venv/lib/python3.11/site-packages/gradio/components/bar_plot.py

"""gr.BarPlot() component."""

from __future__ import annotations

import warnings
from collections.abc import Callable, Sequence
from typing import TYPE_CHECKING, Any, Literal

from gradio_client.documentation import document

from gradio.components.base import Component
from gradio.components.plot import AltairPlot, AltairPlotData, Plot
from gradio.i18n import I18nData

if TYPE_CHECKING:
    import pandas as pd

    from gradio.components import Timer


@document()
class BarPlot(Plot):
    """
    Creates a bar plot component to display data from a pandas DataFrame (as output). As this component does
    not accept user input, it is rarely used as an input component.

    Demos: bar_plot
    """

    data_model = AltairPlotData

    def __init__(
        self,
        value: pd.DataFrame | Callable | None = None,
        x: str | None = None,
        y: str | None = None,
        *,
        color: str | None = None,
        vertical: bool = True,
        group: str | None = None,
        title: str | None = None,
        tooltip: list[str] | str | None = None,
        x_title: str | None = None,
        y_title: str | None = None,
        x_label_angle: float | None = None,
        y_label_angle: float | None = None,
        color_legend_title: str | None = None,
        group_title: str | None = None,
        color_legend_position: Literal[
            "left",
            "right",
            "top",
            "bottom",
            "top-left",
            "top-right",
            "bottom-left",
            "bottom-right",
            "none",
        ]
        | None = None,
        height: int | None = None,
        width: int | None = None,
        y_lim: list[int] | None = None,
        caption: str | None = None,
        interactive: bool | None = True,
        label: str | I18nData | None = None,
        show_label: bool | None = None,
        container: bool = True,
        scale: int | None = None,
        min_width: int = 160,
        every: Timer | float | None = None,
        inputs: Component | Sequence[Component] | set[Component] | None = None,
        visible: bool = True,
        elem_id: str | None = None,
        elem_classes: list[str] | str | None = None,
        render: bool = True,
        key: int | str | tuple[int | str, ...] | None = None,
        preserved_by_key: list[str] | str | None = "value",
        sort: Literal["x", "y", "-x", "-y"] | None = None,
        show_actions_button: bool = False,
    ):
        """
        Parameters:
            value: The pandas dataframe containing the data to display in a scatter plot. If a callable is provided, the function will be called whenever the app loads to set the initial value of the plot.
            x: Column corresponding to the x axis.
            y: Column corresponding to the y axis.
            color: The column to determine the bar color. Must be categorical (discrete values).
            vertical: If True, the bars will be displayed vertically. If False, the x and y axis will be switched, displaying the bars horizontally. Default is True.
            group: The column with which to split the overall plot into smaller subplots.
            title: The title to display on top of the chart.
            tooltip: The column (or list of columns) to display on the tooltip when a user hovers over a bar.
            x_title: The title given to the x axis. By default, uses the value of the x parameter.
            y_title: The title given to the y axis. By default, uses the value of the y parameter.
            x_label_angle: The angle (in degrees) of the x axis labels. Positive values are clockwise, and negative values are counter-clockwise.
            y_label_angle: The angle (in degrees) of the y axis labels. Positive values are clockwise, and negative values are counter-clockwise.
            color_legend_title: The title given to the color legend. By default, uses the value of color parameter.
            group_title: The label displayed on top of the subplot columns (or rows if vertical=True). Use an empty string to omit.
