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uncertainty.c
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// Copyright (c) 2017-2023 California Institute of Technology ("Caltech"). U.S.
// Government sponsorship acknowledged. All rights reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
#include <cholmod.h>
#include <string.h>
#include <math.h>
#include <stdarg.h>
#include "mrcal.h"
#include "minimath/minimath-extra.h"
#include "util.h"
#include "strides.h"
#include "scales.h"
/*
Detailed docs appear in the docstring of
https://mrcal.secretsauce.net/uncertainty-cross-reprojection.html
The punchline:
Jcross_e = J_extrinsics d(compose_rt(rt_cam_ref,rt_ref_ref*)) /drt_ref_ref*
Jcross_f = J_frame d(compose_rt(rt_ref_ref*,rt_ref_frame))/drt_ref_ref*
Jcross_p = J_p d(transform(rt_ref_ref*,p )) /drt_ref_ref*
For each mesurement I pick one of these expressions.
We have rt_ref_ref* = K db for some K that depends on the various J matrices
that are constant for each solve:
K = -pinv(Jcross) J[frames,points,calobject_warp]
THIS function computes
Kpacked = K D
Let's explicate the matrices.
i e f p calobject_warp
| | | | |
V V V V V
[ 0 | 0 | J0_f0 | | J0_cw ]
[ 0 | 0 | J1_f0 | | J1_cw ]
[ 0 | 0 | J2_f0 | | J2_cw ]
[ 0 | 0 | J3_f1 | | J3_cw ]
[ 0 | 0 | J4_f1 | | J4_cw ]
[ 0 | 0 | J5_f1 | | J5_cw ]
J_fpcw = [ 0 | 0 | J6_f2 | | J6_cw ]
[ 0 | 0 | J7_f2 | | J7_cw ]
[ 0 | 0 | J8_f2 | | J8_cw ]
[ 0 | 0 | | J9_p0 | ]
[ 0 | 0 | | J10_p0 | ]
[ 0 | 0 | | J11_p1 | ]
And
[ J0_f0 drt_rf0__drt_rrp ]
[ J1_f0 drt_rf0__drt_rrp ]
[ .... ]
[ J3_f1 drt_rf1__drt_rrp ]
[ J4_f1 drt_rf1__drt_rrp ]
Jcross = [ .... ]
[ J6_e0 drt_cr0__drt_rrp ]
[ J7_e0 drt_cr0__drt_rrp ]
[ .... ]
[ J9_p0 dp0__drt_rrp ]
[ J10_p0 dp0__drt_rrp ]
[ .... ]
Here I used Jcross_e in measurement blocks 6,7 and Jcross_f for the rest.
Note: these all depend ONLY on rt_cam_ref and rt_ref_frame and p, which are
quantities we have. These do NOT depend on rt_ref_ref*.
Putting everything together, we have
rt_ref_ref* = K db
= -pinv(Jcross) J_fpcw db
= -pinv(Jcross) J_packedfpcw dbpacked
= Kpacked dbpacked
so
Kpacked = -inv(Jcross_t Jcross) Jcross_t J_packedfpcw
(6,6) (6, Nmeas_obs) (Nmeas_obs,Nstate)
Usually Nmeas_obs >> Nstate, so I start by computing Jcross_t J_packedfpcw
(shape (6,Nstate)). Its transpose, for convenience;
J_packedfpcw_t Jcross (shape=(Nstate,6)) =
[ 0 ] <- intrinsics
[ 0 ] <- extrinsics
[ J0_packedf0_t J0_packedf0 Dinv drt_rf0__drt_rrp ]
[ J1_packedf0_t J1_packedf0 Dinv drt_rf0__drt_rrp ]
[ ... ]
[ J3_packedf1_t J3_packedf1 Dinv drt_rf1__drt_rrp ]
[ J4_packedf1_t J4_packedf1 Dinv drt_rf1__drt_rrp ] <- frames
[ ... ]
[ J6_packedf2_t J0_packede0 Dinv drt_cr0__drt_rrp ]
[ J7_packedf2_t J1_packede0 Dinv drt_cr0__drt_rrp ]
[ ... ]
[ J9_packedp0_t J9_packedp0 Dinv dp0__drt_rrp ] <- points
[ J10_packedp0_t J10_packedp0 Dinv dp0__drt_rrp ]
[ ... ]
[ sum_i(Ji_cw_t Ji_packedfj Dinv drt_rfj__drt_rrp ) + ] <- calobject_warp
[ sum_i(Ji_cw_t Ji_packedej Dinv drt_crj__drt_rrp ) ]
Jcross_t Jcross = sum(outer(jcross, jcross))
= sum_i( drt_rfj__drt_rrp_t Ji_fj_t Ji_fj drt_rfj__drt_rrp ) +
sum_i( drt_crj__drt_rrp_t Ji_ej_t Ji_ej drt_crj__drt_rrp ) +
sum_i( dpj__drt_rrp_t Ji_fj_t Ji_fj dpj__drt_rrp )
For each frame, both of these expressions need
Ji.._t Ji Dinv D...__drt_rtp
I compute this in a loop, and accumulate in accumulate_frame() and
accumulate_point()
*/
static
void accumulate_frame(// output
// shape (6,6)
double* Jcross_t__Jpackedf, // THIS one frame, many measurements
const int Jcross_t__Jpackedf_stride0_elems,
// rows are assumed stored densely, so there is
// no Jcross_t__Jpackedf_stride1
// shape (6,2)
double* Jcross_t__Jpackedcw, // THIS one frame, many measurements
const int Jcross_t__Jpackedcw_stride0_elems,
// rows are assumed stored densely, so there is
// no Jcross_t__Jpackedcw_stride1
// shape (6,6)
double* Jcross_t__Jcross,
// input
// shape (6,6); symmetric, upper-triangle-only is stored
const double* sum_outer_jpackedf_jpackedf,
// shape (6,2)
const double* sum_outer_jpackedf_jpackedcw,
// shape (6,)
const double* rt_ref_frame_packed)
{
// sum_outer_jpackedf_jpackedf stores only the upper triangle, in the usual
// row-major order.
