def test_urls(axes, test_GridQubit):
row_col_list = ((0, 5), (8, 1), (7, 0), (13, 5), (1, 6), (3, 2), (2, 8))
if test_GridQubit:
qubits = [grid_qubit.GridQubit(*row_col) for row_col in row_col_list]
else:
qubits = row_col_list
values = np.random.random(len(qubits))
test_value_map = {qubit: value for qubit, value in zip(qubits, values)}
test_url_map = {
qubit: 'http://google.com/{}+{}'.format(*row_col)
for qubit, row_col in zip(qubits, row_col_list)
if row_col != (1, 6)
}
# Add an extra entry that should not show up in results because the
# qubit is not in the value map.
extra_qubit = grid_qubit.GridQubit(10, 7) if test_GridQubit else (10, 7)
test_url_map[extra_qubit] = 'http://google.com/10+7'
my_heatmap = heatmap.Heatmap(test_value_map).set_url_map(test_url_map)
mesh, _ = my_heatmap.plot(axes)
expected_urls = [
test_url_map.get(qubit, '')
for row_col, qubit in sorted(zip(row_col_list, qubits))
]
assert mesh.get_urls() == expected_urls
def test_invalid_args():
value_map = {
(grid_qubit.GridQubit(3, 2), grid_qubit.GridQubit(4, 2)):
0.004619111460557768,
(grid_qubit.GridQubit(4, 1), grid_qubit.GridQubit(4, 2)):
0.0076079162393482835,
}
with pytest.raises(ValueError, match="invalid argument.*colormap"):
heatmap.TwoQubitInteractionHeatmap(value_map, colormap='Greys')
def test_two_qubit_nearest_neighbor(ax):
value_map = {
(grid_qubit.GridQubit(3, 2), grid_qubit.GridQubit(4, 2)):
0.004619111460557768,
(grid_qubit.GridQubit(4, 1), grid_qubit.GridQubit(3, 2)):
0.0076079162393482835,
}
with pytest.raises(ValueError, match="not nearest neighbors"):
heatmap.TwoQubitInteractionHeatmap(value_map, coupler_width=0).plot(ax)
def test_two_qubit_heatmap(ax):
value_map = {
(grid_qubit.GridQubit(3, 2), grid_qubit.GridQubit(4, 2)):
0.004619111460557768,
(grid_qubit.GridQubit(4, 1), grid_qubit.GridQubit(4, 2)):
0.0076079162393482835,
}
title = "Two Qubit Interaction Heatmap"
heatmap.TwoQubitInteractionHeatmap(value_map, title=title).plot(ax)
assert ax.get_title() == title
def test_annotation_map(axes, test_GridQubit):
row_col_list = [(0, 5), (8, 1), (7, 0), (13, 5), (1, 6), (3, 2), (2, 8)]
if test_GridQubit:
qubits = [grid_qubit.GridQubit(*row_col) for row_col in row_col_list]
else:
qubits = row_col_list
values = np.random.random(len(qubits))
annos = np.random.choice([c for c in string.ascii_letters], len(qubits))
test_value_map = {qubit: value for qubit, value in zip(qubits, values)}
test_anno_map = {
qubit: anno
for qubit, row_col, anno in zip(qubits, row_col_list, annos)
if row_col != (1, 6)
}
random_heatmap = (
heatmap.Heatmap(test_value_map).set_annotation_map(test_anno_map))
random_heatmap.plot(axes)
actual_texts = set()
for artist in axes.get_children():
if isinstance(artist, mpl.text.Text):
col, row = artist.get_position()
assert (row, col) != (1, 6)
actual_texts.add(((row, col), artist.get_text()))
expected_texts = set((row_col, anno)
for row_col, anno in zip(row_col_list, annos)
if row_col != (1, 6))
assert expected_texts.issubset(actual_texts)
def test_cell_colors(ax, colormap_name):
row_col_list = ((0, 5), (8, 1), (7, 0), (13, 5), (1, 6), (3, 2), (2, 8))
qubits = [grid_qubit.GridQubit(row, col) for (row, col) in row_col_list]
values = 1.0 + 2.0 * np.random.random(len(qubits)) # [1, 3)
test_value_map = {(qubit, ): value for qubit, value in zip(qubits, values)}
test_row_col_map = {rc: value for rc, value in zip(row_col_list, values)}
vmin, vmax = 1.5, 2.5
random_heatmap = heatmap.Heatmap(
test_value_map,
collection_options={'cmap': colormap_name},
