mirror of
https://github.com/Stone-Red-Code/dvc.git
synced 2026-11-10 07:18:27 +01:00
Dave Berenbaum
35b648bbcf
* plots: shorten field names * plots: handle missing field names * plots: make compatible with py3.8 * plots: fix for missing data * plots: add test for field shortening * plots: strip separators regardless of os * plots: don't shorten field name * plots: drop test for shortening field name
490 lines
14 KiB
Python
490 lines
14 KiB
Python
from collections import OrderedDict
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import pytest
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from dvc.exceptions import DvcException
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from dvc.render import VERSION_FIELD
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from dvc.render.converter.vega import FieldNotFoundError, VegaConverter, _lists
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@pytest.mark.parametrize(
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"dictionary, expected_result",
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[
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({}, []),
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({"x": ["a", "b", "c"]}, [["a", "b", "c"]]),
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(
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OrderedDict([("x", {"y": ["a", "b"]}), ("z", {"w": ["c", "d"]})]),
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[["a", "b"], ["c", "d"]],
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),
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],
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)
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def test_finding_lists(dictionary, expected_result):
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result = _lists(dictionary)
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assert list(result) == expected_result
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@pytest.mark.parametrize(
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"input_data,properties,expected_datapoints,expected_properties",
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[
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pytest.param(
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{"f": {"metric": [{"v": 1}, {"v": 2}]}},
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{},
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[
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{
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"v": 1,
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"step": 0,
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VERSION_FIELD: {
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"revision": "r",
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"filename": "f",
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"field": "v",
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},
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},
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{
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"v": 2,
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"step": 1,
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VERSION_FIELD: {
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"revision": "r",
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"filename": "f",
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"field": "v",
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},
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},
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],
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{"x": "step", "y": "v", "x_label": "step", "y_label": "v"},
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id="default_x_y",
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),
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pytest.param(
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{"f": {"metric": [{"v": 1, "v2": 0.1}, {"v": 2, "v2": 0.2}]}},
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{"x": "v", "y": "v2"},
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[
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{
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"v": 1,
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"v2": 0.1,
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VERSION_FIELD: {
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"revision": "r",
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"filename": "f",
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"field": "v2",
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},
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},
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{
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"v": 2,
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"v2": 0.2,
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VERSION_FIELD: {
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"revision": "r",
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"filename": "f",
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"field": "v2",
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},
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},
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],
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{"x": "v", "y": "v2", "x_label": "v", "y_label": "v2"},
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id="choose_x_y",
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),
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pytest.param(
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{
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"f": {
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"some": "noise",
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"very": {
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"nested": {
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"metric": [
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{"v": 1, "v2": 0.1},
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{"v": 2, "v2": 0.2},
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]
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}
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},
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}
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},
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{"x": "v", "y": "v2", "x_label": "x", "y_label": "y"},
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[
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{
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"v": 1,
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"v2": 0.1,
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VERSION_FIELD: {
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"revision": "r",
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"filename": "f",
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"field": "v2",
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},
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},
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{
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"v": 2,
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"v2": 0.2,
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VERSION_FIELD: {
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"revision": "r",
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"filename": "f",
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"field": "v2",
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},
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},
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],
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{"x": "v", "y": "v2", "x_label": "x", "y_label": "y"},
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id="find_in_nested_structure",
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),
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pytest.param(
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{"f": {"metric": [{"v": 1, "v2": 0.1}, {"v": 2, "v2": 0.2}]}},
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{"y": {"f": ["v", "v2"]}},
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[
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{
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VERSION_FIELD: {
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"revision": "r",
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"filename": "f",
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"field": "v",
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},
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"dvc_inferred_y_value": 1,
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"v": 1,
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"v2": 0.1,
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"step": 0,
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},
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{
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VERSION_FIELD: {
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"revision": "r",
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"filename": "f",
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"field": "v",
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},
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"dvc_inferred_y_value": 2,
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"v": 2,
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"v2": 0.2,
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"step": 1,
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},
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{
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VERSION_FIELD: {
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"revision": "r",
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"filename": "f",
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"field": "v2",
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},
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"dvc_inferred_y_value": 0.1,
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"v2": 0.1,
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"v": 1,
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"step": 0,
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},
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{
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VERSION_FIELD: {
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"revision": "r",
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"filename": "f",
