diff --git a/.circleci/config.yml b/.circleci/config.yml index 37247f006..59bc772b3 100644 --- a/.circleci/config.yml +++ b/.circleci/config.yml @@ -39,7 +39,7 @@ jobs: pip install flake8 python -m flake8 . - evaluator_test: + evaluator_tests: <<: *defaults steps: - attach_workspace: @@ -76,14 +76,14 @@ jobs: command: bash <(curl -s https://codecov.io/bash) -cF python - store_test_results: - path: test-results + path: tests-results - store_artifacts: - path: test-results - destination: test-results-evaluator + path: tests-results + destination: tests-results-evaluator - data_quality_test: + data_quality_tests: <<: *defaults steps: - attach_workspace: @@ -105,7 +105,7 @@ jobs: - ~/.local - run: - name: Data Quality Tests + name: Data Quality tests command: | coverage run -m unittest -v tests/test_multitask_decoder.py bash <(curl -s https://codecov.io/bash) -cF python @@ -113,8 +113,6 @@ jobs: bash <(curl -s https://codecov.io/bash) -cF python coverage run -m unittest -v tests/usgs_tests.py bash <(curl -s https://codecov.io/bash) -cF python - coverage run -m unittest -v tests/test_join.py - bash <(curl -s https://codecov.io/bash) -cF python coverage run -m unittest -v tests/test_preprocessing.py coverage run -m unittest -v tests/test_variable_length.py @@ -124,13 +122,13 @@ jobs: command: bash <(curl -s https://codecov.io/bash) -cF python - store_test_results: - path: test-results + path: tests-results - store_artifacts: - path: test-results - destination: test-results-data-quality + path: tests-results + destination: tests-results-data-quality - model_basic_test: + model_basic_tests: <<: *defaults steps: - attach_workspace: @@ -163,34 +161,34 @@ jobs: bash <(curl -s https://codecov.io/bash) -cF python coverage run -m unittest -v tests/test_informer.py bash <(curl -s https://codecov.io/bash) -cF python - coverage run -m unittest -v tests/test_meta_pr.py + coverage run -m unittest -v tests/test_json_config/tests_meta_pr.py bash <(curl -s https://codecov.io/bash) -cF python - coverage run -m unittest -v tests/time_model_test.py + coverage run -m unittest -v tests/test_json_config/time_model_tests.py bash <(curl -s https://codecov.io/bash) -cF python - coverage run -m unittest -v tests/data_loader_tests.py + coverage run -m unittest -v tests/test_json_config/data_loader_tests.py bash <(curl -s https://codecov.io/bash) -cF python - coverage run -m unittest -v tests/test_da_rnn.py + coverage run -m unittest -v tests/test_json_config/tests_da_rnn.py bash <(curl -s https://codecov.io/bash) -cF python - coverage run -m unittest -v tests/test_loss.py + coverage run -m unittest -v tests/test_json_config/tests_loss.py bash <(curl -s https://codecov.io/bash) -cF python - coverage run -m unittest -v tests/test_merging_models.py + coverage run -m unittest -v tests/test_json_config/tests_merging_models.py bash <(curl -s https://codecov.io/bash) -cF python - coverage run -m unittest -v tests/pytorc_train_tests.py + coverage run -m unittest -v tests/test_json_config/pytorc_train_tests.py bash <(curl -s https://codecov.io/bash) -cF python - coverage run -m unittest -v tests/test_classification2_loader.py + coverage run -m unittest -v tests/tests_classification2_loader.py - run: name: upload_stuff when: always command: bash <(curl -s https://codecov.io/bash) -cF python - store_test_results: - path: test-results + path: tests-results - store_artifacts: - path: test-results - destination: test-results-model-tests + path: tests-results + destination: tests-results-model-tests - decoder_test: + decoder_tests: <<: *defaults steps: - attach_workspace: @@ -214,7 +212,7 @@ jobs: - run: name: Decoder tests when: always - command: coverage run -m unittest -v tests/test_decoder.py + command: coverage run -m unittest-v tests/test_decoder.py - run: name: upload_stuff @@ -222,14 +220,14 @@ jobs: command: bash <(curl -s https://codecov.io/bash) -cF python - store_test_results: - path: test-results + path: tests-results - store_artifacts: - path: test-results - destination: test-results-decoder + path: tests-results + destination: tests-results-decoder - trainer_test: + trainer_tests: <<: *defaults steps: - attach_workspace: @@ -253,37 +251,37 @@ jobs: name: Trainer tests when: always command: | - echo -e 'GRU Vanilla test' - coverage run flood_forecast/trainer.py -p tests/gru_vanilla.json - echo -e 'Running classification test' - coverage run flood_forecast/trainer.py -p tests/classification_test.json - echo -e 'Running informer single test' - coverage run flood_forecast/trainer.py -p tests/test_inf_single.json - echo -e 'Running transformer_gaussian test' - coverage run flood_forecast/trainer.py -p tests/transformer_gaussian.json - echo -e 'Running multi_decoder_test.json' - coverage run flood_forecast/trainer.py -p tests/multi_decoder_test.json + echo -e 'GRU Vanilla tests' + coverage run flood_forecast/trainer.py -p tests/test_json_config/gru_vanilla.json + echo -e 'Running classification tests' + coverage run flood_forecast/trainer.py -p tests/test_json_config/classification_test.json + echo -e 'Running informer single tests' + coverage run flood_forecast/trainer.py -p tests/test_json_config/tests_inf_single.json + echo -e 'Running transformer_gaussian tests' + coverage run flood_forecast/trainer.py -p tests/test_json_config/transformer_gaussian.json + echo -e 'Running multi_decoder_tests.json' + coverage run flood_forecast/trainer.py -p tests/test_json_config/multi_decoder_tests.json echo -e 'training multi-task-decoder' - coverage run flood_forecast/trainer.py -p tests/multitask_decoder.json - echo -e 'running da-meta data unit test' - coverage run flood_forecast/trainer.py -p tests/da_meta.json + coverage run flood_forecast/trainer.py -p tests/test_json_config/multitask_decoder.json + echo -e 'running da-meta data unit tests' + coverage run flood_forecast/trainer.py -p tests/test_json_config/da_meta.json echo -e 'running transformer bottleneck' - coverage run flood_forecast/trainer.py -p tests/transformer_bottleneck.json - echo -e 'running da_rnn probabilistic test' - coverage run flood_forecast/trainer.py -p tests/da_rnn_probabilistic.json - echo -e 'running lstm probabilistic test' - coverage run flood_forecast/trainer.py -p tests/lstm_probabilistic_test.json - echo -e 'running probabilistic linear reg test' - coverage run flood_forecast/trainer.py -p tests/probabilistic_linear_regression_test.json + coverage run flood_forecast/trainer.py -p tests/test_json_config/transformer_bottleneck.json + echo -e 'running da_rnn probabilistic tests' + coverage run flood_forecast/trainer.py -p tests/test_json_config/da_rnn_probabilistic.json + echo -e 'running lstm probabilistic tests' + coverage run flood_forecast/trainer.py -p tests/test_json_config/lstm_probabilistic_tests.json + echo -e 'running probabilistic linear reg tests' + coverage run flood_forecast/trainer.py -p tests/test_json_config/probabilistic_linear_regression_tests.json echo -e 'running meta-data fusion' - coverage run flood_forecast/trainer.py -p tests/meta_data_test.json + coverage run flood_forecast/trainer.py -p tests/test_json_config/meta_data_tests.json - store_test_results: - path: test-results + path: tests-results - store_artifacts: - path: test-results - destination: test-results-trainer + path: tests-results + destination: tests-results-trainer - run: name: upload results @@ -291,7 +289,7 @@ jobs: command: bash <(curl -s https://codecov.io/bash) -cF python - trainer_test1: + trainer_tests1: <<: *defaults steps: - attach_workspace: @@ -315,46 +313,46 @@ jobs: name: Trainer1 tests when: always command: | - echo -e 'running test_informer \n' - coverage run flood_forecast/trainer.py -p tests/test_informer.json - echo -e 'running test_iTransformer \n' - coverage run flood_forecast/trainer.py -p tests/test_iTransformer.json - echo -e 'running tsmixer_test \n' - coverage run flood_forecast/trainer.py -p tests/tsmixer_test.json + echo -e 'running tests_informer \n' + coverage run flood_forecast/trainer.py -p tests/test_json_config/tests_informer.json + echo -e 'running tests_iTransformer \n' + coverage run flood_forecast/trainer.py -p tests/test_json_config/tests_iTransformer.json + echo -e 'running tsmixer_tests \n' + coverage run flood_forecast/trainer.py -p tests/test_json_config/tsmixer_tests.json echo -e 'running transformer_b_series.json \n' - coverage run flood_forecast/trainer.py -p tests/transformer_b_series.json - echo -e 'running crossfroer.json \n' - coverage run flood_forecast/trainer.py -p tests/cross_former.json - echo -e 'running nlinear.json \n' - coverage run flood_forecast/trainer.py -p tests/nlinear.json + coverage run flood_forecast/trainer.py -p tests/test_json_config/transformer_b_series.json + echo -e 'running crossformer.json \n' + coverage run flood_forecast/trainer.py -p tests/test_json_config/cross_former.json + echo -e 'running n-linear.json \n' + coverage run flood_forecast/trainer.py -p tests/test_json_config/nlinear.json echo -e 'running dsanet_3\n' - coverage run flood_forecast/trainer.py -p tests/dsanet_3.json + coverage run flood_forecast/trainer.py -p tests/test_json_config/dsanet_3.json echo -e 'running variable_autoencoderl.json\n' - coverage run flood_forecast/trainer.py -p tests/variable_autoencoderl.json + coverage run flood_forecast/trainer.py -p tests/test_json_config/variable_autoencoderl.json echo -e 'running dlinear\n' - coverage run flood_forecast/trainer.py -p tests/dlinear.json + coverage run flood_forecast/trainer.py -p tests/test_json_config/dlinear.json echo -e 'running custom_encode.json\n' - coverage run flood_forecast/trainer.py -p tests/custom_encode.json - echo -e 'running multi_decoder_test \n' - coverage run flood_forecast/trainer.py -p tests/multi_decoder_test.json - echo -e 'test_dual \n' - coverage run flood_forecast/trainer.py -p tests/test_dual.json + coverage run flood_forecast/trainer.py -p tests/test_json_config/custom_encode.json + echo -e 'running multi_decoder_tests \n' + coverage run flood_forecast/trainer.py -p tests/test_json_config/multi_decoder_tests.json + echo -e 'tests_dual \n' + coverage run flood_forecast/trainer.py -p tests/test_json_config/tests_dual.json echo -e 'running dsanet \n' - coverage run flood_forecast/trainer.py -p tests/dsanet.json + coverage run flood_forecast/trainer.py -p tests/test_json_config/dsanet.json - store_test_results: - path: test-results + path: tests-results - store_artifacts: - path: test-results - destination: test-results-trainer2 + path: tests-results + destination: tests-results-trainer2 - run: name: upload results when: always command: bash <(curl -s https://codecov.io/bash) -cF python - trainer_test2: + trainer_tests2: <<: *defaults steps: - attach_workspace: @@ -378,31 +376,31 @@ jobs: name: Trainer tests 2 when: always command: | - echo -e 'running trainer_lstm_test \n ' - coverage run flood_forecast/trainer.py -p tests/lstm_test.json - echo -e 'running trainer_multi_test \n' - coverage run flood_forecast/trainer.py -p tests/multi_test.json - echo -e 'running trainer_full_transformer_test \n' - coverage run flood_forecast/trainer.py -p tests/full_transformer.json - echo -e 'running da_rnn_test \n' - coverage run flood_forecast/trainer.py -p tests/da_rnn.json + echo -e 'running trainer_lstm_tests \n ' + coverage run flood_forecast/trainer.py -p tests/test_json_config/lstm_test.json + echo -e 'running trainer_multi_tests \n' + coverage run flood_forecast/trainer.py -p tests/test_json_config/multi_test.json + echo -e 'running trainer_full_transformer_tests \n' + coverage run flood_forecast/trainer.py -p tests/test_json_config/full_transformer.json + echo -e 'running da_rnn_tests \n' + coverage run flood_forecast/trainer.py -p tests/test_json_config/da_rnn.json echo -e 'running auto_encoder \n' - coverage run flood_forecast/meta_train.py -p tests/auto_encoder.json - echo -e 'running trainer_decoder_test \n' - coverage run flood_forecast/trainer.py -p tests/decoder_test.json + coverage run flood_forecast/meta_train.py -p tests/test_json_config/auto_encoder.json + echo -e 'running trainer_decoder_tests \n' + coverage run flood_forecast/trainer.py -p tests/test_json_config/decoder_test.json - store_test_results: - path: test-results + path: tests-results - store_artifacts: - path: test-results - destination: test-results-trainer + path: tests-results + destination: tests-results-trainer - run: name: upload results when: always command: bash <(curl -s https://codecov.io/bash) -cF python - plot_test: + plot_tests: <<: *defaults steps: - attach_workspace: @@ -429,50 +427,50 @@ jobs: command: | coverage run -m unittest -v tests/test_plot.py bash <(curl -s https://codecov.io/bash) -cF python - coverage run -m unittest -v tests/test_explain_model_output.py + coverage run -m unittest -v tests/test_json_config/test_explain_model_output.py - run: name: upload_stuff when: always command: bash <(curl -s https://codecov.io/bash) -cF python - store_test_results: - path: test-results + path: tests-results - store_artifacts: - path: test-results - destination: test-results-plot + path: tests-results + destination: tests-results-plot workflows: version: 2 - test_and_build: + tests_and_build: jobs: - setup_and_install - linting: requires: - setup_and_install - - evaluator_test: + - evaluator_tests: requires: - setup_and_install - - data_quality_test: + - data_quality_tests: requires: - setup_and_install - - model_basic_test: + - model_basic_tests: requires: - setup_and_install - - decoder_test: + - decoder_tests: requires: - setup_and_install - - trainer_test: + - trainer_tests: requires: - linting - - plot_test: + - plot_tests: requires: - setup_and_install - - trainer_test1: + - trainer_tests1: requires: - setup_and_install - - trainer_test2: + - trainer_tests2: requires: - setup_and_install diff --git a/.idea/workspace.xml b/.idea/workspace.xml index 2967b4ec5..4f776cf9e 100644 --- a/.idea/workspace.xml +++ b/.idea/workspace.xml @@ -6,11 +6,6 @@ - - - - - { "keyToString": { + "ACTIVE_CLOUD_PROJECT_ACCOUNT": "igodfried@isaac26.com", + "ACTIVE_CLOUD_PROJECT_ID": "dashcam-examination", + "ACTIVE_CLOUD_PROJECT_NAME": "dashcam-examination", + "ACTIVE_CLOUD_PROJECT_NUMBER": "752787411222", "Python tests.Python tests for test_cross_vivit.TestCrossVivVit.executor": "Run", "Python tests.Python tests for test_cross_vivit.TestCrossVivVit.test_forward.executor": "Run", "Python tests.Python tests for test_cross_vivit.TestCrossVivVit.test_positional_encoding.executor": "Run", @@ -48,7 +47,7 @@ "Python tests.Python tests for test_variable_length.TestVariableLength.executor": "Run", "Python tests.Python tests in test_cross_vivit.py.executor": "Run", "RunOnceActivity.ShowReadmeOnStart": "true", - "com.google.cloudcode.ide_session_index": "20240803_0000", + "com.google.cloudcode.ide_session_index": "20241201_0003", "git-widget-placeholder": "multimodal__models", "node.js.detected.package.eslint": "true", "node.js.detected.package.stylelint": "true", @@ -155,8 +154,8 @@ - @@ -170,6 +169,11 @@ 1720330545131 + + + + + diff --git a/docs/requirements.txt b/docs/requirements.txt index 99437fb7b..d8ef89674 100644 --- a/docs/requirements.txt +++ b/docs/requirements.txt @@ -1,13 +1,27 @@ -sphinx -sphinx-rtd-theme -sphinx-autodoc-typehints +shap==0.46.0 +scikit-learn>=1.0.1 pandas -numpy torch -matplotlib -plotly +tb-nightly +seaborn +future +h5py +wandb==0.17.2 +google-cloud google-cloud-storage -scikit-learn -wandb -shap +plotly~=5.24.0 +pytz>=2022.1 +setuptools~=69.5.1 +numpy==1.26 +requests +torchvision>=0.6.0 +mpld3>=0.5 +numba>=0.50 +sphinx +sphinx-rtd-theme +sphinx-autodoc-typehints +sphinx einops +pytorch-tsmixer +einsum +jaxtyping diff --git a/docs/source/basic_ae.rst b/docs/source/basic_ae.rst index c9b0eecf7..407fe5575 100644 --- a/docs/source/basic_ae.rst +++ b/docs/source/basic_ae.rst @@ -1,5 +1,5 @@ -Simple AE -============== +Simple Auto Encoder +================== .. automodule:: flood_forecast.meta_models.basic_ae :members: diff --git a/docs/source/basic_utils.rst b/docs/source/basic_utils.rst index 0c2f639af..217e07e0d 100644 --- a/docs/source/basic_utils.rst +++ b/docs/source/basic_utils.rst @@ -1,5 +1,5 @@ Basic Google Cloud Platform Utilities -===================================== +====================================== Flow Forecast natively integrates with Google Cloud Platform. diff --git a/docs/source/custom_opt.rst b/docs/source/custom_opt.rst index 6c27e1a9a..0d94746d0 100644 --- a/docs/source/custom_opt.rst +++ b/docs/source/custom_opt.rst @@ -1,5 +1,5 @@ -Custom Optimizers and more -========================== +Custom Optimizers +==================== .. automodule:: flood_forecast.custom.custom_opt :members: diff --git a/flood_forecast/basic/base_line_methods.py b/flood_forecast/basic/base_line_methods.py index 78afd0b12..9ce031a95 100755 --- a/flood_forecast/basic/base_line_methods.py +++ b/flood_forecast/basic/base_line_methods.py @@ -18,13 +18,13 @@ def __init__(self, seq_length: int, n_time_series: int, output_seq_len=1, metric self.metric_function = self.metric_dict[metric] def forward(self, x: torch.Tensor) -> torch.Tensor: - """_summary_ + """The forward pass of the NaiveModel - Args: - x (torch.Tensor): _description_ + param x: The input tensor of shape (batch_size, seq_len, n_time_series) + type x: torch.Tensor Returns: - torch.Tensor: _description_ + torch.Tensor: The output tensor of shape (batch_size, output_seq_len, 1) """ return self.metric_function(x, self.output_seq_len) diff --git a/flood_forecast/basic/d_n_linear.py b/flood_forecast/basic/d_n_linear.py index 452267a58..a77ac7f97 100644 --- a/flood_forecast/basic/d_n_linear.py +++ b/flood_forecast/basic/d_n_linear.py @@ -3,7 +3,7 @@ class NLinear(nn.Module): - """Normalization-Linear.""" + """Normalization of Linear fixing.""" def __init__(self, forecast_history: int, forecast_length: int, enc_in=128, individual=False, n_targs=1): super(NLinear, self).__init__() @@ -113,11 +113,11 @@ def __init__(self, forecast_history: int, forecast_length: int, individual, enc_ # self.Linear_Trend.weight = nn.Parameter((1/self.seq_len)*torch.ones([self.pred_len2,self.seq_len])) def forward(self, x: torch.Tensor): - """The. + """The forward pass of the D-Linear model. :param x: PyTorch tensor of size [Batch, Input length, Channel] :type x: _type_ - :return: _description_ + :return: Returns the output tensor of size [Batch, Output length, Channel] :rtype: _type_ """ seasonal_init, trend_init = self.decompsition(x) diff --git a/flood_forecast/basic/gru_vanilla.py b/flood_forecast/basic/gru_vanilla.py index a6a2bdd7b..72c28f9e1 100755 --- a/flood_forecast/basic/gru_vanilla.py +++ b/flood_forecast/basic/gru_vanilla.py @@ -8,10 +8,10 @@ def __init__(self, n_time_series: int, hidden_dim: int, num_layers: int, n_targe :param n_time_series: The number of time series present in the data :type n_time_series int: - :param hidden_dim: + :param hidden_dim: The hidden dimension of the GRU. :type hidden_dim: - Note for probablistic n_targets must be set to two and actual multiple targs are not supported now. + Note for probabilistic n_targets must be set to two and actual multiple targets are not supported now. """ super(VanillaGRU, self).__init__() diff --git a/flood_forecast/evaluator.py b/flood_forecast/evaluator.py index 85c256dcd..e75d4fe48 100644 --- a/flood_forecast/evaluator.py +++ b/flood_forecast/evaluator.py @@ -31,7 +31,8 @@ def stream_baseline( river_flow_df: pd.DataFrame, forecast_column: str, hours_forecast=336 ) -> Tuple[pd.DataFrame, float]: - """Function to compute the baseline MSE by using the mean value from the train data.""" + """Function to compute the baseline MSE by using the mean value from the train data. + """ total_length = len(river_flow_df.index) train_river_data = river_flow_df[: total_length - hours_forecast] test_river_data = river_flow_df[total_length - hours_forecast:] @@ -162,8 +163,9 @@ def evaluate_model( return eval_log, df_train_and_test, forecast_start_idx, df_predictions -def run_evaluation(model, df_train_and_test, forecast_history, target_col, end_tensor, g_loss=False, eval_log={}, - end_tensor_0=None) -> Dict: +def run_evaluation(model, df_train_and_test: pd.DataFrame, forecast_history, target_col: str, end_tensor, g_loss=False, + eval_log: Dict = {}, end_tensor_0=None) -> Dict: + """Function to run evaluation on the model.""" inference_params = model.params["inference_params"] for evaluation_metric in model.crit: idx = 0 diff --git a/flood_forecast/explain_model_output.py b/flood_forecast/explain_model_output.py index f47731193..3756fa7a9 100644 --- a/flood_forecast/explain_model_output.py +++ b/flood_forecast/explain_model_output.py @@ -18,7 +18,7 @@ def handle_dl_output(dl, dl_class: str, datetime_start: datetime, device: str) -> Tuple[torch.Tensor, int]: """ - :param dl: The test data-loader. Should be passed directly + :param dl: The test data-loader. Should be passed directly. :type dl: Union[CSVTestLoader, TemporalTestLoader] :param dl_class: A string that is the name of DL passef from the params file :type dl_class: str diff --git a/flood_forecast/preprocessing/multimodal_loaders.py b/flood_forecast/preprocessing/multimodal_loaders.py new file mode 100644 index 000000000..77e756e75 --- /dev/null +++ b/flood_forecast/preprocessing/multimodal_loaders.py @@ -0,0 +1,239 @@ +from torch.utils.data import Dataset +import torch +import pandas as pd +from typing import Dict, List, Optional, Tuple, Union, Any +from pathlib import Path +import os +from PIL import Image +import torchvision.transforms as transforms +from datetime import datetime +from flood_forecast.preprocessing.pytorch_loaders import CSVDataLoader, CSVTestLoader + + +class ImageSequenceHelper: + """Helper class to handle loading and processing of image sequences.""" + + def __init__( + self, + cache_dir: Optional[str] = None, + transform: Optional[transforms.Compose] = None, + cloud_config: Optional[Dict] = None + ): + """Initialize the image sequence helper ad performs manipulations on the images. + :param cache_dir: Directory to cache downloaded images + :type cache_dir: str + :param transform: Image transformation pipeline + :type transform: transforms.Compose + :param cloud_config: Configuration for cloud storage + :type cloud_config: Dict + + """ + self.cache_dir = cache_dir if cache_dir else "./.cache" + self.transform = transform if transform else transforms.Compose([ + transforms.Resize((224, 224)), + transforms.ToTensor(), + ]) + self.cloud_config = cloud_config + os.makedirs(self.cache_dir, exist_ok=True) + + def download_from_cloud(self, path: str) -> str: + """Download file from cloud storage if needed""" + if path.startswith(("gs://", "s3://", "azure://")): + local_path = os.path.join(self.cache_dir, Path(path).name) + if not os.path.exists(local_path): + # Implement cloud download logic based on path prefix + if path.startswith("gs://"): + # Google Cloud Storage logic + pass + elif path.startswith("s3://"): + # AWS S3 logic + pass + elif path.startswith("azure://"): + # Azure Blob Storage logic + pass + return local_path + return path + + def load_context_sequence( + self, + image_paths: List[str], + fill_method: str = "zero" + ) -> torch.Tensor: + """Load a sequence of images and handle missing values + + Args: + image_paths: List of paths to images + fill_method: Method to handle missing images ('zero', 'previous', 'interpolate') + + Returns: + Tensor of shape (sequence_length, channels, height, width) + """ + images = [] + previous_img = None + + for path in image_paths: + if not path or pd.isna(path): + if fill_method == "zero": + img_tensor = torch.zeros((3, 224, 224)) + elif fill_method == "previous" and previous_img is not None: + img_tensor = previous_img + else: + img_tensor = torch.zeros((3, 224, 224)) + else: + local_path = self.download_from_cloud(path) + img = Image.open(local_path).convert('RGB') + img_tensor = self.transform(img) + previous_img = img_tensor + + images.append(img_tensor) + + return torch.stack(images) + + +class UniformMultiModalLoader(CSVDataLoader): + """A data loader for multimodal time series data where different modalities + are aligned with the time series at regular intervals.""" + + def __init__( + self, + csv_data_loader_params: Dict[str, Any], + image_config: Optional[Dict[str, Any]] = None, + text_config: Optional[Dict[str, Any]] = None + ): + """Initializes the UniformMultiModal data loader class + :param csv_data_loader_params: Parameters for the base CSVDataLoader. This should + :type csv_data_loader_params: Dict[str, Any] + :param image_config: Configuration for image modality + :param text_config: Configuration for text modality + + """ + super().__init__(**csv_data_loader_params) + + # Initialize image helper if image config is provided + self.image_helper = None + self.image_path_col = None + if image_config: + self.image_helper = ImageSequenceHelper( + cache_dir=image_config.get('cache_dir'), + transform=image_config.get('transform'), + cloud_config=image_config.get('cloud_config') + ) + self.image_path_col = image_config['path_col'] + + # Validate that image path column exists + if self.image_path_col not in self.df.columns: + raise ValueError(f"Image path column {self.image_path_col} not found in dataframe") + + # Store configs for potential future use + self.image_config = image_config + self.text_config = text_config + + def __getitem__(self, idx: int) -> Tuple[Dict[str, torch.Tensor], torch.Tensor]: + """Get a single item from the dataset + + Args: + idx: Index to retrieve + + Returns: + Tuple of: + - Dictionary containing: + - 'time_series': Time series tensor from base CSVDataLoader + - 'images': Image sequence tensor if image_config provided + - (future) 'text': Text tensor if text_config provided + - Target tensor + """ + # Get base time series data from parent class + ts_src_data, ts_trg_dat = super().