Parsing the numerical output from Sensovation SensoSpot image analysis.
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from collections import namedtuple
import pytest
ExposureSetting = namedtuple("ExposureSetting", ["channel", "time"])
def test_split(data_frame_with_params):
from sensospot_data.utils import split
result = split(data_frame_with_params, "Well.Row")
assert set(result.keys()) == set("ABC")
for key, value_df in result.items():
assert set(value_df["Well.Row"].unique()) == {key}
@pytest.mark.parametrize(
"value,expected",
[
[[1, 2], True],
[(1, 2), True],
[{1, 2}, False],
[{1: 2}, False],
["1, 2", False],
[None, False],
],
)
def test_is_list_or_tuple(value, expected):
from sensospot_data.utils import _is_list_or_tuple
result = _is_list_or_tuple(value)
assert result is expected
@pytest.mark.parametrize(
"value,expected",
[
[1, True],
[1.2, True],
[{1, 2}, False],
[{1: 2}, False],
["1", False],
[None, False],
],
)
def test_is_numerical(value, expected):
from sensospot_data.utils import _is_numerical
result = _is_numerical(value)
assert result is expected
def test_check_valid_exposure_map_entry_ok():
from sensospot_data.utils import _check_valid_exposure_map_entry
result = _check_valid_exposure_map_entry((2, 1))
assert result is None
@pytest.mark.parametrize(
"value", [[], [1], (1, 2, 3), {"a": 1, "b": 2}, ("A", "B")]
)
def test_check_valid_exposure_map_entry_raises_error(value):
from sensospot_data.utils import _check_valid_exposure_map_entry
with pytest.raises(ValueError):
_check_valid_exposure_map_entry(value)
def test_check_exposure_map_ok(exposure_df):
from sensospot_data.utils import _check_exposure_map
exposure_map = {1: ("A", 10), 2: ("B", 20), 3: ("C", 30)}
result = _check_exposure_map(exposure_df, exposure_map)
assert result is None
def test_check_exposure_map_wrong_type(exposure_df):
from sensospot_data.utils import _check_exposure_map
exposure_map = []
with pytest.raises(ValueError):
_check_exposure_map(exposure_df, exposure_map)
def test_check_exposure_map_wrong_ids(exposure_df):
from sensospot_data.utils import _check_exposure_map
exposure_map = {1: ("A", 10), 2: ("B", 20), 4: ("D", 40)}
with pytest.raises(ValueError):
_check_exposure_map(exposure_df, exposure_map)
def test_check_exposure_map_invalid_entries(exposure_df):
from sensospot_data.utils import _check_exposure_map
exposure_map = {1: ("A", 10), 2: ("B", 20), 3: "ERROR"}
with pytest.raises(ValueError):
_check_exposure_map(exposure_df, exposure_map)
def test_infer_exposure_from_parameters(data_frame_with_params):
from sensospot_data.utils import _set_exposure_data_from_parameters
result = _set_exposure_data_from_parameters(data_frame_with_params)
assert all(result["Exposure.Channel"] == result["Parameters.Channel"])
assert all(result["Exposure.Time"] == result["Parameters.Time"])
def test_infer_exposure_from_parameters_raises_error(
data_frame_without_params,
):
from sensospot_data.utils import _set_exposure_data_from_parameters
with pytest.raises(ValueError) as excinfo:
_set_exposure_data_from_parameters(data_frame_without_params)
assert str(excinfo.value).startswith("Exposure Map: measurement")
def test_apply_exposure_map(data_frame_with_params):
from sensospot_data.utils import apply_exposure_map
exposure_map = {
1: ExposureSetting("Cy3", 100),
2: ExposureSetting("Cy5", 15),
3: ExposureSetting("Cy5", 150),
}
result = apply_exposure_map(data_frame_with_params, exposure_map)
for key, value in exposure_map.items():
mask = result["Exposure.Id"] == key
partial = result.loc[mask]
assert set(partial["Exposure.Channel"].unique()) == {value.channel}
assert set(partial["Exposure.Time"].unique()) == {value.time}
def test_apply_exposure_map_raises_error(data_frame_with_params):
from sensospot_data.utils import apply_exposure_map
exposure_map = {
1: ExposureSetting("Cy3", 100),
2: ExposureSetting("Cy5", 15),
"X": ExposureSetting("Cy5", 150),
}
with pytest.raises(ValueError):
apply_exposure_map(data_frame_with_params, exposure_map)
def test_apply_exposure_map_from_parameters(data_frame_with_params):
from sensospot_data.utils import apply_exposure_map
result = apply_exposure_map(data_frame_with_params, None)
assert all(result["Exposure.Channel"] == result["Parameters.Channel"])
assert all(result["Exposure.Time"] == result["Parameters.Time"])
def test_apply_exposure_map_from_parameters_raises_error(
data_frame_without_params,
):
from sensospot_data.utils import apply_exposure_map
with pytest.raises(ValueError) as excinfo:
apply_exposure_map(data_frame_without_params, None)
assert str(excinfo.value).startswith("Exposure Map: measurement")
def test_apply_map(exposure_df):
from sensospot_data.utils import apply_map
map = {
1: {"SomeColumn": "A", "OtherColumn": 9},
2: {"SomeColumn": "B", "OtherColumn": 8},
3: {"SomeColumn": "C", "OtherColumn": 7},
}
result = apply_map(exposure_df, map, "Exposure.Id")
for key, value in map.items():
mask = result["Exposure.Id"] == key
partial = result.loc[mask]
assert set(partial["SomeColumn"].unique()) == {value["SomeColumn"]}
3 years ago
assert set(partial["OtherColumn"].unique()) == {value["OtherColumn"]}