# This file was created automatically by SWIG.
# Don't modify this file, modify the SWIG interface instead.
# This file is compatible with both classic and new-style classes.
import _libfann
def _swig_setattr(self,class_type,name,value):
if (name == "this"):
if isinstance(value, class_type):
self.__dict__[name] = value.this
if hasattr(value,"thisown"): self.__dict__["thisown"] = value.thisown
del value.thisown
return
method = class_type.__swig_setmethods__.get(name,None)
if method: return method(self,value)
self.__dict__[name] = value
def _swig_getattr(self,class_type,name):
method = class_type.__swig_getmethods__.get(name,None)
if method: return method(self)
raise AttributeError,name
import types
try:
_object = types.ObjectType
_newclass = 1
except AttributeError:
class _object : pass
_newclass = 0
del types
NULL = _libfann.NULL
fann_create = _libfann.fann_create
fann_create_array = _libfann.fann_create_array
fann_create_shortcut = _libfann.fann_create_shortcut
fann_create_shortcut_array = _libfann.fann_create_shortcut_array
fann_run_old = _libfann.fann_run_old
fann_destroy = _libfann.fann_destroy
fann_randomize_weights = _libfann.fann_randomize_weights
fann_init_weights = _libfann.fann_init_weights
fann_print_connections = _libfann.fann_print_connections
fann_create_from_file = _libfann.fann_create_from_file
fann_save = _libfann.fann_save
fann_save_to_fixed = _libfann.fann_save_to_fixed
fann_train = _libfann.fann_train
fann_test_old = _libfann.fann_test_old
fann_get_error = _libfann.fann_get_error
fann_get_MSE = _libfann.fann_get_MSE
fann_reset_error = _libfann.fann_reset_error
fann_reset_MSE = _libfann.fann_reset_MSE
fann_read_train_from_file = _libfann.fann_read_train_from_file
fann_destroy_train = _libfann.fann_destroy_train
fann_train_epoch = _libfann.fann_train_epoch
fann_test_data = _libfann.fann_test_data
fann_train_on_data = _libfann.fann_train_on_data
fann_train_on_data_callback = _libfann.fann_train_on_data_callback
fann_train_on_file = _libfann.fann_train_on_file
fann_train_on_file_callback = _libfann.fann_train_on_file_callback
fann_shuffle_train_data = _libfann.fann_shuffle_train_data
fann_merge_train_data = _libfann.fann_merge_train_data
fann_duplicate_train_data = _libfann.fann_duplicate_train_data
fann_save_train = _libfann.fann_save_train
fann_save_train_to_fixed = _libfann.fann_save_train_to_fixed
fann_print_parameters = _libfann.fann_print_parameters
fann_get_training_algorithm = _libfann.fann_get_training_algorithm
fann_set_training_algorithm = _libfann.fann_set_training_algorithm
fann_get_learning_rate = _libfann.fann_get_learning_rate
fann_set_learning_rate = _libfann.fann_set_learning_rate
fann_get_activation_function_hidden = _libfann.fann_get_activation_function_hidden
fann_set_activation_function_hidden = _libfann.fann_set_activation_function_hidden
fann_get_activation_function_output = _libfann.fann_get_activation_function_output
fann_set_activation_function_output = _libfann.fann_set_activation_function_output
fann_get_activation_steepness_hidden = _libfann.fann_get_activation_steepness_hidden
fann_set_activation_steepness_hidden = _libfann.fann_set_activation_steepness_hidden
fann_get_activation_steepness_output = _libfann.fann_get_activation_steepness_output
fann_set_activation_steepness_output = _libfann.fann_set_activation_steepness_output
