Axescheck

At its simplest, Axescheck refers to the systematic validation of coordinate axes, dimensional references, or data vectors within a given system. The term is a portmanteau of "Axes" (referring to the X, Y, Z planes in 3D space, or categorical axes in data) and "Check" (verification against a standard).

However, in professional jargon, Axescheck has evolved to represent a broader discipline: axescheck

The core philosophy of Axescheck is simple: Trust, but verify. Never assume that your axes are correct just because nothing crashed. At its simplest, Axescheck refers to the systematic

Ensuring a batch of data has the correct shape before feeding it to a model. The core philosophy of Axescheck is simple: Trust,

def process_batch(images):
    # Verify we have a batch of 4D tensors (Batch, Height, Width, Channels)
    # Last axis must be 3 (RGB)
    axescheck(images, dims=4, shape=(None, None, None, 3), name="ImageBatch")
# ... proceed with processing ...

name: Axescheck Validation
on: [push]
jobs:
  axescheck:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - name: Run axescheck tests
        run: |
          python -m pytest tests/test_axes.py
      - name: Visual axescheck (screenshot comparison)
        run: |
          python scripts/generate_axis_plot.py --output test.png
          python scripts/compare_axes_to_golden.py test.png golden.png

For physical hardware, schedule an Axescheck routine every morning at 6 AM before production begins. Use a calibrated artifact (e.g., a 1-2-3 block) that the machine measures automatically.