Version 2.1.12

Highlights

This release is excellent. We have made important improvements.

1. We provide dozens of random sampling in NumPy which are not supportted in JAX, such as brainpy.math.random.bernoulli,
   brainpy.math.random.lognormal, brainpy.math.random.binomial, brainpy.math.random.chisquare, brainpy.math.random.dirichlet, brainpy.math.random.geometric, brainpy.math.random.f, brainpy.math.random.hypergeometric, brainpy.math.random.logseries, brainpy.math.random.multinomial, brainpy.math.random.multivariate_normal, brainpy.math.random.negative_binomial, brainpy.math.random.noncentral_chisquare, brainpy.math.random.noncentral_f, brainpy.math.random.power, brainpy.math.random.rayleigh, brainpy.math.random.triangular, brainpy.math.random.vonmises, brainpy.math.random.wald, brainpy.math.random.weibull
2. make efficient checking on numerical values. Instead of direct id_tap() checking which has large overhead, currently brainpy.tools.check_erro_in_jit() is highly efficient.
3. Fix JaxArray operator errors on None
4. improve oo-to-function transformation speeds
5. io works: .save_states() and .load_states()

What's Changed

• support dtype setting in array interchange functions by @chaoming0625 in #209
• fix #144: operations on None raise errors by @chaoming0625 in #210
• add tests and new functions for random sampling by @c-xy17 in #213
• feat: fix io for brainpy.Base by @chaoming0625 in #211
• update advanced tutorial documentation by @chaoming0625 in #212
• fix #149 (dozens of random samplings in NumPy) and fix JaxArray op errors by @chaoming0625 in #216
• feat: efficient checking on numerical values by @chaoming0625 in #217

Full Changelog: V2.1.11...V2.1.12