gomoku_rl.utils.visual module

gomoku_rl.utils.visual.annotate_heatmap(im, data=None, valfmt='{x:.2f}', textcolors=('black', 'white'), threshold=None, **textkw)[source]

A function to annotate a heatmap.

Parameters:
  • im – The AxesImage to be labeled.

  • data – Data used to annotate. If None, the image’s data is used. Optional.

  • valfmt – The format of the annotations inside the heatmap. This should either use the string format method, e.g. “$ {x:.2f}”, or be a matplotlib.ticker.Formatter. Optional.

  • textcolors – A pair of colors. The first is used for values below a threshold, the second for those above. Optional.

  • threshold – Value in data units according to which the colors from textcolors are applied. If None (the default) uses the middle of the colormap as separation. Optional.

  • **kwargs – All other arguments are forwarded to each call to text used to create the text labels.

gomoku_rl.utils.visual.heatmap(data, row_labels, col_labels, ax=None, cbar_kw=None, cbarlabel='', **kwargs)[source]

Create a heatmap from a numpy array and two lists of labels.

Parameters:
  • data – A 2D numpy array of shape (M, N).

  • row_labels – A list or array of length M with the labels for the rows.

  • col_labels – A list or array of length N with the labels for the columns.

  • ax – A matplotlib.axes.Axes instance to which the heatmap is plotted. If not provided, use current axes or create a new one. Optional.

  • cbar_kw – A dictionary with arguments to matplotlib.Figure.colorbar. Optional.

  • cbarlabel – The label for the colorbar. Optional.

  • **kwargs – All other arguments are forwarded to imshow.

gomoku_rl.utils.visual.payoff_headmap(payoff: ndarray, row_labels: list[str] | None = None, col_labels: list[str] | None = None)[source]