//
// Jcross_t__Jpackedf[:, iframe0:iframe+6] =
// drtrfp_drtrrp_t sum_outer_jpackedf_jpackedf /SCALE
//
// where drtrfp_drtrrp = d(compose_rt(rt_ref_ref*,rt_ref_frame)) / drt_ref_ref*
//
// Jcross_t Jcross = sum(outer(jcross, jcross))
// = sum_i( drtrfp_drtrrp_t[i]
// sum_outer_jpackedf_jpackedf
// drtrfp_drtrrp[i] ) /SCALE/SCALE
//
// Jcross has full state, but J_packed has packed state, so I need different
// number of SCALE factors.
//
// drtrfp_drtrrp = d(compose(rt0,rt1)/drt0) where rt0 is tiny. Derivation:
//
// R0 (R1 p + t1) + t0 = R0 R1 p + (R0 t1 + t0)
// -> R01 = R0 R1
// -> t01 = R0 t1 + t0
//
// At rt0 ~ identity we have:
// dt01/dr0 = d(R0 t1)/dr0
//
// rotate_point_r_core() says that
// const val_withgrad_t<N> cross[3] =
// {
// (rg[1]*x_ing[2] - rg[2]*x_ing[1])*sign,
// (rg[2]*x_ing[0] - rg[0]*x_ing[2])*sign,
// (rg[0]*x_ing[1] - rg[1]*x_ing[0])*sign
// };
// const val_withgrad_t<N> inner =
// rg[0]*x_ing[0] +
// rg[1]*x_ing[1] +
// rg[2]*x_ing[2];
// // Small rotation. I don't want to divide by 0, so I take the limit
// // lim(th->0, xrot) =
// // = x + cross(r, x) + r rt x lim(th->0, (1 - cos(th)) / (th*th))
// // = x + cross(r, x) + r rt x lim(th->0, sin(th) / (2*th))
// // = x + cross(r, x) + r rt x/2
// for(int i=0; i<3; i++)
// x_outg[i] =
// x_ing[i] +
// cross[i] +
// rg[i]*inner / 2.;
//
// So t01 = t0 + t1 + linear(r0) + quadratic(r0)
// r0 ~ 0 so I ignore the quadratic term:
// dt01/dr0 = d(cross(r0,t1))/dr0
// = -d(cross(t1,r0))/dr0
// = -d(skew_symmetric(t1) r0))/dr0
// = -skew_symmetric(t1)
// Thus
// drt01/drt0 = [ dr01/dr0 dr01/dt0 ] = [ dr01/dr0 0 ]
// [ dt01/dr0 dt01/dt0 ] = [ -skew_symmetric(t1) I ]
//
// In the above expressions I have drtrfp_drtrrp_t S for some matrix S. Expanded:
//
// drtrfp_drtrrp_t S = [dr/dr_t skew_t1] [ S00 S01 ] = [ dr/dr_t S00 + skew_t1 S10 dr/dr_t S01 + skew_t1 S11]
// [ 0 I ] [ S10 S11 ] [ S10 S11 ]
//
// In the case of the frames, each Sxx block has shape (3,3). For
// calobject_warp, S has shape (6,2) so I only have S00 and S10, each
// with shape (3,2)
double drrfp_drrrp[3*3];
const double r_ref_frame[3] =
{ rt_ref_frame_packed[0] * SCALE_ROTATION_FRAME,
rt_ref_frame_packed[1] * SCALE_ROTATION_FRAME,
rt_ref_frame_packed[2] * SCALE_ROTATION_FRAME };
mrcal_compose_r_tinyr0_gradientr0(drrfp_drrrp,
r_ref_frame);
// Jcross_t__Jpackedf output goes into [Af Bf]
// [Cf Df]
double* Af = &Jcross_t__Jpackedf[Jcross_t__Jpackedf_stride0_elems*0 + 0];
double* Bf = &Jcross_t__Jpackedf[Jcross_t__Jpackedf_stride0_elems*0 + 3];
double* Cf = &Jcross_t__Jpackedf[Jcross_t__Jpackedf_stride0_elems*3 + 0];
double* Df = &Jcross_t__Jpackedf[Jcross_t__Jpackedf_stride0_elems*3 + 3];
double* Acw = &Jcross_t__Jpackedcw[Jcross_t__Jpackedcw_stride0_elems*0];
double* Ccw = &Jcross_t__Jpackedcw[Jcross_t__Jpackedcw_stride0_elems*3];
// I can compute Jcross_t Jcross from the blocks comprising Jcross_t
// Jpackedfpcw. From above:
//
// Jcross_t Jcross ~
// ~ Jcross_t__Jpackedf Dinv drtrfp_drtrrp
//
// ~ [Af Bf] Dinv drtrfp_drtrrp
// [Cf Df]
//
// = [Af/SCALE_R Bf/SCALE_T] [dr/dr 0]
// [Cf/SCALE_R Df/SCALE_T] [ -skew(t1) I]
//
// = [Af/SCALE_R dr/dr - Bf/SCALE_T skew(t1) Bf/SCALE_T]
// [... Df/SCALE_T]
const double t0 = rt_ref_frame_packed[3+0] * SCALE_TRANSLATION_FRAME;
