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#!/usr/bin/python3
# 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
r'''Python-wrap the triangulation routines
'''
import sys
import os
import numpy as np
import numpysane as nps
import numpysane_pywrap as npsp
docstring_module = '''Internal triangulation routines
This is the written-in-C Python extension module that underlies the
triangulation routines. The user-facing functions are available in
mrcal.triangulation module in mrcal/triangulation.py
All functions are exported into the mrcal module. So you can call these via
mrcal._triangulation_npsp.fff() or mrcal.fff(). The latter is preferred.
'''
m = npsp.module( name = "_triangulation_npsp",
docstring = docstring_module,
header = r'''
#include "mrcal.h"
''')
# All the triangulation routines except Lindstrom have an identical structure.
# Lindstrom is slightly different: it takes LOCAL v1 instead of a cam0-coords v1
NAME = "_triangulate_{WHAT}"
DOCS = r"""Internal {LONGNAME} triangulation routine
This is the internals for mrcal.triangulate_{WHAT}(get_gradients = False). As a
user, please call THAT function, and see the docs for that function. The
differences:
- This is just the no-gradients function. The internal function that returns
gradients is _triangulate_{WHAT}_withgrad
A higher-level function mrcal.triangulate() is also available for higher-level
analysis.
"""
DOCS_WITHGRAD = r"""Internal {LONGNAME} triangulation routine (with gradients)
This is the internals for mrcal.triangulate_{WHAT}(get_gradients = True). As a
user, please call THAT function, and see the docs for that function. The
differences:
- This is just the gradients-returning function. The internal function that
skips those is _triangulate_{WHAT}
A higher-level function mrcal.triangulate() is also available for higher-level
analysis.
"""
BODY_SLICE = r'''
const mrcal_point3_t* v0 = (const mrcal_point3_t*)data_slice__v0;
const mrcal_point3_t* v1 = (const mrcal_point3_t*)data_slice__v1;
const mrcal_point3_t* t01 = (const mrcal_point3_t*)data_slice__t01;
*(mrcal_point3_t*)data_slice__output =
mrcal_triangulate_{WHAT}(NULL, NULL, NULL,
v0, v1, t01);
return true;
'''
BODY_SLICE_WITHGRAD = r'''
const mrcal_point3_t* v0 = (const mrcal_point3_t*)data_slice__v0;
const mrcal_point3_t* v1 = (const mrcal_point3_t*)data_slice__v1;
const mrcal_point3_t* t01 = (const mrcal_point3_t*)data_slice__t01;
mrcal_point3_t* dm_dv0 = (mrcal_point3_t*)data_slice__output1;
mrcal_point3_t* dm_dv1 = (mrcal_point3_t*)data_slice__output2;
mrcal_point3_t* dm_dt01 = (mrcal_point3_t*)data_slice__output3;
*(mrcal_point3_t*)data_slice__output0 =
mrcal_triangulate_{WHAT}( dm_dv0, dm_dv1, dm_dt01,
v0, v1, t01);
return true;
'''
common_kwargs = dict( args_input = ('v0', 'v1', 't01'),
prototype_input = ((3,), (3,), (3,)),
prototype_output = (3,),
Ccode_validate = r'''
return CHECK_CONTIGUOUS_AND_SETERROR_ALL();''' )
common_kwargs_withgrad = dict( args_input = ('v0', 'v1', 't01'),
prototype_input = ((3,), (3,), (3,)),
prototype_output = ((3,), (3,3), (3,3), (3,3)),
Ccode_validate = r'''
return CHECK_CONTIGUOUS_AND_SETERROR_ALL();''')
for WHAT,LONGNAME in (('geometric', 'geometric'),
('leecivera_l1', 'Lee-Civera L1'),
('leecivera_linf', 'Lee-Civera L-infinity'),
('leecivera_mid2', 'Lee-Civera Mid2'),
('leecivera_wmid2', 'Lee-Civera wMid2')):
m.function( NAME.format(WHAT = WHAT),
DOCS.format(WHAT = WHAT,
LONGNAME = LONGNAME),
Ccode_slice_eval = { (np.float64,np.float64,np.float64,
np.float64):
BODY_SLICE.format(WHAT = WHAT) },
**common_kwargs
)
m.function( NAME.format( WHAT = WHAT) + "_withgrad",
DOCS_WITHGRAD.format(WHAT = WHAT,
LONGNAME = LONGNAME),
Ccode_slice_eval = { (np.float64,np.float64,np.float64,
np.float64,np.float64,np.float64,np.float64):
BODY_SLICE_WITHGRAD.format(WHAT = WHAT) },
**common_kwargs_withgrad
)
# Lindstrom's triangulation. Takes a local v1, so the arguments are a bit
# different
m.function( "_triangulate_lindstrom",
f"""Internal lindstrom's triangulation routine
This is the internals for mrcal.triangulate_lindstrom(). As a user, please call
THAT function, and see the docs for that function. The differences:
