Changelog

v0.7.8

  • Added the ability to apply Kleinman symmetry to a particular SHG tensor (i.e. enforce full permutation symmetry of the susceptibility indices). Use shgpy.particularize() with the option permute_all_indices=True

v0.7.6

v0.7.5

  • Fixed a number of tensors which were incorrectly defined due to typos in Boyd. The affected tensors were

    • D_6 (dipole)

    • C_4 (quadrupole)

    • C_4h (quadrupole)

    • S_4 (quadrupole)

v0.7.0

  • Officially transitioned to supporting only tensors for which all the involved symbols are purely real, as defined by sympy assumptions. This got rid of a lot of redundancy in function definitions, such as shgpy.fformgen.generate_contracted_fourier_transforms versus shgpy.fformgen.generate_contracted_fourier_transforms_complex, shgpy.formgen.formgen_dipole_quadrupole_real and shgpy.formgen.formgen_dipole_quadrupole_complex, ect. In all cases, these functions have been replaced by a single function, e.g. shgpy.formgen.formgen_dipole_quadrupole, and you will receive a NotImplementedError if you try to use any of the replaced definitions.

  • To aid in explicitly defining the reality of SHG tensors, added shgpy.make_tensor_real to complement shgpy.make_tensor_complex.

  • Transitioned to compiling cost functions at runtime by generating C code with sympy.ulities.codegen. This is a workaround to the fact that complicated sympy.lambdify functions are very slow to evaluate.

  • Added the ability to generate a cost function independently with shgpy.fformfit.gen_cost_func() and use it in one of the fitting routines by the load_cost_func_filename argument.

  • Added shgpy.fformfit.dual_annealing_fit and shgpy.fformfit.dual_annealing_fit_with_bounds.

v0.6.1

  • Added the ability to optionally send arguments to the scipy.optimize.basinhopping function. This is useful e.g. for debugging – use

>>> basinhopping_kwargs = {'disp':True}

to send disp=True to scipy.optimize.basinhopping, which initializes verbose output.

v0.5.1

  • Fixed a bug related to the change in v0.5.0 in which shgpy.load_fform() wasn’t compatible with the new pickling scheme.

v0.5.0

  • In .p file handling, switched from pickling pure sympy expressions in shgpy.fformgen to pickling string represetations of those expressions generated using sympy.srepr. This is a workaround to a sympy / pickle bug in which unpickling sympy expressions will cause sympy to conflate objects like sympy.Symbol('x') with sympy.Symbol('x', real=True).

  • To use v0.5.0, you will have to remake your .p files.