API¶

Probe¶

class probeinterface.Probe(ndim: int = 2, si_units: str = 'um', name: str | None = None, serial_number: str | None = None, model_name: str | None = None, manufacturer: str | None = None)¶

Class to handle the geometry of one probe.

This class mainly handles contact positions, in 2D or 3D. Optionally, it can also handle the shape of the contacts and the shape of the probe.

annotate(**kwargs)¶: Annotates the probe object.

Parameter¶

**kwargs : list of kwyword arguments to add to the annotations

property contact_positions¶: The position of the center for each contact

copy()¶

Copy to another Probe instance.

Note: device_channel_indices is not copied and contact_ids is not copied

create_auto_shape(probe_type: str = 'tip', margin: float = 20.0)¶

Create planar contour automatically based on probe contact positions.

Parameters¶

probe_typestr, by default ‘tip’: The probe type (‘tip’ or ‘rect’)
marginfloat, by default 20.0: The margin to add to the contact positions

static from_dataframe(df: pandas.DataFrame)¶

Create Probe from a pandas.DataFrame see Probe.to_dataframe()

Parameters¶

dfpandas.DataFrame: The dataframe representation of the probe

Returns¶

probeProbe: The instantiated Probe object

static from_dict(d: dict) → Probe¶

Instantiate a Probe from a dictionary

Parameters¶

ddict: The dictionary representation of the probe

Returns¶

probeProbe: The instantiated Probe object

static from_numpy(arr: ndarray)¶

Create Probe from a complex numpy array see Probe.to_numpy()

Parameters¶

arrnp.array: The structured np.array representation of the probe

Returns¶

probeProbe: The instantiated Probe object

get_contact_count() → int¶: Return the number of contacts on the probe.

get_contact_vertices() → list¶: Return a list of contact vertices.

get_shank_count() → int¶: Return the number of shanks for this probe.

get_shanks()¶: Return the list of Shank objects for this Probe

get_slice(selection: ndarray[bool | int])¶

Get a copy of the Probe with a sub selection of contacts.

Selection can be boolean or by index

Parameters¶

selectionnp.array of bool or int (for index): Either an np.array of bool for desired selection of contacts or the indices of the desired contacts

Returns¶

sliced_probe: Probe: The sliced probe

move(translation_vector: np.array | list)¶

Translate the probe in one direction.

Parameters¶

translation_vectorlist or array: The translation vector in shape 2D or 3D

rotate(theta: float, center=None, axis=None)¶

Rotate the probe around a specified axis.

Parameters¶

thetafloat: In degrees, anticlockwise.
centerarray: Center of rotation. If None, the center of probe is used
axisNone: Axis of rotation. It must be None for 2D probes and specified for 3D ones

rotate_contacts(thetas: float | np.array[float] | list[float])¶

Rotate each contact of the probe. Internally, it modifies the contact_plane_axes.

Parameters¶

thetasarray of float: Rotation angle in degrees. If scalar, then it is applied to all contacts.

set_contact_ids(contact_ids: np.array | list)¶

Set contact ids. Channel ids are converted to strings. Contact ids must be unique for the Probe and also for the ProbeGroup

Parameters¶

contact_idslist or array: Array with contact ids. If contact_ids are int or float they are converted to str

set_contacts(positions, shapes='circle', shape_params={'radius': 10}, plane_axes=None, contact_ids=None, shank_ids=None)¶

Sets contacts to a Probe.

This sets four attributes of the probe:: contact_positions, contact_shapes, contact_shape_params, _contact_plane_axes

Parameters¶

positionsarray (num_contacts, ndim): Positions of contacts (2D or 2D depending on probe ‘ndim’).
shapesstr or array: Shape of each contact (‘circle’/’square’/’rect’).
shape_paramsdict or list of dict: Contains kwargs for shapes (“radius” for circle, “width” for square, “width/height” for rect)
plane_axesnp.array (num_contacts, 2, ndim): Defines the two axes of the contact plane for each electrode. The third dimension corresponds to the probe ndim (2d or 3d).
contact_ids: None or array of str: Defines the contact ids for the contacts. If None, contact ids are not assigned.
shank_idsNone or array of str: Defines the shank ids for the contacts. If None, then these are assigned to a unique Shank.

set_device_channel_indices(channel_indices: np.array | list)¶

Manually set the device channel indices.

If some channels are not connected or not recorded then channel should be set to “-1”

Parameters¶

channel_indicesarray of int: The device channel indices to set

set_planar_contour(contour_polygon: list)¶

Set the planar countour (the shape) of the probe.

Parameters¶

contour_polygonlist: List of contour points (2D or 3D depending on ndim)

set_shank_ids(shank_ids: np.array | list)¶

Set shank ids.

