Skip to content

← deprecated package

CreateGeomRange

Create an array that contains a sequence of numbers that follow a geometric progression, i.e

., are evenly spaced on a log scale between a start and end value. This node is deprecated; use Geometric Progression instead. This corresponds to the logspace function in Python and MATLAB(tm) if endpoints are specified as exponents, and otherwise to the geomspace function. 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.

  • verbose name: Array
  • default value: None
  • port type: DataPort
  • value type: AnyArray (can be None)
  • data direction: OUT

like

Optional template array.

  • verbose name: Like
  • default value: None
  • port type: DataPort
  • value type: AnyArray (can be None)
  • data direction: IN

start

Start of the range.

  • verbose name: Start
  • default value: 0
  • port type: FloatPort
  • value type: float (can be None)

stop

End of the range, must be provided.

  • verbose name: Stop
  • default value: None
  • port type: FloatPort
  • value type: float (can be None)

endpoints_are

Whether the endpoints are specified as exponents to the given base (exponents mode), or as the actual start-stop values (simple mode).

  • verbose name: Endpoints Are
  • default value: simple
  • port type: EnumPort
  • value type: str (can be None)

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.

  • verbose name: Number Of Steps
  • default value: None
  • port type: IntPort
  • value type: int (can be None)

inclusive

Whether the stop value is inclusive or exclusive.

  • verbose name: Inclusive
  • default value: True
  • port type: BoolPort
  • value type: bool (can be None)

base

Base of the exponential progression. When using simple mode, this is inferred from the endpoints and the number of steps. Alternatively, when using exponents mode, a default of 10 is assumed, and the provided endpoints will be exponentiated with this base (i.e., the sequence runs from 10start to 10stop). In either case the resulting sequence of numbers will be spaced evenly when transformed to a log scale (i.e., when taking their logarithm).

  • verbose name: Base
  • default value: None
  • port type: FloatPort
  • value type: float (can be None)

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.

  • verbose name: Backend
  • default value: keep
  • port type: EnumPort
  • value type: str (can be None)

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).

  • verbose name: Precision
  • default value: keep
  • port type: EnumPort
  • value type: str (can be None)

set_breakpoint

Set a breakpoint on this node. If this is enabled, your debugger (if one is attached) will trigger a breakpoint.

  • verbose name: Set Breakpoint (Debug Only)
  • default value: False
  • port type: BoolPort
  • value type: bool (can be None)

metadata

User-definable meta-data associated with the node. Usually reserved for technical purposes.

  • verbose name: Metadata
  • default value: {}
  • port type: DictPort
  • value type: dict (can be None)