
+ " pt += [bmpdiff(\"gpu\"+str(i)+\".bmp\", \"gpu\"+str(max(i-1,0))+\".bmp\")[3]]\n",
+ " pt += [bmpdiff(\"gpu\"+str(i)+\".bmp\", \"gpu0.bmp\")[3]]\n",
+ " pt += [bmpdiff(\"cpu\"+str(i)+\".bmp\", \"cpu\"+str(max(i-1,0))+\".bmp\")[3]]\n",
+ " pt += [bmpdiff(\"cpu\"+str(i)+\".bmp\", \"cpu0.bmp\")[3]]\n",
+ " pt += [bmpdiff(\"cpu\"+str(i)+\".bmp\", \"gpu\"+str(i)+\".bmp\")[3]]\n",
+ "\n",
+ " if show_outputs != False:\n",
+ " clear_output()\n",
+ " if i == 0:\n",
+ " im = imshow(imread(\"cpu0.bmp\"), cmap=get_cmap(\"gray\"))\n",
+ " else:\n",
+ " im.set_data(imread(\"cpu\"+str(i)+\".bmp\"))\n",
+ " draw()\n",
+ " title(\"Bounds: %s\" % str(bounds))\n",
+ " \n",
+ " display(\"Precision vs Zoom of \\\"%s\\\" using %s\" % (test_image, exec_name))\n",
+ " p.animate(i)\n",
+ " \n",
+ " if show_outputs != False:\n",
+ " display(gcf()) \n",
+ " \n",
+ " \n",
+ " # [step, x, y, w, h, gpu_delta, gpu_total_delta, cpu_delta, cpu_total_delta, gpu_vs_cpu\n",
+ " data += [pt]\n",
+ " bounds[2] += dw\n",
+ " bounds[3] += dh\n",
+ "\n",
+ " \n",
+ " close(gcf())\n",
+ " return asarray(data)"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [],
+ "prompt_number": 12
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "pz = precision_vs_zoom(\"single\", [0.5,0.5],[1e-5,1e-5],[1e-6,1e-6], 100, \"svg-tests/fox-vector.svg\", show_outputs=True)"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "metadata": {},
+ "output_type": "display_data",
+ "text": [
+ "'Precision vs Zoom of \"svg-tests/fox-vector.svg\" using single'"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ " \r",
+ "[****************100%******************] 100 of 100 complete"
+ ]
+ },
+ {
+ "metadata": {},
+ "output_type": "display_data",
+ "png": 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11fz586s8xQgAAFCfVRu2BgwYUOmtG9auXVvh8oceekgPPfTQ+VUGAABQD3AH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\nxGGLiIiIyEVfAQcK06wQj5M7AAAAAElFTkSuQmCC\n",
+ "text": [
+ "<matplotlib.figure.Figure at 0x7f25259bf290>"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "\n"
+ ]
+ }
+ ],
+ "prompt_number": 13
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "pzd = precision_vs_zoom(\"double\", [0.5,0.5],[1e-13,1e-13],[1e-15,1e-15], 1, \"svg-tests/fox-vector.svg\", show_outputs=True)"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "metadata": {},
+ "output_type": "display_data",
+ "text": [
+ "'Precision vs Zoom of \"svg-tests/fox-vector.svg\" using double'"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ " \r",
+ "[****************100%******************] 1 of 1 complete"
+ ]
+ },
+ {
+ "metadata": {},
+ "output_type": "display_data",
+ "png": 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CFgAAgEOELQAAAIcIWwAAAA55zMzO+k49HgVgt0CDu+CCC07aVllZqdatW5/F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\nGjlypCTpyJEjGjNmjIYNG6Z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+ "text": [
+ "<matplotlib.figure.Figure at 0x7f2525984e50>"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "\n"
+ ]
+ }
+ ],
+ "prompt_number": 16
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "pzgmp = precision_vs_zoom(\"GMPrat\", [0.5,0.5],[1e-13,1e-13],[1e-15,1e-15], 1, \"svg-tests/fox-vector.svg\", show_outputs=True)\n",
+ "# Need to adapt mpfrc++ for required precision. Probably not worth it, just go back to mpfr?"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "metadata": {},
+ "output_type": "display_data",
+ "text": [
+ "'Precision vs Zoom of \"svg-tests/fox-vector.svg\" using GMPrat'"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ " \r",
+ "[****************100%******************] 1 of 1 complete"
+ ]
+ },
+ {
+ "metadata": {},
+ "output_type": "display_data",
+ "png": 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2PHjwAKampq9Vxv79+5Gbm4vt27djxYoV6NatWxG1juj9wZ4tIqJi6MyZM5g2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\n",
+ "text": [
+ "<matplotlib.figure.Figure at 0x7f25259b5450>"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "\n"
+ ]
+ }
+ ],
+ "prompt_number": 17
