ml_python/rbfn.py at main · Levorilh/ml_python · GitHub

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import numpy as np
from ctypes import *
from settings import *

def as_C_array(dataset, datatype=c_float):
    arr_size = len(dataset)
    arr_type = datatype * arr_size
    arr = arr_type(*dataset)
    return arr, arr_type


def create_rbfn_model(input_dim, num_classes, k):
    mylib.create_rbfn_model.argtypes = [c_int, c_int, c_int]
    mylib.create_rbfn_model.restype = c_void_p
    return mylib.create_rbfn_model(input_dim, num_classes, k)


def destroy_rbfn_model(model):
    mylib.destroy_rbfn_model.argtypes = [c_void_p]
    mylib.destroy_rbfn_model.restype = None
    mylib.destroy_rbfn_model(model)


def train_rbfn_model(model, dataset_inputs, dataset_expected_outputs, naif=True, max_iters=100):
    samples_count = len(dataset_inputs)
    flattened_dataset_inputs = np.array(dataset_inputs).flatten()
    flattened_dataset_expected_outputs = np.array(dataset_expected_outputs).flatten()
    arr_input, input_type = as_C_array(flattened_dataset_inputs, c_double)
    arr_output, output_type = as_C_array(flattened_dataset_expected_outputs, c_double)
    mylib.train_rbfn_model.argtypes = [c_void_p, input_type, c_int, output_type, c_bool, c_int]
    mylib.train_rbfn_model.restype = None
    mylib.train_rbfn_model(model, arr_input, samples_count, arr_output, naif, max_iters)


def predict_rbfn(model, dataset_inputs, num_classes=2):
    flattened_dataset_inputs = np.array(dataset_inputs).flatten()
    arr, arr_type = as_C_array(flattened_dataset_inputs, c_double)
    mylib.predict_rbfn.argtypes = [c_void_p, arr_type]
    mylib.predict_rbfn.restype = POINTER(c_double)
    predict_value = mylib.predict_rbfn(model, arr)
    rslt = list(np.ctypeslib.as_array(predict_value, (num_classes,)))
    destroy_rbfn_prediction(predict_value)
    return rslt


def destroy_rbfn_prediction(prediction):
    mylib.destroy_rbfn_prediction.argtypes = [POINTER(c_double)]
    mylib.destroy_rbfn_prediction.restype = None
    mylib.destroy_rbfn_prediction(prediction)

def save_rbf_model(model, path):
    mylib.save_rbf_model.argtypes = [c_void_p, c_char_p]
    mylib.save_rbf_model.restype = None
    mylib.save_rbf_model(model, bytes(path, 'utf-8'))

def load_rbf_model(path):
    mylib.load_rbf_model.argtypes = [c_char_p]
    mylib.load_rbf_model.restype = c_void_p
    p_model = mylib.load_rbf_model(bytes(path, 'utf-8'))

    if not p_model:
        print("le modele n'a pas pu être créé")
        raise ValueError()

    return p_model