| Name | nxmx JSON |
| Version |
0.0.3
JSON |
| download |
| home_page | |
| Summary | Read HDF5 data conforming to the NXmx application definition of the NeXus format |
| upload_time | 2023-08-11 17:19:15 |
| maintainer | |
| docs_url | None |
| author | |
| requires_python | >=3.9 |
| license | BSD 3-Clause License |
| keywords |
nexus
nxmx
|
| VCS |
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| bugtrack_url |
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| requirements |
No requirements were recorded.
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| Travis-CI |
No Travis.
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| coveralls test coverage |
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# Read NXmx-flavour NeXus HDF5 data in Python
[](https://pypi.python.org/pypi/nxmx)
[](https://pypi.org/project/nxmx)
[]( https://github.com/ambv/black)
This package provides a neat and tidy Python interface for reading data from [HDF5 files](https://www.hdfgroup.org/solutions/hdf5/) that are structured according to the [NXmx application definition](https://manual.nexusformat.org/classes/applications/NXmx.html) of the [NeXus standard](https://www.nexusformat.org/).
## Installation
`python-nxmx` is available as `nxmx` on PyPI, so you just need Pip.
```Bash
$ pip install nxmx
```
## Getting started
If you have an HDF5 file in NXmx format, inspecting it with `h5ls` will look something like this:
```Bash
$ h5ls -r my-nxmx-file.h5
/ Group
/entry Group
/entry/data Group
/entry/definition Dataset {SCALAR}
/entry/end_time Dataset {SCALAR}
/entry/end_time_estimated Dataset {SCALAR}
/entry/instrument Group
/entry/instrument/beam Group
/entry/instrument/beam/incident_beam_size Dataset {2}
/entry/instrument/beam/incident_wavelength Dataset {SCALAR}
/entry/instrument/beam/total_flux Dataset {SCALAR}
/entry/instrument/detector Group
... etc. ...
```
With `nxmx`, you can access the NXmx data in Python like this:
```Python
import h5py
import nxmx
with h5py.File("my-nxmx-file.h5") as f:
nxmx_data = nxmx.NXmx(f)
```
## A slightly more detailed example
```Python
import h5py
import nxmx
with h5py.File("my-nxmx-file.h5") as f:
nxmx_data = nxmx.NXmx(f)
# Explore the NXmx data structure.
entry, *_ = nxmx_data.entries
print(entry.definition) # Prints "NXmx".
instrument, *_ = entry.instruments
detector, *_ = instrument.detectors
# Get the h5py object underlying an instance of a NX class.
entry_group = entry._handle # entry_group == f["entry"]
# Find instances of a given NX class in a h5py.Group.
beams = nxmx.find_class(instrument._handle, "NXbeam")
# The equivalent for more than one NX class.
beams, detectors = nxmx.find_classes(instrument._handle, "NXbeam", "NXdetector")
# Query attributes of an object in the normal h5py way.
# Suppose out detector has a transformation called "det_z".
transformations, *_ = nxmx.find_class(detector._handle, "NXtransformations")
attrs = transformations["det_z"].attrs # Get the attributes of the "det_z" dataset.
```
Raw data
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"description": "# Read NXmx-flavour NeXus HDF5 data in Python\n\n[](https://pypi.python.org/pypi/nxmx)\n[](https://pypi.org/project/nxmx)\n[]( https://github.com/ambv/black)\n\nThis package provides a neat and tidy Python interface for reading data from [HDF5 files](https://www.hdfgroup.org/solutions/hdf5/) that are structured according to the [NXmx application definition](https://manual.nexusformat.org/classes/applications/NXmx.html) of the [NeXus standard](https://www.nexusformat.org/).\n\n## Installation\n`python-nxmx` is available as `nxmx` on PyPI, so you just need Pip.\n```Bash\n$ pip install nxmx\n```\n\n## Getting started\n\nIf you have an HDF5 file in NXmx format, inspecting it with `h5ls` will look something like this:\n```Bash\n$ h5ls -r my-nxmx-file.h5 \n/ Group\n/entry Group\n/entry/data Group\n/entry/definition Dataset {SCALAR}\n/entry/end_time Dataset {SCALAR}\n/entry/end_time_estimated Dataset {SCALAR}\n/entry/instrument Group\n/entry/instrument/beam Group\n/entry/instrument/beam/incident_beam_size Dataset {2}\n/entry/instrument/beam/incident_wavelength Dataset {SCALAR}\n/entry/instrument/beam/total_flux Dataset {SCALAR}\n/entry/instrument/detector Group\n\n... etc. ...\n```\nWith `nxmx`, you can access the NXmx data in Python like this:\n```Python\nimport h5py\nimport nxmx\n\nwith h5py.File(\"my-nxmx-file.h5\") as f:\n nxmx_data = nxmx.NXmx(f)\n```\n\n## A slightly more detailed example\n```Python\nimport h5py\nimport nxmx\n\nwith h5py.File(\"my-nxmx-file.h5\") as f:\n nxmx_data = nxmx.NXmx(f)\n # Explore the NXmx data structure.\n entry, *_ = nxmx_data.entries\n print(entry.definition) # Prints \"NXmx\".\n instrument, *_ = entry.instruments\n detector, *_ = instrument.detectors\n \n # Get the h5py object underlying an instance of a NX class.\n entry_group = entry._handle # entry_group == f[\"entry\"]\n\n # Find instances of a given NX class in a h5py.Group.\n beams = nxmx.find_class(instrument._handle, \"NXbeam\")\n # The equivalent for more than one NX class.\n beams, detectors = nxmx.find_classes(instrument._handle, \"NXbeam\", \"NXdetector\")\n\n # Query attributes of an object in the normal h5py way.\n # Suppose out detector has a transformation called \"det_z\".\n transformations, *_ = nxmx.find_class(detector._handle, \"NXtransformations\")\n attrs = transformations[\"det_z\"].attrs # Get the attributes of the \"det_z\" dataset.\n```\n",
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