trifusion.base.plotter module¶

trifusion.base.plotter.bar_plot(*args, **kwargs)[source]¶

Creates a bar plot from a data array.

If a multi-dimensional array is provided, it will create a stacked bar plot.

Parameters:

data : numpy.array Single or multi-dimensional array with plot data. labels : list List of xtick labels. Should have the same length as data. title : str Title of the plot. ax_names : list List with the labels for the x-axis (first element) and y-axis (second element). lgd_list : list For categorical plots, provide the label of each category. reverse_x : bool If True, reverse the x-axis orientation. table_header : list List with the header of the table object. Each element represents a column.

Returns:

fig : matplotlib.Figure Figure object of the plot. lgd : matplotlib.Legend Legend object of the plot. table : list Table data in list format. Each item in the list corresponds to a table row.

trifusion.base.plotter.box_plot(*args, **kwargs)[source]¶

Creates box (whisker) plot.

Parameters:	data : numpy.array Single or multi-dimensional array with plot data. labels : list List of xtick labels. Should have the same length as data. title : str Title of the plot. ax_names : list List with the labels for the x-axis (first element) and y-axis (second element).
Returns:	fig : matplotlib.pyplot.Figure Figure object of the plot. _ : None Placeholder for the legend object. Not used here but assures consistency across other plotting methods. table : list Table data in list format. Each item in the list corresponds to a table row.

trifusion.base.plotter.histogram_plot(*args, **kwargs)[source]¶

Creates an histogram from data.

Parameters:	data : numpy.array Array with plot data. title : str Title of the plot. ax_names : list List with the labels for the x-axis (first element) and y-axis (second element). table_header : list List with the header of the table object. Each element represents a column. real_bin_num : bool If True, then the table data will be forced to be in real numbers.
Returns:	fig : matplotlib.Figure Figure object of the plot. lgd : matplotlib.Legend Legend object of the plot. table : list Table data in list format. Each item in the list corresponds to a table row.

trifusion.base.plotter.histogram_smooth(data, ax_names=None, table_header=None, title=None, legend=None)[source]¶

Creates a smooth histogram-like plot.

Creates a smooth line plot with colored areas with the same distribution as an histogram. It supports a multi-dimensional array, in which case each array will be used to create vertically stacked subplots.

Parameters:	data : numpy.array Array with plot data. ax_names : list List with the labels for the x-axis (first element) and y-axis (second element). table_header : list List with the header of the table object. Each element represents a column. title : str Title of the plot. legend : list If using a multi-dimensional array, provide the name of each subplot.
Returns:	fig : matplotlib.pyplot.Figure Figure object of the plot. _ : None Placeholder for the legend object. Not used here but assures consistency across other plotting methods. table : list Table data in list format. Each item in the list corresponds to a table row.

trifusion.base.plotter.interpolation_plot(*args, **kwargs)[source]¶

Creates black and white interpolation plot

Creates a black and white interpolation plot from data, which must consist of a 0/1 matrix for absence/presence of taxa in genes.

Parameters:	data : numpy.array Single or multi-dimensional array with plot data. title : str Title of the plot. ax_names : list List with the labels for the x-axis (first element) and y-axis (second element).
Returns:	fig : matplotlib.pyplot.Figure Figure object of the plot. _ : None Placeholder for the legend object. Not used here but assures consistency across other plotting methods. _ : None Placeholder for the table header list. Not used here but assures consistency across other plotting methods.

trifusion.base.plotter.multi_bar_plot(*args, **kwargs)[source]¶

Creates a multiple bar plot.

Creates a multiple bar plot from a multi-dimensional array. The bar plots from each array will be grouped and displayed side by side.

Parameters:	data : numpy.array Single or multi-dimensional array. labels : list List of xtick labels. Should have the same length as data. title : str Title of the plot. lgd_list : list For categorical plots, provide the label of each category. ax_names : list List with the labels for the x-axis (first element) and y-axis (second element).
Returns:	fig : matplotlib.Figure Figure object of the plot. lgd : matplotlib.Legend Legend object of the plot. table : list Table data in list format. Each item in the list corresponds to a table row.

trifusion.base.plotter.outlier_densisty_dist(*args, **kwargs)[source]¶

Creates a density distribution for outlier plots.

Parameters:	data : numpy.array 1D array containing data points. outliers : numpy.array 1D array containing the outliers. outliers_labels : list or numpy.array 1D array containing the labels for each outlier. title : str Title of the plot.
Returns:	fig : matplotlib.Figure Figure object of the plot. lgd : matplotlib.Legend Legend object of the plot. table : list Table data in list format. Each item in the list corresponds to a table row.

trifusion.base.plotter.scatter_plot(*args, **kwargs)[source]¶

Generates a scatter plot from a 2D array.

Builds a scatter plot from a 2D array. Also calculates the correlation coefficient if requested by the correlation argument.

Parameters:

data : numpy.array 2D array containing the x and y data points. correlation : bool If True, the spearman’s rank correlation coefficient is calculated and added to the plot as an annotation ax_names : list List with the labels for the x-axis (first element) and y-axis (second element). table_header : list List with the header of the table object. Each element represents a column. title : str Title of the plot.

Returns:

fig : matplotlib.pyplot.Figure Figure object of the plot. _ : None Placeholder for the legend object. Not used here but assures consistency across other plotting methods. table : list Table data in list format. Each item in the list corresponds to a table row.

trifusion.base.plotter.set_props(func)[source]¶

Decorator used to set general plot attributes

This decorator is use to automatically set several plot properties based on the arguments provided to the plotting functions. In this way, there is no need to write repetitive code in each function. The accepted arguments are:

• ax_names : list. Axis names. First element is x-axis label, second is y-axis label
• title : str. Title of the plot

trifusion.base.plotter.sliding_window(*args, **kwargs)[source]¶

Creates a sliding window plot.

Parameters:	data : numpy.array Array with plot data. window_size : int Length of window size for sliding window. table_header : list List with the header of the table object. Each element represents a column. title : str Title of the plot. ax_names : list List with the labels for the x-axis (first element) and y-axis (second element).
Returns:	fig : matplotlib.pyplot.Figure Figure object of the plot. _ : None Placeholder for the legend object. Not used here but assures consistency across other plotting methods. table : list Table data in list format. Each item in the list corresponds to a table row.

trifusion.base.plotter.stacked_bar_plot(*args, **kwargs)[source]¶

Creates a stacked bar plot.

Parameters:

data : numpy.array Multi-dimensional array. labels : list List of xtick labels. Should have the same length as data. title : str Title of the plot. table_header : list List with the header of the table object. Each element represents a column. title : str Title of the plot. ax_names : list List with the labels for the x-axis (first element) and y-axis (second element). normalize : bool If True, values of the data array will be normalized by the normalize_factor normalize_factor : int or float Number used to normalize values of the data array.

Returns:

fig : matplotlib.Figure Figure object of the plot. lgd : matplotlib.Legend Legend object of the plot. table : list Table data in list format. Each item in the list corresponds to a table row.

trifusion.base.plotter.triangular_heat(*args, **kwargs)[source]¶

Creates a triangular heatmap plot.

Parameters:	data : numpy.array Triangular array with plot data. labels : list List of xtick labels. Should have the same length as data. title : str Title of the plot. color_label : str Label for colorbar.
Returns:	fig : matplotlib.pyplot.Figure Figure object of the plot. _ : None Placeholder for the legend object. Not used here but assures consistency across other plotting methods. table : list Table data in list format. Each item in the list corresponds to a table row.