fann_get_activation_hidden_steepness = _libfann.fann_get_activation_hidden_steepness
fann_set_activation_hidden_steepness = _libfann.fann_set_activation_hidden_steepness
fann_get_activation_output_steepness = _libfann.fann_get_activation_output_steepness
fann_set_activation_output_steepness = _libfann.fann_set_activation_output_steepness
fann_set_train_error_function = _libfann.fann_set_train_error_function
fann_get_train_error_function = _libfann.fann_get_train_error_function
fann_get_quickprop_decay = _libfann.fann_get_quickprop_decay
fann_set_quickprop_decay = _libfann.fann_set_quickprop_decay
fann_get_quickprop_mu = _libfann.fann_get_quickprop_mu
fann_set_quickprop_mu = _libfann.fann_set_quickprop_mu
fann_get_rprop_increase_factor = _libfann.fann_get_rprop_increase_factor
fann_set_rprop_increase_factor = _libfann.fann_set_rprop_increase_factor
fann_get_rprop_decrease_factor = _libfann.fann_get_rprop_decrease_factor
fann_set_rprop_decrease_factor = _libfann.fann_set_rprop_decrease_factor
fann_get_rprop_delta_min = _libfann.fann_get_rprop_delta_min
fann_set_rprop_delta_min = _libfann.fann_set_rprop_delta_min
fann_get_rprop_delta_max = _libfann.fann_get_rprop_delta_max
fann_set_rprop_delta_max = _libfann.fann_set_rprop_delta_max
fann_get_num_input = _libfann.fann_get_num_input
fann_get_num_output = _libfann.fann_get_num_output
fann_get_total_neurons = _libfann.fann_get_total_neurons
fann_get_total_connections = _libfann.fann_get_total_connections
fann_set_error_log = _libfann.fann_set_error_log
fann_get_errno = _libfann.fann_get_errno
fann_reset_errno = _libfann.fann_reset_errno
fann_reset_errstr = _libfann.fann_reset_errstr
fann_get_errstr = _libfann.fann_get_errstr
fann_print_error = _libfann.fann_print_error
class fann_neuron(_object):
__swig_setmethods__ = {}
__setattr__ = lambda self, name, value: _swig_setattr(self, fann_neuron, name, value)
__swig_getmethods__ = {}
__getattr__ = lambda self, name: _swig_getattr(self, fann_neuron, name)
def __repr__(self):
return "<C fann_neuron instance at %s>" % (self.this,)
__swig_setmethods__["weights"] = _libfann.fann_neuron_weights_set
__swig_getmethods__["weights"] = _libfann.fann_neuron_weights_get
if _newclass:weights = property(_libfann.fann_neuron_weights_get, _libfann.fann_neuron_weights_set)
__swig_setmethods__["connected_neurons"] = _libfann.fann_neuron_connected_neurons_set
__swig_getmethods__["connected_neurons"] = _libfann.fann_neuron_connected_neurons_get
if _newclass:connected_neurons = property(_libfann.fann_neuron_connected_neurons_get, _libfann.fann_neuron_connected_neurons_set)
__swig_setmethods__["num_connections"] = _libfann.fann_neuron_num_connections_set
__swig_getmethods__["num_connections"] = _libfann.fann_neuron_num_connections_get
if _newclass:num_connections = property(_libfann.fann_neuron_num_connections_get, _libfann.fann_neuron_num_connections_set)
__swig_setmethods__["value"] = _libfann.fann_neuron_value_set
__swig_getmethods__["value"] = _libfann.fann_neuron_value_get
if _newclass:value = property(_libfann.fann_neuron_value_get, _libfann.fann_neuron_value_set)
def __init__(self, *args):
_swig_setattr(self, fann_neuron, 'this', _libfann.new_fann_neuron(*args))
_swig_setattr(self, fann_neuron, 'thisown', 1)
def __del__(self, destroy=_libfann.delete_fann_neuron):
try:
if self.thisown: destroy(self)
except: pass