const double t1 = rt_ref_frame_packed[3+1] * SCALE_TRANSLATION_FRAME;
const double t2 = rt_ref_frame_packed[3+2] * SCALE_TRANSLATION_FRAME;
// Af <- dr/dr_t sum_outer[:3,:3] + skew_t1 sum_outer[3:,:3]
{
mul_gen33_gen33insym66(Af, Jcross_t__Jpackedf_stride0_elems, 1,
// transposed, so 1,3 and not 3,1
drrfp_drrrp, 1,3,
sum_outer_jpackedf_jpackedf, 0, 0,
1./SCALE_ROTATION_FRAME);
// and similar for calobject_warp
// Acw = drtrfp_drtrrp_t Dinv S; ~
// -> Acwt = St Dinv drtrfp_drtrrp;
mul_genNM_genML_accum(// transposed
Acw, 1, Jcross_t__Jpackedcw_stride0_elems,
2,3,3,
// transposed
&sum_outer_jpackedf_jpackedcw[0*2 + 0], 1,2,
drrfp_drrrp, 3,1,
1./SCALE_ROTATION_FRAME);
for(int j=0; j<3; j++)
{
int i;
i = 0;
Af[i*Jcross_t__Jpackedf_stride0_elems + j] +=
(
/*skew[i*3 + 0] + ( 0)*sum_outer_jpackedf_jpackedf[index_sym66(0+3,j)] */
/*skew[i*3 + 1]*/ + (-t2)*sum_outer_jpackedf_jpackedf[index_sym66(1+3,j)]
/*skew[i*3 + 2]*/ + ( t1)*sum_outer_jpackedf_jpackedf[index_sym66(2+3,j)]
) / SCALE_TRANSLATION_FRAME;
i = 1;
Af[i*Jcross_t__Jpackedf_stride0_elems + j] +=
(
/*skew[i*3 + 0]*/ + ( t2)*sum_outer_jpackedf_jpackedf[index_sym66(0+3,j)]
/*skew[i*3 + 1] + ( 0)*sum_outer_jpackedf_jpackedf[index_sym66(1+3,j)] */
/*skew[i*3 + 2]*/ + (-t0)*sum_outer_jpackedf_jpackedf[index_sym66(2+3,j)]
) / SCALE_TRANSLATION_FRAME;
i = 2;
Af[i*Jcross_t__Jpackedf_stride0_elems + j] +=
(
/*skew[i*3 + 0]*/ + (-t1)*sum_outer_jpackedf_jpackedf[index_sym66(0+3,j)]
/*skew[i*3 + 1]*/ + ( t0)*sum_outer_jpackedf_jpackedf[index_sym66(1+3,j)]
/*skew[i*3 + 2] + ( 0)*sum_outer_jpackedf_jpackedf[index_sym66(2+3,j)] */
) / SCALE_TRANSLATION_FRAME;
// and similar for calobject_warp
if(j<2)
{
i = 0;
Acw[i*Jcross_t__Jpackedcw_stride0_elems + j] +=
(
/*skew[i*3 + 0] + ( 0)*sum_outer_jpackedf_jpackedcw[(0+3)*2 + j] */
/*skew[i*3 + 1]*/ + (-t2)*sum_outer_jpackedf_jpackedcw[(1+3)*2 + j]
/*skew[i*3 + 2]*/ + ( t1)*sum_outer_jpackedf_jpackedcw[(2+3)*2 + j]
) / SCALE_TRANSLATION_FRAME;
i = 1;
Acw[i*Jcross_t__Jpackedcw_stride0_elems + j] +=
(
/*skew[i*3 + 0]*/ + ( t2)*sum_outer_jpackedf_jpackedcw[(0+3)*2 + j]
/*skew[i*3 + 1] + ( 0)*sum_outer_jpackedf_jpackedcw[(1+3)*2 + j] */
/*skew[i*3 + 2]*/ + (-t0)*sum_outer_jpackedf_jpackedcw[(2+3)*2 + j]
) / SCALE_TRANSLATION_FRAME;
i = 2;
Acw[i*Jcross_t__Jpackedcw_stride0_elems + j] +=
(
/*skew[i*3 + 0]*/ + (-t1)*sum_outer_jpackedf_jpackedcw[(0+3)*2 + j]
/*skew[i*3 + 1]*/ + ( t0)*sum_outer_jpackedf_jpackedcw[(1+3)*2 + j]
/*skew[i*3 + 2] + ( 0)*sum_outer_jpackedf_jpackedcw[(2+3)*2 + j] */
) / SCALE_TRANSLATION_FRAME;
}
}
}
// Bf <- dr/dr_t sum_outer[:3,3:] + skew_t1 sum_outer[3:,3:]
{
mul_gen33_gen33insym66(Bf, Jcross_t__Jpackedf_stride0_elems, 1,
// transposed, so 1,3 and not 3,1
drrfp_drrrp, 1,3,
sum_outer_jpackedf_jpackedf, 0, 3,
1./SCALE_ROTATION_FRAME);
for(int j=0; j<3; j++)
{
int i;
i = 0;
Bf[i*Jcross_t__Jpackedf_stride0_elems + j] +=
(
/*skew[i*3 + 0] + ( 0)*sum_outer_jpackedf_jpackedf[index_sym66(0+3,j+3)] */
/*skew[i*3 + 1]*/ + (-t2)*sum_outer_jpackedf_jpackedf[index_sym66(1+3,j+3)]
/*skew[i*3 + 2]*/ + ( t1)*sum_outer_jpackedf_jpackedf[index_sym66(2+3,j+3)]
) / SCALE_TRANSLATION_FRAME;
i = 1;
Bf[i*Jcross_t__Jpackedf_stride0_elems + j] +=
(
/*skew[i*3 + 0]*/ + ( t2)*sum_outer_jpackedf_jpackedf[index_sym66(0+3,j+3)]
/*skew[i*3 + 1] + ( 0)*sum_outer_jpackedf_jpackedf[index_sym66(1+3,j+3)] */