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"field": "v2",
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},
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"v": 2,
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"v2": 0.2,
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"dvc_inferred_y_value": 0.2,
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"step": 1,
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},
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],
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{
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"x": "step",
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"y": "dvc_inferred_y_value",
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"y_label": "y",
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"x_label": "step",
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},
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id="y_def_list",
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),
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pytest.param(
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{
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"f": {
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"metric": [{"v": 1}, {"v": 2}],
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"other_metric": [{"z": 3}, {"z": 4}],
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}
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},
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{"y": {"f": ["v", "z"]}},
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[
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{
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"dvc_inferred_y_value": 1,
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"z": 3,
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"v": 1,
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"step": 0,
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VERSION_FIELD: {
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"revision": "r",
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"filename": "f",
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"field": "v",
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},
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},
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{
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"dvc_inferred_y_value": 2,
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"z": 4,
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"step": 1,
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"v": 2,
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VERSION_FIELD: {
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"revision": "r",
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"filename": "f",
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"field": "v",
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},
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},
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{
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"dvc_inferred_y_value": 3,
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"v": 1,
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"z": 3,
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"step": 0,
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VERSION_FIELD: {
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"revision": "r",
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"filename": "f",
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"field": "z",
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},
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},
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{
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"dvc_inferred_y_value": 4,
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"v": 2,
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"z": 4,
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"step": 1,
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VERSION_FIELD: {
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"revision": "r",
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"filename": "f",
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"field": "z",
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},
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},
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],
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{
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"x": "step",
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"y": "dvc_inferred_y_value",
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"y_label": "y",
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"x_label": "step",
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},
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id="multi_source_json",
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),
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pytest.param(
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{
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"f": {"metric": [{"v": 1, "v2": 0.1}, {"v": 2, "v2": 0.2}]},
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"f2": {"metric": [{"v": 3, "v2": 0.3}]},
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},
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{"x": "v", "y": {"f": "v2", "f2": "v2"}},
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[
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{
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"v": 1,
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"v2": 0.1,
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VERSION_FIELD: {
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"revision": "r",
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"filename": "f",
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"field": "v2",
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},
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},
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{
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"v": 2,
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"v2": 0.2,
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VERSION_FIELD: {
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"revision": "r",
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"filename": "f",
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"field": "v2",
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},
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},
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{
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"v": 3,
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"v2": 0.3,
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VERSION_FIELD: {
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"revision": "r",
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"filename": "f2",
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"field": "v2",
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},
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},
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],
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{"x": "v", "y": "v2", "x_label": "v", "y_label": "v2"},
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id="multi_file_json",
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),
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pytest.param(
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{"f": {"metric": [{"v": 1, "v2": 0.1}, {"v": 2, "v2": 0.2}]}},
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{"y": ["v", "v2"]},
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[
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{
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"dvc_inferred_y_value": 1,
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"v": 1,
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"v2": 0.1,
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"step": 0,
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VERSION_FIELD: {
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"revision": "r",
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"filename": "f",
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"field": "v",
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},
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},
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{
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"dvc_inferred_y_value": 2,
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"v": 2,
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"v2": 0.2,
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"step": 1,
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VERSION_FIELD: {
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"revision": "r",
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"filename": "f",
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"field": "v",
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},
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},
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{
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"dvc_inferred_y_value": 0.1,
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"v": 1,
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"v2": 0.1,
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"step": 0,
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VERSION_FIELD: {
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"revision": "r",
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"filename": "f",
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"field": "v2",
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},
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},
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{
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"dvc_inferred_y_value": 0.2,
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"v": 2,
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"v2": 0.2,
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"step": 1,
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VERSION_FIELD: {
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"revision": "r",
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"filename": "f",
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"field": "v2",
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},
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},
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],
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{
