odynn.optim module¶

class odynn.optim.Optimized(dt)[source]¶

Bases: abc.ABC

Abstract class for object to be optimized. It could represent on or a set of neurons, or a circuit.

Attributes:	`init_params` dict, initial parameters `num` int, number of models `variables` dict, current Tf variables

Methods

`apply_constraints`(session)	Apply necessary constraints to the optimized variables
`build_graph`([batch])	Build the tensorflow graph.
`plot_vars`(var_dic, suffix, show, save)	A function to plot the variables of the optimized object
`settings`()	Give a string describing the settings Returns(str): description

apply_init
predump
study_vars

apply_constraints(session)[source]¶

Apply necessary constraints to the optimized variables

Parameters:	session (tf.Session) –

apply_init(session)[source]¶

build_graph(batch=1)[source]¶: Build the tensorflow graph. Take care of the loop and the initial state.

init_params¶: dict, initial parameters

ions = {}¶

num¶: int, number of models

static plot_vars(var_dic, suffix, show, save)[source]¶

A function to plot the variables of the optimized object

Parameters:	var_dic – suffix – show – save –

predump(sess)[source]¶

settings()[source]¶: Give a string describing the settings Returns(str): description

study_vars(p, *args, **kwargs)[source]¶

variables¶: dict, current Tf variables

class odynn.optim.Optimizer(optimized, frequency=30)[source]¶

Bases: abc.ABC

Methods

settings(w, train) Give the settings of the optimization

optimize
plot_out

__init__(optimized, frequency=30)[source]¶

Parameters:	optimized (Optimized) – epochs – frequency –

optimize(dir, train_=None, test_=None, w=None, epochs=700, l_rate=(0.1, 9, 0.92), suffix='', step='', reload=False, reload_dir=None, yshape=None, evol_var=True, plot=True)[source]¶

plot_out(*args, **kwargs)[source]¶

settings(w, train)[source]¶

Give the settings of the optimization

Parameters:	w (tuple) – weights for the loss of voltage and ions concentrations
Returns:	settings
Return type:	str

odynn.optim.get_best_result(dir, i=-1, loss=False)[source]¶

Parameters:	dir (str) – path to the directory i: (Default value = -1)

Returns:

odynn.optim.get_data(dir)[source]¶

odynn.optim.get_model(dir)[source]¶

odynn.optim.get_vars(dir, i=-1, loss=False)[source]¶

get dic of vars from dumped file

Parameters:	dir (str) – path to the directory i: (Default value = -1)

Returns:

odynn.optim.get_vars_all(dir, i=-1, losses=False)[source]¶

get dic of vars from dumped file

Parameters:	dir (str) – path to the directory i: (Default value = -1)

Returns:

odynn.optim.plot_loss_rate(losses, rates, losses_test=None, parallel=1, suffix='', show=False, save=True)[source]¶

plot loss (log10) and learning rate

Parameters:	losses – rates – losses_test – (Default value = None) parallel – (Default value = 1) suffix – (Default value = “”) show (bool) – If True, show the figure (Default value = False) save – (Default value = True)

Returns: