sub.set_xlabel(r"$H$ (T $/\mu_0$)")
sub.set_ylabel(r"$\Delta{}R(H) / R(0) / 10^{-2}$")
sub.xaxis.set_label_position("top")
sub.yaxis.set_label_position("left")
sub.yaxis.set_label_coords(-0.20, 0.5)
sub.set_xlim(xlim)
yunit = 0.01
xminor_locator = AutoMinorLocator(5)
sub.xaxis.set_minor_locator(xminor_locator)
yminor_locator = AutoMinorLocator(5)
sub.yaxis.set_minor_locator(yminor_locator)
fn = r"mr/20121020_02_RvH_2K_Ch1.10P.Al2O3.InterXX_Ch2.10Pa.EuS10.Al2O3.InterXX_Ch3.10Pb.EuS10.Al2O3.InterXX.dat"
ch = 1
data = ppmsana.import_dc(fn)[ch]
corrected = tdrift.linear(data, "R", data["time"][0], data["R"][0], data["time"][-1], data["R"][-1])
down, up = transport.split_MR_down_up(corrected)
upsym = transport.symmetrize_MR(up, down)
downsym = transport.symmetrize_MR(down, up)
d = datasets.merge(upsym, downsym)
# calculate R(0)
d = d.sort("H")
d0 = d.mask(np.abs(d["H"]) < zero_H)
R0 = np.mean(d0["R"])
n = d0["R"].shape[0]
err2 = np.std(d0["R"]) / np.sqrt(n-1)
def plot(fn, co, cos, ls, mk, label, subs):
sub_a, sub_b, sub_c, sub_d = subs
data = ppmsana.import_dc(fn)[ch]
data = datasets.downsample(data,
3,
np.nanmedian,
error_est=errors.combined)
corrected = tdrift.linear(data, "R", data["time"][0], data["R"][0],
data["time"][-1], data["R"][-1])
down, up = transport.split_MR_down_up(corrected)
upsym = transport.symmetrize_MR(up, down)
downsym = transport.symmetrize_MR(down, up)
d = datasets.merge(upsym, downsym)
d = d.sort("H")
d0 = d.mask(np.abs(d["H"]) < zero_H)
n = d0["R"].shape[0]
#print(n)
R0 = np.mean(d0["R"])
err2 = errors.combined(d0["R"], d0.errors["R"])
d["mr"] = d["R"] / R0 - 1.0
d.errors["mr"] = (d.errors["R"] + err2) / R0
d1 = datasets.consolidate(d,
"H",
dH1,
np.nanmean,
error_est=errors.combined)
sub_a.plot(d1["H"] / H_unit,
d1["mr"] / mr_unit,
marker=None,
color=co,
linestyle=ls,
lw=lw,
label=label)
sub_c.plot(d1["H"] / H_unit * cos,
d1["mr"] / mr_unit,
marker=None,
color=co,
linestyle=ls,
lw=lw,
label=label)
d = d1.mask(np.abs(d1["H"]) < H2)
sub_b.errorbar(d["H"] / H_unit,
d["mr"] / mr_unit,
yerr=d.errors["mr"] / mr_unit,
marker=mk,
markerfacecolor="none",
color=co,
linestyle="none",
lw=lw2,
mew=mew2,
label=label)
d = d1.mask(np.abs(d1["H"] * cos) < H2)
sub_d.errorbar(d["H"] / H_unit * cos,
d["mr"] / mr_unit,
yerr=d.errors["mr"] / mr_unit,
marker=mk,
markerfacecolor="none",
color=co,
linestyle="none",
lw=lw2,
mew=mew2,
label=label)
#sub.xaxis.set_label_coords(1, 1.15)
sub.yaxis.set_label_position("left")
#sub.yaxis.set_label_coords(-0.17, 0.0)
sub.set_xlim(xlim)
#sub.set_xticks(xticks)
xminor_locator = AutoMinorLocator(5)
sub.xaxis.set_minor_locator(xminor_locator)
#sub.set_ylim([-15, 29])
#sub.set_yticks(range(-10, 29, 10))
yminor_locator = AutoMinorLocator(5)
sub.yaxis.set_minor_locator(yminor_locator)
fn1 = r"data/20121020_01_RvT_down_Ch1.10P.Al2O3.InterXX_Ch2.10Pa.EuS10.Al2O3.InterXX_Ch3.10Pb.EuS10.Al2O3.InterXX.dat"
data = ppmsana.import_dc(fn1)[0]
sub.plot(x_trans(data["T"]),
y_trans(data["R"] * vdp / quantum_resistance),
color=pal.bl3,
marker="^",
markerfacecolor="none",
markersize=marker_size,
linestyle="none",
label="TI3")
# Sub fig b
sub = sub_b
sub.text(0.1,
0.8,
"(b) TA",
transform=sub.transAxes,
ax.set_yscale("log")
ax.set_xlabel(r"$T \mathrm{(K)}$")
ax.set_ylabel(r"$R_{\Box} (h/e^2)$")
"""
# BL3 / 10P
fn1 = "20121020_01_RvT_down_Ch1.10P.Al2O3.InterXX_Ch2.10Pa.EuS30.Al2O3.InterXX_Ch3.10Pb.EuS30.Al2O3.InterXX.dat"
