cimod : C++ header-only library for a binary quadratic model

How to use

You should only include a header src/binary_quadratic_model.hpp in your project.

Example

C++

#include "src/binary_quadratic_model.hpp"

using namespace cimod;
int main()
{
// Set linear biases and quadratic biases
Linear<uint32_t, double> linear{ {1, 1.0}, {2, 2.0}, {3, 3.0}, {4, 4.0} };
Quadratic<uint32_t, double> quadratic
{
     {std::make_pair(1, 2), 12.0}, {std::make_pair(1, 3), 13.0}, {std::make_pair(1, 4), 14.0},
     {std::make_pair(2, 3), 23.0}, {std::make_pair(2, 4), 24.0},
     {std::make_pair(3, 4), 34.0}
 };

// Set offset
double offset = 0.0;

// Set variable type
Vartype vartype = Vartype::BINARY;
// Create a BinaryQuadraticModel instance
BinaryQuadraticModel<uint32_t, double, cimod::Dense> bqm(linear, quadratic, offset, vartype);

//linear terms -> bqm.get_linear()
//quadratic terms -> bqm.get_quadratic()

return 0;
}

Python

import cimod
import dimod

# Set linear biases and quadratic biases
linear = {1:1.0, 2:2.0, 3:3.0, 4:4.0}
quadratic = {(1,2):12.0, (1,3):13.0, (1,4):14.0, (2,3):23.0, (2,4):24.0, (3,4):34.0}

# Set offset
offset = 0.0

# Set variable type
vartype = dimod.BINARY

# Create a BinaryQuadraticModel instance
bqm = cimod.BinaryQuadraticModel(linear, quadratic, offset, vartype)

print(bqm.linear)
print(bqm.quadratic)

For Contributor

Use pre-commit for auto chech before git commit. .pre-commit-config.yaml

# pipx install pre-commit 
# or 
# pip install pre-commit
pre-commit install

Install

via this directory

$ python -m pip install -vvv .

via pip

# Binary
$ pip install jij-cimod
# From Source 
$ pip install --no-binary=jij-cimod jij-cimod 

Test

Python

$ python -m venv .venv
$ pip install pip-tools 
$ pip-compile setup.cfg
$ pip-compile dev-requirements.in
$ pip-sync requirements.txt dev-requirements.txt
$ source .venv/bin/activate
$ export CMAKE_BUILD_TYPE=Debug
$ python setup.py --force-cmake install --build-type Debug -G Ninja
$ python setup.py --build-type Debug test 
$ python -m coverage html

C++

$ mkdir build 
$ cmake -DCMAKE_BUILD_TYPE=Debug -S . -B build
$ cmake --build build --parallel
$ cd build
$ ./tests/cimod_test
# Alternatively Use CTest 
$ ctest --extra-verbose --parallel --schedule-random

Needs: CMake > 3.22, C++17

• Format

$ pip-compile format-requirements.in
$ pip-sync format-requirements.txt

$ python -m isort 
$ python -m black 

• Aggressive Format

$ python -m isort --force-single-line-imports --verbose ./cimod
$ python -m autoflake --in-place --recursive --remove-all-unused-imports --ignore-init-module-imports --remove-unused-variables ./cimod
$ python -m autopep8 --in-place --aggressive --aggressive  --recursive ./cimod
$ python -m isort ./cimod
$ python -m black ./cimod

• Lint

$ pip-compile setup.cfg
$ pip-compile dev-requirements.in
$ pip-compile lint-requirements.in
$ pip-sync requirements.txt dev-requirements.txt lint-requirements.txt

$ python -m flake8
$ python -m mypy
$ python -m pyright

Benchmark

Benchmark code

import dimod
import cimod
import time

fil = open("benchmark", "w")
fil.write("N t_dimod t_cimod\n")

def benchmark(N, test_fw):
    linear = {}
    quadratic = {}

    spin = {}

    # interactions

    for i in range(N):
        spin[i] = 1

    for elem in range(N):
        linear[elem] = 2.0*elem;

    for i in range(N):
        for j in range(i+1, N):
            if i != j:
                quadratic[(i,j)] = (i+j)/(N)

    t1 = time.time()

    # initialize
    a = test_fw.BinaryQuadraticModel(linear, quadratic, 0, test_fw.BINARY)
    a.change_vartype(test_fw.SPIN)

    # calculate energy for 50 times.
    for _ in range(50):
        print(a.energy(spin))

    t2 = time.time()

    return t2-t1

d_arr = []
c_arr = []

for N in [25, 50, 100, 200, 300, 400, 600, 800,1000, 1600, 2000, 3200, 5000]:
    print("N {}".format(N))
    d = benchmark(N, dimod)
    c = benchmark(N, cimod)
    print("{} {} {}".format(N, d, c))
    fil.write("{} {} {}\n".format(N, d, c))