mirror of
https://github.com/OpenBB-finance/OpenBB.git
synced 2026-10-27 12:40:35 +00:00
Add qa to updated crypto menu (#1557)
* Add yf to crypto load * silence pylint too many branches * Add yf chart * Add exception handling when coins are not found * Fix tests failing * Address PR Comments * Change the backwards yf crypto chart and volume label * fix gst file * add qa to crypto Co-authored-by: Minh Hoang <nminh.hoang1023@gmail.com> Co-authored-by: minhhoang1023 <40023817+minhhoang1023@users.noreply.github.com> Co-authored-by: Theodore Aptekarev <aptekarev@gmail.com> Co-authored-by: Colin Delahunty <72827203+colin99d@users.noreply.github.com>
This commit is contained in:
jmaslek
@@ -63,7 +63,7 @@ class CryptoController(CryptoBaseController):
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"prt",
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"resources",
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]
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CHOICES_MENUS = ["ta", "dd", "ov", "disc", "onchain", "defi", "nft", "pred"]
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CHOICES_MENUS = ["ta", "dd", "ov", "disc", "onchain", "defi", "nft", "pred", "qa"]
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DD_VIEWS_MAPPING = {
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"cg": pycoingecko_view,
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@@ -109,7 +109,8 @@ class CryptoController(CryptoBaseController):
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> nft non-fungible tokens, e.g.: today drops{has_ticker_start}
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> dd due-diligence for loaded coin, e.g.: coin information, social media, market stats
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> ta technical analysis for loaded coin, e.g.: ema, macd, rsi, adx, bbands, obv
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> pred prediction techniques e.g.: regression, arima, rnn, lstm, conv1d, monte carlo[/menu]
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> pred prediction techniques e.g.: regression, arima, rnn, lstm, conv1d, monte carlo
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> qa quantitative analysis, \t e.g.: decompose, cusum, residuals analysis[/menu]
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{has_ticker_end}
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"""
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console.print(text=help_text, menu="Cryptocurrency")
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@@ -507,6 +508,24 @@ class CryptoController(CryptoBaseController):
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else:
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console.print("No coin selected. Use 'load' to load a coin.\n")
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@log_start_end(log=logger)
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def call_qa(self, _):
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"""Process pred command"""
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if self.coin:
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from gamestonk_terminal.cryptocurrency.quantitative_analysis import (
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qa_controller,
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)
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if self.current_interval != "1day":
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console.print("Only interval `1day` is possible for now.\n")
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else:
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self.queue = self.load_class(
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qa_controller.QaController,
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self.coin,
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self.current_df,
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self.queue,
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)
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@log_start_end(log=logger)
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def call_pred(self, _):
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"""Process pred command"""
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@@ -0,0 +1,699 @@
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"""Quantitative Analysis Controller Module"""
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__docformat__ = "numpy"
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import argparse
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import logging
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from typing import List
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import numpy as np
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import pandas as pd
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from prompt_toolkit.completion import NestedCompleter
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from gamestonk_terminal import feature_flags as gtff
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from gamestonk_terminal.common.quantitative_analysis import qa_view, rolling_view
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from gamestonk_terminal.decorators import log_start_end
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from gamestonk_terminal.cryptocurrency import cryptocurrency_helpers as c_help
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from gamestonk_terminal.helper_funcs import (
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EXPORT_ONLY_FIGURES_ALLOWED,
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EXPORT_ONLY_RAW_DATA_ALLOWED,
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check_positive,
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check_proportion_range,
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parse_known_args_and_warn,
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check_list_dates,
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)
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from gamestonk_terminal.menu import session
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from gamestonk_terminal.parent_classes import CryptoBaseController
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from gamestonk_terminal.rich_config import console
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logger = logging.getLogger(__name__)
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class QaController(CryptoBaseController):
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"""Quantitative Analysis Controller class"""
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CHOICES_COMMANDS = [
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"load",
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"pick",
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"raw",
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"summary",
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"line",
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"hist",
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"cdf",
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"bw",
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"rolling",
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"decompose",
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"cusum",
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"acf",
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"spread",
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"quantile",
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"skew",
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"kurtosis",
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"normality",
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"qqplot",
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"unitroot",
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"goodness",
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"unitroot",
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]
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PATH = "/crypto/qa/"
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def __init__(
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self,
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coin: str,
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data: pd.DataFrame,
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queue: List[str] = None,
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):
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"""Constructor"""
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super().__init__(queue)
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data["Returns"] = data["Close"].pct_change()
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data["LogRet"] = np.log(data["Close"]) - np.log(data["Close"].shift(1))
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data = data.dropna()
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self.data = data
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self.coin = coin
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self.target = "Close"
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if session and gtff.USE_PROMPT_TOOLKIT:
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choices: dict = {c: {} for c in self.controller_choices}
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choices["pick"] = {c: None for c in list(data.columns)}
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choices["load"]["-r"] = {c: {} for c in c_help.INTERVALS}
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self.completer = NestedCompleter.from_nested_dict(choices)
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def print_help(self):
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"""Print help"""
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help_text = f"""[cmds]
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load load new coin
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pick pick target column for analysis[/cmds]
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[param]Coin: [/param]{self.coin}
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[param]Target Column: [/param]{self.target}
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[cmds]
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[info]Statistics:[/info]
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summary brief summary statistics of loaded coin.
