コード例 #1
0
def plot_summary(
        x,
        y,
        xlabel,
        ylabel,
        legend=None,
        title=None,
        append_to_filename="",
        ylim=(None, None),
        plot_kwargs={},
        **params,
):
    """Plot 1-dimensional data and save figure."""
    if len(x.shape) > 1:
        logger.warning(f"Failed to plot {params['labber_filename']}: "
                       f"data is more than 1D ({x.shape=})")
        return
    if x.shape[0] != y.shape[0]:
        logger.warning(
            f"Failed to plot {params['labber_filename']}: "
            f"first dimensions of data don't match ({x.shape=}, {y.shape=})")
        return
    try:
        fig = Figure()
        ax = fig.add_subplot()
        plot(
            x,
            y,
            xlabel=xlabel,
            ylabel=ylabel,
            title=title,
            ax=ax,
            label=legend,
            **plot_kwargs,
        )
    except Exception as e:
        logger.warning(
            f"Failed to plot data from {params['labber_filename']}: caught {repr(e)}"
        )
        logger.exception("ERROR")
        return
    ax.set_ylim(ylim)
    scan_id = flat_clfs(params)["scan"]
    stamp(ax, scan_id)
    fig.savefig(out_dir(params) / (scan_id + append_to_filename + ".png"),
                format="png")
コード例 #2
0
def reconstruct_current(name, obj):
    scan = name.split("/")[-1].split("::")[-1]
    if scan not in scans.keys():
        return None
    print(scan, name)
    params = scans[scan]

    field = obj["x magnet field"]
    ibias = obj["dc current bias"]
    dvdi = np.abs(obj["lock-in (impedance)"])

    # extract fraunhofer from data
    ic = extract_switching_current(ibias, dvdi, threshold=params["threshold"])
    fig, ax = plot2d(field, ibias, dvdi)
    plot(
        np.unique(field),
        ic,
        ax=ax,
        title="Ic extraction",
        color="k",
        lw="0",
        marker=".",
        markersize=5,
    )
    ax.axis("off")
    stamp(ax, scan)
    fig.savefig(outdir / f"{scan}_ic-extraction.png")

    field = np.unique(field)

    # center fraunhofer
    argmax_ic = find_fraunhofer_center(field, ic)
    ic_n = extract_switching_current(ibias,
                                     dvdi,
                                     threshold=params["threshold"],
                                     side="negative")
    argmax_ic_n = find_fraunhofer_center(field, np.abs(ic_n))
    field -= (argmax_ic + argmax_ic_n) / 2
    # field = recenter_fraunhofer(np.unique(field), ic) # if just centering at argmax(Ic+)
    fig, ax = plot(
        field / 1e-3,
        np.array([ic, ic_n]).T / 1e-6,
        xlabel="field (mT)",
        ylabel="critical current (μA)",
        title="fraunhofer centered",
    )
    ax.axvline(0, color="k")
    fig.savefig(outdir / f"{scan}_fraunhofer-centered.png")

    # reconstruct current distribution
    x, jx = extract_current_distribution(
        field,
        ic,
        f2k=2 * np.pi * params["jj_length"] / phys_c["mag. flux quantum"][0],
        jj_width=params["jj_width"],
        jj_points=400,
    )
    fig, ax = subplots()
    ax.fill_between(x / 1e-6, jx)
    ax.set_xlabel("position (μA)")
    ax.set_ylabel("critical current density (μA/μm)")
    ax.set_title(
        f"$\ell_\mathrm{{eff}}$ = {round(params['jj_length'] / 1e-6, 1)}μm")
    fig.savefig(outdir / f"{scan}_current-distribution.png")
コード例 #3
0
    zlabel="dV/dI (Ω)",
    title="raw data",
    stamp=COOLDOWN_SCAN,
)
fig.savefig(str(OUTPATH) + "_raw-data.png")

# extract the switching currents
ic_n, ic_p = extract_switching_current(
    ibias,
    dvdi,
    side="both",
    threshold=RESISTANCE_THRESHOLD,
    interp=True,
)
ax.set_title("$I_c$ extraction")
plot(bfield / 1e-3, ic_p / 1e-6, ax=ax, color="w", lw=0, marker=".")
plot(bfield / 1e-3, ic_n / 1e-6, ax=ax, color="w", lw=0, marker=".")
fig.savefig(str(OUTPATH) + "_ic-extraction.png")

# in vector10, positive Bx points into the daughterboard
if FRIDGE == "vector10":
    bfield = np.flip(bfield) * -1
    ic_p = np.flip(ic_p)
# in vector9, positive Bx points out of the daughterboard
elif FRIDGE == "vector9":
    pass
else:
    warnings.warn(f"I don't recognize fridge `{FRIDGE}`")

# parameterize the fit
params = Parameters()
コード例 #4
0
def estimate_bfield_offset(bfield: np.ndarray, ic_p: np.ndarray, ic_n=None):
    """Estimate the coil field at which the true flux is integral.