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "def plot_precision_vs_zoom(pz, gpu=True):\n",
+ " figure(figsize=(9,7))\n",
+ " if gpu:\n",
+ " plot(pz[:,3], pz[:,6], 'o-')\n",
+ " legend([\"GPU\", \"CPU\"])\n",
+ " \n",
+ " yscale('log')\n",
+ " xscale('log')\n",
+ " plot(pz[:,3], pz[:,8], 'o-')\n",
+ " xlabel(\"Width\")\n",
+ " ylabel(\"Average distance to closest pixel in original\")\n",
+ " title(\"Arr Captain We Be Sinking Into The Sea of Precision\")"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [],
+ "prompt_number": 454
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "plot_precision_vs_zoom(pz)"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "metadata": {},
+ "output_type": "display_data",
+ "png": 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MzJCUlISpU6fi8ccf10dsRERERFrROOQ0aNAgHD16FDKZDKmpqSplhsIhJyIi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\n",
+ "text": [
+ "<matplotlib.figure.Figure at 0x7f94baa28290>"
+ ]
+ }
+ ],
+ "prompt_number": 384
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "plot_precision_vs_zoom(pzd, False)"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "metadata": {},
+ "output_type": "display_data",
+ "png": 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HkgMAhYXSbsk//CCdfRXC71uT2rQJGDcOWL4ccHBIQmzsTuTnO0KlUuHEiR44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\nYQJHdoIAAAAASUVORK5CYII=\n",
+ "text": [
+ "<matplotlib.figure.Figure at 0x7f94bae39bd0>"
+ ]
+ }
+ ],
+ "prompt_number": 455
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [],
+ "language": "python",
+ "metadata": {},
+ "outputs": []
+ }
+ ],
+ "metadata": {}
+ }
+ ]
+}
\ No newline at end of file
--- /dev/null
+../src/tests/bmpdiff
\ No newline at end of file
--- /dev/null
+
+import sys
+import os
+import time
+import subprocess
+from progressbar import * # From ipython github site
+from IPython.core.display import Image
+from IPython.display import display, clear_output
+import threading
+
+options = {
+ "real_names" : ["single", "double", "long", "virtual", "Rational_GMPint", "Rational_Arbint", "mpfrc++", "iRRAM", "ParanoidNumber", "GMPrat"],
+ "ipdf_src" : "../src/",
+ "ipdf_bin" : "../bin/ipdf",
+ "local_bin" : "./",
+ "tests" : "../src/tests/",
+ "ignore" : ["virtual", "Rational_Arbint", "iRRAM", "ParanoidNumber"],
+ "tobuild" : ["single", "double", "GMPrat"],
+ "numerical_tests" : ["identitytests"],
+ "built" : []
+}
--- /dev/null
+../src/fonts/
\ No newline at end of file
--- /dev/null
+# From #http://nbviewer.ipython.org/github/ipython/ipython/blob/3607712653c66d63e0d7f13f073bde8c0f209ba8/docs/examples/notebooks/Animations_and_Progress.ipynb
+
+import sys, time
+try:
+ from IPython.display import clear_output
+ have_ipython = True
+except ImportError:
+ have_ipython = False
+
+class ProgressBar:
+ def __init__(self, iterations):
+ self.iterations = iterations
+ self.prog_bar = '[]'
+ self.fill_char = '*'
+ self.width = 40
+ self.__update_amount(0)
+ if have_ipython:
+ self.animate = self.animate_ipython
+ else:
+ self.animate = self.animate_noipython
+
+ def animate_ipython(self, iter):
+ print '\r', self,
+ sys.stdout.flush()
+ self.update_iteration(iter + 1)
+
+ def update_iteration(self, elapsed_iter):
+ self.__update_amount((elapsed_iter / float(self.iterations)) * 100.0)
+ self.prog_bar += ' %d of %s complete' % (elapsed_iter, self.iterations)
+
+ def __update_amount(self, new_amount):
+ percent_done = int(round((new_amount / 100.0) * 100.0))
+ all_full = self.width - 2
+ num_hashes = int(round((percent_done / 100.0) * all_full))
+ self.prog_bar = '[' + self.fill_char * num_hashes + ' ' * (all_full - num_hashes) + ']'
+ pct_place = (len(self.prog_bar) // 2) - len(str(percent_done))
+ pct_string = '%d%%' % percent_done
+ self.prog_bar = self.prog_bar[0:pct_place] + \
+ (pct_string + self.prog_bar[pct_place + len(pct_string):])
+
+ def __str__(self):
+ return str(self.prog_bar)
--- /dev/null
+../src/svg-tests/
\ No newline at end of file
git.ucc.asn.au / ipdf / code.git / commitdiff
UCC git Repository :: git.ucc.asn.au
