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refactor: reduce code repetition further
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@stavros11
stavros11 committed May 20, 2024
1 parent 8b44343 commit 7e40aaf
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Showing 2 changed files with 83 additions and 137 deletions.
149 changes: 79 additions & 70 deletions src/qibocal/protocols/state_tomography.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -213,8 +213,8 @@ def plot_rho(fig, zz, trace_options, figure_options, showlegend=None):
)


def _plot(data: StateTomographyData, fit: StateTomographyResults, target: QubitId):
"""Plotting for state tomography"""
def plot_reconstruction(ideal, measured):
"""Plot 3D plot with reconstruction of ideal and measured density matrix."""
fig = make_subplots(
rows=1,
cols=2,
Expand All @@ -226,82 +226,91 @@ def _plot(data: StateTomographyData, fit: StateTomographyResults, target: QubitI
),
)

if fit is not None:
# computing limits for colorscale
min_re, max_re = np.min(fit.target_density_matrix_real[target]), np.max(
fit.target_density_matrix_real[target]
)
min_im, max_im = np.min(fit.target_density_matrix_imag[target]), np.max(
fit.target_density_matrix_imag[target]
)
# computing limits for colorscale
min_re, max_re = np.min(ideal.real), np.max(ideal.real)
min_im, max_im = np.min(ideal.imag), np.max(ideal.imag)

# add offset
if np.abs(min_re - max_re) < 1e-5:
min_re = min_re - 0.1
max_re = max_re + 0.1
if np.abs(min_im - max_im) < 1e-5:
min_im = min_im - 0.1
max_im = max_im + 0.1

plot_rho(
fig,
measured.real,
trace_options=dict(
color="rgba(255,100,0,0.1)", name="experiment", legendgroup="experiment"
),
figure_options=dict(row=1, col=1),
)

# add offset
if np.abs(min_re - max_re) < 1e-5:
min_re = min_re - 0.1
max_re = max_re + 0.1

if np.abs(min_im - max_im) < 1e-5:
min_im = min_im - 0.1
max_im = max_im + 0.1

plot_rho(
fig,
fit.measured_density_matrix_real[target],
trace_options=dict(
color="rgba(255,100,0,0.1)", name="experiment", legendgroup="experiment"
),
figure_options=dict(row=1, col=1),
)
plot_rho(
fig,
ideal.real,
trace_options=dict(
color="rgba(100,0,100,0.1)", name="simulation", legendgroup="simulation"
),
figure_options=dict(row=1, col=1),
)

plot_rho(
fig,
fit.target_density_matrix_real[target],
trace_options=dict(
color="rgba(100,0,100,0.1)", name="simulation", legendgroup="simulation"
),
figure_options=dict(row=1, col=1),
)
plot_rho(
fig,
measured.imag,
trace_options=dict(
color="rgba(255,100,0,0.1)", name="experiment", legendgroup="experiment"
),
figure_options=dict(row=1, col=2),
showlegend=False,
)

plot_rho(
fig,
fit.measured_density_matrix_imag[target],
trace_options=dict(
color="rgba(255,100,0,0.1)", name="experiment", legendgroup="experiment"
),
figure_options=dict(row=1, col=2),
showlegend=False,
)
plot_rho(
fig,
ideal.imag,
trace_options=dict(
color="rgba(100,0,100,0.1)", name="simulation", legendgroup="simulation"
),
figure_options=dict(row=1, col=2),
showlegend=False,
)

plot_rho(
fig,
fit.target_density_matrix_imag[target],
trace_options=dict(
color="rgba(100,0,100,0.1)", name="simulation", legendgroup="simulation"
),
figure_options=dict(row=1, col=2),
showlegend=False,
)
fig.update_scenes(
xaxis=dict(tickvals=list(range(len(ideal)))),
yaxis=dict(tickvals=list(range(len(ideal)))),
zaxis=dict(range=[-1, 1]),
)

fig.update_scenes(
xaxis=dict(tickvals=[0, 1]),
yaxis=dict(tickvals=[0, 1]),
zaxis=dict(range=[-1, 1]),
)
return fig

