pulse2percept.implants.ensemble

EnsembleImplant

Classes

EnsembleImplant(implants[, preprocess, ...])

class pulse2percept.implants.ensemble.EnsembleImplant(implants, preprocess=False, safe_mode=False)

classmethod from_visual_field_map(implant_type, visual_field_map, locs=None, xrange=None, yrange=None, step=None, region=None)

Create an ensemble implant from a visual field map.

An implant of type implant_type is created for each visual field location specified either by locs or by xrange, yrange and step, and centered at the tissue coordinates the map transforms that location to.

The map may be retinal, cortical, or any other 2D VisualFieldMap. 3D maps are not supported, because placing an implant on a folded surface needs more than the (x, y) anchor this method passes on; see from_neuropythy().

Added in version 0.11.0: Replaces from_cortical_map, which knew about cortex specifically.

Parameters:

• implant_type (type) – Type of implant to create for the ensemble. Must subclass p2p.implants.Implant

• visual_field_map (VisualFieldMap) – Visual field map to create the implant from.

• locs (np.ndarray with shape (n, 2), optional) – Array of visual field locations to create implants at (dva). Not needed if using xrange, yrange, and step.

• xrange (tuple of floats, optional) – Range of x and y coordinates (dva) to create implants at.

• yrange (tuple of floats, optional) – Range of x and y coordinates (dva) to create implants at.

• step (float or (x_step, y_step), optional) – Spacing (dva) between implant centers.

• region (str, optional) – Region of tissue to create the implant in, e.g. 'ret' or 'v1'. Required unless the map has exactly one region.

Returns:

ensemble – Ensemble implant created from the visual field map.

Return type:

p2p.implants.EnsembleImplant

Notes

• These are visual field coordinates, so they may be given as plain numbers of degrees or as unitful quantities (e.g. xrange=(-3 * dva, 3 * dva)). Contrast from_coords(), which places implants by their physical position in microns. See pulse2percept.units.

classmethod from_coords(implant_type, locs=None, xrange=None, yrange=None, step=None)

Create an ensemble implant using physical (cortical or retinal) coordinates.

Parameters:

• implant_type (type) – The type of implant to create for the ensemble.

• locs (np.ndarray with shape (n, 2), optional) – Array of physical locations (um) to create implants at. Not needed if using xrange, yrange, and step.

• xrange (tuple of floats, optional) – Range of x and y coordinates (um) to create implants at. Required (together with step) if locs is not given.

• yrange (tuple of floats, optional) – Range of x and y coordinates (um) to create implants at. Required (together with step) if locs is not given.

• step (float or (x_step, y_step), optional) – Spacing (um) between implant centers.

Raises:

ValueError – If neither locs nor all three of xrange, yrange and step are given.

Notes

• Lengths may be given as plain numbers of microns or as unitful quantities (e.g. xrange=(-1 * mm, 1 * mm)). See pulse2percept.units.

Changed in version 0.10.0: The grid arguments no longer have defaults. They used to fall back on (-3, 3) and 1, which are the degrees of visual angle from_visual_field_map() works in; here they are microns, so the default laid every implant out inside a 6 um square.

property implants

Dict of implants

prepare_stim(source)

Prepare stimulation for an ensemble implant.

source may address the combined electrode array directly, or be a dict keyed by constituent implant keys. Per-implant sources are prepared by each constituent implant, merged, then passed through ensemble-level preprocessing and safety checks. Missing implant keys contribute zeros.

Changed in version 0.11.0: Replaces merge_stimuli and the stimuli previously stored on constituent implants.

Parameters:

source (dict or Stimulus source type) – One source for the whole ensemble, or {implant_key: source}.

Returns:

stim – Merged stimulation for the ensemble.

Return type:

Stimulus or None

Examples

>>> import numpy as np
>>> from pulse2percept.implants import EnsembleImplant
>>> from pulse2percept.implants.cortex import Orion
>>> ensemble = EnsembleImplant.from_coords(
...     Orion, locs=np.array([(0, 0), (-35000, 0)]))
>>> ensemble.prepare_stim({0: np.ones(60),
...                        1: 2 * np.ones(60)}).data.shape
(120, 1)

check_stim(stim)

Quality-check the stimulus

This method is executed every time a stimulus is prepared (see prepare_stim()).

If safe_mode is set to True, this function will only allow stimuli that are charge-balanced. If max_current is set, it will only allow stimuli whose total instantaneous current stays within it.

