ehrapy.plot.scatter

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ehrapy.plot.scatter#

ehrapy.plot.scatter(edata, x=None, y=None, *, color=None, use_raw=None, layers=None, sort_order=True, alpha=None, basis=None, groups=None, components=None, projection='2d', legend_loc='right margin', legend_fontsize=None, legend_fontweight=None, legend_fontoutline=None, color_map=None, palette=None, frameon=None, right_margin=None, left_margin=None, size=None, title=None, show=None, save=None, ax=None)[source]#

Scatter plot along observations or variables axes.

Color the plot using annotations of observations (.obs), variables (.var) or features (.var_names).

Parameters:

  • edata (EHRData) – Central data object.

  • x (str | None, default: None) – x coordinate

  • y (str | None, default: None) – y coordinate

  • color (str | None, default: None) – Keys for annotations of observations/patients or features, or a hex color specification, e.g., ‘ann1’, ‘#fe57a1’, or [‘ann1’, ‘ann2’].

  • use_raw (bool | None, default: None) – Whether to use raw attribute of edata. Defaults to True if .raw is present.

  • layers (str | Collection[str] | None, default: None) – Use the layers attribute of edata if present: specify the layer for x, y and color. If layers is a string, then it is expanded to (layers, layers, layers).

  • basis (Literal['pca', 'tsne', 'umap', 'diffmap', 'draw_graph_fr'] | None, default: None) – String that denotes a plotting tool that computed coordinates.

  • sort_order (bool, default: True) – For continuous annotations used as color parameter, plot data points with higher values on top of others.

  • groups (str | Iterable[str] | None, default: None) – Restrict to a few categories in categorical observation annotation. The default is not to restrict to any groups.

  • components (str | Collection[str] | None, default: None) – For instance, [‘1,2’, ‘2,3’]. To plot all available components use components=’all’.

  • projection (Literal['2d', '3d'], default: '2d') – Projection of plot (default: ‘2d’).

  • legend_loc (str, default: 'right margin') – Location of legend, either ‘on data’, ‘right margin’ or a valid keyword for the loc parameter of Legend.

  • legend_fontsize (int | float | Literal['xx-small', 'x-small', 'small', 'medium', 'large', 'x-large', 'xx-large'] | None, default: None) – Numeric size in pt or string describing the size. See set_fontsize().

  • legend_fontweight (int | Literal['light', 'normal', 'medium', 'semibold', 'bold', 'heavy', 'black'] | None, default: None) – Legend font weight. A numeric value in range 0-1000 or a string. Defaults to ‘bold’ if legend_loc == ‘on data’, otherwise to ‘normal’. See set_fontweight().

  • legend_fontoutline (float | None, default: None) – Line width of the legend font outline in pt. Draws a white outline using the path effect withStroke.

  • size (int | float | None, default: None) – Point size. If None, is automatically computed as 120000 / n_features.Can be a sequence containing the size for each observation. The order should be the same as in edata.obs.

  • color_map (str | Colormap | None, default: None) – Color map to use for continous variables. Can be a name or a Colormap instance (e.g. “magma”, “viridis” or mpl.cm.cividis), see get_cmap(). If None, the value of mpl.rcParams[“image.cmap”] is used. The default color_map can be set using set_figure_params().

  • palette (Cycler | ListedColormap | str | tuple[float, ...] | Sequence[str | tuple[float, ...]] | None, default: None) – Colors to use for plotting categorical annotation groups. The palette can be a valid ListedColormap name (‘Set2’, ‘tab20’, …), a Cycler object, a dict mapping categories to colors, or a sequence of colors. Colors must be valid to matplotlib. (see is_color_like()). If None, mpl.rcParams[“axes.prop_cycle”] is used unless the categorical variable already has colors stored in edata.uns[“{{var}}_colors”]. If provided, values of edata.uns[“{{var}}_colors”] will be set.

  • na_color – Color to use for null or masked values. Can be anything matplotlib accepts as a color. Used for all points if color=None.

  • na_in_legend – If there are missing values, whether they get an entry in the legend. Currently only implemented for categorical legends.

  • frameon (bool | None, default: None) – Draw a frame around the scatter plot. Defaults to value set in set_figure_params() (default: True).

  • title (str | None, default: None) – Provide title for panels either as string or list of strings, e.g. [‘title1’, ‘title2’, …].

  • show (bool | None, default: None) – Whether to display the figure or return axis.

  • save (str | bool | None, default: None) – If True or a str, save the figure. A string is appended to the default filename. Infer the filetype if ending on {‘.pdf’, ‘.png’, ‘.svg’}.

  • ax (Axes | None, default: None) – A matplotlib axes object. Only works if plotting a single component.

Example

import ehrdata as ed
import ehrapy as ep

edata = ed.dt.mimic_2()
ep.pp.knn_impute(edata)
ep.pp.log_norm(edata, offset=1)
ep.pp.neighbors(edata)
ep.pl.scatter(edata, x="age", y="icu_los_day", color="icu_los_day")
Preview:
../../_images/scatter.png
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