    The position of a maximum near the center of the `bfield` range is returned.
    If `ic_n` is given, a better estimate is midway between a peak in `ic_p` and the
    closest valley in `ic_n`.
    """
    peak_locs, _ = find_peaks(ic_p,
                              prominence=(np.max(ic_p) - np.min(ic_p)) / 2)
    guess_loc = peak_locs[len(peak_locs) // 2]
    bfield_guess = bfield[guess_loc]
    if ic_n is not None:
        peak_locs_n, _ = find_peaks(-ic_n,
                                    prominence=(np.max(ic_n) - np.min(ic_n)) /
                                    2)
        guess_loc_n = peak_locs_n[len(peak_locs_n) // 2]
        bfield_guess_n = bfield[guess_loc_n]
        bfield_guess = (bfield_guess + bfield_guess_n) / 2

    # plot the guess
    if ic_n is None:
        fig, ax = plt.subplots()
        ax.set_xlabel("x coil field [mT]")
    else:
        fig, (ax, ax2) = plt.subplots(2, 1, sharex=True)
        ax2.set_xlabel("x coil field [mT]")
        plot(
            bfield / 1e-3,
            ic_n / 1e-6,
            ylabel="supercurrent [μA]",
            ax=ax2,
            marker=".",
        )
        ax2.plot(
            bfield[peak_locs_n] / 1e-3,
            ic_n[peak_locs_n] / 1e-6,
            lw=0,
            marker="*",
            label="$I_{c-}$ peaks",
        )
        ax2.plot(
            bfield[guess_loc_n] / 1e-3,
            ic_n[guess_loc_n] / 1e-6,
            lw=0,
            marker="*",
            label="$I_{c-}$ guess",
        )
        ax2.axvline(bfield_guess / 1e-3, color="k")
        ax2.legend()
    plot(
        bfield / 1e-3,
        ic_p / 1e-6,
        ylabel="supercurrent [μA]",
        title="bfield offset guess",
        stamp=config["COOLDOWN"] + "_" + config["SCAN"],
        ax=ax,
        marker=".",
    )
    ax.axvline(bfield_guess / 1e-3, color="k")
    ax.plot(
        bfield[peak_locs] / 1e-3,
        ic_p[peak_locs] / 1e-6,
        lw=0,
        marker="*",
        label="$I_{c+}$ peaks",
    )
    ax.plot(
        bfield[guess_loc] / 1e-3,
        ic_p[guess_loc] / 1e-6,
        lw=0,
        marker="*",
        label="$I_{c+}$ guess",
    )
    ax.text(
        0.5,
        0.5,
        f"bfield offset $\\approx$ {np.round(bfield_guess / 1e-3, 3)} mT",
        va="center",
        ha="center",
        transform=ax.transAxes,
    )
    ax.legend()
    fig.savefig(str(OUTPATH) + "_bfield-offset.png")
    return bfield_guess
コード例 #5
0
    zlabel="dV/dI (Ω)",
    title="raw data",
    stamp=config["COOLDOWN"] + "_" + config["SCAN"],
)
fig.savefig(str(OUTPATH) + "_raw-data.png")

# extract the switching currents
ic_n, ic_p = extract_switching_current(
    ibias,
    dvdi,
    side="both",
    threshold=config.getfloat("RESISTANCE_THRESHOLD", fallback=None),
    interp=True,
)
ax.set_title("$I_c$ extraction")
plot(bfield / 1e-3, ic_p / 1e-6, ax=ax, color="k", lw=1)
plot(bfield / 1e-3, ic_n / 1e-6, ax=ax, color="k", lw=1)
fig.savefig(str(OUTPATH) + "_ic-extraction.png")

# in vector10, positive Bx points into the daughterboard (depends on mount orientation)
if config["FRIDGE"] == "vector10":
    bfield = np.flip(bfield) * -1
    ic_p = np.flip(ic_p)
    ic_n = np.flip(ic_n)
# in vector9, positive Bx points out of the daughterboard
elif config["FRIDGE"] == "vector9":
    pass
else:
    warnings.warn(f"I don't recognize fridge `{config['FRIDGE']}`")

コード例 #6
0
# from vector9 fridge
FILENAME = "JS602-SE1_4xFlQpcSq-v1_N_WFSBHE01-071"
PATH = get_data_dir() / f"2021/10/Data_1030/{FILENAME}.hdf5"
with LabberData(PATH) as f:
    bfield = f.get_data("Vector Magnet - Field X")
    ibias, dc_volts = f.get_data("VITracer - VI curve", get_x=True)
    dc_volts /= 100  # amplifier gain 100x
    iflux = f.get_data("circleFL 6 - Source current")

# plot extracted switching current for a few flux current values
ic = extract_switching_current(ibias, dc_volts, threshold=3.5e-5)
fig, ax = plot(
    np.unique(bfield) / 1e-6,
    ic[::2].T / 1e-6,
    label=[f"{int(i / 1e-6)} μA" for i in np.unique(iflux[::2])],
    xlabel="Vector Magnet Field (μT)",
    ylabel="Current Bias (μA)",
)
fig.savefig(OUTDIR / f"{FILENAME}_Ic.png")

# broadcast scalar data over vectorial data to have same shape
iflux, bfield, ibias, dc_volts = np.broadcast_arrays(iflux[..., np.newaxis],
                                                     bfield[..., np.newaxis],
                                                     ibias, dc_volts)

# plot the first CPR
fig, ax = plot2d(
    bfield[0] / 1e-6,
    ibias[0] / 1e-6,
    np.diff(dc_volts[0]) / np.diff(ibias[0]),