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normality normality statistics and tests
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unitroot unit root test for stationarity (ADF, KPSS)
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[info]Plots:[/info]
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line line plot of selected target
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hist histogram with density plot
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cdf cumulative distribution function
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bw box and whisker plot
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acf (partial) auto-correlation function differentials of prices
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qqplot residuals against standard normal curve
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[info]Rolling Metrics:[/info]
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rolling rolling mean and std deviation of prices
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spread rolling variance and std deviation of prices
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quantile rolling median and quantile of prices
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skew rolling skewness of distribution of prices
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kurtosis rolling kurtosis of distribution of prices
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[info]Risk:[/info]
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var display value at risk
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es display expected shortfall
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[info]Other:[/info]
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raw print raw data
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decompose decomposition in cyclic-trend, season, and residuals of prices
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cusum detects abrupt changes using cumulative sum algorithm of prices[/cmds]
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"""
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console.print(text=help_text, menu="Crypto - Quantitative Analysis")
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def custom_reset(self):
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"""Class specific component of reset command"""
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if self.coin:
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return ["crypto", f"load {self.coin}", "qa"]
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return []
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@log_start_end(log=logger)
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def call_pick(self, other_args: List[str]):
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"""Process pick command"""
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parser = argparse.ArgumentParser(
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formatter_class=argparse.ArgumentDefaultsHelpFormatter,
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add_help=False,
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prog="pick",
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description="""
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Change target variable
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""",
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)
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parser.add_argument(
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"-t",
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"--target",
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dest="target",
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choices=list(self.data.columns),
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help="Select variable to analyze",
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)
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if other_args and "-t" not in other_args and "-h" not in other_args:
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other_args.insert(0, "-t")
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ns_parser = parse_known_args_and_warn(parser, other_args)
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if ns_parser:
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self.target = ns_parser.target
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console.print("")
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@log_start_end(log=logger)
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def call_raw(self, other_args: List[str]):
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parser = argparse.ArgumentParser(
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formatter_class=argparse.ArgumentDefaultsHelpFormatter,
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add_help=False,
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prog="raw",
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description="""
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Print raw data to console
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""",
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)
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parser.add_argument(
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"-l",
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"--limit",
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help="Number to show",
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type=check_positive,
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default=20,
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dest="limit",
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)
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parser.add_argument(
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"-d",
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"--descend",
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action="store_true",
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default=False,
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dest="descend",
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help="Sort in descending order",
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)
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ns_parser = parse_known_args_and_warn(
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parser, other_args, export_allowed=EXPORT_ONLY_RAW_DATA_ALLOWED
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)
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if ns_parser:
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qa_view.display_raw(
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self.data[self.target],
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num=ns_parser.limit,
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sort="",
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des=ns_parser.descend,
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export=ns_parser.export,
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)
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@log_start_end(log=logger)
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def call_summary(self, other_args: List[str]):
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"""Process summary command"""
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parser = argparse.ArgumentParser(
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formatter_class=argparse.ArgumentDefaultsHelpFormatter,
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add_help=False,
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prog="summary",
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description="""
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Summary statistics
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""",
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)
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ns_parser = parse_known_args_and_warn(
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parser, other_args, export_allowed=EXPORT_ONLY_RAW_DATA_ALLOWED
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)
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if ns_parser:
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qa_view.display_summary(df=self.data, export=ns_parser.export)
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@log_start_end(log=logger)