Parameters¶

shank_idslist or array: Array with shank ids, if int or float converted to strings

to_2d(axes: str = 'xy')¶

Transform 3d probe to 2d probe.

Note: device_channel_indices is not copied.

Parameters¶

planestr: The plane on which the 2D probe is defined. ‘xy’, ‘yz’ ‘, xz’

to_3d(axes: str = 'xz')¶

Transform 2d probe to 3d probe.

Note: device_channel_indices is not copied.

Parameters¶

axesstr, default “xz”: The axes that define the plane on which the 2D probe is defined. ‘xy’, ‘yz’ ‘, xz’

to_dataframe(complete: bool = False) → pandas.DataFrame¶

Export the probe to a pandas dataframe

Parameters¶

completebool, default False: If True, export complete information about the probe, including the probe plane axis.

Returns¶

dfpandas.DataFrame: The dataframe representation of the probe

to_dict(array_as_list: bool = False) → dict¶

Create a dictionary of all necessary attributes. Useful for dumping and saving to json.

Parameters¶

array_as_listbool, default False: If True, arrays are converted to lists

Returns¶

ddict: The dictionary representation of the probe

to_image(values: np.array | list, pixel_size: float = 0.5, num_pixel: int | None = None, method: str = 'linear', xlims: tuple | None = None, ylims: tuple | None = None) → tuple[np.ndarray, tuple, tuple]¶

Generated a 2d (image) from a values vector with an interpolation into a grid mesh.

Parameters¶

values :: vector same size as contact number to be color plotted
pixel_size :: size of one pixel in micrometers
num_pixel :: alternative to pixel_size give pixel number of the image width
methodstr, default ‘linear’: One of the options: ‘linear’ or ‘nearest’ or ‘cubic’
xlimsOptional[tuple], default None: Force image xlims
ylimsOptional[tuple], default None: Force image ylims

Returns¶

image2d array: The generated image
xlimstuple: The x limits
ylimstuple: The y limits

to_numpy(complete: bool = False) → array¶

Export to a numpy vector (structured array). This vector handles all contact attributes.

Equivalent to the ‘to_dataframe()’ pandas function, but without pandas dependency.

Very useful to export/slice/attach to a recording.

Parameters¶

completebool, default False: If True, export complete information about the probe, including contact_plane_axes/si_units/device_channel_indices

returns¶

arrnumpy.array: With complex dtype

wiring_to_device(pathway: str, channel_offset: int = 0)¶

Automatically set device_channel_indices based on a pathway.

See probeinterface.get_available_pathways()

Parameters¶

pathwaystr: The pathway. E.g. ‘H32>RHD’
channel_offset: int, default 0: An optional offset to add to the device_channel_indices

ProbeGroup¶

class probeinterface.ProbeGroup¶

Class to handle a group of Probe objects and the global wiring to a device.

Optionally, it can handle the location of different probes.

auto_generate_contact_ids(*args, **kwargs)¶: Annotate all contacts with unique contact_id values.

Parameters¶

*args: will be forwarded to probeinterface.utils.generate_unique_ids **kwargs: will be forwarded to

probeinterface.utils.generate_unique_ids

auto_generate_probe_ids(*args, **kwargs)¶: Annotate all probes with unique probe_id values.

Parameters¶

*args: will be forwarded to probeinterface.utils.generate_unique_ids **kwargs: will be forwarded to

probeinterface.utils.generate_unique_ids

static from_dict(d)¶

Instantiate a ProbeGroup from a dictionary

Parameters¶

ddict: The dictionary representation of the probegroup

Returns¶

probegroupProbeGroup: The instantiated ProbeGroup object

get_contact_count()¶: Total number of channels.

get_global_contact_ids()¶: get all contact ids concatenated across probes

get_global_device_channel_indices()¶

return a numpy array vector with 2 columns (probe_index, device_channel_indices)

Note:: channel -1 means not connected

set_global_device_channel_indices(channels)¶: Set global indices for all probes

to_dict(array_as_list=False)¶

Create a dictionary of all necessary attributes.

Parameters¶

array_as_listbool, optional: If True, arrays are converted to lists, by default False

Returns¶

ddict: The dictionary representation of the probegroup

to_numpy(complete=False)¶: Export all probes into a numpy array.

Import/export to formats¶

Read/write probe info using a variety of formats:

probeinterface (.json)
PRB (.prb)
CSV (.csv)
mearec (.h5)
spikeglx (.meta)
ironclust/jrclust (.mat)
Neurodata Without Borders (.nwb)

probeinterface.io.read_probeinterface(file: str | Path) → ProbeGroup¶

Read probeinterface JSON-based format.

