def test_embedding_plot_arrow_integer_axis(embset):
emb = embset["red"]
fig, ax = mpl.pyplot.subplots()
emb.plot(
kind="arrow",
x_axis=0,
y_axis=2,
color="blue",
x_label="xlabel",
y_label="ylabel",
title="test plot",
annot=False,
)
props = {
"type": mpl.collections.PolyCollection,
"data": np.concatenate((emb.vector[0:1], emb.vector[2:3])),
"x_label": "xlabel",
"y_label": "ylabel",
"title": "test plot",
"color": mpl.colors.to_rgba_array("blue"),
"aspect": "auto",
# Not applicable: label
}
UV = np.concatenate((ax.collections[1].U, ax.collections[1].V))
assert isinstance(ax.collections[1], props["type"])
assert np.array_equal(UV, props["data"])
assert np.array_equal(ax.collections[1].get_facecolor(), props["color"])
assert ax.texts == []
validate_plot_general_properties(ax, props)
mpl.pyplot.close(fig)
def test_embedding_plot_scatter_emb_axis_with_common_str_axis_metric(embset):
emb = embset["red"]
fig, ax = mpl.pyplot.subplots()
emb.plot(
kind="scatter",
x_axis=embset["blue"],
y_axis=embset["green"],
axis_metric="cosine_distance",
)
props = {
"type":
mpl.collections.PathCollection,
"data":
np.array([
scipy_distance.cosine(emb.vector, embset["blue"].vector),
scipy_distance.cosine(emb.vector, embset["green"].vector),
]),
"x_label":
"blue",
"y_label":
"green",
"color":
mpl.colors.to_rgba_array("steelblue"),
"title":
"",
"label":
"red",
"aspect":
"auto",
}
assert np.array_equal(ax.collections[0].get_offsets()[0], props["data"])
assert isinstance(ax.collections[0], props["type"])
assert ax.texts[0].get_text() == props["label"]
validate_plot_general_properties(ax, props)
mpl.pyplot.close(fig)
def test_embeddingset_plot_arrow_mixed_axis(embset):
fig, ax = mpl.pyplot.subplots()
embset.plot(kind="arrow", x_axis=1, y_axis="red", x_label="xx", color="magenta")
vectors = []
for emb in embset.embeddings.values():
vec = []
vec.append(emb.vector[1])
vec.append(emb > embset["red"])
vectors.append(vec)
vectors = np.array(vectors)
props = {
"type": mpl.collections.PolyCollection,
"data": vectors,
"x_label": "xx",
"y_label": "red",
"title": "",
"label": list(embset.embeddings.keys()),
"color": mpl.colors.to_rgba_array("magenta"),
"aspect": "auto",
}
UV = np.concatenate(
(ax.collections[1].U[:, None], ax.collections[1].V[:, None]), axis=-1
)
assert isinstance(ax.collections[1], props["type"])
assert np.array_equal(UV, props["data"])
assert [t.get_text() for t in ax.texts] == props["label"]
assert np.array_equal(ax.collections[1].get_facecolors(), props["color"])
validate_plot_general_properties(ax, props)
mpl.pyplot.close(fig)
def test_embedding_plot_arrow_emb_axis(embset):
emb = embset["red"] + embset["yellow"]
fig, ax = mpl.pyplot.subplots()
emb.plot(
kind="arrow",
x_axis=embset["blue"],
y_axis=embset["green"],
color="yellow",
show_ops=True,
axis_option="equal",
)
props = {
"type": mpl.collections.PolyCollection,
"data": np.array([emb > embset["blue"], emb > embset["green"]]),
"x_label": "blue",
"y_label": "green",
"color": mpl.colors.to_rgba_array("yellow"),
"title": "",
"label": "(red + yellow)",
"aspect": 1.0,
}
UV = np.concatenate((ax.collections[1].U, ax.collections[1].V))
assert isinstance(ax.collections[1], props["type"])
assert np.array_equal(UV, props["data"])
assert np.array_equal(ax.collections[1].get_facecolor(), props["color"])
assert ax.texts[0].get_text() == props["label"]
validate_plot_general_properties(ax, props)
mpl.pyplot.close(fig)
def test_embeddingset_plot_scatter_str_axis(embset):
fig, ax = mpl.pyplot.subplots()
embset.plot(kind="scatter", x_axis="blue", y_axis="red")
vectors = []
for emb in embset.embeddings.values():
vec = []
vec.append(emb > embset["blue"])
vec.append(emb > embset["red"])
vectors.append(vec)
vectors = np.array(vectors)
props = {
"type": mpl.collections.PathCollection,
"data": vectors,
"x_label": "blue",
"y_label": "red",
"title": "",
"label": list(embset.embeddings.keys()),
"color": mpl.colors.to_rgba_array("steelblue"),
"aspect": "auto",
}
assert isinstance(ax.collections[0], props["type"])
assert np.array_equal(ax.collections[0].get_offsets(), props["data"])
assert [t.get_text() for t in ax.texts] == props["label"]
assert np.array_equal(ax.collections[0].get_facecolors(), props["color"])
validate_plot_general_properties(ax, props)
mpl.pyplot.close(fig)
def test_embeddingset_plot_scatter_emb_axis_with_common_str_axis_metric(embset):
fig, ax = mpl.pyplot.subplots()
embset.plot(
kind="scatter",
x_axis=embset["green"],
y_axis=embset["white"],
axis_metric="euclidean",
)
vectors = []
for emb in embset.embeddings.values():
vectors.append(
[
scipy_distance.euclidean(emb.vector, embset["green"].vector),
scipy_distance.euclidean(emb.vector, embset["white"].vector),
