mirror of
https://github.com/OpenBB-finance/OpenBB.git
synced 2026-10-29 21:42:22 +00:00
2cb229f35e
* spacing before and after rich tables * fix menus to have standard UI * fix tests * fix tests * fix tests
143 lines
4.3 KiB
Python
143 lines
4.3 KiB
Python
"""FinBrain View Module"""
|
|
__docformat__ = "numpy"
|
|
|
|
import logging
|
|
import os
|
|
from typing import Optional, List
|
|
|
|
import numpy as np
|
|
import pandas as pd
|
|
from matplotlib import pyplot as plt
|
|
|
|
from openbb_terminal.config_terminal import theme
|
|
from openbb_terminal.common.behavioural_analysis import finbrain_model
|
|
from openbb_terminal.config_plot import PLOT_DPI
|
|
from openbb_terminal.decorators import log_start_end
|
|
from openbb_terminal.helper_funcs import (
|
|
export_data,
|
|
plot_autoscale,
|
|
print_rich_table,
|
|
is_valid_axes_count,
|
|
)
|
|
from openbb_terminal.rich_config import console
|
|
from openbb_terminal import rich_config
|
|
|
|
|
|
logger = logging.getLogger(__name__)
|
|
|
|
|
|
def lambda_sentiment_coloring(val: float, last_val: float) -> str:
|
|
if float(val) > last_val:
|
|
return f"[green]{val}[/green]"
|
|
return f"[red]{val}[/red]"
|
|
|
|
|
|
@log_start_end(log=logger)
|
|
def display_sentiment_analysis(
|
|
ticker: str,
|
|
raw: bool = False,
|
|
export: str = "",
|
|
external_axes: Optional[List[plt.Axes]] = None,
|
|
):
|
|
"""Sentiment analysis from FinBrain
|
|
|
|
Parameters
|
|
----------
|
|
ticker : str
|
|
Ticker to get the sentiment analysis from
|
|
raw : False
|
|
Display raw table data
|
|
export : str
|
|
Format to export data
|
|
external_axes : Optional[List[plt.Axes]], optional
|
|
External axes (1 axis is expected in the list), by default None
|
|
"""
|
|
sentiment = finbrain_model.get_sentiment(ticker)
|
|
if sentiment.empty:
|
|
console.print("No sentiment data found.\n")
|
|
return
|
|
|
|
if not raw:
|
|
# This plot has 1 axis
|
|
if external_axes is None:
|
|
_, ax = plt.subplots(figsize=plot_autoscale(), dpi=PLOT_DPI)
|
|
elif is_valid_axes_count(external_axes, 1):
|
|
(ax,) = external_axes
|
|
else:
|
|
return
|
|
|
|
for index, row in sentiment.iterrows():
|
|
if float(row["Sentiment Analysis"]) >= 0:
|
|
ax.scatter(
|
|
index, float(row["Sentiment Analysis"]), s=100, color=theme.up_color
|
|
)
|
|
else:
|
|
ax.scatter(
|
|
index,
|
|
float(row["Sentiment Analysis"]),
|
|
s=100,
|
|
color=theme.down_color,
|
|
)
|
|
ax.axhline(y=0, linestyle="--")
|
|
ax.set_xlabel("Time")
|
|
ax.set_ylabel("Sentiment")
|
|
start_date = sentiment.index[-1].strftime("%Y/%m/%d")
|
|
ax.set_title(
|
|
f"FinBrain's Sentiment Analysis for {ticker.upper()} since {start_date}"
|
|
)
|
|
ax.set_ylim([-1.1, 1.1])
|
|
senValues = np.array(pd.to_numeric(sentiment["Sentiment Analysis"].values))
|
|
senNone = np.array(0 * len(sentiment))
|
|
ax.fill_between(
|
|
sentiment.index,
|
|
pd.to_numeric(sentiment["Sentiment Analysis"].values),
|
|
0,
|
|
where=(senValues < senNone),
|
|
alpha=0.30,
|
|
color=theme.down_color,
|
|
interpolate=True,
|
|
)
|
|
ax.fill_between(
|
|
sentiment.index,
|
|
pd.to_numeric(sentiment["Sentiment Analysis"].values),
|
|
0,
|
|
where=(senValues >= senNone),
|
|
alpha=0.30,
|
|
color=theme.up_color,
|
|
interpolate=True,
|
|
)
|
|
theme.style_primary_axis(ax)
|
|
|
|
if external_axes is None:
|
|
theme.visualize_output()
|
|
|
|
else:
|
|
if rich_config.USE_COLOR:
|
|
color_df = sentiment["Sentiment Analysis"].apply(
|
|
lambda_sentiment_coloring, last_val=0
|
|
)
|
|
color_df = pd.DataFrame(
|
|
data=color_df.values,
|
|
index=pd.to_datetime(sentiment.index).strftime("%Y-%m-%d"),
|
|
)
|
|
print_rich_table(
|
|
color_df,
|
|
headers=["Sentiment"],
|
|
title="FinBrain Ticker Sentiment",
|
|
show_index=True,
|
|
)
|
|
else:
|
|
print_rich_table(
|
|
pd.DataFrame(
|
|
data=sentiment.values,
|
|
index=pd.to_datetime(sentiment.index).strftime("%Y-%m-%d"),
|
|
),
|
|
headers=["Sentiment"],
|
|
title="FinBrain Ticker Sentiment",
|
|
show_index=True,
|
|
)
|
|
|
|
export_data(
|
|
export, os.path.dirname(os.path.abspath(__file__)), "headlines", sentiment
|
|
)
|