Ejemplo n.º 1
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def lourenco_eq_dist_mp(mgamma, m, sigma, Ne, Ne_scal, scal_fac=1):
    s = mgamma / 2. / Ne_scal * scal_fac
    #s = mgamma
    prob = mp.power(2, (1 - m) / 2.) * mp.power(Ne, 0.5) * mp.power(
        mp.fabs(s),
        (m - 1) / 2.) * (1 + 1 / (Ne * mp.power(sigma, 2.))) * mp.exp(
            -Ne * s) / (mp.power(mp.pi, 0.5) * mp.power(sigma, m) *
                        mp.gamma(m / 2.)) * mp.besselk(
                            (m - 1) / 2.,
                            Ne * mp.fabs(s) *
                            mp.power(1 + 1 / (Ne * mp.power(sigma, 2.)), 0.5))
    return float(prob / 2 / Ne_scal * scal_fac)
Ejemplo n.º 2
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def check_zero(expression, verbose=False):
    # Setting precision
    precision = 30 # 30 sig digits
    mp.dps = precision

    free_symbols_dict = dict()

    # Setting each variable in free_symbols_set to a random number in [0, 1) according to the hashed string
    # representation of each variable.
    for var in expression.free_symbols:
        # Make sure M_PI is set to its correct value, pi
        if str(var) == "M_PI":
            free_symbols_dict[var] = mp.mpf(pi)
        # Then make sure M_SQRT1_2 is set to its correct value, 1/sqrt(2)
        elif str(var) == "M_SQRT1_2":
            free_symbols_dict[var] = mp.mpf(1.0/sqrt(2.0))
        # All other free variables are set to random numbers
        else:
            # Take the variable [var], turn it into a string, encode the string, hash the string using the md5
            # algorithm, turn the hash into a hex number, turn the hex number into an int, set the random seed to
            # that int. This ensures each variable gets a unique but consistent value.
            random.seed(int(hashlib.md5(str(var).encode()).hexdigest(), 16))
            # Store the random value in free_symbols_dict as a mpf
            free_symbols_dict[var] = mp.mpf(random.random())
            # Warning: might slow Travis CI too much: logging.debug(' ...Setting '+str(var)+' to the random value: '+str(free_symbols_dict[var]))

    # Using SymPy's cse algorithm to optimize our value substitution
    replaced, reduced = cse_postprocess(sp.cse(expression, order='none'))

    # Warning: might slow Travis CI too much: logging.debug(' var = '+str(var)+' |||| replaced = '+str(replaced))

    # Calculate our result_value
    result_value = calculate_value(free_symbols_dict, replaced, reduced)

    # Check if result_value is near-zero, and double checking if it should be zero
    if mp.fabs(result_value) != mp.mpf('0.0') and mp.fabs(result_value) < 10 ** ((-2.0/3)*precision):
        if verbose:
            print("Found |result| (" + str(mp.fabs(result_value)) + ") close to zero. "
                         "Checking if indeed it should be zero.")
        new_result_value = calculate_value(free_symbols_dict, replaced, reduced, precision_factor=2)
        if mp.fabs(new_result_value) < 10 ** (-(4.0/3) * precision):
            if verbose:
                print("After re-evaluating with twice the digits of precision, |result| dropped to " +
                             str(new_result_value) + ". Setting value to zero")
            result_value = mp.mpf('0.0')

    # Store result_value in calculated_dict
    if result_value == mp.mpf('0.0'):
        return True
    return False
Ejemplo n.º 3
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def takagi_fact(a):
    A = mp.matrix(a)
    sing_vs, Q = symmetric_svd(A)
    phase_mat = mp.diag(
        [mp.exp(-1j * mp.arg(sing_v) / 2.0) for sing_v in sing_vs])

    vs = [mp.fabs(sing_v) for sing_v in sing_vs]
    Qp = Q * phase_mat

    return vs, Qp
Ejemplo n.º 4
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def MPDBsc(M):
    Xk = M.copy()
    Yk = mp.eye(M.cols)
    dA = mp.det(M)**(mp.mpf('1.0')/2)
    for i in range(1,30):
        uk = mp.fabs(mp.det(Xk)/dA)**(-1.0/i)
        Xk1 = (uk*Xk + (uk**(-1))*(Yk**(-1)))/2
        Yk1 = (uk*Yk + (uk**(-1))*(Xk**(-1)))/2
        Xk = Xk1
        Yk = Yk1