/*skew[i*3 + 2]*/ + (-t0)*sum_outer_jpackedf_jpackedf[index_sym66(2+3,j+3)]
) / SCALE_TRANSLATION_FRAME;
i = 2;
Bf[i*Jcross_t__Jpackedf_stride0_elems + j] +=
(
/*skew[i*3 + 0]*/ + (-t1)*sum_outer_jpackedf_jpackedf[index_sym66(0+3,j+3)]
/*skew[i*3 + 1]*/ + ( t0)*sum_outer_jpackedf_jpackedf[index_sym66(1+3,j+3)]
/*skew[i*3 + 2] + ( 0)*sum_outer_jpackedf_jpackedf[index_sym66(2+3,j+3)] */
) / SCALE_TRANSLATION_FRAME;
}
}
// Cf <- sum_outer[3:,:3]
{
set_gen33_from_gen33insym66(Cf, Jcross_t__Jpackedf_stride0_elems, 1,
sum_outer_jpackedf_jpackedf, 3, 0,
1./SCALE_TRANSLATION_FRAME);
// and similar for calobject_warp
for(int i=0; i<3; i++)
for(int j=0; j<2; j++)
Ccw[i*Jcross_t__Jpackedcw_stride0_elems + j] +=
sum_outer_jpackedf_jpackedcw[(3+i)*2 + j]/SCALE_TRANSLATION_FRAME;
}
// Df <- sum_outer[3:,3:]
{
set_gen33_from_gen33insym66(Df, Jcross_t__Jpackedf_stride0_elems, 1,
sum_outer_jpackedf_jpackedf, 3, 3,
1./SCALE_TRANSLATION_FRAME);
}
// Jcross_t__Jcross is symmetric, so I just compute the upper triangle,
// and I don't care about the ... block
// Jcross_t__Jcross[rr] <- Af/SCALE_R dr/dr - Bf/SCALE_T skew(t1)
{
mul_gen33_gen33_into33insym66_accum(Jcross_t__Jcross, 0, 0,
Af, Jcross_t__Jpackedf_stride0_elems, 1,
drrfp_drrrp, 3,1,
1./SCALE_ROTATION_FRAME);
int ivalue = 0;
for(int i=0; i<3; i++)
{
for(int j=i; j<3; j++, ivalue++)
{
if(j == 0)
Jcross_t__Jcross[ivalue] -=
(
/*skew[j + 0*3] + Bf[i*Jcross_t__Jpackedf_stride0_elems+0]*( 0) */
/*skew[j + 1*3]*/ + Bf[i*Jcross_t__Jpackedf_stride0_elems+1]*( t2)
/*skew[j + 2*3]*/ + Bf[i*Jcross_t__Jpackedf_stride0_elems+2]*(-t1)
) / SCALE_TRANSLATION_FRAME;
if(j == 1)
Jcross_t__Jcross[ivalue] -=
(
/*skew[j + 0*3]*/ + Bf[i*Jcross_t__Jpackedf_stride0_elems+0]*(-t2)
/*skew[j + 1*3] + Bf[i*Jcross_t__Jpackedf_stride0_elems+1]*( 0) */
/*skew[j + 2*3]*/ + Bf[i*Jcross_t__Jpackedf_stride0_elems+2]*( t0)
) / SCALE_TRANSLATION_FRAME;
if(j == 2)
Jcross_t__Jcross[ivalue] -=
(
/*skew[j + 0*3]*/ + Bf[i*Jcross_t__Jpackedf_stride0_elems+0]*( t1)
/*skew[j + 1*3]*/ + Bf[i*Jcross_t__Jpackedf_stride0_elems+1]*(-t0)
/*skew[j + 2*3] + Bf[i*Jcross_t__Jpackedf_stride0_elems+2]*( 0) */
) / SCALE_TRANSLATION_FRAME;
}
ivalue += 3;
}
}
// Jcross_t__Jcross[rt] <- Bf/SCALE_T
{
set_33insym66_from_gen33_accum(Jcross_t__Jcross, 0, 3,
Bf, Jcross_t__Jpackedf_stride0_elems, 1,
1./SCALE_TRANSLATION_FRAME);
}
// Jcross_t__Jcross[tr] doesn't need to be set: I only have values in
// the upper triangle
// Jcross_t__Jcross[tt] <- Df/SCALE_T = sum_outer[3:,3:]/SCALE_T/SCALE_T
{
const int N = (6+1)*6/2;
const int i0 = index_sym66_assume_upper(3,3);
for(int i=i0; i<N; i++)
Jcross_t__Jcross[i] +=
sum_outer_jpackedf_jpackedf[i] /
(SCALE_TRANSLATION_FRAME*SCALE_TRANSLATION_FRAME);
}
}
static
void accumulate_point(// output
// shape (6,3)
double* Jcross_t__Jpackedp, // THIS one point, many measurements
const int Jcross_t__Jpackedp_stride0_elems,
// rows are assumed stored densely, so there is
// no Jcross_t__Jpackedp_stride1
// shape (6,6)
double* Jcross_t__Jcross,
// input
// shape (3,3); symmetric, upper-triangle-only is stored
const double* sum_outer_jpackedp_jpackedp,
// shape (3,)
const double* ppacked)
{
// sum_outer_jpackedp_jpackedp stores only the upper triangle, in the usual
// row-major order.
