Skip to main content

A header generator and FITS file creator for DKIST data.

Project description

A header generator and FITS file creator for DKIST data

This package is designed to generate sets of FITS files which represent DKIST level 0 and level 1 data. These generated data should not be considered as a promise of what will be delivered when real data is obtained, these products are still a work in progress.

Using

Generating Pesudo Random Data

The simplest way to generate data is to use the dkist_data_simulator.spec122.Spec122Dataset or dkist_data_simulator.spec214.Spec214Dataset classes.

To generate a header:

>>> from dkist_data_simulator.spec122 import Spec122Dataset
>>> ds = Spec122Dataset(dataset_shape=(1, 512, 512), array_shape=(1, 512, 512), time_delta=10)
>>> ds.header()

A complete list of headers for all frames in the dataset can be generated with the generate_headers method.

It is also possible to iterate over a dataset, this changes the .index property.

This can be used to generate a sequence of headers one at a time:

>>> header_generator = (d.header() for d in ds)

It can also be used to generate files in memory:

>>> import io
>>> file_generator = (d.file(io.BytesIO()) for d in ds)

Customising the Generated Data

To customise the data being generated, subclass a dataset. To add new headers, either the add_constant_key method, or the add_generator_function methods can be used in the constructor. Also a shorthand way of having a function generate key values is to use the dkist_data_simulator.dataset.key_function decorator.

>>> from dkist_data_simulator.dataset import key_function
>>> from dkist_data_simulator.spec122 import Spec122Dataset
>>> class ExampleDataset(Spec122Dataset):
...     def __init__(self, *args, **kwargs):
...         super().__init__(*args, **kwargs)
...         # Add a header key with a given, fixed value over all headers
...         self.add_constant_key("INSTRUME", "Example")
...         # Add a header key with a given, single random value over all headers
...         self.add_constant_key("EXPER_ID")
...
...     @key_function("FRAMEVOL")
...     def framevol(self, key):
...         return 10

To remove a key from a generated header (for instance to generate invalid data), overload the header() method and remove keys before returning:

>>> class InvalidDataset(Spec122Dataset):
...     def header(self, *args, **kwargs):
...         header = super().header(*args, **kwargs)
...         header.pop("NAXIS")
...         return header

License

This project is Copyright (c) AURA / NSO and licensed under the terms of the BSD 3-Clause license. This package is based upon the Openastronomy packaging guide which is licensed under the BSD 3-clause licence. See the licenses folder for more information.

Contributing

We love contributions! dkist-data-simulator is open source, built on open source, and we’d love to have you hang out in our community.

Imposter syndrome disclaimer: We want your help. No, really.

There may be a little voice inside your head that is telling you that you’re not ready to be an open source contributor; that your skills aren’t nearly good enough to contribute. What could you possibly offer a project like this one?

We assure you - the little voice in your head is wrong. If you can write code at all, you can contribute code to open source. Contributing to open source projects is a fantastic way to advance one’s coding skills. Writing perfect code isn’t the measure of a good developer (that would disqualify all of us!); it’s trying to create something, making mistakes, and learning from those mistakes. That’s how we all improve, and we are happy to help others learn.

Being an open source contributor doesn’t just mean writing code, either. You can help out by writing documentation, tests, or even giving feedback about the project (and yes - that includes giving feedback about the contribution process). Some of these contributions may be the most valuable to the project as a whole, because you’re coming to the project with fresh eyes, so you can see the errors and assumptions that seasoned contributors have glossed over.

Note: This disclaimer was originally written by Adrienne Lowe for a PyCon talk, and was adapted by dkist-data-simulator based on its use in the README file for the MetPy project.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

dkist_data_simulator-5.2.1.tar.gz (45.7 kB view details)

Uploaded Source

Built Distribution

dkist_data_simulator-5.2.1-py3-none-any.whl (47.6 kB view details)

Uploaded Python 3

File details

Details for the file dkist_data_simulator-5.2.1.tar.gz.

File metadata

  • Download URL: dkist_data_simulator-5.2.1.tar.gz
  • Upload date:
  • Size: 45.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.10.14

File hashes

Hashes for dkist_data_simulator-5.2.1.tar.gz
Algorithm Hash digest
SHA256 9cdfa5a21b8dad1f7a092a6c9f0adabb77280ef04f2342a1eb83860a8f941d12
MD5 6848401cae66a8c8ab1038743c79a439
BLAKE2b-256 fc25946aa1c8b54ebf759fc7455e5221ed8afe7e214d6b821b8ba1ea89531cf0

See more details on using hashes here.

Provenance

File details

Details for the file dkist_data_simulator-5.2.1-py3-none-any.whl.

File metadata

File hashes

Hashes for dkist_data_simulator-5.2.1-py3-none-any.whl
Algorithm Hash digest
SHA256 4b72936a43ea17b2c3d7b9b7c29177fc7281c8c90b8a963685f69c8699bb04a8
MD5 e30fe3791e102c2ca0c42a9044c4f8fb
BLAKE2b-256 ce48f15ac23547709ea80538d87567eb2f0ba619341c6a06bc7a4ebb18b74491

See more details on using hashes here.

Provenance

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page