__getitem__(idx) + + # Initialize return dictionary with time series data + return_dict = { + 'time_series': ts_src_data + } + + # Add image data if configured + if self.image_helper: + image_paths = self.df[self.image_path_col].iloc[ + idx: self.forecast_history + idx + ].tolist() + + images = self.image_helper.load_context_sequence( + image_paths, + fill_method=self.image_config.get('fill_method', 'zero') + ) + return_dict['images'] = images + + # Text modality could be added here in the future + + return return_dict, ts_trg_dat + + def get_from_start_date(self, forecast_start: datetime): + """Get data starting from a specific date + + This overrides the parent method to ensure proper handling of all modalities + """ + dt_row = self.original_df[ + self.original_df["datetime"] == forecast_start + ] + revised_index = dt_row.index[0] + return self.__getitem__(revised_index - self.forecast_history) + + +class UniformMultiModalTestLoader(CSVTestLoader): + """Test data loader for multimodal time series data""" + + def __init__( + self, + df_path: str, + forecast_total: int, + image_config: Optional[Dict[str, Any]] = None, + **kwargs + ): + """Initialize the test loader. + + Args: + df_path: Path to the CSV file + forecast_total: Total forecast length + image_config: Configuration for image modality + **kwargs: Additional arguments for CSVTestLoader + """ + super().__init__(df_path, forecast_total, **kwargs) + + # Initialize image helper if needed + self.image_helper = None + self.image_path_col = None + if image_config: + self.image_helper = ImageSequenceHelper( + cache_dir=image_config.get('cache_dir'), + transform=image_config.get('transform'), + cloud_config=image_config.get('cloud_config') + ) + self.image_path_col = image_config['path_col'] + + def __getitem__(self, idx): + """Get a test item including all modalities""" + # Get base time series data + if self.target_supplied: + historical_rows = self.df.iloc[idx: self.forecast_history + idx] + target_idx_start = self.forecast_history + idx + + all_rows_orig = self.original_df.iloc[ + idx: self.forecast_total + target_idx_start + ].copy() + + return_dict = { + 'time_series': torch.from_numpy(historical_rows.to_numpy()).float() + } + + # Add image data if configured + if self.image_helper: + image_paths = self.df[self.image_path_col].iloc[ + idx: self.forecast_history + idx + ].tolist() + + images = self.image_helper.load_context_sequence( + image_paths, + fill_method='zero' + ) + return_dict['images'] = images + + return return_dict, all_rows_orig, target_idx_start diff --git a/flood_forecast/preprocessing/pytorch_loaders.py b/flood_forecast/preprocessing/pytorch_loaders.py index f9a355607..e8becba9e 100644 --- a/flood_forecast/preprocessing/pytorch_loaders.py +++ b/flood_forecast/preprocessing/pytorch_loaders.py @@ -32,6 +32,7 @@ def __init__( ): """ A data loader that takes a CSV file and properly batches for use in training/eval a PyTorch model + :param file_path: The path to the CSV file you wish to use (GCS compatible) or a Pandas dataframe. :param forecast_history: This is the length of the historical time series data you wish to utilize for forecasting @@ -39,7 +40,7 @@ def __init__( equal history_length) :param relevant_cols: Supply column names you wish to predict in the forecast (others will not be used) :param target_col: The target column or columns you to predict. If you only have one still use a list ['cfs'] - :param scaling: (highly reccomended) If provided should be a subclass of sklearn.base.BaseEstimator + :param scaling: (highly recommended) If provided should be a subclass of sklearn.base.BaseEstimator and sklearn.base.TransformerMixin) i.e StandardScaler, MaxAbsScaler, MinMaxScaler, etc) Note without a scaler the loss is likely to explode and cause infinite loss which will corrupt weights :param start_stamp int: Optional if you want to only use part of a CSV for training, validation diff --git a/flood_forecast/transformer_xl/cross_former.py b/flood_forecast/transformer_xl/cross_former.py index 903388d4a..25f01bad8 100644 --- a/flood_forecast/transformer_xl/cross_former.py +++ b/flood_forecast/transformer_xl/cross_former.py @@ -206,7 +206,7 @@ def forward(self, x): class Encoder(nn.Module): - """The Encoder of Crossformer.""" + """The Encoder of Crossformer model.""" def __init__( self, diff --git a/tests/test_inf_single.json b/tests/test_data/test_inf_single.json similarity index 100% rename from tests/test_inf_single.json rename to tests/test_data/test_inf_single.json diff --git a/tests/test_informer.json b/tests/test_data/test_informer.json similarity index 100% rename from tests/test_informer.json rename to tests/test_data/test_informer.json diff --git a/tests/test_data2/multimodal_data.csv b/tests/test_data2/multimodal_data.csv new file mode 100644 index 000000000..1a5defd3d --- /dev/null +++ b/tests/test_data2/multimodal_data.csv @@ -0,0 +1,5730 @@ +,hour_updated,p01m,valid,tmpf,dwpf,ice_accretion_1hr,mslp,drct,sped,alti,relh,sknt,feel,vsby,gust,skyc1,peak_wind_gust,snowdepth,station_id,index,datetime,cfs,height,sensing_time,base_url +245913,2023-07-06 16:00:00+00:00,0.0,2023-07-06 15:56,85.0,67.0,,1013.3,,3.45,29.95,54.89,3.0,87.59,,,M,,,GNR,1051610,2023-07-06 16:00:00+00:00,773.0,2.31,2023-07-06 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07:56,53.0,50.0,,1010.9,0.0,0.0,29.85,89.51,0.0,53.0,,,M,,,GNR,1053978,2023-07-31 08:00:00+00:00,734.0,2.27,, +246506,2023-07-31 09:00:00+00:00,0.0,2023-07-31 08:56,53.0,50.0,,1011.3,0.0,0.0,29.86,89.51,0.0,53.0,,,M,,,GNR,1053982,2023-07-31 09:00:00+00:00,734.0,2.27,, +246507,2023-07-31 10:00:00+00:00,0.0,2023-07-31 09:56,56.0,51.0,,1011.2,0.0,0.0,29.86,83.26,0.0,56.0,,,M,,,GNR,1053986,2023-07-31 10:00:00+00:00,724.0,2.26,, +246508,2023-07-31 11:00:00+00:00,0.0,2023-07-31 10:56,57.0,52.0,,1011.5,0.0,0.0,29.87,83.33,0.0,57.0,,,M,,,GNR,1053990,2023-07-31 11:00:00+00:00,724.0,2.26,, +246509,2023-07-31 12:00:00+00:00,0.0,2023-07-31 11:56,58.0,52.0,,1012.1,0.0,0.0,29.89,80.38,0.0,58.0,,,M,,,GNR,1053994,2023-07-31 12:00:00+00:00,715.0,2.25,, +246510,2023-07-31 13:00:00+00:00,0.0,2023-07-31 12:56,59.0,52.0,,1012.4,,4.6,29.9,77.55,4.0,59.0,,,M,,,GNR,1053998,2023-07-31 13:00:00+00:00,715.0,2.25,, +246511,2023-07-31 14:00:00+00:00,0.25,2023-07-31 13:56,60.0,54.0,,1012.5,0.0,0.0,29.9,80.53,0.0,60.0,,,M,,,GNR,1054002,2023-07-31 14:00:00+00:00,715.0,2.25,, +246512,2023-07-31 15:00:00+00:00,0.0,2023-07-31 14:56,62.0,55.0,,1012.4,0.0,0.0,29.89,77.81,0.0,62.0,,,M,,,GNR,1054006,2023-07-31 15:00:00+00:00,706.0,2.24,, +246513,2023-07-31 16:00:00+00:00,0.0,2023-07-31 15:56,64.0,54.0,,1012.2,0.0,0.0,29.89,69.92,0.0,64.0,,,M,,,GNR,1054010,2023-07-31 16:00:00+00:00,706.0,2.24,, +246514,2023-07-31 17:00:00+00:00,0.0,2023-07-31 16:56,65.0,56.0,,1011.9,,3.45,29.88,72.62,3.0,65.0,,,M,,,GNR,1054014,2023-07-31 17:00:00+00:00,5390.0,4.99,, +246515,2023-07-31 18:00:00+00:00,0.0,2023-07-31 17:56,65.0,58.0,,1011.6,,4.6,29.87,78.06,4.0,65.0,,,M,,,GNR,1054018,2023-07-31 18:00:00+00:00,5420.0,5.0,, +246516,2023-07-31 19:00:00+00:00,0.0,2023-07-31 18:56,68.0,53.0,,1011.2,,3.45,29.86,58.67,3.0,68.0,,,M,,,GNR,1054022,2023-07-31 19:00:00+00:00,4040.0,4.37,, +246517,2023-07-31 20:00:00+00:00,0.0,2023-07-31 19:56,62.0,54.0,,1012.3,340.0,14.95,29.89,75.02,13.0,62.0,,19.0,M,,,GNR,1054026,2023-07-31 20:00:00+00:00,1750.0,3.11,, +246518,2023-07-31 21:00:00+00:00,0.0,2023-07-31 20:56,62.0,53.0,,1012.2,350.0,11.5,29.89,72.32,10.0,62.0,,16.0,M,,,GNR,1054030,2023-07-31 21:00:00+00:00,1010.0,2.53,, +246519,2023-07-31 22:00:00+00:00,0.0,2023-07-31 21:56,61.0,53.0,,1013.1,330.0,6.9,29.91,74.93,6.0,61.0,,,M,,,GNR,1054034,2023-07-31 22:00:00+00:00,803.0,2.34,, +246520,2023-07-31 23:00:00+00:00,0.0,2023-07-31 22:56,61.0,54.0,,1013.5,310.0,4.6,29.92,77.72,4.0,61.0,,,M,,,GNR,1054038,2023-07-31 23:00:00+00:00,7790.0,5.98,, +246521,2023-08-01 00:00:00+00:00,0.0,2023-07-31 23:56,59.0,55.0,,1013.8,320.0,4.6,29.93,86.56,4.0,59.0,,,M,,,GNR,1054042,2023-08-01 00:00:00+00:00,7820.0,5.99,, +246522,2023-08-01 01:00:00+00:00,2.29,2023-08-01 00:56,56.0,53.0,,1014.7,300.0,4.6,29.96,89.64,4.0,56.0,,,M,,,GNR,1054046,2023-08-01 01:00:00+00:00,7840.0,6.0,, +246523,2023-08-01 02:00:00+00:00,0.0,2023-08-01 01:56,55.0,52.0,,1015.0,290.0,3.45,29.97,89.59,3.0,55.0,,,M,,,GNR,1054050,2023-08-01 02:00:00+00:00,7870.0,6.01,, +246524,2023-08-01 03:00:00+00:00,0.0,2023-08-01 02:56,56.0,53.0,,1015.1,290.0,3.45,29.97,89.64,3.0,56.0,,,M,,,GNR,1054054,2023-08-01 03:00:00+00:00,4040.0,4.37,, +246525,2023-08-01 04:00:00+00:00,0.0,2023-08-01 03:56,55.0,52.0,,1015.3,310.0,4.6,29.98,89.59,4.0,55.0,,,M,,,GNR,1054058,2023-08-01 04:00:00+00:00,1680.0,3.06,, +246526,2023-08-01 05:00:00+00:00,0.0,2023-08-01 04:56,55.0,51.0,,1015.3,310.0,6.9,29.98,86.34,6.0,55.0,,,M,,,GNR,1054062,2023-08-01 05:00:00+00:00,987.0,2.51,, +246527,2023-08-01 06:00:00+00:00,0.0,2023-08-01 05:56,55.0,52.0,,1015.4,340.0,5.75,29.98,89.59,5.0,55.0,,,M,,,GNR,1054066,2023-08-01 06:00:00+00:00,753.0,2.29,, +246528,2023-08-01 07:00:00+00:00,0.0,2023-08-01 06:56,52.0,50.0,,1015.3,0.0,0.0,29.98,92.86,0.0,52.0,,,M,,,GNR,1054070,2023-08-01 07:00:00+00:00,715.0,2.25,, +246529,2023-08-01 08:00:00+00:00,0.0,2023-08-01 07:56,54.0,50.0,,1015.8,360.0,5.75,29.99,86.29,5.0,54.0,,,M,,,GNR,1054074,2023-08-01 08:00:00+00:00,696.0,2.23,, +246530,2023-08-01 09:00:00+00:00,0.0,2023-08-01 08:56,51.0,48.0,,1016.0,340.0,4.6,30.0,89.42,4.0,51.0,,,M,,,GNR,1054078,2023-08-01 09:00:00+00:00,696.0,2.23,, +246531,2023-08-01 10:00:00+00:00,0.0,2023-08-01 09:56,52.0,48.0,,1016.7,330.0,6.9,30.01,86.17,6.0,52.0,,,M,,,GNR,1054082,2023-08-01 10:00:00+00:00,696.0,2.23,, +246532,2023-08-01 11:00:00+00:00,0.0,2023-08-01 10:56,55.0,50.0,,1017.2,350.0,4.6,30.03,83.2,4.0,55.0,,,M,,,GNR,1054086,2023-08-01 11:00:00+00:00,687.0,2.22,, +246533,2023-08-01 12:00:00+00:00,0.0,2023-08-01 11:56,57.0,49.0,,1017.8,340.0,6.9,30.05,74.55,6.0,57.0,,,M,,,GNR,1054090,2023-08-01 12:00:00+00:00,687.0,2.22,, +246534,2023-08-01 13:00:00+00:00,0.0,2023-08-01 12:56,60.0,49.0,,1018.1,320.0,8.05,30.06,66.95,7.0,60.0,,,M,,,GNR,1054094,2023-08-01 13:00:00+00:00,687.0,2.22,, +246535,2023-08-01 14:00:00+00:00,0.0,2023-08-01 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19:56,69.0,63.0,,1014.8,120.0,9.2,29.97,81.19,8.0,69.0,,,M,,,GNR,1055562,2023-08-16 20:00:00+00:00,8780.0,6.37,, +246902,2023-08-16 21:00:00+00:00,0.25,2023-08-16 20:56,66.0,63.0,,1015.3,140.0,8.05,29.98,90.05,7.0,66.0,,,M,,,GNR,1055566,2023-08-16 21:00:00+00:00,8830.0,6.39,, +246903,2023-08-16 22:00:00+00:00,0.51,2023-08-16 21:56,65.0,63.0,,1015.5,,5.75,29.99,93.24,5.0,65.0,,,M,,,GNR,1055570,2023-08-16 22:00:00+00:00,8860.0,6.4,, +246904,2023-08-16 23:00:00+00:00,0.0,2023-08-16 22:56,64.0,63.0,,1015.1,,4.6,29.98,96.55,4.0,64.0,,,M,,,GNR,1055574,2023-08-16 23:00:00+00:00,8860.0,6.4,, +246905,2023-08-17 00:00:00+00:00,0.0,2023-08-16 23:56,64.0,63.0,,1015.4,140.0,5.75,29.99,96.55,5.0,64.0,,,M,,,GNR,1055578,2023-08-17 00:00:00+00:00,8860.0,6.4,, +246906,2023-08-17 01:00:00+00:00,0.0,2023-08-17 00:56,63.0,63.0,,1015.9,150.0,5.75,30.01,100.0,5.0,63.0,,,M,,,GNR,1055582,2023-08-17 01:00:00+00:00,8880.0,6.41,, +246907,2023-08-17 02:00:00+00:00,0.0,2023-08-17 01:56,64.0,63.0,,1016.2,170.0,3.45,30.02,96.55,3.0,64.0,,,M,,,GNR,1055586,2023-08-17 02:00:00+00:00,8910.0,6.42,, +246908,2023-08-17 03:00:00+00:00,0.0,2023-08-17 02:56,64.0,63.0,,1016.4,150.0,3.45,30.02,96.55,3.0,64.0,,,M,,,GNR,1055590,2023-08-17 03:00:00+00:00,8860.0,6.4,, +246909,2023-08-17 04:00:00+00:00,0.0,2023-08-17 03:56,63.0,62.0,,1016.5,0.0,0.0,30.03,96.54,0.0,63.0,,,M,,,GNR,1055594,2023-08-17 04:00:00+00:00,4190.0,4.44,, +246910,2023-08-17 05:00:00+00:00,0.0,2023-08-17 04:56,63.0,62.0,,1016.5,,3.45,30.02,96.54,3.0,63.0,,,M,,,GNR,1055598,2023-08-17 05:00:00+00:00,1690.0,3.07,, +246911,2023-08-17 06:00:00+00:00,0.0,2023-08-17 05:56,63.0,61.0,,1016.4,,3.45,30.02,93.18,3.0,63.0,,,M,,,GNR,1055602,2023-08-17 06:00:00+00:00,987.0,2.51,, +246912,2023-08-17 07:00:00+00:00,0.0,2023-08-17 06:56,62.0,61.0,,1016.2,150.0,4.6,30.02,96.52,4.0,62.0,,,M,,,GNR,1055606,2023-08-17 07:00:00+00:00,744.0,2.28,, +246913,2023-08-17 08:00:00+00:00,0.0,2023-08-17 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13:56,63.0,62.0,,1017.8,,4.6,30.06,96.54,4.0,63.0,,,M,,,GNR,1055634,2023-08-17 14:00:00+00:00,660.0,2.19,, +246920,2023-08-17 15:00:00+00:00,0.0,2023-08-17 14:56,64.0,61.0,,1017.7,,4.6,30.06,89.97,4.0,64.0,,,M,,,GNR,1055638,2023-08-17 15:00:00+00:00,660.0,2.19,, +246921,2023-08-17 16:00:00+00:00,0.0,2023-08-17 15:56,64.0,61.0,,1017.4,150.0,8.05,30.05,89.97,7.0,64.0,,,M,,,GNR,1055642,2023-08-17 16:00:00+00:00,660.0,2.19,, +246922,2023-08-17 17:00:00+00:00,0.0,2023-08-17 16:56,66.0,61.0,,1016.9,140.0,8.05,30.04,83.91,7.0,66.0,,15.0,M,,,GNR,1055646,2023-08-17 17:00:00+00:00,5350.0,4.97,, +246923,2023-08-17 18:00:00+00:00,0.0,2023-08-17 17:56,66.0,61.0,,1016.8,,5.75,30.03,83.91,5.0,66.0,,,M,,,GNR,1055650,2023-08-17 18:00:00+00:00,5370.0,4.98,, +246924,2023-08-17 19:00:00+00:00,0.0,2023-08-17 18:56,66.0,61.0,,1016.7,,5.75,30.03,83.91,5.0,66.0,,,M,,,GNR,1055654,2023-08-17 