class fann_neuronPtr(fann_neuron):
def __init__(self, this):
_swig_setattr(self, fann_neuron, 'this', this)
if not hasattr(self,"thisown"): _swig_setattr(self, fann_neuron, 'thisown', 0)
_swig_setattr(self, fann_neuron,self.__class__,fann_neuron)
_libfann.fann_neuron_swigregister(fann_neuronPtr)
class fann_layer(_object):
__swig_setmethods__ = {}
__setattr__ = lambda self, name, value: _swig_setattr(self, fann_layer, name, value)
__swig_getmethods__ = {}
__getattr__ = lambda self, name: _swig_getattr(self, fann_layer, name)
def __repr__(self):
return "<C fann_layer instance at %s>" % (self.this,)
__swig_setmethods__["first_neuron"] = _libfann.fann_layer_first_neuron_set
__swig_getmethods__["first_neuron"] = _libfann.fann_layer_first_neuron_get
if _newclass:first_neuron = property(_libfann.fann_layer_first_neuron_get, _libfann.fann_layer_first_neuron_set)
__swig_setmethods__["last_neuron"] = _libfann.fann_layer_last_neuron_set
__swig_getmethods__["last_neuron"] = _libfann.fann_layer_last_neuron_get
if _newclass:last_neuron = property(_libfann.fann_layer_last_neuron_get, _libfann.fann_layer_last_neuron_set)
def __init__(self, *args):
_swig_setattr(self, fann_layer, 'this', _libfann.new_fann_layer(*args))
_swig_setattr(self, fann_layer, 'thisown', 1)
def __del__(self, destroy=_libfann.delete_fann_layer):
try:
if self.thisown: destroy(self)
except: pass
class fann_layerPtr(fann_layer):
def __init__(self, this):
_swig_setattr(self, fann_layer, 'this', this)
if not hasattr(self,"thisown"): _swig_setattr(self, fann_layer, 'thisown', 0)
_swig_setattr(self, fann_layer,self.__class__,fann_layer)
_libfann.fann_layer_swigregister(fann_layerPtr)
class fann(_object):
__swig_setmethods__ = {}
__setattr__ = lambda self, name, value: _swig_setattr(self, fann, name, value)
__swig_getmethods__ = {}
__getattr__ = lambda self, name: _swig_getattr(self, fann, name)
def __repr__(self):
return "<C fann instance at %s>" % (self.this,)
__swig_setmethods__["errno_f"] = _libfann.fann_errno_f_set
__swig_getmethods__["errno_f"] = _libfann.fann_errno_f_get
if _newclass:errno_f = property(_libfann.fann_errno_f_get, _libfann.fann_errno_f_set)
__swig_setmethods__["error_log"] = _libfann.fann_error_log_set
__swig_getmethods__["error_log"] = _libfann.fann_error_log_get
if _newclass:error_log = property(_libfann.fann_error_log_get, _libfann.fann_error_log_set)
__swig_setmethods__["errstr"] = _libfann.fann_errstr_set
__swig_getmethods__["errstr"] = _libfann.fann_errstr_get
if _newclass:errstr = property(_libfann.fann_errstr_get, _libfann.fann_errstr_set)
__swig_setmethods__["learning_rate"] = _libfann.fann_learning_rate_set
__swig_getmethods__["learning_rate"] = _libfann.fann_learning_rate_get
if _newclass:learning_rate = property(_libfann.fann_learning_rate_get, _libfann.fann_learning_rate_set)
__swig_setmethods__["connection_rate"] = _libfann.fann_connection_rate_set
__swig_getmethods__["connection_rate"] = _libfann.fann_connection_rate_get
if _newclass:connection_rate = property(_libfann.fann_connection_rate_get, _libfann.fann_connection_rate_set)
__swig_setmethods__["shortcut_connections"] = _libfann.fann_shortcut_connections_set
__swig_getmethods__["shortcut_connections"] = _libfann.fann_shortcut_connections_get
if _newclass:shortcut_connections = property(_libfann.fann_shortcut_connections_get, _libfann.fann_shortcut_connections_set)
