Update darts (#2750)

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

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,

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,

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,

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,
         )
 
 

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,

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