19:00:00+00:00,8120.0,6.11,, +246925,2023-08-17 20:00:00+00:00,0.0,2023-08-17 19:56,65.0,61.0,,1016.5,,6.9,30.02,86.88,6.0,65.0,,,M,,,GNR,1055658,2023-08-17 20:00:00+00:00,8810.0,6.38,, +246926,2023-08-17 21:00:00+00:00,0.0,2023-08-17 20:56,65.0,61.0,,1016.5,,5.75,30.02,86.88,5.0,65.0,,,M,,,GNR,1055662,2023-08-17 21:00:00+00:00,8830.0,6.39,, +246927,2023-08-17 22:00:00+00:00,0.0,2023-08-17 21:56,65.0,61.0,,1016.0,0.0,0.0,30.0,86.88,0.0,65.0,,,M,,,GNR,1055666,2023-08-17 22:00:00+00:00,8860.0,6.4,, +246928,2023-08-17 23:00:00+00:00,0.25,2023-08-17 22:56,63.0,62.0,,1015.6,,5.75,29.99,96.54,5.0,63.0,,,M,,,GNR,1055670,2023-08-17 23:00:00+00:00,8860.0,6.4,, +246929,2023-08-18 00:00:00+00:00,0.0,2023-08-17 23:56,63.0,62.0,,1015.6,,,29.99,96.54,,63.0,,,M,,,GNR,1055674,2023-08-18 00:00:00+00:00,8910.0,6.42,, +246930,2023-08-18 01:00:00+00:00,0.0,2023-08-18 00:56,63.0,61.0,,1015.3,,4.6,29.98,93.18,4.0,63.0,,,M,,,GNR,1055678,2023-08-18 01:00:00+00:00,8940.0,6.43,, +246931,2023-08-18 02:00:00+00:00,0.0,2023-08-18 01:56,62.0,61.0,,1014.7,,6.9,29.97,96.52,6.0,62.0,,,M,,,GNR,1055682,2023-08-18 02:00:00+00:00,8940.0,6.43,, +246932,2023-08-18 03:00:00+00:00,0.25,2023-08-18 02:56,62.0,61.0,,1014.3,140.0,8.05,29.95,96.52,7.0,62.0,,,M,,,GNR,1055686,2023-08-18 03:00:00+00:00,8910.0,6.42,, +246933,2023-08-18 04:00:00+00:00,0.51,2023-08-18 03:56,62.0,61.0,,1013.8,150.0,6.9,29.94,96.52,6.0,62.0,,14.0,M,,,GNR,1055690,2023-08-18 04:00:00+00:00,3930.0,4.32,, +246934,2023-08-18 05:00:00+00:00,0.0,2023-08-18 04:56,62.0,61.0,,1013.3,160.0,10.35,29.93,96.52,9.0,62.0,,17.0,M,,,GNR,1055694,2023-08-18 05:00:00+00:00,1620.0,3.02,, +246935,2023-08-18 06:00:00+00:00,0.0,2023-08-18 05:56,62.0,62.0,,1012.7,,4.6,29.91,100.0,4.0,62.0,,,M,,,GNR,1055698,2023-08-18 06:00:00+00:00,953.0,2.48,, +246936,2023-08-18 07:00:00+00:00,0.51,2023-08-18 06:56,62.0,61.0,,1011.9,130.0,9.2,29.89,96.52,8.0,62.0,,,M,,,GNR,1055702,2023-08-18 07:00:00+00:00,744.0,2.28,, +246937,2023-08-18 08:00:00+00:00,0.0,2023-08-18 07:56,62.0,61.0,,1011.3,140.0,10.35,29.87,96.52,9.0,62.0,,,M,,,GNR,1055706,2023-08-18 08:00:00+00:00,687.0,2.22,, +246938,2023-08-18 09:00:00+00:00,0.0,2023-08-18 08:56,62.0,61.0,,1010.4,120.0,8.05,29.84,96.52,7.0,62.0,,,M,,,GNR,1055710,2023-08-18 09:00:00+00:00,669.0,2.2,, +246939,2023-08-18 10:00:00+00:00,0.25,2023-08-18 09:56,62.0,61.0,,1010.4,130.0,8.05,29.84,96.52,7.0,62.0,,,M,,,GNR,1055714,2023-08-18 10:00:00+00:00,660.0,2.19,, +246940,2023-08-18 11:00:00+00:00,0.0,2023-08-18 10:56,62.0,62.0,,1009.9,120.0,10.35,29.83,100.0,9.0,62.0,,,M,,,GNR,1055718,2023-08-18 11:00:00+00:00,660.0,2.19,, +246941,2023-08-18 12:00:00+00:00,0.0,2023-08-18 11:56,63.0,62.0,,1009.5,130.0,9.2,29.81,96.54,8.0,63.0,,,M,,,GNR,1055722,2023-08-18 12:00:00+00:00,660.0,2.19,, +246942,2023-08-18 13:00:00+00:00,0.0,2023-08-18 12:56,63.0,62.0,,1009.5,130.0,8.05,29.81,96.54,7.0,63.0,,,M,,,GNR,1055726,2023-08-18 13:00:00+00:00,651.0,2.18,, +246943,2023-08-18 14:00:00+00:00,0.0,2023-08-18 13:56,64.0,63.0,,1008.7,110.0,8.05,29.79,96.55,7.0,64.0,,,M,,,GNR,1055730,2023-08-18 14:00:00+00:00,651.0,2.18,, +246944,2023-08-18 15:00:00+00:00,0.0,2023-08-18 14:56,65.0,64.0,,1007.7,140.0,10.35,29.76,96.57,9.0,65.0,,,M,,,GNR,1055734,2023-08-18 15:00:00+00:00,651.0,2.18,, +246945,2023-08-18 16:00:00+00:00,0.25,2023-08-18 15:56,65.0,64.0,,1007.6,130.0,11.5,29.76,96.57,10.0,65.0,,,M,,,GNR,1055738,2023-08-18 16:00:00+00:00,651.0,2.18,, +246946,2023-08-18 17:00:00+00:00,0.0,2023-08-18 16:56,65.0,65.0,,1006.1,120.0,9.2,29.72,100.0,8.0,65.0,,,M,,,GNR,1055742,2023-08-18 17:00:00+00:00,5320.0,4.96,, +246947,2023-08-18 18:00:00+00:00,0.0,2023-08-18 17:56,66.0,65.0,,1005.7,130.0,10.35,29.7,96.58,9.0,66.0,,,M,,,GNR,1055746,2023-08-18 18:00:00+00:00,5370.0,4.98,, +246948,2023-08-18 19:00:00+00:00,1.52,2023-08-18 18:56,67.0,65.0,,1004.5,110.0,10.35,29.67,93.29,9.0,67.0,,,M,,,GNR,1055750,2023-08-18 19:00:00+00:00,8320.0,6.19,, +246949,2023-08-18 20:00:00+00:00,2.54,2023-08-18 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08:56,26.0,22.0,,1025.1,140.0,5.75,30.21,84.59,5.0,19.27,,,M,,,GNR,1071165,2024-01-26 09:00:00+00:00,1780.0,3.13,, +250784,2024-01-26 10:00:00+00:00,0.0,2024-01-26 09:56,26.0,22.0,,1024.3,150.0,5.75,30.19,84.59,5.0,19.27,,,M,,,GNR,1071169,2024-01-26 10:00:00+00:00,1770.0,3.12,, +250785,2024-01-26 11:00:00+00:00,0.0,2024-01-26 10:56,26.0,23.0,,1023.8,130.0,8.05,30.17,88.23,7.0,17.47,,,M,,,GNR,1071173,2024-01-26 11:00:00+00:00,1770.0,3.12,, +250786,2024-01-26 12:00:00+00:00,0.0,2024-01-26 11:56,26.0,24.0,,1023.4,150.0,4.6,30.16,92.01,4.0,20.41,,,M,,,GNR,1071177,2024-01-26 12:00:00+00:00,1770.0,3.12,, +250787,2024-01-26 13:00:00+00:00,0.0,2024-01-26 12:56,26.0,25.0,,1023.6,140.0,11.5,30.17,95.93,10.0,15.44,,17.0,M,,,GNR,1071181,2024-01-26 13:00:00+00:00,1770.0,3.12,, +250788,2024-01-26 14:00:00+00:00,0.0,2024-01-26 13:56,26.0,24.0,,1023.1,130.0,9.2,30.15,92.01,8.0,16.72,,21.0,M,,,GNR,1071185,2024-01-26 14:00:00+00:00,1770.0,3.12,, +250789,2024-01-26 15:00:00+00:00,0.0,2024-01-26 14:56,26.0,25.0,,1023.8,140.0,9.2,30.17,95.93,8.0,16.72,,,M,,,GNR,1071189,2024-01-26 15:00:00+00:00,1770.0,3.12,, +250790,2024-01-26 16:00:00+00:00,1.02,2024-01-26 15:56,26.0,25.0,,1022.4,130.0,10.35,30.13,95.93,9.0,16.05,,,M,,,GNR,1071193,2024-01-26 16:00:00+00:00,1770.0,3.12,, +250791,2024-01-26 17:00:00+00:00,0.76,2024-01-26 16:56,27.0,25.0,,1021.2,130.0,6.9,30.1,92.05,6.0,19.51,,,M,,,GNR,1071197,2024-01-26 17:00:00+00:00,1780.0,3.13,, +250792,2024-01-26 18:00:00+00:00,1.02,2024-01-26 17:56,27.0,25.0,,1019.6,130.0,10.35,30.05,92.05,9.0,17.3,,,M,,,GNR,1071201,2024-01-26 18:00:00+00:00,1780.0,3.13,, +250793,2024-01-26 19:00:00+00:00,1.02,2024-01-26 18:56,27.0,25.0,,1019.2,120.0,6.9,30.03,92.05,6.0,19.51,,,M,,,GNR,1071205,2024-01-26 19:00:00+00:00,1780.0,3.13,, +250794,2024-01-26 20:00:00+00:00,1.02,2024-01-26 19:56,27.0,25.0,,1019.0,120.0,8.05,30.03,92.05,7.0,18.68,,,M,,,GNR,1071209,2024-01-26 20:00:00+00:00,1780.0,3.13,, +250795,2024-01-26 21:00:00+00:00,1.02,2024-01-26 20:56,27.0,25.0,,1019.5,120.0,5.75,30.04,92.05,5.0,20.46,,,M,,,GNR,1071213,2024-01-26 21:00:00+00:00,1780.0,3.13,, +250796,2024-01-26 22:00:00+00:00,1.52,2024-01-26 21:56,27.0,25.0,,1019.6,110.0,6.9,30.04,92.05,6.0,19.51,,,M,,,GNR,1071217,2024-01-26 22:00:00+00:00,1770.0,3.12,, +250797,2024-01-26 23:00:00+00:00,0.76,2024-01-26 22:56,26.0,24.0,,1019.4,110.0,6.9,30.04,92.01,6.0,18.3,,,M,,,GNR,1071221,2024-01-26 23:00:00+00:00,3580.0,4.15,, +250798,2024-01-27 00:00:00+00:00,0.0,2024-01-26 23:56,27.0,24.0,,1019.8,0.0,0.0,30.05,88.28,0.0,27.0,,,M,,,GNR,1071225,2024-01-27 00:00:00+00:00,8630.0,6.31,, +250799,2024-01-27 01:00:00+00:00,0.0,2024-01-27 00:56,26.0,25.0,,1019.8,0.0,0.0,30.05,95.93,0.0,26.0,,,M,,,GNR,1071229,2024-01-27 01:00:00+00:00,8700.0,6.34,, +250800,2024-01-27 02:00:00+00:00,0.0,2024-01-27 01:56,27.0,25.0,,1019.9,0.0,0.0,30.05,92.05,0.0,27.0,,,M,,,GNR,1071233,2024-01-27 02:00:00+00:00,8700.0,6.34,, +250801,2024-01-27 03:00:00+00:00,0.0,2024-01-27 02:56,27.0,26.0,,1020.5,0.0,0.0,30.07,95.95,0.0,27.0,,,M,,,GNR,1071237,2024-01-27 03:00:00+00:00,4340.0,4.51,, +250802,2024-01-27 04:00:00+00:00,0.0,2024-01-27 03:56,27.0,25.0,,1021.0,0.0,0.0,30.09,92.05,0.0,27.0,,,M,,,GNR,1071241,2024-01-27 04:00:00+00:00,2030.0,3.29,, +250803,2024-01-27 05:00:00+00:00,0.0,2024-01-27 04:56,27.0,26.0,,1021.3,0.0,0.0,30.09,95.95,0.0,27.0,,,M,,,GNR,1071245,2024-01-27 05:00:00+00:00,1800.0,3.14,, +250804,2024-01-27 06:00:00+00:00,0.0,2024-01-27 05:56,26.0,25.0,,1021.2,330.0,5.75,30.09,95.93,5.0,19.27,,,M,,,GNR,1071249,2024-01-27 06:00:00+00:00,1780.0,3.13,, +250805,2024-01-27 07:00:00+00:00,0.0,2024-01-27 06:56,27.0,25.0,,1020.4,360.0,5.75,30.07,92.05,5.0,20.46,,,M,,,GNR,1071253,2024-01-27 07:00:00+00:00,1780.0,3.13,, +250806,2024-01-27 08:00:00+00:00,0.0,2024-01-27 07:56,25.0,24.0,,1020.2,300.0,4.6,30.06,95.91,4.0,19.25,,,M,,,GNR,1071257,2024-01-27 08:00:00+00:00,1780.0,3.13,, +250807,2024-01-27 09:00:00+00:00,0.0,2024-01-27 08:56,25.0,23.0,,1020.3,350.0,4.6,30.07,91.97,4.0,19.25,,,M,,,GNR,1071261,2024-01-27 09:00:00+00:00,1780.0,3.13,, +250808,2024-01-27 10:00:00+00:00,0.0,2024-01-27 09:56,25.0,23.0,,1021.0,300.0,4.6,30.09,91.97,4.0,19.25,,,M,,,GNR,1071265,2024-01-27 10:00:00+00:00,1770.0,3.12,, +250809,2024-01-27 11:00:00+00:00,0.0,2024-01-27 10:56,24.0,23.0,,1022.0,300.0,4.6,30.11,95.89,4.0,18.08,,,M,,,GNR,1071269,2024-01-27 11:00:00+00:00,1770.0,3.12,, +250810,2024-01-27 12:00:00+00:00,0.0,2024-01-27 11:56,24.0,23.0,,1022.0,320.0,4.6,30.12,95.89,4.0,18.08,,,M,,,GNR,1071273,2024-01-27 12:00:00+00:00,1770.0,3.12,, +250811,2024-01-27 13:00:00+00:00,0.0,2024-01-27 12:56,25.0,23.0,,1022.5,320.0,3.45,30.13,91.97,3.0,20.69,,,M,,,GNR,1071277,2024-01-27 13:00:00+00:00,1770.0,3.12,, +250812,2024-01-27 14:00:00+00:00,0.0,2024-01-27 13:56,25.0,23.0,,1023.2,320.0,4.6,30.15,91.97,4.0,19.25,,,M,,,GNR,1071281,2024-01-27 14:00:00+00:00,1770.0,3.12,, +250813,2024-01-27 15:00:00+00:00,0.0,2024-01-27 14:56,26.0,23.0,,1023.2,330.0,5.75,30.15,88.23,5.0,19.27,,,M,,,GNR,1071285,2024-01-27 15:00:00+00:00,1770.0,3.12,, +250814,2024-01-27 16:00:00+00:00,0.0,2024-01-27 15:56,27.0,24.0,,1022.8,,3.45,30.14,88.28,3.0,22.97,,,M,,,GNR,1071289,2024-01-27 16:00:00+00:00,1770.0,3.12,, +250815,2024-01-27 17:00:00+00:00,0.0,2024-01-27 16:56,28.0,25.0,,1022.4,,3.45,30.13,88.33,3.0,24.12,,,M,,,GNR,1071293,2024-01-27 17:00:00+00:00,1770.0,3.12,, +250816,2024-01-27 18:00:00+00:00,0.0,2024-01-27 17:56,28.0,25.0,,1022.3,310.0,4.6,30.12,88.33,4.0,22.75,,,M,,,GNR,1071297,2024-01-27 18:00:00+00:00,1770.0,3.12,, +250817,2024-01-27 19:00:00+00:00,0.0,2024-01-27 18:56,28.0,24.0,,1022.0,330.0,6.9,30.12,84.72,6.0,20.71,,,M,,,GNR,1071301,2024-01-27 19:00:00+00:00,1770.0,3.12,, +250818,2024-01-27 20:00:00+00:00,0.0,2024-01-27 19:56,28.0,24.0,,1021.0,340.0,5.75,30.09,84.72,5.0,21.64,,,M,,,GNR,1071305,2024-01-27 20:00:00+00:00,1770.0,3.12,, +250819,2024-01-27 21:00:00+00:00,0.0,2024-01-27 20:56,28.0,25.0,,1020.8,340.0,4.6,30.08,88.33,4.0,22.75,,,M,,,GNR,1071309,2024-01-27 21:00:00+00:00,1750.0,3.11,, +250820,2024-01-27 22:00:00+00:00,0.0,2024-01-27 21:56,28.0,25.0,,1021.7,0.0,0.0,30.11,88.33,0.0,28.0,,,M,,,GNR,1071313,2024-01-27 22:00:00+00:00,1770.0,3.12,, +250821,2024-01-27 23:00:00+00:00,0.0,2024-01-27 22:56,28.0,25.0,,1021.5,310.0,3.45,30.1,88.33,3.0,24.12,,,M,,,GNR,1071317,2024-01-27 23:00:00+00:00,1770.0,3.12,, +250822,2024-01-28 00:00:00+00:00,0.0,2024-01-27 23:56,28.0,25.0,,1021.6,310.0,4.6,30.1,88.33,4.0,22.75,,,M,,,GNR,1071321,2024-01-28 00:00:00+00:00,5370.0,4.98,, +250823,2024-01-28 01:00:00+00:00,0.0,2024-01-28 00:56,28.0,25.0,,1021.0,,5.75,30.09,88.33,5.0,21.64,,,M,,,GNR,1071325,2024-01-28 01:00:00+00:00,8630.0,6.31,, +250824,2024-01-28 02:00:00+00:00,0.0,2024-01-28 01:56,28.0,25.0,,1021.0,310.0,4.6,30.09,88.33,4.0,22.75,,,M,,,GNR,1071329,2024-01-28 02:00:00+00:00,8650.0,6.32,, +250825,2024-01-28 03:00:00+00:00,0.0,2024-01-28 02:56,29.0,25.0,,1020.4,310.0,5.75,30.07,84.79,5.0,22.83,,,M,,,GNR,1071333,2024-01-28 03:00:00+00:00,8600.0,6.3,, +250826,2024-01-28 04:00:00+00:00,0.0,2024-01-28 03:56,29.0,26.0,,1020.4,0.0,0.0,30.07,88.38,0.0,29.0,,,M,,,GNR,1071337,2024-01-28 04:00:00+00:00,4040.0,4.37,, +250827,2024-01-28 05:00:00+00:00,0.0,2024-01-28 04:56,29.0,26.0,,1020.1,0.0,0.0,30.07,88.38,0.0,29.0,,,M,,,GNR,1071341,2024-01-28 05:00:00+00:00,1980.0,3.26,, +250828,2024-01-28 06:00:00+00:00,0.0,2024-01-28 05:56,29.0,26.0,,1019.1,320.0,5.75,30.04,88.38,5.0,22.83,,,M,,,GNR,1071345,2024-01-28 06:00:00+00:00,1780.0,3.13,, +250829,2024-01-28 07:00:00+00:00,0.0,2024-01-28 06:56,29.0,26.0,,1018.7,310.0,4.6,30.02,88.38,4.0,23.92,,,M,,,GNR,1071349,2024-01-28 07:00:00+00:00,1780.0,3.13,, +250830,2024-01-28 08:00:00+00:00,0.0,2024-01-28 07:56,29.0,25.0,,1017.9,320.0,10.35,30.0,84.79,9.0,19.78,,18.0,M,,,GNR,1071353,2024-01-28 08:00:00+00:00,1770.0,3.12,, +250831,2024-01-28 09:00:00+00:00,0.0,2024-01-28 08:56,29.0,25.0,,1017.3,310.0,8.05,29.98,84.79,7.0,21.12,,,M,,,GNR,1071357,2024-01-28 09:00:00+00:00,1770.0,3.12,, +250832,2024-01-28 10:00:00+00:00,0.0,2024-01-28 09:56,29.0,25.0,,1017.6,300.0,5.75,29.99,84.79,5.0,22.83,,,M,,,GNR,1071361,2024-01-28 10:00:00+00:00,1770.0,3.12,, +250833,2024-01-28 11:00:00+00:00,0.0,2024-01-28 10:56,28.0,25.0,,1017.6,,3.45,29.99,88.33,3.0,24.12,,,M,,,GNR,1071365,2024-01-28 11:00:00+00:00,1770.0,3.12,, +250834,2024-01-28 12:00:00+00:00,0.0,2024-01-28 11:56,28.0,25.0,,1017.8,300.0,4.6,30.0,88.33,4.0,22.75,,,M,,,GNR,1071369,2024-01-28 12:00:00+00:00,1770.0,3.12,, +250835,2024-01-28 13:00:00+00:00,0.0,2024-01-28 12:56,29.0,25.0,,1017.0,0.0,0.0,29.98,84.79,0.0,29.0,,,M,,,GNR,1071373,2024-01-28 13:00:00+00:00,1770.0,3.12,, +250836,2024-01-28 14:00:00+00:00,0.0,2024-01-28 13:56,29.0,25.0,,1017.1,0.0,0.0,29.98,84.79,0.0,29.0,,,M,,,GNR,1071377,2024-01-28 14:00:00+00:00,1750.0,3.11,, +250837,2024-01-28 15:00:00+00:00,0.0,2024-01-28 14:56,30.0,25.0,,1016.4,300.0,4.6,29.96,81.4,4.0,25.08,,,M,,,GNR,1071381,2024-01-28 15:00:00+00:00,1770.0,3.12,, +250838,2024-01-28 16:00:00+00:00,0.0,2024-01-28 