vmin=vmin,
vmax=vmax)
_, mesh = random_heatmap.plot(ax)
colormap = mpl.cm.get_cmap(colormap_name)
for path, facecolor in zip(mesh.get_paths(), mesh.get_facecolors()):
vertices = path.vertices[0:4]
row = int(round(np.mean([v[1] for v in vertices])))
col = int(round(np.mean([v[0] for v in vertices])))
value = test_row_col_map[(row, col)]
color_scale = (value - vmin) / (vmax - vmin)
if color_scale < 0.0:
color_scale = 0.0
if color_scale > 1.0:
color_scale = 1.0
expected_color = np.array(colormap(color_scale))
assert np.all(np.isclose(facecolor, expected_color))
def test_non_float_values(ax, format_string):
class Foo:
def __init__(self, value: float, unit: str):
self.value = value
self.unit = unit
def __float__(self):
return self.value
def __format__(self, format_string):
if format_string == 's':
return f'{self.value}{self.unit}'
else:
return format(self.value, format_string)
row_col_list = ((0, 5), (8, 1), (7, 0), (13, 5), (1, 6), (3, 2), (2, 8))
qubits = [grid_qubit.GridQubit(row, col) for (row, col) in row_col_list]
values = np.random.random(len(qubits))
units = np.random.choice([c for c in string.ascii_letters], len(qubits))
test_value_map = {(qubit, ): Foo(float(value), unit)
for qubit, value, unit in zip(qubits, values, units)}
row_col_map = {
row_col: Foo(float(value), unit)
for row_col, value, unit in zip(row_col_list, values, units)
}
colormap_name = 'viridis'
vmin, vmax = 0.0, 1.0
random_heatmap = heatmap.Heatmap(
test_value_map,
collection_options={'cmap': colormap_name},
vmin=vmin,
vmax=vmax,
annotation_format=format_string,
)
_, mesh = random_heatmap.plot(ax)
colormap = mpl.cm.get_cmap(colormap_name)
for path, facecolor in zip(mesh.get_paths(), mesh.get_facecolors()):
vertices = path.vertices[0:4]
row = int(round(np.mean([v[1] for v in vertices])))
col = int(round(np.mean([v[0] for v in vertices])))
foo = row_col_map[(row, col)]
color_scale = (foo.value - vmin) / (vmax - vmin)
expected_color = np.array(colormap(color_scale))
assert np.all(np.isclose(facecolor, expected_color))
for artist in ax.get_children():
if isinstance(artist, mpl.text.Text):
col, row = artist.get_position()
if (row, col) in test_value_map:
foo = test_value_map[(row, col)]
actual_text = artist.get_text()
expected_text = format(foo, format_string)
assert actual_text == expected_text
def test_cells_positions(ax):
row_col_list = ((0, 5), (8, 1), (7, 0), (13, 5), (1, 6), (3, 2), (2, 8))
qubits = [grid_qubit.GridQubit(row, col) for (row, col) in row_col_list]
values = np.random.random(len(qubits))
test_value_map = {(qubit, ): value for qubit, value in zip(qubits, values)}
_, collection = heatmap.Heatmap(test_value_map).plot(ax)
found_qubits = set()
for path in collection.get_paths():
vertices = path.vertices[0:4]
row = int(round(np.mean([v[1] for v in vertices])))
col = int(round(np.mean([v[0] for v in vertices])))
found_qubits.add((row, col))
assert found_qubits == set(row_col_list)
def test_colorbar(ax, position, size, pad):
row_col_list = ((0, 5), (8, 1), (7, 0), (13, 5), (1, 6), (3, 2), (2, 8))
qubits = [grid_qubit.GridQubit(row, col) for (row, col) in row_col_list]
values = np.random.random(len(qubits))
test_value_map = {(qubit, ): value for qubit, value in zip(qubits, values)}
random_heatmap = heatmap.Heatmap(test_value_map, plot_colorbar=False)
fig1, ax1 = plt.subplots()
random_heatmap.plot(ax1)
fig2, ax2 = plt.subplots()
random_heatmap.plot(ax2,
plot_colorbar=True,
colorbar_position=position,
colorbar_size=size,
colorbar_pad=pad)
