diff --git a/pyproject.toml b/pyproject.toml
new file mode 100644
index 0000000000000000000000000000000000000000..9787c3bdf008a57ae3cb2e27a8261eb3f134ff73
--- /dev/null
+++ b/pyproject.toml
@@ -0,0 +1,3 @@
+[build-system]
+requires = ["setuptools", "wheel"]
+build-backend = "setuptools.build_meta"
diff --git a/setup.cfg b/setup.cfg
index e40d558e5d94fa5322183991a9cefc953df01448..c9df0ea3baebf1708523e1a04f6fd8b8603f7dbc 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -1,6 +1,6 @@
[metadata]
name = comsar
-version = 0.0.1
+version = 0.0.2
description = Computational Music and Sound Archiving
long_description = file: README.md
licence = BSD-3-Clause
@@ -10,9 +10,8 @@ keywords = hmm, som, comsar, music, analysis
classifiers =
Programming Language :: Python :: 3
- Programming Language :: Python :: 3.6
- Programming Language :: Python :: 3.7
Programming Language :: Python :: 3 :: Only
+ Programming Language :: Python :: 3.7
Programming Language :: Python :: Implementation :: CPython
Topic :: Scientific/Engineering
Topic :: Database
@@ -22,16 +21,15 @@ classifiers =
License :: OSI Approved :: BSD License
[options]
-zip_safe = True
-include_package_data = True
-packages = find:
-scripts = scripts/comsar
-setup_requires = numpy
+zip_safe = False
+package_dir =
+ =src
+include_package_data = False
+packages = find_namespace:
+python_requires >= '3.7'
install_requires =
numpy
- scipy >= "0.19.0"
- matplotlib >= "2"
- pandas >= "0.20"
- setuptools >= "40.0.0"
- sklearn >= "0.20"
-
+ pandas
+
+[options.packages.find]
+where = src
diff --git a/comsar/__init__.py b/src/comsar/__init__.py
similarity index 50%
rename from comsar/__init__.py
rename to src/comsar/__init__.py
index 2ba8bbf8da4bfdf8938557f7661e8b3ee747f6c9..c6750dd4dbfa24dfdbdc50cbabcb977f7faf757f 100644
--- a/comsar/__init__.py
+++ b/src/comsar/__init__.py
@@ -1,6 +1,3 @@
import pkg_resources as _pkg
-from .tracks.timbre import TimbreTrack
-from .tracks.utilities import TrackResult
-
__version__ = _pkg.get_distribution('comsar').version
diff --git a/comsar/tracks/__int__.py b/src/comsar/_tracks/__int__.py
similarity index 100%
rename from comsar/tracks/__int__.py
rename to src/comsar/_tracks/__int__.py
diff --git a/comsar/tracks/form.py b/src/comsar/_tracks/form.py
similarity index 100%
rename from comsar/tracks/form.py
rename to src/comsar/_tracks/form.py
diff --git a/comsar/tracks/pitch.py b/src/comsar/_tracks/pitch.py
similarity index 100%
rename from comsar/tracks/pitch.py
rename to src/comsar/_tracks/pitch.py
diff --git a/comsar/tracks/rhythm.py b/src/comsar/_tracks/rhythm.py
similarity index 100%
rename from comsar/tracks/rhythm.py
rename to src/comsar/_tracks/rhythm.py
diff --git a/comsar/tracks/timbre.py b/src/comsar/_tracks/timbre.py
similarity index 51%
rename from comsar/tracks/timbre.py
rename to src/comsar/_tracks/timbre.py
index 14e173ba89b0f3255f57efa1d300ef23977a9515..9098d134ee51aa1776dc490fa1015b571456e9f2 100644
--- a/comsar/tracks/timbre.py
+++ b/src/comsar/_tracks/timbre.py
@@ -2,7 +2,7 @@
License: BSD-3-Clasuse
Copyright (C) 2020, Michael Blaß, michael.blass@uni-hamburg.de
"""
-from dataclasses import dataclass
+from datetime import datetime
from timeit import default_timer as timer
from typing import Optional
@@ -13,10 +13,10 @@ from apollon.audio import AudioFile
from apollon.segment import Segmentation
from apollon.signal import container, features
from apollon.signal.spectral import StftSegments
-from apollon.tools import time_stamp
import comsar
-from comsar.tracks.utilities import TrackMeta, TrackParams, TrackResult, TimbreTrackParams
+from comsar._tracks.utilities import (TrackMeta, TrackResult, SourceMeta,
+ TimbreTrackParams, TimbreTrackCorrGramParams)
STFT_DEFAULT = container.StftParams(fps=44100, window='hamming', n_fft=None,
@@ -29,9 +29,90 @@ CORR_DIM_DEFAULT = container.CorrDimParams(delay=14, m_dim=80, n_bins=1000,
CORR_GRAM_DEFAULT = container.CorrGramParams(wlen=2**10, n_delay=2**8, total=True)
+class TimbreTrack:
+ """Compute timbre track of an audio file.