15:56,30.0,25.0,,1015.7,0.0,0.0,29.94,81.4,0.0,30.0,,,M,,,GNR,1071385,2024-01-28 16:00:00+00:00,1770.0,3.12,, +250839,2024-01-28 17:00:00+00:00,0.0,2024-01-28 16:56,30.0,25.0,,1014.9,320.0,4.6,29.91,81.4,4.0,25.08,,,M,,,GNR,1071389,2024-01-28 17:00:00+00:00,1750.0,3.11,, +250840,2024-01-28 18:00:00+00:00,0.0,2024-01-28 17:56,30.0,25.0,,1014.0,320.0,4.6,29.89,81.4,4.0,25.08,,,M,,,GNR,1071393,2024-01-28 18:00:00+00:00,1750.0,3.11,, +250841,2024-01-28 19:00:00+00:00,0.0,2024-01-28 18:56,29.0,25.0,,1012.9,320.0,4.6,29.85,84.79,4.0,23.92,,,M,,,GNR,1071397,2024-01-28 19:00:00+00:00,1750.0,3.11,, +250842,2024-01-28 20:00:00+00:00,0.0,2024-01-28 19:56,29.0,24.0,,1012.5,340.0,3.45,29.84,81.32,3.0,25.26,,,M,,,GNR,1071401,2024-01-28 20:00:00+00:00,1750.0,3.11,, +250843,2024-01-28 21:00:00+00:00,0.0,2024-01-28 20:56,29.0,25.0,,1012.1,0.0,0.0,29.83,84.79,0.0,29.0,,,M,,,GNR,1071405,2024-01-28 21:00:00+00:00,1750.0,3.11,, +250844,2024-01-28 22:00:00+00:00,0.0,2024-01-28 21:56,29.0,25.0,,1011.7,0.0,0.0,29.82,84.79,0.0,29.0,,,M,,,GNR,1071409,2024-01-28 22:00:00+00:00,5300.0,4.95,, +250845,2024-01-28 23:00:00+00:00,0.0,2024-01-28 22:56,28.0,25.0,,1011.6,350.0,3.45,29.81,88.33,3.0,24.12,,,M,,,GNR,1071413,2024-01-28 23:00:00+00:00,8780.0,6.37,, +250846,2024-01-29 00:00:00+00:00,0.0,2024-01-28 23:56,28.0,25.0,,1011.2,20.0,5.75,29.8,88.33,5.0,21.64,,,M,,,GNR,1071417,2024-01-29 00:00:00+00:00,8810.0,6.38,, +250847,2024-01-29 01:00:00+00:00,0.0,2024-01-29 00:56,28.0,25.0,,1010.9,30.0,3.45,29.8,88.33,3.0,24.12,,,M,,,GNR,1071421,2024-01-29 01:00:00+00:00,8830.0,6.39,, +250848,2024-01-29 02:00:00+00:00,0.0,2024-01-29 01:56,28.0,25.0,,1009.8,10.0,3.45,29.76,88.33,3.0,24.12,,,M,,,GNR,1071425,2024-01-29 02:00:00+00:00,8860.0,6.4,, +250849,2024-01-29 03:00:00+00:00,0.0,2024-01-29 02:56,28.0,24.0,,1009.0,10.0,4.6,29.74,84.72,4.0,22.75,,,M,,,GNR,1071429,2024-01-29 03:00:00+00:00,8830.0,6.39,, +250850,2024-01-29 04:00:00+00:00,0.0,2024-01-29 03:56,27.0,24.0,,1009.0,350.0,9.2,29.74,88.28,8.0,17.95,,,M,,,GNR,1071433,2024-01-29 04:00:00+00:00,8860.0,6.4,, +250851,2024-01-29 05:00:00+00:00,0.0,2024-01-29 04:56,26.0,24.0,,1008.4,360.0,8.05,29.72,92.01,7.0,17.47,,,M,,,GNR,1071437,2024-01-29 05:00:00+00:00,4170.0,4.43,, +250852,2024-01-29 06:00:00+00:00,0.0,2024-01-29 05:56,26.0,24.0,,1008.4,10.0,9.2,29.72,92.01,8.0,16.72,,,M,,,GNR,1071441,2024-01-29 06:00:00+00:00,1990.0,3.27,, +250853,2024-01-29 07:00:00+00:00,0.0,2024-01-29 06:56,26.0,23.0,,1007.2,10.0,8.05,29.69,88.23,7.0,17.47,,,M,,,GNR,1071445,2024-01-29 07:00:00+00:00,1800.0,3.14,, +250854,2024-01-29 08:00:00+00:00,0.0,2024-01-29 07:56,26.0,23.0,,1006.4,350.0,5.75,29.66,88.23,5.0,19.27,,,M,,,GNR,1071449,2024-01-29 08:00:00+00:00,1780.0,3.13,, +250855,2024-01-29 09:00:00+00:00,0.0,2024-01-29 08:56,26.0,23.0,,1006.1,10.0,16.1,29.65,88.23,14.0,13.43,,28.0,M,28.0,,GNR,1071453,2024-01-29 09:00:00+00:00,1780.0,3.13,, +250856,2024-01-29 10:00:00+00:00,0.0,2024-01-29 09:56,26.0,22.0,,1006.4,360.0,12.65,29.66,84.59,11.0,14.88,,19.0,M,,,GNR,1071457,2024-01-29 10:00:00+00:00,1770.0,3.12,, +250857,2024-01-29 11:00:00+00:00,0.0,2024-01-29 10:56,26.0,21.0,,1007.1,350.0,12.65,29.68,81.09,11.0,14.88,,,M,,,GNR,1071461,2024-01-29 11:00:00+00:00,1770.0,3.12,, +250858,2024-01-29 12:00:00+00:00,0.0,2024-01-29 11:56,26.0,21.0,,1007.9,360.0,10.35,29.7,81.09,9.0,16.05,,17.0,M,,,GNR,1071465,2024-01-29 12:00:00+00:00,1770.0,3.12,, +250859,2024-01-29 13:00:00+00:00,0.0,2024-01-29 12:56,26.0,21.0,,1008.4,360.0,11.5,29.72,81.09,10.0,15.44,,19.0,M,,,GNR,1071469,2024-01-29 13:00:00+00:00,1770.0,3.12,, +250860,2024-01-29 14:00:00+00:00,0.0,2024-01-29 13:56,26.0,22.0,,1008.7,360.0,12.65,29.73,84.59,11.0,14.88,,20.0,M,,,GNR,1071473,2024-01-29 14:00:00+00:00,5880.0,5.2,, +250861,2024-01-29 15:00:00+00:00,0.0,2024-01-29 14:56,26.0,22.0,,1009.3,360.0,11.5,29.74,84.59,10.0,15.44,,19.0,M,,,GNR,1071477,2024-01-29 15:00:00+00:00,8680.0,6.33,, +250862,2024-01-29 16:00:00+00:00,0.0,2024-01-29 15:56,27.0,22.0,,1009.6,10.0,10.35,29.75,81.17,9.0,17.3,,19.0,M,,,GNR,1071481,2024-01-29 16:00:00+00:00,4210.0,4.45,, +250863,2024-01-29 17:00:00+00:00,0.0,2024-01-29 16:56,27.0,21.0,,1010.0,10.0,12.65,29.77,77.8,11.0,16.15,,,M,,,GNR,1071485,2024-01-29 17:00:00+00:00,1990.0,3.27,, +250864,2024-01-29 18:00:00+00:00,0.0,2024-01-29 17:56,27.0,21.0,,1010.4,10.0,13.8,29.78,77.8,12.0,15.64,,,M,,,GNR,1071489,2024-01-29 18:00:00+00:00,1780.0,3.13,, +250865,2024-01-29 19:00:00+00:00,0.0,2024-01-29 18:56,27.0,20.0,,1011.3,360.0,14.95,29.8,74.57,13.0,15.16,,24.0,M,,,GNR,1071493,2024-01-29 19:00:00+00:00,1770.0,3.12,, +250866,2024-01-29 20:00:00+00:00,0.0,2024-01-29 19:56,26.0,20.0,,1012.2,20.0,12.65,29.83,77.71,11.0,14.88,,21.0,M,,,GNR,1071497,2024-01-29 20:00:00+00:00,1770.0,3.12,, +250867,2024-01-29 21:00:00+00:00,0.0,2024-01-29 20:56,26.0,19.0,,1013.2,10.0,13.8,29.86,74.46,12.0,14.37,,20.0,M,,,GNR,1071501,2024-01-29 21:00:00+00:00,1770.0,3.12,, +250868,2024-01-29 22:00:00+00:00,0.0,2024-01-29 21:56,25.0,18.0,,1014.4,360.0,11.5,29.89,74.36,10.0,14.19,,,M,,,GNR,1071505,2024-01-29 22:00:00+00:00,1750.0,3.11,, +250869,2024-01-29 23:00:00+00:00,0.0,2024-01-29 22:56,23.0,19.0,,1015.5,350.0,12.65,29.92,84.39,11.0,11.09,,,M,,,GNR,1071509,2024-01-29 23:00:00+00:00,6220.0,5.34,, +250870,2024-01-30 00:00:00+00:00,0.0,2024-01-29 23:56,22.0,17.0,,1016.8,360.0,13.8,29.96,80.77,12.0,9.27,,18.0,M,,,GNR,1071513,2024-01-30 00:00:00+00:00,8700.0,6.34,, +250871,2024-01-30 01:00:00+00:00,0.0,2024-01-30 00:56,21.0,16.0,,1017.6,350.0,10.35,29.98,80.69,9.0,9.84,,,M,,,GNR,1071517,2024-01-30 01:00:00+00:00,8700.0,6.34,, +250872,2024-01-30 02:00:00+00:00,0.0,2024-01-30 01:56,19.0,14.0,,1018.3,350.0,11.5,30.0,80.52,10.0,6.67,,,M,,,GNR,1071521,2024-01-30 02:00:00+00:00,8750.0,6.36,, +250873,2024-01-30 03:00:00+00:00,0.0,2024-01-30 02:56,17.0,12.0,,1019.0,360.0,8.05,30.02,80.36,7.0,6.5,,,M,,,GNR,1071525,2024-01-30 03:00:00+00:00,8810.0,6.38,, +250874,2024-01-30 04:00:00+00:00,0.0,2024-01-30 03:56,15.0,10.0,,1019.7,360.0,10.35,30.04,80.19,9.0,2.38,,,M,,,GNR,1071529,2024-01-30 04:00:00+00:00,8810.0,6.38,, +250875,2024-01-30 05:00:00+00:00,0.0,2024-01-30 04:56,14.0,9.0,,1020.4,350.0,5.75,30.06,80.1,5.0,5.02,,,M,,,GNR,1071533,2024-01-30 05:00:00+00:00,4400.0,4.54,, +250876,2024-01-30 06:00:00+00:00,0.0,2024-01-30 05:56,13.0,7.0,,1021.0,10.0,6.9,30.08,76.48,6.0,2.65,,,M,,,GNR,1071537,2024-01-30 06:00:00+00:00,2030.0,3.29,, +250877,2024-01-30 07:00:00+00:00,0.0,2024-01-30 06:56,12.0,7.0,,1021.7,10.0,5.75,30.09,79.93,5.0,2.64,,,M,,,GNR,1071541,2024-01-30 07:00:00+00:00,1780.0,3.13,, +250878,2024-01-30 08:00:00+00:00,0.0,2024-01-30 07:56,10.0,6.0,,1022.1,340.0,5.75,30.1,83.49,5.0,0.27,,,M,,,GNR,1071545,2024-01-30 08:00:00+00:00,1770.0,3.12,, +250879,2024-01-30 09:00:00+00:00,0.0,2024-01-30 08:56,7.0,4.0,,1022.9,310.0,5.75,30.12,87.2,5.0,-3.29,,,M,,,GNR,1071549,2024-01-30 09:00:00+00:00,1770.0,3.12,, +250880,2024-01-30 10:00:00+00:00,0.0,2024-01-30 09:56,3.0,0.0,,1023.5,320.0,9.2,30.13,86.96,8.0,-11.61,,,M,,,GNR,1071553,2024-01-30 10:00:00+00:00,1770.0,3.12,, +250881,2024-01-30 11:00:00+00:00,0.0,2024-01-30 10:56,1.0,-3.0,,1024.1,310.0,6.9,30.15,82.81,6.0,-11.81,,,M,,,GNR,1071557,2024-01-30 11:00:00+00:00,1770.0,3.12,, +250882,2024-01-30 12:00:00+00:00,0.0,2024-01-30 11:56,-1.0,-4.0,,1024.8,320.0,4.6,30.17,86.72,4.0,-11.12,,,M,,,GNR,1071561,2024-01-30 12:00:00+00:00,3810.0,4.26,, +250883,2024-01-30 13:00:00+00:00,0.0,2024-01-30 12:56,0.0,-5.0,,1025.6,340.0,4.6,30.19,78.86,4.0,-9.95,,,M,,,GNR,1071565,2024-01-30 13:00:00+00:00,8830.0,6.39,, +250884,2024-01-30 14:00:00+00:00,0.0,2024-01-30 13:56,5.0,1.0,,1025.8,0.0,0.0,30.2,83.12,0.0,5.0,,,M,,,GNR,1071569,2024-01-30 14:00:00+00:00,4040.0,4.37,, +250885,2024-01-30 15:00:00+00:00,0.0,2024-01-30 14:56,5.0,2.0,,1026.4,0.0,0.0,30.21,87.08,0.0,5.0,,,M,,,GNR,1071573,2024-01-30 15:00:00+00:00,1960.0,3.25,, +250886,2024-01-30 16:00:00+00:00,0.0,2024-01-30 15:56,9.0,4.0,,1026.1,0.0,0.0,30.21,79.67,0.0,9.0,,,M,,,GNR,1071577,2024-01-30 16:00:00+00:00,1770.0,3.12,, +250887,2024-01-30 17:00:00+00:00,0.0,2024-01-30 16:56,13.0,3.0,,1025.5,0.0,0.0,30.19,63.68,0.0,13.0,,,M,,,GNR,1071581,2024-01-30 17:00:00+00:00,1770.0,3.12,, +250888,2024-01-30 18:00:00+00:00,0.0,2024-01-30 17:56,15.0,4.0,,1024.9,20.0,3.45,30.17,61.09,3.0,9.25,,,M,,,GNR,1071585,2024-01-30 18:00:00+00:00,1770.0,3.12,, +250889,2024-01-30 19:00:00+00:00,0.0,2024-01-30 18:56,18.0,4.0,,1024.0,0.0,0.0,30.15,53.64,0.0,18.0,,,M,,,GNR,1071589,2024-01-30 19:00:00+00:00,1770.0,3.12,, +250890,2024-01-30 20:00:00+00:00,0.0,2024-01-30 19:56,18.0,3.0,,1024.1,0.0,0.0,30.15,51.23,0.0,18.0,,,M,,,GNR,1071593,2024-01-30 20:00:00+00:00,1750.0,3.11,, +250891,2024-01-30 21:00:00+00:00,0.0,2024-01-30 20:56,17.0,3.0,,1023.9,,3.45,30.14,53.48,3.0,11.54,,,M,,,GNR,1071597,2024-01-30 21:00:00+00:00,1750.0,3.11,, +250892,2024-01-30 22:00:00+00:00,0.0,2024-01-30 21:56,12.0,2.0,,1024.0,0.0,0.0,30.14,63.54,0.0,12.0,,,M,,,GNR,1071601,2024-01-30 22:00:00+00:00,1750.0,3.11,, +250893,2024-01-30 23:00:00+00:00,0.0,2024-01-30 22:56,9.0,-1.0,,1024.1,130.0,4.6,30.13,63.12,4.0,0.56,,,M,,,GNR,1071605,2024-01-30 23:00:00+00:00,1750.0,3.11,, +250894,2024-01-31 00:00:00+00:00,0.0,2024-01-30 23:56,8.0,0.0,,1024.1,0.0,0.0,30.13,69.21,0.0,8.0,,,M,,,GNR,1071609,2024-01-31 00:00:00+00:00,5930.0,5.22,, +250895,2024-01-31 01:00:00+00:00,0.0,2024-01-31 00:56,8.0,-2.0,,1024.0,140.0,3.45,30.13,62.98,3.0,1.25,,,M,,,GNR,1071613,2024-01-31 01:00:00+00:00,8780.0,6.37,, +250896,2024-01-31 02:00:00+00:00,0.0,2024-01-31 01:56,9.0,-3.0,,1023.6,140.0,4.6,30.12,57.41,4.0,0.56,,,M,,,GNR,1071617,2024-01-31 02:00:00+00:00,8780.0,6.37,, +250897,2024-01-31 03:00:00+00:00,0.0,2024-01-31 02:56,8.0,-4.0,,1023.0,120.0,6.9,30.1,57.26,6.0,-3.37,,,M,,,GNR,1071621,2024-01-31 03:00:00+00:00,4380.0,4.53,, +250898,2024-01-31 04:00:00+00:00,0.0,2024-01-31 03:56,8.0,-3.0,,1022.6,150.0,4.6,30.1,60.06,4.0,-0.61,,,M,,,GNR,1071625,2024-01-31 04:00:00+00:00,2030.0,3.29,, +250899,2024-01-31 05:00:00+00:00,0.0,2024-01-31 04:56,6.0,-3.0,,1022.6,170.0,3.45,30.1,65.76,3.0,-1.03,,,M,,,GNR,1071629,2024-01-31 05:00:00+00:00,1770.0,3.12,, +250900,2024-01-31 06:00:00+00:00,0.0,2024-01-31 05:56,6.0,-4.0,,1022.0,130.0,3.45,30.08,62.69,3.0,-1.03,,,M,,,GNR,1071633,2024-01-31 06:00:00+00:00,1770.0,3.12,, +250901,2024-01-31 07:00:00+00:00,0.0,2024-01-31 06:56,5.0,-5.0,,1021.7,0.0,0.0,30.08,62.55,0.0,5.0,,,M,,,GNR,1071637,2024-01-31 07:00:00+00:00,1770.0,3.12,, +250902,2024-01-31 08:00:00+00:00,0.0,2024-01-31 07:56,8.0,-3.0,,1021.1,0.0,0.0,30.06,60.06,0.0,8.0,,,M,,,GNR,1071641,2024-01-31 08:00:00+00:00,1780.0,3.13,, +250903,2024-01-31 09:00:00+00:00,0.0,2024-01-31 08:56,4.0,-4.0,,1020.3,0.0,0.0,30.03,68.7,0.0,4.0,,,M,,,GNR,1071645,2024-01-31 09:00:00+00:00,1800.0,3.14,, +250904,2024-01-31 10:00:00+00:00,0.0,2024-01-31 09:56,5.0,-3.0,,1019.7,0.0,0.0,30.01,68.83,0.0,5.0,,,M,,,GNR,1071649,2024-01-31 10:00:00+00:00,1810.0,3.15,, +250905,2024-01-31 11:00:00+00:00,0.0,2024-01-31 10:56,11.0,1.0,,1019.2,0.0,0.0,30.0,63.4,0.0,11.0,,,M,,,GNR,1071653,2024-01-31 11:00:00+00:00,1830.0,3.16,, +250906,2024-01-31 12:00:00+00:00,0.0,2024-01-31 11:56,12.0,1.0,,1019.4,0.0,0.0,30.0,60.65,0.0,12.0,,,M,,,GNR,1071657,2024-01-31 12:00:00+00:00,1830.0,3.16,, +250907,2024-01-31 13:00:00+00:00,0.0,2024-01-31 12:56,13.0,3.0,,1019.2,0.0,0.0,30.0,63.68,0.0,13.0,,,M,,,GNR,1071661,2024-01-31 13:00:00+00:00,1860.0,3.18,, +250908,2024-01-31 14:00:00+00:00,0.0,2024-01-31 13:56,16.0,6.0,,1018.6,0.0,0.0,29.99,64.09,0.0,16.0,,,M,,,GNR,1071665,2024-01-31 14:00:00+00:00,1870.0,3.19,, +250909,2024-01-31 15:00:00+00:00,0.0,2024-01-31 14:56,17.0,9.0,,1018.3,0.0,0.0,29.98,70.3,0.0,17.0,,,M,,,GNR,1071669,2024-01-31 15:00:00+00:00,1890.0,3.2,, +250910,2024-01-31 16:00:00+00:00,0.0,2024-01-31 15:56,20.0,14.0,,1017.5,0.0,0.0,29.96,77.16,0.0,20.0,,,M,,,GNR,1071673,2024-01-31 16:00:00+00:00,1900.0,3.21,, +250911,2024-01-31 17:00:00+00:00,0.0,2024-01-31 16:56,23.0,16.0,,1016.7,250.0,3.45,29.94,74.15,3.0,18.4,,,M,,,GNR,1071677,2024-01-31 17:00:00+00:00,1920.0,3.22,, +250912,2024-01-31 18:00:00+00:00,0.0,2024-01-31 17:56,25.0,17.0,,1016.0,0.0,0.0,29.92,71.22,0.0,25.0,,,M,,,GNR,1071681,2024-01-31 18:00:00+00:00,1900.0,3.21,, +250913,2024-01-31 19:00:00+00:00,0.0,2024-01-31 18:56,26.0,19.0,,1015.4,,3.45,29.9,74.46,3.0,21.83,,,M,,,GNR,1071685,2024-01-31 19:00:00+00:00,1830.0,3.16,, +250914,2024-01-31 20:00:00+00:00,0.0,2024-01-31 19:56,26.0,20.0,,1015.3,0.0,0.0,29.9,77.71,0.0,26.0,,,M,,,GNR,1071689,2024-01-31 20:00:00+00:00,1770.0,3.12,, +250915,2024-01-31 21:00:00+00:00,0.0,2024-01-31 20:56,27.0,20.0,,1015.1,,3.45,29.89,74.57,3.0,22.97,,,M,,,GNR,1071693,2024-01-31 21:00:00+00:00,1750.0,3.11,, +250916,2024-01-31 22:00:00+00:00,0.0,2024-01-31 21:56,26.0,20.0,,1014.8,200.0,3.45,29.88,77.71,3.0,21.83,,,M,,,GNR,1071697,2024-01-31 22:00:00+00:00,1750.0,3.11,, +250917,2024-01-31 23:00:00+00:00,0.0,2024-01-31 22:56,23.0,17.0,,1015.3,0.0,0.0,29.9,77.44,0.0,23.0,,,M,,,GNR,1071701,2024-01-31 23:00:00+00:00,5720.0,5.13,, +250918,2024-02-01 00:00:00+00:00,0.0,2024-01-31 