Both are questions about electricity, and neither can be answered about a stimulus that is not a current, so each raises a DimensionMismatchError on one. In the ordinary flow this cannot happen: prepare_stim() has already checked the stimulus against stimulus_unit. check_stim is public, though, and may be handed anything.

The user can define their own checks in implants that inherit from Implant.

Parameters:

stim (Stimulus source type) – A valid source type for the Stimulus object (e.g., scalar, NumPy array, pulse train).

Raises:

• DimensionMismatchError – If an electrical check was requested and stim is not measured in units of current.

• .. versionchanged: – 0.10.0: The electrical checks verify that the stimulus really is electrical, instead of reading whatever numbers it holds as microamps.

property electrode_array

Electrode array

property electrode_names

Return a list of all electrode names in the electrode array

property electrode_objects

Return a list of all electrode objects in the array

property electrodes

Return all electrode names and objects in the electrode array

Internally, electrodes are stored in an ordered dictionary. You can iterate over different electrodes in the array as follows:

for name, electrode in implant.electrodes.items():
    print(name, electrode)

You can access an individual electrode by indexing directly into the implant, e.g. implant['A1'] or implant[0], and ask how many there are with len(implant).

property encoder

Stimulus encoder used for image or video input.

Must be an ImplantEncoder. Model-aware encoders such as TraceEncoder are called directly instead. If None, dimensionless image/video stimuli are not encoded automatically.

Assigning an unbound encoder (encoder.implant is None) binds it to this implant. An encoder bound to a different implant is rejected with a ValueError.

family = None

Named device family, if applicable, e.g. 'PRIMA'. .. versionadded:: 0.11.0

property max_current

Total instantaneous current (uA) the stimulator can source

property n_electrodes

Number of electrodes in the array

This is equivalent to calling electrode_array.n_electrodes.

placement = None

Where the device sits relative to the tissue it stimulates, where the literature is unambiguous about it; None where it is not, or where the class describes a family rather than a device.

plot(annotate=False, autoscale=True, ax=None, stim=None, stim_cmap=False)

Plot the device in its local coordinate frame.

Use model.plot(show_implant=True) to show model-side placement.

Parameters:

• annotate (bool, optional) – Whether to label electrodes.

• autoscale (bool, optional) – Whether to adjust the x,y limits of the plot to fit the implant

• ax (matplotlib.axes._subplots.AxesSubplot, optional) – A Matplotlib axes object. If None, will either use the current axes (if exists) or create a new Axes object.

• stim (Stimulus source type, optional) –

  What is presented to the device. Prepared through prepare_stim(), so the colors show what the electrodes actually deliver. Required by stim_cmap.

  Added in version 0.11.0.

• stim_cmap (bool, str, or matplotlib colormap, optional) – If not false, the fill color of the plotted electrodes will vary based on maximum stimulus amplitude on each electrode. The chosen colormap will be used if provided

Returns:

ax – Returns the axis object of the plot

Return type:

matplotlib.axes.Axes

preprocess_stim(stim)

Preprocess the stimulus

This method is executed every time a stimulus is prepared.

No preprocessing is performed by default, but the user can define their own method in implants that inherit from return stim Implant.

A custom method must return a Stimulus object with the correct number of electrodes for the implant.

Parameters:

stim (Stimulus source type) – A valid source type for the Stimulus object (e.g., scalar, NumPy array, pulse train).

Returns:

stim_out

Return type:

Stimulus object

property raster

Raster pattern used to schedule stimulation across electrodes.

Assigning a raster binds it to this implant.

property scene_input_frame

Coordinate frame used to register scene input.

'eye' means gaze changes which scene content reaches the implant; 'head' means scene input is fixed relative to the head.

Defaults to default_scene_input_frame. Setting to None restores that default.

Added in version 0.11.0.

stimulus_unit = uA

Unit used by prepared stimuli. Defaults to electrical current.

technology = None

Stimulation technology, e.g. 'photovoltaic'. .. versionadded:: 0.11.0

property thresholds

Perceptual threshold current (uA) for each electrode.

Assign a single current for the whole array, a per-electrode dict, or None to clear the calibration. Threshold-relative pulse trains are calibrated against whatever is in force at the moment prepare_stim() runs.

Added in version 0.10.0.

Changed in version 0.11.0: Changing thresholds affects the next stimulus prepared, rather than rewriting one the implant was holding.