__swig_setmethods__["first_layer"] = _libfann.fann_first_layer_set
__swig_getmethods__["first_layer"] = _libfann.fann_first_layer_get
if _newclass:first_layer = property(_libfann.fann_first_layer_get, _libfann.fann_first_layer_set)
__swig_setmethods__["last_layer"] = _libfann.fann_last_layer_set
__swig_getmethods__["last_layer"] = _libfann.fann_last_layer_get
if _newclass:last_layer = property(_libfann.fann_last_layer_get, _libfann.fann_last_layer_set)
__swig_setmethods__["total_neurons"] = _libfann.fann_total_neurons_set
__swig_getmethods__["total_neurons"] = _libfann.fann_total_neurons_get
if _newclass:total_neurons = property(_libfann.fann_total_neurons_get, _libfann.fann_total_neurons_set)
__swig_setmethods__["num_input"] = _libfann.fann_num_input_set
__swig_getmethods__["num_input"] = _libfann.fann_num_input_get
if _newclass:num_input = property(_libfann.fann_num_input_get, _libfann.fann_num_input_set)
__swig_setmethods__["num_output"] = _libfann.fann_num_output_set
__swig_getmethods__["num_output"] = _libfann.fann_num_output_get
if _newclass:num_output = property(_libfann.fann_num_output_get, _libfann.fann_num_output_set)
__swig_setmethods__["train_errors"] = _libfann.fann_train_errors_set
__swig_getmethods__["train_errors"] = _libfann.fann_train_errors_get
if _newclass:train_errors = property(_libfann.fann_train_errors_get, _libfann.fann_train_errors_set)
__swig_setmethods__["activation_function_hidden"] = _libfann.fann_activation_function_hidden_set
__swig_getmethods__["activation_function_hidden"] = _libfann.fann_activation_function_hidden_get
if _newclass:activation_function_hidden = property(_libfann.fann_activation_function_hidden_get, _libfann.fann_activation_function_hidden_set)
__swig_setmethods__["activation_function_output"] = _libfann.fann_activation_function_output_set
__swig_getmethods__["activation_function_output"] = _libfann.fann_activation_function_output_get
if _newclass:activation_function_output = property(_libfann.fann_activation_function_output_get, _libfann.fann_activation_function_output_set)
__swig_setmethods__["activation_steepness_hidden"] = _libfann.fann_activation_steepness_hidden_set
__swig_getmethods__["activation_steepness_hidden"] = _libfann.fann_activation_steepness_hidden_get
if _newclass:activation_steepness_hidden = property(_libfann.fann_activation_steepness_hidden_get, _libfann.fann_activation_steepness_hidden_set)
__swig_setmethods__["activation_steepness_output"] = _libfann.fann_activation_steepness_output_set
__swig_getmethods__["activation_steepness_output"] = _libfann.fann_activation_steepness_output_get
if _newclass:activation_steepness_output = property(_libfann.fann_activation_steepness_output_get, _libfann.fann_activation_steepness_output_set)
__swig_setmethods__["training_algorithm"] = _libfann.fann_training_algorithm_set
__swig_getmethods__["training_algorithm"] = _libfann.fann_training_algorithm_get
if _newclass:training_algorithm = property(_libfann.fann_training_algorithm_get, _libfann.fann_training_algorithm_set)
__swig_setmethods__["activation_results_hidden"] = _libfann.fann_activation_results_hidden_set
__swig_getmethods__["activation_results_hidden"] = _libfann.fann_activation_results_hidden_get
if _newclass:activation_results_hidden = property(_libfann.fann_activation_results_hidden_get, _libfann.fann_activation_results_hidden_set)