    return Xk
Ejemplo n.º 5
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    def run(qtype, FW, R, alpha=0, beta=0):
        X, W = mp.gauss_quadrature(n, qtype, alpha=alpha, beta=beta)

        a = 0
        for i in xrange(len(X)):
            a += W[i] * F(X[i])

        b = mp.quad(lambda x: FW(x) * F(x), R)

        c = mp.fabs(a - b)

        if verbose:
            print(qtype, c, a, b)

        assert c < 1e-5
Ejemplo n.º 6
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    def run(qtype, FW, R, alpha = 0, beta = 0):
        X, W = mp.gauss_quadrature(n, qtype, alpha = alpha, beta = beta)

        a = 0
        for i in xrange(len(X)):
            a += W[i] * F(X[i])

        b = mp.quad(lambda x: FW(x) * F(x), R)

        c = mp.fabs(a - b)

        if verbose:
            print(qtype, c, a, b)

        assert c < 1e-5
Ejemplo n.º 7
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def iterations_to_escape_ap(c, max_iterations=100):
    """ Calculate the number of iterations to escape the mandelbrot set.

    Uses arbitrary precision for calculations. Returns an (interpolated)
    mpmath floating point value. If no escape, returns a value greater
    than max_iterations.
    """
    iterations = 0
    z = mp.mpc(0)
    while mp.mag(z) < ESCAPE_MAGNITUDE:
        iterations += 1
        if iterations > max_iterations:
            break
        z = z * z + c
    inner_log = mp.log(mp.fabs(z) / ESCAPE_MAGNITUDE)
    if inner_log.real > 0:
        adjustment = 1 - mp.log(inner_log, b=2)
    else:
        adjustment = 0
    return float(iterations + adjustment)
Ejemplo n.º 8
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def plot_RgMmn_g22_g33_g12_g23(n,
                               k,
                               Rmin,
                               Rmax,
                               klim=10,
                               Taylor_tol=1e-4,
                               Rnum=50):
    Rlist = np.linspace(Rmin, Rmax, Rnum)
    absg11list = np.zeros_like(Rlist)
    g22list = np.zeros_like(Rlist)
    g33list = np.zeros_like(Rlist)
    g12list = np.zeros_like(Rlist)
    g23list = np.zeros_like(Rlist)
    rholist = np.zeros_like(Rlist)
    for i in range(Rnum):
        print(i)
        R = Rlist[i]
        rholist[i] = mp_rho_M(n, k * R)
        Gmat = speedup_Green_Taylor_Arnoldi_RgMmn_oneshot(
            n, k, R, 3, klim, Taylor_tol)  #vecnum=3 for the elements we need
        absg11list[i] = mp.fabs(Gmat[0, 0])
        g22list[i] = mp.re(Gmat[1, 1])  #note the indexing off-by-one
        g33list[i] = mp.re(Gmat[2, 2])
        g12list[i] = mp.re(Gmat[0, 1])
        g23list[i] = mp.re(Gmat[1, 2])

    normalRlist = Rlist * k / (2 * np.pi)  #R/lambda list
    plt.figure()
    plt.plot(normalRlist, g22list, '-r', label='$G_{22}$')
    plt.plot(normalRlist, g12list, '--r', label='$G_{12}$')
    plt.plot(normalRlist, g33list, '-b', label='$G_{33}$')
    plt.plot(normalRlist, g23list, '--b', label='$G_{23}$')
    plt.plot(normalRlist, absg11list, '-k', label='$|G_{11}|$')
    plt.plot(normalRlist, rholist, '--k', label='$\\rho_M$')

    plt.xlabel('$R/\lambda$', **axisfont)
    plt.title(
        'Green Function matrix elements \n for Arnoldi family radial number n='
        + str(n), **axisfont)
    plt.legend()
    plt.show()
Ejemplo n.º 9
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def _eigenvals_eigenvects_mpmath(M):
    norm2 = lambda v: mp.sqrt(sum(i**2 for i in v))

    v1 = None
    prec = max([x._prec for x in M.atoms(Float)])
    eps = 2**-prec

    while prec < DEFAULT_MAXPREC:
        with workprec(prec):
            A = mp.matrix(M.evalf(n=prec_to_dps(prec)))
            E, ER = mp.eig(A)
            v2 = norm2([i for e in E for i in (mp.re(e), mp.im(e))])
            if v1 is not None and mp.fabs(v1 - v2) < eps:
                return E, ER
            v1 = v2
        prec *= 2