+ """
+ def __init__(self,
+ stft_params: Optional[container.StftParams] = None,
+ corr_dim_params: Optional[container.CorrDimParams] = None,
+ ) -> None:
+ """
+ Args:
+ """
+ self.params = TimbreTrackParams(stft_params or STFT_DEFAULT,
+ corr_dim_params or CORR_DIM_DEFAULT)
+ self.cutter = Segmentation(self.params.stft.n_perseg,
+ self.params.stft.n_overlap,
+ self.params.stft.extend,
+ self.params.stft.pad)
-class TimbreTrack:
+ self.stft = StftSegments(self.params.stft.fps, self.params.stft.window,
+ self.params.stft.n_fft)
+
+ self.feature_names = ('SpectralCentroid', 'SpectralSpread',
+ 'SpectralFlux', 'Roughness', 'Sharpness',
+ 'SPL', 'CorrelationDimension')
+
+ self.funcs = [features.spectral_centroid,
+ features.spectral_spread,
+ features.spectral_flux,
+ features.roughness_helmholtz,
+ features.sharpness,
+ features.spl,
+ features.cdim]
+
+ self.pace = np.zeros(self.n_features)
+ self.verbose = False
+
+ @property
+ def n_features(self) -> int:
+ """Number of features on track"""
+ return len(self.feature_names)
+
+ def extract(self, path) -> pd.DataFrame:
+ """Perform extraction.
+ """
+ snd = AudioFile(path)
+ if snd.fps != self.params.stft.fps:
+ snd.close()
+ raise ValueError('Sample rate of {snd!str} differs from init.')
+
+ segs = self.cutter.transform(snd.data.squeeze())
+ sxx = self.stft.transform(segs)
+
+ args = [(sxx.frqs, sxx.power),
+ (sxx.frqs, sxx.power),
+ (sxx.abs,),
+ (sxx.d_frq, sxx.abs, 15000),
+ (sxx.frqs, sxx.abs),
+ (segs.data,),
+ (segs.data,)]
+
+ kwargs = [{}, {}, {}, {}, {}, {}, self.params.corr_dim.to_dict()]
+
+ out = np.zeros((segs.n_segs, self.n_features))
+ for i, (fun, arg, kwarg) in enumerate(zip(self.funcs, args, kwargs)):
+ out[:, i] = self._worker(i, fun, arg, kwarg)
+
+ file_meta = SourceMeta(*snd.file_name.split('.'), snd.hash)
+ track_meta = TrackMeta(comsar.__version__, datetime.utcnow(),
+ file_meta)
+ out = pd.DataFrame(data=out, columns=self.feature_names)
+ snd.close()
+ return TrackResult(track_meta, self.params, out)
+
+ def _worker(self, idx, func, args, kwargs) -> np.ndarray:
+ print(self.feature_names[idx], end=' ... ')
+ pace = timer()
+ res = func(*args, **kwargs)
+ pace = timer() - pace
+ self.pace[idx] = pace
+ print(f'{pace:.4} s.')
+ return res
+
+
+class TimbreTrackCorrGram:
"""Compute timbre track of an audio file.
