# Path: bigbang/visualisation/stackedareachart.py
# def get_ylabels(data) -> List[str]:
# def data_transformation(
#     idata: dict,
#     ylabels: Optional[List[str]] = None,
#     percentage: bool = False,
# ) -> np.ndarray:
# def stacked_area_chart(
#     data: dict,
#     ax: mpl.axes,
#     domains_in_focus: Optional[list] = None,
#     percentage: bool = False,
#     colormap: Optional[mpl.colors.LinearSegmentedColormap] = None,
#     color_default: Optional[np.array] = None,
# ):
# 
# Path: bigbang/visualisation/utils.py
# def create_color_palette(
#     ylabels: List[str],
#     domains_in_focus: Optional[List[str]] = None,
#     colormap: mpl.colors.LinearSegmentedColormap = mpl.cm.jet,
#     include_dof: bool = True,
#     color_dof: np.array = np.array([175, 175, 175]),
#     return_dict: bool = False,
# ) -> list:


from typing import Dict, List, Optional, Tuple, Union
from colour import Color
from pylab import cm
from matplotlib.pyplot import figure
from bigbang.visualisation import stackedareachart
from bigbang.visualisation import utils
import numpy as np
import pylab
import matplotlib as mpl
import matplotlib.pyplot as plt
import matplotlib.lines as mlines




def evolution_of_participation_1D(
    data: dict,
    ax: mpl.axes,
    entity_in_focus: Optional[list] = None,
    percentage: bool = False,
    colormap: mpl.colors.LinearSegmentedColormap = mpl.cm.jet,
) -> mpl.axes:
    """
    Parameters
    ----------
    data : Dictionary with a format {'x_axis_labels': {'y_axis_labels': y_values}}
    entity_in_focus :
    percentage :
    """
    x = list(data.keys())
    ylabels = stackedareachart.get_ylabels(data)
    y = stackedareachart.data_transformation(data, ylabels, percentage)

# Path: bigbang/visualisation/stackedareachart.py
# def get_ylabels(data) -> List[str]:
# def data_transformation(
#     idata: dict,
#     ylabels: Optional[List[str]] = None,
#     percentage: bool = False,
# ) -> np.ndarray:
# def stacked_area_chart(
#     data: dict,
#     ax: mpl.axes,
#     domains_in_focus: Optional[list] = None,
#     percentage: bool = False,
#     colormap: Optional[mpl.colors.LinearSegmentedColormap] = None,
#     color_default: Optional[np.array] = None,
# ):
# 
# Path: bigbang/visualisation/utils.py
# def create_color_palette(
#     ylabels: List[str],
#     domains_in_focus: Optional[List[str]] = None,
#     colormap: mpl.colors.LinearSegmentedColormap = mpl.cm.jet,
#     include_dof: bool = True,
#     color_dof: np.array = np.array([175, 175, 175]),
#     return_dict: bool = False,
# ) -> list:


# Path: bigbang/visualisation/lines.py
from typing import Dict, List, Optional, Tuple, Union
from colour import Color
from pylab import cm
from matplotlib.pyplot import figure
from bigbang.visualisation import stackedareachart
from bigbang.visualisation import utils
import numpy as np
import pylab
import matplotlib as mpl
import matplotlib.pyplot as plt
import matplotlib.lines as mlines





def evolution_of_participation_1D(
    data: dict,
    ax: mpl.axes,
    entity_in_focus: Optional[list] = None,
    percentage: bool = False,
    colormap: mpl.colors.LinearSegmentedColormap = mpl.cm.jet,
) -> mpl.axes:
    """
    Parameters
    ----------
    data : Dictionary with a format {'x_axis_labels': {'y_axis_labels': y_values}}
    entity_in_focus :
    percentage :
    """
    x = list(data.keys())
    ylabels = stackedareachart.get_ylabels(data)
    y = stackedareachart.data_transformation(data, ylabels, percentage)

    colors = utils.create_color_palette(