"""module with functions that handle .txt annotation files
from Raven (https://ravensoundsoftware.com/software/).
Adapted in part from ``opensoundscape``
https://github.com/kitzeslab/opensoundscape/blob/master/opensoundscape/annotations.py
under MIT license
"""
import pathlib
from typing import ClassVar, List, Optional
import attr
import pandas as pd
import pandera.pandas
from pandera.typing import Series
import crowsetta
from crowsetta.typing import PathLike
[docs]
class RavenSchema(pandera.pandas.DataFrameModel):
"""A :class:`pandera.pandas.DataFrameModel` that validates a :type:`pandas.DataFrame`
loaded from a txt file, created by exporting a Selection Table from Raven.
"""
begin_time_s: Series[float] = pandera.pandas.Field()
end_time_s: Series[float] = pandera.pandas.Field()
low_freq_hz: Series[float] = pandera.pandas.Field()
high_freq_hz: Series[float] = pandera.pandas.Field()
annotation: Series[pd.StringDtype] = pandera.pandas.Field(coerce=True)
[docs]
class Config:
# we set strict fo False
# because we just ignore other columns, e.g. 'Selection',
# and because there should be an annotation column
# and we don't want to throw an error because of it
strict = False
[docs]
@crowsetta.interface.BBoxLike.register
@attr.define
class Raven:
"""Class that represents txt annotation files
from Raven (https://ravensoundsoftware.com/software/),
created by exporting a Selection Table.
Attributes
----------
name: str
Shorthand name for annotation format: 'raven'.
ext: str
Extension of files in annotation format: '.txt'
df : pandas.DataFrame
with annotations loaded into it
annot_path : str, pathlib.Path
Path to Raven txt file from which annotations were loaded.
audio_path : str. pathlib.Path
Path to audio file that the Raven txt file annotates.
Examples
--------
>>> raven = crowsetta.example('Recording1')
>>> print(raven)
Raven(df= Selection View Channel begin_time_s end_time_s low_freq_hz high_freq_hz annotation
0 1 Spectrogram 1 1 154.387793 154.911598 2878.2 4049.0 EATO
1 2 Spectrogram 1 1 167.526598 168.173020 2731.9 3902.7 EATO
2 3 Spectrogram 1 1 183.609637 184.097752 2878.2 3975.8 EATO
3 4 Spectrogram 1 1 250.527481 251.160711 2756.2 3951.4 EATO
4 5 Spectrogram 1 1 277.887243 278.480896 2707.5 3975.8 EATO
5 6 Spectrogram 1 1 295.529708 296.110168 2951.4 3975.8 EATO, annot_path=PosixPath('/Users/davidnicholson/Documents/repos/vocalpy/crowsetta/src/crowsetta/examples/Recording_1_Segment_02.Table.1.selections.txt'), annot_col='Species', audio_path=None) # noqa: E501
"""
name: ClassVar[str] = "raven"
ext: ClassVar[str] = (".txt",)
COLUMNS_MAP: ClassVar[dict] = {
"Begin Time (s)": "begin_time_s",
"End Time (s)": "end_time_s",
"Low Freq (Hz)": "low_freq_hz",
"High Freq (Hz)": "high_freq_hz",
}
df: pd.DataFrame
annot_path: pathlib.Path
annot_col: str
audio_path: Optional[pathlib.Path] = attr.field(default=None, converter=attr.converters.optional(pathlib.Path))
[docs]
@classmethod
def from_file(
cls, annot_path: PathLike, annot_col: str = "Annotation", audio_path: Optional[PathLike] = None
) -> "Self": # noqa: F821
"""Load annotations from a Raven annotation file,
created by exporting a Selection Table.
Parameters
----------
annot_path : str, pathlib.Path
Path to a txt file exported from Raven.
annot_col : str
Name of column that contains annotations.
audio_path : str, pathlib.Path
Path to audio file that the Raven txt file annotates.
