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Doc for brainpylib>=0.3.0 #645

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merged 4 commits into from
Mar 3, 2024
Merged

Doc for brainpylib>=0.3.0 #645

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99d0f2d
update docs
chaoming0625 Mar 3, 2024
104bffb
update changelogs
chaoming0625 Mar 3, 2024
9d71746
add `noise` option to neurons in `brainpy.dyn`
chaoming0625 Mar 3, 2024
14fdd70
Merge branch 'dynold-integration' into doc-v0.3.0
chaoming0625 Mar 3, 2024
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43 changes: 0 additions & 43 deletions .github/workflows/docs.yml
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2,663 changes: 2,663 additions & 0 deletions brainpy-changelog.md
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31 changes: 28 additions & 3 deletions brainpy/_src/dyn/neurons/hh.py
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Original file line number Diff line number Diff line change
Expand Up @@ -315,6 +315,9 @@ def __init__(
m_initializer: Optional[Union[Callable, ArrayType]] = None,
h_initializer: Optional[Union[Callable, ArrayType]] = None,
n_initializer: Optional[Union[Callable, ArrayType]] = None,

# noise
noise: Union[float, ArrayType, Callable] = None,
):
# initialization
super().__init__(size=size,
Expand All @@ -340,8 +343,14 @@ def __init__(
self._n_initializer = is_initializer(n_initializer, allow_none=True)
self._V_initializer = is_initializer(V_initializer)

# noise
self.noise = init_noise(noise, self.varshape, num_vars=4)

# integral
self.integral = odeint(method=method, f=self.derivative)
if self.noise is None:
self.integral = odeint(method=method, f=self.derivative)
else:
self.integral = sdeint(method=self.method, f=self.derivative, g=self.noise)

# model
if init_var:
Expand Down Expand Up @@ -622,6 +631,9 @@ def __init__(
V_th: Union[float, ArrayType, Callable] = 10.,
W_initializer: Union[Callable, ArrayType] = OneInit(0.02),
V_initializer: Union[Callable, ArrayType] = Uniform(-70., -60.),

# noise
noise: Union[float, ArrayType, Callable] = None,
):
# initialization
super().__init__(size=size,
Expand Down Expand Up @@ -650,8 +662,13 @@ def __init__(
self._W_initializer = is_initializer(W_initializer)
self._V_initializer = is_initializer(V_initializer)

# noise
self.noise = init_noise(noise, self.varshape, num_vars=2)
# integral
self.integral = odeint(method=method, f=self.derivative)
if self.noise is not None:
self.integral = sdeint(method=self.method, f=self.derivative, g=self.noise)
else:
self.integral = odeint(method=method, f=self.derivative)

# model
if init_var:
Expand Down Expand Up @@ -895,6 +912,9 @@ def __init__(
V_initializer: Union[Callable, ArrayType] = OneInit(-65.),
h_initializer: Union[Callable, ArrayType] = OneInit(0.6),
n_initializer: Union[Callable, ArrayType] = OneInit(0.32),

# noise
noise: Union[float, ArrayType, Callable] = None,
):
# initialization
super().__init__(size=size,
Expand All @@ -920,8 +940,13 @@ def __init__(
self._n_initializer = is_initializer(n_initializer)
self._V_initializer = is_initializer(V_initializer)

# noise
self.noise = init_noise(noise, self.varshape, num_vars=3)
# integral
self.integral = odeint(method=method, f=self.derivative)
if self.noise is not None:
self.integral = sdeint(method=self.method, f=self.derivative, g=self.noise)
else:
self.integral = odeint(method=method, f=self.derivative)

# model
if init_var:
Expand Down
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