__swig_setmethods__["activation_values_hidden"] = _libfann.fann_activation_values_hidden_set
__swig_getmethods__["activation_values_hidden"] = _libfann.fann_activation_values_hidden_get
if _newclass:activation_values_hidden = property(_libfann.fann_activation_values_hidden_get, _libfann.fann_activation_values_hidden_set)
__swig_setmethods__["activation_results_output"] = _libfann.fann_activation_results_output_set
__swig_getmethods__["activation_results_output"] = _libfann.fann_activation_results_output_get
if _newclass:activation_results_output = property(_libfann.fann_activation_results_output_get, _libfann.fann_activation_results_output_set)
__swig_setmethods__["activation_values_output"] = _libfann.fann_activation_values_output_set
__swig_getmethods__["activation_values_output"] = _libfann.fann_activation_values_output_get
if _newclass:activation_values_output = property(_libfann.fann_activation_values_output_get, _libfann.fann_activation_values_output_set)
__swig_setmethods__["total_connections"] = _libfann.fann_total_connections_set
__swig_getmethods__["total_connections"] = _libfann.fann_total_connections_get
if _newclass:total_connections = property(_libfann.fann_total_connections_get, _libfann.fann_total_connections_set)
__swig_setmethods__["output"] = _libfann.fann_output_set
__swig_getmethods__["output"] = _libfann.fann_output_get
if _newclass:output = property(_libfann.fann_output_get, _libfann.fann_output_set)
__swig_setmethods__["num_MSE"] = _libfann.fann_num_MSE_set
__swig_getmethods__["num_MSE"] = _libfann.fann_num_MSE_get
if _newclass:num_MSE = property(_libfann.fann_num_MSE_get, _libfann.fann_num_MSE_set)
__swig_setmethods__["MSE_value"] = _libfann.fann_MSE_value_set
__swig_getmethods__["MSE_value"] = _libfann.fann_MSE_value_get
if _newclass:MSE_value = property(_libfann.fann_MSE_value_get, _libfann.fann_MSE_value_set)
__swig_setmethods__["train_error_function"] = _libfann.fann_train_error_function_set
__swig_getmethods__["train_error_function"] = _libfann.fann_train_error_function_get
if _newclass:train_error_function = property(_libfann.fann_train_error_function_get, _libfann.fann_train_error_function_set)
__swig_setmethods__["quickprop_decay"] = _libfann.fann_quickprop_decay_set
__swig_getmethods__["quickprop_decay"] = _libfann.fann_quickprop_decay_get
if _newclass:quickprop_decay = property(_libfann.fann_quickprop_decay_get, _libfann.fann_quickprop_decay_set)
__swig_setmethods__["quickprop_mu"] = _libfann.fann_quickprop_mu_set
__swig_getmethods__["quickprop_mu"] = _libfann.fann_quickprop_mu_get
if _newclass:quickprop_mu = property(_libfann.fann_quickprop_mu_get, _libfann.fann_quickprop_mu_set)
__swig_setmethods__["rprop_increase_factor"] = _libfann.fann_rprop_increase_factor_set
__swig_getmethods__["rprop_increase_factor"] = _libfann.fann_rprop_increase_factor_get
if _newclass:rprop_increase_factor = property(_libfann.fann_rprop_increase_factor_get, _libfann.fann_rprop_increase_factor_set)
__swig_setmethods__["rprop_decrease_factor"] = _libfann.fann_rprop_decrease_factor_set
__swig_getmethods__["rprop_decrease_factor"] = _libfann.fann_rprop_decrease_factor_get
if _newclass:rprop_decrease_factor = property(_libfann.fann_rprop_decrease_factor_get, _libfann.fann_rprop_decrease_factor_set)
