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  1. SAFe Program
  2. SP-27

Investigate CALC design or redesign

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      The key benefit hypotheses are:

      1. Being able to integrate CALC into the SKA TMC prototype provides us the assurance of a well validated and accurate library for delay calculations and the like, it reduces the risk of having to redevelop these features from scratch. 2. Validating CALC scalability either directly or with some redesign will provide clarity on how we will meet SKA requirements for delay calculations. 3. A wrapper that provides a Python callable API eases the integration effort with TMC

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      The key benefit hypotheses are: 1. Being able to integrate CALC into the SKA TMC prototype provides us the assurance of a well validated and accurate library for delay calculations and the like, it reduces the risk of having to redevelop these features from scratch. 2. Validating CALC scalability either directly or with some redesign will provide clarity on how we will meet SKA requirements for delay calculations. 3. A wrapper that provides a Python callable API eases the integration effort with TMC
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      1. The test results comparing CALC outputs with expected values is available across a range of test cases 2. Scalability test results available showing how CALC scales in performance from a smaller no of stations to higher 3. Relevant wrapper APIs can be succesfully called from a Python script and return correct values

      Show
      1. The test results comparing CALC outputs with expected values is available across a range of test cases 2. Scalability test results available showing how CALC scales in performance from a smaller no of stations to higher 3. Relevant wrapper APIs can be succesfully called from a Python script and return correct values
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    Description

      Are we going to use CALC or not?

      If we are going to use CALC - how do we wrap it?

      If not, what is the alternative?

      Stretch objective: How does this integrate in with pointing interface?

       

      Tentative seed stories (based on discussion with Robert Laing

      Create a test shell for validating CALC delay calculations

      • Inputs: Station locations and pointing direction
      • Compare CALC output with expected delay results (Analytical or Meerkat code?)

      Check for scalability of CALC and performance as stations increase

      Create  wrapper for Python for ease of integration

      T-shirt sizing M without considering pointing

      Stretch goal: Validate pointing (Convert ICRF to tropocentric Alt Az However we might carve out the pointing aspects as a separate feature 

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          Feature - A Feature is a service that fulfills a stakeholder need. Each feature includes a benefit hypothesis and acceptance criteria, and is sized or split as necessary to be delivered by a single Agile Release Train (ART) in a Program Increment (PI). SP-380 KATPoint Delay CalculationTechnical Debt

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                v.mohile Mohile, Vivek
                n.rees Rees, Nick
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