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WIP: Structure Docs #252
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WIP: Structure Docs #252
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| ====================== | ||
| Explaining Sunkit-spex | ||
| ====================== | ||
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| Here we will explain not only the need for Sunkit-spex but also the design philosophy we've adopted to handle this complicated process. | ||
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| .. toctree:: | ||
| :maxdepth: 2 | ||
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| infrastructure |
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| ************************** | ||
| Sunkit-spex Infrastructure | ||
| ************************** | ||
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| This section will detail the workflow design of Sunkit-spex. Here we | ||
| will provide details on the flexible package structure while providing | ||
| relavent links to examples and code. | ||
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| Overview | ||
| ======== | ||
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| Sunkit-spex takes a modular design perspective when it comes to working | ||
| with X-ray spectral data. Broadly, four categories exist: 1. the spectral | ||
| data; 2. the models; 3. the statistical approach; and 4. the model-to-data | ||
| comparison. The diagram below shows how the former three categories come | ||
| together, enabling the model-to-data comparison and also indicates how the | ||
| three categories are dependent on each other issuing the need for checks. | ||
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| .. raw:: html | ||
| :file: ./basic-pipeline.drawio.svg | ||
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| 1. For data provided from a given instrument team, a user can use **Spectrum | ||
| containers** to store the all information relavent for fitting each | ||
| specific spectrum. | ||
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| 2. **Core Model Objects** are provided although users can create their own. | ||
| These borrow their use from Astropy somewhat and can be combined into | ||
| composite models for more complicated cases. | ||
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| 3. The final piece of the puzzle before model-to-data comparison can take | ||
| place is for the **Objective Function** or comparison statistics to be | ||
| defined. These will be used to govern the goodness of comparison and | ||
| their choice can influence validity of the model-to-data comparison | ||
| analysis. | ||
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| 4. Providing the information contained above, a given model can be compared | ||
| to the user's data. All three components above are all in some way dependent | ||
| on each other; therefore, some **Checks (4a)** need to be performed for | ||
| validility. Post-checks, the models can be converted to the same unit-space | ||
| as the data using the observation & instrument information from the | ||
| **Spectrum Container** for direct comparison in the **Model-to-Data Comparison | ||
| Object (4b)**. Comparison will take place using the determined **Objective | ||
| Function** that will be consistent with the data error type from the | ||
| **Spectrum Container**. | ||
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| Spectral Data | ||
| ============= | ||
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| Instrument Data Container | ||
| ------------------------- | ||
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| Spectrum Container | ||
| ------------------ | ||
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| Core Model Object | ||
| ================= | ||
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| Objective Function | ||
| ================== | ||
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| Fitter | ||
| ====== | ||
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| Model-to-Data Comparison Object | ||
| ------------------------------- |
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So potentially we could keep the high level information in the root but more detailed stuffs should go under discussion e.g. discussion/design discussion/fitting discussion/statistics if we're going to follow https://diataxis.fr
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This makes more sense and absolutely happy to move to it from what I have.