Parameters¶

file: Path or str: The file path

Returns¶

probegroup : ProbeGroup object

probeinterface.io.write_probeinterface(file: str | Path, probe_or_probegroup: Probe | ProbeGroup)¶

Write a probeinterface JSON file.

The format handles several probes in one file.

Parameters¶

filePath or str: The file path
probe_or_probegroupProbe or ProbeGroup object: If probe is given a probegroup is created anyway

probeinterface.io.read_prb(file: str | Path) → ProbeGroup¶

Read a PRB file and return a ProbeGroup object.

Since PRB does not handle contact shapes, contacts are set to be circle of 5um radius. Same for the probe shape, where an auto shape is created.

PRB format does not contain any information about the channel of the probe Only the channel index on device is given.

Parameters¶

filePath or str: The file path

Returns¶

probegroup : ProbeGroup object

probeinterface.io.write_prb(file: str, probegroup: ProbeGroup, total_nb_channels: int | None = None, radius: float | None = None, group_mode: str = 'by_probe')¶

Write ProbeGroup into a prb file.

This format handles:

multi Probe with channel group index key
channel positions with “geometry”
device_channel_indices with “channels “key

Note: much information is lost in the PRB format:

contact shape
shape
channel index

Note:

“total_nb_channels” is needed by spyking-circus
“radius” is needed by spyking-circus
“graph” is not handled

Parameters¶

file: str: The name of the file to be written
probegroup: ProbeGroup: The Probegroup to be used for writing
total_nb_channels: Optional[int], default None: ***to do
radius: Optional[float], default None: *** to do
group_mode: str: One of “by_probe” or “by_shank

probeinterface.io.read_csv(file: str | Path)¶: Return a 2 or 3 columns csv file with contact positions

probeinterface.io.write_csv(file, probe)¶: Write contact postions into a 2 or 3 columns csv file

probeinterface.io.read_spikeglx(file: str | Path) → Probe¶

Read probe position for the meta file generated by SpikeGLX

See http://billkarsh.github.io/SpikeGLX/#metadata-guides for implementation. The x_pitch/y_pitch/width are set automatically depending the NP version.

The shape is auto generated as a shank.

Now reads:

NP0.0 (=phase3A)
NP1.0 (=phase3B2)
NP2.0 with 4 shank
NP1.0-NHP

Parameters¶

filePath or str: The .meta file path

Returns¶

probe : Probe object

probeinterface.io.read_mearec(file: str | Path) → Probe¶

Read probe position, and contact shape from a MEArec file.

See https://mearec.readthedocs.io/en/latest/ and https://doi.org/10.1007/s12021-020-09467-7 for implementation.

Parameters¶

filePath or str: The file path

Returns¶

probe : Probe object

probeinterface.io.read_nwb(file)¶: Read probe position from an NWB file

Probe generators¶

This module contains useful helper functions for generating probes.

probeinterface.generator.generate_dummy_probe(elec_shapes: str = 'circle') → Probe¶

Generate a dummy probe with 3 columns and 32 contacts. Mainly used for testing and examples.

Parameters¶

elec_shapesstr, , by default ‘circle’: Shape of the electrodes with possibilities of (‘circle’, ‘square’, ‘rect’)

Returns¶

probeProbe: The generated probe

probeinterface.generator.generate_dummy_probe_group() → ProbeGroup¶

Generate a ProbeGroup with 2 probes. Mainly used for testing and examples.

Returns¶

probeProbe: The generated probe

probeinterface.generator.generate_tetrode(r: float = 10) → Probe¶

Generate a tetrode Probe. Parameters ———- r: float

The distance multiplier for the positions

Returns¶

probeProbe: The generated probe

probeinterface.generator.generate_multi_columns_probe(num_columns: int = 3, num_contact_per_column: int = 10, xpitch: float = 20, ypitch: float = 20, y_shift_per_column: np.array | list | None = None, contact_shapes: str = 'circle', contact_shape_params: dict = {'radius': 6}) → Probe¶

Generate a Probe with several columns.

Parameters¶

num_columnsint, by default 3: Number of columns
num_contact_per_columnint, by default 10: Number of contacts per column
xpitchfloat, by default 20: Pitch in x direction
ypitchfloat, by default 20: Pitch in y direction
y_shift_per_columnarray-like, optional: Shift in y direction per column. It needs to have the same length as num_columns, by default None
contact_shapesstr, by default ‘circle’: Shape of the contacts (‘circle’, ‘rect’, ‘square’)
contact_shape_paramsdict, default {‘radius’: 6}: Parameters for the shape. For circle: {“radius”: float} For square: {“width”: float} For rectangle: {“width”: float, “height”: float}

Returns¶

probeProbe: The generated probe

probeinterface.generator.generate_linear_probe(num_elec: int = 16, ypitch: float = 20, contact_shapes: str = 'circle', contact_shape_params: dict = {'radius': 6}) → Probe¶

Generate a one-column linear probe.