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def call_line(self, other_args: List[str]):
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"""Process line command"""
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parser = argparse.ArgumentParser(
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formatter_class=argparse.ArgumentDefaultsHelpFormatter,
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add_help=False,
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prog="line",
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description="Show line plot of selected data and allow to draw lines or highlight specific datetimes.",
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)
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parser.add_argument(
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"--log",
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help="Plot with y on log scale",
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dest="log",
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action="store_true",
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default=False,
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)
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parser.add_argument(
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"-d",
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"--draw",
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help="Draw lines and annotate on the plot",
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dest="draw",
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action="store_true",
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default=False,
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)
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parser.add_argument(
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"--ml",
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help="Draw vertical line markers to highlight certain events",
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dest="ml",
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type=check_list_dates,
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default="",
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)
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parser.add_argument(
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"--ms",
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help="Draw scatter markers to highlight certain events",
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dest="ms",
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type=check_list_dates,
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default="",
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)
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ns_parser = parse_known_args_and_warn(
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parser, other_args, export_allowed=EXPORT_ONLY_FIGURES_ALLOWED
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)
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if ns_parser:
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qa_view.display_line(
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self.data[self.target],
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title=f"{self.coin} {self.target}",
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log_y=ns_parser.log,
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draw=ns_parser.draw,
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markers_lines=ns_parser.ml,
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markers_scatter=ns_parser.ms,
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)
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@log_start_end(log=logger)
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def call_hist(self, other_args: List[str]):
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"""Process hist command"""
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parser = argparse.ArgumentParser(
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formatter_class=argparse.ArgumentDefaultsHelpFormatter,
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add_help=False,
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prog="hist",
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description="""
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Histogram with density and rug
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""",
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)
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parser.add_argument(
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"-b", "--bins", type=check_positive, default=15, dest="n_bins"
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)
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ns_parser = parse_known_args_and_warn(parser, other_args)
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if ns_parser:
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qa_view.display_hist(
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name=self.coin,
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df=self.data,
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target=self.target,
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bins=ns_parser.n_bins,
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)
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@log_start_end(log=logger)
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def call_cdf(self, other_args: List[str]):
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"""Process cdf command"""
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parser = argparse.ArgumentParser(
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formatter_class=argparse.ArgumentDefaultsHelpFormatter,
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add_help=False,
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prog="cdf",
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description="""
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Cumulative distribution function
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""",
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)
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ns_parser = parse_known_args_and_warn(
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parser, other_args, export_allowed=EXPORT_ONLY_RAW_DATA_ALLOWED
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)
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if ns_parser:
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qa_view.display_cdf(
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name=self.coin,
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df=self.data,
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target=self.target,
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export=ns_parser.export,
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)
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@log_start_end(log=logger)
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def call_bw(self, other_args: List[str]):
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"""Process bwy command"""
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parser = argparse.ArgumentParser(
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formatter_class=argparse.ArgumentDefaultsHelpFormatter,
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add_help=False,
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prog="bw",
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description="""
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Box and Whisker plot
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""",
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)
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parser.add_argument(
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"-y",
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"--yearly",
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action="store_true",
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default=False,
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dest="year",
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help="Flag to show yearly bw plot",
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)
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ns_parser = parse_known_args_and_warn(parser, other_args)
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if ns_parser:
