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Artificial Neural Networks made easy with the FANN library

, 28 Aug 2013
Neural networks are typically associated with specialised applications, developed only by select groups of experts. This misconception has had a highly negative effect on its popularity. Hopefully, the FANN library will help fill this gap.
fann-1_2_0.zip
fann-1.2.0
debian
changelog
compat
control
copyright
docs
libfann1-dev.dirs
libfann1-dev.examples
libfann1-dev.files
libfann1-dev.install
libfann1.dirs
libfann1.files
libfann1.install
rules
doc
fann_doc_complete_1.0.pdf
Makefile
html
src
include
Makefile.in
Makefile.am
Makefile.in
COPYING
Makefile.am
win32_dll
examples
makefile
README
Makefile.in
configure
AUTHORS
COPYING
ChangeLog
INSTALL
Makefile.am
NEWS
TODO
aclocal.m4
config.guess
config.sub
configure.in
depcomp
fann.pc.in
fann.spec.in
install-sh
ltmain.sh
missing
mkinstalldirs
benchmarks
datasets
building.test
building.train
diabetes.test
diabetes.train
gene.test
gene.train
mushroom.test
mushroom.train
robot.test
robot.train
soybean.test
soybean.train
thyroid.test
thyroid.train
two-spiral.train
pumadyn-32fm.test
pumadyn-32fm.train
two-spiral.test
parity8.train
parity8.test
parity13.test
parity13.train
Makefile
README
benchmark.sh
benchmarks.pdf
gnuplot
performance.cc
quality.cc
.cvsignore
examples
Makefile
xor.data
python
README
examples
libfann.i
makefile.gnu
makefile.msvc
libfann.pyc
MSVC++
libfann.dsp
all.dsw
simple_test.dsp
simple_train.dsp
steepness_train.dsp
xor_test.dsp
xor_train.dsp
config.in
fann_win32_dll-1_2_0.zip
changelog
compat
control
copyright
docs
libfann1-dev.dirs
libfann1-dev.examples
libfann1-dev.files
libfann1-dev.install
libfann1.dirs
libfann1.files
libfann1.install
rules
fann_doc_complete_1.0.pdf
Makefile
Makefile.in
Makefile.am
Makefile.in
COPYING
Makefile.am
makefile
README
Makefile.in
configure
AUTHORS
COPYING
ChangeLog
INSTALL
Makefile.am
NEWS
TODO
aclocal.m4
config.guess
config.sub
configure.in
depcomp
fann.pc.in
fann.spec.in
install-sh
ltmain.sh
missing
mkinstalldirs
building.test
building.train
diabetes.test
diabetes.train
gene.test
gene.train
mushroom.test
mushroom.train
robot.test
robot.train
soybean.test
soybean.train
thyroid.test
thyroid.train
two-spiral.train
pumadyn-32fm.test
pumadyn-32fm.train
two-spiral.test
parity8.train
parity8.test
parity13.test
parity13.train
Makefile
README
benchmark.sh
benchmarks.pdf
gnuplot
performance.cc
quality.cc
.cvsignore
Makefile
xor.data
README
libfann.i
makefile.gnu
makefile.msvc
libfann.pyc
libfann.dsp
all.dsw
simple_test.dsp
simple_train.dsp
steepness_train.dsp
xor_test.dsp
xor_train.dsp
config.in
bin
fanndoubled.dll
fanndoubled.lib
fanndoubleMTd.dll
fanndoubleMTd.lib
fannfixedd.dll
fannfixedd.lib
fannfixedMTd.dll
fannfixedMTd.lib
fannfloatd.dll
fannfloatd.lib
fannfloatMTd.dll
fannfloatMTd.lib
fanndouble.dll
fanndouble.lib
fanndoubleMT.dll
fanndoubleMT.lib
fannfixed.dll
fannfixed.lib
fannfixedMT.dll
fannfixedMT.lib
fannfloat.dll
fannfloat.lib
fannfloatMT.dll
fannfloatMT.lib
vs_net2003.zip
VS.NET2003
# 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

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