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bfe8afc3bf
* poetry, req files * installer spec pywry 0.6.0 changes * fix `df_volume` being sent as `pd.Series` on Macs * more `pd.Series` fixes * bump pywry to 0.6.1 -fixes linux install
1924 lines
64 KiB
Python
1924 lines
64 KiB
Python
"""Chart and style helpers for Plotly."""
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# pylint: disable=C0302,R0902,W3301
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import contextlib
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import json
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import sys
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import textwrap
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from datetime import datetime, timedelta
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from math import floor
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from pathlib import Path
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from typing import (
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TYPE_CHECKING,
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Any,
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Dict,
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List,
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Literal,
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Optional,
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Tuple,
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TypeVar,
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Union,
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)
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import numpy as np
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import pandas as pd
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import plotly.graph_objects as go
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import plotly.io as pio
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import statsmodels.api as sm
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from plotly.subplots import make_subplots
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from scipy import stats
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from openbb_terminal import config_terminal
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from openbb_terminal.base_helpers import console, strtobool
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from openbb_terminal.core.config.paths import STYLES_DIRECTORY_REPO
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from openbb_terminal.core.plots.backend import PLOTLYJS_PATH, plots_backend
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from openbb_terminal.core.plots.config.openbb_styles import (
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PLT_COLORWAY,
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PLT_DECREASING_COLORWAY,
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PLT_INCREASING_COLORWAY,
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PLT_TBL_ROW_COLORS,
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)
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from openbb_terminal.core.session.current_system import get_current_system
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from openbb_terminal.core.session.current_user import get_current_user
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if TYPE_CHECKING:
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with contextlib.suppress(ImportError):
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from darts import TimeSeries # pylint: disable=W0611 # noqa: F401
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TimeSeriesT = TypeVar("TimeSeriesT", bound="TimeSeries")
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class TerminalStyle:
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"""The class that helps with handling of style configurations.
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It serves styles for 2 libraries. For `Plotly` this class serves absolute paths
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to the .pltstyle files. For `Plotly` and `Rich` this class serves custom
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styles as python dictionaries.
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"""
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STYLES_REPO = STYLES_DIRECTORY_REPO
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USER_STYLES_DIRECTORY: Path = get_current_user().preferences.USER_STYLES_DIRECTORY
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plt_styles_available: Dict[str, Path] = {}
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plt_style: str = "dark"
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plotly_template: Dict[str, Any] = {}
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mapbox_style: str = "dark"
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console_styles_available: Dict[str, Path] = {}
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console_style: Dict[str, Any] = {}
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line_color: str = ""
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up_color: str = ""
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down_color: str = ""
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up_colorway: List[str] = []
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down_colorway: List[str] = []
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up_color_transparent: str = ""
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down_color_transparent: str = ""
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line_width: float = 1.5
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def __new__(cls, *args, **kwargs): # pylint: disable=W0613
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"""Create a singleton."""
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if not hasattr(cls, "instance"):
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cls.instance = super().__new__(cls) # pylint: disable=E1120
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return cls.instance
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def __init__(
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self,
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plt_style: Optional[str] = "",
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console_style: Optional[str] = "",
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):
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"""Initialize the class.
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Parameters
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----------
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plt_style : `str`, optional
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The name of the Plotly style to use, by default ""
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console_style : `str`, optional
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The name of the Rich style to use, by default ""
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"""
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self.plt_style = plt_style or self.plt_style
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self.load_available_styles()
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self.load_style(plt_style)
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self.apply_console_style(console_style)
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self.apply_style()
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def apply_console_style(self, style: Optional[str] = None) -> None:
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"""Apply the style to the console."""
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if style:
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if style in self.console_styles_available:
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json_path: Optional[Path] = self.console_styles_available[style]
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else:
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self.load_available_styles()
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if style in self.console_styles_available:
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json_path = self.console_styles_available[style]
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else:
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console.print(f"\nInvalid console style '{style}', using default.")
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json_path = self.console_styles_available.get("dark", None)
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if json_path:
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self.console_style = self.load_json_style(json_path)
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else:
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console.print("Error loading default.")
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def apply_style(self, style: Optional[str] = "") -> None:
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"""Apply the style to the libraries."""
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style = style or self.plt_style
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if style != self.plt_style:
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self.load_style(style)
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style = style.lower().replace("light", "white") # type: ignore
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if self.plt_style and self.plotly_template:
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self.plotly_template.setdefault("layout", {}).setdefault(
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"mapbox", {}
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).setdefault("style", "dark")
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if "tables" in self.plt_styles_available:
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tables = self.load_json_style(self.plt_styles_available["tables"])
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pio.templates["openbb_tables"] = go.layout.Template(tables)
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try:
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pio.templates["openbb"] = go.layout.Template(self.plotly_template)
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except ValueError as err:
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if "plotly.graph_objs.Layout: 'legend2'" in str(err):
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console.print(
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"[red]Warning: Plotly multiple legends are "
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"not supported in currently installed version.[/]\n\n"
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"[yellow]Please update plotly to version >= 5.15.0[/]\n"
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"[green]pip install plotly --upgrade[/]"
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)
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sys.exit(1)
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if style in ["dark", "white"]:
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pio.templates.default = f"plotly_{style}+openbb"
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return
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pio.templates.default = "openbb"
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self.mapbox_style = (
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self.plotly_template.setdefault("layout", {})
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.setdefault("mapbox", {})
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.setdefault("style", "dark")
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)
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def load_available_styles_from_folder(self, folder: Path) -> None:
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"""Load custom styles from folder.
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Parses the styles/default and styles/user folders and loads style files.
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To be recognized files need to follow a naming convention:
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*.pltstyle - plotly stylesheets
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*.richstyle.json - rich stylesheets
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Parameters
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----------
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folder : str
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Path to the folder containing the stylesheets
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"""
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if not folder.exists():
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return
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for attr, ext in zip(
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["plt_styles_available", "console_styles_available"],
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[".pltstyle.json", ".richstyle.json"],
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):
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for file in folder.rglob(f"*{ext}"):
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getattr(self, attr)[file.name.replace(ext, "")] = file
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def load_available_styles(self) -> None:
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"""Load custom styles from default and user folders."""
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self.load_available_styles_from_folder(self.STYLES_REPO)
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self.load_available_styles_from_folder(self.USER_STYLES_DIRECTORY)
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def load_json_style(self, file: Path) -> Dict[str, Any]:
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"""Load style from json file.
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Parameters
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----------
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file : Path
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Path to the file containing the style
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Returns
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-------
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Dict[str, Any]
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Style as a dictionary
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"""
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with open(file) as f:
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return json.load(f)
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def load_style(self, style: Optional[str] = "") -> None:
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"""Load style from file.
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Parameters
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----------
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style : str
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Name of the style to load
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"""
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style = style or self.plt_style
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if style not in self.plt_styles_available:
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console.print(
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f"[red]Plot Style {style} not found. Using default style.[/red]",
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)
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style = "dark"
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self.load_plt_style(style)
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def load_plt_style(self, style: str) -> None:
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"""Load Plotly style from file.
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Parameters
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----------
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style : str
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Name of the style to load
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"""
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self.plt_style = style
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self.plotly_template = self.load_json_style(self.plt_styles_available[style])
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line = self.plotly_template.pop("line", {})
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self.up_color = line.get("up_color", "#00ACFF")
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self.down_color = line.get("down_color", "#FF0000")
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self.up_color_transparent = line.get(
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"up_color_transparent", "rgba(0, 170, 255, 0.50)"
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)
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self.down_color_transparent = line.get(
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"down_color_transparent", "rgba(230, 0, 57, 0.50)"
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)
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self.line_color = line.get("color", "#ffed00")
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self.line_width = line.get("width", self.line_width)
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self.down_colorway = line.get("down_colorway", PLT_DECREASING_COLORWAY)
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self.up_colorway = line.get("up_colorway", PLT_INCREASING_COLORWAY)
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def get_colors(self, reverse: bool = False) -> list:
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"""Get colors for the plot.
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Parameters
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----------
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reverse : bool, optional
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Whether to reverse the colors, by default False
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Returns
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-------
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list
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List of colors e.g. ["#00ACFF", "#FF0000"]
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"""
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colors = (
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self.plotly_template.get("layout", {}).get("colorway", PLT_COLORWAY).copy()
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)
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if reverse:
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colors.reverse()
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return colors
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theme = TerminalStyle(
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get_current_user().preferences.CHART_STYLE,
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get_current_user().preferences.RICH_STYLE,
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)
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# pylint: disable=R0913
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class OpenBBFigure(go.Figure):
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"""Custom Figure class for OpenBB Terminal.