    # we get here because the next step would have taken us
    # past MAXPREC or because we never took a step; in case
    # of the latter, we refuse to send back a solution since
    # it would not have been verified; we also resist taking
    # a small step to arrive exactly at MAXPREC since then
    # the two calculations might be artificially close.
    raise PrecisionExhausted
Ejemplo n.º 10
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Zc = mp.matrix(f.size, 1)
A = np.ndarray(f.size)
R = np.ndarray(f.size)
I = np.ndarray(f.size)
Gr = np.ndarray(f.size)
Gi = np.ndarray(f.size)

for n in range(f.size):
    Zap[n] = ZapA[n]*( i0(gammac[n]*a) / i1(gammac[n]*a) )
    Zbp[n] = ZbpA[n] * ((i0(gammac[n]*b) * k1(gammac[n]*c) + k0(gammac[n]*b)*i1(gammac[n]*c)) / ( i1(gammac[n]*c)*k1(gammac[n]*b) - i1(gammac[n]*b)*k1(gammac[n]*c) ) )
    ZL[n] = 1j*omega[n]*Lp
    YC[n] = 1j*omega[n]*Cp
    Zp[n] = Zap[n] + Zbp[n] + ZL[n]
    Yp[n] = YC[n] # + G[n]
    Zc[n] = mp.sqrt(Zp[n]/Yp[n])
    A[n] = mp.fabs(Zc[n])
    R[n] = mp.re(Zc[n])
    I[n] = mp.im(Zc[n])
    Gr[n] = mp.re(mp.sqrt(Zp[n]*Yp[n]))
    Gi[n] = mp.im(mp.sqrt(Zp[n]*Yp[n]))

fig = plt.figure()
plt.plot(f/10**6, A, label='Magnitude', color='red')
plt.xlabel('Frequency [MHz]')
plt.ylabel('Magnitude of Z$_{c}$ [$\Omega$]')
plt.legend()
plt.xlim([-0.3,100])
#plt.show()
fig2 = plt.figure()
plt.plot(f/10**6, R, label='Real Part', color='red')
plt.xlabel('Frequency [MHz]')
Ejemplo n.º 11
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def Abs(a):
    return mp.fabs(a)
Ejemplo n.º 12
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def Abs(a):
    return mp.fabs(a)
Ejemplo n.º 13
0
    def run_posit_2op_exhaustive(self,
                                 op_str=None,
                                 nbits_range=None,
                                 es_range=None):
        op = None
        mpop = None
        if op_str == '+':
            op = PCPosit.__add__
            mpop = mp.mpf.__add__
        elif op_str == '-':
            op = PCPosit.__sub__
            mpop = mp.mpf.__sub__
        elif op_str == '*':
            op = PCPosit.__mul__
            mpop = mp.mpf.__mul__
        elif op_str == '/':
            op = PCPosit.__truediv__
            mpop = mp.mpf.__truediv__
        else:
            raise NotImplementedError("op={}".format(op_str))

        if nbits_range is None:
            nbits_range = self.nbits_range
        if es_range is None:
            es_range = self.es_range

        for nbits in nbits_range:
            mask = bitops.create_mask(nbits)
            cinf_bits = 1 << (nbits - 1)
            is_special = lambda bits: bits == 0 or bits == cinf_bits
            is_normal = lambda bits: not is_special(bits)
            for es in es_range:
                for abits in range(2**nbits):
                    for bbits in range(2**nbits):
                        a = PCPosit(abits, nbits=nbits, es=es, mode='bits')
                        b = PCPosit(bbits, nbits=nbits, es=es, mode='bits')
                        c = op(a, b)
                        cbits = coder.encode_posit_binary(c.rep)

                        test_info = {
                            'nbits': nbits,
                            'es': es,
                            'a': str(a),
                            'b': str(b),
                            'c': str(c),
                            'abits': abits,
                            'bbits': bbits,
                            'cbits': cbits,
                            'arep': a.rep,
                            'brep': b.rep,
                            'crep': c.rep,
                        }

                        if is_normal(abits) and is_normal(
                                bbits) and cbits == 0:
                            self.assertTrue(op_str in ['+', '-'])
                            if op_str == '+':
                                self.assertEqual(abits, -bbits & mask)
                            else:  # '-'
                                self.assertEqual(abits, bbits)

                        elif is_normal(abits) and is_normal(bbits):
                            self.assertNotEqual(cbits, 0)
                            self.assertNotEqual(cbits, cinf_bits)

