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DocumentationPlotting Library

Plotting Library

Utilities available under datacards.utilities.plotting

The plotting library is a collection of helper functions for creating plots using matplotlib. It is used by the various matplotlib cards.

Area Calculation

plot_area

def plot_area(
    rows: int,
    columns: int,
    dpi: float = 100.0,
    value_in_card: bool = False,
    unit_in_card: bool = False
) -> Tuple[float, float]:

Calculates the appropriate figure size for datacard plots.

Parameters:

  • rows: Number of rows in the plot
  • columns: Number of columns in the plot
  • dpi: Dots per inch (default: 100.0)
  • value_in_card: Whether value is shown in card (default: False)
  • unit_in_card: Whether unit is shown in card (default: False)

Returns:

  • Tuple[float, float]: Width and height of the figure

Basic Plots

boxplot

def boxplot(
    x: List[float],
    thumbnail: bool
) -> Tuple[plt.Figure, plt.Axes]:

Creates a boxplot visualization.

Parameters:

  • x: List of numerical values to plot
  • thumbnail: Whether to create a thumbnail version

Returns:

  • Tuple[plt.Figure, plt.Axes]: Figure and axes objects containing the plot

histogram

def histogram(
    x: List[float],
    x_label: str,
    y_label: str,
    kernel_density: bool,
    thumbnail: bool
) -> Tuple[plt.Figure, plt.Axes]:

Creates a histogram with optional kernel density estimation.

Parameters:

  • x: List of numerical values to plot
  • x_label: Label for the x-axis
  • y_label: Label for the y-axis
  • kernel_density: Whether to show kernel density estimation
  • thumbnail: Whether to create a thumbnail version

Returns:

  • Tuple[plt.Figure, plt.Axes]: Figure and axes objects containing the plot

scatterplot

def scatterplot(
    x: List[float],
    y: List[float],
    x_label: str,
    y_label: str,
    thumbnail: bool,
    flag: Optional[List[str]] = None
) -> Tuple[plt.Figure, plt.Axes]:

Creates a scatter plot with optional color coding.

Parameters:

  • x: List of x-coordinates
  • y: List of y-coordinates
  • x_label: Label for the x-axis
  • y_label: Label for the y-axis
  • thumbnail: Whether to create a thumbnail version
  • flag: Optional list of status flags (‘neutral’, ‘lessen’, ‘warning’, ‘danger’, ‘success’)

Returns:

  • Tuple[plt.Figure, plt.Axes]: Figure and axes objects containing the plot

lineplot

def lineplot(
    x: List[float],
    y: List[float],
    x_label: str,
    y_label: str,
    thumbnail: bool,
    flag: Optional[List[str]] = None,
    majorante_x: Optional[List[float]] = None,
    majorante_y: Optional[List[float]] = None,
    minorante_x: Optional[List[float]] = None,
    minorante_y: Optional[List[float]] = None,
    **kwargs
) -> Tuple[plt.Figure, plt.Axes]:

Creates a line plot with optional confidence intervals.

Parameters:

  • x: List of x-coordinates
  • y: List of y-coordinates
  • x_label: Label for the x-axis
  • y_label: Label for the y-axis
  • thumbnail: Whether to create a thumbnail version
  • flag: Optional list of status flags
  • majorante_x: Optional x-coordinates for upper bound
  • majorante_y: Optional y-coordinates for upper bound
  • minorante_x: Optional x-coordinates for lower bound
  • minorante_y: Optional y-coordinates for lower bound
  • **kwargs: Additional matplotlib plotting parameters

Returns:

  • Tuple[plt.Figure, plt.Axes]: Figure and axes objects containing the plot

barplot

def barplot(
    basket_labels: List[str],
    grp_value_dictionary: Dict[str, List[float]],
    y_label: str,
    show_legend: bool = True
) -> Tuple[plt.Figure, plt.Axes]:

Creates a grouped bar plot along several baskets (e.g. years).

Parameters:

  • basket_labels: List of labels for each group
  • grp_value_dictionary: Dictionary mapping group names to their values
  • y_label: Label for the y-axis
  • show_legend: Whether to show the legend (default: True)

Returns:

  • Tuple[plt.Figure, plt.Axes]: Figure and axes objects containing the plot

Specialized Plots

speedometer

def speedometer(
    x: float,
    limits: List[float],
    thumbnail: bool,
    x_label: str
) -> Tuple[plt.Figure, plt.Axes]:

Creates a speedometer-style gauge visualization.

Parameters:

  • x: Current value to display
  • limits: List of limit values for the gauge
  • thumbnail: Whether to create a thumbnail version
  • x_label: Label for the x-axis

Returns:

  • Tuple[plt.Figure, plt.Axes]: Figure and axes objects containing the plot

traffic_lights

def traffic_lights(
    red: bool,
    yellow: bool,
    green: bool
) -> Tuple[plt.Figure, plt.Axes]:

Creates a traffic light visualization.

Parameters:

  • red: Whether red light is on
  • yellow: Whether yellow light is on
  • green: Whether green light is on

Returns:

  • Tuple[plt.Figure, plt.Axes]: Figure and axes objects containing the plot

donutplot

def donutplot(
    x: List[float],
    labels: List[str],
    thumbnail: bool
) -> Tuple[plt.Figure, plt.Axes]:

Creates a donut/pie chart visualization.

Parameters:

  • x: List of values for each segment
  • labels: List of labels for each segment
  • thumbnail: Whether to create a thumbnail version

Returns:

  • Tuple[plt.Figure, plt.Axes]: Figure and axes objects containing the plot

flight_envelope_bg

def flight_envelope_bg(
    polyMACHdf: pd.DataFrame,
    polyDTAMBdf: pd.DataFrame,
    thumbnail: bool
) -> Tuple[plt.Figure, dict[str, plt.Axes]]:

Used to create the special flight envelope plot. Draws a figure with two named axes DTAMB and MACH with shared ALTITUDE-axes.

Parameters:

  • polyMACHdf: DataFrame containing MACH polygon vertices
  • polyDTAMBdf: DataFrame containing DTAMB polygon vertices
  • thumbnail: Whether to create a thumbnail version

Returns:

  • Tuple[plt.Figure, dict[str, plt.Axes]]: Figure and dictionary of axes objects containing the plot

Color Mapping

The library uses the following color scheme for status flags:

  • Danger: #FF0B5F (Red)
  • Warning: #FFD90B (Yellow)
  • Success: #0BFF85 (Green)
  • Neutral: #E5E5E5 (Light Grey)
  • Lessen: #AAAAAA (Dark Grey)
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