plot_tools

A set of convenience functions used for producing plots in dabest.

sankeydiag

 sankeydiag (data:pandas.core.frame.DataFrame, xvar:str, yvar:str,
             left_idx:str, right_idx:str, leftLabels:list=None,
             rightLabels:list=None, palette:Union[str,dict]=None, ax=None,
             one_sankey:bool=False, width:float=0.4,
             rightColor:bool=False, align:str='center', alpha:float=0.65,
             **kwargs)

Read in melted pd.DataFrame, and draw multiple sankey diagram on a single axes using the value in column yvar according to the value in column xvar left_idx in the column xvar is on the left side of each sankey diagram right_idx in the column xvar is on the right side of each sankey diagram

	Type	Default	Details
data	pd.DataFrame
xvar	str		x column to be plotted.
yvar	str		y column to be plotted.
left_idx	str		the value in column xvar that is on the left side of each sankey diagram
right_idx	str		the value in column xvar that is on the right side of each sankey diagram, if len(left_idx) == 1, it will be broadcasted to the same length as right_idx, otherwise it should have the same length as right_idx
leftLabels	list	None	labels for the left side of the diagram. The diagram will be sorted by these labels.
rightLabels	list	None	labels for the right side of the diagram. The diagram will be sorted by these labels.
palette	str \| dict	None
ax	NoneType	None	matplotlib axes to be drawn on
one_sankey	bool	False	determined by the driver function on plotter.py, if True, draw the sankey diagram across the whole raw data axes
width	float	0.4	the width of each sankey diagram
rightColor	bool	False	if True, each strip of the diagram will be colored according to the corresponding left labels
align	str	center	the alignment of each sankey diagram, can be ‘center’ or ‘left’
alpha	float	0.65	the transparency of each strip
kwargs

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single_sankey

 single_sankey (left:<built-infunctionarray>, right:<built-
                infunctionarray>, xpos:float=0, leftWeight:<built-
                infunctionarray>=None, rightWeight:<built-
                infunctionarray>=None, colorDict:dict=None,
                leftLabels:list=None, rightLabels:list=None, ax=None,
                width=0.5, alpha=0.65, bar_width=0.2,
                rightColor:bool=False, align:bool='center')

Make a single Sankey diagram showing proportion flow from left to right Original code from: https://github.com/anazalea/pySankey Changes are added to normalize each diagram’s height to be 1

	Type	Default	Details
left	np.array		data on the left of the diagram
right	np.array		data on the right of the diagram, len(left) == len(right)
xpos	float	0	the starting point on the x-axis
leftWeight	np.array	None	weights for the left labels, if None, all weights are 1
rightWeight	np.array	None	weights for the right labels, if None, all weights are corresponding leftWeight
colorDict	dict	None	input format: {‘label’: ‘color’}
leftLabels	list	None	labels for the left side of the diagram. The diagram will be sorted by these labels.
rightLabels	list	None	labels for the right side of the diagram. The diagram will be sorted by these labels.
ax	NoneType	None	matplotlib axes to be drawn on
width	float	0.5
alpha	float	0.65
bar_width	float	0.2
rightColor	bool	False	if True, each strip of the diagram will be colored according to the corresponding left labels
align	bool	center	if ‘center’, the diagram will be centered on each xtick, if ‘edge’, the diagram will be aligned with the left edge of each xtick

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normalize_dict

 normalize_dict (nested_dict, target)

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check_data_matches_labels

 check_data_matches_labels (labels, data, side:str)

Function to check that the labels and data match in the sankey diagram. And enforce labels and data to be lists. Raises an exception if the labels and data do not match.

	Type	Details
labels		list of input labels
data		Pandas Series of input data
side	str	‘left’ or ‘right’ on the sankey diagram

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error_bar

 error_bar (data:pandas.core.frame.DataFrame, x:str, y:str,
            type:str='mean_sd', offset:float=0.2, ax=None,
            line_color='black', gap_width_percent=1, pos:list=[0, 1],
            method:str='gapped_lines', **kwargs:dict)

Function to plot the standard deviations as vertical errorbars. The mean is a gap defined by negative space.

This function combines the functionality of gapped_lines(), proportional_error_bar(), and sankey_error_bar().

	Type	Default	Details
data	pd.DataFrame		This DataFrame should be in ‘long’ format.
x	str		x column to be plotted.
y	str		y column to be plotted.
type	str	mean_sd	Choose from [‘mean_sd’, ‘median_quartiles’]. Plots the summary statistics for each group. If ‘mean_sd’, then the mean and standard deviation of each group is plotted as a gapped line. If ‘median_quantiles’, then the median and 25th and 75th percentiles of each group is plotted instead.
offset	float	0.2	Give a single float (that will be used as the x-offset of all gapped lines), or an iterable containing the list of x-offsets.
ax	NoneType	None	If a matplotlib Axes object is specified, the gapped lines will be plotted in order on this axes. If None, the current axes (plt.gca()) is used.
line_color	str	black
gap_width_percent	int	1
pos	list	[0, 1]	The positions of the error bars for the sankey_error_bar method.
method	str	gapped_lines	The method to use for drawing the error bars. Options are: ‘gapped_lines’, ‘proportional_error_bar’, and ‘sankey_error_bar’.
kwargs	dict

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get_swarm_spans

 get_swarm_spans (coll)

Given a matplotlib Collection, will obtain the x and y spans for the collection. Will return None if this fails.

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halfviolin

 halfviolin (v, half='right', fill_color='k', alpha=1, line_color='k',
             line_width=0)