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Update code
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@hagenw
hagenw committed Jul 8, 2024
1 parent 6dcd0a7 commit a89f368
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Showing 3 changed files with 153 additions and 41 deletions.
189 changes: 150 additions & 39 deletions audinterface/core/process.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -255,6 +255,7 @@ def _process_file(
Args:
file: file path
idx: index value
root: optional root path of file
start: start time to read media file
end: end time to read media file
Expand All @@ -274,7 +275,7 @@ def _process_file(
# Text files
if ext in ["json", "txt"]:
data = utils.read_text(file, root=root)
y = self._call_data(
y, file = self._process_data(
data,
idx=idx,
root=root,
Expand Down Expand Up @@ -339,6 +340,11 @@ def process_file(
) -> pd.Series:
r"""Process the content of an audio file.
The results of processed audio/video files
are returned with a segmented index,
all other processed files
with a filewise index.
Args:
file: file path
start: start processing at this position.
Expand Down Expand Up @@ -380,7 +386,10 @@ def process_file(
end=end,
process_func_args=process_func_args,
)
index = audformat.segmented_index(files, starts, ends)
if starts is None and ends is None:
index = audformat.filewise_index(files)
else:
index = audformat.segmented_index(files, starts, ends)

if len(y) == 0:
return pd.Series([], index, dtype=object)
Expand All @@ -398,6 +407,12 @@ def process_files(
) -> pd.Series:
r"""Process a list of files.
The index of the returned series
is a segmented index,
if any of the processed files
are audio/video files.
Otherwise it is a filewise index.
Args:
files: list of file paths
starts: segment start positions.
Expand Down Expand Up @@ -479,7 +494,15 @@ def process_files(
starts = list(itertools.chain.from_iterable([x[2] for x in xs]))
ends = list(itertools.chain.from_iterable([x[3] for x in xs]))

index = audformat.segmented_index(files, starts, ends)
if (
len(audeer.unique(starts)) == 1
and audeer.unique(starts)[0] is None
and len(audeer.unique(ends)) == 1
and audeer.unique(ends)[0] is None
):
index = audformat.filewise_index(files)
else:
index = audformat.segmented_index(files, starts, ends)
y = pd.Series(y, index)

return y
Expand All @@ -494,6 +517,12 @@ def process_folder(
) -> pd.Series:
r"""Process files in a folder.
The index of the returned series
is a segmented index,
if any of the processed files
are audio/video files.
Otherwise it is a filewise index.
.. note:: At the moment does not scan in sub-folders!
Args:
Expand Down Expand Up @@ -577,7 +606,16 @@ def _process_index_wo_segment(
starts = list(itertools.chain.from_iterable([x[2] for x in xs]))
ends = list(itertools.chain.from_iterable([x[3] for x in xs]))

index = audformat.segmented_index(files, starts, ends)
if (
len(audeer.unique(starts)) == 1
and audeer.unique(starts)[0] is None
and len(audeer.unique(ends)) == 1
and audeer.unique(ends)[0] is None
):
index = audformat.filewise_index(files)
else:
index = audformat.segmented_index(files, starts, ends)

y = pd.Series(y, index)

return y
Expand Down Expand Up @@ -607,8 +645,10 @@ def process_index(
and :attr:`audinterface.Process.segment` is ``None``
the returned index
will be of same type
as the original one,
otherwise always a segmented index is returned
as the original one.
Otherwise it will be a segmented index
if any audio/video files are processed,
or a filewise index otherwise
root: root folder to expand relative file paths
cache_root: cache folder (see description)
process_func_args: (keyword) arguments passed on
Expand Down Expand Up @@ -678,6 +718,7 @@ def _process_signal(
typing.List[pd.Timedelta],
typing.List[pd.Timedelta],
]:
r"""Process signal and handle special processing function arguments."""
signal = np.atleast_2d(signal)

# Find start and end index
Expand Down Expand Up @@ -742,6 +783,64 @@ def _process_signal(

return y, [file] * len(starts), starts, ends

def _process_data(
self,
data: typing.Any,
*,
idx: int = 0,
root: str = None,
file: str = None,
process_func_args: typing.Dict[str, typing.Any] = None,
) -> typing.Tuple[typing.Any, str]:
r"""Process signal and handle special processing function arguments."""
y = self._call_data(
data,
idx=idx,
root=root,
file=file,
process_func_args=process_func_args,
)
return y, file