//
// Jcross_t__Jpackedp[:, ipoint0:ipoint+3] =
// dpref_drrp_t sum_outer_jpackedp_jpackedp /SCALE
//
// where dpref_drrp = d(transform(rt_ref_ref*,p*)) / drt_ref_ref*
//
// Jcross_t Jcross = sum(outer(jcross, jcross))
// = sum_i( dpref_drrp_t[i]
// sum_outer_jpackedp_jpackedp
// dpref_drrp[i] ) /SCALE/SCALE
//
// Jcross has full state, but J_packed has packed state, so I need different
// number of SCALE factors.
//
// dpref_drrp = d(transform(rt_ref_ref*,p)/drt_ref_ref*) where drt_ref_ref*
// is tiny. Derivation using the Rodrigues rotation formula:
//
// rotate(r,p)
// ~ p cos(th) + cross(r/th,p) sin(th) + r/th inner(r/th,p) (1-cos(th))
// ~ p + cross(r,p) + r inner(r,p) / (th^2)*(1-cos(th))
// ~ p + cross(r,p) + r inner(r,p) / (th^2)*(1- (1-th^2))
// ~ p + cross(r,p) + r inner(r,p)
// ~ p + linear(r) + quadratic(r)
//
// I assume r is tiny so I only look at the linear term:
//
// d/dr = -skew_symmetric(p)
// d/dt = I
//
// In the above expressions I have dpref_drrp_t:
//
// dpref_drrp_t = [skew_p]
// [I ]
// Jcross_t__Jpackedp output goes into [A]
// [B]
//
// A = dpref_drrp_t[:3,:] sum_outer_jpackedp_jpackedp /SCALE
// B = dpref_drrp_t[3:,:] sum_outer_jpackedp_jpackedp /SCALE
//
// A = skew_p sum_outer_jpackedp_jpackedp /SCALE
// B = sum_outer_jpackedp_jpackedp /SCALE
double* A = &Jcross_t__Jpackedp[Jcross_t__Jpackedp_stride0_elems*0 + 0];
double* B = &Jcross_t__Jpackedp[Jcross_t__Jpackedp_stride0_elems*3 + 0];
// A <- skew_p sum_outer_jpackedp_jpackedp /SCALE
{
// p = ppacked * SCALE_POSITION_POINT,
// [ 0 -p2 p1]
// skew_p = [ p2 0 -p0]
// [-p1 p0 0]
for(int j=0; j<3; j++)
{
int i;
i = 0;
A[i*Jcross_t__Jpackedp_stride0_elems + j] +=
(
/*skew[i*3 + 0] + ( 0)*sum_outer_jpackedp_jpackedp[index_sym33(0,j)] */
/*skew[i*3 + 1]*/ + (-ppacked[2])*sum_outer_jpackedp_jpackedp[index_sym33(1,j)]
/*skew[i*3 + 2]*/ + ( ppacked[1])*sum_outer_jpackedp_jpackedp[index_sym33(2,j)]
);
i = 1;
A[i*Jcross_t__Jpackedp_stride0_elems + j] +=
(
/*skew[i*3 + 0]*/ + ( ppacked[2])*sum_outer_jpackedp_jpackedp[index_sym33(0,j)]
/*skew[i*3 + 1] + ( 0)*sum_outer_jpackedp_jpackedp[index_sym33(1,j)] */
/*skew[i*3 + 2]*/ + (-ppacked[0])*sum_outer_jpackedp_jpackedp[index_sym33(2,j)]
);
i = 2;
A[i*Jcross_t__Jpackedp_stride0_elems + j] +=
(
/*skew[i*3 + 0]*/ + (-ppacked[1])*sum_outer_jpackedp_jpackedp[index_sym33(0,j)]
/*skew[i*3 + 1]*/ + ( ppacked[0])*sum_outer_jpackedp_jpackedp[index_sym33(1,j)]
/*skew[i*3 + 2] + ( 0)*sum_outer_jpackedp_jpackedp[index_sym33(2,j)] */
);
}
}
// B <= sum_outer_jpackedp_jpackedp /SCALE
{
for(int j=0; j<3; j++)
for(int i=0; i<3; i++)
B[i*Jcross_t__Jpackedp_stride0_elems + j] +=
sum_outer_jpackedp_jpackedp[index_sym33(i,j)]
/ SCALE_POSITION_POINT;
}
// Jcross_t__Jcross is symmetric, so I just compute the upper triangle,
// and I don't care about the ... block
// Jcross_t__Jcross <- [A] [-skew_p I]
// [B]
// = [-A skew_p A]
// [-B skew_p B]
// Jcross_t__Jcross[00] <- -A skew_p / SCALE
{
int ivalue = 0;
for(int i=0; i<3; i++)
{
for(int j=i; j<3; j++, ivalue++)
{
if(j == 0)
Jcross_t__Jcross[ivalue] -=
(
/*skew[j + 0*3] + A[i*Jcross_t__Jpackedp_stride0_elems+0]*( 0) */
/*skew[j + 1*3]*/ + A[i*Jcross_t__Jpackedp_stride0_elems+1]*( ppacked[2])
/*skew[j + 2*3]*/ + A[i*Jcross_t__Jpackedp_stride0_elems+2]*(-ppacked[1])
);
if(j == 1)
Jcross_t__Jcross[ivalue] -=
(
/*skew[j + 0*3]*/ + A[i*Jcross_t__Jpackedp_stride0_elems+0]*(-ppacked[2])
/*skew[j + 1*3] + A[i*Jcross_t__Jpackedp_stride0_elems+1]*( 0) */
/*skew[j + 2*3]*/ + A[i*Jcross_t__Jpackedp_stride0_elems+2]*( ppacked[0])
);
if(j == 2)
Jcross_t__Jcross[ivalue] -=
(
/*skew[j + 0*3]*/ + A[i*Jcross_t__Jpackedp_stride0_elems+0]*( ppacked[1])
/*skew[j + 1*3]*/ + A[i*Jcross_t__Jpackedp_stride0_elems+1]*(-ppacked[0])
/*skew[j + 2*3] + A[i*Jcross_t__Jpackedp_stride0_elems+2]*( 0) */
);
}
ivalue += 3;
}
}
