NumPy Array Shape Helper

When to use

• When a NumPy expression fails due to shape mismatch.
• When planning reshape or matmul operations before coding.
• When comparing MATLAB vectors with NumPy one-dimensional arrays.

How to use

1. Enter the code, error text, shape values, or template details requested by the form.
2. Choose the relevant language, style, operation, or option set, then click Analyze Array Shape.
3. Review warnings and unsupported-pattern notes before copying or downloading the result.
4. Paste the generated snippet into your own MATLAB or Python environment only after inspection and testing.

Inputs

Shape values

First shape, second shape, operation, optional target shape, axis, and MATLAB comparison notes.

Notation

Output explanation

• Compatibility statement and output shape when valid.
• Suggested NumPy code for the selected operation.
• Warnings about row/column ambiguity, axis choices, and MATLAB differences.

Supported patterns

• broadcasting compatibility
• matrix multiplication output shape
• reshape product checks
• simple concatenate axis checks
• MATLAB-to-NumPy row and column notes

Unsupported patterns

• runtime dtype checks, ragged arrays, object arrays, masked arrays, or xarray labels
• memory layout benchmarking
• executing array operations

Interpretation

• Treat generated code as a starting point that must be tested with representative data.
• Warnings identify cases where the rule-based helper cannot prove semantic equivalence.
• The visual summary is a checklist or structure preview, not an execution trace.

Code-helper guidance

• Write shapes in comments beside complex array code.
• Use reshape only when the element count is preserved.

Worked examples

Assumptions

• Shapes contain finite positive integer dimensions.
• The helper follows ordinary NumPy shape rules, not library-specific wrappers.

Practical guidance

• Write shapes in comments beside complex array code.
• Use reshape only when the element count is preserved.

Common mistakes

• Confusing (n,) with (n,1).
• Using axis 1 on a one-dimensional array.

Limitations

• The helper does not execute MATLAB, Python, NumPy, pandas, or Matplotlib code.
• Generated snippets may require imports, workspace variables, data cleaning, or environment-specific changes.
• The rule set does not replace code review, unit tests, validated numerical software, or qualified professional judgment.

Related workflow links