"""
def __init__(self,
@@ -41,7 +122,7 @@ class TimbreTrack:
"""
Args:
"""
- self.params = TimbreTrackParams(stft_params or STFT_DEFAULT,
+ self.params = TimbreTrackCorrGramParams(stft_params or STFT_DEFAULT,
corr_dim_params or CORR_DIM_DEFAULT,
corr_gram_params or CORR_GRAM_DEFAULT)
@@ -52,9 +133,9 @@ class TimbreTrack:
self.stft = StftSegments(self.params.stft.fps, self.params.stft.window,
self.params.stft.n_fft)
- self.feature_names = ('Spectral Centroid', 'Spectral Spread',
- 'Spectral Flux', 'Roughness', 'Sharpness',
- 'SPL', 'Correlation Dimension', 'Correlogram')
+ self.feature_names = ('SpectralCentroid', 'SpectralSpread',
+ 'SpectralFlux', 'Roughness', 'Sharpness',
+ 'SPL', 'CorrelationDimension', 'Correlogram')
self.funcs = [features.spectral_centroid,
features.spectral_spread,
@@ -101,7 +182,7 @@ class TimbreTrack:
out[:, i] = self._worker(i, fun, arg, kwarg)
snd.close()
- meta = TrackMeta(comsar.__version__, time_stamp(), snd.file_name)
+ meta = TrackMeta(comsar.__version__, datetime.utcnow(), snd.file_name)
out = pd.DataFrame(data=out, columns=self.feature_names)
return TrackResult(meta, self.params, out)
diff --git a/comsar/tracks/utilities.py b/src/comsar/_tracks/utilities.py
similarity index 81%
rename from comsar/tracks/utilities.py
rename to src/comsar/_tracks/utilities.py
index 549acbfe4f438eb3564b23c6c7ba984be62ef864..c07c68ba2dcc056b1ca0d797bec2c1d0ff768ed5 100644
--- a/comsar/tracks/utilities.py
+++ b/src/comsar/_tracks/utilities.py
@@ -2,6 +2,7 @@
License: BSD-3-Clasuse
Copyright (C) 2020, Michael Blaß, michael.blass@uni-hamburg.de
"""
+import datetime
import pathlib
import pickle
from typing import ClassVar, Type, TypeVar, Union
@@ -12,20 +13,30 @@ import pandas as pd
from apollon import io
from apollon import container
-from apollon import signal
+from apollon.signal import container as asc
from apollon.tools import standardize
from apollon import types
T = TypeVar('T')
+
+@dataclass
+class SourceMeta(container.Params):
+ """Source file meta data."""
+ _schema: ClassVar[types.Schema] = None
+ name: str
+ extension: str
+ hash_: str
+
+
@dataclass
class TrackMeta(container.Params):
"""Track meta data."""
_schema: ClassVar[types.Schema] = None
version: str
- time_stamp: str
- source: str
+ extraction_date: datetime.datetime
+ source: SourceMeta
@dataclass
@@ -37,9 +48,15 @@ class TrackParams(container.Params):
@dataclass
class TimbreTrackParams(TrackParams):
"""Parameter set for TimbreTrack"""
- stft: signal.container.StftParams
- corr_dim: signal.container.CorrDimParams
- corr_gram: signal.container.CorrGramParams
+ stft: asc.StftParams
+ corr_dim: asc.CorrDimParams
+
+
+@dataclass
+class TimbreTrackCorrGramParams(TrackParams):
+ """Parameter set for TimbreTrack"""
+ stft: asc.StftParams
+ corr_dim: asc.CorrDimParams
class TrackResult:
@@ -84,13 +101,17 @@ class TrackResult:
"""Serialize TrackResults to dictionary."""
return {'meta': self._meta.to_dict(),
'params': self._params.to_dict(),
- 'data': self._data.to_dict()}
+ 'data': self._data.to_dict(orient='list')}
def to_json(self, path: Union[str, pathlib.Path]) -> None:
"""Serialize TrackResults to JSON."""
io.json.dump(self.to_dict(), path)
+ def to_mongo(self, db_con) -> None:
+ """Write TrackResults to open MongoDB connection:"""
+ pass
+
def to_pickle(self, path: Union[str, pathlib.Path]) -> None:
"""Serialize Track Results to pickle."""