            color_legend_position: The position of the color legend. If the string value 'none' is passed, this legend is omitted. For other valid position values see: https://vega.github.io/vega/docs/legends/#orientation.
            height: The height of the plot in pixels.
            width: The width of the plot in pixels. If None, expands to fit.
            y_lim: A tuple of list containing the limits for the y-axis, specified as [y_min, y_max].
            caption: The (optional) caption to display below the plot.
            interactive: Whether users should be able to interact with the plot by panning or zooming with their mouse or trackpad.
            label: The (optional) label to display on the top left corner of the plot.
            show_label: Whether the label should be displayed.
            every: Continously calls `value` to recalculate it if `value` is a function (has no effect otherwise). Can provide a Timer whose tick resets `value`, or a float that provides the regular interval for the reset Timer.
            inputs: Components that are used as inputs to calculate `value` if `value` is a function (has no effect otherwise). `value` is recalculated any time the inputs change.
            visible: Whether the plot should be visible.
            elem_id: An optional string that is assigned as the id of this component in the HTML DOM. Can be used for targeting CSS styles.
            elem_classes: An optional list of strings that are assigned as the classes of this component in the HTML DOM. Can be used for targeting CSS styles.
            render: If False, component will not render be rendered in the Blocks context. Should be used if the intention is to assign event listeners now but render the component later.
            key: in a gr.render, Components with the same key across re-renders are treated as the same component, not a new component. Properties set in 'preserved_by_key' are not reset across a re-render.
            preserved_by_key: A list of parameters from this component's constructor. Inside a gr.render() function, if a component is re-rendered with the same key, these (and only these) parameters will be preserved in the UI (if they have been changed by the user or an event listener) instead of re-rendered based on the values provided during constructor.
            sort: Specifies the sorting axis as either "x", "y", "-x" or "-y". If None, no sorting is applied.
            show_actions_button: Whether to show the actions button on the top right corner of the plot.
        """
        self.x = x
        self.y = y
        self.color = color
        self.vertical = vertical
        self.group = group
        self.group_title = group_title
        self.tooltip = tooltip
        self.title = title
        self.x_title = x_title
        self.y_title = y_title
        self.x_label_angle = x_label_angle
        self.y_label_angle = y_label_angle
        self.color_legend_title = color_legend_title
        self.group_title = group_title
        self.color_legend_position = color_legend_position
        self.y_lim = y_lim
        self.caption = caption
        self.interactive_chart = interactive
        if isinstance(width, str):
            width = None
            warnings.warn(
                "Width should be an integer, not a string. Setting width to None."
            )
        if isinstance(height, str):
            warnings.warn(
                "Height should be an integer, not a string. Setting height to None."
            )
            height = None
        self.width = width
        self.height = height
        self.sort = sort
        self.show_actions_button = show_actions_button
        if label is None and show_label is None:
            show_label = False
        super().__init__(
            value=value,
            label=label,
            show_label=show_label,
            container=container,
            scale=scale,
            min_width=min_width,
            visible=visible,
            elem_id=elem_id,
            elem_classes=elem_classes,
            render=render,
            key=key,
            preserved_by_key=preserved_by_key,
            every=every,
            inputs=inputs,
        )