- This is just the no-gradients function. The internal function that returns
gradients is _triangulate_lindstrom_withgrad
""",
args_input = ('v0_local', 'v1_local', 'Rt01'),
prototype_input = ((3,), (3,), (4,3),),
prototype_output = ((3,) ),
Ccode_validate = r'''
return CHECK_CONTIGUOUS_AND_SETERROR_ALL();''',
Ccode_slice_eval = { (np.float64,np.float64,np.float64,
np.float64):
r'''
const mrcal_point3_t* v0 = (const mrcal_point3_t*)data_slice__v0_local;
const mrcal_point3_t* v1 = (const mrcal_point3_t*)data_slice__v1_local;
const mrcal_point3_t* Rt01= (const mrcal_point3_t*)data_slice__Rt01;
*(mrcal_point3_t*)data_slice__output =
mrcal_triangulate_lindstrom(NULL,NULL,NULL,
v0, v1, Rt01);
return true;
'''},
)
m.function( "_triangulate_lindstrom_withgrad",
f"""Internal lindstrom's triangulation routine
This is the internals for mrcal.triangulate_lindstrom(). As a user, please call
THAT function, and see the docs for that function. The differences:
- This is just the gradient-returning function. The internal function that skips those
is _triangulate_lindstrom
""",
args_input = ('v0_local', 'v1_local', 'Rt01'),
prototype_input = ((3,), (3,), (4,3),),
prototype_output = ((3,), (3,3), (3,3), (3,4,3) ),
Ccode_validate = r'''
return CHECK_CONTIGUOUS_AND_SETERROR_ALL();''',
Ccode_slice_eval = { (np.float64,np.float64,np.float64,
np.float64,np.float64,np.float64,np.float64):
r'''
const mrcal_point3_t* v0 = (const mrcal_point3_t*)data_slice__v0_local;
const mrcal_point3_t* v1 = (const mrcal_point3_t*)data_slice__v1_local;
const mrcal_point3_t* Rt01= (const mrcal_point3_t*)data_slice__Rt01;
mrcal_point3_t* dm_dv0 = (mrcal_point3_t*)data_slice__output1;
mrcal_point3_t* dm_dv1 = (mrcal_point3_t*)data_slice__output2;
mrcal_point3_t* dm_dRt01= (mrcal_point3_t*)data_slice__output3;
*(mrcal_point3_t*)data_slice__output0 =
mrcal_triangulate_lindstrom(dm_dv0, dm_dv1, dm_dRt01,
v0, v1, Rt01);
return true;
''' },
)
# The triangulation function used inside the optimization loop. Returns an
# "error" scalar instead of a triangulated point
m.function( "_triangulated_error",
f"""Internal triangulation routine used in the optimization loop
This is the internals for mrcal.triangulated_error(). As a user, please call
THAT function, and see the docs for that function. The differences:
- This is just the no-gradients function. The internal function that returns
gradients is _triangulated_error_withgrad
""",
args_input = ('v0', 'v1', 't01'),
prototype_input = ((3,), (3,), (3,),),
prototype_output = (),
Ccode_validate = r'''
return CHECK_CONTIGUOUS_AND_SETERROR_ALL();''',
Ccode_slice_eval = { (np.float64,np.float64,np.float64,
np.float64):
r'''
const mrcal_point3_t* v0 = (const mrcal_point3_t*)data_slice__v0;
const mrcal_point3_t* v1 = (const mrcal_point3_t*)data_slice__v1;
const mrcal_point3_t* t01 = (const mrcal_point3_t*)data_slice__t01;
*(double*)data_slice__output =
_mrcal_triangulated_error(NULL,NULL,
v0, v1, t01);
return true;
'''},
)
m.function( "_triangulated_error_withgrad",
f"""Internal triangulation routine used in the optimization loop
This is the internals for mrcal.triangulated_error(). As a user, please call
THAT function, and see the docs for that function. The differences:
- This is just the gradient-returning function. The internal function that skips those
is _triangulated_error
""",
args_input = ('v0', 'v1', 't01'),
prototype_input = ((3,), (3,), (3,),),
prototype_output = ((), (3,), (3,) ),
Ccode_validate = r'''
return CHECK_CONTIGUOUS_AND_SETERROR_ALL();''',
Ccode_slice_eval = { (np.float64,np.float64,np.float64,
np.float64,np.float64,np.float64):
r'''
const mrcal_point3_t* v0 = (const mrcal_point3_t*)data_slice__v0;
const mrcal_point3_t* v1 = (const mrcal_point3_t*)data_slice__v1;
const mrcal_point3_t* t01 = (const mrcal_point3_t*)data_slice__t01;
mrcal_point3_t* derr_dv1 = (mrcal_point3_t*)data_slice__output1;
mrcal_point3_t* derr_dt01 = (mrcal_point3_t*)data_slice__output2;
*(double*)data_slice__output0 =
_mrcal_triangulated_error(derr_dv1, derr_dt01,
v0, v1, t01);
return true;
''' },
)
m.write()
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