__swig_setmethods__["rprop_delta_min"] = _libfann.fann_rprop_delta_min_set
__swig_getmethods__["rprop_delta_min"] = _libfann.fann_rprop_delta_min_get
if _newclass:rprop_delta_min = property(_libfann.fann_rprop_delta_min_get, _libfann.fann_rprop_delta_min_set)
__swig_setmethods__["rprop_delta_max"] = _libfann.fann_rprop_delta_max_set
__swig_getmethods__["rprop_delta_max"] = _libfann.fann_rprop_delta_max_get
if _newclass:rprop_delta_max = property(_libfann.fann_rprop_delta_max_get, _libfann.fann_rprop_delta_max_set)
__swig_setmethods__["train_slopes"] = _libfann.fann_train_slopes_set
__swig_getmethods__["train_slopes"] = _libfann.fann_train_slopes_get
if _newclass:train_slopes = property(_libfann.fann_train_slopes_get, _libfann.fann_train_slopes_set)
__swig_setmethods__["prev_steps"] = _libfann.fann_prev_steps_set
__swig_getmethods__["prev_steps"] = _libfann.fann_prev_steps_get
if _newclass:prev_steps = property(_libfann.fann_prev_steps_get, _libfann.fann_prev_steps_set)
__swig_setmethods__["prev_train_slopes"] = _libfann.fann_prev_train_slopes_set
__swig_getmethods__["prev_train_slopes"] = _libfann.fann_prev_train_slopes_get
if _newclass:prev_train_slopes = property(_libfann.fann_prev_train_slopes_get, _libfann.fann_prev_train_slopes_set)
def __init__(self, *args):
_swig_setattr(self, fann, 'this', _libfann.new_fann(*args))
_swig_setattr(self, fann, 'thisown', 1)
def __del__(self, destroy=_libfann.delete_fann):
try:
if self.thisown: destroy(self)
except: pass
class fannPtr(fann):
def __init__(self, this):
_swig_setattr(self, fann, 'this', this)
if not hasattr(self,"thisown"): _swig_setattr(self, fann, 'thisown', 0)
_swig_setattr(self, fann,self.__class__,fann)
_libfann.fann_swigregister(fannPtr)
class fann_train_data(_object):
__swig_setmethods__ = {}
__setattr__ = lambda self, name, value: _swig_setattr(self, fann_train_data, name, value)
__swig_getmethods__ = {}
__getattr__ = lambda self, name: _swig_getattr(self, fann_train_data, name)
def __repr__(self):
return "<C fann_train_data instance at %s>" % (self.this,)
__swig_setmethods__["errno_f"] = _libfann.fann_train_data_errno_f_set
__swig_getmethods__["errno_f"] = _libfann.fann_train_data_errno_f_get
if _newclass:errno_f = property(_libfann.fann_train_data_errno_f_get, _libfann.fann_train_data_errno_f_set)
__swig_setmethods__["error_log"] = _libfann.fann_train_data_error_log_set
__swig_getmethods__["error_log"] = _libfann.fann_train_data_error_log_get
if _newclass:error_log = property(_libfann.fann_train_data_error_log_get, _libfann.fann_train_data_error_log_set)
__swig_setmethods__["errstr"] = _libfann.fann_train_data_errstr_set
__swig_getmethods__["errstr"] = _libfann.fann_train_data_errstr_get
if _newclass:errstr = property(_libfann.fann_train_data_errstr_get, _libfann.fann_train_data_errstr_set)
__swig_setmethods__["num_data"] = _libfann.fann_train_data_num_data_set
__swig_getmethods__["num_data"] = _libfann.fann_train_data_num_data_get
if _newclass:num_data = property(_libfann.fann_train_data_num_data_get, _libfann.fann_train_data_num_data_set)
__swig_setmethods__["num_input"] = _libfann.fann_train_data_num_input_set
__swig_getmethods__["num_input"] = _libfann.fann_train_data_num_input_get
if _newclass:num_input = property(_libfann.fann_train_data_num_input_get, _libfann.fann_train_data_num_input_set)
