class_docstr: Granger causality matrix.
code: def __init__(
      self,
      data: pd.DataFrame,
      dfl: pd.DataFrame,
      critical: float = 0.05,
      cmap: str = "PuBu_r",
      bg_reject: str = "#ffffff",
      fg_reject: str = "#dddddd",
      labels_format: str = "{:.5f}",
      hovertemplate: str = "<b>%{x} => %{y}</b>: %{z}<extra></extra>",
      xrotation: int = 0,
      **kwargs: Any,
  ) -> None:
      super().__init__(
          data=data,
          colorbar_limit=(0, critical),
          colorbar=False,
          cmap=cmap_to_list(cmap, 9) + [bg_reject],
          xrotation=xrotation,
          labels_format=labels_format,
          hovertemplate=hovertemplate,
          **kwargs,
      )
      self.dfl = dfl
      self.critical = critical
      self.accept_cmap = cmap
      self.fg_reject = fg_reject
  
file_path: tslumen/tslumen/plot/interactive/misc.py
imports: from typing import Any
  import pandas
  from tslumen.plot.interactive.base import go
  from tslumen.plot.interactive.comparison import Heatmap
  from tslumen.plot.utils import cmapper, cmap_to_list, ccontrast
label_desc: Use image node_id 1 to create a new GrangerMatrix object from inherited base classes: Heatmap with example: obj = GrangerMatrix(data, dfl, critical, cmap, bg_reject, fg_reject, labels_format, hovertemplate, xrotation)