eelbrain.plot.Regression
- class eelbrain.plot.Regression(y, x, cat=None, match=None, sub=None, data=None, xlabel=True, ylabel=True, alpha=0.2, legend=None, labels=None, c=('#009CFF', '#FF7D26', '#54AF3A', '#FE58C6', '#20F2C3'), **kwargs)
Plot the regression of
y
onx
- Parameters
cat (Union[Factor, Interaction, NestedEffect, str]) – Plot the regression separately for different categories.
match (Union[Factor, Interaction, NestedEffect, str]) – Match cases for a repeated measures design.
data (Dataset) – If a Dataset is specified, all data-objects can be specified as names of Dataset variables
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.
alpha (float) – alpha for individual data points (to control visualization of overlap)
legend (Optional[Union[str, int, Tuple[float, float], 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).c (color | sequence of colors) – Colors.
tight (bool) – Use matplotlib’s tight_layout to expand all axes to fill the figure (default True)
... – Also accepts General layout parameters.
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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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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Create FMTXT Image from the figure |
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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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Set the figure window title |
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Set the label for the x-axis |
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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 |