# We need to call savefig() explicitly for updating axes position since the figure
# object has been altered in the HeatMap._plot_colorbar function.
tmp_dir = mkdtemp()
fig2.savefig(pathlib.Path(tmp_dir) / 'tmp.png')
# Check that the figure has one more object in it when colorbar is on.
assert len(fig2.get_children()) == len(fig1.get_children()) + 1
fig_pos = fig2.get_axes()[0].get_position()
colorbar_pos = fig2.get_axes()[1].get_position()
origin_axes_size = (fig_pos.xmax - fig_pos.xmin if position
in ["left", "right"] else fig_pos.ymax - fig_pos.ymin)
expected_pad = int(pad.replace("%", "")) / 100 * origin_axes_size
expected_size = int(size.replace("%", "")) / 100 * origin_axes_size
if position == "right":
pad_distance = colorbar_pos.xmin - fig_pos.xmax
colorbar_size = colorbar_pos.xmax - colorbar_pos.xmin
elif position == "left":
pad_distance = fig_pos.xmin - colorbar_pos.xmax
colorbar_size = colorbar_pos.xmax - colorbar_pos.xmin
elif position == "top":
pad_distance = colorbar_pos.ymin - fig_pos.ymax
colorbar_size = colorbar_pos.ymax - colorbar_pos.ymin
elif position == "bottom":
pad_distance = fig_pos.ymin - colorbar_pos.ymax
colorbar_size = colorbar_pos.ymax - colorbar_pos.ymin
assert np.isclose(colorbar_size, expected_size)
assert np.isclose(pad_distance, expected_pad)
plt.close(fig1)
plt.close(fig2)
def test_annotation_position_and_content(ax, format_string):
row_col_list = ((0, 5), (8, 1), (7, 0), (13, 5), (1, 6), (3, 2), (2, 8))
qubits = [grid_qubit.GridQubit(row, col) for (row, col) in row_col_list]
values = np.random.random(len(qubits))
test_value_map = {(qubit, ): value for qubit, value in zip(qubits, values)}
test_row_col_map = {rc: value for rc, value in zip(row_col_list, values)}
random_heatmap = heatmap.Heatmap(test_value_map,
annotation_format=format_string)
random_heatmap.plot(ax)
actual_texts = set()
for artist in ax.get_children():
if isinstance(artist, mpl.text.Text):
col, row = artist.get_position()
text = artist.get_text()
actual_texts.add(((row, col), text))
expected_texts = set((qubit, format(value, format_string))
for qubit, value in test_row_col_map.items())
assert expected_texts.issubset(actual_texts)
def test_default_annotation(ax):
"""Tests that the default annotation is '.2g' format on float(value)."""
row_col_list = ((0, 5), (8, 1), (7, 0), (13, 5), (1, 6), (3, 2), (2, 8))
qubits = [grid_qubit.GridQubit(row, col) for (row, col) in row_col_list]
values = ['3.752', '42', '-5.27e8', '-7.34e-9', 732, 0.432, 3.9753e28]
test_value_map = {(qubit, ): value for qubit, value in zip(qubits, values)}
test_row_col_map = {rc: value for rc, value in zip(row_col_list, values)}
random_heatmap = heatmap.Heatmap(test_value_map)
random_heatmap.plot(ax)
actual_texts = set()
for artist in ax.get_children():
if isinstance(artist, mpl.text.Text):
col, row = artist.get_position()
text = artist.get_text()
actual_texts.add(((row, col), text))
expected_texts = set((qubit, format(float(value), '.2g'))
for qubit, value in test_row_col_map.items())
assert expected_texts.issubset(actual_texts)
def test_plot_updates_local_config():
value_map_2d = {
(grid_qubit.GridQubit(3, 2), grid_qubit.GridQubit(4, 2)):
0.004619111460557768,
(grid_qubit.GridQubit(4, 1), grid_qubit.GridQubit(4, 2)):
0.0076079162393482835,
}
value_map_1d = {
(grid_qubit.GridQubit(3, 2), ): 0.004619111460557768,
(grid_qubit.GridQubit(4, 2), ): 0.0076079162393482835,
}
original_title = "Two Qubit Interaction Heatmap"
new_title = "Temporary title for the plot"
for random_heatmap in [
heatmap.TwoQubitInteractionHeatmap(value_map_2d,
title=original_title),
heatmap.Heatmap(value_map_1d, title=original_title),
]:
_, ax = plt.subplots()
random_heatmap.plot(ax, title=new_title)
assert ax.get_title() == new_title
_, ax = plt.subplots()
random_heatmap.plot(ax)
assert ax.get_title() == original_title