Up to date

This page is up to date for NumDot stable. If you still find outdated information, please open an issue.

NumPy, xtensor, and NumDot

NumDot attempts to recreate NumPy-like behavior, and uses xtensor under the hood. While most things are consistent across all three libraries, differences exist.

Fundamental Comparison

NumDot functions always return tensors, to avoid accidentally promoting dtypes. NumPy returned types like np.float32 can be used like primitive numbers.
NumDot does not overload operators like + and *, due to a gdscript limitation.
NumDot does not support subscripts (a[start:stop:step], due to a gdscript limitation. Instead, use a.get(nd.range(start, stop, step).
NumPy supports keyword arguments. NumDot only supports ordered arguments, due to a gdscript limitation.
xtensor operations are lazy views. NumPy and NumDot operations evaluate immediately, with the exception of strideable views.

Function Cheat Sheet

NumPy, xtensor and NumDot Cheat Sheet
NumPy	xtensor	NumDot	Notes
`a.shape`	`a.shape()`	`a.shape()`
`a.size`	`a.size()`	`a.size()`
`a.ndim`	`a.dimension()`	`a.ndim()`
`a[0]`	`xt::view(a, { 0 })` `a(0)`	`a.get(0)` `a.get_int(0)` `a.get_float(0)`	Create a view, or return an element of the tensor.
`a[0] = b`	`xt::view(a, { 0 }) = b` `a(0) = b`	`a.set(b, 0)`	Update a slice of a tensor.
`a[:]`	`xt::view(a, { xt::all() })`	`a.get(&":")`	Select all elements.
`a[None]`	`xt::view(a, { xt::newaxis() })`	`a.get(&"newaxis")`, `a.get(null)`	Insert new axis.
`a[..., 0]`	`xt::view(a, { xt::ellipsis(), 0 })`	`a.get(&"...", 0)`	Ellipsis stands in for all other dimensions.
`a[2:]`	`xt::view(a, { 2\|_ })`	`a.get(nd.from(2))`	Select elements starting at index 2.
`a[:2]`	`xt::view(a, { _\|2 })`	`a.get(nd.to(2))`	Select elements ending at index 2.
`a[2:4]`	`xt::view(a, { 2\|4 })`	`a.get(nd.range(2, 4))`	Select elements starting at index 2, ending at index 4.
`a[2:40:2]`	`xt::view(a, { 2\|40\|2 })`	`a.get(nd.range(2, 40, 2))`	Select every second element, starting at index 2, ending at index 4.
`a + b` `np.add(a, b)`	`a + b`	`nd.add(a, b)`
`a - b` `np.subtract(a, b)`	`a - b`	`nd.subtract(a, b)`
`a * b` `np.multiply(a, b)`	`a * b`	`nd.multiply(a, b)`
`a / b` `np.divide(a, b)`	`a / b`	`nd.divide(a, b)`
`np.sin(a)`	`xt::sin(a)`	`nd.sin(a)`	Analogous for all trig functions.
`np.degrees` `np.deg2rad`	`xt::deg2rad`	`nd.deg2rad`
`np.radians` `np.rad2deg`	`xt::rad2deg`	`nd.rad2deg`

Haven't found what you need? Try nd!

User-contributed notes

Please read the User-contributed notes policy before submitting a comment.