__swig_setmethods__["num_output"] = _libfann.fann_train_data_num_output_set
__swig_getmethods__["num_output"] = _libfann.fann_train_data_num_output_get
if _newclass:num_output = property(_libfann.fann_train_data_num_output_get, _libfann.fann_train_data_num_output_set)
__swig_setmethods__["input"] = _libfann.fann_train_data_input_set
__swig_getmethods__["input"] = _libfann.fann_train_data_input_get
if _newclass:input = property(_libfann.fann_train_data_input_get, _libfann.fann_train_data_input_set)
__swig_setmethods__["output"] = _libfann.fann_train_data_output_set
__swig_getmethods__["output"] = _libfann.fann_train_data_output_get
if _newclass:output = property(_libfann.fann_train_data_output_get, _libfann.fann_train_data_output_set)
def __init__(self, *args):
_swig_setattr(self, fann_train_data, 'this', _libfann.new_fann_train_data(*args))
_swig_setattr(self, fann_train_data, 'thisown', 1)
def __del__(self, destroy=_libfann.delete_fann_train_data):
try:
if self.thisown: destroy(self)
except: pass
class fann_train_dataPtr(fann_train_data):
def __init__(self, this):
_swig_setattr(self, fann_train_data, 'this', this)
if not hasattr(self,"thisown"): _swig_setattr(self, fann_train_data, 'thisown', 0)
_swig_setattr(self, fann_train_data,self.__class__,fann_train_data)
_libfann.fann_train_data_swigregister(fann_train_dataPtr)
class fann_error(_object):
__swig_setmethods__ = {}
__setattr__ = lambda self, name, value: _swig_setattr(self, fann_error, name, value)
__swig_getmethods__ = {}
__getattr__ = lambda self, name: _swig_getattr(self, fann_error, name)
def __repr__(self):
return "<C fann_error instance at %s>" % (self.this,)
__swig_setmethods__["errno_f"] = _libfann.fann_error_errno_f_set
__swig_getmethods__["errno_f"] = _libfann.fann_error_errno_f_get
if _newclass:errno_f = property(_libfann.fann_error_errno_f_get, _libfann.fann_error_errno_f_set)
__swig_setmethods__["error_log"] = _libfann.fann_error_error_log_set
__swig_getmethods__["error_log"] = _libfann.fann_error_error_log_get
if _newclass:error_log = property(_libfann.fann_error_error_log_get, _libfann.fann_error_error_log_set)
__swig_setmethods__["errstr"] = _libfann.fann_error_errstr_set
__swig_getmethods__["errstr"] = _libfann.fann_error_errstr_get
if _newclass:errstr = property(_libfann.fann_error_errstr_get, _libfann.fann_error_errstr_set)
def __init__(self, *args):
_swig_setattr(self, fann_error, 'this', _libfann.new_fann_error(*args))
_swig_setattr(self, fann_error, 'thisown', 1)
def __del__(self, destroy=_libfann.delete_fann_error):
try:
if self.thisown: destroy(self)
except: pass
class fann_errorPtr(fann_error):
def __init__(self, this):
_swig_setattr(self, fann_error, 'this', this)
if not hasattr(self,"thisown"): _swig_setattr(self, fann_error, 'thisown', 0)
_swig_setattr(self, fann_error,self.__class__,fann_error)
_libfann.fann_error_swigregister(fann_errorPtr)
FANN_TRAIN_INCREMENTAL = _libfann.FANN_TRAIN_INCREMENTAL
FANN_TRAIN_BATCH = _libfann.FANN_TRAIN_BATCH
FANN_TRAIN_RPROP = _libfann.FANN_TRAIN_RPROP
FANN_TRAIN_QUICKPROP = _libfann.FANN_TRAIN_QUICKPROP
FANN_ERRORFUNC_LINEAR = _libfann.FANN_ERRORFUNC_LINEAR
FANN_ERRORFUNC_TANH = _libfann.FANN_ERRORFUNC_TANH
fann_run = _libfann.fann_run
fann_test = _libfann.fann_test
get_train_data_input = _libfann.get_train_data_input
get_train_data_output = _libfann.get_train_data_output
cvar = _libfann.cvar