                            amp = mp.mpf(
                                eval(coder.positrep_to_rational_str(a.rep)))
                            bmp = mp.mpf(
                                eval(coder.positrep_to_rational_str(b.rep)))
                            c2mp = mpop(amp, bmp)

                            c0bits = (cbits - 1) & mask
                            while c0bits == 0 or c0bits == cinf_bits:
                                c0bits = (c0bits - 1) & mask

                            c1bits = (cbits + 1) & mask
                            while c1bits == 0 or c1bits == cinf_bits:
                                c1bits = (c1bits + 1) & mask

                            c0 = PCPosit(c0bits,
                                         nbits=nbits,
                                         es=es,
                                         mode='bits')
                            c1 = PCPosit(c1bits,
                                         nbits=nbits,
                                         es=es,
                                         mode='bits')

                            test_info['c0'] = str(c0)
                            test_info['c1'] = str(c1)
                            test_info['c0bits'] = c0bits
                            test_info['c1bits'] = c1bits
                            test_info['c0rep'] = c0.rep
                            test_info['c1rep'] = c1.rep

                            rcmp = mp.mpf(
                                eval(coder.positrep_to_rational_str(c.rep)))
                            cratiodiffmp = mp.fabs(mp.log(
                                rcmp / c2mp)) if c2mp != 0 else mp.fabs(rcmp -
                                                                        c2mp)
                            cabsdiffmp = mp.fabs(rcmp - c2mp)

                            c0mp = mp.mpf(
                                eval(coder.positrep_to_rational_str(c0.rep)))
                            c0ratiodiffmp = mp.fabs(mp.log(
                                c0mp / c2mp)) if c2mp != 0 else mp.fabs(c0mp -
                                                                        c2mp)
                            c0absdiffmp = mp.fabs(c0mp - c2mp)
                            self.assertTrue(
                                cratiodiffmp <= c0ratiodiffmp
                                or cabsdiffmp <= c0absdiffmp, test_info)

                            c1mp = mp.mpf(
                                eval(coder.positrep_to_rational_str(c1.rep)))
                            c1ratiodiffmp = mp.fabs(mp.log(
                                c1mp / c2mp)) if c2mp != 0 else mp.fabs(c1mp -
                                                                        c2mp)
                            c1absdiffmp = mp.fabs(c1mp - c2mp)
                            self.assertTrue(
                                cratiodiffmp <= c1ratiodiffmp
                                or cabsdiffmp <= c1absdiffmp, test_info)

                        elif abits == cinf_bits:
                            self.assertTrue(op_str in ['+', '-', '*', '/'])
                            self.assertEqual(cbits, cinf_bits)

                        elif abits != cinf_bits and bbits == cinf_bits:
                            self.assertTrue(op_str in ['+', '-', '*', '/'])
                            if op_str == '/':
                                self.assertEqual(cbits, 0)
                            else:
                                self.assertEqual(cbits, cinf_bits)

                        elif abits == 0 and bbits == 0:
                            self.assertTrue(op_str in ['+', '-', '*', '/'])
                            if op_str == '/':
                                self.assertEqual(cbits, cinf_bits)
                            else:
                                self.assertEqual(cbits, 0)

                        elif is_normal(abits) and bbits == 0:
                            if op_str == '+' or op_str == '-':
                                self.assertEqual(cbits, abits)
                            elif op_str == '*':
                                self.assertEqual(cbits, 0)
                            elif op_str == '/':
                                self.assertEqual(cbits, cinf_bits)
                            else:
                                self.assertTrue(False)

                        elif abits == 0 and is_normal(bbits):
                            self.assertTrue(op_str in ['+', '-', '*', '/'])
                            if op_str == '+':
                                self.assertEqual(cbits, bbits)
                            elif op_str == '-':
                                self.assertEqual(cbits, -bbits & mask)
                            else:
                                self.assertEqual(cbits, 0)

                        else:
                            self.assertTrue(False)
Ejemplo n.º 14
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def S_Kummer(beta0, kc, L, order, qmax):
    """Compute even and odd coefficents at an order number"""
    K = 2 * pi / L
    beta_n = lambda n: beta0 + n * K
    gamma_n = lambda n: -1j * np.sqrt(kc ** 2 - beta_n(n) ** 2 + 0j)
    theta_n = lambda n: np.arcsin(beta_n(n) / kc - 1j * np.sign(n) * np.spacing(1))

    if order == 0:
        qs = np.hstack([np.arange(-qmax, 0), np.arange(1, qmax + 1)])