]
)
vectors = np.array(vectors)
props = {
"type": mpl.collections.PathCollection,
"data": vectors,
"x_label": "green",
"y_label": "white",
"title": "",
"label": list(embset.embeddings.keys()),
"color": mpl.colors.to_rgba_array("steelblue"),
"aspect": "auto",
}
assert isinstance(ax.collections[0], props["type"])
assert np.array_equal(ax.collections[0].get_offsets(), props["data"])
assert [t.get_text() for t in ax.texts] == props["label"]
assert np.array_equal(ax.collections[0].get_facecolors(), props["color"])
validate_plot_general_properties(ax, props)
mpl.pyplot.close(fig)
def test_embeddingset_plot_arrow_integer_axis_with_str_axis_metric(embset):
fig, ax = mpl.pyplot.subplots()
embset.plot(
kind="arrow",
x_axis=1,
y_axis=2,
axis_metric="cosine_distance",
x_label="1",
y_label="2",
color="yellow",
axis_option="scaled",
)
vectors = np.concatenate((embset.to_X()[:, 1:2], embset.to_X()[:, 2:3]), axis=-1)
props = {
"type": mpl.collections.PolyCollection,
"data": vectors,
"x_label": "1",
"y_label": "2",
"title": "",
"label": list(embset.embeddings.keys()),
"color": mpl.colors.to_rgba_array("yellow"),
"aspect": 1.0,
}
UV = np.concatenate(
(ax.collections[1].U[:, None], ax.collections[1].V[:, None]), axis=-1
)
assert isinstance(ax.collections[1], props["type"])
assert np.array_equal(UV, props["data"])
assert [t.get_text() for t in ax.texts] == props["label"]
assert np.array_equal(ax.collections[1].get_facecolors(), props["color"])
validate_plot_general_properties(ax, props)
mpl.pyplot.close(fig)
def test_embedding_plot_text_integer_axis(embset):
emb = embset["red"]
fig, ax = mpl.pyplot.subplots()
emb.plot(kind="text", x_axis=1, y_axis=2)
props = {
"data": np.concatenate((emb.vector[1:2] + 0.01, emb.vector[2:3])),
"x_label": "Dimension 1",
"y_label": "Dimension 2",
"title": "",
"label": "red",
"aspect": "auto",
# Not applicable: type, color
}
assert np.array_equal(ax.texts[0].get_position(), props["data"])
assert ax.collections == []
assert ax.texts[0].get_text() == props["label"]
validate_plot_general_properties(ax, props)
mpl.pyplot.close(fig)
def test_embedding_plot_scatter_integer_axis(embset):
emb = embset["red"]
fig, ax = mpl.pyplot.subplots()
emb.plot(kind="scatter", x_axis=0, y_axis=1)
props = {
"type": mpl.collections.PathCollection,
"data": emb.vector[0:2],
"x_label": "Dimension 0",
"y_label": "Dimension 1",
"title": "",
"color": mpl.colors.to_rgba_array("steelblue"),
"label": "red",
"aspect": "auto",
}
assert np.array_equal(ax.collections[0].get_offsets()[0], props["data"])
assert isinstance(ax.collections[0], props["type"])
assert np.array_equal(ax.collections[0].get_facecolor(), props["color"])
assert ax.texts[0].get_text() == props["label"]
validate_plot_general_properties(ax, props)
mpl.pyplot.close(fig)
def test_embeddingset_plot_scatter_integer_axis(embset):
fig, ax = mpl.pyplot.subplots()
embset.plot(kind="scatter", x_axis=0, y_axis=1, annot=False, color="black")
vectors = np.concatenate((embset.to_X()[:, 0:1], embset.to_X()[:, 1:2]), axis=-1)
props = {
"type": mpl.collections.PathCollection,
"data": vectors,
"x_label": "Dimension 0",
"y_label": "Dimension 1",
"title": "",
"color": mpl.colors.to_rgba_array("black"),
"aspect": "auto",
# Not applicable: label
}
assert isinstance(ax.collections[0], props["type"])
assert np.array_equal(ax.collections[0].get_offsets(), props["data"])
assert ax.texts == []
assert np.array_equal(ax.collections[0].get_facecolors(), props["color"])
validate_plot_general_properties(ax, props)
mpl.pyplot.close(fig)
def test_embeddingset_plot_arrow_emb_axis_with_different_axis_metric(embset):
fig, ax = mpl.pyplot.subplots()
embset.plot(
kind="arrow",
x_axis=embset["blue"],
y_axis="red",
axis_metric=[scipy_distance.correlation, "cosine_similarity"],
x_label="xx",
color="magenta",
)
vectors = []
for emb in embset.embeddings.values():
vectors.append(
[
scipy_distance.correlation(emb.vector, embset["blue"].vector),
1.0 - scipy_distance.cosine(emb.vector, embset["red"].vector),
]
)
vectors = np.array(vectors)
props = {
"type": mpl.collections.PolyCollection,
"data": vectors,
"x_label": "xx",
"y_label": "red",
"title": "",
"label": list(embset.embeddings.keys()),
"color": mpl.colors.to_rgba_array("magenta"),
"aspect": "auto",
}
UV = np.concatenate(
(ax.collections[1].U[:, None], ax.collections[1].V[:, None]), axis=-1
)
assert isinstance(ax.collections[1], props["type"])
assert np.array_equal(UV, props["data"])
assert [t.get_text() for t in ax.texts] == props["label"]
assert np.array_equal(ax.collections[1].get_facecolors(), props["color"])
validate_plot_general_properties(ax, props)
mpl.pyplot.close(fig)