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qa_view.display_bw(
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name=self.coin,
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df=self.data,
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target=self.target,
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yearly=ns_parser.year,
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)
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@log_start_end(log=logger)
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def call_decompose(self, other_args: List[str]):
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"""Process decompose command"""
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parser = argparse.ArgumentParser(
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add_help=False,
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formatter_class=argparse.ArgumentDefaultsHelpFormatter,
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prog="decompose",
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description="""
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Decompose time series as:
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- Additive Time Series = Level + CyclicTrend + Residual + Seasonality
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- Multiplicative Time Series = Level * CyclicTrend * Residual * Seasonality
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""",
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)
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parser.add_argument(
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"-m",
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"--multiplicative",
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action="store_true",
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default=False,
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dest="multiplicative",
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help="decompose using multiplicative model instead of additive",
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)
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ns_parser = parse_known_args_and_warn(
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parser, other_args, export_allowed=EXPORT_ONLY_RAW_DATA_ALLOWED
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)
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if ns_parser:
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qa_view.display_seasonal(
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name=self.coin,
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df=self.data,
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target=self.target,
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multiplicative=ns_parser.multiplicative,
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export=ns_parser.export,
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)
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@log_start_end(log=logger)
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def call_cusum(self, other_args: List[str]):
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"""Process cusum command"""
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parser = argparse.ArgumentParser(
|
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add_help=False,
|
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formatter_class=argparse.ArgumentDefaultsHelpFormatter,
|
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prog="cusum",
|
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description="""
|
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Cumulative sum algorithm (CUSUM) to detect abrupt changes in data
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""",
|
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)
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parser.add_argument(
|
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"-t",
|
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"--threshold",
|
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dest="threshold",
|
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type=float,
|
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default=(
|
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max(self.data[self.target].values) - min(self.data[self.target].values)
|
||||
)
|
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/ 40,
|
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help="threshold",
|
||||
)
|
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parser.add_argument(
|
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"-d",
|
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"--drift",
|
||||
dest="drift",
|
||||
type=float,
|
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default=(
|
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max(self.data[self.target].values) - min(self.data[self.target].values)
|
||||
)
|
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/ 80,
|
||||
help="drift",
|
||||
)
|
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ns_parser = parse_known_args_and_warn(parser, other_args)
|
||||
if ns_parser:
|
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qa_view.display_cusum(
|
||||
df=self.data,
|
||||
target=self.target,
|
||||
threshold=ns_parser.threshold,
|
||||
drift=ns_parser.drift,
|
||||
)
|
||||
|
||||
@log_start_end(log=logger)
|
||||
def call_acf(self, other_args: List[str]):
|
||||
"""Process acf command"""
|
||||
parser = argparse.ArgumentParser(
|
||||
add_help=False,
|
||||
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
|
||||
prog="acf",
|
||||
description="""
|
||||
Auto-Correlation and Partial Auto-Correlation Functions for diff and diff diff crypto data
|
||||
""",
|
||||
)
|
||||
parser.add_argument(
|
||||
"-l",
|
||||
"--lags",
|
||||
dest="lags",
|
||||
type=check_positive,
|
||||
default=15,
|
||||
help="maximum lags to display in plots",
|
||||
)
|
||||
ns_parser = parse_known_args_and_warn(parser, other_args)
|
||||
if ns_parser:
|
||||
if self.target != "Close":
|
||||
console.print(
|
||||
"Target not Close. For best results, use `pick Close` first."
|
||||
)
|
||||
|
||||
qa_view.display_acf(
|
||||
name=self.coin,
|
||||
df=self.data,
|
||||
target=self.target,
|
||||
lags=ns_parser.lags,
|
||||
)
|
||||
|
||||
@log_start_end(log=logger)
|
||||
def call_rolling(self, other_args: List[str]):
|
||||
"""Process rolling command"""
|
||||
parser = argparse.ArgumentParser(
|
||||
add_help=False,
|
||||
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
|
||||
prog="rolling",
|
||||
description="""
|
||||
Rolling mean and std deviation
|
||||
""",
|
||||
)
|
||||
parser.add_argument(
|
||||
"-w",
|
||||
"--window",
|
||||
action="store",
|
||||
dest="n_window",
|
||||
type=check_positive,
|
||||
default=14,
|
||||
help="Window length",
|
||||
)
|
||||
ns_parser = parse_known_args_and_warn(
|
||||
parser, other_args, export_allowed=EXPORT_ONLY_RAW_DATA_ALLOWED
|
||||
)
|
||||
if ns_parser:
|
||||
rolling_view.display_mean_std(
|
||||
name=self.coin,
|
||||
df=self.data,
|
||||
target=self.target,
|
||||
window=ns_parser.n_window,
|
||||
export=ns_parser.export,
|
||||
)
|
||||
|
||||
@log_start_end(log=logger)
|
||||
def call_spread(self, other_args: List[str]):
|
||||
"""Process spread command"""
|
||||
parser = argparse.ArgumentParser(
|
||||
add_help=False,
|
||||
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
|
||||
prog="spread",
|
||||
description="""Shows rolling spread measurement
|
||||
""",
|
||||
)
|
||||
parser.add_argument(
|
||||
"-w",
|
||||
"--window",
|
||||
action="store",
|
||||
dest="n_window",
|
||||
type=check_positive,
|
||||
default=14,
|
||||
help="Window length",
|
||||
)
|
||||
ns_parser = parse_known_args_and_warn(
|
||||
parser, other_args, export_allowed=EXPORT_ONLY_RAW_DATA_ALLOWED
|
||||
)
|
||||
if ns_parser:
|
||||
rolling_view.display_spread(
|
||||
name=self.coin,
|
||||
df=self.data,
|
||||
target=self.target,
|
||||
window=ns_parser.n_window,
|
||||
export=ns_parser.export,
|
||||
)
|
||||
|
||||
@log_start_end(log=logger)
|
||||
def call_quantile(self, other_args: List[str]):
|
||||
"""Process quantile command"""
|
||||
parser = argparse.ArgumentParser(
|
||||
add_help=False,
|
||||
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
|
||||
prog="quantile",
|
||||
description="""
|
||||
The quantiles are values which divide the distribution such that
|
||||
there is a given proportion of observations below the quantile.
