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v0.7.0 - Complex Number Support #25

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jono merged 8 commits from v0.7.0 into main 2026-01-31 15:31:57 +00:00
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README.md
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@@ -12,6 +12,7 @@ A Python library for representing, manipulating, and solving polynomial equation
## Key Features ## Key Features
* **Numerically Stable Solver**: Makes complex calculations **practical**. Leverage your GPU to power the robust genetic algorithm, solving high-degree polynomials accurately in a reasonable timeframe. * **Numerically Stable Solver**: Makes complex calculations **practical**. Leverage your GPU to power the robust genetic algorithm, solving high-degree polynomials accurately in a reasonable timeframe.
* **Complex Number Support**: Fully supports complex coefficients and finding roots in the complex plane (e.g., $x^2 + 1 = 0 \to \pm i$).
* **Numba Accelerated CPU Solver**: The default genetic algorithm is JIT-compiled with Numba for high-speed CPU performance, right out of the box. * **Numba Accelerated CPU Solver**: The default genetic algorithm is JIT-compiled with Numba for high-speed CPU performance, right out of the box.
* **CUDA Accelerated**: Leverage NVIDIA GPUs for a massive performance boost when finding roots in large solution spaces. * **CUDA Accelerated**: Leverage NVIDIA GPUs for a massive performance boost when finding roots in large solution spaces.
* **Create and Manipulate Polynomials**: Easily define polynomials of any degree using integer or float coefficients, and perform arithmetic operations like addition, subtraction, multiplication, and scaling. * **Create and Manipulate Polynomials**: Easily define polynomials of any degree using integer or float coefficients, and perform arithmetic operations like addition, subtraction, multiplication, and scaling.
@@ -75,12 +76,19 @@ roots_analytic = f1.quadratic_solve()
print(f"Analytic roots: {sorted(roots_analytic)}") print(f"Analytic roots: {sorted(roots_analytic)}")
# > Analytic roots: [-1.0, 2.5] # > Analytic roots: [-1.0, 2.5]
# 6. Find roots with the genetic algorithm (Numba CPU) # 6. Find REAL roots with the genetic algorithm (Numba CPU)
#    This is the default, JIT-compiled CPU solver. # This is the default, JIT-compiled CPU solver.
ga_opts = GA_Options(num_of_generations=20) ga_opts = GA_Options(num_of_generations=20)
roots_ga = f1.get_real_roots(ga_opts, use_cuda=False) roots_ga = f1.get_real_roots(ga_opts, use_cuda=False)
print(f"Approximate roots from GA: {roots_ga[:2]}") print(f"Approximate real roots: {roots_ga[:2]}")
# > Approximate roots from GA: [-1.000..., 2.500...] # > Approximate real roots: [-1.000..., 2.500...]
# 7. Find ALL roots (Real + Complex)
# Use get_roots() to search the complex plane.
f_complex = Function(2, [1, 0, 1]) # x^2 + 1
roots_all = f_complex.get_roots(ga_opts)
print(f"Approximate complex roots: {roots_all}")
# > Approximate complex roots: [-1.00...j, 1.00...j]
# If you installed a CUDA extra, you can run it on the GPU: # If you installed a CUDA extra, you can run it on the GPU:
# roots_ga_gpu = f1.get_real_roots(ga_opts, use_cuda=True) # roots_ga_gpu = f1.get_real_roots(ga_opts, use_cuda=True)
@@ -114,7 +122,10 @@ ga_robust_search = GA_Options(
# Increase the crossover blend factor to 0.75. # Increase the crossover blend factor to 0.75.
# This allows new solutions to be created further # This allows new solutions to be created further
# away from their parents, increasing exploration. # away from their parents, increasing exploration.
blend_alpha=0.75 blend_alpha=0.75,
# Enable complex root finding (default is True)
find_complex=True
) )
# Pass the custom options to the solver # Pass the custom options to the solver