Parameters¶

num_elecint: Number of electrodes, by default 16
ypitchfloat: Pitch in y direction, by default 20
contact_shapesstr, default ‘circle’: Shape of the contacts (‘circle’, ‘rect’, ‘square’)
contact_shape_paramsdict, default {‘radius’: 6}: Parameters for the shape. For circle: {“radius”: float} For square: {“width”: float} For rectangle: {“width”: float, “height”: float}

Returns¶

probeProbe: The generated probe

Plotting¶

A simple implementation for plotting a Probe or ProbeGroup using matplotlib.

Depending on Probe.ndim, the plotting is done in 2D or 3D

probeinterface.plotting.plot_probe(probe, ax=None, contacts_colors=None, with_contact_id=False, with_device_index=False, text_on_contact=None, contacts_values=None, cmap='viridis', title=True, contacts_kargs={}, probe_shape_kwargs={}, xlims=None, ylims=None, zlims=None, show_channel_on_click=False)¶

Plot a Probe object. Generates a 2D or 3D axis, depending on Probe.ndim

Parameters¶

probeProbe: The probe object
axmatplotlib.axis, optional: The axis to plot the probe on. If None, an axis is created, by default None
contacts_colorsmatplotlib color, optional: The color of the contacts, by default None
with_contact_idbool, optional: If True, channel ids are displayed on top of the channels, by default False
with_device_indexbool, optional: If True, device channel indices are displayed on top of the channels, by default False
text_on_contact: None or list or numpy.array: Addintional text to plot on each contact
contacts_valuesnp.array, optional: Values to color the contacts with, by default None
cmapstr, optional: [description], by default ‘viridis’
titlebool, optional: If True, the axis title is set to the probe name, by default True
contacts_kargsdict, optional: Dict with kwargs for contacts (e.g. alpha, edgecolor, lw), by default {}
probe_shape_kwargsdict, optional: Dict with kwargs for probe shape (e.g. alpha, edgecolor, lw), by default {}
xlimstuple, optional: Limits for x dimension, by default None
ylimstuple, optional: Limits for y dimension, by default None
zlimstuple, optional: Limits for z dimension, by default None
show_channel_on_clickbool, optional: If True, the channel information is shown upon click, by default False

Returns¶

polyPolyCollection: The polygon collection for contacts
poly_contourPolyCollection: The polygon collection for the probe shape

probeinterface.plotting.plot_probe_group(probegroup, same_axes=True, **kargs)¶

Plot all probes from a ProbeGroup Can be in an existing set of axes or separate axes.

Parameters¶

probegroupProbeGroup: The ProbeGroup to plot
same_axesbool, optional: If True, the probes are plotted on the same axis, by default True

Library¶

Provides functions to download and cache pre-existing probe files from some manufacturers.

The library is hosted here: https://gin.g-node.org/spikeinterface/probeinterface_library

The gin platform enables contributions from users.

probeinterface.library.get_probe(manufacturer: str, probe_name: str, name: str | None = None) → Probe¶

Get probe from ProbeInterface library

Parameters¶

manufacturerstr: The probe manufacturer (e.g. ‘cambridgeneurotech’, ‘neuronexus’)
probe_namestr: The probe name
namestr or None: Optional name for the probe

Returns¶

probe : Probe object

API¶

Probe¶

Parameter¶

Parameters¶

Parameters¶

Returns¶

Parameters¶

Returns¶

Parameters¶

Returns¶

Parameters¶

Returns¶

Parameters¶

Parameters¶

Parameters¶

Parameters¶

Parameters¶

Parameters¶

Parameters¶

Parameters¶

Parameters¶

Parameters¶

Parameters¶

Returns¶

Parameters¶

Returns¶

Parameters¶

Returns¶

Parameters¶

returns¶

Parameters¶

ProbeGroup¶

Parameters¶

Parameters¶

Parameters¶

Returns¶

Parameters¶

Returns¶

Import/export to formats¶

Parameters¶

Returns¶

Parameters¶

Parameters¶

Returns¶

Parameters¶

Parameters¶

Returns¶

Parameters¶

Returns¶

Probe generators¶

Parameters¶

Returns¶

Returns¶

Returns¶

Parameters¶

Returns¶

Parameters¶

Returns¶

Plotting¶

Parameters¶

Returns¶

Parameters¶

Library¶

Parameters¶

Returns¶