|
||||
For example, the median is a quantile. The median is the central
|
||||
value of the distribution, such that half the points are less than
|
||||
or equal to it and half are greater than or equal to it.
|
||||
|
||||
By default, q is set at 0.5, which effectively is median. Change q to
|
||||
get the desired quantile (0<q<1).
|
||||
""",
|
||||
)
|
||||
parser.add_argument(
|
||||
"-w",
|
||||
"--window",
|
||||
action="store",
|
||||
dest="n_window",
|
||||
type=check_positive,
|
||||
default=14,
|
||||
help="window length",
|
||||
)
|
||||
parser.add_argument(
|
||||
"-q",
|
||||
"--quantile",
|
||||
action="store",
|
||||
dest="f_quantile",
|
||||
type=check_proportion_range,
|
||||
default=0.5,
|
||||
help="quantile",
|
||||
)
|
||||
ns_parser = parse_known_args_and_warn(
|
||||
parser, other_args, export_allowed=EXPORT_ONLY_RAW_DATA_ALLOWED
|
||||
)
|
||||
if ns_parser:
|
||||
rolling_view.display_quantile(
|
||||
name=self.coin,
|
||||
df=self.data,
|
||||
target=self.target,
|
||||
window=ns_parser.n_window,
|
||||
quantile=ns_parser.f_quantile,
|
||||
export=ns_parser.export,
|
||||
)
|
||||
|
||||
@log_start_end(log=logger)
|
||||
def call_skew(self, other_args: List[str]):
|
||||
"""Process skew command"""
|
||||
parser = argparse.ArgumentParser(
|
||||
add_help=False,
|
||||
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
|
||||
prog="skew",
|
||||
description="""
|
||||
Skewness is a measure of asymmetry or distortion of symmetric
|
||||
distribution. It measures the deviation of the given distribution
|
||||
of a random variable from a symmetric distribution, such as normal
|
||||
distribution. A normal distribution is without any skewness, as it is
|
||||
symmetrical on both sides. Hence, a curve is regarded as skewed if
|
||||
it is shifted towards the right or the left.
|
||||
""",
|
||||
)
|
||||
parser.add_argument(
|
||||
"-w",
|
||||
"--window",
|
||||
action="store",
|
||||
dest="n_window",
|
||||
type=check_positive,
|
||||
default=14,
|
||||
help="window length",
|
||||
)
|
||||
ns_parser = parse_known_args_and_warn(
|
||||
parser, other_args, export_allowed=EXPORT_ONLY_RAW_DATA_ALLOWED
|
||||
)
|
||||
if ns_parser:
|
||||
rolling_view.display_skew(
|
||||
name=self.coin,
|
||||
df=self.data,
|
||||
target=self.target,
|
||||
window=ns_parser.n_window,
|
||||
export=ns_parser.export,
|
||||
)
|
||||
|
||||
@log_start_end(log=logger)
|
||||
def call_kurtosis(self, other_args: List[str]):
|
||||
"""Process kurtosis command"""
|
||||
parser = argparse.ArgumentParser(
|
||||
add_help=False,
|
||||
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
|
||||
prog="kurtosis",
|
||||
description="""
|
||||
Kurtosis is a measure of the "tailedness" of the probability distribution
|
||||
of a real-valued random variable. Like skewness, kurtosis describes the shape
|
||||
of a probability distribution and there are different ways of quantifying it
|
||||
for a theoretical distribution and corresponding ways of estimating it from
|
||||
a sample from a population. Different measures of kurtosis may have different
|
||||
interpretations.