// Jcross_t__Jcross[01] <- A/SCALE
{
set_33insym66_from_gen33_accum(Jcross_t__Jcross, 0, 3,
A, Jcross_t__Jpackedp_stride0_elems, 1,
1./SCALE_POSITION_POINT);
}
// Jcross_t__Jcross[10] doesn't need to be set: I only have values in
// the upper triangle
// Jcross_t__Jcross[11] <- B / SCALE
{
const int N = (6+1)*6/2;
const int i0 = index_sym66_assume_upper(3,3);
for(int i=i0; i<N; i++)
Jcross_t__Jcross[i] +=
sum_outer_jpackedp_jpackedp[i-i0] /
(SCALE_POSITION_POINT*SCALE_POSITION_POINT);
}
}
// LAPACK prototypes for a packed cholesky factorization and a linear solve
// using that factorization, respectively
int dpptrf_(char* uplo, int* n, double* ap,
int* info, int uplo_len);
int dpptrs_(char* uplo, int* n, int* nrhs,
double* ap, double* b, int* ldb, int* info,
int uplo_len);
bool mrcal_drt_ref_refperturbed__dbpacked(// output
// Shape (6,Nstate_frames)
double* Kpackedf,
int Kpackedf_stride0, // in bytes. <= 0 means "contiguous"
int Kpackedf_stride1, // in bytes. <= 0 means "contiguous"
// Shape (6,Nstate_points)
double* Kpackedp,
int Kpackedp_stride0, // in bytes. <= 0 means "contiguous"
int Kpackedp_stride1, // in bytes. <= 0 means "contiguous"
// Shape (6,Nstate_calobject_warp)
double* Kpackedcw,
int Kpackedcw_stride0, // in bytes. <= 0 means "contiguous"
int Kpackedcw_stride1, // in bytes. <= 0 means "contiguous"
// inputs
// stuff that describes this solve
const double* b_packed,
// used only to confirm that the user passed-in the buffer they
// should have passed-in. The size must match exactly
int buffer_size_b_packed,
// The unitless (packed) Jacobian,
// used by the internal optimization
// routines cholmod_analyze() and
// cholmod_factorize() require
// non-const
/* const */
cholmod_sparse* Jt,
// meta-parameters
int Ncameras_intrinsics, int Ncameras_extrinsics, int Nframes,
int Npoints, int Npoints_fixed, // at the end of points[]
int Nobservations_board,
int Nobservations_point,
const mrcal_lensmodel_t* lensmodel,
mrcal_problem_selections_t problem_selections,
int calibration_object_width_n,
int calibration_object_height_n)
{
const int Nmeas_boards =
mrcal_num_measurements_boards(Nobservations_board,
calibration_object_width_n,
calibration_object_height_n);
const int Nmeas_points =
mrcal_num_measurements_points(Nobservations_point);
const int Nmeas_obs = Nmeas_boards + Nmeas_points;
const int state_index_frame0 =
mrcal_state_index_frames(0,
Ncameras_intrinsics, Ncameras_extrinsics,
Nframes,
Npoints, Npoints_fixed, Nobservations_board,
problem_selections,
lensmodel);
const int state_index_point0 =
mrcal_state_index_points(0,
Ncameras_intrinsics, Ncameras_extrinsics,
Nframes,
Npoints, Npoints_fixed, Nobservations_board,
problem_selections,
lensmodel);
const int state_index_calobject_warp0 =
mrcal_state_index_calobject_warp(Ncameras_intrinsics, Ncameras_extrinsics,
Nframes,
Npoints, Npoints_fixed, Nobservations_board,
problem_selections,
lensmodel);
const int Nstate =
mrcal_num_states(Ncameras_intrinsics, Ncameras_extrinsics,
Nframes,
Npoints, Npoints_fixed, Nobservations_board,
problem_selections,
lensmodel);
const int Nstate_intrinsics =
mrcal_num_states_intrinsics(Ncameras_intrinsics,
problem_selections,
lensmodel);
const int Nstate_extrinsics =
mrcal_num_states_extrinsics(Ncameras_extrinsics,
problem_selections);
const int Nstate_frames =
mrcal_num_states_frames(Nframes,
problem_selections);
const int Nstate_points =
mrcal_num_states_points(Npoints,Npoints_fixed,
problem_selections);
const int Nstate_calobject_warp =
mrcal_num_states_calobject_warp(problem_selections,
Nobservations_board);
#warning check all Nstate_ and state_index_ references; some of those could be invalid (if some variables are locked for instance). Figure out what makes sense and what we should BARF() against
#warning Do I need this? Where do I assume it?
