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Section Navigation

  • Getting Started
  • Coding conventions
  • Jupyter Notebook Style Guide
  • Tooling
  • Releasing Scipp
  • Dependencies
  • Architecture Decision Records
    • ADR 0001: Remove dataset masking support
    • ADR 0002: Remove instrument view 2D projection options
    • ADR 0003: Refactor plotting code to use Model-View-Controller design pattern
    • ADR 0004: Use the ipympl backend for Matplotlib figures in Jupyter
    • ADR 0005: Remove need for bins property when calling bin or histogram
    • ADR 0006: Add read-only flags
    • ADR 0007: Do not support arguments referring to x or y
    • ADR 0008: Consistent multi-dimensional coords
    • ADR 0009: Handle dimensionless as non-counts
    • ADR 0010: Acknowledge stability and maintainability tasks
    • ADR 0011: Renaming of Dimensions in transform_coords
    • ADR 0012: Rebin should apply irreducible masks
    • ADR 0013: Plot should not resample automatically
    • ADR 0014: Switch to Calendar Versioning
    • ADR 0015: Disable support for broadcasting variances
    • ADR 0016: Do not support “attrs”
    • ADR 0017: Restrict Dataset to items with matching dimensionality
    • ADR 0018: More explicit control of replaced dims in bin and hist functions
  • Internals
    • Concepts
    • C++ API for constructing variables
    • Customizing Scipp
    • Multi-Dimensional Indexing
    • Transforming data
    • Implementation of class Variable
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Internals#

  • Concepts
    • DataArray and Dataset meta data handling
  • C++ API for constructing variables
  • Customizing Scipp
    • Overview
    • Custom dtypes
  • Multi-Dimensional Indexing
    • ViewIndex
    • MultiIndex
  • Transforming data
    • Overview
    • Basic usage
    • Recommended usage
  • Implementation of class Variable
    • Type erasure
    • Views and variables
    • VariableConstView
    • Binned variables

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ADR 0018: More explicit control of replaced dims in bin and hist functions

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Concepts

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