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dvc/tests/unit/render/test_vega_converter.py
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from collections import OrderedDict
import pytest
from dvc.exceptions import DvcException
from dvc.render import VERSION_FIELD
from dvc.render.converter.vega import VegaConverter, _lists
@pytest.mark.parametrize(
"dictionary, expected_result",
[
({}, []),
({"x": ["a", "b", "c"]}, [["a", "b", "c"]]),
(
OrderedDict([("x", {"y": ["a", "b"]}), ("z", {"w": ["c", "d"]})]),
[["a", "b"], ["c", "d"]],
),
],
)
def test_finding_lists(dictionary, expected_result):
result = _lists(dictionary)
assert list(result) == expected_result
@pytest.mark.parametrize(
"input_data,properties,expected_datapoints,expected_properties",
[
pytest.param(
{"f": {"metric": [{"v": 1}, {"v": 2}]}},
{},
[
{
"v": 1,
"step": 0,
VERSION_FIELD: {
"revision": "r",
"filename": "f",
"field": "v",
},
},
{
"v": 2,
"step": 1,
VERSION_FIELD: {
"revision": "r",
"filename": "f",
"field": "v",
},
},
],
{"x": "step", "y": "v", "x_label": "step", "y_label": "v"},
id="default_x_y",
),
pytest.param(
{"f": {"metric": [{"v": 1, "v2": 0.1}, {"v": 2, "v2": 0.2}]}},
{"x": "v", "y": "v2"},
[
{
"v": 1,
"v2": 0.1,
VERSION_FIELD: {
"revision": "r",
"filename": "f",
"field": "v2",
},
},
{
"v": 2,
"v2": 0.2,
VERSION_FIELD: {
"revision": "r",
"filename": "f",
"field": "v2",
},
},
],
{"x": "v", "y": "v2", "x_label": "v", "y_label": "v2"},
id="choose_x_y",
),
pytest.param(
{
"f": {
"some": "noise",
"very": {
"nested": {
"metric": [
{"v": 1, "v2": 0.1},
{"v": 2, "v2": 0.2},
]
}
},
}
},
{"x": "v", "y": "v2", "x_label": "x", "y_label": "y"},
[
{
"v": 1,
"v2": 0.1,
VERSION_FIELD: {
"revision": "r",
"filename": "f",
"field": "v2",
},
},
{
"v": 2,
"v2": 0.2,
VERSION_FIELD: {
"revision": "r",
"filename": "f",
"field": "v2",
},
},
],
{"x": "v", "y": "v2", "x_label": "x", "y_label": "y"},
id="find_in_nested_structure",
),
pytest.param(
{"f": {"metric": [{"v": 1, "v2": 0.1}, {"v": 2, "v2": 0.2}]}},
{"y": {"f": ["v", "v2"]}},
[
{
VERSION_FIELD: {
"revision": "r",
"filename": "f",
"field": "v",
},
"dvc_inferred_y_value": 1,
"v": 1,
"v2": 0.1,
"step": 0,
},
{
VERSION_FIELD: {
"revision": "r",
"filename": "f",
"field": "v",
},
"dvc_inferred_y_value": 2,
"v": 2,
"v2": 0.2,
"step": 1,
},
{
VERSION_FIELD: {
"revision": "r",
"filename": "f",
"field": "v2",
},
"dvc_inferred_y_value": 0.1,
"v2": 0.1,
"v": 1,
"step": 0,
},
{
VERSION_FIELD: {
"revision": "r",
"filename": "f",
"field": "v2",
},
"v": 2,
"v2": 0.2,
"dvc_inferred_y_value": 0.2,
"step": 1,
},
],
{
"x": "step",
"y": "dvc_inferred_y_value",
"y_label": "y",
"x_label": "step",
},
id="y_def_list",
),
pytest.param(
{
"f": {
"metric": [{"v": 1}, {"v": 2}],
"other_metric": [{"z": 3}, {"z": 4}],
}
},
{"y": {"f": ["v", "z"]}},
[
{
"dvc_inferred_y_value": 1,
"z": 3,
"v": 1,
"step": 0,
VERSION_FIELD: {
"revision": "r",
"filename": "f",
"field": "v",
},
},
{
"dvc_inferred_y_value": 2,
"z": 4,
"step": 1,
"v": 2,
VERSION_FIELD: {
"revision": "r",
"filename": "f",
"field": "v",
},
},
{
"dvc_inferred_y_value": 3,
"v": 1,
"z": 3,
"step": 0,
VERSION_FIELD: {
"revision": "r",
"filename": "f",
"field": "z",
},
},
{
"dvc_inferred_y_value": 4,
"v": 2,
"z": 4,
"step": 1,
VERSION_FIELD: {
"revision": "r",
"filename": "f",
"field": "z",
},
},
],
{
"x": "step",