23:56,23.0,17.0,,1015.2,0.0,0.0,29.9,77.44,0.0,23.0,,,M,,,GNR,1071705,2024-02-01 00:00:00+00:00,8680.0,6.33,, +250919,2024-02-01 01:00:00+00:00,0.0,2024-02-01 00:56,23.0,17.0,,1015.0,0.0,0.0,29.89,77.44,0.0,23.0,,,M,,,GNR,1071709,2024-02-01 01:00:00+00:00,8750.0,6.36,, +250920,2024-02-01 02:00:00+00:00,0.0,2024-02-01 01:56,23.0,17.0,,1014.6,0.0,0.0,29.89,77.44,0.0,23.0,,,M,,,GNR,1071713,2024-02-01 02:00:00+00:00,8750.0,6.36,, +250921,2024-02-01 03:00:00+00:00,0.0,2024-02-01 02:56,23.0,17.0,,1014.2,0.0,0.0,29.88,77.44,0.0,23.0,,,M,,,GNR,1071717,2024-02-01 03:00:00+00:00,8780.0,6.37,, +250922,2024-02-01 04:00:00+00:00,0.0,2024-02-01 03:56,23.0,18.0,,1013.9,0.0,0.0,29.87,80.85,0.0,23.0,,,M,,,GNR,1071721,2024-02-01 04:00:00+00:00,4080.0,4.39,, +250923,2024-02-01 05:00:00+00:00,0.0,2024-02-01 04:56,24.0,19.0,,1013.5,0.0,0.0,29.86,80.93,0.0,24.0,,,M,,,GNR,1071725,2024-02-01 05:00:00+00:00,1960.0,3.25,, +250924,2024-02-01 06:00:00+00:00,0.0,2024-02-01 05:56,24.0,19.0,,1012.9,0.0,0.0,29.85,80.93,0.0,24.0,,,M,,,GNR,1071729,2024-02-01 06:00:00+00:00,1770.0,3.12,, +250925,2024-02-01 07:00:00+00:00,0.0,2024-02-01 06:56,25.0,20.0,,1013.3,0.0,0.0,29.86,81.01,0.0,25.0,,,M,,,GNR,1071733,2024-02-01 07:00:00+00:00,1770.0,3.12,, +250926,2024-02-01 08:00:00+00:00,0.0,2024-02-01 07:56,25.0,21.0,,1013.1,0.0,0.0,29.85,84.53,0.0,25.0,,,M,,,GNR,1071737,2024-02-01 08:00:00+00:00,1750.0,3.11,, +250927,2024-02-01 09:00:00+00:00,0.0,2024-02-01 08:56,25.0,21.0,,1013.2,0.0,0.0,29.86,84.53,0.0,25.0,,,M,,,GNR,1071741,2024-02-01 09:00:00+00:00,1750.0,3.11,, +250928,2024-02-01 10:00:00+00:00,0.0,2024-02-01 09:56,26.0,21.0,,1012.9,0.0,0.0,29.85,81.09,0.0,26.0,,,M,,,GNR,1071745,2024-02-01 10:00:00+00:00,1750.0,3.11,, +250929,2024-02-01 11:00:00+00:00,0.0,2024-02-01 10:56,26.0,22.0,,1013.1,0.0,0.0,29.85,84.59,0.0,26.0,,,M,,,GNR,1071749,2024-02-01 11:00:00+00:00,1740.0,3.1,, +250930,2024-02-01 12:00:00+00:00,0.0,2024-02-01 11:56,25.0,21.0,,1013.4,130.0,5.75,29.86,84.53,5.0,18.08,,,M,,,GNR,1071753,2024-02-01 12:00:00+00:00,1740.0,3.1,, +250931,2024-02-01 13:00:00+00:00,0.0,2024-02-01 12:56,25.0,22.0,,1013.5,110.0,5.75,29.86,88.18,5.0,18.08,,,M,,,GNR,1071757,2024-02-01 13:00:00+00:00,1740.0,3.1,, +250932,2024-02-01 14:00:00+00:00,0.0,2024-02-01 13:56,25.0,21.0,,1013.5,130.0,6.9,29.86,84.53,6.0,17.1,,,M,,,GNR,1071761,2024-02-01 14:00:00+00:00,1740.0,3.1,, +250933,2024-02-01 15:00:00+00:00,0.0,2024-02-01 14:56,25.0,22.0,,1013.8,140.0,5.75,29.87,88.18,5.0,18.08,,,M,,,GNR,1071765,2024-02-01 15:00:00+00:00,1740.0,3.1,, +250934,2024-02-01 16:00:00+00:00,0.0,2024-02-01 15:56,27.0,23.0,,1012.8,150.0,8.05,29.84,84.66,7.0,18.68,,,M,,,GNR,1071769,2024-02-01 16:00:00+00:00,1740.0,3.1,, +250935,2024-02-01 17:00:00+00:00,0.0,2024-02-01 16:56,27.0,23.0,,1012.3,140.0,4.6,29.83,84.66,4.0,21.58,,,M,,,GNR,1071773,2024-02-01 17:00:00+00:00,1740.0,3.1,, +250936,2024-02-01 18:00:00+00:00,0.0,2024-02-01 17:56,28.0,24.0,,1011.6,130.0,8.05,29.81,84.72,7.0,19.9,,,M,,,GNR,1071777,2024-02-01 18:00:00+00:00,1740.0,3.1,, +250937,2024-02-01 19:00:00+00:00,0.0,2024-02-01 18:56,28.0,24.0,,1011.4,130.0,8.05,29.81,84.72,7.0,19.9,,,M,,,GNR,1071781,2024-02-01 19:00:00+00:00,1740.0,3.1,, +250938,2024-02-01 20:00:00+00:00,0.0,2024-02-01 19:56,28.0,25.0,,1010.9,150.0,8.05,29.79,88.33,7.0,19.9,,,M,,,GNR,1071785,2024-02-01 20:00:00+00:00,1740.0,3.1,, +250939,2024-02-01 21:00:00+00:00,0.51,2024-02-01 20:56,28.0,27.0,,1010.6,150.0,6.9,29.78,95.97,6.0,20.71,,,M,,,GNR,1071789,2024-02-01 21:00:00+00:00,1740.0,3.1,, +250940,2024-02-01 22:00:00+00:00,0.25,2024-02-01 21:56,28.0,27.0,,1010.2,140.0,4.6,29.77,95.97,4.0,22.75,,,M,,,GNR,1071793,2024-02-01 22:00:00+00:00,1740.0,3.1,, +250941,2024-02-01 23:00:00+00:00,0.51,2024-02-01 22:56,28.0,27.0,,1010.1,150.0,4.6,29.77,95.97,4.0,22.75,,,M,,,GNR,1071797,2024-02-01 23:00:00+00:00,5950.0,5.23,, +250942,2024-02-02 00:00:00+00:00,0.51,2024-02-01 23:56,28.0,27.0,,1010.3,140.0,4.6,29.77,95.97,4.0,22.75,,,M,,,GNR,1071801,2024-02-02 00:00:00+00:00,8680.0,6.33,, +250943,2024-02-02 01:00:00+00:00,0.51,2024-02-02 00:56,28.0,27.0,,1010.4,140.0,5.75,29.78,95.97,5.0,21.64,,,M,,,GNR,1071805,2024-02-02 01:00:00+00:00,8750.0,6.36,, +250944,2024-02-02 02:00:00+00:00,0.0,2024-02-02 01:56,28.0,27.0,,1010.5,140.0,5.75,29.78,95.97,5.0,21.64,,,M,,,GNR,1071809,2024-02-02 02:00:00+00:00,8810.0,6.38,, +250945,2024-02-02 03:00:00+00:00,0.0,2024-02-02 02:56,28.0,27.0,,1010.2,130.0,4.6,29.77,95.97,4.0,22.75,,,M,,,GNR,1071813,2024-02-02 03:00:00+00:00,4420.0,4.55,, +250946,2024-02-02 04:00:00+00:00,0.0,2024-02-02 03:56,28.0,27.0,,1010.0,130.0,4.6,29.77,95.97,4.0,22.75,,,M,,,GNR,1071817,2024-02-02 04:00:00+00:00,2010.0,3.28,, +250947,2024-02-02 05:00:00+00:00,0.0,2024-02-02 04:56,28.0,27.0,,1009.7,130.0,4.6,29.76,95.97,4.0,22.75,,,M,,,GNR,1071821,2024-02-02 05:00:00+00:00,1770.0,3.12,, +250948,2024-02-02 06:00:00+00:00,0.25,2024-02-02 05:56,28.0,27.0,,1009.6,130.0,3.45,29.76,95.97,3.0,24.12,,,M,,,GNR,1071825,2024-02-02 06:00:00+00:00,1750.0,3.11,, +250949,2024-02-02 07:00:00+00:00,0.0,2024-02-02 06:56,28.0,27.0,,1009.8,0.0,0.0,29.76,95.97,0.0,28.0,,,M,,,GNR,1071829,2024-02-02 07:00:00+00:00,1750.0,3.11,, +250950,2024-02-02 08:00:00+00:00,0.0,2024-02-02 07:56,26.0,25.0,,1009.4,0.0,0.0,29.75,95.93,0.0,26.0,,,M,,,GNR,1071833,2024-02-02 08:00:00+00:00,1740.0,3.1,, +250951,2024-02-02 09:00:00+00:00,0.0,2024-02-02 08:56,27.0,25.0,,1009.6,320.0,3.45,29.76,92.05,3.0,22.97,,,M,,,GNR,1071837,2024-02-02 09:00:00+00:00,1740.0,3.1,, +250952,2024-02-02 10:00:00+00:00,0.0,2024-02-02 09:56,27.0,25.0,,1009.8,0.0,0.0,29.76,92.05,0.0,27.0,,,M,,,GNR,1071841,2024-02-02 10:00:00+00:00,1740.0,3.1,, +250953,2024-02-02 11:00:00+00:00,0.0,2024-02-02 10:56,28.0,26.0,,1010.3,0.0,0.0,29.78,92.08,0.0,28.0,,,M,,,GNR,1071845,2024-02-02 11:00:00+00:00,1740.0,3.1,, +250954,2024-02-02 12:00:00+00:00,0.0,2024-02-02 11:56,27.0,25.0,,1010.9,320.0,3.45,29.79,92.05,3.0,22.97,,,M,,,GNR,1071849,2024-02-02 12:00:00+00:00,1740.0,3.1,, +250955,2024-02-02 13:00:00+00:00,0.0,2024-02-02 12:56,28.0,26.0,,1011.5,330.0,4.6,29.81,92.08,4.0,22.75,,,M,,,GNR,1071853,2024-02-02 13:00:00+00:00,1740.0,3.1,, +250956,2024-02-02 14:00:00+00:00,0.0,2024-02-02 13:56,28.0,26.0,,1011.8,340.0,3.45,29.82,92.08,3.0,24.12,,,M,,,GNR,1071857,2024-02-02 14:00:00+00:00,1740.0,3.1,, +250957,2024-02-02 15:00:00+00:00,0.0,2024-02-02 14:56,29.0,27.0,,1011.9,330.0,9.2,29.83,92.12,8.0,20.42,,,M,,,GNR,1071861,2024-02-02 15:00:00+00:00,1740.0,3.1,, +250958,2024-02-02 16:00:00+00:00,0.0,2024-02-02 15:56,28.0,26.0,,1012.5,340.0,8.05,29.84,92.08,7.0,19.9,,16.0,M,,,GNR,1071865,2024-02-02 16:00:00+00:00,1740.0,3.1,, +250959,2024-02-02 17:00:00+00:00,0.0,2024-02-02 16:56,27.0,25.0,,1012.6,350.0,11.5,29.84,92.05,10.0,16.7,,16.0,M,,,GNR,1071869,2024-02-02 17:00:00+00:00,1740.0,3.1,, +250960,2024-02-02 18:00:00+00:00,0.0,2024-02-02 17:56,27.0,24.0,,1012.5,330.0,12.65,29.84,88.28,11.0,16.15,,18.0,M,,,GNR,1071873,2024-02-02 18:00:00+00:00,1720.0,3.09,, +250961,2024-02-02 19:00:00+00:00,0.0,2024-02-02 18:56,26.0,23.0,,1013.0,340.0,13.8,29.85,88.23,12.0,14.37,,18.0,M,,,GNR,1071877,2024-02-02 19:00:00+00:00,1720.0,3.09,, +250962,2024-02-02 20:00:00+00:00,0.0,2024-02-02 19:56,25.0,22.0,,1013.5,340.0,10.35,29.87,88.18,9.0,14.81,,17.0,M,,,GNR,1071881,2024-02-02 20:00:00+00:00,1720.0,3.09,, +250963,2024-02-02 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13:56,15.0,10.0,,1018.4,340.0,10.35,29.99,80.19,9.0,2.38,,18.0,M,,,GNR,1071953,2024-02-03 14:00:00+00:00,1720.0,3.09,, +250981,2024-02-03 15:00:00+00:00,0.0,2024-02-03 14:56,17.0,10.0,,1018.1,360.0,5.75,29.99,73.52,5.0,8.58,,,M,,,GNR,1071957,2024-02-03 15:00:00+00:00,1720.0,3.09,, +250982,2024-02-03 16:00:00+00:00,0.0,2024-02-03 15:56,19.0,9.0,,1017.8,,5.75,29.98,64.5,5.0,10.96,,15.0,M,,,GNR,1071961,2024-02-03 16:00:00+00:00,1720.0,3.09,, +250983,2024-02-03 17:00:00+00:00,0.0,2024-02-03 16:56,20.0,7.0,,1017.4,350.0,13.8,29.97,56.47,12.0,6.73,,19.0,M,,,GNR,1071965,2024-02-03 17:00:00+00:00,1720.0,3.09,, +250984,2024-02-03 18:00:00+00:00,0.0,2024-02-03 17:56,22.0,7.0,,1016.6,350.0,13.8,29.95,51.88,12.0,9.27,,22.0,M,,,GNR,1071969,2024-02-03 18:00:00+00:00,1720.0,3.09,, +250985,2024-02-03 19:00:00+00:00,0.0,2024-02-03 18:56,23.0,8.0,,1016.0,350.0,14.95,29.93,52.04,13.0,10.04,,21.0,M,,,GNR,1071973,2024-02-03 19:00:00+00:00,1720.0,3.09,, +250986,2024-02-03 20:00:00+00:00,0.0,2024-02-03 19:56,23.0,8.0,,1015.9,350.0,14.95,29.93,52.04,13.0,10.04,,22.0,M,,,GNR,1071977,2024-02-03 20:00:00+00:00,1720.0,3.09,, +250987,2024-02-03 21:00:00+00:00,0.0,2024-02-03 20:56,22.0,8.0,,1015.7,340.0,12.65,29.92,54.28,11.0,9.83,,23.0,M,,,GNR,1071981,2024-02-03 21:00:00+00:00,1720.0,3.09,, +250988,2024-02-03 22:00:00+00:00,0.0,2024-02-03 21:56,20.0,9.0,,1015.9,350.0,9.2,29.92,61.8,8.0,9.33,,,M,,,GNR,1071985,2024-02-03 22:00:00+00:00,1720.0,3.09,, +250989,2024-02-03 23:00:00+00:00,0.0,2024-02-03 22:56,20.0,10.0,,1016.0,340.0,17.25,29.92,64.64,15.0,5.22,,26.0,M,26.0,,GNR,1071989,2024-02-03 23:00:00+00:00,1720.0,3.09,, +250990,2024-02-04 00:00:00+00:00,0.0,2024-02-03 23:56,18.0,10.0,,1016.6,340.0,11.5,29.94,70.41,10.0,5.41,,19.0,M,28.0,,GNR,1071993,2024-02-04 00:00:00+00:00,4360.0,4.52,, +250991,2024-02-04 01:00:00+00:00,0.0,2024-02-04 00:56,17.0,8.0,,1016.7,350.0,6.9,29.94,67.2,6.0,7.46,,18.0,M,,,GNR,1071997,2024-02-04 01:00:00+00:00,8650.0,6.32,, +250992,2024-02-04 02:00:00+00:00,0.0,2024-02-04 01:56,15.0,4.0,,1016.8,350.0,9.2,29.94,61.09,8.0,3.17,,17.0,M,,,GNR,1072001,2024-02-04 02:00:00+00:00,4850.0,4.75,, +250993,2024-02-04 03:00:00+00:00,0.0,2024-02-04 02:56,14.0,2.0,,1016.7,340.0,9.2,29.94,58.18,8.0,1.94,,18.0,M,,,GNR,1072005,2024-02-04 03:00:00+00:00,2060.0,3.31,, +250994,2024-02-04 04:00:00+00:00,0.0,2024-02-04 03:56,12.0,3.0,,1016.5,340.0,8.05,29.94,66.56,7.0,0.4,,16.0,M,,,GNR,1072009,2024-02-04 04:00:00+00:00,1750.0,3.11,, +250995,2024-02-04 05:00:00+00:00,0.0,2024-02-04 04:56,12.0,2.0,,1016.2,330.0,10.35,29.93,63.54,9.0,-1.35,,,M,,,GNR,1072013,2024-02-04 05:00:00+00:00,1750.0,3.11,, +250996,2024-02-04 06:00:00+00:00,0.0,2024-02-04 05:56,11.0,3.0,,1015.5,330.0,8.05,29.9,69.58,7.0,-0.82,,,M,,,GNR,1072017,2024-02-04 06:00:00+00:00,1750.0,3.11,, +250997,2024-02-04 07:00:00+00:00,0.0,2024-02-04 06:56,10.0,4.0,,1015.4,330.0,8.05,29.9,76.18,7.0,-2.04,,,M,,,GNR,1072021,2024-02-04 07:00:00+00:00,1770.0,3.12,, +250998,2024-02-04 08:00:00+00:00,0.0,2024-02-04 07:56,9.0,4.0,,1015.2,,5.75,29.9,79.67,5.0,-0.92,,,M,,,GNR,1072025,2024-02-04 08:00:00+00:00,1780.0,3.13,, +250999,2024-02-04 09:00:00+00:00,0.0,2024-02-04 08:56,8.0,4.0,,1015.7,,,29.91,83.34,,,,,M,,,GNR,1072029,2024-02-04 09:00:00+00:00,1810.0,3.15,, +251000,2024-02-04 10:00:00+00:00,0.0,2024-02-04 09:56,7.0,4.0,,1015.9,,6.9,29.91,87.2,6.0,-4.58,,,M,,,GNR,1072033,2024-02-04 10:00:00+00:00,1840.0,3.17,, +251001,2024-02-04 11:00:00+00:00,0.0,2024-02-04 10:56,7.0,4.0,,1015.7,0.0,0.0,29.91,87.2,0.0,7.0,,,M,,,GNR,1072037,2024-02-04 11:00:00+00:00,1870.0,3.19,, +251002,2024-02-04 12:00:00+00:00,0.0,2024-02-04 11:56,7.0,4.0,,1015.1,330.0,9.2,29.89,87.2,8.0,-6.68,,18.0,M,,,GNR,1072041,2024-02-04 12:00:00+00:00,1890.0,3.2,, +251003,2024-02-04 13:00:00+00:00,0.0,2024-02-04 12:56,9.0,5.0,,1015.0,330.0,12.65,29.89,83.41,11.0,-6.6,,22.0,M,,,GNR,1072045,2024-02-04 13:00:00+00:00,1900.0,3.21,, +251004,2024-02-04 14:00:00+00:00,0.0,2024-02-04 13:56,12.0,6.0,,1014.6,340.0,13.8,29.87,76.38,12.0,-3.45,,23.0,M,27.0,,GNR,1072049,2024-02-04 14:00:00+00:00,1920.0,3.22,, +251005,2024-02-04 15:00:00+00:00,0.0,2024-02-04 14:56,16.0,5.0,,1014.4,330.0,13.8,29.87,61.23,12.0,1.64,,22.0,M,28.0,,GNR,1072053,2024-02-04 15:00:00+00:00,1950.0,3.24,, +251006,2024-02-04 16:00:00+00:00,0.0,2024-02-04 15:56,19.0,6.0,,1014.2,330.0,14.95,29.87,56.32,13.0,4.91,,23.0,M,,,GNR,1072057,2024-02-04 16:00:00+00:00,1930.0,3.23,, +251007,2024-02-04 17:00:00+00:00,0.0,2024-02-04 16:56,21.0,6.0,,1013.6,320.0,10.35,29.85,51.72,9.0,9.84,,22.0,M,26.0,,GNR,1072061,2024-02-04 17:00:00+00:00,1890.0,3.2,, +251008,2024-02-04 18:00:00+00:00,0.0,2024-02-04 17:56,22.0,7.0,,1013.0,320.0,21.85,29.83,51.88,19.0,6.21,,26.0,M,26.0,,GNR,1072065,2024-02-04 18:00:00+00:00,1830.0,3.16,, +251009,2024-02-04 19:00:00+00:00,0.0,2024-02-04 18:56,23.0,8.0,,1012.4,330.0,13.8,29.82,52.04,12.0,10.55,,26.0,M,27.0,,GNR,1072069,2024-02-04 19:00:00+00:00,1740.0,3.1,, +251010,2024-02-04 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23:56,26.0,18.0,,1024.1,350.0,8.05,30.17,71.33,7.0,17.47,,,M,,,GNR,1072281,2024-02-07 00:00:00+00:00,3870.0,4.29,, +251063,2024-02-07 01:00:00+00:00,0.0,2024-02-07 00:56,26.0,18.0,,1024.6,20.0,6.9,30.18,71.33,6.0,18.3,,,M,,,GNR,1072285,2024-02-07 01:00:00+00:00,8290.0,6.18,, +251064,2024-02-07 02:00:00+00:00,0.0,2024-02-07 01:56,22.0,17.0,,1024.9,310.0,5.75,30.19,80.77,5.0,14.52,,,M,,,GNR,1072289,2024-02-07 02:00:00+00:00,8370.0,6.21,, +251065,2024-02-07 03:00:00+00:00,0.0,2024-02-07 02:56,23.0,17.0,,1025.1,330.0,6.9,30.19,77.44,6.0,14.69,,,M,,,GNR,1072293,2024-02-07 03:00:00+00:00,8340.0,6.2,, +251066,2024-02-07 04:00:00+00:00,0.0,2024-02-07 