|
||||
""",
|
||||
)
|
||||
parser.add_argument(
|
||||
"-w",
|
||||
"--window",
|
||||
action="store",
|
||||
dest="n_window",
|
||||
type=check_positive,
|
||||
default=14,
|
||||
help="window length",
|
||||
)
|
||||
ns_parser = parse_known_args_and_warn(
|
||||
parser, other_args, export_allowed=EXPORT_ONLY_RAW_DATA_ALLOWED
|
||||
)
|
||||
if ns_parser:
|
||||
rolling_view.display_kurtosis(
|
||||
name=self.coin,
|
||||
df=self.data,
|
||||
target=self.target,
|
||||
window=ns_parser.n_window,
|
||||
export=ns_parser.export,
|
||||
)
|
||||
|
||||
@log_start_end(log=logger)
|
||||
def call_normality(self, other_args: List[str]):
|
||||
"""Process normality command"""
|
||||
parser = argparse.ArgumentParser(
|
||||
add_help=False,
|
||||
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
|
||||
prog="normality",
|
||||
description="""
|
||||
Normality tests
|
||||
""",
|
||||
)
|
||||
ns_parser = parse_known_args_and_warn(
|
||||
parser, other_args, export_allowed=EXPORT_ONLY_RAW_DATA_ALLOWED
|
||||
)
|
||||
if ns_parser:
|
||||
qa_view.display_normality(
|
||||
df=self.data, target=self.target, export=ns_parser.export
|
||||
)
|
||||
|
||||
@log_start_end(log=logger)
|
||||
def call_qqplot(self, other_args: List[str]):
|
||||
"""Process qqplot command"""
|
||||
parser = argparse.ArgumentParser(
|
||||
add_help=False,
|
||||
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
|
||||
prog="qqplot",
|
||||
description="""
|
||||
Display QQ plot vs normal quantiles
|
||||
""",
|
||||
)
|
||||
ns_parser = parse_known_args_and_warn(parser, other_args)
|
||||
if ns_parser:
|
||||
qa_view.display_qqplot(name=self.coin, df=self.data, target=self.target)
|
||||
|
||||
@log_start_end(log=logger)
|
||||
def call_unitroot(self, other_args: List[str]):
|
||||
"""Process unitroot command"""
|
||||
parser = argparse.ArgumentParser(
|
||||
add_help=False,
|
||||
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
|
||||
prog="unitroot",
|
||||
description="""
|
||||
Unit root test / stationarity (ADF, KPSS)
|
||||
""",
|
||||
)
|
||||
parser.add_argument(
|
||||
"-r",
|
||||
"--fuller_reg",
|
||||
help="Type of regression. Can be ‘c’,’ct’,’ctt’,’nc’ 'c' - Constant and t - trend order",
|
||||
choices=["c", "ct", "ctt", "nc"],
|
||||
default="c",
|
||||
type=str,
|
||||
dest="fuller_reg",
|
||||
)
|
||||
parser.add_argument(
|
||||
"-k",
|
||||
"--kps_reg",
|
||||
help="Type of regression. Can be ‘c’,’ct'",
|
||||
choices=["c", "ct"],
|
||||
type=str,
|
||||
dest="kpss_reg",
|
||||
default="c",
|
||||
)
|
||||
ns_parser = parse_known_args_and_warn(
|
||||
parser, other_args, export_allowed=EXPORT_ONLY_RAW_DATA_ALLOWED
|
||||
)
|
||||
if ns_parser:
|
||||
qa_view.display_unitroot(
|
||||
df=self.data,
|
||||
target=self.target,
|
||||
fuller_reg=ns_parser.fuller_reg,
|
||||
kpss_reg=ns_parser.kpss_reg,
|
||||
export=ns_parser.export,
|
||||
)
|
||||
@@ -17,5 +17,6 @@ Source:
|
||||
> dd due-diligence for loaded coin, e.g.: coin information, social media, market stats
|
||||
> ta technical analysis for loaded coin, e.g.: ema, macd, rsi, adx, bbands, obv
|
||||
> pred prediction techniques e.g.: regression, arima, rnn, lstm, conv1d, monte carlo
|
||||
> qa quantitative analysis, e.g.: decompose, cusum, residuals analysis
|
||||
[/unvl]
|
||||
|
||||
|
||||
Reference in New Issue
Block a user