def as_normalized(observations: np.ndarray,
coordinates: ty.Coordinates,
labels=None) -> ty.Dataset:
"""Create a dummy dataset from transformed spectra"""
dimensionality = observations.shape[1] if len(
observations.shape) > 1 else 0
artificial_mz = np.arange(dimensionality)
normalized = ty.Dataset(observations, coordinates, artificial_mz, labels)
return normalized
import aspect._export as ex
class DatasetNameTest(unittest.TestCase):
def test_extracts_dataset_name(self):
name = 'some-dataset'
analysis_root = os.path.join(DATA_ROOT, name, 'tSNE', 'blah')
found = ex.dataset_name(analysis_root)
self.assertEqual(name, found)
SPECTRA = [[4]]
COORDINATES = ty.Coordinates([1], [2], [3])
MZ = [5]
LABELS = [6]
DATASET = ty.Dataset(SPECTRA, COORDINATES, MZ, LABELS)
def returns(value):
return MagicMock(return_value=value)
def throws(exception):
return MagicMock(side_effect=exception)
@patch.object(ex, ex.dataset_name.__name__, new=returns('data'))
@patch.object(ex, ex.load_dataset.__name__, new=returns(DATASET))
class GetMetadataTest(unittest.TestCase):
def test_loads_coordinates_and_labels_of_analysed_dataset(self):
metadata = ex.get_metadata('blah')
def test_throws_on_mismatching_labels(self):
with self.assertRaises(ValueError):
ty.Dataset(spectra=[[1, 2], [3, 4]],
coordinates=self.coordinates,
mz=[1.1, 2.2],
labels=[9])
import unittest
from unittest.mock import MagicMock, mock_open, patch
from io import StringIO
import numpy as np
import numpy.testing as npt
import spdata.types as ty
import spdata.reader as rd
import spdata.common as cmn
import data_utils
COORDINATES = ty.Coordinates(x=[1], y=[2], z=[3])
DATASET = ty.Dataset([[4, 5]], COORDINATES, [6, 7], [8])
SPECTRA = DATASET.spectra
def mock_iterable_open(mock=None, read_data=''):
iterable_mock = mock_open(mock, read_data)
iterable_mock.return_value.__iter__ = lambda self: self
iterable_mock.return_value.__next__ = lambda self: next(iter(self.readline, ''))
return iterable_mock
class AsNormalizedTest(unittest.TestCase):
def test_throws_on_sizes_mismatch(self):
with self.assertRaises(ValueError):
data_utils.as_normalized(np.array([[1], [2]]), COORDINATES)
with self.assertRaises(ValueError):
def test_throws_on_missing_mzs(self):
with self.assertRaises(ValueError):
ty.Dataset(spectra=[[1, 2], [3, 4]],
coordinates=self.coordinates,
mz=[1.1])