aigct.plot_util

Functions

barchart(df, x, y[, x_label, y_label, ci, filename, ...])
create_feature_palette(→ dict)
get_colors(→ list)
heatmap(df[, y_column, x_column, value_column, ...])	Plot a heatmap using seaborn.

Module Contents

aigct.plot_util.barchart(df: pandas.DataFrame, x: str, y: str, x_label: str = '', y_label: str = '', ci: pandas.DataFrame = None, filename: str = None, hatch: str = None, edgecolor=None, palette=None, errorbar=None, estimator: str = 'mean', title: str = '', title_fontsize: int = 20, y_label_fontsize: int = 15, x_label_fontsize: int = 15, y_tick_label_size: int = 15, x_tick_label_size: int = 15, xtick_rotation: int = None, xtick_rotation_mode: str = None, file_dpi: int = 300, bbox_inches: str = 'tight')

aigct.plot_util.create_feature_palette(values: list) → dict

aigct.plot_util.get_colors(num_colors: int) → list

aigct.plot_util.heatmap(df: pandas.DataFrame, y_column: str = None, x_column: str = None, value_column: str = None, x_label: str = '', y_label: str = '', title: str = '', cmap: str = 'viridis', annot: bool = True, fmt: str = '.2f', linewidths: float = 0.5, title_fontsize: int = 20, label_fontsize: int = 15, tick_fontsize: int = 12, annot_fontsize: int = 10, figsize: tuple = (10, 8), filename: str = None, vmin: float = None, vmax: float = None, cbar: bool = True, cbar_kws: dict = None, square: bool = False, mask: pandas.DataFrame = None, file_dpi: int = 300, bbox_inches: str = 'tight')

Plot a heatmap using seaborn.

Parameters

dfpd.DataFrame

DataFrame to plot as heatmap

y_columnstr, optional

Column to use for y-axis categories. If provided along with x_column and value_column, the function will pivot the data before plotting.

x_columnstr, optional

Column to use for x-axis categories. If provided along with y_column and value_column, the function will pivot the data before plotting.

value_columnstr, optional

Column containing values to plot. If provided along with x_column and y_column, the function will pivot the data before plotting.

x_labelstr, optional

Label for x-axis

y_labelstr, optional

Label for y-axis

titlestr, optional

Title of the plot

cmapstr, optional

Colormap to use

annotbool, optional

Whether to annotate cells with values

fmtstr, optional

Format string for annotations

linewidthsfloat, optional

Width of lines between cells

title_fontsizeint, optional

Font size for title

label_fontsizeint, optional

Font size for axis labels

tick_fontsizeint, optional

Font size for tick labels

annot_fontsizeint, optional

Font size for annotations

figsizetuple, optional

Figure size (width, height) in inches

filenamestr, optional

If provided, save figure to this file

vminfloat, optional

Minimum value for colormap scaling

vmaxfloat, optional

Maximum value for colormap scaling

cbarbool, optional

Whether to draw a colorbar

cbar_kwsdict, optional

Additional arguments for colorbar

squarebool, optional

Whether to make cells square-shaped

maskpd.DataFrame, optional

Boolean DataFrame of same shape as df, True values will not be plotted

file_dpiint, optional

DPI for saved figure

bbox_inchesstr, optional

Bounding box in inches for saved figure

Returns

matplotlib.axes.Axes

The matplotlib axes containing the plot