autots package

Subpackages

• autots.datasets package
  • Submodules
  • autots.datasets.fred module
    • get_fred_data()
  • autots.datasets.synthetic module
    • SyntheticDailyGenerator
      • SyntheticDailyGenerator.SERIES_TYPE_DESCRIPTIONS
      • SyntheticDailyGenerator.TEMPLATE_VERSION
      • SyntheticDailyGenerator.get_all_labels()
      • SyntheticDailyGenerator.get_anomalies()
      • SyntheticDailyGenerator.get_components()
      • SyntheticDailyGenerator.get_data()
      • SyntheticDailyGenerator.get_holiday_config()
      • SyntheticDailyGenerator.get_holiday_impacts()
      • SyntheticDailyGenerator.get_holiday_splash_impacts()
      • SyntheticDailyGenerator.get_lagged_influences()
      • SyntheticDailyGenerator.get_level_shifts()
      • SyntheticDailyGenerator.get_noise_changepoints()
      • SyntheticDailyGenerator.get_noise_to_signal_ratios()
      • SyntheticDailyGenerator.get_regressor_impacts()
      • SyntheticDailyGenerator.get_regressors()
      • SyntheticDailyGenerator.get_seasonality_changepoints()
      • SyntheticDailyGenerator.get_series_noise_levels()
      • SyntheticDailyGenerator.get_series_scales()
      • SyntheticDailyGenerator.get_series_seasonality_strengths()
      • SyntheticDailyGenerator.get_series_type_description()
      • SyntheticDailyGenerator.get_template()
      • SyntheticDailyGenerator.get_trend_changepoints()
      • SyntheticDailyGenerator.machine_summary()
      • SyntheticDailyGenerator.plot()
      • SyntheticDailyGenerator.render_template()
      • SyntheticDailyGenerator.summary()
      • SyntheticDailyGenerator.to_csv()
      • SyntheticDailyGenerator.tune_to_data()
    • augment_with_synthetic_bounds()
    • generate_synthetic_daily_data()
  • Module contents
    • SyntheticDailyGenerator
      • SyntheticDailyGenerator.SERIES_TYPE_DESCRIPTIONS
      • SyntheticDailyGenerator.TEMPLATE_VERSION
      • SyntheticDailyGenerator.get_all_labels()
      • SyntheticDailyGenerator.get_anomalies()
      • SyntheticDailyGenerator.get_components()
      • SyntheticDailyGenerator.get_data()
      • SyntheticDailyGenerator.get_holiday_config()
      • SyntheticDailyGenerator.get_holiday_impacts()
      • SyntheticDailyGenerator.get_holiday_splash_impacts()
      • SyntheticDailyGenerator.get_lagged_influences()
      • SyntheticDailyGenerator.get_level_shifts()
      • SyntheticDailyGenerator.get_noise_changepoints()
      • SyntheticDailyGenerator.get_noise_to_signal_ratios()
      • SyntheticDailyGenerator.get_regressor_impacts()
      • SyntheticDailyGenerator.get_regressors()
      • SyntheticDailyGenerator.get_seasonality_changepoints()
      • SyntheticDailyGenerator.get_series_noise_levels()
      • SyntheticDailyGenerator.get_series_scales()
      • SyntheticDailyGenerator.get_series_seasonality_strengths()
      • SyntheticDailyGenerator.get_series_type_description()
      • SyntheticDailyGenerator.get_template()
      • SyntheticDailyGenerator.get_trend_changepoints()
      • SyntheticDailyGenerator.machine_summary()
      • SyntheticDailyGenerator.plot()
      • SyntheticDailyGenerator.render_template()
      • SyntheticDailyGenerator.summary()
      • SyntheticDailyGenerator.to_csv()
      • SyntheticDailyGenerator.tune_to_data()
    • generate_synthetic_daily_data()
    • load_artificial()
    • load_daily()
    • load_hourly()
    • load_linear()
    • load_live_daily()
    • load_monthly()
    • load_sine()
    • load_weekdays()
    • load_weekly()
    • load_yearly()
    • load_zeroes()
• autots.evaluator package
  • Submodules
  • autots.evaluator.anomaly_detector module
  • autots.evaluator.auto_model module
  • autots.evaluator.auto_ts module
