diff --git a/build/conda/conda-3-9-env-full.yaml b/build/conda/conda-3-9-env-full.yaml index 4813933a99f..17a677be414 100644 --- a/build/conda/conda-3-9-env-full.yaml +++ b/build/conda/conda-3-9-env-full.yaml @@ -5,6 +5,6 @@ dependencies: - python=3.9.6 - pip - pytorch-lightning=1.6.5 - - u8darts[torch]=0.21.0 + - u8darts[torch]=0.23.0 - poetry=1.1.13 - cvxpy=1.2.1 diff --git a/openbb_terminal/forecast/brnn_model.py b/openbb_terminal/forecast/brnn_model.py index 1219efa2566..04733e78597 100644 --- a/openbb_terminal/forecast/brnn_model.py +++ b/openbb_terminal/forecast/brnn_model.py @@ -30,7 +30,6 @@ def get_brnn_data( output_chunk_length: int = 5, model_type: str = "LSTM", n_rnn_layers: int = 1, - hidden_size: int = 20, dropout: float = 0.0, batch_size: int = 32, n_epochs: int = 100, @@ -62,8 +61,6 @@ def get_brnn_data( Either a string specifying the RNN module type ("RNN", "LSTM" or "GRU"). Defaults to "LSTM". n_rnn_layers (int, optional): Number of layers in the RNN module. Defaults to 1. - hidden_size (int, optional): - Size for feature maps for each hidden RNN layer. Defaults to 20. dropout (float, optional): Fraction of neurons afected by Dropout. Defaults to 0.0. batch_size (int, optional): @@ -121,7 +118,6 @@ def get_brnn_data( output_chunk_length=output_chunk_length, model=model_type, n_rnn_layers=n_rnn_layers, - hidden_size=hidden_size, dropout=dropout, batch_size=batch_size, n_epochs=n_epochs, diff --git a/openbb_terminal/forecast/brnn_view.py b/openbb_terminal/forecast/brnn_view.py index ec1b0727ce5..a332b95e3b7 100644 --- a/openbb_terminal/forecast/brnn_view.py +++ b/openbb_terminal/forecast/brnn_view.py @@ -29,7 +29,6 @@ def display_brnn_forecast( output_chunk_length: int = 5, model_type: str = "LSTM", n_rnn_layers: int = 1, - hidden_size: int = 20, dropout: float = 0.0, batch_size: int = 16, n_epochs: int = 100, @@ -71,8 +70,6 @@ def display_brnn_forecast( Either a string specifying the RNN module type ("RNN", "LSTM" or "GRU"). Defaults to "LSTM". n_rnn_layers (int, optional): Number of layers in the RNN module. Defaults to 1. - hidden_size (int, optional): - Size for feature maps for each hidden RNN layer. Defaults to 20. dropout (float, optional): Fraction of neurons afected by Dropout. Defaults to 0.0. batch_size (int, optional): @@ -130,7 +127,6 @@ def display_brnn_forecast( output_chunk_length=output_chunk_length, model_type=model_type, n_rnn_layers=n_rnn_layers, - hidden_size=hidden_size, dropout=dropout, batch_size=batch_size, n_epochs=n_epochs, diff --git a/openbb_terminal/forecast/forecast_controller.py b/openbb_terminal/forecast/forecast_controller.py index 94c2e68c55f..292c84fa387 100644 --- a/openbb_terminal/forecast/forecast_controller.py +++ b/openbb_terminal/forecast/forecast_controller.py @@ -368,7 +368,7 @@ class ForecastController(BaseController): past_covariates: bool = False, all_past_covariates: bool = False, lags: bool = False, - hidden_size: int = None, + hidden_size: int = 0, n_jumps: bool = False, end: bool = False, start: bool = False, @@ -2170,7 +2170,6 @@ class ForecastController(BaseController): target_dataset=True, n_days=True, target_column=True, - hidden_size=20, residuals=True, forecast_only=True, start=True, @@ -2198,7 +2197,6 @@ class ForecastController(BaseController): output_chunk_length=ns_parser.output_chunk_length, model_type=ns_parser.model_type, n_rnn_layers=ns_parser.n_rnn_layers, - hidden_size=ns_parser.hidden_size, dropout=ns_parser.dropout, batch_size=ns_parser.batch_size, n_epochs=ns_parser.n_epochs, diff --git a/openbb_terminal/forecast/helpers.py b/openbb_terminal/forecast/helpers.py index ab1ec0d1266..2f5596b0e46 100644 --- a/openbb_terminal/forecast/helpers.py +++ b/openbb_terminal/forecast/helpers.py @@ -706,7 +706,6 @@ def plot_residuals( num_bins: int = 20, default_formatting: bool = False, ): - del default_formatting if past_covariates: console.print( "[red]Cannot calculate and plot residuals if there are past covariates.[/red]" @@ -728,8 +727,7 @@ def plot_residuals( residuals=residuals, num_bins=num_bins, fill_nan=True, - # TODO: uncomment this once darts pr #1224 becomes a part of the package - # default_formatting=default_formatting, + default_formatting=default_formatting, ) diff --git a/openbb_terminal/helper_funcs.py b/openbb_terminal/helper_funcs.py index 9487cd01b0e..05e2cd20899 100644 --- a/openbb_terminal/helper_funcs.py +++ b/openbb_terminal/helper_funcs.py @@ -1735,10 +1735,10 @@ def screenshot_to_canvas(shot, plot_exists: bool = False): x = int((background.width - OUTSIDE_CANVAS_WIDTH) / 2) y = UPPER_SPACE - white_shape = [ + white_shape = ( (x, y), (x + OUTSIDE_CANVAS_WIDTH, y + OUTSIDE_CANVAS_HEIGHT), - ] + ) img = ImageDraw.Draw(background) img.rounded_rectangle( white_shape, diff --git a/website/content/terminal/forecast/brnn/_index.md b/website/content/terminal/forecast/brnn/_index.md index 734be44f831..64e8b7885b0 100644 --- a/website/content/terminal/forecast/brnn/_index.md +++ b/website/content/terminal/forecast/brnn/_index.md @@ -14,8 +14,6 @@ Perform BRNN forecast (Vanilla RNN, LSTM, GRU) optional arguments: --n-rnn-layers N_RNN_LAYERS Number of layers in the RNN module. (default: 1) - --hidden-size HIDDEN_SIZE - Size for feature maps for each hidden RNN layer (h_n) (default: 20) --past-covariates PAST_COVARIATES Past covariates(columns/features) in same dataset. Comma separated. (default: None) --all-past-covariates