コード例 #1
0
def proc_info(info, f, data, fn, noisedata):
    info_list = info.upper().split()
    if len(info_list) == 5:
        info = freq_mult, twoporttype, datatype, rtype, z0 = info_list
    elif len(info_list) == 3:
        info = freq_mult, twoporttype, datatype = info_list
        z0 = 1.
    else:
        msg = ("# format should only have 5 values this one has %d" %
               len(info_list))
        raise TouchstoneError(msg)
    z0 = float(z0)
    f = f * freqmultdict[freq_mult]
    if fn is not None:
        fn = fn * freqmultdict[freq_mult]

    convfunc = dict(RI=re_im_to_complex,
                    DB=dB_angle_to_complex,
                    MA=mag_angle_to_complex)

    if datatype not in convfunc:
        pars = datatype
        msg = "Unknown dataformat: %s, valid formats: RI, DB, MAG" % pars
        raise TouchstoneError(msg)

    out = np.empty((data.shape[0], data.shape[1] // 2), dtype=np.complex128)

    out[...] = convfunc[datatype](data[:, ::2], data[:, 1::2])
    if out.shape[1] == 1:
        out.shape = (out.shape[0], 1, 1)
    elif out.shape[1] == 4:
        out.shape = (out.shape[0], 2, 2)
        out = out.transpose(0, 2, 1)
    else:
        N = int(sqrt(out.shape[1]))
        out.shape = (out.shape[0], N, N)

    dims = (DimSweep("freq", f, unit="Hz"), )
    if fn is not None and len(f) == len(fn) and np.allclose(f, fn):
        noisedims = dims
    elif fn is None:
        noisedims = None
    else:
        noisedims = (DimSweep("freqn", fn, unit="Hz"), )
    out = make_matrix(out, dims)
    f = hfarray(f, dims)
    db = DataBlock()
    db[info[1]] = out
    if noisedata is not None:
        db.Rn = hfarray(noisedata[..., -1], dims=noisedims) * z0
        db.Fmin = 10**(hfarray(noisedata[..., 0], dims=noisedims) / 10)
        db.Gopt = hfarray(convfunc[datatype](noisedata[:, 1], noisedata[:, 2]),
                          dims=noisedims)
    db.Z0 = hfarray(z0, unit="Ohm")
    return db
コード例 #2
0
ファイル: touchstone.py プロジェクト: hftools/hftools
def proc_info(info, f, data, fn, noisedata):
    info_list = info.upper().split()
    if len(info_list) == 5:
        info = freq_mult, twoporttype, datatype, rtype, z0 = info_list
    elif len(info_list) == 3:
        info = freq_mult, twoporttype, datatype = info_list
        z0 = 1.
    else:
        msg = ("# format should only have 5 values this one has %d" %
               len(info_list))
        raise TouchstoneError(msg)
    z0 = float(z0)
    f = f * freqmultdict[freq_mult]
    if fn is not None:
        fn = fn * freqmultdict[freq_mult]

    convfunc = dict(RI=re_im_to_complex,
                    DB=dB_angle_to_complex,
                    MA=mag_angle_to_complex)

    if datatype not in convfunc:
        pars = datatype
        msg = "Unknown dataformat: %s, valid formats: RI, DB, MAG" % pars
        raise TouchstoneError(msg)

    out = np.empty((data.shape[0], data.shape[1] // 2), dtype=np.complex128)

    out[...] = convfunc[datatype](data[:, ::2],  data[:, 1::2])
    if out.shape[1] == 1:
        out.shape = (out.shape[0], 1, 1)
    elif out.shape[1] == 4:
        out.shape = (out.shape[0], 2, 2)
        out = out.transpose(0, 2, 1)
    else:
        N = int(sqrt(out.shape[1]))
        out.shape = (out.shape[0], N, N)

    dims = (DimSweep("freq", f, unit="Hz"), )
    if fn is not None and len(f) == len(fn) and np.allclose(f, fn):
        noisedims = dims
    elif fn is None:
        noisedims = None
    else:
        noisedims = (DimSweep("freqn", fn, unit="Hz"), )
    out = make_matrix(out, dims)
    f = hfarray(f, dims)
    db = DataBlock()
    db[info[1]] = out
    if noisedata is not None:
        db.Rn = hfarray(noisedata[..., -1], dims=noisedims) * z0
        db.Fmin = 10 ** (hfarray(noisedata[..., 0], dims=noisedims) / 10)
        db.Gopt = hfarray(convfunc[datatype](noisedata[:, 1], noisedata[:, 2]),
                          dims=noisedims)
    db.Z0 = hfarray(z0, unit="Ohm")
    return db
コード例 #3
0
    def noise_parameters(self, partial=False):
        db = DataBlock()
        db.S = SArray(self.N)
        if isinstance(self.N, ABCDArray):
            CA = self.C / (2 * k * 290)
            CA11 = CA[..., 0, 0]
            CA12 = CA[..., 0, 1]
            CA22 = CA[..., 1, 1]
            Rn = CA11.real
            Yopt = (np.sqrt(CA22 / CA11 - (CA12.imag / CA11) ** 2) +
                    1j * (CA12.imag / CA11))
            Fmin = 1 + (CA12 + CA11 * Yopt.conj()).real
            if partial:
                db.CA = CA
            db.Rn = Rn
            db.Yopt = Yopt
            db.Fmin = Fmin
            db.Gopt = (1 / 50. - Yopt) / (1 / 50. + Yopt)
            return db

        N = self.convert(YArray)
        Y11 = N.N[..., 0, 0]
        Y21 = N.N[..., 1, 0]
        C = N.C / (4 * k * 290)
        CY11 = C[..., 0, 0]
        CY12 = C[..., 0, 1]
        CY22 = C[..., 1, 1]
        Rn = (CY22 / abs(Y21) ** 2).real
        Ycor = Y11 - CY12 / CY22 * Y21
        Gn = (CY11 - abs(Y11 - Ycor) ** 2 * Rn).real
        Yopt = np.sqrt(Gn / Rn + Ycor.real ** 2) - 1j * Ycor.imag
        Fmin = 1 + 2 * Rn * (Ycor.real + Yopt.real)

        db.CY = C
        db.Gn = Gn
        db.Ycor = Ycor
        db.S = SArray(self.N)
        db.Rn = Rn
        db.Fmin = Fmin
        db.Gopt = (1 / 50. - Yopt) / (1 / 50. + Yopt)
        db.Yopt = Yopt
        return db