neuralib.plot.tools

class neuralib.plot.tools.AnchoredScaleBar[source]
__init__(transform, sizex=0, sizey=0, labelx=None, labely=None, loc=4, pad=0.1, borderpad=0.1, sep=2, color='black', lw=1.5, color_txt='black', prop=None, **kwargs)[source]

Set of scale bars that match the size of the ticks of the plot.

Draws a horizontal and/or vertical bar with the size in data coordinates of the give axes. A label will be drawn underneath (center-aligned).

Parameters:

  • transform (Transform) – Matplotlib Transform The coordinate frame (typically axes.transData)

  • sizex (float) – Width of x bar, in data units. 0 to omit.

  • sizey (float) – Width of y bar, in data units. 0 to omit.

  • labelx (str | None) – Labels for x bars; None to omit

  • labely (str | None) – Labels for y bars; None to omit

  • loc (int | str) – Position in containing axes.

  • pad (float) – Padding, in fraction of the legend font size (or prop).

  • borderpad

  • sep (int) – Separation between labels and bars in points.

  • color (str) – Bars color

  • lw (float) – Bars width

  • color_txt (str) – color

  • prop – Font property.

  • kwargs – additional arguments passed to base class constructor

set(*, agg_filter=<UNSET>, alpha=<UNSET>, animated=<UNSET>, bbox_to_anchor=<UNSET>, child=<UNSET>, clip_box=<UNSET>, clip_on=<UNSET>, clip_path=<UNSET>, gid=<UNSET>, height=<UNSET>, in_layout=<UNSET>, label=<UNSET>, mouseover=<UNSET>, offset=<UNSET>, path_effects=<UNSET>, picker=<UNSET>, rasterized=<UNSET>, sketch_params=<UNSET>, snap=<UNSET>, transform=<UNSET>, url=<UNSET>, visible=<UNSET>, width=<UNSET>, zorder=<UNSET>)

Set multiple properties at once.

Supported properties are

Properties:

agg_filter: a filter function, which takes a (m, n, 3) float array and a dpi value, and returns a (m, n, 3) array and two offsets from the bottom left corner of the image alpha: float or None animated: bool bbox_to_anchor: unknown child: unknown clip_box: ~matplotlib.transforms.BboxBase or None clip_on: bool clip_path: Patch or (Path, Transform) or None figure: ~matplotlib.figure.Figure gid: str height: float in_layout: bool label: object mouseover: bool offset: (float, float) or callable path_effects: list of .AbstractPathEffect picker: None or bool or float or callable rasterized: bool sketch_params: (scale: float, length: float, randomness: float) snap: bool or None transform: ~matplotlib.transforms.Transform url: str visible: bool width: float zorder: float

class neuralib.plot.tools.AxesExtendHelper[source]

Add a child inset Axes to this existing Axes

Example of add hist:

>>> from neuralib.plot import plot_figure

>>> x = np.random.sample(10)
>>> y = np.random.sample(10)
>>> with plot_figure(None) as ax:
...     ax.plot(x, y, 'k.')
...     helper = AxesExtendHelper(ax)
...     helper.xhist(x, bins=10)
...     helper.yhist(y, bins=10)

Example of add bar:

>>> from neuralib.plot import plot_figure
>>> img = np.random.sample((10, 10))
>>> with plot_figure(None) as ax:
...     ax.imshow(img)
...     helper = AxesExtendHelper(ax)
...     x = y = np.arange(10)
...     helper.xbar(x, np.mean(img, axis=0), align='center')
...     helper.ybar(y, np.mean(img, axis=1), align='center')
__init__(ax, mode='both')[source]
Parameters:

  • ax (Axes) – matplotlib.axes.Axes

  • mode (Literal['both', 'x', 'y']) – extended axis {‘both’, ‘x’, ‘y’}. default is to add both

ax_x: Axes | None
ax_y: Axes | None
xhist(values, bins, **kwargs)[source]

x axis histogram

Parameters:

  • values (ndarray[Any, dtype[T]] | list[T] | tuple[T, ...] | Series | Series) – histogram x axis

  • bins (int | Sequence[float] | str | None) – number of bins

  • kwargs – additional arguments passed to Axes.hist()

yhist(values, bins, **kwargs)[source]

y axis histogram

Parameters:

  • values (ndarray[Any, dtype[T]] | list[T] | tuple[T, ...] | Series | Series) – histogram x axis

  • bins (int | Sequence[float] | str | None) – number of bins

  • kwargs – additional arguments passed to Axes.hist()

xbar(x, height, width=None, **kwargs)[source]

x axis bar

Parameters:

  • x (ndarray[Any, dtype[T]] | list[T] | tuple[T, ...] | Series | Series) – x axis

  • height (ndarray) – bar height

  • width (float | ndarray | None) – bar width

  • kwargs – additional arguments passed to Axes.bar()

ybar(y, width, height=None, **kwargs)[source]

y axis bar

Parameters:

  • y (ndarray[Any, dtype[T]] | list[T] | tuple[T, ...] | Series | Series) – y axis

  • height (float | ndarray | None) – bar height

  • width (ndarray) – bar width

  • kwargs – additional arguments passed to Axes.bar()

neuralib.plot.tools.insert_latex_equation(ax, tex, output=None)[source]

Plot figure with latex expression, and save as image

Parameters:

  • ax (Axes) – matplotlib.axes.Axes

  • tex (str) – latex string

  • output (str | Path | bytes | BinaryIO | BufferedIOBase | BufferedReader | None) – output of the fig, if None then save the figure