fitting_report = table_html(
table_dict(
target,
[
"Fidelity",
],
[
np.round(fit.fidelity[target], 4),
],
)

def _plot(data: StateTomographyData, fit: StateTomographyResults, target: QubitId):
"""Plotting for state tomography"""
if fit is None:
return [], ""

ideal = np.array(fit.target_density_matrix_real[target]) + 1j * np.array(
fit.target_density_matrix_imag[target]
)
measured = np.array(fit.measured_density_matrix_real[target]) + 1j * np.array(
fit.measured_density_matrix_imag[target]
)
fig = plot_reconstruction(ideal, measured)

fitting_report = table_html(
table_dict(
target,
[
"Fidelity",
],
[
np.round(fit.fidelity[target], 4),
],
)
)

return [fig], fitting_report
return [], ""
return [fig], fitting_report


state_tomography = Routine(_acquisition, _fit, _plot)
71 changes: 4 additions & 67 deletions src/qibocal/protocols/two_qubit_state_tomography.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -18,7 +18,7 @@
from qibocal.auto.operation import DATAFILE, Data, Results, Routine
from qibocal.auto.transpile import dummy_transpiler, execute_transpiled_circuit

from .state_tomography import StateTomographyParameters, plot_rho
from .state_tomography import StateTomographyParameters, plot_reconstruction
from .utils import table_dict, table_html

SINGLE_QUBIT_BASIS = ["X", "Y", "Z"]
Expand Down Expand Up @@ -222,7 +222,6 @@ def plot_measurements(data: StateTomographyData, target: QubitPairId):
fig = make_subplots(
rows=3,
cols=3,
# "$\text{Plot 1}$"
subplot_titles=tuple(
f"{basis1}<sub>1</sub>{basis2}<sub>2</sub>"
for basis1, basis2 in TWO_QUBIT_BASIS
Expand Down Expand Up @@ -282,72 +281,10 @@ def _plot(data: StateTomographyData, fit: StateTomographyResults, target: QubitP
)
return [fig_measurements], fitting_report

fig = make_subplots(
rows=1,
cols=2,
start_cell="top-left",
specs=[[{"type": "scatter3d"}, {"type": "scatter3d"}]],
subplot_titles=(
"Re(ρ)",
"Im(ρ)",
),
)
# computing limits for colorscale
min_re, max_re = np.min(data.ideal[target].real), np.max(data.ideal[target].real)
min_im, max_im = np.min(data.ideal[target].imag), np.max(data.ideal[target].imag)

# add offset
if np.abs(min_re - max_re) < 1e-5:
min_re = min_re - 0.1
max_re = max_re + 0.1

if np.abs(min_im - max_im) < 1e-5:
min_im = min_im - 0.1
max_im = max_im + 0.1

plot_rho(
fig,
fit.measured_density_matrix_real[target],
trace_options=dict(
color="rgba(255,100,0,0.1)", name="experiment", legendgroup="experiment"
),
figure_options=dict(row=1, col=1),
)

plot_rho(
fig,
data.ideal[target].real,
trace_options=dict(
color="rgba(100,0,100,0.1)", name="simulation", legendgroup="simulation"
),
figure_options=dict(row=1, col=1),
)

plot_rho(
fig,
fit.measured_density_matrix_imag[target],
trace_options=dict(
color="rgba(255,100,0,0.1)", name="experiment", legendgroup="experiment"
),
figure_options=dict(row=1, col=2),
showlegend=False,
)

plot_rho(
fig,
data.ideal[target].imag,
trace_options=dict(
color="rgba(100,0,100,0.1)", name="simulation", legendgroup="simulation"
),
figure_options=dict(row=1, col=2),
showlegend=False,
)

fig.update_scenes(
xaxis=dict(tickvals=list(range(4))),
yaxis=dict(tickvals=list(range(4))),
zaxis=dict(range=[-1, 1]),
measured = np.array(fit.measured_density_matrix_real[target]) + 1j * np.array(
fit.measured_raw_density_matrix_imag[target]
)
fig = plot_reconstruction(data.ideal[target], measured)

fitting_report = table_html(
table_dict(
Expand Down

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