pulse2percept.utils.constants

DT, MIN_AMP, MS_PER_S, UM_PER_MM, VIDEO_BLOCK_SIZE, ZORDER

Module Attributes

`MIN_AMP`	Pulses with net currents smaller than 10 picoamps are considered charge-balanced (here expressed in microamps).
`DT`	Sampling time step (ms); defines the duration of the signal edge transitions.
`MS_PER_S`	Milliseconds in a second (1000).
`UM_PER_MM`	Microns in a millimeter (1000).
`ZORDER`	An enum specifying the zorder values to use in Matplotlib plots, ensuring that foreground items (like implants) always appear on top of background items (like axon maps).

pulse2percept.utils.constants.MIN_AMP = 1e-05: Pulses with net currents smaller than 10 picoamps are considered charge-balanced (here expressed in microamps).

pulse2percept.utils.constants.DT = 0.001: Sampling time step (ms); defines the duration of the signal edge transitions.

pulse2percept.utils.constants.MS_PER_S = 1000.0

Milliseconds in a second (1000).

p2p counts durations in milliseconds and frequencies in hertz, so anything that turns one into the other needs this factor: a pulse train’s window is MS_PER_S / freq ms, and a duration in ms is dur / MS_PER_S seconds. Derived from the unit system once, at import time, rather than written down as a bare 1000 at each site – those are the conversions that go wrong silently. Numerical code divides by it and stays plain floats; nothing here puts a Quantity inside a loop.

Added in version 0.10.0.

pulse2percept.utils.constants.UM_PER_MM = 1000.0

Microns in a millimeter (1000).

p2p stores tissue coordinates in microns, while published cortical and retinal fits are written in millimeters and plots are labelled in them. Same idea as MS_PER_S: derive the factor from the unit system once, then do plain arithmetic with it.

Added in version 0.10.0.

pulse2percept.utils.constants.ZORDER = {'annotate': 2000, 'back': 0, 'background': 1, 'foreground': 50, 'front': 9999}: An enum specifying the zorder values to use in Matplotlib plots, ensuring that foreground items (like implants) always appear on top of background items (like axon maps).