if(state_index_frame0 >= 0 &&
state_index_calobject_warp0 >= 0 &&
!(state_index_calobject_warp0 == state_index_frame0 + Nstate_frames))
{
MSG("I assume that the calobject_warp state variables follow the frame state variables immediately");
return false;
}
#warning Do I need this? Where do I assume it?
if(state_index_calobject_warp0 >= 0 &&
!(Nstate_calobject_warp == 2))
{
MSG("I assume that the calobject_warp has exactly 2 state variables");
return false;
}
if( buffer_size_b_packed != Nstate*(int)sizeof(double) )
{
MSG("The buffer b_packed has the wrong size. Needed exactly %d bytes, but got %d bytes",
Nstate*(int)sizeof(double),buffer_size_b_packed);
return false;
}
if(Nstate != (int)Jt->nrow)
{
MSG("Inconsistent inputs. I have Nstate=%d, but Jt->nrow=%d. Giving up",
Nstate, (int)Jt->nrow);
return false;
}
if(state_index_frame0 < 0 &&
state_index_point0 < 0)
{
MSG("Neither board poses nor points are being optimized. Cannot compute uncertainty if we're not optimizing any observations");
return false;
}
#define INIT_ARRAY(Kpacked, N) \
init_stride_2D(Kpacked, 6, N); \
const int Kpacked ## _stride0_elems = Kpacked ## _stride0 / sizeof(double); \
if(Kpacked != NULL) \
{ \
if(Kpacked ## _stride0_elems*(int)sizeof(double) != Kpacked ## _stride0) \
{ \
MSG("Currently the implementation assumes that " #Kpacked "_stride0 is a multiple of sizeof(double): all elements of Kpacked are aligned. Got Kpacked ## _stride0 = %d", \
Kpacked ## _stride0); \
return false; \
} \
\
if(Kpacked ## _stride1 == sizeof(double)) \
{ \
/* each row is stored densely */ \
if(Kpacked ## _stride0 == (int)sizeof(double)*N) \
/* each column is stored densely as well. I can memset() the whole */ \
/* block of memory */ \
memset(Kpacked, 0, 6*N*sizeof(double)); \
else \
for(int i=0; i<6; i++) \
memset(&Kpacked[i*Kpacked ## _stride0_elems], 0, N*sizeof(double)); \
} \
else \
{ \
MSG("Currently the implementation assumes that Kpacked has densely-stored rows: " #Kpacked "_stride1 must be sizeof(double). Instead I got Kpacked ## _stride1 = %d", \
Kpacked ## _stride1); \
return false; \
} \
}
INIT_ARRAY(Kpackedf, Nstate_frames);
INIT_ARRAY(Kpackedp, Nstate_points);
INIT_ARRAY(Kpackedcw, Nstate_calobject_warp);
// sum(outer(dx/drt_ref_frame,dx/drt_ref_frame)) for this frame. I sum over
// all the observations. Uses PACKED gradients. Only the upper triangle is
// stored, in the usual row-major order
double sum_outer_jpackedf_jpackedf[(6+1)*6/2] = {};
// sum(outer(dx/dpoint,dx/dpoint)) for this point. I sum over all the
// observations. Uses PACKED gradients. Only the upper triangle is stored,
// in the usual row-major order
double sum_outer_jpackedp_jpackedp[(3+1)*3/2] = {};
// sum(outer(j_frame_measi*, j_calobject_warp_measi*)) for this frame. Uses
// PACKED gradients. Stored densely, since it isn't symmetric. Shape (6,2)
double sum_outer_jpackedf_jpackedcw[6*2] = {};
double Jcross_t__Jcross[(6+1)*6/2] = {};
int state_index_frame_current = -1;
int state_index_point_current = -1;
const int* Jrowptr = (int*) Jt->p;
const int* Jcolidx = (int*) Jt->i;
const double* Jval = (double*)Jt->x;
for(int imeas=0; imeas<Nmeas_obs; imeas++)
{
int32_t ival = Jrowptr[imeas];
int32_t icol;
#warning linear search
// I look through the jacobian until I find either a frame or a point
// gradient. This is an inefficient linear search.