  • autots.evaluator.benchmark module
  • autots.evaluator.event_forecasting module
  • autots.evaluator.feature_detector module
  • autots.evaluator.metrics module
    • array_last_val()
    • chi_squared_hist_distribution_loss()
    • containment()
    • contour()
    • default_scaler()
    • dwae()
    • full_metric_evaluation()
    • kde()
    • kde_kl_distance()
    • kl_divergence()
    • linearity()
    • mae()
    • mda()
    • mean_absolute_differential_error()
    • mean_absolute_error()
    • medae()
    • median_absolute_error()
    • mlvb()
    • mqae()
    • msle()
    • numpy_ffill()
    • oda()
    • pinball_loss()
    • precomp_wasserstein()
    • qae()
    • rmse()
    • root_mean_square_error()
    • rps()
    • scaled_pinball_loss()
    • smape()
    • smoothness()
    • spl()
    • symmetric_mean_absolute_percentage_error()
    • threshold_loss()
    • unsorted_wasserstein()
    • wasserstein()
  • autots.evaluator.validation module
  • Module contents
• autots.mcp package
  • Submodules
  • autots.mcp.server module
  • Module contents
• autots.models package
  • Submodules
  • autots.models.arch module
  • autots.models.base module
  • autots.models.basics module
  • autots.models.cassandra module
  • autots.models.composite module
  • autots.models.deepssm module
  • autots.models.dnn module
    • ElasticNetwork
      • ElasticNetwork.fit()
      • ElasticNetwork.predict()
    • KerasRNN
      • KerasRNN.fit()
      • KerasRNN.predict()
    • Transformer
      • Transformer.fit()
      • Transformer.predict()
    • transformer_build_model()
    • transformer_encoder()
  • autots.models.ensemble module
  • autots.models.gluonts module
  • autots.models.matrix_var module
  • autots.models.mlensemble module
  • autots.models.model_list module
    • auto_model_list()
    • model_list_to_dict()
  • autots.models.neural_forecast module
  • autots.models.prophet module
  • autots.models.pytorch module
  • autots.models.sklearn module
  • autots.models.statsmodels module
  • autots.models.tide module
  • Module contents
• autots.templates package
  • Submodules
  • autots.templates.general module
  • Module contents
• autots.tools package
  • Submodules
  • autots.tools.anomaly_utils module
    • anomaly_df_to_holidays()
    • anomaly_new_params()
    • create_dates_df()
    • dates_to_holidays()
    • detect_anomalies()
    • fit_anomaly_classifier()
    • gaussian_mixture()
    • holiday_new_params()
    • limits_to_anomalies()
    • loop_sk_outliers()
    • nonparametric_multivariate()
    • score_to_anomaly()
    • sk_outliers()
    • values_to_anomalies()
    • zscore_survival_function()
  • autots.tools.autoencoder module
    • VAE
      • VAE.forward()
      • VAE.reparameterize()
    • VAEAnomalyDetector
      • VAEAnomalyDetector.fit()
      • VAEAnomalyDetector.predict()
    • VAEDecoder
      • VAEDecoder.forward()
    • VAEEncoder
      • VAEEncoder.forward()
    • loop_vae_outliers()
    • vae_outliers()
  • autots.tools.bayesian_regression module
    • BayesianMultiOutputRegression
      • BayesianMultiOutputRegression.coefficient_interval()
      • BayesianMultiOutputRegression.fit()
      • BayesianMultiOutputRegression.predict()
      • BayesianMultiOutputRegression.sample_posterior()
  • autots.tools.calendar module
    • gregorian_to_chinese()
    • gregorian_to_christian_lunar()
    • gregorian_to_hebrew()
    • gregorian_to_hindu()
    • gregorian_to_islamic()
    • heb_is_leap()
    • lunar_from_lunar()
    • lunar_from_lunar_full()
    • to_jd()
  • autots.tools.changepoints module
    • ChangepointDetector
      • ChangepointDetector.create_features()
      • ChangepointDetector.detect()
      • ChangepointDetector.fit()