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Parameters
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----------
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fig : `go.Figure`, optional
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Figure to copy, by default None
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has_subplots : `bool`, optional
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Whether the figure has subplots, by default False
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**kwargs
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Keyword arguments to pass to `go.Figure.update_layout`
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Class Methods
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-------------
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create_subplots(rows: `int`, cols: `int`, **kwargs) -> `OpenBBFigure`
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Creates a subplots figure
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to_table(data: `pd.DataFrame`, columnwidth: `list`, print_index: `bool`, ...)
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Converts a DataFrame to a table figure
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Methods
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-------
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add_hline_legend(y: `float`, name: `str`, line: `dict`, legendrank: `int`, **kwargs)
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Adds a horizontal line with a legend label
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add_vline_legend(x: `float`, name: `str`, line: `dict`, legendrank: `int`, **kwargs)
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Adds a vertical line with a legend label
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add_legend_label(trace: `str`, label: `str`, mode: `str`, marker: `dict`, **kwargs)
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Adds a legend label
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add_histplot(x: `list`, name: `str`, colors: `list`, bins: `int`, show_curve: `str`, ...)
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Adds a histogram plot
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horizontal_legend(x: `float`, y: `float`, xanchor: `str`, yanchor: `str`, ...)
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Moves the legend to a horizontal position
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to_subplot(subplot: `OpenBBFigure`, row: `int`, col: `int`, secondary_y: `bool`, ...)
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Returns the figure as a subplot of another figure
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"""
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plotlyjs_path: Path = PLOTLYJS_PATH
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def __init__(self, fig: Optional[go.Figure] = None, **kwargs) -> None:
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super().__init__()
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if fig is None and config_terminal.current_figure and config_terminal.HOLD:
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fig = config_terminal.current_figure
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if fig:
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self.__dict__ = fig.__dict__
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self._has_secondary_y = kwargs.pop("has_secondary_y", False)
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self._subplots_kwargs: Dict[str, Any] = kwargs.pop("subplots_kwargs", {})
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self._multi_rows = kwargs.pop("multi_rows", False)
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self._added_logscale = False
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self._date_xaxs: dict = {}
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self._margin_adjusted = False
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self._feature_flags_applied = False
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self._exported = False
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self._cmd_xshift = 0
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self._bar_width = 0.15
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self._export_image: Optional[Union[Path, str]] = ""
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self._subplot_xdates: Dict[int, Dict[int, List[Any]]] = {}
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fig = config_terminal.get_current_figure()
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if fig is None and config_terminal.HOLD:
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config_terminal.append_legend(config_terminal.last_legend)
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if fig is not None:
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traces = len(fig.data)
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self.update_layout(
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{f"yaxis{traces+1}": dict(title=kwargs.pop("yaxis_title", ""))}
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)
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config_terminal.append_legend(config_terminal.last_legend)
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if xaxis := kwargs.pop("xaxis", None):
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self.update_xaxes(xaxis)
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if yaxis := kwargs.pop("yaxis", None):
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self.update_yaxes(yaxis)
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self.update_layout(**kwargs)
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if plots_backend().isatty:
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self.update_layout(
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margin=dict(l=0, r=0, t=0, b=0, pad=0, autoexpand=True),
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height=plots_backend().HEIGHT,
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width=plots_backend().WIDTH,
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)
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def set_secondary_axis(
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self, title: str, row: Optional[int] = None, col: Optional[int] = None, **kwargs
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) -> "OpenBBFigure":
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"""Set secondary axis.
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Parameters
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----------
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title : str
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Title of the axis
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row : int, optional
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Row of the axis, by default None
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col : int, optional
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Column of the axis, by default None
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**kwargs
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Keyword arguments to pass to go.Figure.update_layout
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"""
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axis = "yaxis"
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title = kwargs.pop("title", "")
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if (fig := config_terminal.get_current_figure()) is not None:
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total_axes = max(2, len(list(fig.select_yaxes())))
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axis = f"yaxis{total_axes+1}"
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if config_terminal.make_new_axis():
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kwargs["side"] = "left"
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kwargs.pop("secondary_y", None)
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return self.update_layout(**{axis: dict(title=title, **kwargs)})
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return self.update_yaxes(title=title, row=row, col=col, **kwargs)
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@property
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def subplots_kwargs(self):
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"""Get subplots kwargs property."""
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return self._subplots_kwargs
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@subplots_kwargs.setter
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def subplots_kwargs(self, value):
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"""Get subplots kwargs setter."""
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self._subplots_kwargs = value
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@property
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def has_subplots(self):
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"""Has subplots property."""
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return self._has_subplots()
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@property
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def bar_width(self):
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"""Bar width property."""
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return self._bar_width
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@bar_width.setter
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def bar_width(self, value):
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"""Bar width setter."""
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self._bar_width = value
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@property
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def cmd_xshift(self):
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"""Command line x shift property."""
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return self._cmd_xshift
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@cmd_xshift.setter
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def cmd_xshift(self, value):
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"""Command line x shift setter."""
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self._cmd_xshift = value
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@classmethod
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def create_subplots(
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cls,
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rows: int = 1,
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cols: int = 1,
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shared_xaxes: bool = True,
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vertical_spacing: Optional[float] = None,
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horizontal_spacing: Optional[float] = None,
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subplot_titles: Optional[Union[List[str], tuple]] = None,
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row_width: Optional[List[Union[float, int]]] = None,
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specs: Optional[List[List[Optional[Dict[Any, Any]]]]] = None,
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**kwargs,
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) -> "OpenBBFigure":
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"""Create a new Plotly figure with subplots.
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Parameters
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----------
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rows : `int`, optional
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Number of rows, by default 1
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cols : `int`, optional
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Number of columns, by default 1
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shared_xaxes : `bool`, optional
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Whether to share x axes, by default True
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vertical_spacing : `float`, optional
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Vertical spacing between subplots, by default None
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horizontal_spacing : `float`, optional
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Horizontal spacing between subplots, by default None
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subplot_titles : `Union[List[str], tuple]`, optional
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Titles for each subplot, by default None
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row_width : `List[Union[float, int]]`, optional
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Width of each row, by default [1]
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specs : `List[List[dict]]`, optional
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Subplot specs, by default `[[{}] * cols] * rows` (all subplots are the same size)
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"""
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# We save the original kwargs to store them in the figure for later use
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subplots_kwargs = dict(
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rows=rows,
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cols=cols,
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shared_xaxes=shared_xaxes,
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vertical_spacing=vertical_spacing,
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horizontal_spacing=horizontal_spacing,
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subplot_titles=subplot_titles,
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row_width=row_width or [1] * rows,
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specs=specs or [[{}] * cols] * rows,
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**kwargs,
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)
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fig = make_subplots(**subplots_kwargs)
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kwargs = {
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"multi_rows": rows > 1,
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"subplots_kwargs": subplots_kwargs,
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}
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if specs and any(
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spec.get("secondary_y", False) for row in specs for spec in row if spec
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):
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kwargs["has_secondary_y"] = True
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return cls(fig, **kwargs)
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def add_trend(
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self,
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data: pd.DataFrame,
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row: int = 1,
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col: int = 1,
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secondary_y: bool = False,
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**kwargs,
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):
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"""Add a trend line to the figure.
