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)