eelbrain.plot.Butterfly
- class eelbrain.plot.Butterfly(y, xax=None, sensors=None, axtitle=True, xlabel=True, ylabel=True, xticklabels='bottom', yticklabels='left', color=None, linewidth=None, data=None, sub=None, x='time', vmax=None, vmin=None, xlim=None, clip=None, **kwargs)
Butterfly plot for NDVars
- Parameters
y ((list of) NDVar) – Data to plot.
xax (None | categorial) – Create a separate plot for each cell in this model.
sensors (None or list of sensor IDs) – sensors to plot (
None
= all)axtitle (bool | sequence of str) – Title for the individual axes. The default is to show the names of the epochs, but only if multiple axes are plotted.
xlabel (Union[bool, str]) – X-axis label. By default the label is inferred from the data.
ylabel (Union[bool, str]) – Y-axis label. By default the label is inferred from the data.
xticklabels (Union[str, int, Sequence[int]]) – Specify which axes should be annotated with x-axis tick labels. Use
int
for a single axis, a sequence ofint
for multiple specific axes, or one of'left' | 'bottom' | 'all' | 'none'
.yticklabels (Union[str, int, Sequence[int]]) – Specify which axes should be annotated with y-axis tick labels. Use
int
for a single axis, a sequence ofint
for multiple specific axes, or one of'left' | 'bottom' | 'all' | 'none'
.color (matplotlib color | dict) – Either a color for all lines, or a dictionary mapping levels of the line dimension to colors. The default is to use
NDVar.info['color']
if available, otherwise the matplotlib default color alternation. Usecolor=True
to use the matplotlib default.linewidth (scalar) – Linewidth for plots (defult is to use
matplotlib.rcParams
).data (Dataset) – If a Dataset is provided,
epochs
andxax
can be specified as strings.sub (str | array) – Specify a subset of the data.
x (str) – Dimension to plot on the x-axis (default ‘time’).
vmax (scalar) – Top of the y axis (default depends on data).
vmin (scalar) – Bottom of the y axis (default depends on data).
xlim (scalar | (scalar, scalar)) – Initial x-axis view limits as
(left, right)
tuple or aslength
scalar (default is the full x-axis in the data).clip (bool) – Clip lines outside of axes (the default depends on whether
frame
is closed or open).tight (bool) – Use matplotlib’s tight_layout to expand all axes to fill the figure (default True)
... – Also accepts General layout parameters.
Notes
- Navigation:
↑
: scroll up↓
: scroll down←
: scroll left→
: scroll righthome
: scroll to beginningend
: scroll to endf
: x-axis zoom in (reduce x axis range)d
: x-axis zoom out (increase x axis range)r
: y-axis zoom in (reduce y-axis range)c
: y-axis zoom out (increase y-axis range)
- Keys available for sensor data:
t
: open aTopomap
plot for the time point under the mouse pointer.T
: open a largerTopomap
plot with visible sensor names for the time point under the mouse pointer.
Methods
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Draw a horizontal line on one or more axes |
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Draw a horizontal bar on one or more axes |
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Draw a vertical line on one or more axes |
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Draw a vertical bar on one or more axes |
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Draw vertical bars over axes |
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Close the figure. |
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(Re-)draw the figure (after making manual changes). |
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Draw crosshairs under the cursor |
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Draw the outline of the figure |
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Retrieve the current time |
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Create FMTXT Image from the figure |
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Link the time axis of this figure with another figure |
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Cycle through the time axis |
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Plot the legend (or remove it from the figure). |
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Short-cut for Matplotlib's |
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Save the legend as image file |
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Save the figure with moving time axis as movie |
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Set the figure window title |
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Set the time point to display |
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Set the label for the x-axis |
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Set the x-axis limits for all axes |
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Rotate every x-axis tick-label by an angle (counterclockwise, in degrees) |
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Set the label for the y-axis |
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Set the y-axis limits |