diff --git a/docs/tutorials/time_series_forecasting.ipynb b/docs/tutorials/time_series_forecasting.ipynb index 44b53c0f6..e59d89224 100644 --- a/docs/tutorials/time_series_forecasting.ipynb +++ b/docs/tutorials/time_series_forecasting.ipynb @@ -47,8 +47,8 @@ "name": "#%%\n" }, "ExecuteTime": { - "end_time": "2024-05-29T17:10:09.091832200Z", - "start_time": "2024-05-29T17:10:09.061123600Z" + "end_time": "2024-06-12T14:56:18.647123700Z", + "start_time": "2024-06-12T14:56:18.624006Z" } } }, @@ -67,8 +67,8 @@ "metadata": { "collapsed": false, "ExecuteTime": { - "end_time": "2024-05-29T17:10:09.099206700Z", - "start_time": "2024-05-29T17:10:09.093830500Z" + "end_time": "2024-06-12T14:56:18.656269200Z", + "start_time": "2024-06-12T14:56:18.649123200Z" } }, "outputs": [ @@ -101,7 +101,7 @@ "outputs": [ { "data": { - "text/plain": "", + "text/plain": "", "image/png": "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" }, "execution_count": 23, @@ -115,8 +115,8 @@ "metadata": { "collapsed": false, "ExecuteTime": { - "end_time": "2024-05-29T17:10:09.196961400Z", - "start_time": "2024-05-29T17:10:09.099206700Z" + "end_time": "2024-06-12T14:56:18.778402800Z", + "start_time": "2024-06-12T14:56:18.653758900Z" } }, "execution_count": 23 @@ -136,8 +136,8 @@ "metadata": { "collapsed": false, "ExecuteTime": { - "end_time": "2024-05-29T17:10:09.197960800Z", - "start_time": "2024-05-29T17:10:09.174885Z" + "end_time": "2024-06-12T14:56:18.781401Z", + "start_time": "2024-06-12T14:56:18.731420200Z" } }, "outputs": [], @@ -164,8 +164,8 @@ "metadata": { "collapsed": false, "ExecuteTime": { - "end_time": "2024-05-29T17:10:09.198463900Z", - "start_time": "2024-05-29T17:10:09.181893700Z" + "end_time": "2024-06-12T14:56:18.781401Z", + "start_time": "2024-06-12T14:56:18.737179600Z" } }, "outputs": [], @@ -182,7 +182,7 @@ "\n", "neural_network = NeuralNetworkRegressor(\n", " InputConversionTimeSeries(),\n", - " [ForwardLayer(256), LSTMLayer(128), ForwardLayer(1)],\n", + " [ForwardLayer(256), LSTMLayer(512), ForwardLayer(1)],\n", ")" ] }, @@ -210,8 +210,8 @@ "metadata": { "collapsed": false, "ExecuteTime": { - "end_time": "2024-05-29T17:10:22.072485300Z", - "start_time": "2024-05-29T17:10:09.184448600Z" + "end_time": "2024-06-12T14:56:30.949080300Z", + "start_time": "2024-06-12T14:56:18.739691600Z" } }, "execution_count": 26 @@ -231,22 +231,14 @@ "metadata": { "collapsed": false, "ExecuteTime": { - "end_time": "2024-05-29T17:10:22.113606700Z", - "start_time": "2024-05-29T17:10:22.072485300Z" + "end_time": "2024-06-12T14:56:30.989575200Z", + "start_time": "2024-06-12T14:56:30.950080700Z" } }, "outputs": [], "source": [ "\n", - "prediction = fitted_neural_network.predict(\n", - " test_set.to_time_series_dataset(\n", - " target_name=\"value\",\n", - " window_size=10,\n", - " forecast_horizon=1,\n", - " continuous=False,\n", - " extra_names= [\"date\"]\n", - " )\n", - ")\n", + "prediction = fitted_neural_network.predict(test_set)\n", "prediction = prediction.to_table()" ] }, @@ -265,14 +257,14 @@ "metadata": { "collapsed": false, "ExecuteTime": { - "end_time": "2024-05-29T17:10:22.114606800Z", - "start_time": "2024-05-29T17:10:22.112094700Z" + "end_time": "2024-06-12T14:56:30.991965600Z", + "start_time": "2024-06-12T14:56:30.989575200Z" } }, "outputs": [], "source": [ "prediction = trained_scaler.inverse_transform(prediction)\n", - "test_set = trained_scaler.inverse_transform(test_set)\n" + "test_set = trained_scaler.inverse_transform(test_set)" ] }, { @@ -284,8 +276,8 @@ "metadata": { "collapsed": false, "ExecuteTime": { - "end_time": "2024-05-29T17:10:22.117044700Z", - "start_time": "2024-05-29T17:10:22.113606700Z" + "end_time": "2024-06-12T14:56:30.997483900Z", + "start_time": "2024-06-12T14:56:30.993971900Z" } }, "execution_count": 