Metadata-Version: 2.3
Name: find_delay
Version: 2.9
Summary: Calculate the delay between two arrays
Project-URL: Homepage, https://github.com/RomainPastureau/find_delay
Project-URL: Bug Tracker, https://github.com/RomainPastureau/find_delay/issues
Project-URL: Documentation, https://find-delay.readthedocs.io/en/latest/
Project-URL: PyPI, https://pypi.org/project/find-delay/
Author-email: Romain Pastureau <r.pastureau@bcbl.eu>
License-File: LICENSE
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.7
Requires-Dist: matplotlib>=3.7
Requires-Dist: numpy>=1.25.0
Requires-Dist: scipy>=1.11.0
Description-Content-Type: text/markdown

# find_delay 2.9
[![Documentation Status](https://readthedocs.org/projects/find-delay/badge/?version=latest)](https://find-delay.readthedocs.io/en/latest/?badge=latest)

[PyPI page](https://pypi.org/project/find-delay/)

Author: Romain Pastureau

## What is find_delay?
**find_delay** is a **Python package** that tries to find the delay where a time series appears in another via 
cross-correlation. It can theoretically work with any time series (see the examples in the 
[demos folder](https://github.com/RomainPastureau/find_delay/tree/main/demos), but was created to try to align 
audio files.
**[Read the documentation here!](https://find-delay.readthedocs.io/en/latest/)**

## How to
The best way to use this function is to install the find_delay module for Python by running 
`py -m pip install find-delay`.

You can then import the function by writing `from find_delay import find_delay` (or `from find_delay import find_delays`
if you want to locate multiple excerpts in one big time series).

You can also run demos/demo.py to get four examples (in that case, you will need to download the .wav files present in 
the repository and place them in the same folder for examples 3 and 4).

## Quick use for audio files
To find when an excerpt starts in an audio file, use the `find_delay` function and fill only the first four parameters;
leave the other parameters default (just set `plot_figure = True` if you want to visualize the output of the function).

## Specifics
The function accepts two arrays containing time series - the time series can be of different frequency or amplitude.

The function can then calculate the envelope of the time series (recommended for audio files) and apply a band-pass 
filter to the result.

The function can also resample the arrays (necessary when the two time series do not have the same frequency).

Finally, the function performs the cross-correlation between the two arrays.

The results can be then plotted if the corresponding parameters are activated, and the function returns the delay at 
which to find the second array in the first by selecting the delay with the maximum correlation value (optionally, the 
function can also return this correlation value).

## Dependencies
* **Matplotlib** for the plots
* **Numpy** for handling the numerical arrays
* **Scipy** for loading the WAV files, performing the resampling, calculating the envelope, and applying a band-pass 
  filter.

## Examples
### Delay between two numerical time series
```    
array_1 = [24, 70, 28, 59, 13, 97, 63, 30, 89, 4, 8, 15, 16, 23, 42, 37, 70, 18, 59, 48, 41, 83, 99, 6, 24, 86]
array_2 = [4, 8, 15, 16, 23, 42]

find_delay(array_1, array_2, compute_envelope=False, plot_figure=True, path_figure="figure_1.png")
```

![Delay between two numerical time series](https://raw.githubusercontent.com/RomainPastureau/find_delay/package/demos/figure_1.png)

### Delay between a sine function and a portion of it, different frequencies
```
timestamps_1 = np.linspace(0, np.pi * 2, 200001)
array_1 = np.sin(timestamps_1)
timestamps_2 = np.linspace(np.pi * 0.5, np.pi * 0.75, 6001)
array_2 = np.sin(timestamps_2)

find_delay(array_1, array_2, 100000 / np.pi, 6000 / (np.pi / 4),
           compute_envelope=False, resampling_rate=1000, window_size_res=20000, overlap_ratio_res=0.5,
           resampling_mode="cubic", plot_figure=True, path_figure="figure_2.png", plot_intermediate_steps=True,
           verbosity=1)
```

![Delay between a sine function and a portion of it, different frequencies](https://raw.githubusercontent.com/RomainPastureau/find_delay/package/demos/figure_2.png)

### Delay between an audio file and an excerpt from it
```
audio_path = "i_have_a_dream_full.wav"
audio_wav = wavfile.read(audio_path)
audio_frequency = audio_wav[0]
audio_array = audio_wav[1][:, 0]  # Turn to mono

excerpt_path = "i_have_a_dream_excerpt.wav"
excerpt_wav = wavfile.read(excerpt_path)
excerpt_frequency = excerpt_wav[0]
excerpt_array = excerpt_wav[1][:, 0]  # Turn to mono

find_delay(audio_array, excerpt_array, audio_frequency, excerpt_frequency,
           compute_envelope=True, window_size_env=1e6, overlap_ratio_env=0.5,
           resampling_rate=1000, window_size_res=1e7, overlap_ratio_res=0.5, return_delay_format="timedelta",
           resampling_mode="cubic", plot_figure=True, path_figure="figure_3.png", plot_intermediate_steps=True,
           verbosity=1)
```

![Delay between an audio file and an excerpt from it](https://raw.githubusercontent.com/RomainPastureau/find_delay/package/demos/figure_3.png)

### Latest version
**2.9 (2024-09-05)**
* Added the possibility to pass paths to WAV files as parameters of `find_delay` and `find_delays`
* Added the parameter mono_channel describing the method for converting multiple-channel audio to mono
* Added the function _convert_to_mono to perform the conversion to mono
* Corrected the display of negative delays when they are in timedelta format. A delay of -1 second
  will now print `-0:00:01` instead of `-1 day, 23:59:59`.
* Corrected a bug preventing the figure to display when the excerpt is found at the edges of the first
  array
* Closed the figure at the end of _create_figure to prevent warnings
* Added an FAQ page in the documentation
* Corrected typos and type errors in the documentation

[See version history](https://find-delay.readthedocs.io/en/latest/version_history.html)

If you detect any bug, please [open an issue](https://github.com/RomainPastureau/find_delay/issues/new).

Thanks! 🦆

