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arfx-2.6.9
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Advanced Recording Format Tools
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | arfx-2.6.9 |
| نام | arfx |
| نسخه کتابخانه | 2.6.9 |
| نگهدارنده | ['Dan Meliza'] |
| ایمیل نگهدارنده | ['dan@meliza.org'] |
| نویسنده | Dan Meliza |
| ایمیل نویسنده | dan@meliza.org |
| آدرس صفحه اصلی | https://github.com/melizalab/arfx |
| آدرس اینترنتی | https://pypi.org/project/arfx/ |
| مجوز | BSD 3-Clause License |
## arfx
**arfx** is a family of commandline tools for copying sampled data in and out of ARF
containers. ARF (<https://github.com/melizalab/arf>)
is an open, portable file format for storing behavioral and neural data, based
on [HDF5](http://www.hdfgroup.org/HDF5).
### requirements
- Python 3.6 or greater
- numpy>=1.19
- arf>=2.6 (<https://github.com/melizalab/arf>)
- ewave>=1.0.5 (<https://github.com/melizalab/py-ewave>)
### installation
```bash
pip install arfx
```
or from source:
```bash
python setup.py install
```
### usage
The general syntax is `arfx operation [options] files`. The syntax is similar to `tar`. Operations are as
follows:
- **-A:** copy data from one container to another
- **-c:** create a new container
- **-r:** append data to the container
- **-t:** list contents of the container
- **-x:** extract entries from the container
- **-d:** delete entries from the container
Options specify the target ARF file, verbosity, automatic naming schemes, and
any metadata to be stored in the entry.
- **-f FILE:** use ARF file FILE
- **-v:** verbose output
- **-n NAME:** name entries sequentially, using NAME as the base
- **-a ANIMAL:** specify the animal
- **-e EXPERIMENTER:** specify the experimenter
- **-p PROTOCOL:** specify the protocol
- **-s HZ:** specify the sampling rate of the data, in Hz
- **-T DATATYPE:** specify the type of data
- **-u:** do not compress data in the arf file
- **-P:** when deleting entries, do not repack
###### input files
**arfx** can read sampled data from `pcm`, `wave`, `npy` and `mda` files. Support
for additional file formats can be added as plugins (see 4).
When adding data to an ARF container (`-c` and `-r` modes), the input files are
specified on the command line, and added in the order given. By default, entries
are given the same name as the input file, minus the extension; however, if the
input file has more than one entry, they are given an additional numerical
extension. To override this, the `-n` flag can be used to specify the base name;
all entries are given sequential names based on this.
The `-n, -a, -e, -p, -s, -T` options are used to store information about the
data being added to the file. The DATATYPE argument can be the numerical code or
enumeration code (run `arfx --help-datatypes` for a list), and indicates the
type of data in the entries. All of the entries created in a single run of arfx
are given these values. The `-u` option tells arfx not to compress the data,
which can speed up I/O operations slightly.
Currently only one sampled dataset per entry is supported. Clearly this does not
encompass many use cases, but **arfx** is intended as a simple tool. More
specialized import procedures can be easily written in Python using the `arf`
library.
###### output files
The entries to be extracted (in `-x` mode) can be specified by name. If no names
are specified, all the entries are extracted. All sampled datasets in each entry
are extracted as separate channels, because they may have different sampling
rates. Event datasets are not extracted.
By default the output files will be in `wave` format and will have names with
the format `entry_channel.wav`. The `-n` argument can be used to customize the
names and file format of the output files. The argument must be a template in
the format defined by the [python string module](http://docs.python.org/library/string.html###format-specification-mini-language). Supported field names include
`entry`, `channel`, and `index`, as well as the names of any HDF5 attributes
stored on the entry or channel. The extension of the output template is used
to determine the file format. Currently only `wave` is supported, but
additional formats may be supplied as plugins (see 4).
The metadata options are ignored when extracting files; any metadata present in
the ARF container that is also supported by the target container is copied.