data = ppmsana.import_dc(fn1)[1]
ax.plot(data["T"], data["R"] * vdp / quantum_resistance, "rx", label="BL3")
"""
# S4 / SB02
fn1 = r"raw\20140320_01_RvT_down_Ch1SB01.Rxx1234_Ch2NONE_Ch3SB02.Rxx1234.csv"
fn2 = r"raw\20140323_01_RvT_up_Ch1SB01.Rxx1324_Ch2NONE_Ch3SB02.Rxx1324.csv"
out = r"S4.dat"
down = ppmsana.import_dc(fn1)[2]
up = ppmsana.import_dc(fn2)[2]
data = transport.van_der_Pauw_set(down, up, "T")
data["Rs"] = data["R"] / quantum_resistance
data["err_Rs"] = data.errors["R"] / quantum_resistance
data.errors = None
datasets.save_csv(data, out, columns=columns)
ax.plot(data["T"],
data["Rs"],
linestyle='None',
color="C3",
marker="v",
label="S4")
# S3 / SB01
#sub.xaxis.set_label_coords(1, 1.15)
sub.yaxis.set_label_position("left")
#sub.yaxis.set_label_coords(-0.17, 0.0)
sub.set_xlim(xlim)
#sub.set_xticks(xticks)
xminor_locator = AutoMinorLocator(5)
sub.xaxis.set_minor_locator(xminor_locator)
#sub.set_ylim([-15, 29])
#sub.set_yticks(range(-10, 29, 10))
yminor_locator = AutoMinorLocator(5)
sub.yaxis.set_minor_locator(yminor_locator)
fn1 = r"data/20120729_01_RvT_down_Ch1EuS2SiBSxx_Ch2EuS3SapBSxx_Ch3EuS2SiBSxy.dat"
data = ppmsana.import_dc(fn1)[1]
sub.plot(x_trans(data["T"]), y_trans(data["R"] * vdp / quantum_resistance), color=pal.bl1, marker="d", markerfacecolor="none", markersize=marker_size, linestyle="none", label="BL1")
fn1 = r"data/20121020_01_RvT_down_Ch1.10P.Al2O3.InterXX_Ch2.10Pa.EuS10.Al2O3.InterXX_Ch3.10Pb.EuS10.Al2O3.InterXX.dat"
data = ppmsana.import_dc(fn1)[2]
sub.plot(x_trans(data["T"]), y_trans(data["R"] * vdp / quantum_resistance), color=pal.bl2, marker="o", markerfacecolor="none", markersize=marker_size, linestyle="none", label="BL2")
data = ppmsana.import_dc(fn1)[1]
sub.plot(x_trans(data["T"]), y_trans(data["R"] * vdp / quantum_resistance), color=pal.bl3, marker="^", markerfacecolor="none", markersize=marker_size, linestyle="none", label="BL3")
fn1 = r"data/20130518_16_RvT_up_180D_Ch1.temp_Ch2.11P.EuS11.Al2O3.xx_Ch3.off.dat"
data = ppmsana.import_dc(fn1)[1]
sub.plot(x_trans(data["T"]), y_trans(data["R"] * vdp / quantum_resistance), color=pal.bl4, marker="v", markerfacecolor="none", markersize=marker_size, linestyle="none", label="BL4")
# Sub fig b
sub = sub_b
sub.text(0.1, 0.8, "(b) TA", transform=sub.transAxes, ha="left", va="center")
fn = r"raw\20121023_01_RvH_2K_Ch1.10P.Al2O3.InterXY_Ch2.10Pa.EuS10.Al2O3.InterXY_Ch3.10Pb.EuS10.Al2O3.InterXY.dat"
data = ppmsana.import_dc(fn)[1]
down, up = transport.split_MR_down_up(data)
upsym = transport.antisymmetrize_MR(up, down)
downsym = transport.antisymmetrize_MR(down, up)
plt.plot(upsym["H"], -upsym["R"], linestyle='None', color="C0", marker="+", label="BL3")
plt.plot(downsym["H"], -downsym["R"], linestyle='None', color="C0", marker="+")
"""
# S4 / SB02
fn = r"raw\20140321_01_RvH_2K_Ch1SB01.Rxy1423_Ch2SB02.Rxy1423_Ch3SB02.Rxy2314.dat"
data = ppmsana.import_dc(fn)[1]
down, up = transport.split_MR_down_up(data)
upsym = transport.antisymmetrize_MR(up, down)
downsym = transport.antisymmetrize_MR(down, up)
mask = upsym["H"] >= H_start
a = upsym.mask(mask)
mask = downsym["H"] >= H_start
b = downsym.mask(mask)
c = datasets.merge(a, b)
averager, err_est = signal.decorrelate_neighbour_averager(
4, np.nanmean, estimate_error=True)
d = datasets.consolidate(c, "H", H_step, averager, error_est=err_est)
