mirror of
https://github.com/Ladebeze66/projetcbaollm.git
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167 lines
7.0 KiB
Python
167 lines
7.0 KiB
Python
"""gr.Plot() component."""
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from __future__ import annotations
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import json
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from collections.abc import Sequence
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from types import ModuleType
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from typing import TYPE_CHECKING, Any, Literal
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from gradio_client.documentation import document
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from gradio import processing_utils, wasm_utils
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from gradio.components.base import Component
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from gradio.data_classes import GradioModel
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from gradio.events import Events
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if TYPE_CHECKING:
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from gradio.components import Timer
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class PlotData(GradioModel):
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type: Literal["altair", "bokeh", "plotly", "matplotlib"]
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plot: str
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class AltairPlotData(PlotData):
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chart: Literal["bar", "line", "scatter"]
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type: Literal["altair"] = "altair" # type: ignore
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@document()
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class Plot(Component):
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"""
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Creates a plot component to display various kinds of plots (matplotlib, plotly, altair, or bokeh plots are supported). As this component does
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not accept user input, it is rarely used as an input component.
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Demos: blocks_kinematics, stock_forecast
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Guides: plot-component-for-maps
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"""
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data_model = PlotData
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EVENTS = [Events.change]
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def __init__(
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self,
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value: Any | None = None,
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*,
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format: str = "png"
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if wasm_utils.IS_WASM
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else "webp", # webp is a good default for speed (see #7845) but can't be used in Wasm because the the version of matplotlib used in Wasm (3.5.2 in the case of Pyodide 0.26.1) doesn't support it.
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label: str | None = None,
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every: Timer | float | None = None,
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inputs: Component | Sequence[Component] | set[Component] | None = None,
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show_label: bool | None = None,
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container: bool = True,
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scale: int | None = None,
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min_width: int = 160,
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visible: bool = True,
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elem_id: str | None = None,
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elem_classes: list[str] | str | None = None,
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render: bool = True,
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key: int | str | None = None,
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):
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"""
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Parameters:
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value: Optionally, supply a default plot object to display, must be a matplotlib, plotly, altair, or bokeh figure, or a callable. If a function is provided, the function will be called each time the app loads to set the initial value of this component.
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format: File format in which to send matplotlib plots to the front end, such as 'jpg' or 'png'.
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label: the label for this component. Appears above the component and is also used as the header if there are a table of examples for this component. If None and used in a `gr.Interface`, the label will be the name of the parameter this component is assigned to.
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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.
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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.
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show_label: if True, will display label.
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container: If True, will place the component in a container - providing some extra padding around the border.
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scale: relative size compared to adjacent Components. For example if Components A and B are in a Row, and A has scale=2, and B has scale=1, A will be twice as wide as B. Should be an integer. scale applies in Rows, and to top-level Components in Blocks where fill_height=True.
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min_width: minimum pixel width, will wrap if not sufficient screen space to satisfy this value. If a certain scale value results in this Component being narrower than min_width, the min_width parameter will be respected first.
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visible: If False, component will be hidden.
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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.
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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.
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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.
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key: if assigned, will be used to assume identity across a re-render. Components that have the same key across a re-render will have their value preserved.
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"""
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self.format = format
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super().__init__(
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label=label,
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every=every,
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inputs=inputs,
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show_label=show_label,
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container=container,
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scale=scale,
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min_width=min_width,
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visible=visible,
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elem_id=elem_id,
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elem_classes=elem_classes,
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render=render,
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key=key,
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value=value,
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)
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def get_config(self):
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try:
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import bokeh # type: ignore
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bokeh_version = bokeh.__version__
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except ImportError:
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bokeh_version = None
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config = super().get_config()
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config["bokeh_version"] = bokeh_version
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return config
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def preprocess(self, payload: PlotData | None) -> PlotData | None:
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"""
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Parameters:
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payload: The data to display in the plot.
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Returns:
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(Rarely used) passes the data displayed in the plot as an PlotData dataclass, which includes the plot information as a JSON string, as well as the type of chart and the plotting library.
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"""
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return payload
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def example_payload(self) -> Any:
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return None
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def example_value(self) -> Any:
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return None
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def postprocess(self, value: Any) -> PlotData | None:
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"""
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Parameters:
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value: Expects plot data in one of these formats: a matplotlib.Figure, bokeh.Model, plotly.Figure, or altair.Chart object.
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Returns:
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PlotData: A dataclass containing the plot data as a JSON string, as well as the type of chart and the plotting library.
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"""
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if value is None:
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return None
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if isinstance(value, PlotData):
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return value
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if isinstance(value, ModuleType) or "matplotlib" in value.__module__:
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dtype = "matplotlib"
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out_y = processing_utils.encode_plot_to_base64(value, self.format)
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elif "bokeh" in value.__module__:
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dtype = "bokeh"
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from bokeh.embed import json_item
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out_y = json.dumps(json_item(value))
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else:
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is_altair = "altair" in value.__module__
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dtype = "altair" if is_altair else "plotly"
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out_y = value.to_json()
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return PlotData(type=dtype, plot=out_y)
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class AltairPlot:
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@staticmethod
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def create_legend(position, title):
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if position == "none":
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legend = None
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else:
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position = {"orient": position} if position else {}
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legend = {"title": title, **position}
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return legend
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@staticmethod
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def create_scale(limit):
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import altair as alt
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return alt.Scale(domain=limit) if limit else alt.Undefined
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