Exemplo n.º 1
0
    def test_2d_decimate_active(self):
        shape = self.shape2D
        known_data = np.random.normal(size=shape).astype(np.float32).view(
            np.complex64)
        idata = bf.ndarray(known_data, space='cuda')
        odata = bf.empty((idata.shape[0] // 2, idata.shape[1]),
                         dtype=idata.dtype,
                         space='cuda')
        coeffs = self.coeffs * 1.0
        coeffs.shape += (1, )
        coeffs = np.repeat(coeffs, idata.shape[1], axis=1)
        coeffs.shape = (coeffs.shape[0], idata.shape[1])
        coeffs = bf.ndarray(coeffs, space='cuda')

        fir = Fir()
        fir.init(coeffs, 2)
        fir.execute(idata, odata)
        fir.execute(idata, odata)
        odata = odata.copy('system')

        for i in range(known_data.shape[1]):
            zf = lfiltic(self.coeffs, 1.0, 0.0)
            known_result, zf = lfilter(self.coeffs,
                                       1.0,
                                       known_data[:, i],
                                       zi=zf)
            known_result, zf = lfilter(self.coeffs,
                                       1.0,
                                       known_data[:, i],
                                       zi=zf)
            known_result = known_result[0::2]
            compare(odata[:, i], known_result)
Exemplo n.º 2
0
    def test_3d_initial(self):
        shape = self.shape3D
        known_data = np.random.normal(size=shape).astype(np.float32).view(
            np.complex64)
        idata = bf.ndarray(known_data, space='cuda')
        odata = bf.empty_like(idata)
        coeffs = self.coeffs * 1.0
        coeffs.shape += (1, )
        coeffs = np.repeat(coeffs, idata.shape[1] * idata.shape[2], axis=1)
        coeffs.shape = (coeffs.shape[0], idata.shape[1], idata.shape[2])
        coeffs = bf.ndarray(coeffs, space='cuda')

        fir = Fir()
        fir.init(coeffs, 1)
        fir.execute(idata, odata)
        odata = odata.copy('system')

        for i in range(known_data.shape[1]):
            for j in range(known_data.shape[2]):
                zf = lfiltic(self.coeffs, 1.0, 0.0)
                known_result, zf = lfilter(self.coeffs,
                                           1.0,
                                           known_data[:, i, j],
                                           zi=zf)
                compare(odata[:, i, j], known_result)
Exemplo n.º 3
0
    def test_2d_active(self):
        shape = self.shape2D
        known_data = np.random.normal(size=shape).astype(np.float32).view(
            np.complex64)
        idata = bf.ndarray(known_data, space='cuda_managed')
        odata = bf.empty_like(idata)
        coeffs = self.coeffs * 1.0
        coeffs.shape += (1, )
        coeffs = np.repeat(coeffs, idata.shape[1], axis=1)
        coeffs.shape = (coeffs.shape[0], idata.shape[1])
        coeffs = bf.ndarray(coeffs, space='cuda_managed')

        fir = Fir()
        fir.init(coeffs, 1)
        fir.execute(idata, odata)
        fir.execute(idata, odata)
        stream_synchronize()

        for i in range(known_data.shape[1]):
            zf = lfiltic(self.coeffs, 1.0, 0.0)
            known_result, zf = lfilter(self.coeffs,
                                       1.0,
                                       known_data[:, i],
                                       zi=zf)
            known_result, zf = lfilter(self.coeffs,
                                       1.0,
                                       known_data[:, i],
                                       zi=zf)
            compare(odata[:, i], known_result)