    def get_block_name(self) -> str:
        return "plot"

    @staticmethod
    def create_plot(
        value: pd.DataFrame,
        x: str,
        y: str,
        color: str | None = None,
        vertical: bool = True,
        group: str | None = None,
        title: str | None = None,
        tooltip: list[str] | str | None = None,
        x_title: str | None = None,
        y_title: str | None = None,
        x_label_angle: float | None = None,
        y_label_angle: float | None = None,
        color_legend_title: str | None = None,
        group_title: str | None = None,
        color_legend_position: Literal[
            "left",
            "right",
            "top",
            "bottom",
            "top-left",
            "top-right",
            "bottom-left",
            "bottom-right",
            "none",
        ]
        | None = None,
        height: int | None = None,
        width: int | None = None,
        y_lim: list[int] | None = None,
        interactive: bool | None = True,
        sort: Literal["x", "y", "-x", "-y"] | None = None,
    ):
        """Helper for creating the bar plot."""
        import altair as alt

        interactive = True if interactive is None else interactive
        orientation = {"field": group, "title": group_title} if group else {}

        x_title = x_title or x
        y_title = y_title or y

        # If horizontal, switch x and y
        if not vertical:
            y, x = x, y
            x = f"sum({x}):Q"
            y_title, x_title = x_title, y_title
            orientation = {"row": alt.Row(**orientation)} if orientation else {}  # type: ignore
            x_lim = y_lim
            y_lim = None
        else:
            y = f"sum({y}):Q"
            x_lim = None
            orientation = {"column": alt.Column(**orientation)} if orientation else {}  # type: ignore

        encodings = dict(
            x=alt.X(
                x,  # type: ignore
                title=x_title,  # type: ignore
                scale=AltairPlot.create_scale(x_lim),  # type: ignore
                axis=alt.Axis(labelAngle=x_label_angle)
                if x_label_angle is not None
                else alt.Axis(),
                sort=sort if vertical and sort is not None else None,
            ),
            y=alt.Y(
                y,  # type: ignore
                title=y_title,  # type: ignore
                scale=AltairPlot.create_scale(y_lim),  # type: ignore
                axis=alt.Axis(labelAngle=y_label_angle)
                if y_label_angle is not None
                else alt.Axis(),
                sort=sort if not vertical and sort is not None else None,
            ),
            **orientation,
        )
        properties = {}
        if title:
            properties["title"] = title
        if height:
            properties["height"] = height
        if width:
            properties["width"] = width

        if color:
            color_legend_position = color_legend_position or "bottom"
            domain = value[color].unique().tolist()
            range_ = list(range(len(domain)))
            encodings["color"] = {
                "field": color,
                "type": "nominal",
                "scale": {"domain": domain, "range": range_},
                "legend": AltairPlot.create_legend(
                    position=color_legend_position, title=color_legend_title
                ),
            }

        if tooltip:
            encodings["tooltip"] = tooltip  # type: ignore

        chart = (
            alt.Chart(value)  # type: ignore
            .mark_bar()  # type: ignore
            .encode(**encodings)
            .properties(background="transparent", **properties)
        )
        if interactive:
            chart = chart.interactive()

        return chart

    def preprocess(self, payload: AltairPlotData) -> AltairPlotData:
        """
        Parameters:
            payload: The data to display in a bar plot.
        Returns:
            (Rarely used) passes the data displayed in the bar plot as an AltairPlotData dataclass, which includes the plot information as a JSON string, as well as the type of plot (in this case, "bar").
        """
        return payload

    def postprocess(self, value: pd.DataFrame | None) -> AltairPlotData | None:
        """
        Parameters:
            value: Expects a pandas DataFrame containing the data to display in the bar plot. The DataFrame should contain at least two columns, one for the x-axis (corresponding to this component's `x` argument) and one for the y-axis (corresponding to `y`).
        Returns:
            The data to display in a bar plot, in the form of an AltairPlotData dataclass, which includes the plot information as a JSON string, as well as the type of plot (in this case, "bar").
        """
        # if None or update
        if value is None:
            return value
        if self.x is None or self.y is None:
            raise ValueError("No value provided for required parameters `x` and `y`.")
        chart = self.create_plot(
            value=value,
            x=self.x,
            y=self.y,
            color=self.color,
            vertical=self.vertical,
            group=self.group,
            title=self.title,
            tooltip=self.tooltip,
            x_title=self.x_title,
            y_title=self.y_title,
            x_label_angle=self.x_label_angle,
            y_label_angle=self.y_label_angle,
            color_legend_title=self.color_legend_title,
            color_legend_position=self.color_legend_position,  # type: ignore
            group_title=self.group_title,
            y_lim=self.y_lim,
            interactive=self.interactive_chart,
            height=self.height,
            width=self.width,
            sort=self.sort,  # type: ignore
        )

        return AltairPlotData(type="altair", plot=chart.to_json(), chart="bar")

    def example_payload(self) -> Any:
        return None

    def example_value(self) -> Any:
        import pandas as pd

        return pd.DataFrame({self.x: [1, 2, 3], self.y: [4, 5, 6]})