29 @@ -296,15 +288,15 @@ "metadata": { "collapsed": false, "ExecuteTime": { - "end_time": "2024-05-29T17:10:22.191343300Z", - "start_time": "2024-05-29T17:10:22.117044700Z" + "end_time": "2024-06-12T14:56:31.078460800Z", + "start_time": "2024-06-12T14:56:30.996484900Z" } }, "outputs": [ { "data": { - "text/plain": "", - "image/png": "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" + "text/plain": "", + "image/png": "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" }, "execution_count": 30, "metadata": {}, diff --git a/src/safeds/data/tabular/containers/__init__.py b/src/safeds/data/tabular/containers/__init__.py index f1ffc3110..18cc631cd 100644 --- a/src/safeds/data/tabular/containers/__init__.py +++ b/src/safeds/data/tabular/containers/__init__.py @@ -19,7 +19,7 @@ "Column": "._column:Column", "Row": "._row:Row", "StringCell": "._string_cell:StringCell", - "TemporalCell": "._temporal_cell:", + "TemporalCell": "._temporal_cell:TemporalCell", "Table": "._table:Table", }, ) diff --git a/src/safeds/ml/nn/converters/_input_converter_time_series.py b/src/safeds/ml/nn/converters/_input_converter_time_series.py index 78fce0878..08e166f19 100644 --- a/src/safeds/ml/nn/converters/_input_converter_time_series.py +++ b/src/safeds/ml/nn/converters/_input_converter_time_series.py @@ -5,7 +5,7 @@ from safeds._utils import _structural_hash from safeds.data.labeled.containers import TimeSeriesDataset -from safeds.data.tabular.containers import Column +from safeds.data.tabular.containers import Column, Table from ._input_converter import InputConversion @@ -14,7 +14,7 @@ from torch.utils.data import DataLoader -class InputConversionTimeSeries(InputConversion[TimeSeriesDataset, TimeSeriesDataset]): +class InputConversionTimeSeries(InputConversion[TimeSeriesDataset, Table]): """The input conversion for a neural network, defines the input parameters for the neural network.""" def __init__( @@ -24,9 +24,9 @@ def __init__( self._forecast_horizon = 0 self._first = True self._target_name: str = "" - self._time_name: str = "" self._feature_names: list[str] = [] self._continuous: bool = False + self._extra_names: list[str] = [] def __eq__(self, other: object) -> bool: if not isinstance(other, type(self)): @@ -38,6 +38,7 @@ def __eq__(self, other: object) -> bool: and self._target_name == other._target_name and self._feature_names == other._feature_names and self._continuous == other._continuous + and self._extra_names == other._extra_names ) def __hash__(self) -> int: @@ -46,9 +47,9 @@ def __hash__(self) -> int: self._window_size, self._forecast_horizon, self._target_name, - self._time_name, self._feature_names, self._continuous, + self._extra_names, ) def __sizeof__(self) -> int: @@ -56,9 +57,9 @@ def __sizeof__(self) -> int: sys.getsizeof(self._window_size) + sys.getsizeof(self._forecast_horizon) + sys.getsizeof(self._target_name) - + sys.getsizeof(self._time_name) + sys.getsizeof(self._feature_names) + sys.getsizeof(self._continuous) + + sys.getsizeof(self._extra_names) ) @property @@ -87,26 +88,41 @@ def _data_conversion_fit( continuous=self._continuous, ) - def _data_conversion_predict(self, input_data: TimeSeriesDataset, batch_size: int) -> DataLoader: - return input_data._into_dataloader_with_window_predict(self._window_size, self._forecast_horizon, batch_size) + def _data_conversion_predict(self, input_data: Table, batch_size: int) -> DataLoader: + data: TimeSeriesDataset + data = input_data.to_time_series_dataset( + target_name=self._target_name, + window_size=self._window_size, + extra_names=self._extra_names, + forecast_horizon=self._forecast_horizon, + continuous=self._continuous, + ) + return data._into_dataloader_with_window_predict( + self._window_size, + self._forecast_horizon, + batch_size, + ) def _data_conversion_output( self, - input_data: TimeSeriesDataset, + input_data: Table, output_data: Tensor, ) -> TimeSeriesDataset: + table_data: Table window_size: int = self._window_size forecast_horizon: int = self._forecast_horizon - input_data_table = input_data.to_table() - input_data_table = input_data_table.slice_rows(start=window_size + forecast_horizon) + table_data = input_data + input_data_table = table_data.slice_rows(start=window_size + forecast_horizon) return input_data_table.replace_column( self._target_name, [Column(self._target_name, output_data.tolist())], ).to_time_series_dataset( target_name=self._target_name, - extra_names=input_data.extras.column_names, - window_size=window_size, + window_size=self._window_size, + extra_names=self._extra_names, + forecast_horizon=self._forecast_horizon, + continuous=self._continuous, ) def _is_fit_data_valid(self, input_data: TimeSeriesDataset) -> bool: @@ -117,9 +133,18 @@ def _is_fit_data_valid(self, input_data: TimeSeriesDataset) -> bool: self._target_name = input_data.target.name self._continuous = input_data._continuous self._first = False - return (sorted(input_data.features.column_names)).__eq__( - sorted(self._feature_names), - ) and input_data.target.name == self._target_name + self._extra_names = input_data.extras.column_names + return ( + sorted(input_data.features.column_names).__eq__( + sorted(self._feature_names), + ) + and input_data.target.name == self._target_name + ) - def _is_predict_data_valid(self, input_data: TimeSeriesDataset) -> bool: - return self._is_fit_data_valid(input_data) + def _is_predict_data_valid(self, input_data: Table) -> bool: + for name in self._feature_names: + if name not in input_data.column_names: + return False + if self._target_name not in input_data.column_names: + return False + return True diff --git a/tests/safeds/ml/nn/converters/test_input_converter_time_series.py b/tests/safeds/ml/nn/converters/test_input_converter_time_series.py index 606c8a520..58830a05c 100644 --- a/tests/safeds/ml/nn/converters/test_input_converter_time_series.py +++ b/tests/safeds/ml/nn/converters/test_input_converter_time_series.py @@ -24,10 +24,18 @@ def test_should_raise_if_is_fitted_is_set_correctly_lstm() -> None: ) assert not model.is_fitted model = model.fit(ts) - model.predict(ts) + model.predict(ts.to_table()) assert model.is_fitted +def test_is_predict_data_valid() -> None: + input_conv = InputConversionTimeSeries() + data = Table({"target": [1, 1, 1, 1], "time": [0, 0, 0, 0], "feat": [0, 0, 0, 0]}) + assert not input_conv._is_predict_data_valid(data) + input_conv._feature_names = ["XYZ"] + assert not input_conv._is_predict_data_valid(data) + + class TestEq: @pytest.mark.parametrize( ("output_conversion_ts1", "output_conversion_ts2"), diff --git a/tests/safeds/ml/nn/test_lstm_workflow.py b/tests/safeds/ml/nn/test_lstm_workflow.py index add96765f..307a139c6 100644 --- a/tests/safeds/ml/nn/test_lstm_workflow.py +++ b/tests/safeds/ml/nn/test_lstm_workflow.py @@ -48,15 +48,7 @@ def test_lstm_model(device: Device) -> None: epoch_size=1, ) - trained_model.predict( - test_table.to_time_series_dataset( - "value", - window_size=7, - forecast_horizon=12, - continuous=True, - extra_names=["date"], - ), - ) + trained_model.predict(test_table) trained_model_2 = model_2.fit( train_table.to_time_series_dataset( "value", @@ -68,14 +60,6 @@ def test_lstm_model(device: Device) -> None: epoch_size=1, ) - trained_model_2.predict( - test_table.to_time_series_dataset( - "value", - window_size=7, - forecast_horizon=12, - continuous=False, - extra_names=["date"], - ), - ) + trained_model_2.predict(test_table) assert trained_model._model is not None assert trained_model._model.state_dict()["_pytorch_layers.0._layer.weight"].device == _get_device()