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|
|
|
Parameters
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|
----------
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data : `pd.DataFrame`
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Data to plot
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row : `int`, optional
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Row number, by default 1
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col : `int`, optional
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Column number, by default 1
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secondary_y : `bool`, optional
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Whether to plot on secondary y axis, by default None
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"""
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try:
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for column, color in zip(
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["OC_High_trend", "OC_Low_trend"], [theme.up_color, theme.down_color]
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):
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if column in data.columns:
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name = column.split("_")[1].title()
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trend = data.copy().dropna()
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self.add_shape(
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type="line",
|
|
name=f"{name} Trend",
|
|
x0=trend.index[0],
|
|
y0=trend[column].iloc[0],
|
|
x1=trend.index[-1],
|
|
y1=trend[column].iloc[-1],
|
|
line=dict(color=color, width=2),
|
|
row=row,
|
|
col=col,
|
|
secondary_y=secondary_y,
|
|
**kwargs,
|
|
)
|
|
|
|
except Exception:
|
|
console.print("[red]Error adding trend line[/red]")
|
|
|
|
def add_histplot(
|
|
self,
|
|
dataset: Union[np.ndarray, pd.Series, TimeSeriesT],
|
|
name: Optional[Union[str, List[str]]] = None,
|
|
colors: Optional[List[str]] = None,
|
|
bins: Union[int, str] = 15,
|
|
curve: Literal["normal", "kde"] = "normal",
|
|
show_curve: bool = True,
|
|
show_rug: bool = True,
|
|
show_hist: bool = True,
|
|
forecast: bool = False,
|
|
row: int = 1,
|
|
col: int = 1,
|
|
) -> None:
|
|
"""Add a histogram with a curve and rug plot if desired.
|
|
|
|
Parameters
|
|
----------
|
|
dataset : `Union[np.ndarray, pd.Series, TimeSeriesT]`
|
|
Data to plot
|
|
name : `Optional[Union[str, List[str]]]`, optional
|
|
Name of the plot, by default None
|
|
colors : `Optional[List[str]]`, optional
|
|
Colors of the plot, by default None
|
|
bins : `Union[int, str]`, optional
|
|
Number of bins, by default 15
|
|
curve : `Literal["normal", "kde"]`, optional
|
|
Type of curve to plot, by default "normal"
|
|
show_curve : `bool`, optional
|
|
Whether to show the curve, by default True
|
|
show_rug : `bool`, optional
|
|
Whether to show the rug plot, by default True
|
|
show_hist : `bool`, optional
|
|
Whether to show the histogram, by default True
|
|
forecast : `bool`, optional
|
|
Whether the data is a darts forecast TimeSeries, by default False
|
|
row : `int`, optional
|
|
Row of the subplot, by default 1
|
|
col : `int`, optional
|
|
Column of the subplot, by default 1
|
|
"""
|
|
callback = stats.norm if curve == "normal" else stats.gaussian_kde
|
|
|
|
def _validate_x(data: Union[np.ndarray, pd.Series, type[TimeSeriesT]]):
|
|
if forecast:
|
|
data = data.univariate_values() # type: ignore
|
|
if isinstance(data, pd.Series):
|
|
data = data.values
|
|
if isinstance(data, np.ndarray):
|
|
data = data.tolist()
|
|
if isinstance(data, list):
|
|
data = [data]
|
|
|
|
return data
|
|
|
|
valid_x = _validate_x(dataset)
|
|
|
|
if isinstance(name, str):
|
|
name = [name]
|
|
|
|
if isinstance(colors, str):
|
|
colors = [colors]
|
|
if not name:
|
|
name = [None] * len(valid_x) # type: ignore
|
|
if not colors:
|
|
colors = [None] * len(valid_x) # type: ignore
|
|
|
|
max_y = 0
|
|
for i0, (x_i, name_i, color_i) in enumerate(zip(valid_x, name, colors)):
|
|
if not color_i:
|
|
color_i = ( # noqa: PLW2901
|
|
theme.up_color if i0 % 2 == 0 else theme.down_color
|
|
)
|
|
|
|
res_mean, res_std = np.mean(x_i), np.std(x_i)
|
|
res_min, res_max = min(x_i), max(x_i)
|
|
x = np.linspace(res_min, res_max, 100)
|
|
if show_hist:
|
|
if forecast:
|
|
components = list(dataset.components[:4]) # type: ignore
|
|
values = (
|
|
dataset[components].all_values(copy=False).flatten(order="F") # type: ignore
|
|
)
|
|
n_components = len(components)
|
|
n_entries = len(values) // n_components
|
|
for i, label in zip(range(n_components), components):
|
|
self.add_histogram(
|
|
x=values[i * n_entries : (i + 1) * n_entries], # noqa: E203
|
|
name=label,
|
|
marker_color=color_i,
|
|
nbinsx=bins,
|
|
opacity=0.7,
|
|
row=row,
|
|
col=col,
|
|
)
|
|
else:
|
|
self.add_histogram(
|
|
x=x_i,
|
|
name=name_i,
|
|
marker_color=color_i,
|
|
nbinsx=bins,
|
|
histnorm="probability density",
|
|
histfunc="sum",
|
|
opacity=0.7,
|
|
row=row,
|
|
col=col,
|
|
)
|
|
|
|
if show_rug:
|
|
self.add_scatter(
|
|
x=x_i,
|
|
y=[0.00002] * len(x_i),
|
|
name=name_i if len(name) < 2 else name[1],
|
|
mode="markers",
|
|
marker=dict(
|
|
color=theme.down_color,
|
|
symbol="line-ns-open",
|
|
size=10,
|
|
),
|
|
row=row,
|
|
col=col,
|
|
)
|
|
if show_curve:
|
|
# type: ignore
|
|
if curve == "kde":
|
|
curve_x = [None] * len(valid_x)
|
|
curve_y = [None] * len(valid_x)
|
|
# pylint: disable=consider-using-enumerate
|
|
for index in range(len(valid_x)):
|
|
curve_x[index] = [ # type: ignore
|
|
res_min + xx * (res_max - res_min) / 500
|
|
for xx in range(500)
|
|
]
|
|
curve_y[index] = stats.gaussian_kde(valid_x[index])(
|
|
curve_x[index]
|
|
)
|
|
for index in range(len(valid_x)):
|
|
self.add_scatter(
|
|
x=curve_x[index], # type: ignore
|
|
y=curve_y[index], # type: ignore
|
|
name=name_i,
|
|
mode="lines",
|
|
showlegend=False,
|
|
marker=dict(color=color_i),
|
|
row=row,
|
|
col=col,
|
|
)
|
|
max_y = max(max_y, max(curve_y[index]) * 1.2) # type: ignore
|
|
|
|
else:
|
|
y = (
|
|
callback(res_mean, res_std).pdf(x)
|
|
* len(valid_x[0])
|
|
* (res_max - res_min)
|
|
/ bins
|
|
)
|
|
|
|
self.add_scatter(
|
|
x=x,
|
|
y=y,
|
|
name=name_i,
|
|
mode="lines",
|
|
marker=dict(color=color_i),
|
|
showlegend=False,
|
|
row=row,
|
|
col=col,
|
|
)
|
|
|
|
max_y = max(max_y, *(y * 2))
|
|
|
|
self.update_yaxes(
|
|
position=0.0,
|
|
range=[0, max_y],
|
|
row=row,
|
|
col=col,
|
|
automargin=False,
|
|
autorange=False,
|
|
)
|
|
|
|
self.update_layout(barmode="overlay", bargap=0.01, bargroupgap=0)
|
|
|
|
def is_image_export(self, export: Optional[str] = "") -> bool:
|
|
"""Check if the export format is an image format.
|
|
|
|
Parameters
|
|
----------
|
|
export : `str`
|
|
Export format
|
|
|
|
Returns
|
|
-------
|
|
`bool`
|
|
True if the export format is an image format, False otherwise
|
|
"""
|
|
if not export:
|
|
return False
|
|
|
|
return any(ext in export for ext in ["jpg", "pdf", "png", "svg"])
|
|
|
|
def set_title(
|
|
self, title: str, wrap: bool = False, wrap_width: int = 80, **kwargs
|
|
) -> "OpenBBFigure":
|
|
"""Set the main title of the figure.
|
|
|
|
Parameters
|
|
----------
|
|
title : `str`
|
|
Title of the figure
|
|
wrap : `bool`
|
|
If True, the title will be wrapped according to the wrap_width parameter
|
|
wrap_width : `int`
|
|
Width in characters to wrap the title if wrap is True, default is 80
|
|
"""
|
|
if wrap:
|
|
title = "<br>".join(textwrap.wrap(title, width=wrap_width))
|
|
|
|
if kwargs.get("row", None) is not None and kwargs.get("col", None) is not None:
|
|
self.add_annotation(
|
|
text=title,
|
|
xref="x domain",
|
|
yref="y domain",
|
|
x=0.5,
|
|
y=1.0,
|
|
xanchor="center",
|
|
yanchor="bottom",
|
|
**kwargs,
|
|
)
|
|
return self
|
|
|
|
self.update_layout(title=dict(text=title, **kwargs))
|
|
return self
|
|
|
|
def set_xaxis_title(
|
|
self,
|
|
title: str,
|
|
row: Optional[int] = None,
|
|
col: Optional[int] = None,
|
|
**kwargs,
|
|
) -> "OpenBBFigure":
|
|
"""Set the x axis title of the figure or subplot (if row and col are specified).