        S0sum = 1 / gamma_n(qs) - 1 / (K * np.abs(qs)) \
            - (kc ** 2 + 2 * beta0 ** 2) / (2 * K ** 3 * np.abs(qs) ** 3)

        S0sum = np.sum(S0sum)

        S0 = -1 - (2j / pi) * (np.euler_gamma + np.log(kc / (2 * K))) \
        - 2j / (gamma_n(0) * L) \
        - 2j * (kc ** 2 + 2 * beta0 ** 2) * zeta(3) / (K ** 3 * L) \
        - (2j / L) * S0sum

        return S0

    qs = np.arange(1, qmax + 1)

    oeven = 2 * order
    oodd = 2 * order - 1
    # Even sum with wavenumber terms, large terms excluded
    SEsum0 = np.exp(-1j * oeven * theta_n(qs)) / gamma_n(qs) \
        + np.exp(1j * oeven * theta_n(-qs)) / gamma_n(-qs)
    SEsum0 = SEsum0.sum()
    SEsum0 += np.exp(-1j * oeven * theta_n(0)) / gamma_n(0)
    SEsum0 *= -2j / L

    # Odd sum with wavenumber terms, large terms excluded
    SOsum0 = np.exp(-1j * oodd * theta_n(qs)) / gamma_n(qs) \
        - np.exp(1j * oodd * theta_n(-qs)) / gamma_n(-qs)
    SOsum0 = SOsum0.sum()
    SOsum0 += np.exp(-1j * oodd * theta_n(0)) / gamma_n(0)
    SOsum0 *= 2j / L

    # Even sum with factorial terms
    ms = np.arange(1., order + 1)
    b = np.array([float(mp.bernpoly(2 * m, beta0 / K)) for m in ms])

    SEsumF = (-1) ** ms * 2 ** (2 * ms) * factorial(order + ms - 1) \
        * (K / kc) ** (2 * ms) * b \
        / (factorial(2 * ms) * factorial(order - ms))
    SEsumF = np.sum(SEsumF)
    SEsumF *= 1j / pi

    # Odd sum with factorial terms
    ms = np.arange(0, order)
    b = np.array([float(mp.bernpoly(2 * m + 1, beta0 / K)) for m in ms])

    SOsumF = (-1) ** ms * 2 ** (2 * ms) * factorial(order + ms - 1) \
        * (K / kc) ** (2 * ms + 1) * b \
        / (factorial(2 * ms + 1) * factorial(order - ms - 1))
    SOsumF = np.sum(SOsumF)
    SOsumF *= -2 / pi

    # extended precision calculations for large sum terms
    t1 = (1 / pi) * (kc / (2 * K)) ** oeven
    t2 = (beta0 * L * order / pi ** 2) * (kc / (2 * K)) ** oodd

    # assume we need ~15 digits of precision at a magnitude of 1
    dps = np.max([int(np.ceil(np.log10(np.abs(t1)))) + 15,
                 int(np.ceil(np.log10(np.abs(t2)))) + 15,
                 15])
    mp.dps = dps

    arg_ = mp.mpf(kc / (2 * K))
    SEinf = -(-1) ** order * arg_ ** (2 * order) \
          * mp.zeta(2 * order + 1) / mp.pi
    SOinf = (-1) ** order * beta0 * L * order * arg_ ** (2 * order - 1) \
          * mp.zeta(2 * order + 1) / mp.pi ** 2

    for i, m in enumerate(mp.arange(1, qmax + 1)):

        even_term = ((-1) ** order / (m * mp.pi)) * (arg_ / m) ** (2 * order)
        odd_term = ((-1) ** order * beta0 * L * order / (m ** 2 * mp.pi ** 2)) \
                * (arg_ / m) ** (2 * order - 1)
        SEinf += even_term
        SOinf -= odd_term

        # break condition, where we should be OK moving back to double precision
        if mp.fabs(even_term) < 1 and mp.fabs(odd_term) < 1:
            break

    mp.dps = 15
    SEinf = complex(SEinf)
    SOinf = complex(SOinf)

    if i + 1 < qmax:
        ms = np.arange(i + 2, qmax)
        even_terms = ((-1) ** order / (ms * pi)) \
                   * (kc / (2 * K * ms)) ** (2 * order)
        odd_terms = ((-1) ** order * beta0 * L * order / (ms ** 2 * pi ** 2)) \
                  * (kc / (2 * K * ms)) ** (2 * order - 1)

    SEinf += even_terms.sum()
    SEinf *= 2j
    SOinf -= odd_terms.sum()
    SOinf *= 2

