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vscode-numpy-viewer-simple

vscode-numpy-viewer-simple

SunYingkai

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8 installs
| (0) | Free
Display (binary) .npy or .npz files in VSCode. Based on numpy-viewer but adds shape info in status bar and only show ten rows in table view.
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Numpy file viewer

VSCode NumPy Viewer Simple

License: MIT PRs Welcome

Enhanced version of vscode-numpy-viewer with improved data visualization

! Displaying very large arrays (e.g., size > 10,000,000) is not currently supported.

Display (binary) .npy or .npz files in VSCode with enhanced features.

New Features in Simple Version

  • ✅ Shape Information Display: Shows array dimensions for each file in .npz archives
  • ✅ Limited Row Display: Shows only first 10 rows/elements for better performance and readability
  • ✅ Enhanced Table View: Improved table display with truncation indicators
  • ✅ Multi-dimensional Limiting: Limits display in all dimensions, not just rows

img

Change log

Please refer to CHANGELOG.md.

Other Features

  • [x] Show array shape. [see gif]
  • [x] Table view for 2D/1D array. [see gif]
  • [ ] Array slice. (In progress)

Supported Data Type

Refer: numpy/typing/tests/data/pass/scalars.py | numpy/typing/tests/test_typing.py

Status Name Description Abbrev
✅ uint8 numpy.unsignedinteger[numpy._typing._8Bit] u1
✅ uint16 numpy.unsignedinteger[numpy._typing._16Bit] u2
✅ uint32 numpy.unsignedinteger[numpy._typing._32Bit] u4
✅ uint64 numpy.unsignedinteger[numpy._typing._64Bit] u8
✅ int8 numpy.signedinteger[numpy._typing._8Bit] i1
✅ int16 numpy.signedinteger[numpy._typing._16Bit] i2
✅ int32 numpy.signedinteger[numpy._typing._32Bit] i4
✅ int64 numpy.signedinteger[numpy._typing._64Bit] i8
✅ float16 numpy.floating[numpy._typing._16Bit] f2
✅ float32 numpy.floating[numpy._typing._32Bit] f4
✅ float64 numpy.floating[numpy._typing._64Bit] f8
float128 numpy.floating[numpy._typing._128Bit] f16
complex64 numpy.complexfloating[numpy._typing._32Bit, numpy._typing._32Bit] c8
✅ complex128 numpy.complexfloating[numpy._typing._64Bit, numpy._typing._64Bit] c16
complex256 numpy.complexfloating[numpy._typing._128Bit, numpy._typing._128Bit] c32
✅ bool_ b1
✅ str_ U
✅ bytes_ S
datetime64 M
timedelta64 m
Alias
ubyte numpy.unsignedinteger[{dct['_NBitByte']}]
ushort numpy.unsignedinteger[{dct['_NBitShort']}]
uintc numpy.unsignedinteger[{dct['_NBitIntC']}]
uintp numpy.unsignedinteger[{dct['_NBitIntP']}]
uint numpy.unsignedinteger[{dct['_NBitInt']}]
ulonglong numpy.unsignedinteger[{dct['_NBitLongLong']}]
byte numpy.signedinteger[{dct['_NBitByte']}]
short numpy.signedinteger[{dct['_NBitShort']}]
intc numpy.signedinteger[{dct['_NBitIntC']}]
intp numpy.signedinteger[{dct['_NBitIntP']}]
int_ numpy.signedinteger[{dct['_NBitInt']}]
longlong numpy.signedinteger[{dct['_NBitLongLong']}]
half numpy.floating[{dct['_NBitHalf']}]
single numpy.floating[{dct['_NBitSingle']}]
double numpy.floating[{dct['_NBitDouble']}]
longdouble numpy.floating[{dct['_NBitLongDouble']}]
csingle numpy.complexfloating[{dct['_NBitSingle']}, {dct['_NBitSingle']}]
cdouble numpy.complexfloating[{dct['_NBitDouble']}, {dct['_NBitDouble']}]
clongdouble numpy.complexfloating[{dct['_NBitLongDouble']}, {dct['_NBitLongDouble']}]

* bold items are defaults.

Reference

  • ludwigschubert/js-numpy-parser
  • tomoki1207/vscode-pdfviewer
  • janisdd/vscode-edit-csv

Copyright and License

Copyright (c) 2024 SunYingkai

This project is licensed under the MIT License - see the LICENSE file for details.

Based on the original vscode-numpy-viewer by Percy, enhanced with improved data visualization features.

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