Projection vector.
A basic class to proj a meaningful print for projection vectors.
Warning
This class is generally not meant to be instantiated
directly, use compute_proj_*
functions instead.
Methods
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True if the dictionary has the specified key, else False. |
x.__getitem__(y) <==> x[y] |
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Implement iter(self). |
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Return len(self). |
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Create a new dictionary with keys from iterable and values set to value. |
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Return the value for key if key is in the dictionary, else default. |
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Plot topographic maps of SSP projections. |
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If key is not found, d is returned if given, otherwise KeyError is raised |
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Remove and return a (key, value) pair as a 2-tuple. |
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Insert key with a value of default if key is not in the dictionary. |
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If E is present and has a .keys() method, then does: for k in E: D[k] = E[k] If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v In either case, this is followed by: for k in F: D[k] = F[k] |
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True if the dictionary has the specified key, else False.
x.__getitem__(y) <==> x[y]
Implement iter(self).
Return len(self).
Create a new dictionary with keys from iterable and values set to value.
Return the value for key if key is in the dictionary, else default.
Plot topographic maps of SSP projections.
mne.Info
The mne.Info
object with information about the sensors and methods of measurement. Used to determine the layout.
None
Colormap to use. If tuple, the first value indicates the colormap to
use and the second value is a boolean defining interactivity. In
interactive mode (only works if colorbar=True
) the colors are
adjustable by clicking and dragging the colorbar with left and right
mouse button. Left mouse button moves the scale up and down and right
mouse button adjusts the range. Hitting space bar resets the range. Up
and down arrows can be used to change the colormap. If None (default),
‘Reds’ is used for all positive data, otherwise defaults to ‘RdBu_r’.
If ‘interactive’, translates to (None, True).
str
Add markers for sensor locations to the plot. Accepts matplotlib plot format string (e.g., ‘r+’ for red plusses). If True, a circle will be used (via .add_artist). Defaults to True.
Plot a colorbar.
int
The resolution of the topomap image (n pixels along each side).
Side length of the topomaps in inches (only applies when plotting multiple topomaps at a time).
Show figure if True.
dict
| None
The outlines to be drawn. If ‘head’, the default head scheme will be drawn. If ‘skirt’ the head scheme will be drawn, but sensors are allowed to be plotted outside of the head circle. If dict, each key refers to a tuple of x and y positions, the values in ‘mask_pos’ will serve as image mask. Alternatively, a matplotlib patch object can be passed for advanced masking options, either directly or as a function that returns patches (required for multi-axis plots). If None, nothing will be drawn. Defaults to ‘head’.
int
| array
of float
The number of contour lines to draw. If 0, no contours will be drawn. When an integer, matplotlib ticker locator is used to find suitable values for the contour thresholds (may sometimes be inaccurate, use array for accuracy). If an array, the values represent the levels for the contours. Defaults to 6.
str
The image interpolation to be used. Options are 'cubic'
(default)
to use scipy.interpolate.CloughTocher2DInterpolator
,
'nearest'
to use scipy.spatial.Voronoi
or
'linear'
to use scipy.interpolate.LinearNDInterpolator
.
Axes
| list
| None
The axes to plot to. If list, the list must be a list of Axes of the same length as the number of projectors. If instance of Axes, there must be only one projector. Defaults to None.
tuple
of length 2 | ‘joint’Colormap limits to use. If tuple
, specifies the lower and
upper bounds of the colormap (in that order); providing None
for
either of these will set the corresponding boundary at the min/max of
the data (separately for each projector). The keyword value 'joint'
will compute the colormap limits jointly across all provided
projectors of the same channel type, using the min/max of the projector
data. If vlim is 'joint'
, info
must not be None
. Defaults
to (None, None)
.
float
| array-like | instance of ConductorModel
| None
| ‘auto’ | ‘eeglab’The sphere parameters to use for the head outline. Can be array-like of
shape (4,) to give the X/Y/Z origin and radius in meters, or a single float
to give just the radius (origin assumed 0, 0, 0). Can also be an instance
of a spherical ConductorModel
to use the origin and
radius from that object. If 'auto'
the sphere is fit to digitization
points. If 'eeglab'
the head circle is defined by EEG electrodes
'Fpz'
, 'Oz'
, 'T7'
, and 'T8'
(if 'Fpz'
is not present,
it will be approximated from the coordinates of 'Oz'
). None
(the
default) is equivalent to 'auto'
when enough extra digitization points
are available, and (0, 0, 0, 0.095) otherwise. Currently the head radius
does not affect plotting.
New in version 0.20.
Changed in version 1.1: Added 'eeglab'
option.
float
| ‘mean’Value to extrapolate to on the topomap borders. If 'mean'
(default),
then each extrapolated point has the average value of its neighbours.
New in version 0.20.
Figure
Figure distributing one image per channel across sensor topography.
Notes
New in version 0.15.0.
If key is not found, d is returned if given, otherwise KeyError is raised
Remove and return a (key, value) pair as a 2-tuple.
Pairs are returned in LIFO (last-in, first-out) order. Raises KeyError if the dict is empty.
Insert key with a value of default if key is not in the dictionary.
Return the value for key if key is in the dictionary, else default.
If E is present and has a .keys() method, then does: for k in E: D[k] = E[k] If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v In either case, this is followed by: for k in F: D[k] = F[k]
mne.Projection
#Background on projectors and projections