initiating_dea

gistfile1.txt

class DEA(object):
    random.seed(5)
    def __init__(self, inputs, outputs):
        """
        Initialize the DEA object with input data
        n = number of entities (observations)
        m = number of inputs (variables, features)
        r = number of outputs
        :param inputs: inputs, n x m numpy array
        :param outputs: outputs, n x r numpy array
        :return: self
        """
        # supplied data
        self.inputs = inputs
        self.outputs = outputs
        # parameters
        self.n = inputs.shape[0]
        self.m = inputs.shape[1]
        self.r = outputs.shape[1]
        # iterators
        self.unit_ = range(self.n)
        self.input_ = range(self.m)
        self.output_ = range(self.r)
        # result arrays
        self.output_w = np.zeros((self.r, 1), dtype=np.float)  # output weights
        self.input_w = np.zeros((self.m, 1), dtype=np.float)  # input weights
        self.lambdas = np.zeros((self.n, 1), dtype=np.float)  # unit efficiencies
        self.efficiency = np.zeros_like(self.lambdas)  # thetas
        # names
        self.names = []