03:56,21.0,16.0,,1025.1,0.0,0.0,30.2,80.69,0.0,21.0,,,M,,,GNR,1072297,2024-02-07 04:00:00+00:00,4420.0,4.55,, +251067,2024-02-07 05:00:00+00:00,0.0,2024-02-07 04:56,20.0,17.0,,1025.2,340.0,5.75,30.2,87.92,5.0,12.14,,,M,,,GNR,1072301,2024-02-07 05:00:00+00:00,1860.0,3.18,, +251068,2024-02-07 06:00:00+00:00,0.0,2024-02-07 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11:56,14.0,12.0,,1026.2,30.0,5.75,30.23,91.57,5.0,5.02,,,M,,,GNR,1072329,2024-02-07 12:00:00+00:00,1780.0,3.13,, +251075,2024-02-07 13:00:00+00:00,0.0,2024-02-07 12:56,18.0,15.0,,1026.6,320.0,3.45,30.24,87.81,3.0,12.68,,,M,,,GNR,1072333,2024-02-07 13:00:00+00:00,1800.0,3.14,, +251076,2024-02-07 14:00:00+00:00,0.0,2024-02-07 13:56,21.0,16.0,,1026.9,40.0,3.45,30.25,80.69,3.0,16.11,,,M,,,GNR,1072337,2024-02-07 14:00:00+00:00,1810.0,3.15,, +251077,2024-02-07 15:00:00+00:00,0.0,2024-02-07 14:56,27.0,20.0,,1026.6,320.0,6.9,30.25,74.57,6.0,19.51,,,M,,,GNR,1072341,2024-02-07 15:00:00+00:00,1830.0,3.16,, +251078,2024-02-07 16:00:00+00:00,0.0,2024-02-07 15:56,27.0,19.0,,1026.2,70.0,4.6,30.23,71.45,4.0,21.58,,,M,,,GNR,1072345,2024-02-07 16:00:00+00:00,1840.0,3.17,, +251079,2024-02-07 17:00:00+00:00,0.0,2024-02-07 16:56,31.0,21.0,,1025.3,0.0,0.0,30.21,66.07,0.0,31.0,,,M,,,GNR,1072349,2024-02-07 17:00:00+00:00,1800.0,3.14,, +251080,2024-02-07 18:00:00+00:00,0.0,2024-02-07 17:56,34.0,20.0,,1024.4,,4.6,30.19,56.12,4.0,29.76,,,M,,,GNR,1072353,2024-02-07 18:00:00+00:00,1740.0,3.1,, +251081,2024-02-07 19:00:00+00:00,0.0,2024-02-07 18:56,34.0,20.0,,1024.0,330.0,8.05,30.17,56.12,7.0,27.22,,,M,,,GNR,1072357,2024-02-07 19:00:00+00:00,1710.0,3.08,, +251082,2024-02-07 20:00:00+00:00,0.0,2024-02-07 19:56,35.0,20.0,,1024.3,310.0,5.75,30.18,53.93,5.0,29.96,,,M,,,GNR,1072361,2024-02-07 20:00:00+00:00,1710.0,3.08,, +251083,2024-02-07 21:00:00+00:00,0.0,2024-02-07 20:56,34.0,19.0,,1024.5,320.0,5.75,30.19,53.77,5.0,28.77,,,M,,,GNR,1072365,2024-02-07 21:00:00+00:00,1710.0,3.08,, +251084,2024-02-07 22:00:00+00:00,0.0,2024-02-07 21:56,31.0,19.0,,1024.8,0.0,0.0,30.19,60.67,0.0,31.0,,,M,,,GNR,1072369,2024-02-07 22:00:00+00:00,1710.0,3.08,, +251085,2024-02-07 23:00:00+00:00,0.0,2024-02-07 22:56,28.0,18.0,,1024.8,0.0,0.0,30.19,65.69,0.0,28.0,,,M,,,GNR,1072373,2024-02-07 23:00:00+00:00,1710.0,3.08,, +251086,2024-02-08 00:00:00+00:00,0.0,2024-02-07 23:56,26.0,18.0,,1025.5,0.0,0.0,30.21,71.33,0.0,26.0,,,M,,,GNR,1072377,2024-02-08 00:00:00+00:00,6270.0,5.36,, +251087,2024-02-08 01:00:00+00:00,0.0,2024-02-08 00:56,29.0,18.0,,1025.5,350.0,4.6,30.21,63.05,4.0,23.92,,,M,,,GNR,1072381,2024-02-08 01:00:00+00:00,8830.0,6.39,, +251088,2024-02-08 02:00:00+00:00,0.0,2024-02-08 01:56,29.0,19.0,,1025.4,360.0,5.75,30.21,65.81,5.0,22.83,,,M,,,GNR,1072385,2024-02-08 02:00:00+00:00,4360.0,4.52,, +251089,2024-02-08 03:00:00+00:00,0.0,2024-02-08 02:56,27.0,19.0,,1025.1,0.0,0.0,30.21,71.45,0.0,27.0,,,M,,,GNR,1072389,2024-02-08 03:00:00+00:00,1980.0,3.26,, +251090,2024-02-08 04:00:00+00:00,0.0,2024-02-08 03:56,27.0,19.0,,1025.1,310.0,4.6,30.21,71.45,4.0,21.58,,,M,,,GNR,1072393,2024-02-08 04:00:00+00:00,1720.0,3.09,, +251091,2024-02-08 05:00:00+00:00,0.0,2024-02-08 04:56,25.0,18.0,,1025.2,40.0,5.75,30.21,74.36,5.0,18.08,,,M,,,GNR,1072397,2024-02-08 05:00:00+00:00,1720.0,3.09,, +251092,2024-02-08 06:00:00+00:00,0.0,2024-02-08 05:56,26.0,19.0,,1024.9,320.0,5.75,30.21,74.46,5.0,19.27,,,M,,,GNR,1072401,2024-02-08 06:00:00+00:00,1710.0,3.08,, +251093,2024-02-08 07:00:00+00:00,0.0,2024-02-08 06:56,27.0,19.0,,1025.2,350.0,5.75,30.22,71.45,5.0,20.46,,,M,,,GNR,1072405,2024-02-08 07:00:00+00:00,1710.0,3.08,, +251094,2024-02-08 08:00:00+00:00,0.0,2024-02-08 07:56,28.0,20.0,,1025.0,360.0,4.6,30.21,71.56,4.0,22.75,,,M,,,GNR,1072409,2024-02-08 08:00:00+00:00,1710.0,3.08,, +251095,2024-02-08 09:00:00+00:00,0.0,2024-02-08 08:56,25.0,19.0,,1025.4,30.0,4.6,30.22,77.62,4.0,19.25,,,M,,,GNR,1072413,2024-02-08 09:00:00+00:00,1710.0,3.08,, +251096,2024-02-08 10:00:00+00:00,0.0,2024-02-08 09:56,26.0,19.0,,1025.7,310.0,3.45,30.23,74.46,3.0,21.83,,,M,,,GNR,1072417,2024-02-08 10:00:00+00:00,1710.0,3.08,, +251097,2024-02-08 11:00:00+00:00,0.0,2024-02-08 10:56,26.0,19.0,,1025.9,330.0,3.45,30.23,74.46,3.0,21.83,,,M,,,GNR,1072421,2024-02-08 11:00:00+00:00,1710.0,3.08,, +251098,2024-02-08 12:00:00+00:00,0.0,2024-02-08 11:56,24.0,17.0,,1026.3,350.0,4.6,30.24,74.26,4.0,18.08,,,M,,,GNR,1072425,2024-02-08 12:00:00+00:00,1710.0,3.08,, +251099,2024-02-08 13:00:00+00:00,0.0,2024-02-08 12:56,25.0,18.0,,1026.6,40.0,4.6,30.25,74.36,4.0,19.25,,,M,,,GNR,1072429,2024-02-08 13:00:00+00:00,1710.0,3.08,, +251100,2024-02-08 14:00:00+00:00,0.0,2024-02-08 13:56,29.0,19.0,,1026.3,40.0,4.6,30.25,65.81,4.0,23.92,,,M,,,GNR,1072433,2024-02-08 14:00:00+00:00,1690.0,3.07,, +251101,2024-02-08 15:00:00+00:00,0.0,2024-02-08 14:56,32.0,20.0,,1026.2,0.0,0.0,30.24,60.81,0.0,32.0,,,M,,,GNR,1072437,2024-02-08 15:00:00+00:00,1690.0,3.07,, +251102,2024-02-08 16:00:00+00:00,0.0,2024-02-08 15:56,34.0,19.0,,1026.4,340.0,5.75,30.25,53.77,5.0,28.77,,,M,,,GNR,1072441,2024-02-08 16:00:00+00:00,1690.0,3.07,, +251103,2024-02-08 17:00:00+00:00,0.0,2024-02-08 16:56,37.0,19.0,,1025.4,0.0,0.0,30.22,47.74,0.0,37.0,,,M,,,GNR,1072445,2024-02-08 17:00:00+00:00,1690.0,3.07,, +251104,2024-02-08 18:00:00+00:00,0.0,2024-02-08 17:56,37.0,18.0,,1024.6,,3.45,30.2,45.73,3.0,34.4,,,M,,,GNR,1072449,2024-02-08 18:00:00+00:00,1690.0,3.07,, +251105,2024-02-08 19:00:00+00:00,0.0,2024-02-08 18:56,38.0,18.0,,1023.9,,3.45,30.18,43.97,3.0,35.55,,,M,,,GNR,1072453,2024-02-08 19:00:00+00:00,1690.0,3.07,, +251106,2024-02-08 20:00:00+00:00,0.0,2024-02-08 19:56,39.0,17.0,,1023.7,290.0,4.6,30.18,40.5,4.0,35.59,,,M,,,GNR,1072457,2024-02-08 20:00:00+00:00,1690.0,3.07,, +251107,2024-02-08 21:00:00+00:00,0.0,2024-02-08 20:56,38.0,18.0,,1023.8,320.0,3.45,30.18,43.97,3.0,35.55,,,M,,,GNR,1072461,2024-02-08 21:00:00+00:00,1690.0,3.07,, +251108,2024-02-08 22:00:00+00:00,0.0,2024-02-08 21:56,35.0,19.0,,1024.3,0.0,0.0,30.19,51.67,0.0,35.0,,,M,,,GNR,1072465,2024-02-08 22:00:00+00:00,1690.0,3.07,, +251109,2024-02-08 23:00:00+00:00,0.0,2024-02-08 22:56,30.0,19.0,,1024.5,0.0,0.0,30.19,63.18,0.0,30.0,,,M,,,GNR,1072469,2024-02-08 23:00:00+00:00,1690.0,3.07,, +251110,2024-02-09 00:00:00+00:00,0.0,2024-02-08 23:56,27.0,18.0,,1024.7,80.0,3.45,30.19,68.45,3.0,22.97,,,M,,,GNR,1072473,2024-02-09 00:00:00+00:00,6590.0,5.49,, +251111,2024-02-09 01:00:00+00:00,0.0,2024-02-09 00:56,28.0,18.0,,1024.7,130.0,4.6,30.19,65.69,4.0,22.75,,,M,,,GNR,1072477,2024-02-09 01:00:00+00:00,8810.0,6.38,, +251112,2024-02-09 02:00:00+00:00,0.0,2024-02-09 01:56,29.0,19.0,,1023.8,120.0,6.9,30.17,65.81,6.0,21.92,,,M,,,GNR,1072481,2024-02-09 02:00:00+00:00,4400.0,4.54,, +251113,2024-02-09 03:00:00+00:00,0.0,2024-02-09 02:56,30.0,20.0,,1023.4,120.0,6.9,30.17,65.94,6.0,23.12,,,M,,,GNR,1072485,2024-02-09 03:00:00+00:00,1960.0,3.25,, +251114,2024-02-09 04:00:00+00:00,0.0,2024-02-09 03:56,29.0,19.0,,1022.5,120.0,8.05,30.14,65.81,7.0,21.12,,,M,,,GNR,1072489,2024-02-09 04:00:00+00:00,1720.0,3.09,, +251115,2024-02-09 05:00:00+00:00,0.0,2024-02-09 04:56,29.0,19.0,,1022.4,130.0,6.9,30.14,65.81,6.0,21.92,,,M,,,GNR,1072493,2024-02-09 05:00:00+00:00,1710.0,3.08,, +251116,2024-02-09 06:00:00+00:00,0.0,2024-02-09 05:56,27.0,19.0,,1022.5,130.0,5.75,30.14,71.45,5.0,20.46,,,M,,,GNR,1072497,2024-02-09 06:00:00+00:00,1710.0,3.08,, +251117,2024-02-09 07:00:00+00:00,0.0,2024-02-09 06:56,26.0,18.0,,1022.6,130.0,4.6,30.14,71.33,4.0,20.41,,,M,,,GNR,1072501,2024-02-09 07:00:00+00:00,1710.0,3.08,, +251118,2024-02-09 08:00:00+00:00,0.0,2024-02-09 07:56,26.0,18.0,,1021.6,130.0,8.05,30.12,71.33,7.0,17.47,,,M,,,GNR,1072505,2024-02-09 08:00:00+00:00,1710.0,3.08,, +251119,2024-02-09 09:00:00+00:00,0.0,2024-02-09 08:56,27.0,19.0,,1020.9,130.0,5.75,30.09,71.45,5.0,20.46,,,M,,,GNR,1072509,2024-02-09 09:00:00+00:00,1710.0,3.08,, +251120,2024-02-09 10:00:00+00:00,0.0,2024-02-09 09:56,26.0,19.0,,1020.8,140.0,6.9,30.09,74.46,6.0,18.3,,,M,,,GNR,1072513,2024-02-09 10:00:00+00:00,1740.0,3.1,, +251121,2024-02-09 11:00:00+00:00,0.0,2024-02-09 10:56,28.0,20.0,,1020.8,150.0,8.05,30.09,71.56,7.0,19.9,,,M,,,GNR,1072517,2024-02-09 11:00:00+00:00,1750.0,3.11,, +251122,2024-02-09 12:00:00+00:00,0.0,2024-02-09 11:56,27.0,20.0,,1020.5,130.0,8.05,30.07,74.57,7.0,18.68,,,M,,,GNR,1072521,2024-02-09 12:00:00+00:00,1770.0,3.12,, +251123,2024-02-09 13:00:00+00:00,0.0,2024-02-09 12:56,28.0,20.0,,1020.1,140.0,9.2,30.06,71.56,8.0,19.19,,,M,,,GNR,1072525,2024-02-09 13:00:00+00:00,1780.0,3.13,, +251124,2024-02-09 14:00:00+00:00,0.0,2024-02-09 13:56,29.0,21.0,,1019.4,140.0,10.35,30.04,71.67,9.0,19.78,,17.0,M,,,GNR,1072529,2024-02-09 14:00:00+00:00,1800.0,3.14,, +251125,2024-02-09 15:00:00+00:00,0.0,2024-02-09 14:56,29.0,22.0,,1018.9,140.0,9.2,30.03,74.77,8.0,20.42,,,M,,,GNR,1072533,2024-02-09 15:00:00+00:00,1800.0,3.14,, +251126,2024-02-09 16:00:00+00:00,0.0,2024-02-09 15:56,29.0,22.0,,1018.1,150.0,8.05,30.01,74.77,7.0,21.12,,16.0,M,,,GNR,1072537,2024-02-09 16:00:00+00:00,1710.0,3.08,, +251127,2024-02-09 17:00:00+00:00,0.0,2024-02-09 16:56,30.0,23.0,,1017.0,150.0,8.05,29.98,74.87,7.0,22.34,,,M,,,GNR,1072541,2024-02-09 17:00:00+00:00,1690.0,3.07,, +251128,2024-02-09 18:00:00+00:00,0.0,2024-02-09 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23:56,34.0,30.0,,1014.5,170.0,4.6,29.91,85.11,4.0,29.76,,,M,,,GNR,1072569,2024-02-10 00:00:00+00:00,1890.0,3.2,, +251135,2024-02-10 01:00:00+00:00,0.0,2024-02-10 00:56,33.0,29.0,,1013.8,140.0,6.9,29.88,85.04,6.0,26.73,,,M,,,GNR,1072573,2024-02-10 01:00:00+00:00,8730.0,6.35,, +251136,2024-02-10 02:00:00+00:00,0.0,2024-02-10 01:56,32.0,29.0,,1013.3,140.0,8.05,29.87,88.53,7.0,24.78,,,M,,,GNR,1072577,2024-02-10 02:00:00+00:00,5050.0,4.84,, +251137,2024-02-10 03:00:00+00:00,0.0,2024-02-10 02:56,32.0,28.0,,1013.0,140.0,6.9,29.86,84.98,6.0,25.53,,,M,,,GNR,1072581,2024-02-10 03:00:00+00:00,2200.0,3.4,, +251138,2024-02-10 04:00:00+00:00,0.0,2024-02-10 03:56,31.0,28.0,,1012.3,140.0,6.9,29.84,88.48,6.0,24.33,,,M,,,GNR,1072585,2024-02-10 04:00:00+00:00,1720.0,3.09,, +251139,2024-02-10 05:00:00+00:00,0.0,2024-02-10 04:56,31.0,29.0,,1011.1,130.0,8.05,29.8,92.19,7.0,23.56,,,M,,,GNR,1072589,2024-02-10 05:00:00+00:00,1710.0,3.08,, +251140,2024-02-10 06:00:00+00:00,0.0,2024-02-10 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00:00:00+00:00,0.0,2024-02-11 23:56,33.0,27.0,,1007.8,300.0,12.65,29.72,78.34,11.0,23.73,,21.0,M,27.0,,GNR,1072761,2024-02-12 00:00:00+00:00,5650.0,5.1,, +251183,2024-02-12 01:00:00+00:00,0.0,2024-02-12 00:56,33.0,27.0,,1007.7,300.0,10.35,29.71,78.34,9.0,24.76,,18.0,M,27.0,,GNR,1072765,2024-02-12 01:00:00+00:00,8780.0,6.37,, +251184,2024-02-12 02:00:00+00:00,0.0,2024-02-12 01:56,33.0,27.0,,1008.0,300.0,10.35,29.72,78.34,9.0,24.76,,19.0,M,,,GNR,1072769,2024-02-12 02:00:00+00:00,4230.0,4.46,, +251185,2024-02-12 03:00:00+00:00,0.0,2024-02-12 02:56,32.0,27.0,,1007.9,310.0,10.35,29.72,81.55,9.0,23.51,,17.0,M,,,GNR,1072773,2024-02-12 03:00:00+00:00,1980.0,3.26,, +251186,2024-02-12 04:00:00+00:00,0.0,2024-02-12 03:56,32.0,27.0,,1007.7,310.0,13.8,29.71,81.55,12.0,22.0,,21.0,M,,,GNR,1072777,2024-02-12 04:00:00+00:00,1770.0,3.12,, +251187,2024-02-12 05:00:00+00:00,0.0,2024-02-12 04:56,32.0,26.0,,1008.1,310.0,11.5,29.73,78.25,10.0,22.97,,20.0,M,,,GNR,1072781,2024-02-12 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19:56,11.0,-2.0,,1014.1,290.0,9.2,29.87,55.06,8.0,-1.76,,21.0,M,30.0,,GNR,1074473,2024-02-29 20:00:00+00:00,1280.0,2.76,, +251610,2024-02-29 21:00:00+00:00,0.0,2024-02-29 20:56,10.0,-5.0,,1015.1,270.0,11.5,29.89,49.89,10.0,-4.62,,24.0,M,31.0,,GNR,1074477,2024-02-29 21:00:00+00:00,1280.0,2.76,, +251611,2024-02-29 22:00:00+00:00,0.0,2024-02-29 21:56,9.0,-5.0,,1016.4,280.0,11.5,29.92,52.17,10.0,-5.87,,30.0,M,30.0,,GNR,1074481,2024-02-29 22:00:00+00:00,1280.0,2.76,, +251612,2024-02-29 23:00:00+00:00,0.0,2024-02-29 22:56,8.0,-2.0,,1018.0,290.0,12.65,29.96,62.98,11.0,-7.86,,25.0,M,,,GNR,1074485,2024-02-29 23:00:00+00:00,1280.0,2.76,, +251613,2024-03-01 00:00:00+00:00,0.0,2024-02-29 23:56,6.0,-4.0,,1019.4,290.0,12.65,30.0,62.69,11.0,-10.39,,31.0,M,38.0,,GNR,1074489,2024-03-01 00:00:00+00:00,4100.0,4.4,, +251614,2024-03-01 01:00:00+00:00,0.0,2024-03-01 00:56,5.0,-10.0,,1020.7,290.0,12.65,30.03,49.03,11.0,-11.65,,25.0,M,35.0,,GNR,1074493,2024-03-01 01:00:00+00:00,8880.0,6.41,, +251615,2024-03-01 02:00:00+00:00,0.0,2024-03-01 01:56,4.0,-10.0,,1021.7,310.0,12.65,30.07,51.33,11.0,-12.92,,30.0,M,30.0,,GNR,1074497,2024-03-01 02:00:00+00:00,4260.0,4.47,, +251616,2024-03-01 03:00:00+00:00,0.0,2024-03-01 02:56,3.0,-10.0,,1022.4,300.0,13.8,30.08,53.76,12.0,-14.91,,26.0,M,30.0,,GNR,1074501,2024-03-01 03:00:00+00:00,1830.0,3.16,, +251617,2024-03-01 04:00:00+00:00,0.0,2024-03-01 03:56,2.0,-10.0,,1022.9,300.0,11.5,30.1,56.31,10.0,-14.65,,25.0,M,29.0,,GNR,1074505,2024-03-01 04:00:00+00:00,1380.0,2.84,, +251618,2024-03-01 05:00:00+00:00,0.0,2024-03-01 04:56,2.0,-11.0,,1023.4,300.0,10.35,30.12,53.59,9.0,-13.79,,22.0,M,,,GNR,1074509,2024-03-01 05:00:00+00:00,1370.0,2.83,, +251619,2024-03-01 06:00:00+00:00,0.0,2024-03-01 