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.