###### other operations
As with `tar`, the `-t` operation will list the contents of the
archive. Each entry/channel is listed on a separate line in path notation.
The `-A` flag is used to copy the contents of one ARF file to another. The
entries are copied without modification from the source ARF file(s) to the
target container.
The `-d` (delete) operation uses the same syntax as the extract operation, but
instead of extracting the entries, they are deleted. Because of limitations in
the underlying HDF5 library, this does not free up the space, so the file is
repacked unless the `-P` option is set.
The `-U` (update) operation can be used to add or update attributes of entries,
and to rename entries (if the `-n` flag is set).
The `--write-attr` operation can be used to store the contents of text files in top-level attributes. The attributes have the name `user_<filename>`. The `--read-attr` operation can be used to read out those attributes. This is useful when data collection programs generate log or settings files that you want to store in the ARF file.
### other utilities
This package comes with a few additional scripts that do fairly specific operations.
#### arfx-split
This script is used to reorganize very large recordings, possibly contained in multiple files, into manageable chunks. Each new entry is given an updated timestamp and attributes from the source entries. Currently, no effort is made to splice data across entries or files. This may result in some short
entries. Only sampled datasets are processed.
#### arfx-collect-sampled
This script is used to export data into a flat binary structure. It collects sampled data across channels and entries into a single 2-D array. The output can be stored in a multichannel wav file or in a raw binary `dat` format (N samples by M channels), which is used by a wide variety of spike-sorting tools.
### extending arfx
Additional formats for reading and writing can be added using the Python
setuptools plugin system. Plugins must be registered in the `arfx.io` entry
point group, with a name corresponding to the extension of the file format
handled by the plugin.
An arfx IO plugin is a class with the following required methods:
`__init__(path, mode, **attributes)`: Opens the file at `path`. The `mode`
argument specifies whether the file is opened for reading (`r`), writing (`w`),
or appending (`a`). Must throw an `IOError` if the file does not exist or cannot
be created, and a `ValueError` if the specified value for `mode` is not
supported. The additional `attributes` arguments specify metadata to be stored
in the file when created. **arfx** will pass all attributes of the channel and
entry (e.g., `channels`, `sampling_rate`, `units`, and `datatype`) when opening a file for writing. This method may issue a `ValueError` if the
caller fails to set a required attribute, or attempts to set an attribute
inconsistent with the data format. Unsupported attributes should be ignored.
`read()`: Reads the contents of the opened file and returns the data in a format suitable
for storage in an ARF file. Specifically, it must be an acceptable type for the
`arf.entry.add_data()` method (see <https://github.com/melizalab/arf> for
documentation).
`write(data)`: Writes data to the file. Must issue an `IOError` if the file is opened in the
wrong mode, and `TypeError` if the data format is not correct for the file
format.
`timestamp`: A readable property giving the time point of the data. The value may be a scalar
indicating the number of seconds since the epoch, or a two-element sequence
giving the number of seconds and microseconds since the epoch. If this property
is writable it will be set by **arfx** when writing data.
`sampling_rate`: A property indicating the sampling rate of the data in the file (or current
entry), in units of Hz.
The class may also define the following methods and properties. If any property
is not defined, it is assumed to have the default value defined below.
`nentries`: A readable property indicating the number of entries in the file. Default value
is 1.
`entry`: A readable and writable integer-valued property corresponding to the
index of the currently active entry in the file. Active means that the `read()`
and `write()` methods will affect only that entry. Default is 0, and **arfx**
will not attempt to change the property if `nentries` is 1.
### version information
**arfx** uses semantic versioning and is synchronized with the major/minor version
numbers of the arf package specification.
نیازمندی
| مقدار | نام |
|---|---|
| >=2.6 | arf |
| >=1.0.5 | ewave |
| - | tqdm |
| - | natsort |
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.6 | Python |
نحوه نصب
نصب پکیج whl arfx-2.6.9:
pip install arfx-2.6.9.whl
نصب پکیج tar.gz arfx-2.6.9:
pip install arfx-2.6.9.tar.gz