/vscode-numpy-viewer

Display (binary) .npy or .npz files in VSCode.

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Numpy file viewer

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

Display (binary) .npy or .npz files in VSCode.

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Change log

Please refer to CHANGELOG.md.

Other Features

  • Show array shape. [see gif]
  • 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