Version 2.1.11

What's Changed

• fix: cross-correlation bug by @ztqakita in #201
• update apis, test and docs of numpy ops by @chaoming0625 in #202
• docs: add sphinx_book_theme by @ztqakita in #203
• fix: add requirements-doc.txt by @ztqakita in #204
• update contro flow, integrators, operators, and docs by @chaoming0625 in #205
• improve oo-to-function transformation speed by @chaoming0625 in #208

Full Changelog: V2.1.10...V2.1.11

Version 2.1.9

What's Changed

• update control flow APIs and Docs by @chaoming0625 in #192
• doc: update docs of dynamics simulation by @chaoming0625 in #193
• fix #125: add channel models and two-compartment Pinsky-Rinzel model by @chaoming0625 in #194
• JIT errors do not change Variable values by @chaoming0625 in #195
• fix a bug in math.activations.py by @c-xy17 in #196
• Functionalinaty improvements by @chaoming0625 in #197
• update rate docs by @chaoming0625 in #198
• update brainpy.dyn doc by @chaoming0625 in #199

Full Changelog: V2.1.8...V2.1.9

Version 2.1.10

• Fix bugs on synapse delay

Full Changelog: V2.1.9...V2.1.10

Version 2.1.8

What's Changed

• Fix #120 by @chaoming0625 in #178
• feat: brainpy.Collector supports addition and subtraction by @chaoming0625 in #179
• feat: delay variables support "indices" and "reset()" function by @chaoming0625 in #180
• Support reset functions in neuron and synapse models by @chaoming0625 in #181
• update() function on longer need _t and _dt by @chaoming0625 in #183
• small updates by @chaoming0625 in #188
• feat: easier control flows with brainpy.math.ifelse by @chaoming0625 in #189
• feat: update delay couplings of DiffusiveCoupling and AdditiveCouping by @chaoming0625 in #190
• update version and changelog by @chaoming0625 in #191

Full Changelog: V2.1.7...V2.1.8

Version 2.1.7

What's Changed

• synapse models support heterogeneuos weights by @chaoming0625 in #170
• more efficient synapse implementation by @chaoming0625 in #171
• fix input models in brainpy.dyn by @chaoming0625 in #172
• fix: np array astype by @ztqakita in #173
• update README: 'brain-py' to 'brainpy' by @chaoming0625 in #174
• fix: fix the updating rules in the STP model by @c-xy17 in #176
• Updates and fixes by @chaoming0625 in #177

Full Changelog: V2.1.5...V2.1.7

Version 2.1.5

What's Changed

• brainpy.math.random.shuffle is numpy like by @chaoming0625 in #153
• update LICENSE by @chaoming0625 in #155
• docs: add m1 warning by @ztqakita in #154
• compatible apis of 'brainpy.math' with those of 'jax.numpy' in most modules by @chaoming0625 in #156
• Important updates by @chaoming0625 in #157
• Updates by @chaoming0625 in #159
• Add LayerNorm, GroupNorm, and InstanceNorm as nn_nodes in normalization.py by @c-xy17 in #162
• feat: add conv & pooling nodes by @ztqakita in #161
• fix: update setup.py by @ztqakita in #163
• update setup.py by @chaoming0625 in #165
• fix: change trigger condition by @ztqakita in #166
• fix: add build_conn() function by @ztqakita in #164
• update synapses by @chaoming0625 in #167
• get the deserved name: brainpy by @chaoming0625 in #168
• update tests by @chaoming0625 in #169

Full Changelog: V2.1.4...V2.1.5

Version 2.1.4

What's Changed

• fix doc parsing bug by @chaoming0625 in #127
• Update overview_of_dynamic_model.ipynb by @c-xy17 in #129
• Reorganization of brainpylib.custom_op and adding interface in brainpy.math by @ztqakita in #128
• Fix: modify register_op and brainpy.math interface by @ztqakita in #130
• new features about RNN training and delay differential equations by @chaoming0625 in #132
• Fix #123: Add low-level operators docs and modify register_op by @ztqakita in #134
• feat: add generate_changelog by @ztqakita in #135
• fix #133, support batch size training with offline algorithms by @chaoming0625 in #136
• fix #84: support online training algorithms by @chaoming0625 in #137
• feat: add the batch normalization node by @c-xy17 in #138
• fix: fix shape checking error by @chaoming0625 in #139
• solve #131, support efficient synaptic computation for special connection types by @chaoming0625 in #140
• feat: update the API and test for batch normalization by @c-xy17 in #142
• Node is default trainable by @chaoming0625 in #143
• Updates training apis and docs by @chaoming0625 in #145
• fix: add dependencies and update version by @ztqakita in #147
• update requirements by @chaoming0625 in #146
• data pass of the Node is default SingleData by @chaoming0625 in #148

Full Changelog: V2.1.3...V2.1.4

Version 2.1.3

This release improves the functionality and usability of BrainPy. Core changes include

• support customization of low-level operators by using Numba
• fix bugs

What's Changed

• Provide custom operators written in numba for jax jit by @ztqakita in #122
• fix DOGDecay bugs; add more features by @chaoming0625 in #124
• fix bugs by @chaoming0625 in #126

Full Changelog: V2.1.2...V2.1.3

Version 2.1.2

• support rate-based whole-brain modeling
• add more neuron models, including rate neurons/synapses
• support Python 3.10
• improve delays etc. APIs
• and much more

What's Changed

• fix matplotlib dependency on "brainpy.analysis" module by @chaoming0625 in #110
• Sync master to brainpy-2.x branch by @ztqakita in #111
• add py3.6 test & delete multiple macos env by @ztqakita in #112
• Modify ci by @ztqakita in #113
• Add py3.10 test by @ztqakita in #115
• update python version by @chaoming0625 in #114
• add brainpylib mac py3.10 by @ztqakita in #116
• Enhance measure/input/brainpylib by @chaoming0625 in #117
• fix #105: Add customize connections docs by @ztqakita in #118
• fix bugs by @chaoming0625 in #119
• Whole brain modeling by @chaoming0625 in #121

Full Changelog: V2.1.1...V2.1.2

Version 2.1.1

This release continues to update the functionality of BrainPy. Core changes include

• numerical solvers for fractional differential equations
• more standard brainpy.nn interfaces

New Features

• Numerical solvers for fractional differential equations
  • brainpy.fde.CaputoEuler
  • brainpy.fde.CaputoL1Schema
  • brainpy.fde.GLShortMemory
• Fractional neuron models
  • brainpy.dyn.FractionalFHR
  • brainpy.dyn.FractionalIzhikevich
• support shared_kwargs in RNNTrainer and RNNRunner