Path |
Digest |
Size |
science_optimization/__init__.py |
sha256=bh7Zp2XLBBlfLv98_BKoCFNJSBBnWAms7OsUGRVFY2M
|
193 |
science_optimization/algorithms/__init__.py |
sha256=PAEcA08yi4rNXZ212KfM2GwA6jjESLgG4BMrZyUKJ6Q
|
272 |
science_optimization/algorithms/base_algorithms.py |
sha256=87SpQFaEq3D3wAw35y3reBsnFlNAXO-7F97Mwo8-RTo
|
901 |
science_optimization/algorithms/cutting_plane/__init__.py |
sha256=ffHOX2xyc82TmHGCkHusEHOVoySm3KJiPQRzfqpBELo
|
85 |
science_optimization/algorithms/cutting_plane/ellipsoid_method.py |
sha256=lgk1-eZLRRqJaWiQPRS86SIE7OPZkSO79HHJm4HQq_8
|
6028 |
science_optimization/algorithms/decomposition/__init__.py |
sha256=lVmD0_LUu8BHwibyFuKC6gEu-rp1WaVVGet9Ahxlx30
|
89 |
science_optimization/algorithms/decomposition/dual_decomposition.py |
sha256=TN-eyLTd0SpX0cJ5hiPCGQlQmfgd1lXdEFs0cdAnnEY
|
7106 |
science_optimization/algorithms/derivative_free/__init__.py |
sha256=LisQZjedYXIA-YOzykSb1W9bcWJhZxVPGAqaViFIB-U
|
77 |
science_optimization/algorithms/derivative_free/nelder_mead.py |
sha256=r3AdXmzLFe51XCt1I84su1JuMoW9hU6p9RZY7fIT_-4
|
17247 |
science_optimization/algorithms/lagrange/__init__.py |
sha256=YFFZd25-3cWj2Rs02a4SnPXtFYtFmlUrt9JbWFtNNYY
|
88 |
science_optimization/algorithms/lagrange/augmented_lagrangian.py |
sha256=ZgUKjmL5rjB-7Ulm-8iYQvz_YUdzPOnv-WRKsxXYCGY
|
5177 |
science_optimization/algorithms/linear_programming/__init__.py |
sha256=2mi7fOaXnIO4fPrV1xPi0LZVkt6ctA8OoXt0RcdWdm0
|
233 |
science_optimization/algorithms/linear_programming/glop.py |
sha256=7B4ntEvjV84gh1Kt9CdkwmjV80ezqno4ERvJQbzwCzI
|
4543 |
science_optimization/algorithms/linear_programming/scipy_base_linear.py |
sha256=QZBJswGyoT447zpT3gkErllETD3ZG_D8UaFNtHZR-0c
|
3369 |
science_optimization/algorithms/linear_programming/scipy_highs_method.py |
sha256=xArHz3AG5hWZgAk6MLOOjgbaFoGVpedFFv_f27TEZ8o
|
444 |
science_optimization/algorithms/linear_programming/scipy_interior_point_method.py |
sha256=gEY3YjTjetl1A5Si1ez0mrmfY2yeHEySJX8csPfm48g
|
435 |
science_optimization/algorithms/linear_programming/scipy_simplex_method.py |
sha256=DYTNYPeX6Yvajl7OGJ6_B9UH1fuIvEvwyFS5AZ2XXq4
|
407 |
science_optimization/algorithms/search_direction/__init__.py |
sha256=0Nvo1Jz5k13oyR_U2AoAaXUCmppEnniywUadGRVbiiQ
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231 |
science_optimization/algorithms/search_direction/base_search_direction.py |
sha256=9XDef4KUGsj-oYOISmCXEC1bPRgSTZRdFfIgWrQXMuY
|
9608 |
science_optimization/algorithms/search_direction/gradient_algorithm.py |
sha256=jqJcs4KJqIgdUkNCTTA4q-1xGqNGaarmc7HnZCWtDtU
|
731 |
science_optimization/algorithms/search_direction/newton_algorithm.py |
sha256=Fn_HgDaZaAhShqZgKR802DiRz7WAPA5cAdvq0yze19g
|
589 |
science_optimization/algorithms/search_direction/quasi_newton.py |
sha256=zGE8ML7gypszjEpDU-53wfd5KBF7atPam29vWGHWOS0
|
3121 |
science_optimization/algorithms/unidimensional/__init__.py |
sha256=b7YoJ1enUf9_1wWzFzNJzc6HBMG1aaFhsyXiNkHhvkw
|
197 |
science_optimization/algorithms/unidimensional/base_unidimensional.py |
sha256=d8nyiF0g556kI-6om3uWfxbQtVUCu7XXLRUaPMCVyg0
|
1824 |
science_optimization/algorithms/unidimensional/golden_section.py |
sha256=v6s38CHQTofC_Jtv3IifF7KNO38c-QPNUkSy9lKVujk
|
1305 |
science_optimization/algorithms/unidimensional/multimodal_golden_section.py |
sha256=GYJc1GuVscpuUQXQul6semUj_UKLad4nH34f8fVZUWA
|
5579 |
science_optimization/algorithms/utils/__init__.py |
sha256=2HeJKc-E1vBsEC0ou6iMk5q16vtpCryOHAPUwQ_CwEw
|
63 |
science_optimization/algorithms/utils/algorithms_utils.py |
sha256=wZZUAM1z_WJMRQV0NaYlgs7HCtZuNZBSnSOo5uf9vmo
|
4684 |
science_optimization/builder/__init__.py |
sha256=pm6hz47R8iowEgDv494Ahsgt_oMO08AKKprsbrpkoYM
|
255 |
science_optimization/builder/builder_optimization_problem.py |
sha256=ljOQ9hFvDPFfjCckOmaexlQ1Xxu0rRAAjm81zcbsYvY
|
446 |
science_optimization/builder/constraint.py |
sha256=2hBumRjb7SC98F-UQd_jwOWgqjD03UoKw6BmVU22HXc
|
4766 |
science_optimization/builder/objective.py |
sha256=dqeyqHhvsCTZlYFQYHSXiAbZCSLAL1UlX_R4r8OlDFw
|
1823 |
science_optimization/builder/optimization_problem.py |
sha256=AuYwZbR5sj2cCtaaNpOQ_YeUP6VDLNFmnsjZypw59ks
|
15936 |