while(ival < Jrowptr[imeas+1])
{
icol = Jcolidx[ival];
if( state_index_frame0 >= 0 && state_index_frame0 <= icol)
break;
if( state_index_point0 >= 0 && state_index_point0 <= icol)
break;
ival++;
}
if(!(ival < Jrowptr[imeas+1]))
continue;
// if(frame gradient). If these don't exist in this problem,
// Nstate_frames==0, and this will always be false
if( state_index_frame0 <= icol &&
icol < state_index_frame0 + Nstate_frames )
{
// This observation is of chessboards
// We're looking at SOME rt_ref_frame gradient. I expect 6 values
// for the rt_ref_frame gradient followed by 2 values for the
// calobject_warp gradient
//
// Consecutive chunks of Nw*Nh*2 measurements will represent the
// same board pose, and the same rt_ref_frame
if(icol < state_index_frame_current)
{
MSG("Unexpected jacobian structure. I'm assuming non-decreasing frame references. The Jcross_t__Jcross computation uses chunks of Kpackedf; it assumes that once the chunk is computed, it is DONE, and never revisited. Non-monotonic frame indices break that");
return false;
}
if(state_index_frame_current >= 0 &&
icol != state_index_frame_current)
{
// Looking at a new frame. Finish the previous frame
accumulate_frame( // output
&Kpackedf[state_index_frame_current-state_index_frame0],
Kpackedf_stride0_elems,
Kpackedcw,
Kpackedcw_stride0_elems,
Jcross_t__Jcross,
// input
sum_outer_jpackedf_jpackedf,
sum_outer_jpackedf_jpackedcw,
&b_packed[state_index_frame_current]);
memset(sum_outer_jpackedf_jpackedf, 0, (6+1)*6/2*sizeof(double));
memset(sum_outer_jpackedf_jpackedcw, 0, 6*2 *sizeof(double));
}
state_index_frame_current = icol;
// I have dx/drt_ref_frame for this frame. This is 6 numbers
const double* dx_drt_ref_frame_packed = &Jval[ival];
// sum(outer(dx/drt_ref_frame,dx/drt_ref_frame)) into sum_outer_jpackedf_jpackedf
// This is used to compute Jcross_t J_packedfpcw and Jcross_t
// Jcross. This result is used in accumulate_frame()
//
// Uses PACKED gradients. Only the upper triangle is stored, in
// the usual row-major order
for(int i=0, ivalue=0; i<6; i++)
for(int j=i; j<6; j++, ivalue++)
sum_outer_jpackedf_jpackedf[ivalue] +=
dx_drt_ref_frame_packed[i]*dx_drt_ref_frame_packed[j];
// I just looked at all the frame gradients. Fast-forward past
// them all
ival += 6;
if(!(ival < Jrowptr[imeas+1]))
{
// No more gradients for this measurement. There is no
// calobject_warp
if(Kpackedcw != NULL)
{
MSG("Unexpected jacobian structure. There's no calobject_warp gradient in measurement %d, but the user asked for it",
imeas);
return false;
}
continue; // next measurement
}
icol = Jcolidx[ival];
if(!(icol >= state_index_calobject_warp0 &&
icol < state_index_calobject_warp0 + Nstate_calobject_warp) )
{
MSG("Unexpected jacobian structure. I'm assuming frame jacobians to be followed immediately by calobject_warp jacobians");
return false;
}
// calobject_warp
if(Kpackedcw == NULL)
{
MSG("Unexpected jacobian structure. There's a calobject_warp gradient in measurement %d, but the user didn't ask for it",
imeas);
return false;
}
const double* dx_dcalobject_warp_packed = &Jval[ival];
// Similar to the above, but this isn't symmetric, so I store it
// densely
int ivalue = 0;
for(int i=0; i<6; i++)
for(int j=0; j<2; j++, ivalue++)
sum_outer_jpackedf_jpackedcw[ivalue] +=
dx_drt_ref_frame_packed[i]*
dx_dcalobject_warp_packed[j];
// I just looked at all the calobject_warp gradients.
// Fast-forward past them all
ival += Nstate_calobject_warp;
if(ival < Jrowptr[imeas+1])
{
MSG("Unexpected jacobian structure. The calobject_warp jacobians should be the last gradient for each measurement");
return false;
}
}
// if(point gradient). If these don't exist in this problem,
// Nstate_points==0, and this will always be false
if( state_index_point0 <= icol &&
icol < state_index_point0 + Nstate_points )
{
// This observation is of a point
// We're looking at SOME point gradient: 3 values
if(icol < state_index_point_current)
{
MSG("Unexpected jacobian structure. I'm assuming non-decreasing point references. The Jcross_t__Jcross computation uses chunks of Kpackedp; it assumes that once the chunk is computed, it is DONE, and never revisited. Non-monotonic point indices break that");
return false;
}
if(state_index_point_current >= 0 &&
icol != state_index_point_current)
{
// Looking at a new point. Finish the previous point
accumulate_point( // output
&Kpackedp[state_index_point_current-state_index_point0],
Kpackedp_stride0_elems,
Jcross_t__Jcross,
// input
sum_outer_jpackedp_jpackedp,
&b_packed[state_index_point_current]);
memset(sum_outer_jpackedp_jpackedp, 0, (3+1)*3/2*sizeof(double));
}
state_index_point_current = icol;