|
|
|
|
Parameters
|
|
----------
|
|
title : `str`
|
|
Title of the x axis
|
|
row : `int`, optional
|
|
Row number, by default None
|
|
col : `int`, optional
|
|
Column number, by default None
|
|
"""
|
|
self.update_xaxes(title=title, row=row, col=col, **kwargs)
|
|
return self
|
|
|
|
def set_yaxis_title(
|
|
self, title: str, row: Optional[int] = None, col: Optional[int] = None, **kwargs
|
|
) -> "OpenBBFigure":
|
|
"""Set the y axis title of the figure or subplot (if row and col are specified).
|
|
|
|
Parameters
|
|
----------
|
|
title : `str`
|
|
Title of the x axis
|
|
row : `int`, optional
|
|
Row number, by default None
|
|
col : `int`, optional
|
|
Column number, by default None
|
|
"""
|
|
self.set_secondary_axis(title=title, row=row, col=col, **kwargs)
|
|
return self
|
|
|
|
def add_hline_legend(
|
|
self,
|
|
y: float,
|
|
name: str,
|
|
line: Optional[dict] = None,
|
|
legendrank: Optional[int] = None,
|
|
**kwargs,
|
|
) -> None:
|
|
"""Add a horizontal line with a legend label.
|
|
|
|
Parameters
|
|
----------
|
|
y : `float`
|
|
y value of the line
|
|
name : `str`
|
|
Name of the to display in the legend
|
|
line : `dict`
|
|
Line style
|
|
legendrank : `int`, optional
|
|
Legend rank, by default None (e.g. 1 is above 2)
|
|
"""
|
|
if line is None:
|
|
line = {}
|
|
|
|
self.add_hline(
|
|
y,
|
|
line=line,
|
|
)
|
|
self.add_legend_label(
|
|
label=name,
|
|
mode="lines",
|
|
line_dash=line.get("dash", "solid"),
|
|
marker=dict(color=line.get("color", theme.line_color)),
|
|
legendrank=legendrank,
|
|
**kwargs,
|
|
)
|
|
|
|
def add_vline_legend(
|
|
self,
|
|
x: float,
|
|
name: str,
|
|
line: Optional[dict] = None,
|
|
legendrank: Optional[int] = None,
|
|
**kwargs,
|
|
) -> None:
|
|
"""Add a vertical line with a legend label.
|
|
|
|
Parameters
|
|
----------
|
|
x : `float`
|
|
x value of the line
|
|
name : `str`
|
|
Name of the to display in the legend
|
|
line : `dict`
|
|
Line style
|
|
legendrank : `int`, optional
|
|
Legend rank, by default None (e.g. 1 is above 2)
|
|
"""
|
|
if line is None:
|
|
line = {}
|
|
|
|
self.add_vline(
|
|
x,
|
|
line=line,
|
|
)
|
|
self.add_legend_label(
|
|
label=name,
|
|
mode="lines",
|
|
line_dash=line.get("dash", "solid"),
|
|
marker=dict(color=line.get("color", theme.line_color)),
|
|
legendrank=legendrank,
|
|
**kwargs,
|
|
)
|
|
|
|
def horizontal_legend(
|
|
self,
|
|
x: float = 1,
|
|
y: float = 1.02,
|
|
xanchor: str = "right",
|
|
yanchor: str = "bottom",
|
|
orientation: str = "h",
|
|
**kwargs,
|
|
) -> None:
|
|
"""Set the legend to be horizontal.
|
|
|
|
Parameters
|
|
----------
|
|
x : `float`, optional
|
|
The x position of the legend, by default 1
|
|
y : `float`, optional
|
|
The y position of the legend, by default 1.02
|
|
xanchor : `str`, optional
|
|
The x anchor of the legend, by default "right"
|
|
yanchor : `str`, optional
|
|
The y anchor of the legend, by default "bottom"
|
|
orientation : `str`, optional
|
|
The orientation of the legend, by default "h"
|
|
"""
|
|
self.update_layout(
|
|
legend=dict(
|
|
x=x,
|
|
y=y,
|
|
xanchor=xanchor,
|
|
yanchor=yanchor,
|
|
orientation=orientation,
|
|
**kwargs,
|
|
)
|
|
)
|
|
|
|
@staticmethod
|
|
def chart_volume_scaling(
|
|
df_volume: pd.DataFrame, volume_ticks_x: int = 7
|
|
) -> Dict[str, list]:
|
|
"""Takes df_volume and returns volume_ticks, tickvals for chart volume scaling
|
|
|
|
Parameters
|
|
----------
|
|
df_volume : pd.DataFrame
|
|
Dataframe of volume (e.g. df_volume = df["Volume"])
|
|
volume_ticks_x : int, optional
|
|
Number to multiply volume, by default 7
|
|
|
|
Returns
|
|
-------
|
|
Dict[str, list]
|
|
{"range": volume_range, "ticks": tickvals}
|
|
"""
|
|
df_volume = df_volume.apply(lambda x: f"{x:.1f}")
|
|
df_volume = pd.to_numeric(df_volume.astype(float))
|
|
|
|
if isinstance(df_volume, pd.Series):
|
|
df_volume = df_volume.to_frame()
|
|
|
|
volume_ticks = int(df_volume.max().max())
|
|
round_digits = -3
|
|
first_val = round(volume_ticks * 0.20, round_digits)
|
|
|
|
for x, y in zip([2, 5, 6, 7, 8, 9, 10], [1, 4, 5, 6, 7, 8, 9]):
|
|
if len(str(volume_ticks)) > x:
|
|
round_digits = -y
|
|
first_val = round(volume_ticks * 0.20, round_digits)
|
|
|
|
tickvals = [
|
|
floor(first_val),
|
|
floor(first_val * 2),
|
|
floor(first_val * 3),
|
|
floor(first_val * 4),
|
|
]
|
|
volume_range = [0, floor(volume_ticks * volume_ticks_x)]
|
|
|
|
return {"range": volume_range, "ticks": tickvals}
|
|
|
|
def add_inchart_volume(
|
|
self,
|
|
df_stock: pd.DataFrame,
|
|
close_col: Optional[str] = "Close",
|
|
volume_col: Optional[str] = "Volume",
|
|
row: Optional[int] = 1,
|
|
col: Optional[int] = 1,
|
|
volume_ticks_x: int = 7,
|
|
) -> None:
|
|
"""Add in-chart volume to a subplot.
|
|
|
|
Parameters
|
|
----------
|
|
df_stock : `pd.DataFrame`
|
|
Dataframe of the stock
|
|
close_col : `str`, optional
|
|
Name of the close column, by default "Close"
|
|
volume_col : `str`, optional
|
|
Name of the volume column, by default "Volume"
|
|
row : `int`, optional
|
|
Row number, by default 2
|
|
col : `int`, optional
|
|
Column number, by default 1
|
|
volume_ticks_x : int, optional
|
|
Number to multiply volume, by default 7
|
|
"""
|
|
colors = np.where(
|
|
df_stock.Open < df_stock[close_col], theme.up_color, theme.down_color
|
|
)
|
|
vol_scale = self.chart_volume_scaling(df_stock[volume_col], volume_ticks_x)
|
|
self.add_bar(
|
|
x=df_stock.index,
|
|
y=df_stock[volume_col],
|
|
name="Volume",
|
|
marker_color=colors,
|
|
yaxis="y2",
|
|
row=row,
|
|
col=col,
|
|
opacity=0.7,
|
|
secondary_y=True,
|
|
)
|
|
ticksize = 13 - (self.subplots_kwargs["rows"] // 2)
|
|
self.update_layout(
|
|
yaxis2=dict(
|
|
fixedrange=True,
|
|
side="left",
|
|
nticks=10,
|
|
range=vol_scale["range"],
|
|
tickvals=vol_scale["ticks"],
|
|
showgrid=False,
|
|
showline=False,
|
|
zeroline=False,
|
|
tickfont=dict(size=ticksize),
|
|
overlaying="y",
|
|
),
|
|
yaxis=dict(
|
|
autorange=True,
|
|
automargin=True,
|
|
side="right",
|
|
fixedrange=False,
|
|
anchor="x",
|
|
layer="above traces",
|
|
),
|
|
)
|
|
|
|
def add_legend_label(
|
|
self,
|
|
trace: Optional[str] = None,
|
|
label: Optional[str] = None,
|
|
mode: Optional[str] = None,
|
|
marker: Optional[dict] = None,
|
|
line_dash: Optional[str] = None,
|
|
legendrank: Optional[int] = None,
|
|
**kwargs,
|
|
) -> None:
|
|
"""Add a legend label.
