Exemplo n.º 1
0
plt.grid(True)
plt.legend(loc="upper right")
plt.savefig("plots/temperature_resistance.eps")


# energy gap plot

intrinsic_regime_c = eV/(2*kB*np.array([upperc, lowerc]))
intrinsic_regime_h = eV/(2*kB*np.array([upperh, lowerh]))

X_polyfitc = Xc[np.logical_and(Xc >= lowerc, Xc <= upperc)]
Y_polyfitc = Yc[np.logical_and(Xc >= lowerc, Xc <= upperc)]
X_polyfith = Xh[np.logical_and(Xh >= lowerh, Xh <= upperh)]
Y_polyfith = Yh[np.logical_and(Xh >= lowerh, Xh <= upperh)]

coeffsc = hp.phpolyfit(X_polyfitc, hp.pnumpy.log(Y_polyfitc), 1)
E_gc = coeffsc[0]
A_c = hp.pnumpy.exp(-copy.copy(coeffsc[1]))
coeffsh = hp.phpolyfit(X_polyfith, hp.pnumpy.log(Y_polyfith), 1)
E_gh = coeffsh[0]
A_h = hp.pnumpy.exp(-copy.copy(coeffsh[1]))

#print(E_gc)
#print(E_gh)
E_gc.sf = 4
E_gh.sf = 4

pc = lambda x: np.polyval(copy.copy(coeffsc), x)
xc = np.linspace(6, 16, 10)
ph = lambda x: np.polyval(copy.copy(coeffsh), x)
xh = np.linspace(6, 20, 10)
Exemplo n.º 2
0
k_1 = lambda T: np.polyval(np.polyfit([250.0, 400.0], [401.0, 391.0], 1), T
                           )  # W/mK
k_2 = lambda T: np.polyval(np.polyfit([275.0, 400.0], [21.9, 26.6], 1), T
                           )  # W/mK
F_1 = np.pi * (0.5 * d_1)**2  # m^2
F_2 = np.pi * (0.5 * d_2)**2  # m^2

# linear polyfit of the reference table of the type k thermocouple
C = np.arange(-10, 21, 1)  # °C
V = np.array([
    -0.392, -0.353, -0.314, -0.275, -0.236, -0.197, -0.157, -0.118, -0.079,
    -0.039, 0.000, 0.039, 0.079, 0.119, 0.158, 0.198, 0.238, 0.277, 0.317,
    0.357, 0.397, 0.437, 0.477, 0.517, 0.557, 0.597, 0.637, 0.677, 0.718,
    0.758, 0.798
]) * 10**-3  # V
coeffs1 = hp.phpolyfit(V, C, 1)
p1 = lambda x: np.polyval(coeffs1, x)

hp.replace("thermoFitline", hp.fmt_fit(coeffs1, None, 'V_T'))

# order of the colors in the plots
colors = {
    "30": "b",  # blue
    "50": "g",  # green
    "80": "r",  # red
    "110": "c"  # cyan
}

Pi12VTable, Pi12ITable = {}, {}
PiI = []
PiV = []
Exemplo n.º 3
0
                           )  # W/mK
k_2 = lambda T: np.polyval(np.polyfit([275.0, 400.0], [21.9, 26.6], 1), T
                           )  # W/mK
F_1 = np.pi * (0.5 * d_1)**2  # m^2
F_2 = np.pi * (0.5 * d_2)**2  # m^2
deltaI_T = 8.5 * 10**-6

# linear polyfit of the reference table of the type k thermocouple
C = np.arange(-10, 21, 1)  # °C
V = np.array([
    -0.392, -0.353, -0.314, -0.275, -0.236, -0.197, -0.157, -0.118, -0.079,
    -0.039, 0.000, 0.039, 0.079, 0.119, 0.158, 0.198, 0.238, 0.277, 0.317,
    0.357, 0.397, 0.437, 0.477, 0.517, 0.557, 0.597, 0.637, 0.677, 0.718,
    0.758, 0.798
]) * 10**-3  # V
coeffs1 = hp.phpolyfit(V, C, 1)
p1 = lambda x: np.polyval(coeffs1, x)

# order of the colors in the plots
colors = {
    "30": "b",  # blue
    "50": "g",  # green
    "80": "r",  # red
    "110": "c"  # cyan
}

r1 = hp.physical(10**-7, 10**-8, 1)  # Ohm
r2 = hp.physical(5.232, 0.21, 4)  # Ohm
rp = r1 + r2
rm = r1 * r2
Exemplo n.º 4
0
delta_z_counts = hp.pnumpy.sqrt(
    hp.fetch2('data/angle_distribution.xlsx', 'z counts [#]'))
z_counts = hp.fetch2('data/angle_distribution.xlsx', 'z counts [#]',
                     delta_z_counts)
z_time = hp.fetch2('data/angle_distribution.xlsx', 'z time [s]',
                   time_readoff_error)
ctps = z_counts / z_time

fx = ctps / omega_D1(X_twiggle)
Y = ctps / omega_D1(X_twiggle)

logY = hp.pnumpy.log(Y)
logX = hp.pnumpy.log(hp.pnumpy.sin(T / 2))
coeffs = hp.phpolyfit(
    logX,
    logY,
    1,
)
a = coeffs[0]
C = hp.pnumpy.exp(coeffs[1])
#C = hp.physical(np.exp(0.09), 0.001)
b = coeffs[1]

hp.replace("fit:b", b)

hp.replace("a", a)
hp.replace("C", C)

fitline2 = lambda theta: hp.pnumpy.log(C) + a * hp.pnumpy.log(
    hp.pnumpy.sin(0.5 * theta))
fitline = lambda x: np.log(C.n) + a.n * x
Exemplo n.º 5
0
    #plt.show()
    #exit()

# Plot of linearity of the measurement system
if run['system linearity']:

    i = 1
    for det in detectors:
        print("processing " + det['name'] + "-detector data ...")

        dE_gamma = np.abs(hp.fetch2(det['file'], 'dC-pos [keV]'))
        dE_channel = np.abs(hp.fetch2(det['file'], 'dC-pos [ch]'))
        E_gamma = hp.fetch2(det['file'], 'C-pos [keV]', dE_gamma)
        E_channel = hp.fetch2(det['file'], 'C-pos [ch]', dE_channel)

        coeffs = hp.phpolyfit(E_gamma, E_channel, 1)
        p = lambda x: np.polyval(coeffs, x)
        pu = lambda x: np.polyval(coeffs.copy() + hp.stddev(coeffs), x)
        pl = lambda x: np.polyval(coeffs.copy() - hp.stddev(coeffs), x)
        x = np.linspace(0, 2500, 5)

        E_gamma_cs = E_gamma[0]
        E_channel_cs = E_channel[0]
        E_gamma_eu = E_gamma[1:6]
        E_channel_eu = E_channel[1:6]
        E_gamma_co = E_gamma[6:8]
        E_channel_co = E_channel[6:8]
        E_gamma_na = E_gamma[8]
        E_channel_na = E_channel[8]
        E_gamma_bi = E_gamma[9:]
        E_channel_bi = E_channel[9:]