science_optimization/builder/variable.py |
sha256=ajBmi-pJMxAPpGK4fjNMV63VcDJLA8x5MuAgIhTwdLc
|
3292 |
science_optimization/examples/__init__.py |
sha256=Bp3sdE0Njs3qmUemMFXPeWw1yQG6En7ANFkfgzT9aaY
|
599 |
science_optimization/examples/decomposition_example.py |
sha256=VL0N5NOydR1It9B91ejxszfDTQXSQ_LF_ydMiP-3AAI
|
2002 |
science_optimization/examples/diet_example.py |
sha256=KeWhZ_GRJzazG0sIZygm3JQqHJK4Z-9RIeuwgcFWVfw
|
1323 |
science_optimization/examples/ellipsoid_example.py |
sha256=BSIzp_syZ2-gO8fIyKCnAyJRc34aN_YjnHseKlR_6y0
|
1542 |
science_optimization/examples/generic_function_example.py |
sha256=NvIJIklb22UbbhYMEzGYG_AifQ73ij3OgjABEZp7_bw
|
1213 |
science_optimization/examples/kleeminty_example.py |
sha256=RzXrkiBzRp_-VDayqeyPNa1FWBG5sXTh5hMY1e7x048
|
660 |
science_optimization/examples/lp_sampling.py |
sha256=hL3VW_jQlKqEeAQLKMHxGoCnbG_d5TfwdNFMpLyGfGw
|
909 |
science_optimization/examples/mgs_rastringin.py |
sha256=VOFlUdO9lmi5bglevn8tHjYp7An4eoE7YgWQxallTjI
|
1236 |
science_optimization/examples/multiobjective_example.py |
sha256=0UfWS-Aj6bYJa9xJRKL8yey4MVxDxzu1KEzgaJQSLQQ
|
2003 |
science_optimization/examples/neldermead_article_example.py |
sha256=9SFQh9SUuz5tm_0Vrm7X5-PYqASHGlqTvHKF98Ni6-A
|
4106 |
science_optimization/examples/neldermead_example.py |
sha256=YDVdcOorDgOv1nVwauEO2G4NaesXG6r-c7eF4tCt_10
|
10402 |
science_optimization/examples/pareto_sampling_cs0.py |
sha256=05GX-pln__x6BvPlTzDXmTuLM3H-RP8lv-HP1fVapuA
|
3144 |
science_optimization/examples/pareto_sampling_cs1.py |
sha256=cGZCiAhhTHyxqektjqr9XRwLPEZxdtizUlWdUZPo0ZE
|
3295 |
science_optimization/examples/pareto_sampling_cs2.py |
sha256=o6tGTqxiSR-n2kCGzpSTHPcfIz7Yc1P1zjY1B80yrHw
|
1655 |
science_optimization/examples/pareto_sampling_cs3.py |
sha256=ckYWD1l3dba6OfpcmI4kwXyn9g8eQy7gXTlBzjEcK_s
|
1956 |
science_optimization/examples/plot_example.py |
sha256=d98gpEY61uGxay949fl1Q0V_gZyOSGO0HCq9Vwx3-Z0
|
1622 |
science_optimization/examples/quadratic_example.py |
sha256=cGEo5CRxKN3--1asfz6i8aH0ofmKmBW-tBu5C14LFpg
|
1530 |
science_optimization/function/__init__.py |
sha256=t_rTPlm4TcIRp2vZjpn2-Z8wfITkpZrLkxo_6H6yV-I
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318 |
science_optimization/function/base_function.py |
sha256=aAY0TCySuCMVS5GpYiPEoy4CtKJyjqPKHGa-JS42WSw
|
10400 |
science_optimization/function/functions_composite.py |
sha256=fVemiMxqeSq2-K4zr1F7K5VnjbM1HUcKDUl70gneifE
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7807 |
science_optimization/function/generic_function.py |
sha256=9F2sKMuP7ws3asJ7l1qImGh1z__8WC3VnT82LH71A7E
|
2486 |
science_optimization/function/lagrange_function.py |
sha256=sg0FRGDbJ98KURBepfJti3X6n-HQb-G1TT-P8eiYEfo
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5421 |
science_optimization/function/linear_function.py |
sha256=VefzmonqML6DSzOCUwvCUaESm-26bfXfPf6CMpDEMHs
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3198 |
science_optimization/function/polynomial_function.py |
sha256=jvhtQ56t8noCfbk1JUOJhLJEoK6KQs86o_xV0Qh0lME
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8303 |
science_optimization/function/quadratic_function.py |
sha256=nx7yYCMdX8mYX8TUUxfykKRjdlXdWWS1Z9JBJdge2ng
|
2855 |
science_optimization/problems/__init__.py |
sha256=3QSDCr17kc-lmxpy5ZLeEavVrz-HDV38nfYI5n1Kaeo
|
297 |
science_optimization/problems/diet.py |
sha256=TZSHFKYkII8QzWu0qiSImB1rnZESyRYq0boI9qmjgqU
|
2964 |
science_optimization/problems/generic.py |
sha256=1jsOuSWhjk7rBNqqNcJucqEnvzEza8gVjl6TZsLYh84
|
2694 |
science_optimization/problems/klee_minty.py |
sha256=ou_EBHiraWMtXZ0x3tw2gbpELEYbLPy-vkMKT4ail1s
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2333 |
science_optimization/problems/mip.py |
sha256=nTB4fvQ1ISUE87LPMwJNhOkvhraeM-7_GcFUdbhVhnM
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4853 |
science_optimization/problems/quadratic.py |
sha256=kCO3Rr3T5ltT8KKNrTIB3qPNDlXdqj3oLSa7I0EZX5A
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2416 |
science_optimization/problems/rosen_suzuki.py |
sha256=12-zGYkmKW5KxiOc_JR2yUg6TchMzfY_lOv2nmmWuhs
|
5971 |
science_optimization/problems/separable_resource_allocation.py |
