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)))