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remove webapp & polish readme
* `webapp/` hasn't been updated in 6 years we previously discussed removing at last grcon (2023-09) * Fixed small issues in `README.md` * Incremented abi to `v1.1.5` so we can create a release
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README.md

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<p align="center">
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<img src="https://github.com/gnuradio/SigMF/blob/sigmf-v1.x/logo/sigmf_logo.png" width="30%" />
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</p>
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<p align="center"><img src="https://github.com/gnuradio/SigMF/blob/sigmf-v1.x/logo/sigmf_logo.png" width="30%" /></p>
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This repository contains a python module for interacting with SigMF Objects.
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This module works with Python 3.6 and higher. This module is distributed freely
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This python module makes it easy to interact with Signal Metadata Format
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(SigMF) objects. This module works with Python 3.6+ and is distributed freely
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under the terms GNU Lesser GPL v3 License.
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# Signal Metadata Format (SigMF)
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The [SigMF specification document](https://github.com/sigmf/SigMF/blob/HEAD/sigmf-spec.md), `sigmf-spec.md` is located in the
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https://github.com/gnuradio/SigMF repository.
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The [SigMF specification document](https://github.com/sigmf/SigMF/blob/HEAD/sigmf-spec.md)
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is located in the [SigMF](https://github.com/gnuradio/SigMF) repository.
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# Installation
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To install the latest released version of the SigMF package, install it from pip:
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To install the latest release, install from pip:
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```bash
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pip install sigmf
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```
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To install the latest development version, build the package from source:
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To install the latest development version, build from source:
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```bash
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git clone https://github.com/sigmf/sigmf-python.git
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To run the included QA tests:
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```bash
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cd test/
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python3 -m pytest
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# basic
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python3 -m pytest tests/
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# fancy
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coverage run --a --source sigmf -m pytest --doctest-modules
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```
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# Examples
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Since an *archive* is merely a tarball (uncompressed), and since there any many
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excellent tools for manipulating tar files, it's fairly straightforward to
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access the *data* part of a SigMF archive without untaring it.
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This is a compelling feature because 1) archives make it harder for the `-data`
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and the `-meta` to get separated, and 2) some datasets are so large that it can
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access the *data* part of a SigMF archive without un-taring it. This is a
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compelling feature because __1__ archives make it harder for the `-data` and
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the `-meta` to get separated, and __2__ some datasets are so large that it can
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be impractical (due to available disk space, or slow network speeds if the
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archive file resides on a network file share) or simply obnoxious to untar it
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first.
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```python
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In [1]: import sigmf
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In [2]: arc = sigmf.SigMFArchiveReader('/src/LTE.sigmf')
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In [3]: arc.shape
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Out[3]: (15379532,)
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In [4]: arc.ndim
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Out[4]: 1
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In [5]: arc[:10]
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Out[5]:
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>>> import sigmf
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>>> arc = sigmf.SigMFArchiveReader('/src/LTE.sigmf')
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>>> arc.shape
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(15379532,)
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>>> arc.ndim
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1
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>>> arc[:10]
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array([-20.+11.j, -21. -6.j, -17.-20.j, -13.-52.j, 0.-75.j, 22.-58.j,
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48.-44.j, 49.-60.j, 31.-56.j, 23.-47.j], dtype=complex64)
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```
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The preceeding example exhibits another feature of this approach; the archive
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`LTE.sigmf` is actually `complex-int16`'s on disk, for which there is no
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corresponding type in `numpy`.
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However, the `.sigmffile` member keeps track of this, and converts the data
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to `numpy.complex64` *after* slicing it, that is, after reading it from disk.
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corresponding type in `numpy`. However, the `.sigmffile` member keeps track of
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this, and converts the data to `numpy.complex64` *after* slicing it, that is,
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after reading it from disk.
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```python
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In [6]: arc.sigmffile.get_global_field(sigmf.SigMFFile.DATATYPE_KEY)
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Out[6]: 'ci16_le'
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>>> arc.sigmffile.get_global_field(sigmf.SigMFFile.DATATYPE_KEY)
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'ci16_le'
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In [7]: arc.sigmffile._memmap.dtype
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Out[7]: dtype('int16')
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>>> arc.sigmffile._memmap.dtype
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dtype('int16')
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In [8]: arc.sigmffile._return_type
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Out[8]: '<c8'
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>>> arc.sigmffile._return_type
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'<c8'
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```
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Another supported mode is the case where you might have an archive that *is not
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read it, this can be done "in mid air" or "without touching the ground (disk)".
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```python
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In [1]: import sigmf, io
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In [2]: sigmf_bytes = io.BytesIO(open('/src/LTE.sigmf', 'rb').read())
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In [3]: arc = sigmf.SigMFArchiveReader(archive_buffer=sigmf_bytes)
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In [4]: arc[:10]
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Out[4]:
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>>> import sigmf, io
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>>> sigmf_bytes = io.BytesIO(open('/src/LTE.sigmf', 'rb').read())
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>>> arc = sigmf.SigMFArchiveReader(archive_buffer=sigmf_bytes)
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>>> arc[:10]
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array([-20.+11.j, -21. -6.j, -17.-20.j, -13.-52.j, 0.-75.j, 22.-58.j,
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48.-44.j, 49.-60.j, 31.-56.j, 23.-47.j], dtype=complex64)
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```
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### Is this a GNU Radio effort?
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*No*, this is not a GNU Radio-specific effort. It is hosted under the GNU Radio
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Github account because this effort first emerged from a group of GNU Radio core
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*No*, this is not a GNU Radio-specific effort.
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This effort first emerged from a group of GNU Radio core
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developers, but the goal of the project to provide a standard that will be
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useful to anyone and everyone, regardless of tool or workflow.
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sigmf/__init__.py

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#
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# SPDX-License-Identifier: LGPL-3.0-or-later
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__version__ = "1.1.4"
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__version__ = "1.1.5"
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from .archive import SigMFArchive
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from .sigmffile import SigMFFile, SigMFCollection

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