feat: add batch support and refactor mixture evaluation logic #46
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This commit unifies the sample generators for all mixture types (NMM, NMV, NV) by integrating canonical form support directly into the main generator function. Previously, each mixture type had separate classical and canonical generators. Now, the generator checks mixture_form inside the function and switches behavior accordingly. In canonical form, the beta parameter is not used. This simplifies the generator API and reduces code duplication. - Updated nm_generator.py, nmv_generator.py, nv_generator.py - Remembered `mixture_form` in AbstractMixture class - Updated tests and notebook to use the new unified API BREAKING CHANGE: canonical_generate() methods were removed; use generate() instead.
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- Updated `moment`, `pdf`, `cdf`, and `logpdf` methods to support both scalar and list inputs for efficient batch computation. - Extracted shared evaluation logic (e.g., `moment`, `pdf`, `cdf`, `logpdf`) into the `AbstractMixtures` base class to eliminate code duplication across subclasses. - Centralized input validation, RQMC integration, and distribution handling within the base class for better maintainability. - Fixed type annotations to align with abstract method signatures and resolve `mypy` type-checking issues. These changes improve code clarity, enable vectorized evaluations, and make future extensions easier to implement.
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feat: dynamic integrator selection
feat: unify mixture generators and support canonical forms
plidan123
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feat: add batch support and refactor mixture evaluation logic
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moment,pdf,cdf, andlogpdfmethods to support both scalar and list inputs for efficient batch computation.moment,pdf,cdf,logpdf) into theAbstractMixturesbase class to eliminate code duplication across subclasses.mypytype-checking issues.These changes improve code clarity, enable vectorized evaluations, and make future extensions easier to implement.