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Merge pull request #30 from SKA-ScienceDataProcessor/feature-SIM-407
Stable docker release
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**May 1, 2019** [Tim] New workflow to map a function across an image: image_rsexecute_map_workflow | ||
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**April 28, 2019** [Tim] Fill in all __init__.py files so that tab completion works. | ||
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**April 16, 2019** [Tim] Added examples/comparisons directory hold code for comparing ARL results with those from | ||
other packages. | ||
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**April 04, 2019** [Tim] Pointing simulation capabilities put in place. New data model PointingTable similar to | ||
GainTable. testing_support now has a function to simulate pointing errors. See workflows/scripts/SKA_SIM for examples. | ||
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**March 25, 2019** [Tim] Performance measurement capabilites and improvements. See workflows/scripts/performance for | ||
tests. | ||
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**January 26, 2019** [Feng] Added create_blockvisibility_from_uvfits. | ||
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**January 23, 2019** [Tim] Work on MPC. Documented in SDP memo 97. | ||
Branch feature_mpc merged into master. The old modelpartition code has | ||
been removed. | ||
1. SkyModel now has image, mask, and gaintable. | ||
2. Gaintable now has phasecentre, as needed for non-isoplanatic | ||
processing. | ||
3. Improved speed of scalar calibration. | ||
4. Improved HDF5 for SkyModel. Old ones not compatible. | ||
5. Functions for working with skycomponents e.g. filtering, | ||
neighbour filtering. | ||
6. Voronoi partitioning. | ||
7. Predict and invert workflows for skymodel. | ||
8. Ensure imaging_weights retained in BlockVisibility. | ||
9. Ionospheric phase screen simulation using | ||
ARatmospy: create_gaintable_from_screen. Gaintable phases can be | ||
back-propagated to screen: grid_gaintable_to_screen. | ||
10. Pipeline for MPCCAL: mpccal_skymodel_list_rsexecute_workflow. | ||
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**November 26, 2018** [Tim] Many changes in run up to demo: | ||
1. Parallel weighting, imaging weight added to BlockVisibility | ||
2. GLEAM lookup optimised, can now generate a skymodel and predict from it. | ||
3. Added skycomponent filtering | ||
4. Default visibility format is Visibility not BlockVisibility. This means fewer conversions. | ||
5. arl_demo notebook in place | ||
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**September 25, 2018** [Tim] Gridding/degridding code has been refactored to a cleaner design. It also allows more | ||
control of AW projection. | ||
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**September 18, 2018** [Rodrigo] Fix for daliuge port execution of list, to match dask.delayed capabilities. Need to | ||
update version of daliuge: | ||
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pip install "daliuge>=0.5.3" pytest | ||
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**September 16, 2018** [Tim] Deleted imaging-pipelines-sip.ipynb. Use imaging-pipelines-serial.ipynb instead. | ||
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**September 4, 2018** [Rodrigo] Added add support for daliuge as an (experimental) backend of the rsexecute module. | ||
Support uses daliuge's delayed function, which accepts the same parameters as dask's; therefore the change is simple, | ||
and transparent to the rest of the ARL code. All these changes are within the context of [SDP ticket | ||
TSK-2569](https://jira.ska-sdp.org/browse/TSK-2569). See also the | ||
[Integration of ARL with the DALiuGE Execution Framework, part 2](https://confluence.ska-sdp.org/display/WBS/Integration+of+ARL+with+the+DALiuGE+Execution+Framework%2C+part+2) | ||
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**August 16, 2018** [Tim] More refactoring to being closer alignment with SDP architecture. | ||
1. There are now wrappers for all processing components, both serial and | ||
rsexecute. At the moment, these are just pass-throughs but the point is that they can | ||
be expanded as appropriate. The non-python wrappers will be more substantial. | ||
2. There are only workflows for calibration, imaging, and pipelines. | ||
3. To distinguish the nature of the workflows, these are now all called something like | ||
predict_list_rsexecute_workflow since they all work on lists of data models rather | ||
than just data models. | ||
4. The workflows for serial and rsexecute should work alike. For example, all now | ||
expect lists of Data Models. This is compared to processing_components | ||
where only single Data Models are accepted. A necessary consequence is | ||
that the full range of imaging algorithms are only available via | ||
workflows, either as serial or rsexecute versions (and soon other | ||
types of wrappers). | ||
5. libs has been renamed to processing_library. | ||
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All Dask/rsexecute code now lives in either wrappers or workflows. | ||
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![ARL Module View](./docs/ARL_Module_View.png) | ||
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**July 26, 2018** [Tim], Extracted pure-serial uses of processing components | ||
into workflows/serial (in analogy with workflows/rsexecute). This means that | ||
all functions remaining in processing components are suitable for use in | ||
workflows. The split between processing components and workflows is clearer. | ||
As a consequence nearly all notebooks have moved to workflows/notebooks. | ||
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**July 24, 2018** [Tim], Renamed calskymodel to modelpartition to | ||
be in line with the SDP model views. Also documentation cleanup. | ||
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**June 15, 2018** [Tim], Some more moves and renaming: | ||
* processing_components/component_support->libs/execution support | ||
* processing_components/util->processing_components/simulation | ||
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generic functions moved to image_components and visibility_components | ||
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**June 15 2018** [Tim], the capabilities for reading measurement sets have been improved. | ||
* Both BlockVisibility's and Visibility's can be created. The former is preferred. | ||
* A channel range e.g. range(17,32) can be specified. | ||
* See tests/processing_components/test_visibility_ms for various ways to use this capability. | ||
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**June 14, 2018 [Tim]**, BufferDataModel has been introduced as the root of e.g. BufferImage, BufferSkyModel. All of | ||
these, except for BufferImage use ad hoc HDF5 files. Image can use fits. | ||
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**June 12, 2018 [Tim]**, To fill out the architecture, there is now a ProcessingComponentInterface function for executing | ||
some components. Components have to be wrapped by hand, and the interface defined via a JSON file. | ||
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**May 25, 2018** [Piers], Kubernetes support added. | ||
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**April 30 2018** [Tim], the ARL has been updated to be consistent with the SDP Processing Architecture. This required | ||
very substantial changes throughout. The code is consistent internally but ARL code kept outside the code tree will | ||
need to be updated manually. | ||
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* The top level directory arl has been split into three: libs, processing_components, and workflows | ||
- libs contains functions that are not accessed directly by the Execution Framework | ||
- processing_components contains functions that may be accessed by the EF. | ||
- workflows contains high level workflows using the processing_components. This eventually will migrate to the EF | ||
but some are kept here as scripts or notebooks. | ||
* The tests and notebooks have been moved to be inside the appropriate directory. | ||
* The data definitions formerly in rascil/data have been moved to a top level directory data_models. | ||
* The top level Makefile has been updated | ||
* The docs have been updated | ||
* The use of the term 'graph' has been replaced in many places by 'list' to reflect the wrapping of dask in | ||
rsexecute. | ||
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**April 18, 2018** [Tim], Deconvolution can now be done using overlapped, tapered sub-images (aka facets). | ||
Look for deconvolve_facets, deconvolve_overlap, and deconvolve_taper. | ||
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