myco.vis

Visualization tools for ndarray data and tensorflow modeling.

get_styles()

Lists the available plotting styles.

Returns:

Type	Description
list	list of style names to pass to set_style()

Source code in myco/vis.py

def get_styles() -> list:
    """Lists the available plotting styles.

    Args:
        None.

    Returns:
        list of style names to pass to `set_style()`
    """
    styles = mpl.style.available
    return styles

plot_3d_array(array, vmin=None, vmax=None, labels=None, title=None, colorbar=True, cmap=DEFAULT_CMAP, style=DEFAULT_STYLE, **kwargs)

Creates a square set of subplots for a 3d numpy array.

Parameters:

Name	Type	Description	Default
array	np.ndarray	a [height, width, nbands] numpy array. Will become nbands subplots.	required
vmin	_number	set the lower range of the colorbar to this value.	None
vmax	_number	set the upper range of the colorbar to this value.	None
labels	list	nbands-length list of band labels to apply to each subplot.	None
title	str	the full figure title.	None
colorbar	bool	add a labeled colorbar to each subplot.	True
cmap	mpl.colors.LinearSegmentedColormap	the colormap to apply to each band.	DEFAULT_CMAP
style	str	the matplotlib plot style to apply.	DEFAULT_STYLE
**kwargs		keyword arguments to pass to plt.subplots()	{}

Returns:

Type	Description
tuple	(fig, axs) matplotlib subplot figure and axes. run fig.show() to display.

Source code in myco/vis.py

def plot_3d_array(
    array: np.ndarray,
    vmin: _number = None,
    vmax: _number = None,
    labels: list = None,
    title: "str" = None,
    colorbar: bool = True,
    cmap: mpl.colors.LinearSegmentedColormap = DEFAULT_CMAP,
    style: "str" = DEFAULT_STYLE,
    **kwargs,
) -> tuple:
    """Creates a square set of subplots for a 3d numpy array.

    Args:
        array: a [height, width, nbands] numpy array. Will become `nbands` subplots.
        vmin: set the lower range of the colorbar to this value.
        vmax: set the upper range of the colorbar to this value.
        labels: `nbands`-length list of band labels to apply to each subplot.
        title: the full figure title.
        colorbar: add a labeled colorbar to each subplot.
        cmap: the colormap to apply to each band.
        style: the matplotlib plot style to apply.
        **kwargs: keyword arguments to pass to `plt.subplots()`

    Returns:
        (fig, axs) matplotlib subplot figure and axes. run `fig.show()` to display.
    """
    height, width, nbands = array.shape

    if style is not None:
        set_style(style)

    if labels is None:
        n_digits = _count_digits(nbands)
        labels = [f"band_{i+1:0{n_digits}d}" for i in range(nbands)]

    # create the subplots
    figx, figy = _square_factor(nbands)
    fig, axs = plt.subplots(figx, figy, **kwargs)

    # handle single/multiband differences
    if nbands == 1:
        axs = [axs]
    else:
        axs = axs.reshape(nbands)

    # plot each array
    for idx in range(nbands):
        ax = axs[idx]
        data = array[:, :, idx]
        label = labels[idx]

        im = ax.imshow(data, cmap=cmap, vmin=vmin, vmax=vmax)
        ax.set_title(label, fontsize="x-small")
        ax.axis("off")
        if colorbar:
            cbar = plt.colorbar(im, ax=ax)
            cbar.ax.tick_params(labelsize="xx-small")
            cbar.outline.set_linewidth(0.5)

    fig.suptitle(title, fontsize="x-small")
    fig.tight_layout()

    if nbands == 1:
        axs = axs[0]

    return fig, axs

set_style(style)

Sets a series of plot style parameters.

Parameters:

Name	Type	Description	Default
style	str	str of the style name to use. from plot.get_styles()	required

Returns:

Type	Description
None	None. Updates matplotlib.rcParams

Source code in myco/vis.py

def set_style(style: str) -> None:
    """Sets a series of plot style parameters.

    Args:
        style: str of the style name to use. from `plot.get_styles()`

    Returns:
        None. Updates matplotlib.rcParams
    """
    mpl.style.use(style)