|
|
|
|
Parameters
|
|
----------
|
|
trace : `str`, optional
|
|
The name of the trace to use as a template, by default None
|
|
label : `str`, optional
|
|
The label to use, by default None (uses the trace name if trace is specified)
|
|
If trace is not specified, label must be specified
|
|
mode : `str`, optional
|
|
The mode to use, by default "lines" (uses the trace mode if trace is specified)
|
|
marker : `dict`, optional
|
|
The marker to use, by default dict() (uses the trace marker if trace is specified)
|
|
line_dash : `str`, optional
|
|
The line dash to use, by default "solid" (uses the trace line dash if trace is specified)
|
|
legendrank : `int`, optional
|
|
The legend rank, by default None (e.g. 1 is above 2)
|
|
|
|
Raises
|
|
------
|
|
ValueError
|
|
If trace is not found
|
|
ValueError
|
|
If label is not specified and trace is not specified
|
|
"""
|
|
if trace:
|
|
for trace_ in self.data:
|
|
if trace_.name == trace:
|
|
for arg, default in zip(
|
|
[label, mode, marker, line_dash],
|
|
[trace, trace_.mode, trace_.marker, trace_.line_dash],
|
|
):
|
|
if not arg and default:
|
|
arg = default # noqa: PLW2901
|
|
|
|
kwargs.update(dict(yaxis=trace_.yaxis))
|
|
break
|
|
else:
|
|
raise ValueError(f"Trace '{trace}' not found")
|
|
|
|
if not label:
|
|
raise ValueError("Label must be specified")
|
|
|
|
self.add_scatter(
|
|
x=[None],
|
|
y=[None],
|
|
mode=mode or "lines",
|
|
name=label,
|
|
marker=marker or dict(),
|
|
line_dash=line_dash or "solid",
|
|
legendrank=legendrank,
|
|
**kwargs,
|
|
)
|
|
|
|
def show(
|
|
self,
|
|
*args,
|
|
external: bool = False,
|
|
export_image: Optional[Union[Path, str]] = "",
|
|
**kwargs,
|
|
) -> Optional["OpenBBFigure"]:
|
|
"""Show the figure.
|
|
|
|
Parameters
|
|
----------
|
|
external : `bool`, optional
|
|
Whether to return the figure object instead of showing it, by default False
|
|
export_image : `Union[Path, str]`, optional
|
|
The path to export the figure image to, by default ""
|
|
cmd_xshift : `int`, optional
|
|
The x shift of the command source annotation, by default 0
|
|
bar_width : `float`, optional
|
|
The width of the bars, by default 0.0001
|
|
date_xaxis : `bool`, optional
|
|
Whether to check if the xaxis is a date axis, by default True
|
|
"""
|
|
self.cmd_xshift = kwargs.pop("cmd_xshift", self.cmd_xshift)
|
|
self.bar_width = kwargs.pop("bar_width", self.bar_width)
|
|
self._export_image = export_image
|
|
|
|
if export_image and not plots_backend().isatty:
|
|
if isinstance(export_image, str):
|
|
export_image = Path(export_image).resolve()
|
|
export_image.touch()
|
|
|
|
if kwargs.pop("margin", True):
|
|
self._adjust_margins()
|
|
|
|
self._apply_feature_flags()
|
|
if kwargs.pop("date_xaxis", True):
|
|
self.add_rangebreaks()
|
|
self._xaxis_tickformatstops()
|
|
|
|
self.update_traces(marker_line_width=self.bar_width, selector=dict(type="bar"))
|
|
self.update_traces(
|
|
selector=dict(type="scatter", hovertemplate=None),
|
|
hovertemplate="%{y}",
|
|
)
|
|
|
|
# Set modebar style
|
|
if plots_backend().isatty:
|
|
self.update_layout( # type: ignore
|
|
newshape_line_color="gold"
|
|
if theme.mapbox_style == "dark"
|
|
else "#0d0887",
|
|
modebar=dict(
|
|
orientation="v",
|
|
bgcolor="#2A2A2A" if theme.mapbox_style == "dark" else "gray",
|
|
color="#FFFFFF" if theme.mapbox_style == "dark" else "black",
|
|
activecolor="#d1030d" if theme.mapbox_style == "dark" else "blue",
|
|
),
|
|
spikedistance=2,
|
|
hoverdistance=2,
|
|
)
|
|
|
|
if external or self._exported:
|
|
return self # type: ignore
|
|
|
|
# We check if in headless mode to return the JSON
|
|
if strtobool(get_current_system().HEADLESS):
|
|
return self.to_json()
|
|
|
|
kwargs.update(config=dict(scrollZoom=True, displaylogo=False))
|
|
if plots_backend().isatty:
|
|
try:
|
|
# We check if we need to export the image
|
|
# This is done to avoid opening after exporting
|
|
if export_image:
|
|
self._exported = True
|
|
if config_terminal.HOLD:
|
|
# pylint: disable=import-outside-toplevel
|
|
from openbb_terminal.helper_funcs import command_location
|
|
|
|
for trace in self.select_traces():
|
|
if trace.name and "/" in trace.name:
|
|
continue
|
|
trace.name = f"{trace.name} {command_location}"
|
|
config_terminal.set_current_figure(self)
|
|
# We send the figure to the backend to be displayed
|
|
return None
|
|
return plots_backend().send_figure(self, export_image)
|
|
except Exception:
|
|
# If the backend fails, we just show the figure normally
|
|
# This is a very rare case, but it's better to have a fallback
|
|
if get_current_system().DEBUG_MODE:
|
|
console.print_exception()
|
|
|
|
# We check if any figures were initialized before the backend failed
|
|
# If so, we show them with the default plotly backend
|
|
queue = plots_backend().get_pending()
|
|
for pending in queue:
|
|
fig = json.loads(pending).get("plotly", {})
|
|
if not fig:
|
|
continue
|
|
pio.show(fig, *args, **kwargs)
|
|
|
|
self.update_layout(
|
|
legend=dict(
|
|
orientation="v"
|
|
if not self.layout.legend.orientation
|
|
else self.layout.legend.orientation,
|
|
),
|
|
barmode="overlay",
|
|
bargap=0,
|
|
bargroupgap=0,
|
|
)
|
|
|
|
return pio.show(self, *args, **kwargs)
|
|
|
|
def _xaxis_tickformatstops(self) -> None:
|
|
"""Set the datetickformatstops for the xaxis if the x data is datetime."""
|
|
if (dateindex := self.get_dateindex()) is None or list(
|
|
self.select_xaxes(lambda x: hasattr(x, "tickformat") and x.tickformat)
|
|
):
|
|
return
|
|
|
|
tickformatstops = [
|
|
dict(dtickrange=[None, 86_400_000], value="%I:%M%p\n%b,%d"),
|
|
dict(dtickrange=[86_400_000, 604_800_000], value="%Y-%m-%d"),
|
|
]
|
|
xhoverformat = "%I:%M%p %Y-%m-%d"
|
|
|
|
# We check if daily data if the first and second time are the same
|
|
# since daily data will have the same time (2021-01-01 00:00:00)
|
|
if (
|
|
not hasattr(dateindex[-1], "time")
|
|
or dateindex[-1].time() == dateindex[-2].time()
|
|
):
|
|
xhoverformat = "%Y-%m-%d"
|
|
tickformatstops = [dict(dtickrange=[None, 604_800_000], value="%Y-%m-%d")]
|
|
|
|
for entry in self._date_xaxs.values():
|
|
self.update_xaxes(
|
|
tickformatstops=[
|
|
*tickformatstops,
|
|
dict(dtickrange=[604_800_000, "M1"], value="%Y-%m-%d"),
|
|
dict(dtickrange=["M1", None], value="%Y-%m-%d"),
|
|
],
|
|
type="date",
|
|
row=entry["row"],
|
|
col=entry["col"],
|
|
tick0=0.5,
|
|
)
|
|
self.update_traces(
|
|
xhoverformat=xhoverformat, selector=dict(name=entry["name"])
|
|
)
|
|
|
|
def get_subplots_dict(self) -> Dict[str, Dict[str, List[Any]]]:
|
|
"""Return the subplots dict.
