LinearProgression¶
Create a raw array that contains an arithmetic progression of numbers with real-valued step size and starts/ends.
This corresponds to the linspace function in Python and MATLAB(tm). One may optionally specify a template array to determine the num value if desired; in this case the shape of the created array will conform to that of the template array, which must be a vector. The node supports alternative compute backends, which can be used to speed up processing. Version 1.0.0
Ports/Properties¶
array¶
Output array.
like¶
Optional template array.
start¶
Start value of the range.
stop¶
End value of the range, must be provided. In contrast to CreateIntegerRange, this is included in the range unless the inclusive option is set to False.
num¶
Number of steps to use. If an array or list has been wired into the 'like' input of the node, then this value may be omitted and will then match the size of that array.
inclusive¶
Whether the stop value is included in the range or excluded.
backend¶
Optional compute backend to use. Keep is the current default, which resolves to that of the template array if one is provided and otherwise numpy unless overridden. Numpy is the standard CPU backend that underpins most of NeuroPype's operations. The others require one or more GPUs to be present on the system, except for torch-cpu. For best performance, keep all arrays that interact with each other (via processing nodes) on the same backend.
precision¶
Numeric precision to use. Keep resolves to the precision of the template array if one is provided, and otherwise to the current default (usually 64-bit). Can be reduced to save memory (e.g. if running on GPU).
set_breakpoint¶
Set a breakpoint on this node. If this is enabled, your debugger (if one is attached) will trigger a breakpoint.
metadata¶
User-definable meta-data associated with the node. Usually reserved for technical purposes.