Merge branch 'main' into v3

Author: ago109

README.md

@@ -32,7 +32,7 @@ ngc-learn requires:
 1) Python (>=3.10)
 2) NumPy (>=1.22.0)
 3) SciPy (>=1.7.0)
-4) ngcsimlib (>=2.0.0), (visit official page <a href="https://github.com/NACLab/ngc-sim-lib">here</a>)
+4) ngcsimlib (>=3.0.0), (visit official page <a href="https://github.com/NACLab/ngc-sim-lib">here</a>)
 5) JAX (>=0.4.28) (to enable GPU use, make sure to install one of the CUDA variants)
 <!--
 5) scikit-learn (>=1.3.1) if using `ngclearn.utils.density`
@@ -42,7 +42,7 @@ ngc-learn requires:
 -->
 
 ---
-ngc-learn 3.0.0 and later require Python 3.10 or newer as well as ngcsimlib >=2.0.0.
+ngc-learn 3.0.0 and later require Python 3.10 or newer as well as ngcsimlib >=3.0.0.
 ngc-learn's plotting capabilities (routines within `ngclearn.utils.viz`) require
 Matplotlib (>=3.8.0) and imageio (>=2.31.5) and both plotting and density estimation
 tools (routines within ``ngclearn.utils.density``) will require Scikit-learn (>=0.24.2).

docs/requirements.txt

@@ -8,4 +8,4 @@ matplotlib>=3.8.0
 jax>=0.4.28
 jaxlib>=0.4.28
 imageio>=2.31.5
-ngcsimlib>=1.0.0
+ngcsimlib>=1.0.1

docs/tutorials/neurocog/hodgkin_huxley_cell.md

@@ -68,8 +68,6 @@ essentially probability values:
 `m` ($\mathbf{m}_t$)  for the probability of sodium channel subunit activation, and 
 `h` ($\mathbf{h}_t$)  for the probability of sodium channel subunit inactivation.  
 
-neurons and muscle cells. It is a continuous-time dynamical system.
-
 Formally, the core dynamics of the H-H cell can be written out as follows:
 
 $$

ngclearn/utils/model_utils.py

@@ -515,10 +515,13 @@ def d_sigmoid(x):
     sigm_x = nn.sigmoid(x) ## pre-compute once
     return sigm_x * (1. - sigm_x)
 
+def inverse_sigmoid(x, clip_bound=0.03): ## wrapper call for naming convention ease
+    return inverse_logistic(x, clip_bound=clip_bound)
+
 @jit
-def inverse_logistic(x, clip_bound=0.03): # 0.03
+def inverse_logistic(x, clip_bound=0.03):
     """
-    The inverse logistic link - logit function.
+    The inverse logistic link - the logit function.
 
     Args:
         x: data to transform via inverse logistic function