from gamestonk_terminal.common.quantitative_analysis.qa_view import (
display_seasonal as decompose, )
from gamestonk_terminal.common.quantitative_analysis.qa_view import (
display_cusum as cusum, )
from gamestonk_terminal.common.quantitative_analysis.qa_view import display_acf as acf
from gamestonk_terminal.common.quantitative_analysis.rolling_view import (
display_mean_std as rolling, )
from gamestonk_terminal.common.quantitative_analysis.rolling_view import (
display_spread as spread, )
from gamestonk_terminal.common.quantitative_analysis.rolling_view import (
display_quantile as quantile, )
from gamestonk_terminal.common.quantitative_analysis.rolling_view import (
display_skew as skew, )
from gamestonk_terminal.common.quantitative_analysis.rolling_view import (
display_kurtosis as kurtosis, )
from gamestonk_terminal.common.quantitative_analysis.qa_view import (
display_normality as normality, )
from gamestonk_terminal.common.quantitative_analysis.qa_view import (
display_qqplot as qqplot, )
from gamestonk_terminal.common.quantitative_analysis.qa_view import (
display_unitroot as unitroot, )
from .factors_view import capm_view as capm
# Models
# NOTE: The raw function is used here to point to the commons path where all the
# qa models are expected to live
models = _models([
os.path.abspath(os.path.dirname(raw.__code__.co_filename)),
os.path.abspath(os.path.dirname(__file__)),
])
"""Screener context API.""" import os from gamestonk_terminal.helper_classes import ModelsNamespace as _models # flake8: noqa # pylint: disable=unused-import # Context menus from gamestonk_terminal.etf.screener.screener_view import view_screener as screen # Models models = _models(os.path.abspath(os.path.dirname(__file__)))
import os
from gamestonk_terminal.helper_classes import ModelsNamespace as _models
# flake8: noqa
# pylint: disable=unused-import
# Menu commands
from gamestonk_terminal.common.prediction_techniques.ets_view import (
display_exponential_smoothing as ets, )
from gamestonk_terminal.common.prediction_techniques.knn_view import (
display_k_nearest_neighbors as knn, )
from gamestonk_terminal.common.prediction_techniques.regression_view import (
display_regression as regression, )
from gamestonk_terminal.common.prediction_techniques.arima_view import (
display_arima as arima, )
from gamestonk_terminal.common.prediction_techniques.neural_networks_view import (
display_mlp as mlp, )
from gamestonk_terminal.common.prediction_techniques.neural_networks_view import (
display_rnn as rnn, )
from gamestonk_terminal.common.prediction_techniques.neural_networks_view import (
display_lstm as lstm, )
from gamestonk_terminal.common.prediction_techniques.neural_networks_view import (
display_conv1d as conv1d, )
from gamestonk_terminal.common.prediction_techniques.mc_view import (
display_mc_forecast as mc, )
# Models
# NOTE: The ets function is used here to point to the commons path where all the
# inference models are expected to live
models = _models(os.path.abspath(os.path.dirname(ets.__code__.co_filename)))