sha256=HnSxW2KpkRmiZ8ZHxtY-LFPpLWXhEw8cje45GqKNcNs
|
3145 |
science_optimization/profiling/__init__.py |
sha256=4bkQnNImtbJv_w4hP_sDldldyjYjR5WyjThSQ3GI0iE
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science_optimization/profiling/profiling.py |
sha256=4ngmEyLaGVBpg2MLBqkG0Cu64r70XT8M3386SDFSh9Q
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2164 |
science_optimization/solvers/__init__.py |
sha256=osdqqIgYvbBFWXb2IBgeGOExxH64_2TrvnR4FV6EUpk
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150 |
science_optimization/solvers/optimization_results.py |
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2824 |
science_optimization/solvers/optimizer.py |
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2616 |
science_optimization/solvers/pareto_samplers/__init__.py |
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science_optimization/solvers/pareto_samplers/base_pareto_samplers.py |
sha256=ye84t-vQZXEbTNnxCz6bnprQeMowPGMSRXhKLfo92DU
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5804 |
science_optimization/solvers/pareto_samplers/epsilon_sampler.py |
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8087 |
science_optimization/solvers/pareto_samplers/lambda_sampler.py |
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3270 |
science_optimization/solvers/pareto_samplers/mu_sampler.py |
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3845 |
science_optimization/solvers/pareto_samplers/nondominated_sampler.py |
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3786 |
science_optimization/solvers/pareto_samplers/random_sampler.py |
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2202 |
science_optimization/test/__init__.py |
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science_optimization/test/test_algorithm_utils.py |
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science_optimization/test/test_base_linear.py |
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science_optimization/test/test_builder_package.py |
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science_optimization/test/test_constraint_algorithms.py |
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39169 |
science_optimization/test/test_functions.py |
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35795 |
science_optimization/test/test_glop.py |
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science_optimization/test/test_pareto_sampler.py |
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science_optimization/test/test_problems.py |
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science_optimization/test/test_search_direction.py |
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science_optimization/test/test_unidimensional.py |
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science_optimization/test/valueslinear.pickle |
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science_optimization/test/valuesquad.pickle |
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science_optimization/test/valuessparse.pickle |
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src/__init__.py |
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0 |
src/algorithms.h |
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src/matrix.h |
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src/nlpalg.cpp |
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src/nlpalg.pdf |
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src/pybind.vcxproj |
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nlpalg.cpython-38-x86_64-linux-gnu.so |
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science_optimization/builder/__init__.pyc |
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science_optimization-9.0.3.dist-info/LICENSE |
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science_optimization-9.0.3.dist-info/METADATA |
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science_optimization-9.0.3.dist-info/WHEEL |
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science_optimization-9.0.3.dist-info/RECORD |
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