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Feature Request: Persist Ayanamsha Selection at Kundali/Profile Level

Problem Statement

Currently, when a user generates a Kundali using a specific Ayanamsha (e.g., Lahiri) and later revisits the same profile, the system resets the Ayanamsha selection to the application default (e.g., Nadi). This requires the user to manually reselect the preferred Ayanamsha and regenerate the Kundali.


Expected Behavior

Initiallly when new Kundali is generated that screen can show Application Default. After that selected Ayanamsha should be saved at the Kundali/Profile level and automatically loaded whenever that Kundali is reopened.


Benefits

  1. Improved User Experience

    • Eliminates the need to repeatedly select the same Ayanamsha.

    • Reduces user frustration and avoids accidental interpretation using an incorrect Ayanamsha.

  2. Consistency of Astrological Analysis

    • Ensures charts are always viewed using the Ayanamsha originally chosen by the user.

    • Prevents confusion caused by different planetary positions and calculations across Ayanamsha systems.

  3. Reduced Compute Consumption

    • Avoids unnecessary chart regeneration when users discover the wrong Ayanamsha was loaded.

    • Reduces duplicate calculations and server processing.

Suggested Implementation

  • Store the selected Ayanamsha as part of the Kundali/Profile metadata.

  • When a profile is opened:

    • Load the saved Ayanamsha if available.

    • Fall back to the application default only for new profiles or profiles without a saved setting.

  • Optionally display the active Ayanamsha prominently on the Kundali screen for clarity.

Example Scenario

  1. User creates a Kundali using Lahiri Ayanamsha.

  2. System saves Ayanamsha = Lahiri against that profile.

  3. User revisits the profile after a week.

  4. Kundali automatically loads with Lahiri selected and calculations already aligned with that setting.

Priority: Low-Medium

This enhancement would improve usability, maintain calculation consistency, and reduce unnecessary computational overhead

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