Setigen

Latest version: v2.7.0

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1.2.0

New functionality + improved API. Note that these changes may break code written for earlier version of setigen.

New:
* Save and load entire frames using pickle
* View frames with `frame.render()` and `frame.bl_render()` for blimpy visualization
* Support integrating `f_profile` for more accurate calculations w.r.t frequency
* Support custom metadata as part of Frame objects
* Calculate accurate frequency ranges from slices of filterbank files
* Add `frame.get_waterfall()` to directly access blimpy Waterfall object corresponding to frame
* In `stg.split_utils`, allow truncating data by desired number of time samples when creating waterfall generator

Summary of API changes:

* `stg.Frame(fil)` -> `stg.Frame(waterfall)`
* `frame.compute_intensity()` -> `frame.get_intensity()`
* `frame.compute_SNR()` -> `frame.get_snr()`
* `db` -> `use_db` in `frame.get_data()` function arguments
* `frame.freq_to_index()` -> `frame.get_index()`. Add `frame.get_frequency()` function.
* `frame.save_data()` and `frame.load_data()` -> `frame.save_npy()` and `frame.load_npy()`
* In `frame.add_signal`:
* `integrate_time` -> `integrate_t_profile`
* `mean_f_position` -> `integrate_path`
* `time_subsamples` -> `t_subsamples`
* `stg.fil_utils` -> `stg.waterfall_utils`
* `stg.split_utils.split_fil_generator()` -> `stg.split_utils.split_waterfall_generator()`

1.1.1

Update requirements and installation documentation.

1.1.0

* Use sigma clipping for better noise estimation
* Support usage of arrays / floats for path, t_profile, and bp_profile in Frame.add_signal
* Optimize signal injection by removing expensive / superfluous calculations
* Added a lot more documentation, covering all substantial functions
* Update Sphinx docs to point to docstrings: https://setigen.readthedocs.io/en/master/setigen.html

1.0.1

1.0.0

Focus signal generation around the Frame object, with the following updates:
* Load and save data from arrays or fil/h5 files
* Add Gaussian noise throughout the frame, either by user-provided distribution parameter or by sampling from pre-loaded parameters drawn from real GBT observations
* Add custom signals, from a simple, constant-intensity line to complex, modulated signals through a combination of built-in or user-defined callbacks
* Integration with astropy units, so that frame parameters and synthetic signals have physical meaning.
* And more instance methods that simplify calculating basic statistics, SNR to intensity, etc

0.0.1

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