def test_dataset_2ddata_loading(nt_dataset_doubledot, tmp_path):
ds = Dataset(1, db_name="temp.db", db_folder=str(tmp_path))
assert ds.exp_id == 1
assert ds.dimensions['dc_current'] == 2
assert ds.dimensions['dc_sensor'] == 2
assert len(ds.raw_data) == 2
assert len(ds.data) == 2
ds_vx = ds.raw_data['current']['v_x'].values
ds_vy = ds.raw_data['current']['v_y'].values
ds_sig = ds.raw_data['current'].values
ds_sens = ds.raw_data['sensor'].values
xv, yv, ddot, sensor = generate_doubledot_data()
x = np.unique(xv)
y = np.unique(yv)
assert np.allclose(ds_vx, x)
assert np.allclose(ds_vy, y)
assert np.allclose(ds_sig, ddot.T)
assert np.allclose(ds_sens, sensor.T)
assert ds.get_plot_label('dc_current', 0) == "voltage x [V]"
assert ds.get_plot_label('dc_sensor', 0) == "voltage x [V]"
assert ds.get_plot_label('dc_current', 1) == "voltage y [V]"
assert ds.get_plot_label('dc_sensor', 1) == "voltage y [V]"
assert ds.get_plot_label('dc_current', 2) == "dc current [A]"
assert ds.get_plot_label('dc_sensor', 2) == "dc sensor [A]"
def test_dataset_1ddata_loading(nt_dataset_pinchoff, tmp_path):
ds = Dataset(1, db_name="temp.db", db_folder=str(tmp_path))
assert ds.exp_id == 1
assert ds.dimensions['dc_current'] == 1
assert ds.dimensions['dc_sensor'] == 1
assert len(ds.raw_data) == 2
assert len(ds.data) == 2
vx = np.linspace(-0.1, 0, 120)
ds_vx = ds.raw_data['current']['voltage'].values
assert np.allclose(ds_vx, vx)
ds_sig = ds.raw_data['current'].values
sig = 0.6 * (1 + np.tanh(1000 * vx + 50))
assert np.allclose(ds_sig, sig)
assert ds.get_plot_label('dc_current', 0) == "voltage x [V]"
assert ds.get_plot_label('dc_sensor', 0) == "voltage x [V]"
assert ds.get_plot_label('dc_current', 1) == "dc current [A]"
assert ds.get_plot_label('dc_sensor', 1) == "dc sensor [A]"
with pytest.raises(AssertionError):
ds.get_plot_label('dc_sensor', 2)
def plot_dataset(
qc_run_id: int,
db_name: str,
save_figures: bool = True,
db_folder: Optional[str] = None,
plot_filtered_data: bool = False,
plot_params: Optional[plot_params_type] = None,
ax: Optional[matplotlib.axes.Axes] = None,
colorbar: Optional[matplotlib.colorbar.Colorbar] = None,
filename: Optional[str] = None,
file_location: Optional[str] = None,
) -> AxesTuple:
"""
If to be saved and no file location specified, the figure will be saved at
os.path.join(nt.config['db_folder'], 'tuning_results', dataset.device_name)
in both eps and png
"""
if plot_params is None:
plot_params = default_plot_params
matplotlib.rcParams.update(plot_params)
if db_folder is None:
_, db_folder = nt.get_database()
dataset = Dataset(qc_run_id, db_name, db_folder=db_folder)
if plot_filtered_data:
data = dataset.filtered_data
else:
data = dataset.data
if ax is None:
fig_size = copy.deepcopy(plot_params["figure.figsize"])
fig_size[1] *= len(dataset.data) * 0.8 # type: ignore
fig, ax = plt.subplots(
len(dataset.data),
1,
squeeze=False,
figsize=fig_size,
)
colorbars: List[matplotlib.colorbar.Colorbar] = []
fig_title = dataset.guid
for r_i, read_meth in enumerate(dataset.readout_methods):
c_name = default_coord_names['voltage'][0]
voltage_x = data[read_meth][c_name].values
signal = data[read_meth].values.T
if dataset.dimensions[read_meth] == 1:
colorbar = None
ax[r_i, 0].plot(
voltage_x,
signal,
zorder=6,
)
ax[r_i, 0].set_xlabel(dataset.get_plot_label(read_meth, 0))
ax[r_i, 0].set_ylabel(dataset.get_plot_label(read_meth, 1))
ax[r_i, 0].set_title(str(fig_title))
divider = make_axes_locatable(ax[r_i, 0])
cbar_ax = divider.append_axes("right", size="5%", pad=0.06)
cbar_ax.set_facecolor("none")
for caxis in ["top", "bottom", "left", "right"]:
cbar_ax.spines[caxis].set_linewidth(0)
cbar_ax.set_xticks([])
cbar_ax.set_yticks([])
colorbars.append(colorbars)
ax[r_i, 0].figure.tight_layout()
elif dataset.dimensions[read_meth] == 2:
c_name = default_coord_names['voltage'][1]
voltage_y = data[read_meth][c_name].values
colormesh = ax[r_i, 0].pcolormesh(
voltage_x,
voltage_y,
signal,
shading="auto",
)
if colorbar is not None:
colorbars.append(ax[r_i, 0].figure.colorbar(colormesh,
ax=ax[r_i, 0],
cax=colorbar.ax))
else:
# colorbar = fig.colorbar(colormesh, ax=ax[r_i, 0])
divider = make_axes_locatable(ax[r_i, 0])
cbar_ax = divider.append_axes("right", size="5%", pad=0.06)
colorbars.append(
fig.colorbar(
colormesh,
ax=ax[r_i, 0],
cax=cbar_ax,
))
colorbars[-1].set_label(
dataset.get_plot_label(read_meth, 2),
rotation=-270,
)
ax[r_i, 0].set_xlabel(dataset.get_plot_label(read_meth, 0))
ax[r_i, 0].set_ylabel(dataset.get_plot_label(read_meth, 1))
ax[r_i, 0].set_title(str(fig_title))
ax[r_i, 0].figure.tight_layout()
else:
raise NotImplementedError
if save_figures:
if file_location is None:
file_location = os.path.join(nt.config["db_folder"],
"tuning_results", dataset.device_name)
if not os.path.exists(file_location):
os.makedirs(file_location)
if filename is None:
filename = "dataset_" + str(dataset.guid)
else:
filename = os.path.splitext(filename)[0]
path = os.path.join(file_location, filename + ".png")
plt.savefig(path, format="png", dpi=600, bbox_inches="tight")
return ax, colorbars