|
|
|
|
Returns
|
|
-------
|
|
`dict`
|
|
The subplots dict
|
|
"""
|
|
subplots: Dict[str, Dict[str, List[Any]]] = {}
|
|
|
|
if not self.has_subplots:
|
|
return subplots
|
|
|
|
grid_ref = self._validate_get_grid_ref() # pylint: disable=protected-access
|
|
for r, plot_row in enumerate(grid_ref):
|
|
for c, plot_refs in enumerate(plot_row):
|
|
if not plot_refs:
|
|
continue
|
|
for subplot_ref in plot_refs:
|
|
if subplot_ref.subplot_type == "xy":
|
|
xaxis, yaxis = subplot_ref.layout_keys
|
|
xref = xaxis.replace("axis", "")
|
|
yref = yaxis.replace("axis", "")
|
|
row = r + 1
|
|
col = c + 1
|
|
subplots.setdefault(xref, {}).setdefault(yref, []).append(
|
|
(row, col)
|
|
)
|
|
|
|
return subplots
|
|
|
|
def get_dateindex(self) -> Optional[List[datetime]]:
|
|
"""Return the dateindex of the figure.
|
|
|
|
Returns
|
|
-------
|
|
`list`
|
|
The dateindex
|
|
"""
|
|
output: Optional[List[datetime]] = None
|
|
subplots = self.get_subplots_dict()
|
|
|
|
try:
|
|
false_y = list(self.select_traces(secondary_y=False))
|
|
true_y = list(self.select_traces(secondary_y=True))
|
|
except Exception:
|
|
false_y = []
|
|
true_y = []
|
|
|
|
for trace in self.select_traces():
|
|
if not hasattr(trace, "xaxis"):
|
|
continue
|
|
xref, yref = trace.xaxis, trace.yaxis
|
|
row, col = subplots.get(xref, {}).get(yref, [(None, None)])[0]
|
|
|
|
if trace.x is not None and len(trace.x) > 5:
|
|
for x in trace.x[:2]:
|
|
if isinstance(x, (datetime, np.datetime64, pd.DatetimeIndex)):
|
|
output = trace.x
|
|
name = trace.name if hasattr(trace, "name") else f"{trace}"
|
|
|
|
secondary_y: Optional[bool] = trace in true_y
|
|
if trace not in (false_y + true_y):
|
|
secondary_y = None
|
|
|
|
self._date_xaxs[trace.xaxis] = {
|
|
"yaxis": trace.yaxis,
|
|
"name": name,
|
|
"row": row,
|
|
"col": col,
|
|
"secondary_y": secondary_y,
|
|
}
|
|
self._subplot_xdates.setdefault(row, {}).setdefault(
|
|
col, []
|
|
).append(trace.x)
|
|
|
|
# We convert the dateindex to a list of datetime objects if it's a numpy array
|
|
if output is not None and isinstance(output[0], np.datetime64):
|
|
output = (
|
|
pd.to_datetime(output).to_pydatetime().astype("datetime64[ms]").tolist()
|
|
)
|
|
|
|
return output
|
|
|
|
def hide_date_gaps(
|
|
self,
|
|
df_data: pd.DataFrame,
|
|
row: Optional[int] = None,
|
|
col: Optional[int] = None,
|
|
) -> None:
|
|
"""Add rangebreaks to hide datetime gaps on the xaxis.
|
|
|
|
Parameters
|
|
----------
|
|
df_data : `pandas.DataFrame`
|
|
The dataframe with the data.
|
|
row : `int`, optional
|
|
The row of the subplot to hide the gaps, by default None
|
|
col : `int`, optional
|
|
The column of the subplot to hide the gaps, by default None
|
|
"""
|
|
# We get the min and max dates
|
|
dt_start, dt_end = df_data.index.min(), df_data.index.max()
|
|
rangebreaks: List[Dict[str, Any]] = []
|
|
|
|
# if weekly or monthly data, we don't need to hide gaps
|
|
# this prevents distortions in the plot
|
|
check_freq = df_data.index.to_series().diff(-5).dt.days.abs().mode().iloc[0]
|
|
if check_freq > 7:
|
|
return
|
|
|
|
# We get the missing days
|
|
is_daily = df_data.index[-1].time() == df_data.index[-2].time()
|
|
dt_days = pd.date_range(start=dt_start, end=dt_end, normalize=True)
|
|
|
|
# We get the dates that are missing
|
|
dt_missing_days = list(
|
|
set(dt_days.strftime("%Y-%m-%d")) - set(df_data.index.strftime("%Y-%m-%d"))
|
|
)
|
|
dt_missing_days = pd.to_datetime(dt_missing_days)
|
|
|
|
if len(dt_missing_days) < 2_000:
|
|
rangebreaks = [dict(values=dt_missing_days)]
|
|
|
|
df_data = df_data.sort_index()
|
|
# We add a rangebreak if the first and second time are not the same
|
|
# since daily data will have the same time (00:00)
|
|
if not is_daily:
|
|
for i in range(len(df_data) - 1):
|
|
if df_data.index[i + 1] - df_data.index[i] > timedelta(hours=2):
|
|
rangebreaks.insert(
|
|
0,
|
|
dict(
|
|
bounds=[
|
|
df_data.index[i]
|
|
+ timedelta(minutes=60 - df_data.index[i].minute),
|
|
df_data.index[i + 1],
|
|
]
|
|
),
|
|
)
|
|
|
|
self.update_xaxes(rangebreaks=rangebreaks, row=row, col=col)
|
|
|
|
def add_rangebreaks(self) -> None:
|
|
"""Add rangebreaks to hide datetime gaps on the xaxis."""
|
|
if self.get_dateindex() is None:
|
|
return
|
|
|
|
for row, row_dict in self._subplot_xdates.items():
|
|
for col, values in row_dict.items():
|
|
try:
|
|
x_values = (
|
|
pd.to_datetime(np.concatenate(values))
|
|
.to_pydatetime()
|
|
.astype("datetime64[ms]")
|
|
)
|
|
self.hide_date_gaps(
|
|
pd.DataFrame(index=x_values.tolist()),
|
|
row=row,
|
|
col=col,
|
|
)
|
|
except ValueError:
|
|
continue
|
|
|
|
def to_subplot(
|
|
self,
|
|
subplot: "OpenBBFigure",
|
|
row: int,
|
|
col: int,
|
|
secondary_y: bool = False,
|
|
**kwargs,
|
|
) -> "OpenBBFigure":
|
|
"""Return the figure as a subplot of another figure.
|
|
|
|
Parameters
|
|
----------
|
|
subplot : `plotly.graph_objects.Figure`
|
|
The subplot
|
|
row : `int`
|
|
Row number
|
|
col : `int`
|
|
Column number
|
|
secondary_y : `bool`, optional
|
|
Whether to use the secondary y axis, by default False
|
|
|
|
Returns
|
|
-------
|
|
`plotly.graph_objects.Figure`
|
|
The subplot with the figure added
|
|
"""
|
|
for trace in self.data:
|
|
if kwargs:
|
|
trace.update(**kwargs)
|
|
|
|
subplot.add_trace(trace, row=row, col=col, secondary_y=secondary_y)
|
|
subplot.set_xaxis_title(self.layout.xaxis.title.text, row=row, col=col)
|
|
subplot.set_yaxis_title(self.layout.yaxis.title.text, row=row, col=col)
|
|
|
|
return subplot
|
|
|
|
def to_html(self, *args, **kwargs) -> str:
|
|
"""Return the figure as HTML."""