    SEven = SEsum0 + SEinf + 1j / (pi * order) + SEsumF
    SOdd = SOsum0 + SOinf + SOsumF

    return SOdd, SEven
Ejemplo n.º 15
0
# Set the dps option
mp.dps = 256

# Convert stuff to mpmath
inc = mp.mpf(args.spacing)
eps = mp.power(10, -args.eps)

cutoffs = [None] * (args.max_n+1)
cutoff_diffs = [None] * (args.max_n+1)

x = mp.mpf(0)
maxdiff = eps * 2.0 # force loop to run

while maxdiff > eps:
  x = x + inc

  F_real = BoysValue(args.max_n, x) 
  F_long = BoysValue_Asymptotic(args.max_n, x)

  diff = [ mp.fabs(F_real[i] - F_long[i]) for i in range(0, len(F_real)) ]
  maxdiff = max(diff)

  for idx,val in enumerate(diff):
      if not cutoffs[idx] and diff[idx] < eps:
          cutoffs[idx] = x
          cutoff_diffs[idx] = val

for idx,val in enumerate(cutoffs):
    print("{:4}  {}".format(idx, mp.nstr(val)))
    def run_posit_2op_exhaustive(self,
                                 op_str=None,
                                 nbits_range=None,
                                 es_range=None):
        op = None
        mpop = None
        if op_str == '+':
            op = PCPosit.__add__
            mpop = mp.mpf.__add__
        elif op_str == '-':
            op = PCPosit.__sub__
            mpop = mp.mpf.__sub__
        elif op_str == '*':
            op = PCPosit.__mul__
            mpop = mp.mpf.__mul__
        elif op_str == '/':
            op = PCPosit.__truediv__
            mpop = mp.mpf.__truediv__
        else:
            raise NotImplementedError("op={}".format(op_str))

        for nbits in nbits_range:
            mask = bitops.create_mask(nbits)
            for es in es_range:
                for abits in range(2**nbits):
                    for bbits in range(2**nbits):
                        a = PCPosit(abits, nbits=nbits, es=es, mode='bits')
                        b = PCPosit(bbits, nbits=nbits, es=es, mode='bits')
                        c = op(a, b)

                        if a.rep['t'] == 'n' and b.rep['t'] == 'n':
                            amp = mp.mpf(
                                eval(coder.positrep_to_rational_str(a.rep)))
                            bmp = mp.mpf(
                                eval(coder.positrep_to_rational_str(b.rep)))
                            c2mp = mpop(amp, bmp)
                            c0 = PCPosit((bbits - 1) & mask,
                                         nbits=nbits,
                                         es=es,
                                         mode='bits')
                            c1 = PCPosit((bbits + 1) & mask,
                                         nbits=nbits,
                                         es=es,
                                         mode='bits')

                            cbits = coder.encode_posit_binary(c.rep)
                            roundedc = coder.decode_posit_binary(cbits,
                                                                 nbits=nbits,
                                                                 es=es)

                            rcmp = mp.mpf(
                                eval(coder.positrep_to_rational_str(roundedc)))
                            cratiodiffmp = mp.fabs(mp.log(
                                rcmp / c2mp)) if c2mp != 0 else mp.fabs(rcmp -
                                                                        c2mp)
                            cabsdiffmp = mp.fabs(rcmp - c2mp)
                            if c0.rep['t'] != 'c':
                                c0mp = mp.mpf(
                                    eval(coder.positrep_to_rational_str(
                                        c0.rep)))
                                c0ratiodiffmp = mp.fabs(mp.log(
                                    c0mp /
                                    c2mp)) if c2mp != 0 else mp.fabs(c0mp -
                                                                     c2mp)
                                c0absdiffmp = mp.fabs(c0mp - c2mp)
                                self.assertTrue(cratiodiffmp <= c0ratiodiffmp
                                                or cabsdiffmp <= c0absdiffmp)
                            if c1.rep['t'] != 'c':
                                c1mp = mp.mpf(
                                    eval(coder.positrep_to_rational_str(
                                        c1.rep)))
                                c1ratiodiffmp = mp.fabs(mp.log(
                                    c1mp /
                                    c2mp)) if c2mp != 0 else mp.fabs(c1mp -
                                                                     c2mp)
                                c1absdiffmp = mp.fabs(c1mp - c2mp)
                                self.assertTrue(cratiodiffmp <= c1ratiodiffmp
                                                or cabsdiffmp <= c1absdiffmp)