def process_data(
self,
data: typing.Any,
file: str = None,
process_func_args: typing.Dict[str, typing.Any] = None,
) -> pd.Series:
r"""Process audio signal and return result.
If file is given,
the returned series contains a filewise index.
Otherwise, an integer index is returned.
Args:
data: data to process
file: file path
process_func_args: (keyword) arguments passed on
to the processing function.
They will temporarily overwrite
the ones stored in
:attr:`audinterface.Process.process_func_args`
Returns:
Series with processed data
"""
y, file = self._process_data(
data,
file=file,
process_func_args=process_func_args,
)
if file is not None:
index = audformat.filewise_index([file])
else:
index = pd.Index([0], dtype="int")
if len(y) == 0:
return pd.Series([], index, dtype=object)
else:
return pd.Series([y], index)

def process_signal(
self,
signal: np.ndarray,
Expand Down Expand Up @@ -799,31 +898,24 @@ def process_signal(
process_func_args=process_func_args,
)
else:
# Text files
if sampling_rate is None:
pass
# Implement

# Audio/video files
else:
if start is not None:
start = utils.to_timedelta(start, sampling_rate)
if end is not None:
end = utils.to_timedelta(end, sampling_rate)
if start is not None:
start = utils.to_timedelta(start, sampling_rate)
if end is not None:
end = utils.to_timedelta(end, sampling_rate)

y, files, starts, ends = self._process_signal(
signal,
sampling_rate,
file=file,
start=start,
end=end,
process_func_args=process_func_args,
)
y, files, starts, ends = self._process_signal(
signal,
sampling_rate,
file=file,
start=start,
end=end,
process_func_args=process_func_args,
)

if file is not None:
index = audformat.segmented_index(files, starts, ends)
else:
index = utils.signal_index(starts, ends)
if file is not None:
index = audformat.segmented_index(files, starts, ends)
else:
index = utils.signal_index(starts, ends)

if len(y) == 0:
return pd.Series([], index, dtype=object)
Expand Down Expand Up @@ -1034,7 +1126,24 @@ def _call_data(
file: str = None,
process_func_args: typing.Dict[str, typing.Any] = None,
) -> typing.Any:
r"""Call processing function on general data."""
r"""Call processing function on general data.
It does not make any assumptions about ``data``.
Special arguments are extracted,
and passed to the processing function.
Args:
data: data object passed to processing function
idx: index
root: root path
file: file path
process_func_args: processing function arguments
Returns:
result of processing function
"""
process_func_args = process_func_args or self.process_func_args
special_args = self._special_args(idx, root, file, process_func_args)
y = self.process_func(data, **special_args, **process_func_args)
Expand Down Expand Up @@ -1072,33 +1181,35 @@ def _special_args(

def __call__(
self,
signal: np.ndarray,
data: typing.Any,
sampling_rate: int = None,
) -> typing.Any:
r"""Apply processing to signal.
r"""Apply processing to data/signal.
This function processes the signal
This function processes the data/signal
**without** transforming the output into a :class:`pd.Series`.
Instead, it will return the raw processed signal.
Instead, it will return the raw processed data/signal.
However,
if channel selection, mixdown and/or resampling is enabled,
and ``sampling_rate`` is not ``None``,
the signal will be first remixed and resampled
if the input sampling rate does not fit the expected sampling rate.
Args:
signal: signal values
sampling_rate: sampling rate in Hz
data: data or signal
sampling_rate: sampling rate in Hz.
If not ``None``,
``data`` is expected to be a :class:`numpy.ndarray`
Returns:
Processed signal
Processed data/signal
Raises:
RuntimeError: if sampling rates do not match
RuntimeError: if channel selection is invalid
"""
if sampling_rate is not None:
return self._call(signal, sampling_rate)
return self._call(data, sampling_rate)
else:
return self._call_data(signal)
return self._call_data(data)
3 changes: 2 additions & 1 deletion audinterface/core/utils.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -6,6 +6,7 @@
import numpy as np
import pandas as pd

import audeer
import audformat
import audiofile
import audmath
Expand Down Expand Up @@ -172,7 +173,7 @@ def read_text(
ext = audeer.file_extension(file).lower()
if ext == "json":
with open(file) as json_file:
data = json.load(f)
data = json.load(json_file)
elif ext == "txt":
with open(file) as txt_file:
data = txt_file.read()
Expand Down
2 changes: 1 addition & 1 deletion pyproject.toml
View file
Original file line number Diff line number Diff line change
Expand Up @@ -31,7 +31,7 @@ classifiers = [
]
requires-python = '>=3.9'
dependencies = [
'audeer >=1.18.0',
'audeer >=2.1.0',
'audformat >=1.0.1,<2.0.0',
'audiofile >=1.3.0',
'audmath >=1.4.1',
Expand Down

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