|
|
self.update_traces(marker_line_width=0.0001, selector=dict(type="bar"))
|
|
kwargs.update(
|
|
dict(
|
|
config={"scrollZoom": True, "displaylogo": False},
|
|
include_plotlyjs=kwargs.pop("include_plotlyjs", False),
|
|
full_html=False,
|
|
)
|
|
)
|
|
self._apply_feature_flags()
|
|
self._xaxis_tickformatstops()
|
|
|
|
if not plots_backend().isatty and self.data[0].type != "table":
|
|
for key, max_val in zip(["l", "r", "b", "t"], [60, 60, 80, 40]):
|
|
if key in self.layout.margin and (
|
|
self.layout.margin[key] is None
|
|
or (self.layout.margin[key] > max_val)
|
|
):
|
|
self.layout.margin[key] = max_val
|
|
|
|
orientation = "v" if self.layout.legend.orientation is None else "h"
|
|
|
|
for annotation in self.select_annotations(
|
|
selector=dict(x=0, xanchor="right")
|
|
):
|
|
annotation.font.size = (
|
|
annotation.font.size - 1.8 if annotation.font.size else 10
|
|
)
|
|
|
|
for trace in self.select_traces(
|
|
lambda trace: hasattr(trace, "legend") and trace.legend is not None
|
|
):
|
|
if trace.legend in self.layout:
|
|
self.layout[trace.legend].font.size = 12
|
|
|
|
self.update_layout(
|
|
legend=dict(orientation=orientation, font=dict(size=12)),
|
|
font=dict(size=14),
|
|
)
|
|
self.update_xaxes(tickfont=dict(size=13))
|
|
self.update_yaxes(tickfont=dict(size=13))
|
|
|
|
return super().to_html(*args, **kwargs)
|
|
|
|
@staticmethod
|
|
def row_colors(data: pd.DataFrame) -> Optional[List[str]]:
|
|
"""Return the row colors of the table.
|
|
|
|
Parameters
|
|
----------
|
|
data : `pandas.DataFrame`
|
|
The dataframe
|
|
|
|
Returns
|
|
-------
|
|
`list`
|
|
The list of colors
|
|
"""
|
|
row_count = len(data)
|
|
# we determine how many rows in `data` and then create a list with alternating
|
|
# row colors
|
|
row_odd_count = floor(row_count / 2) + row_count % 2
|
|
row_even_count = floor(row_count / 2)
|
|
odd_list = [PLT_TBL_ROW_COLORS[0]] * row_odd_count
|
|
even_list = [PLT_TBL_ROW_COLORS[1]] * row_even_count
|
|
color_list = [x for y in zip(odd_list, even_list) for x in y]
|
|
if row_odd_count > row_even_count:
|
|
color_list.append(PLT_TBL_ROW_COLORS[0])
|
|
|
|
return color_list
|
|
|
|
@staticmethod
|
|
def _tbl_values(data: pd.DataFrame, print_index: bool) -> Tuple[List[str], List]:
|
|
"""Return the values of the table.
|
|
|
|
Parameters
|
|
----------
|
|
data : `pandas.DataFrame`
|
|
The dataframe to convert
|
|
print_index : `bool`
|
|
Whether to print the index
|
|
|
|
Returns
|
|
-------
|
|
`tuple`
|
|
The header values and the cell values
|
|
"""
|
|
if print_index:
|
|
header_values = list(
|
|
[data.index.name if data.index.name is not None else "", *data.columns]
|
|
)
|
|
cell_values = [data.index, *[data[col] for col in data]]
|
|
|
|
else:
|
|
header_values = data.columns.to_list()
|
|
cell_values = [data[col] for col in data]
|
|
|
|
header_values = [f"<b>{x}</b>" for x in header_values]
|
|
|
|
return header_values, cell_values
|
|
|
|
@classmethod
|
|
def to_table(
|
|
cls,
|
|
data: pd.DataFrame,
|
|
columnwidth: Optional[List[Union[int, float]]] = None,
|
|
print_index: bool = True,
|
|
**kwargs,
|
|
) -> "OpenBBFigure":
|
|
"""Convert a dataframe to a table figure.
|
|
|
|
Parameters
|
|
----------
|
|
data : `pandas.DataFrame`
|
|
The dataframe to convert
|
|
columnwidth : `list`, optional
|
|
The width of each column, by default None (auto)
|
|
print_index : `bool`, optional
|
|
Whether to print the index, by default True
|
|
height : `int`, optional
|
|
The height of the table, by default len(data.index) * 28 + 25
|
|
width : `int`, optional
|
|
The width of the table, by default sum(columnwidth) * 8.7
|
|
|
|
Returns
|
|
-------
|
|
`plotly.graph_objects.Figure`
|
|
The figure as a table
|
|
"""
|
|
if not columnwidth:
|
|
# we get the length of each column using the max length of the column
|
|
# name and the max length of the column values as the column width
|
|
columnwidth = [
|
|
max(len(str(data[col].name)), data[col].astype(str).str.len().max())
|
|
for col in data.columns
|
|
]
|
|
# we add the length of the index column if we are printing the index
|
|
if print_index:
|
|
columnwidth.insert(
|
|
0,
|
|
max(
|
|
len(str(data.index.name)),
|
|
data.index.astype(str).str.len().max(),
|
|
),
|
|
)
|
|
|
|
# we add a percentage of max to the min column width
|
|
columnwidth = [
|
|
int(x + (max(columnwidth) - min(columnwidth)) * 0.2)
|
|
for x in columnwidth
|
|
]
|
|
|
|
header_values, cell_values = cls._tbl_values(data, print_index)
|
|
|
|
if (height := kwargs.get("height", None)) and height < len(
|
|
data.index
|
|
) * 28 + 25:
|
|
kwargs.pop("height")
|
|
if (width := kwargs.get("width", None)) and width < sum(columnwidth) * 8.7:
|
|
kwargs.pop("width")
|
|
|
|
height = kwargs.pop("height", len(data.index) * 28 + 25)
|
|
width = kwargs.pop("width", sum(columnwidth) * 8.7)
|
|
|
|
fig: OpenBBFigure = cls()
|
|
fig.add_table(
|
|
header=dict(values=header_values),
|
|
cells=dict(
|
|
values=cell_values,
|
|
align="left",
|
|
height=25,
|
|
),
|
|
columnwidth=columnwidth,
|
|
**kwargs,
|
|
)
|
|
fig.update_layout(
|
|
height=height,
|
|
width=width,
|
|
template="openbb_tables",
|
|
margin=dict(l=0, r=0, b=0, t=0, pad=0),
|
|
font=dict(size=14),
|
|
)
|
|
|
|
return fig
|
|
|
|
def _adjust_margins(self) -> None:
|
|
"""Adjust the margins of the figure."""
|
|
if self._margin_adjusted:
|
|
return
|
|
|
|
margin_add = (
|
|
dict(l=80, r=60, b=80, t=40, pad=0)
|
|
if not self._has_secondary_y or not self.has_subplots
|
|
else dict(l=60, r=50, b=85, t=40, pad=0)
|
|
)
|
|
|
|
# We adjust margins
|
|
if plots_backend().isatty:
|
|
for key in ["l", "r", "b", "t", "pad"]:
|
|
if key in self.layout.margin and self.layout.margin[key] is not None:
|
|
self.layout.margin[key] += margin_add.get(key, 0)
|
|
else:
|
|
self.layout.margin[key] = margin_add.get(key, 0)
|
|
|
|
if not plots_backend().isatty:
|
|
org_margin = self.layout.margin
|
|
margin = dict(l=40, r=60, b=80, t=50)
|
|
for key, max_val in zip(["l", "r", "b", "t"], [60, 50, 80, 50]):
|
|
org = org_margin[key] or 0
|
|
if (org + margin[key]) > max_val:
|
|
self.layout.margin[key] = max_val
|
|
else:
|
|
self.layout.margin[key] = org + margin[key]
|
|
|
|
self._margin_adjusted = True
|
|
|
|
def _set_watermark(self) -> None:
|
|
"""Set the watermark for OpenBB Terminal."""
|
|
if (
|
|
not plots_backend().isatty
|
|
or not get_current_user().preferences.PLOT_ENABLE_PYWRY
|
|
or isinstance(self._export_image, Path)
|
|
and self._export_image.suffix in [".svg", ".pdf"]
|
|
):
|
|
self.add_annotation(
|
|
yref="paper",
|
|
xref="paper",
|
|
x=1,
|
|
y=0,
|
|
showarrow=False,
|
|
text="OpenBB Terminal",
|
|
font_size=17,
|
|
font_color="gray",
|
|
opacity=0.5,
|
|
xanchor="right",
|
|
yanchor="bottom",
|
|
yshift=-80,
|
|
xshift=40,
|
|
)
|
|
|
|
# pylint: disable=import-outside-toplevel
|
|
def _add_cmd_source(self) -> None:
|
|
"""Set the watermark for OpenBB Terminal."""
