class_docstr: SmartPlotter is a Bridge pattern decoupling plotting functions from SmartExplainer.
  The smartplotter class includes all the methods used to display graphics
  Each SmartPlotter method is easy to use from a Smart explainer object,
  just use the following syntax
  Attributes :
  explainer: object
      SmartExplainer instance to point to.
  Example
  --------
  >>> xpl.plot.my_plot_method(param=value)
class_docstr_tok: ["SmartPlotter","is","a","Bridge","pattern","decoupling","plotting","functions","from","SmartExplainer",".","The","smartplotter","class","includes","all","the","methods","used","to","display","graphics","Each","SmartPlotter","method","is","easy","to","use","from","a","Smart","explainer","object",",","just","use","the","following","syntax","Attributes",":","explainer",":","object","SmartExplainer","instance","to","point","to",".","Example","--","--","--","--",">",">",">","xpl.plot.my_plot_method","(","param=value",")"]
docstr: Function used to generate a scatter plot figure for the interactions plots.
  Parameters
  ----------
  x_name : str
      Name of the variable used as the x axis
  y_name : str
      Name of the variable used as the y axis
  col_name : str
      Name of the variable used as the color attribute
  x_values : pd.DataFrame
      Values of the points on the x axis as a 1 column DataFrame
  y_values : pd.DataFrame
      Values of the points on the y axis as a 1 column DataFrame
  col_values : pd.DataFrame
      Values of the color of the points as a 1 column DataFrame
  col_scale : list
      color scale
  Returns
  -------
  go.Figure
code: def _plot_interactions_scatter(
      self,
      x_name,
      y_name,
      col_name,
      x_values,
      y_values,
      col_values,
      col_scale,
  ):
      """
      Function used to generate a scatter plot figure for the interactions plots.
      Parameters
      ----------
      x_name : str
          Name of the variable used as the x axis
      y_name : str
          Name of the variable used as the y axis
      col_name : str
          Name of the variable used as the color attribute
      x_values : pd.DataFrame
          Values of the points on the x axis as a 1 column DataFrame
      y_values : pd.DataFrame
          Values of the points on the y axis as a 1 column DataFrame
      col_values : pd.DataFrame
          Values of the color of the points as a 1 column DataFrame
      col_scale : list
          color scale
      Returns
      -------
      go.Figure
      """
      # add break line to X label if necessary
      max_len_by_row = max(
          [
              round(
                  50
                  / self.explainer.features_desc[
                      x_values.columns.values[0]
                  ]
              ),
              8,
          ]
      )
      x_values.iloc[:, 0] = x_values.iloc[:, 0].apply(
          add_line_break,
          args=(
              max_len_by_row,
              120,
          ),
      )
  
      data_df = pd.DataFrame(
          {
              x_name: x_values.values.flatten(),
              y_name: y_values.values.flatten(),
              col_name: col_values.values.flatten(),
          }
      )
  
      if isinstance(col_values.values.flatten()[0], str):
          fig = px.scatter(
              data_df,
              x=x_name,
              y=y_name,
              color=col_name,
              color_discrete_sequence=self._style_dict[
                  "interactions_discrete_colors"
              ],
          )
      else:
          fig = px.scatter(
              data_df,
              x=x_name,
              y=y_name,
              color=col_name,
              color_continuous_scale=col_scale,
          )
  
      fig.update_traces(mode="markers")
  
      return fig
  
imports: import warnings
  from numbers import Number
  import random
  import copy
  import math
  import numpy
  from scipy.optimize import fsolve
  import scipy.cluster.hierarchy
  import pandas
  from plotly import graph_objs
  import plotly.express
  from plotly.subplots import make_subplots
  from plotly.offline import plot
  from shapash.manipulation.select_lines import select_lines
  from shapash.manipulation.summarize import compute_features_import, project_feature_values_1d, compute_corr
  from shapash.utils.utils import add_line_break, truncate_str, compute_digit_number, add_text, maximum_difference_sort_value, compute_sorted_variables_interactions_list_indices, compute_top_correlations_features
  from shapash.webapp.utils.utils import round_to_k
  from shapash.style.style_utils import colors_loading, select_palette, define_style
label_desc: Use image node_id 19 for calling the SmartPlotter obj's underlying member method code with example usage: obj._plot_interactions_scatter(x_name, y_name, col_name, x_values, y_values, col_values, col_scale) and returns: fig