eelbrain.plot.UTSStat¶
-
class
eelbrain.plot.
UTSStat
(y, x=None, xax=None, match=None, sub=None, ds=None, main=<function mean>, error='sem', pool_error=None, legend='upper right', labels=None, axtitle=True, xlabel=True, ylabel=True, xticklabels='bottom', yticklabels='left', invy=False, bottom=None, top=None, xdim=None, xlim=None, clip=None, colors=None, error_alpha=0.3, mask=None, clusters=None, pmax=0.05, ptrend=0.1, **kwargs)¶ Plot statistics for a one-dimensional NDVar
- Parameters
y (1d-NDVar) – Dependent variable (one-dimensional NDVar).
x (categorial) – Model: specification of conditions which should be plotted separately.
xax (categorial) – Make separate axes for each category in this categorial model.
match (categorial) – Identifier for repeated measures data.
sub (index array) – Only use a subset of the data provided.
ds (
Optional
[Dataset
]) – If a Dataset is specified, all data-objects can be specified as names of Dataset variables.main (func | None) – Measure for the central tendency (function that takes an
axis
argument). The default is numpy.mean.error (
str
) – Measure of variability to plot. Examples:sem
: Standard error of the mean;2sem
: 2 standard error of the mean;ci
: 95% confidence interval;99%ci
: 99% confidence interval.all
: Show all traces.none
: No variability indication.pool_error (
Optional
[bool
]) – Pool the errors for the estimate of variability (default is True for related measures designs, False otherwise). See Loftus & Masson (1994).legend (
Union
[str
,int
,bool
]) – Matplotlib figure legend location argument or ‘fig’ to plot the legend in a separate figure.labels (dict) – Alternative labels for legend as
{cell: label}
dictionary (preserves order).axtitle (
Union
[bool
,Sequence
[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. Useint
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. Useint
for a single axis, a sequence ofint
for multiple specific axes, or one of'left' | 'bottom' | 'all' | 'none'
.invy (
bool
) – Invert the y axis (ifbottom
and/ortop
are specified explicitly they take precedence; an inverted y-axis can also be produced by specifyingbottom > top
).bottom (
Optional
[float
]) – The lower end of the plot’s y axis.xdim (
Optional
[str
]) – dimension for the x-axis (default is ‘time’)xlim (
Union
[float
,Tuple
[float
,float
],None
]) – Initial x-axis view limits as(left, right)
tuple or aslength
scalar (default is the full x-axis in the data).clip (
Optional
[bool
]) – Clip lines outside of axes (the default depends on whetherframe
is closed or open).color (matplotlib color) – Color if just a single category of data is plotted.
colors (
Optional
[Dict
[Union
[str
,Tuple
[str
, …]],Any
]]) – Colors for the plots if multiple categories of data are plotted. str: A colormap name; Cells ofx
are mapped onto the colormap in regular intervals. list: A list of colors in the same sequence asx.cells
. dict: A dictionary mapping each cell inx
to a color. Colors are specified as matplotlib compatible color arguments.error_alpha (
float
) – Alpha of the error plot (default 0.3).mask (NDVar | {cell: NDVar}) – Mask certain time points.
clusters (
Optional
[Dataset
]) – Clusters to add to the plots. The clusters should be provided as Dataset, as stored in test results’clusters
.pmax (
float
) – Maximum p-value of clusters to plot as solid.ptrend (
float
) – Maximum p-value of clusters to plot as trend.tight – Use matplotlib’s tight_layout to expand all axes to fill the figure (default True)
title – Figure title.
.. – Also accepts General layout parameters.
Notes
- Navigation:
↑
: scroll up↓
: scroll downr
: y-axis zoom in (reduce y-axis range)c
: y-axis zoom out (increase y-axis range)
Methods¶
|
Draw a horizontal line on one or more axes |
|
Draw a horizontal bar on one or more axes |
|
Draw a vertical line on one or more axes |
|
Draw a vertical bar on one or more axes |
|
Draw vertical bars over axes |
|
Close the figure. |
|
(Re-)draw the figure (after making manual changes). |
|
Draw crosshairs under the cursor |
|
|
|
|
|
Create FMTXT Image from the figure |
|
Plot the legend (or remove it from the figure). |
|
Short-cut for Matplotlib’s |
|
Save the legend as image file |
|
Add clusters from a cluster test to the plot (as shaded area). |
|
Set the figure window title |
|
Set the label for the x-axis |
|
Set the x-axis limits for all axes |
|
Rotate every x-axis tick-label by an angle (counterclockwise, in degrees) |
|
Set the label for the y-axis |
|
Set the y-axis limits |