|
|
from openbb_terminal.helper_funcs import command_location
|
|
|
|
if command_location:
|
|
yaxis = self.layout.yaxis
|
|
yaxis2 = self.layout.yaxis2 if hasattr(self.layout, "yaxis2") else None
|
|
xshift = -70 if yaxis.side == "right" else -80
|
|
|
|
if self.layout.margin["l"] > 100:
|
|
xshift -= 50 if self._added_logscale else 40
|
|
|
|
if (
|
|
yaxis2
|
|
and (yaxis.title.text and yaxis2.title.text)
|
|
and (yaxis.side == "left" or yaxis2.side == "left")
|
|
):
|
|
self.layout.margin["l"] += 20
|
|
|
|
if (yaxis2 and yaxis2.side == "left") or yaxis.side == "left":
|
|
title = (
|
|
yaxis.title.text
|
|
if not yaxis2 or yaxis2.side != "left"
|
|
else yaxis2.title.text
|
|
)
|
|
xshift = -110 if not title else -135
|
|
self.layout.margin["l"] += 60
|
|
|
|
self.add_annotation(
|
|
x=0,
|
|
y=0.5,
|
|
yref="paper",
|
|
xref="paper",
|
|
text=command_location,
|
|
textangle=-90,
|
|
font_size=24,
|
|
font_color="gray" if theme.mapbox_style == "dark" else "black",
|
|
opacity=0.5,
|
|
yanchor="middle",
|
|
xanchor="left",
|
|
xshift=xshift + self.cmd_xshift,
|
|
)
|
|
|
|
# pylint: disable=import-outside-toplevel
|
|
def _apply_feature_flags(self) -> None:
|
|
"""Apply watermark and command source annotations."""
|
|
if self._feature_flags_applied:
|
|
return
|
|
|
|
self._add_cmd_source()
|
|
self._set_watermark()
|
|
|
|
self._feature_flags_applied = True
|
|
|
|
def add_logscale_menus(self, yaxis: str = "yaxis") -> None:
|
|
"""Set the menus for the figure."""
|
|
self._added_logscale = True
|
|
bg_color = "#000000" if theme.mapbox_style == "dark" else "#FFFFFF" # type: ignore
|
|
font_color = "#FFFFFF" if theme.mapbox_style == "dark" else "#000000" # type: ignore
|
|
self.update_layout(
|
|
xaxis=dict(
|
|
rangeslider=dict(visible=False),
|
|
rangeselector=dict(
|
|
bgcolor=bg_color,
|
|
font=dict(color=font_color),
|
|
buttons=list(
|
|
[
|
|
dict(
|
|
count=1,
|
|
label="1M",
|
|
step="month",
|
|
stepmode="backward",
|
|
),
|
|
dict(
|
|
count=3,
|
|
label="3M",
|
|
step="month",
|
|
stepmode="backward",
|
|
),
|
|
dict(count=1, label="YTD", step="year", stepmode="todate"),
|
|
dict(
|
|
count=1,
|
|
label="1y",
|
|
step="year",
|
|
stepmode="backward",
|
|
),
|
|
dict(step="all"),
|
|
]
|
|
),
|
|
),
|
|
),
|
|
bargap=0,
|
|
bargroupgap=0,
|
|
)
|
|
|
|
self.update_layout(
|
|
updatemenus=[
|
|
dict(
|
|
bgcolor=bg_color,
|
|
font=dict(color=font_color, size=14),
|
|
buttons=[
|
|
dict(
|
|
label="linear ",
|
|
method="relayout",
|
|
args=[{f"{yaxis}.type": "linear"}],
|
|
),
|
|
dict(
|
|
label="log",
|
|
method="relayout",
|
|
args=[{f"{yaxis}.type": "log"}],
|
|
),
|
|
],
|
|
y=1.07,
|
|
x=-0.01,
|
|
)
|
|
],
|
|
)
|
|
|
|
def add_corr_plot(
|
|
self,
|
|
series: pd.DataFrame,
|
|
max_lag: int = 20,
|
|
m: Optional[int] = None,
|
|
alpha: Optional[float] = 0.05,
|
|
marker: Optional[dict] = None,
|
|
row: Optional[int] = None,
|
|
col: Optional[int] = None,
|
|
pacf: bool = False,
|
|
**kwargs,
|
|
) -> None:
|
|
"""Add a correlation plot to a figure object.
|
|
|
|
Parameters
|
|
----------
|
|
fig : OpenBBFigure
|
|
Figure object to add plot to
|
|
series : pd.DataFrame
|
|
Dataframe to look at
|
|
max_lag : int, optional
|
|
Number of lags to look at, by default 15
|
|
m: Optional[int]
|
|
Optionally, a time lag to highlight on the plot. Default is none.
|
|
alpha: Optional[float]
|
|
Optionally, a significance level to highlight on the plot. Default is 0.05.
|
|
row : int, optional
|
|
Row to add plot to, by default None
|
|
col : int, optional
|
|
Column to add plot to, by default None
|
|
pacf : bool, optional
|
|
Flag to indicate whether to use partial autocorrelation or not, by default False
|
|
"""
|
|
mode = "markers+lines" if marker else "lines"
|
|
line = kwargs.pop("line", None)
|
|
|
|
def _prepare_data_corr_plot(x, lags):
|
|
zero = True
|
|
irregular = False
|
|
if lags is None:
|
|
# GH 4663 - use a sensible default value
|
|
nobs = x.shape[0]
|
|
lim = min(int(np.ceil(10 * np.log10(nobs))), nobs - 1)
|
|
lags = np.arange(not zero, lim + 1)
|
|
elif np.isscalar(lags):
|
|
lags = np.arange(not zero, int(lags) + 1) # +1 for zero lag
|
|
else:
|
|
irregular = True
|
|
lags = np.asanyarray(lags).astype(int)
|
|
nlags = lags.max(0)
|
|
|
|
return lags, nlags, irregular
|
|
|
|
lags, nlags, irregular = _prepare_data_corr_plot(series, max_lag)
|
|
|
|
callback = sm.tsa.stattools.pacf if pacf else sm.tsa.stattools.acf
|
|
if not pacf:
|
|
kwargs.update(dict(fft=False))
|
|
|
|
acf_x = callback(
|
|
series,
|
|
nlags=nlags,
|
|
alpha=alpha,
|
|
**kwargs,
|
|
)
|
|
|
|
acf_x, confint = acf_x[:2] if not pacf else acf_x
|
|
|
|
if irregular:
|
|
acf_x = acf_x[lags]
|
|
|
|
try:
|
|
confint = confint[lags]
|
|
if lags[0] == 0:
|
|
lags = lags[1:]
|
|
confint = confint[1:]
|
|
acf_x = acf_x[1:]
|
|
lags = lags.astype(float)
|
|
lags[0] -= 0.5
|
|
lags[-1] += 0.5
|
|
|
|
upp_band = confint[:, 0] - acf_x
|
|
low_band = confint[:, 1] - acf_x
|
|
|
|
# pylint: disable=C0200
|
|
for x in range(len(acf_x)):
|
|
self.add_scatter(
|
|
x=(x, x),
|
|
y=(0, acf_x[x]),
|
|
mode=mode,
|
|
marker=marker,
|
|
line=line,
|
|
line_width=(2 if m is not None and x == m else 1),
|
|
row=row,
|
|
col=col,
|
|
)
|
|
|
|
self.add_scatter(
|
|
x=lags,
|
|
y=upp_band,
|
|
mode="lines",
|
|
line_color="rgba(0, 0, 0, 0)",
|
|
opacity=0,
|
|
row=row,
|
|
col=col,
|
|
)
|
|
|
|
self.add_scatter(
|
|
x=lags,
|
|
y=low_band,
|
|
mode="lines",
|
|
fillcolor="rgba(255, 217, 0, 0.30)",
|
|
fill="tonexty",
|
|
line_color="rgba(0, 0, 0, 0.0)",
|
|
opacity=0,
|
|
row=row,
|
|
col=col,
|
|
)
|
|
self.add_scatter(
|
|
x=[0, max_lag + 1],
|
|
y=[0, 0],
|
|
mode="lines",
|
|
line_color="white",
|
|
row=row,
|
|
col=col,
|
|
)
|
|
self.update_traces(showlegend=False)
|
|
|
|
except ValueError:
|
|
pass
|