path = pathlib.Path(path)
diff --git a/comsar/cli/__init__.py b/src/comsar/cli/__init__.py
similarity index 100%
rename from comsar/cli/__init__.py
rename to src/comsar/cli/__init__.py
diff --git a/comsar/cli/apollon_hmm.py b/src/comsar/cli/apollon_hmm.py
similarity index 100%
rename from comsar/cli/apollon_hmm.py
rename to src/comsar/cli/apollon_hmm.py
diff --git a/comsar/cli/apollon_onsets.py b/src/comsar/cli/apollon_onsets.py
similarity index 100%
rename from comsar/cli/apollon_onsets.py
rename to src/comsar/cli/apollon_onsets.py
diff --git a/comsar/cli/apollon_position.py b/src/comsar/cli/apollon_position.py
similarity index 100%
rename from comsar/cli/apollon_position.py
rename to src/comsar/cli/apollon_position.py
diff --git a/comsar/cli/comsar_features.py b/src/comsar/cli/comsar_features.py
similarity index 100%
rename from comsar/cli/comsar_features.py
rename to src/comsar/cli/comsar_features.py
diff --git a/src/comsar/tracks.py b/src/comsar/tracks.py
new file mode 100644
index 0000000000000000000000000000000000000000..41aee0798c76b89ce1baf81e5cf4e077c691cece
--- /dev/null
+++ b/src/comsar/tracks.py
@@ -0,0 +1,2 @@
+from . _tracks.timbre import TimbreTrack
+from . _tracks.timbre import TimbreTrackCorrGram
diff --git a/tests/tracks/test_timbre.py b/tests/tracks/test_timbre.py
index 4287cb6858eca9fa840d82eba02c76264b2c5515..9dabb3279c757efac6a1a761f984e3a040bccfd6 100644
--- a/tests/tracks/test_timbre.py
+++ b/tests/tracks/test_timbre.py
@@ -3,10 +3,7 @@ import numpy as np
import pandas as pd
from apollon.tools import time_stamp
-from comsar.tracks.timbre import (TimbreTrack,
- STFT_DEFAULT, CORR_DIM_DEFAULT, CORR_GRAM_DEFAULT)
-import comsar
-from comsar.tracks.utilities import TrackMeta, TrackParams, TrackResult, TimbreTrackParams
+from comsar.tracks import TimbreTrack
class TestTimbreTrack(unittest.TestCase):
@@ -15,5 +12,3 @@ class TestTimbreTrack(unittest.TestCase):
def test_nfeatures(self):
self.assertIsInstance(self.track.n_features, int)
-
-
diff --git a/tests/tracks/test_utilities.py b/tests/tracks/test_utilities.py
index 5e85e29e3e0e6c80666313f07b4407afdf54741c..107be3436ad825b939a444f6f324b9c06ab25ddc 100644
--- a/tests/tracks/test_utilities.py
+++ b/tests/tracks/test_utilities.py
@@ -4,15 +4,14 @@ import unittest
from hypothesis import given
-from comsar import TrackResult
-from comsar.tracks.timbre import TimbreTrackParams
-from .. utils import timbre_track_results
+from comsar._tracks.utilities import TimbreTrackParams, TrackResult
+from utils import timbre_track_results
class TestTrackResult(unittest.TestCase):
def setUp(self) -> None:
self.tf_descr, self.tf_name = tempfile.mkstemp(suffix='.json',
- text=True)
+ text=True)
@given(timbre_track_results())
def test_init(self, ttr) -> None:
diff --git a/tests/utils.py b/tests/utils.py
index cd2c3b4c42359d6e4221013f493422c5ac5de9b7..2cac6809ec7835a5eeca0c2f126ecc0d5f30a5a9 100644
--- a/tests/utils.py
+++ b/tests/utils.py
@@ -1,3 +1,6 @@
+"""
+Utilities for testing.
+"""
import string
from hypothesis.strategies import (composite, integers, lists, sampled_from,
@@ -7,8 +10,8 @@ import pandas as pd
from apollon.tools import time_stamp
import comsar
-from comsar.tracks import timbre
-from comsar.tracks.utilities import TrackMeta, TimbreTrackParams, TrackResult
+from comsar._tracks import timbre
+from comsar._tracks.utilities import TrackMeta, TimbreTrackParams, TrackResult
def ascii_strings() -> SearchStrategy:
@@ -16,10 +19,12 @@ def ascii_strings() -> SearchStrategy:
return text(sampled_from(string.ascii_letters+string.digits),
min_size=2, max_size=10)
+
def lists_of_strings() -> SearchStrategy:
"""Lists of unique ascii_strings."""
return lists(ascii_strings(), min_size=2, max_size=10, unique=True)
+
@composite
def numerical_dataframes(draw) -> pd.DataFrame:
"""Generate pandas DataFrames.
@@ -32,11 +37,14 @@ def numerical_dataframes(draw) -> pd.DataFrame:
data = draw(arrays('float64', (n_rows, len(names))))
return pd.DataFrame(data=data, columns=names)
+
@composite
def timbre_track_results(draw) -> TrackResult:
- meta = TrackMeta(comsar.__version__, time_stamp(), 'testfile.wav')
+ """Mock the result of a timbre track extraction pipeline.
+ """
+ meta = TrackMeta(comsar.__version__, time_stamp(), 'testfile.wav',
+ draw(ascii_strings()))
params = TimbreTrackParams(timbre.STFT_DEFAULT,
- timbre.CORR_DIM_DEFAULT,
- timbre.CORR_GRAM_DEFAULT)
+ timbre.CORR_DIM_DEFAULT)
data = draw(numerical_dataframes())
return TrackResult(meta, params, data)