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"x": "step",
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"y": "dvc_inferred_y_value",
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"x_label": "step",
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"y_label": "y",
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},
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id="y_list",
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),
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pytest.param(
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{
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"f": {"metric": [{"v": 1, "v2": 0.1, "v3": 0.01}]},
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"f2": {"metric": [{"v": 1, "v2": 0.1}]},
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},
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{"y": {"f": ["v2", "v3"], "f2": ["v2"]}, "x": "v"},
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[
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{
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"dvc_inferred_y_value": 0.1,
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"v": 1,
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"v2": 0.1,
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"v3": 0.01,
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VERSION_FIELD: {
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"revision": "r",
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"filename": "f",
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"field": "v2",
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},
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},
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{
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"dvc_inferred_y_value": 0.01,
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"v": 1,
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"v2": 0.1,
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"v3": 0.01,
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VERSION_FIELD: {
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"revision": "r",
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"filename": "f",
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"field": "v3",
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},
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},
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{
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"dvc_inferred_y_value": 0.1,
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"v": 1,
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"v2": 0.1,
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VERSION_FIELD: {
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"revision": "r",
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"filename": "f2",
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"field": "v2",
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},
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},
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],
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{
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"x": "v",
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"y": "dvc_inferred_y_value",
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"x_label": "v",
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"y_label": "y",
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},
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id="multi_source_y_single_x",
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),
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pytest.param(
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{
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"dir/f": {"metric": [{"v": 1, "v2": 0.1}]},
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"dir/f2": {"metric": [{"v": 1, "v2": 0.1}]},
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},
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{"y": {"dir/f": ["v2"], "dir/f2": ["v2"]}, "x": "v"},
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[
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{
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"v": 1,
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"v2": 0.1,
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VERSION_FIELD: {
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"revision": "r",
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"filename": "f",
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"field": "v2",
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},
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},
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{
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"v": 1,
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"v2": 0.1,
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VERSION_FIELD: {
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"revision": "r",
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"filename": "f2",
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"field": "v2",
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},
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},
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],
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{
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"x": "v",
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"y": "v2",
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"x_label": "v",
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"y_label": "v2",
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},
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id="multi_file_y_same_prefix",
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),
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],
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)
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def test_convert(
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input_data,
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properties,
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expected_datapoints,
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expected_properties,
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):
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converter = VegaConverter("f", input_data, properties)
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datapoints, resolved_properties = converter.flat_datapoints("r")
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assert datapoints == expected_datapoints
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assert resolved_properties == expected_properties
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@pytest.mark.parametrize(
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"input_data,properties,exc",
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[
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pytest.param(
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{
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"f": {
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"metric": [
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{"v": 1},
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{"v": 2},
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]
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},
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"f2": {"metric": [{"v2": 0.1}]},
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},
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{"x": {"f": "v"}, "y": {"f2": "v2"}},
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DvcException,
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id="unequal_datapoints",
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),
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pytest.param(
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{
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"f": {
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"metric": [
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{"v": 1, "v2": 0.1},
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{"v": 2, "v2": 0.2},
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]
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},
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"f2": {
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"metric": [
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{"v": 3, "v2": 0.3},
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]
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},
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},
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{"x": {"f": "v", "f2": "v3"}, "y": {"f": "v2"}},
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FieldNotFoundError,
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id="unequal_x_y",
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),
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],
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)
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def test_convert_fail(input_data, properties, exc):
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converter = VegaConverter("f", input_data, properties)
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with pytest.raises(exc):
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converter.flat_datapoints("r")
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@pytest.mark.parametrize(
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"properties,label",
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[
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({"x": {"actual.csv": "actual"}}, "actual"),
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(
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{"x": {"train_actual.csv": "actual", "val_actual.csv": "actual"}},
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"actual",
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),
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(
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{"x": {"actual.csv": "actual", "predicted.csv": "predicted"}},
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"x",
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),
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],
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)
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def test_infer_x_label(properties, label):
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assert VegaConverter.infer_x_label(properties) == label
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