05:56,1.0,-11.0,,1024.1,300.0,12.65,30.14,56.15,11.0,-16.71,,23.0,M,27.0,,GNR,1074513,2024-03-01 06:00:00+00:00,1370.0,2.83,, +251620,2024-03-01 07:00:00+00:00,0.0,2024-03-01 06:56,1.0,-12.0,,1024.9,300.0,12.65,30.16,53.42,11.0,-16.71,,24.0,M,29.0,,GNR,1074517,2024-03-01 07:00:00+00:00,1380.0,2.84,, +251621,2024-03-01 08:00:00+00:00,0.0,2024-03-01 07:56,0.0,-12.0,,1025.6,290.0,11.5,30.18,55.98,10.0,-17.16,,24.0,M,27.0,,GNR,1074521,2024-03-01 08:00:00+00:00,1430.0,2.88,, +251622,2024-03-01 09:00:00+00:00,0.0,2024-03-01 08:56,0.0,-12.0,,1026.6,300.0,10.35,30.21,55.98,9.0,-16.28,,23.0,M,27.0,,GNR,1074525,2024-03-01 09:00:00+00:00,1220.0,2.71,, +251623,2024-03-01 10:00:00+00:00,0.0,2024-03-01 09:56,0.0,-12.0,,1027.4,310.0,12.65,30.23,55.98,11.0,-17.97,,24.0,M,,,GNR,1074529,2024-03-01 10:00:00+00:00,1080.0,2.59,, +251624,2024-03-01 11:00:00+00:00,0.0,2024-03-01 10:56,0.0,-10.0,,1028.4,300.0,8.05,30.25,61.82,7.0,-14.23,,16.0,M,,,GNR,1074533,2024-03-01 11:00:00+00:00,1060.0,2.58,, +251625,2024-03-01 12:00:00+00:00,0.0,2024-03-01 11:56,1.0,-10.0,,1029.0,320.0,11.5,30.27,58.99,10.0,-15.91,,20.0,M,,,GNR,1074537,2024-03-01 12:00:00+00:00,1060.0,2.58,, +251626,2024-03-01 13:00:00+00:00,0.0,2024-03-01 12:56,4.0,-8.0,,1029.4,320.0,11.5,30.29,56.63,10.0,-12.14,,19.0,M,,,GNR,1074541,2024-03-01 13:00:00+00:00,1080.0,2.59,, +251627,2024-03-01 14:00:00+00:00,0.0,2024-03-01 13:56,7.0,-6.0,,1029.8,310.0,9.2,30.3,54.41,8.0,-6.68,,20.0,M,,,GNR,1074545,2024-03-01 14:00:00+00:00,1090.0,2.6,, +251628,2024-03-01 15:00:00+00:00,0.0,2024-03-01 14:56,11.0,-6.0,,1029.4,310.0,13.8,30.29,45.47,12.0,-4.73,,28.0,M,29.0,,GNR,1074549,2024-03-01 15:00:00+00:00,1090.0,2.6,, +251629,2024-03-01 16:00:00+00:00,0.0,2024-03-01 15:56,15.0,-5.0,,1029.3,290.0,8.05,30.3,40.0,7.0,4.06,,24.0,M,29.0,,GNR,1074553,2024-03-01 16:00:00+00:00,1040.0,2.56,, +251630,2024-03-01 17:00:00+00:00,0.0,2024-03-01 16:56,18.0,-2.0,,1029.1,,6.9,30.29,40.54,6.0,8.67,,19.0,M,,,GNR,1074557,2024-03-01 17:00:00+00:00,1030.0,2.55,, +251631,2024-03-01 18:00:00+00:00,0.0,2024-03-01 17:56,20.0,-1.0,,1028.7,,5.75,30.28,39.01,5.0,12.14,,,M,,,GNR,1074561,2024-03-01 18:00:00+00:00,1030.0,2.55,, +251632,2024-03-01 19:00:00+00:00,0.0,2024-03-01 18:56,22.0,-1.0,,1028.2,,6.9,30.27,35.84,6.0,13.49,,,M,,,GNR,1074565,2024-03-01 19:00:00+00:00,1020.0,2.54,, +251633,2024-03-01 20:00:00+00:00,0.0,2024-03-01 19:56,25.0,-1.0,,1028.1,,,30.27,31.6,,,,,M,,,GNR,1074569,2024-03-01 20:00:00+00:00,999.0,2.52,, +251634,2024-03-01 21:00:00+00:00,0.0,2024-03-01 20:56,25.0,1.0,,1028.6,,3.45,30.28,34.71,3.0,20.69,,,M,,,GNR,1074573,2024-03-01 21:00:00+00:00,987.0,2.51,, +251635,2024-03-01 22:00:00+00:00,0.0,2024-03-01 21:56,24.0,5.0,,1029.1,,,30.29,43.54,,,,,M,,,GNR,1074577,2024-03-01 22:00:00+00:00,976.0,2.5,, +251636,2024-03-01 23:00:00+00:00,0.0,2024-03-01 22:56,24.0,10.0,,1029.8,,5.75,30.31,54.59,5.0,16.89,,,M,,,GNR,1074581,2024-03-01 23:00:00+00:00,964.0,2.49,, +251637,2024-03-02 00:00:00+00:00,0.0,2024-03-01 23:56,24.0,11.0,,1029.8,0.0,0.0,30.32,57.08,0.0,24.0,,,M,,,GNR,1074585,2024-03-02 00:00:00+00:00,976.0,2.5,, +251638,2024-03-02 01:00:00+00:00,0.0,2024-03-02 00:56,22.0,11.0,,1029.9,0.0,0.0,30.32,62.09,0.0,22.0,,,M,,,GNR,1074589,2024-03-02 01:00:00+00:00,9010.0,6.46,, +251639,2024-03-02 02:00:00+00:00,0.0,2024-03-02 01:56,23.0,13.0,,1030.1,0.0,0.0,30.33,65.03,0.0,23.0,,,M,,,GNR,1074593,2024-03-02 02:00:00+00:00,4060.0,4.38,, +251640,2024-03-02 03:00:00+00:00,0.0,2024-03-02 02:56,21.0,13.0,,1029.8,120.0,4.6,30.32,70.76,4.0,14.57,,,M,,,GNR,1074597,2024-03-02 03:00:00+00:00,1770.0,3.12,, +251641,2024-03-02 04:00:00+00:00,0.0,2024-03-02 03:56,24.0,13.0,,1029.5,0.0,0.0,30.32,62.36,0.0,24.0,,,M,,,GNR,1074601,2024-03-02 04:00:00+00:00,1120.0,2.63,, diff --git a/tests/test_data2/small_modal_csv.csv b/tests/test_data2/small_modal_csv.csv new file mode 100644 index 000000000..e69de29bb diff --git a/tests/test_join.py b/tests/test_join.py deleted file mode 100644 index 46be6362e..000000000 --- a/tests/test_join.py +++ /dev/null @@ -1,32 +0,0 @@ -import unittest -from flood_forecast.preprocessing.buil_dataset import combine_data -import pandas as pd -import os -import json -from datetime import datetime -import pytz - - -class JoinTest(unittest.TestCase): - def setUp(self): - self.test_data_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), "test_data") - # 1 - - def test_join_function(self): - df = pd.read_csv(os.path.join(self.test_data_path, "fake_test_small.csv"), sep="\t") - asos_df = pd.read_csv(os.path.join(self.test_data_path, "asos-12N_small.csv")) - old_timezone = pytz.timezone("America/New_York") - new_timezone = pytz.timezone("UTC") - # This assumes timezones are consistent throughout the USGS stream (this should be true for all) - df["datetime"] = df["datetime"].map(lambda x: old_timezone.localize( - datetime.strptime(x, "%Y-%m-%d %H:%M")).astimezone(new_timezone)) - with open(os.path.join(self.test_data_path, "big_black_md.json")) as a: - meta_data = json.load(a) - self.assertEqual(meta_data['gage_id'], 1010070) - result_df, nan_f, nan_p = combine_data(df, asos_df) - self.assertEqual(result_df.iloc[0]['p01m'], 0) - self.assertEqual(result_df.iloc[0]['cfs'], 2210) - self.assertEqual(result_df.iloc[0]['tmpf'], 19.94) - -if __name__ == '__main__': - unittest.main() diff --git a/tests/24_May_202202_25PM_1.json b/tests/test_json_config/24_May_202202_25PM_1.json similarity index 100% rename from tests/24_May_202202_25PM_1.json rename to tests/test_json_config/24_May_202202_25PM_1.json diff --git a/tests/auto_encoder.json b/tests/test_json_config/auto_encoder.json similarity index 100% rename from tests/auto_encoder.json rename to tests/test_json_config/auto_encoder.json diff --git a/tests/classification_test.json b/tests/test_json_config/classification_test.json similarity index 100% rename from tests/classification_test.json rename to tests/test_json_config/classification_test.json diff --git a/tests/config.json b/tests/test_json_config/config.json similarity index 100% rename from tests/config.json rename to tests/test_json_config/config.json diff --git a/tests/cross_former.json b/tests/test_json_config/cross_former.json similarity index 99% rename from tests/cross_former.json rename to tests/test_json_config/cross_former.json index aa6e8bb35..1dabf54c9 100644 --- a/tests/cross_former.json +++ b/tests/test_json_config/cross_former.json @@ -7,7 +7,6 @@ "n_time_series": 3, "forecast_length": 10, "seg_len": 4 - }, "n_targets": 4, "dataset_params": diff --git a/tests/custom_encode.json b/tests/test_json_config/custom_encode.json similarity index 100% rename from tests/custom_encode.json rename to tests/test_json_config/custom_encode.json diff --git a/tests/da_meta.json b/tests/test_json_config/da_meta.json similarity index 100% rename from tests/da_meta.json rename to tests/test_json_config/da_meta.json diff --git a/tests/da_rnn.json b/tests/test_json_config/da_rnn.json similarity index 100% rename from tests/da_rnn.json rename to tests/test_json_config/da_rnn.json diff --git a/tests/da_rnn_probabilistic.json b/tests/test_json_config/da_rnn_probabilistic.json similarity index 100% rename from tests/da_rnn_probabilistic.json rename to tests/test_json_config/da_rnn_probabilistic.json diff --git a/tests/decoder_test.json b/tests/test_json_config/decoder_test.json similarity index 100% rename from tests/decoder_test.json rename to tests/test_json_config/decoder_test.json diff --git a/tests/dlinear.json b/tests/test_json_config/dlinear.json similarity index 100% rename from tests/dlinear.json rename to tests/test_json_config/dlinear.json diff --git a/tests/dsanet.json b/tests/test_json_config/dsanet.json similarity index 100% rename from tests/dsanet.json rename to tests/test_json_config/dsanet.json diff --git a/tests/dsanet_3.json b/tests/test_json_config/dsanet_3.json similarity index 100% rename from tests/dsanet_3.json rename to tests/test_json_config/dsanet_3.json diff --git a/tests/full_transformer.json b/tests/test_json_config/full_transformer.json similarity index 100% rename from tests/full_transformer.json rename to tests/test_json_config/full_transformer.json diff --git a/tests/gru_vanilla.json b/tests/test_json_config/gru_vanilla.json similarity index 100% rename from tests/gru_vanilla.json rename to tests/test_json_config/gru_vanilla.json diff --git a/tests/lstm_probabilistic_test.json b/tests/test_json_config/lstm_probabilistic_test.json similarity index 100% rename from tests/lstm_probabilistic_test.json rename to tests/test_json_config/lstm_probabilistic_test.json diff --git a/tests/lstm_test.json b/tests/test_json_config/lstm_test.json similarity index 100% rename from tests/lstm_test.json rename to tests/test_json_config/lstm_test.json diff --git a/tests/meta_data_test.json b/tests/test_json_config/meta_data_test.json similarity index 100% rename from tests/meta_data_test.json rename to tests/test_json_config/meta_data_test.json diff --git a/tests/multi_config.json b/tests/test_json_config/multi_config.json similarity index 100% rename from tests/multi_config.json rename to tests/test_json_config/multi_config.json diff --git a/tests/multi_decoder_test.json b/tests/test_json_config/multi_decoder_test.json similarity index 100% rename from tests/multi_decoder_test.json rename to tests/test_json_config/multi_decoder_test.json diff --git a/tests/multi_test.json b/tests/test_json_config/multi_test.json similarity index 100% rename from tests/multi_test.json rename to tests/test_json_config/multi_test.json diff --git a/tests/multitask_decoder.json b/tests/test_json_config/multitask_decoder.json similarity index 100% rename from tests/multitask_decoder.json rename to tests/test_json_config/multitask_decoder.json diff --git a/tests/nlinear.json b/tests/test_json_config/nlinear.json similarity index 100% rename from tests/nlinear.json rename to tests/test_json_config/nlinear.json diff --git a/tests/probabilistic_linear_regression_test.json b/tests/test_json_config/probabilistic_linear_regression_test.json similarity index 100% rename from tests/probabilistic_linear_regression_test.json rename to tests/test_json_config/probabilistic_linear_regression_test.json diff --git a/tests/scaling_json.json b/tests/test_json_config/scaling_json.json similarity index 100% rename from tests/scaling_json.json rename to tests/test_json_config/scaling_json.json diff --git a/tests/test_dual.json b/tests/test_json_config/test_dual.json similarity index 100% rename from tests/test_dual.json rename to tests/test_json_config/test_dual.json diff --git a/tests/test_iTransformer.json b/tests/test_json_config/test_iTransformer.json similarity index 100% rename from tests/test_iTransformer.json rename to tests/test_json_config/test_iTransformer.json diff --git a/tests/transformer_b_series.json b/tests/test_json_config/transformer_b_series.json similarity index 100% rename from tests/transformer_b_series.json rename to tests/test_json_config/transformer_b_series.json diff --git a/tests/transformer_bottleneck.json b/tests/test_json_config/transformer_bottleneck.json similarity index 100% rename from tests/transformer_bottleneck.json rename to tests/test_json_config/transformer_bottleneck.json diff --git a/tests/transformer_gaussian.json b/tests/test_json_config/transformer_gaussian.json similarity index 100% rename from tests/transformer_gaussian.json rename to tests/test_json_config/transformer_gaussian.json diff --git a/tests/tsmixer_test.json b/tests/test_json_config/tsmixer_test.json similarity index 100% rename from tests/tsmixer_test.json rename to tests/test_json_config/tsmixer_test.json diff --git a/tests/variable_autoencoderl.json b/tests/test_json_config/variable_autoencoderl.json similarity index 100% rename from tests/variable_autoencoderl.json rename to tests/test_json_config/variable_autoencoderl.json diff --git a/tests/test_multi_modal_loader.py b/tests/test_multi_modal_loader.py new file mode 100644 index 000000000..e69de29bb diff --git a/tests/test_multimodal_processor.py b/tests/test_multimodal_processor.py new file mode 100644 index 000000000..513b433a4 --- /dev/null +++ b/tests/test_multimodal_processor.py @@ -0,0 +1,39 @@ +import os +import unittest + +from sklearn.preprocessing import StandardScaler + +from flood_forecast.preprocessing.multimodal_loaders import UniformMultiModalLoader + + +class TestUniformMultiModalLoader(unittest.TestCase): + def setUp(self): + core_parameters = { + "file_path": "test_data2/multimodal_data.csv", + "forecast_history": 10, + "forecast_length": 5, + "target_col": "cfs", + "relevant_cols": ["cfs", "height"], + "scaling": StandardScaler(), + "interpolate_param": False + + } + text_config = { + + } + image_config = { + + } + + self.multimodal_loader = UniformMultiModalLoader( + csv_data_loader_params=core_parameters, + image_config=image_config, + text_config=text_config + ) + + def test_output_single_row(self): + pass + + +if __name__ == '__main__': + unittest.main()