power_balance.plotting.common#

Source: power_balance/plotting/common.py

add_plot_objects#

add_plot_objects(figure: <function figure at 0x7fe371db5b40>, x_array: numpy.ndarray, y_array: numpy.ndarray, x_label: str, y_label: str, point_threshold: int = 100) -> None

Create a Bokeh plot source

Parameters#

• x_array: numpy.ndarray

  independent variable array

• y_array: numpy.ndarray

  dependent variable array

• x_label: str

  label for independent data array

• y_label: str

  label for dependent data array

• point_threshold: int, default 100

  threshold on number of data points to display, default is 100

make_hover_tool#

make_hover_tool(x_label: str, y_label: str, dec_places: int = 4) -> bokeh.models.tools.HoverTool

Create a HoverTool instance for a variable plot. This allows the interface user to hover over data points and see info.

Parameters#

• x_label: str

  name of independent variable

• y_label: str

  name of dependent variable

• dec_places: int, default 4

  number of decimal places before the exponent, default is 4

Returns#

• bokeh.models.tools.HoverTool

  instance of hover tool to be added to Bokeh plot

plot_to_image#

plot_to_image(x_array: Iterable, y_array: Iterable, x_label: str, y_label: str, file_name: str, dpi: int = 900, filetype: str = 'jpeg') -> None

Plots graph of power against time and saves to the given file address.

Parameters#

• x_array: typing.Iterable

  x axis array

• y_array: typing.Iterable

  y array

• x_label: str

  independent variable label

• y_label: str

  dependent variable label

• file_name: str

  output file name (should match filetype)

• dpi: int, default 900

  image resolution, by default 900

• filetype: str, default jpeg

  file format, by default "jpeg"