"y": "dvc_inferred_y_value",
"y_label": "y",
"x_label": "step",
},
id="multi_source_json",
),
pytest.param(
{
"f": {"metric": [{"v": 1, "v2": 0.1}, {"v": 2, "v2": 0.2}]},
"f2": {"metric": [{"v": 3, "v2": 0.3}]},
},
{"x": "v", "y": {"f": "v2", "f2": "v2"}},
[
{
"v": 1,
"v2": 0.1,
VERSION_FIELD: {
"revision": "r",
"filename": "f",
"field": "v2",
},
},
{
"v": 2,
"v2": 0.2,
VERSION_FIELD: {
"revision": "r",
"filename": "f",
"field": "v2",
},
},
{
"v": 3,
"v2": 0.3,
VERSION_FIELD: {
"revision": "r",
"filename": "f2",
"field": "v2",
},
},
],
{"x": "v", "y": "v2", "x_label": "v", "y_label": "v2"},
id="multi_file_json",
),
pytest.param(
{"f": {"metric": [{"v": 1, "v2": 0.1}, {"v": 2, "v2": 0.2}]}},
{"y": ["v", "v2"]},
[
{
"dvc_inferred_y_value": 1,
"v": 1,
"v2": 0.1,
"step": 0,
VERSION_FIELD: {
"revision": "r",
"filename": "f",
"field": "v",
},
},
{
"dvc_inferred_y_value": 2,
"v": 2,
"v2": 0.2,
"step": 1,
VERSION_FIELD: {
"revision": "r",
"filename": "f",
"field": "v",
},
},
{
"dvc_inferred_y_value": 0.1,
"v": 1,
"v2": 0.1,
"step": 0,
VERSION_FIELD: {
"revision": "r",
"filename": "f",
"field": "v2",
},
},
{
"dvc_inferred_y_value": 0.2,
"v": 2,
"v2": 0.2,
"step": 1,
VERSION_FIELD: {
"revision": "r",
"filename": "f",
"field": "v2",
},
},
],
{
"x": "step",
"y": "dvc_inferred_y_value",
"x_label": "step",
"y_label": "y",
},
id="y_list",
),
pytest.param(
{
"f": {"metric": [{"v": 1, "v2": 0.1, "v3": 0.01}]},
"f2": {"metric": [{"v": 1, "v2": 0.1}]},
},
{"y": {"f": ["v2", "v3"], "f2": ["v2"]}, "x": "v"},
[
{
"dvc_inferred_y_value": 0.1,
"v": 1,
"v2": 0.1,
"v3": 0.01,
VERSION_FIELD: {
"revision": "r",
"filename": "f",
"field": "v2",
},
},
{
"dvc_inferred_y_value": 0.01,
"v": 1,
"v2": 0.1,
"v3": 0.01,
VERSION_FIELD: {
"revision": "r",
"filename": "f",
"field": "v3",
},
},
{
"dvc_inferred_y_value": 0.1,
"v": 1,
"v2": 0.1,
VERSION_FIELD: {
"revision": "r",
"filename": "f2",
"field": "v2",
},
},
],
{
"x": "v",
"y": "dvc_inferred_y_value",
"x_label": "v",
"y_label": "y",
},
id="multi_source_y_single_x",
),
],
)
def test_convert(
input_data,
properties,
expected_datapoints,
expected_properties,
):
converter = VegaConverter("f", input_data, properties)
datapoints, resolved_properties = converter.flat_datapoints("r")
assert datapoints == expected_datapoints
assert resolved_properties == expected_properties
@pytest.mark.parametrize(
"input_data,properties",
[
pytest.param(
{
"f": {
"metric": [
{"v": 1},
{"v": 2},
]
},
"f2": {"metric": [{"v2": 0.1}]},
},
{"x": {"f": "v"}, "y": {"f2": "v2"}},
id="unequal_datapoints",
),
pytest.param(
{
"f": {
"metric": [
{"v": 1, "v2": 0.1},
{"v": 2, "v2": 0.2},
]
},
"f2": {
"metric": [
{"v": 3, "v2": 0.3},
]
},
},
{"x": {"f": "v", "f2": "v3"}, "y": {"f": "v2"}},
id="unequal_x_y",
),
],
)
def test_convert_fail(input_data, properties):
converter = VegaConverter("f", input_data, properties)
with pytest.raises(DvcException):
converter.flat_datapoints("r")
@pytest.mark.parametrize(
"properties,label",
[
({"x": {"actual.csv": "actual"}}, "actual"),
(
{"x": {"train_actual.csv": "actual", "val_actual.csv": "actual"}},
"actual",
),
(
{"x": {"actual.csv": "actual", "predicted.csv": "predicted"}},
"x",
),
],
)
def test_infer_x_label(properties, label):
assert VegaConverter.infer_x_label(properties) == label
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