      • ChangepointDetector.fit_transform()
      • ChangepointDetector.get_market_changepoints()
      • ChangepointDetector.get_new_params()
      • ChangepointDetector.inverse_transform()
      • ChangepointDetector.plot()
      • ChangepointDetector.transform()
    • changepoint_fcst_from_last_row()
    • create_changepoint_features()
    • find_market_changepoints_multivariate()
    • generate_random_changepoint_params()
    • half_yr_spacing()
  • autots.tools.cointegration module
    • btcd_decompose()
    • coint_fast()
    • coint_johansen()
    • fourier_series()
    • lagmat()
  • autots.tools.constraint module
    • apply_adjustment_single()
    • apply_constraint_single()
    • apply_fit_constraint()
    • constant_growth_rate()
    • constraint_new_params()
    • fit_constraint()
  • autots.tools.cpu_count module
    • cpu_count()
    • set_n_jobs()
  • autots.tools.fast_kalman module
    • Usage example
    • Gaussian
      • Gaussian.empty()
      • Gaussian.unvectorize_state()
      • Gaussian.unvectorize_vars()
    • KalmanFilter
      • KalmanFilter.Result
      • KalmanFilter.compute()
      • KalmanFilter.em()
      • KalmanFilter.em_observation_noise()
      • KalmanFilter.em_process_noise()
      • KalmanFilter.predict()
      • KalmanFilter.predict_next()
      • KalmanFilter.predict_observation()
      • KalmanFilter.smooth()
      • KalmanFilter.smooth_current()
      • KalmanFilter.update()
    • autoshape()
    • ddot()
    • ddot_t_right()
    • ddot_t_right_old()
    • dinv()
    • douter()
    • em_initial_state()
    • ensure_matrix()
    • predict()
    • predict_observation()
    • priv_smooth()
    • priv_update_with_nan_check()
    • smooth()
    • stable_pinv()
    • update()
    • update_with_nan_check()
  • autots.tools.fast_kalman_params module
    • ensure_stability()
    • holt_winters_damped_matrices()
    • new_kalman_params()
    • random_matrix()
    • random_state_space()
    • random_state_space_original()
  • autots.tools.fft module
    • FFT
      • FFT.fit()
      • FFT.generate_harmonics_dataframe()
      • FFT.predict()
    • fourier_extrapolation()
  • autots.tools.fir_filter module
    • apply_fir_filter_time_domain()
    • apply_fir_filter_to_timeseries()
    • fft_fir_filter_to_timeseries()
    • generate_random_fir_params()
  • autots.tools.g7xx_codec module
    • G711Scaler
      • G711Scaler.fit()
      • G711Scaler.fit_transform()
      • G711Scaler.get_new_params()
      • G711Scaler.inverse_transform()
      • G711Scaler.transform()
    • G726Filter
      • G726Filter.fit()
      • G726Filter.fit_transform()
      • G726Filter.get_new_params()
      • G726Filter.inverse_transform()
      • G726Filter.transform()
    • g711_decode()
    • g711_encode()
    • g726_adpcm_filter()
  • autots.tools.hierarchial module
    • compute_volatility_weights()
    • erm_reconcile()
    • hierarchial
      • hierarchial.fit()
      • hierarchial.reconcile()
      • hierarchial.transform()
    • iterative_mint_reconcile()
    • iterative_volatility_mint_reconcile()
    • ledoit_wolf_covariance()
    • mint_reconcile()
    • volatility_weighted_mint_reconcile()
  • autots.tools.holiday module
    • holiday_flag()
    • query_holidays()
  • autots.tools.impute module
    • FillNA()
    • SeasonalityMotifImputer
      • SeasonalityMotifImputer.impute()
    • SimpleSeasonalityMotifImputer
      • SimpleSeasonalityMotifImputer.impute()
    • biased_ffill()
    • fake_date_fill()
    • fake_date_fill_old()
    • fill_forward()
    • fill_forward_alt()
    • fill_mean()
    • fill_mean_old()
    • fill_median()
    • fill_median_old()
    • fill_one()
    • fill_zero()
    • fillna_np()