Optional, defaults to None.
Examples
--------
>>> path = crowsetta.example('Recording1', return_path=True)
>>> raven = crowsetta.formats.bbox.Raven.from_file(path, annot_col="Species")
>>> print(raven)
Raven(df= Selection View Channel begin_time_s end_time_s low_freq_hz high_freq_hz annotation
0 1 Spectrogram 1 1 154.387793 154.911598 2878.2 4049.0 EATO
1 2 Spectrogram 1 1 167.526598 168.173020 2731.9 3902.7 EATO
2 3 Spectrogram 1 1 183.609637 184.097752 2878.2 3975.8 EATO
3 4 Spectrogram 1 1 250.527481 251.160711 2756.2 3951.4 EATO
4 5 Spectrogram 1 1 277.887243 278.480896 2707.5 3975.8 EATO
5 6 Spectrogram 1 1 295.529708 296.110168 2951.4 3975.8 EATO, annot_path=PosixPath('/Users/davidnicholson/Documents/repos/vocalpy/crowsetta/src/crowsetta/examples/Recording_1_Segment_02.Table.1.selections.txt'), annot_col='Species', audio_path=None) # noqa: E501
"""
annot_path = pathlib.Path(annot_path)
crowsetta.validation.validate_ext(annot_path, extension=cls.ext)
# assume file is space-separated with no header
df = pd.read_csv(annot_path, sep="\t")
if len(df) < 1:
raise ValueError(f"Cannot load annotations, " f"there are no rows in Raven txt file:\n{df}")
columns_map = dict(cls.COLUMNS_MAP) # copy
columns_map.update({annot_col: "annotation"})
df.rename(columns=columns_map, inplace=True)
df = RavenSchema.validate(df)
return cls(
df=df,
annot_path=annot_path,
annot_col=annot_col,
audio_path=audio_path,
)
[docs]
def to_bbox(self) -> List[crowsetta.BBox]:
"""Convert this Raven annotation to a
:class:`list` of :class:`crowsetta.Bbox` instances.
Returns
-------
bboxes : list
A :class:`list` of :class:`crowsetta.BBox` instances.
Examples
--------
>>> path = crowsetta.example('Recording1')
>>> raven = crowsetta.formats.bbox.Raven.from_file(path)
>>> bboxes = raven.to_bbox()
"""
bboxes = []
for begin_time, end_time, low_freq, high_freq, label in zip(
self.df.begin_time_s.values,
self.df.end_time_s.values,
self.df.low_freq_hz.values,
self.df.high_freq_hz.values,
self.df["annotation"].values,
):
bboxes.append(
crowsetta.BBox(onset=begin_time, offset=end_time, low_freq=low_freq, high_freq=high_freq, label=label)
)
return bboxes
[docs]
def to_annot(self) -> crowsetta.Annotation:
"""Convert this Raven annotation to a
:class:`crowsetta.Annotation`.
Returns
-------
annot : crowsetta.Annotation
Examples
--------
>>> path = crowsetta.example('Recording1')
>>> raven = crowsetta.formats.bbox.Raven.from_file(path)
>>> annot = raven.to_annot()
"""
bboxes = self.to_bbox()
return crowsetta.Annotation(annot_path=self.annot_path, notated_path=self.audio_path, bboxes=bboxes)
[docs]
def to_file(self, annot_path: PathLike) -> None:
"""Make a txt file that can be read by Raven
from this annotation
Parameters
----------
annot_path : str, pahtlib.Path
Path including filename where file should be saved.
Must have extension '.txt'
"""
crowsetta.validation.validate_ext(annot_path, extension=self.ext)
columns_map = {v: k for k, v in self.COLUMNS_MAP.items()} # copy
columns_map.update({"annotation": self.annot_col})
df_out = self.df.rename(columns=columns_map)
df_out.to_csv(annot_path, sep="\t", index=False)
