Source code for piel.tools.cocotb.data

"""
This file contains a range of functions used to read, plot and analyse cocotb simulations in a data-flow standard as suggested
"""
import functools
import pandas as pd
from piel.types import PathTypes
from piel.file_system import return_path, get_files_recursively_in_directory

__all__ = [
    "get_simulation_output_files",
    "get_simulation_output_files_from_design",
    "read_simulation_data",
    "simple_plot_simulation_data",
]

get_simulation_output_files = functools.partial(
    get_files_recursively_in_directory, path="./tb/out/", extension="csv"
)


def get_simulation_output_files_from_design(
    design_directory: PathTypes,
    extension: str = "csv",
):
    """
    This function returns a list of all the simulation output files in the design directory.

    Args:
        design_directory (PathTypes): The path to the design directory.

    Returns:
        output_files (list): List of all the simulation output files in the design directory.
    """
    design_directory = return_path(design_directory)
    output_files = get_files_recursively_in_directory(
        path=design_directory / "tb" / "out", extension=extension
    )
    return output_files


def read_simulation_data(file_path: PathTypes):
    """
    This function returns a Pandas dataframe that contains all the simulation data outputted from the simulation run.

    Args:
        file_path (PathTypes): The path to the simulation data file.

    Returns:
        simulation_data (pd.DataFrame): The simulation data in a Pandas dataframe.
    """
    file_path = return_path(file_path)
    simulation_data = pd.read_csv(file_path)
    return simulation_data


def simple_plot_simulation_data(simulation_data: pd.DataFrame):
    from bokeh.models import ColumnDataSource
    from bokeh.plotting import figure, show
    from bokeh.layouts import column

    source = ColumnDataSource(
        data=dict(time=simulation_data.t, signal=simulation_data.x)
    )

    p = figure(
        height=300,
        width=800,
        tools="xpan",
        toolbar_location=None,
        # x_axis_type="datetime",
        x_axis_location="above",
        background_fill_color="#efefef",
    )

    p.line("time", "signal", source=source)
    # p.yaxis.axis_label = "Price"

    select = figure(
        title="Drag the middle and edges of the selection box to change the range above",
        height=130,
        width=800,
        y_range=p.y_range,
        # x_axis_type="datetime",
        y_axis_type=None,
        tools="",
        toolbar_location=None,
        background_fill_color="#efefef",
    )

    # range_tool = RangeTool(x_range=p.x_range)
    # range_tool.overlay.fill_color = "navy"
    # range_tool.overlay.fill_alpha = 0.2

    select.line("time", "signal", source=source)
    select.ygrid.grid_line_color = None
    # select.add_tools(range_tool)

    return show(column(p, select))