    • rolling_mean()
    • seasonal_linear_imputer()
  • autots.tools.kalman module
    • kalman_fusion_forecasts()
    • robust_pinv()
  • autots.tools.lunar module
    • dcos()
    • dsin()
    • fixangle()
    • kepler()
    • moon_phase()
    • moon_phase_alternative()
    • moon_phase_df()
    • moon_phase_df_alternative()
    • phase_string()
    • todeg()
    • torad()
  • autots.tools.mocks module
    • DataLoader
    • Dataset
    • MinMaxScaler
      • MinMaxScaler.fit()
      • MinMaxScaler.fit_transform()
      • MinMaxScaler.transform()
    • Module
      • Module.eval()
      • Module.forward()
      • Module.load_state_dict()
      • Module.state_dict()
      • Module.train()
    • StandardScaler
      • StandardScaler.fit()
      • StandardScaler.fit_transform()
      • StandardScaler.inverse_transform()
      • StandardScaler.transform()
    • TensorDataset
    • butter()
    • curve_fit()
    • fftconvolve()
    • norm
      • norm.cdf()
      • norm.ppf()
    • savgol_filter()
    • sosfiltfilt()
    • tqdm()
  • autots.tools.percentile module
    • nan_percentile()
    • nan_quantile()
    • trimmed_mean()
  • autots.tools.plotting module
    • calculate_peak_density()
    • create_seaborn_palette_from_cmap()
    • plot_distributions()
    • plot_feature_panels()
    • plot_forecast_with_intervals()
    • plot_risk_score_bar()
    • plot_simulation_paths()
  • autots.tools.probabilistic module
    • Point_to_Probability()
    • Variable_Point_to_Probability()
    • historic_quantile()
    • inferred_normal()
    • percentileofscore_appliable()
  • autots.tools.profile module
  • autots.tools.regressor module
  • autots.tools.seasonal module
    • anchored_segment_fourier_features()
    • anchored_warped_fourier_features()
    • create_datepart_components()
    • create_seasonality_feature()
    • date_part()
    • fourier_df()
    • fourier_series()
    • random_datepart()
    • seasonal_independent_match()
    • seasonal_int()
    • seasonal_repeating_wavelet()
    • seasonal_window_match()
  • autots.tools.shaping module
    • NumericTransformer
      • NumericTransformer.fit()
      • NumericTransformer.fit_transform()
      • NumericTransformer.inverse_transform()
      • NumericTransformer.transform()
    • clean_weights()
    • df_cleanup()
    • drop_leading_na_block()
    • freq_to_timedelta()
    • infer_frequency()
    • long_to_wide()
    • simple_train_test_split()
    • split_digits_and_non_digits()
    • subset_series()
    • wide_to_3d()
  • autots.tools.thresholding module
    • NonparametricThreshold
      • NonparametricThreshold.compare_to_epsilon()
      • NonparametricThreshold.find_epsilon()
      • NonparametricThreshold.prune_anoms()
      • NonparametricThreshold.score_anomalies()
    • consecutive_groups()
    • nonparametric()
  • autots.tools.transform module
  • autots.tools.wavelet module
    • continuous_db2_wavelet()
    • create_daubechies_db2_wavelet()
    • create_gaussian_wavelet()
    • create_haar_wavelet()
    • create_mexican_hat_wavelet()
    • create_morlet_wavelet()
    • create_narrowing_wavelets()
    • create_real_morlet_wavelet()
    • create_wavelet()
    • offset_wavelet()
  • autots.tools.window_functions module
    • chunk_reshape()
    • last_window()
    • np_2d_arange()
    • retrieve_closest_indices()
    • rolling_window_view()
    • sliding_window_view()
    • window_id_maker()
    • window_lin_reg()
    • window_lin_reg_mean()
    • window_lin_reg_mean_no_nan()
    • window_maker()
    • window_maker_2()
    • window_maker_3()
    • window_sum_mean()
    • window_sum_mean_nan_tail()
    • window_sum_nan_mean()
  • Module contents

Module contents