Add audformat.Database.get()

audformat/core/database.py

@@ -433,6 +433,119 @@ def duration(file: str) -> pd.Timedelta:
 
         return y
 
+    def get(
+            self,
+            schemes: typing.Union[str, typing.Sequence],
+    ) -> pd.Series:
+        r"""Get labels by scheme(s).
+
+        Return all labels
+        that match the requested schemes.
+        A scheme is defined more broadly
+        and does not only match
+        schemes of the database,
+        but also columns with the same name
+        or labels of a scheme with the requested name.
+
+        Args:
+            schemes: scheme or sequence of scheme.
+
+        Returns:
+            labels
+
+        """
+
+        def scheme_in_column(scheme, column, column_id):
+            # Check if scheme
+            # is attached to a column,
+            # or is part of the column name
+            return (
+                scheme in column_id
+                or (
+                    column.scheme_id is not None
+                    and scheme in column.scheme_id
+                )
+            )
+
+        def clean_y(y):
+            # Remove NaN and normalize dtypes
+            #
+            # TODO: at the moment we simply convert to string
+            # to avoid errors for different categorical data types.
+            # In real implementation we need to adjust those dtypes.
+            return y.dropna().astype('string')
+
+        requested_schemes = audeer.to_list(schemes)
+
+        print(f'{requested_schemes=}')
+        # Check if requested schemes
+        # are stored as labels in other schemes
+        scheme_mappings = []
+        for scheme_id, scheme in self.schemes.items():
+
+            print(f'{scheme_id=}')
+            if scheme.uses_table and scheme_id in self.misc_tables:
+                print('scheme stored in misc table')
+                # Labels stored as misc table
+                for column_id, column in self[scheme_id].columns.items():
+                    print(f'{column_id=}')
+                    for requested_scheme in requested_schemes:
+                        if scheme_in_column(
+                                requested_scheme, column, column_id
+                        ):
+                            scheme_mappings.append(
+                                (scheme_id, requested_scheme)
+                            )
+                            break
+            else:
+                # Labels stored in scheme
+                for requested_scheme in requested_schemes:
+                    print('scheme stored in labels')
+                    if scheme_id in scheme.labels_as_list:
+                        scheme_mappings.append((scheme_id, requested_scheme))
+                        break
+            print(f'{scheme_mappings=}')
+            print(f'{requested_schemes=}')
+
+            # Get data points for requested schemes
+            ys = []
+            for table_id, table in self.tables.items():
+                print(f'{table_id=}')
+                for column_id, column in table.columns.items():
+                    print(f'{column_id=}')
+                    print(f'{column.scheme_id=}')
+                    print(f'{"speaker" in column_id=}')
+                    print(f'{"speaker" in column.scheme_id=}')
+                    # Get series based on scheme in column
+                    if any(
+                            [
+                                scheme_in_column(
+                                    requested_scheme,
+                                    column,
+                                    column_id,
+                                )
+                                for requested_scheme in requested_schemes
+                            ]
+                    ):
+                        print('Found requested scheme')
+                        y = self[table_id][column_id].get()
+                        ys.append(clean_y(y))
+                    # Get series based on label of scheme
+                    else:
+                        print('Look for mapped schemes')
+                        for (scheme_id, mapping) in scheme_mappings:
+                            print(f'{scheme_id=}')
+                            if scheme_in_column(scheme_id, column, column_id):
+                                print('Found scheme')
+                                y = self[table_id][column_id].get(map=mapping)
+                                ys.append(clean_y(y))
+
+            index = utils.union([y.index for y in ys])
+            y = utils.concat(ys).loc[index]
+            y.name = ', '.join(requested_schemes)
+
+        return y
+
     def map_files(
             self,
             func: typing.Callable[[str], str],

tests/test_database_get.py

@@ -0,0 +1,93 @@
+import numpy as np
+import pandas as pd
+import pytest
+
+import audeer
+
+import audformat
+import audformat.testing
+
+
+@pytest.fixture(scope='function', autouse=True)
+def mono_db(tmpdir):
+    r"""Database with ..."""
+    name = 'mono-db'
+    path = audeer.mkdir(audeer.path(tmpdir, name))
+    db = audformat.Database(name)
+
+    db.schemes['age'] = audformat.Scheme('int', minimum=0)
+
+    # Misc table with speaker information
+    index = pd.Index(['s1', 's2', 's3'], name='speaker', dtype='string')
+    db['speaker'] = audformat.MiscTable(index)
+    db['speaker']['age'] = audformat.Column(scheme_id='age')
+    db['speaker']['gender'] = audformat.Column()
+    db['speaker']['age'].set([23, np.NaN, 59])
+    db['speaker']['gender'].set(['female', '', 'male'])
+
+    db.schemes['speaker'] = audformat.Scheme('str', labels='speaker')
+
+    # Filewise table with speaker information
+    index = audformat.filewise_index(['f1.wav', 'f2.wav', 'f3.wav'])
+    db['files'] = audformat.Table(index)
+    db['files']['channel0'] = audformat.Column(scheme_id='speaker')
+    db['files']['channel0'].set(['s1', 's2', 's3'])
+
+    db.save(path)
+    audformat.testing.create_audio_files(db, channels=1, file_duration='1s')
+
+    return db
+
+
+@pytest.fixture(scope='function')
+def stereo_db(tmpdir):
+    r"""Database with ..."""
+    name = 'stereo-db'
+    path = audeer.mkdir(audeer.path(tmpdir, name))
+    db = audformat.Database(name)
+
+    db.schemes['age'] = audformat.Scheme('int', minimum=0)
+
+    # Misc table with speaker information
+    index = pd.Index(['s1', 's2', 's3'], name='speaker', dtype='string')
+    db['speaker'] = audformat.MiscTable(index)
+    db['speaker']['age'] = audformat.Column(scheme_id='age')
+    db['speaker']['gender'] = audformat.Column()
+    db['speaker']['age'].set([23, np.NaN, 59])
+    db['speaker']['gender'].set(['female', '', 'male'])
+
+    db.schemes['speaker'] = audformat.Scheme('str', labels='speaker')
+
+    # Filewise table with speaker information
+    index = audformat.filewise_index(['f1.wav', 'f2.wav', 'f3.wav'])
+    db['files'] = audformat.Table(index)
+    db['files']['channel0'] = audformat.Column(scheme_id='speaker')
+    db['files']['channel1'] = audformat.Column(scheme_id='speaker')
+    db['files']['channel0'].set(['s1', 's2', 's3'])
+    db['files']['channel1'].set(['s3', 's1', 's2'])
+
+    db.save(path)
+    audformat.testing.create_audio_files(db, channels=2, file_duration='1s')
+
+
+@pytest.mark.parametrize(
+    'db, schemes, expected',
+    [
+        (
+            'mono_db',
+            ['sex', 'gender'],
+            pd.Series(
+                ['female', '', 'male'],
+                index=audformat.filewise_index(['f1.wav', 'f2.wav', 'f3.wav']),
+                dtype='string',
+                name='sex, gender',
+            ),
+        ),
+    ]
+)
+def test_database_get(request, db, schemes, expected):
+    db = request.getfixturevalue(db)
+    y = db.get(schemes)
+    print(f'{y=}')
+    print(f'{expected=}')
+    pd.testing.assert_series_equal(y, expected)