brainpy.dyn.channels.CalciumFixed#

class brainpy.dyn.channels.CalciumFixed(size, E=120.0, C=0.05, method='exp_auto', name=None, **channels)[source]#

Fixed Calcium dynamics.

This calcium model has no dynamics. It only holds a fixed reversal potential \(E\).

__init__(size, E=120.0, C=0.05, method='exp_auto', name=None, **channels)[source]#

Methods

__init__(size[, E, C, method, name])

current(V[, C_Ca, E_Ca])

get_delay_data(name, delay_step, *indices)

Get delay data according to the provided delay steps.

has(**children_cls)

The aggressive operation to gather master and children classes.

ints([method])

Collect all integrators in this node and the children nodes.

load_states(filename[, verbose])

Load the model states.

nodes([method, level, include_self])

Collect all children nodes.

register_delay(name, delay_step, delay_target)

Register delay variable.

register_implicit_nodes(nodes)

register_implicit_vars(variables)

reset(V[, C_Ca, E_Ca])

Reset function which reset the whole variables in the model.

reset_delay(name, delay_target)

Reset the delay variable.

save_states(filename[, variables])

Save the model states.

train_vars([method, level, include_self])

The shortcut for retrieving all trainable variables.

unique_name([name, type_])

Get the unique name for this object.

update(t, dt, V)

Step function of a network.

update_delay(name, delay_data)

Update the delay according to the delay data.

vars([method, level, include_self])

Collect all variables in this node and the children nodes.

Attributes

global_delay_vars

name

steps