def load(self, fname):
        f = open(fname)
        c = []
        # the first line determines whether we interpret the file as
        # giving min/max of features or mean/std
        x = f.readline()
        self.meanstd = False if x == 'x' else True

        # the next line gives the normalization bounds
        bounds = array(f.readline().split()).astype(float)
        for line in f:
            c.append(array(line.split()).astype(float)[1:])
        self.dim = len(c)
        c = array(c)
        self.par1 = c[:, 0]
        self.par2 = c[:, 1]
        self.scale = (c[:, 1] - c[:, 0]) / (bounds[1] - bounds[0])
        self.newmin = bounds[0]
        self.newmax = bounds[1]
dataset/ETHPy150Open pybrain/pybrain/pybrain/tools/datasettools.py/DataSetNormalizer.load/swapped operands of `/`