Add AutoregressionTask

docs/api/datasets.rst

@@ -211,6 +211,11 @@ ADVANCE
 
 .. autoclass:: ADVANCE
 
+Air Quality
+^^^^^^^^^^^
+
+.. autoclass:: AirQuality
+
 Benin Cashew Plantations
 ^^^^^^^^^^^^^^^^^^^^^^^^
 

docs/api/datasets/non_geo_datasets.csv

@@ -1,5 +1,6 @@
 Dataset,Task,Source,License,# Samples,# Classes,Size (px),Resolution (m),Bands
 `ADVANCE`_,C,"Google Earth, Freesound","CC-BY-4.0","5,075",13,512x512,0.5,RGB
+`Air Quality`_,"R,T","UCI Machine Learning Repository","CC-BY-4.0","9,358",,,,
 `Benin Cashew Plantations`_,S,Airbus Pléiades,"CC-BY-4.0",70,6,"1,122x1,186",10,MSI
 `BigEarthNet`_,C,Sentinel-1/2,"CDLA-Permissive-1.0","590,326",19--43,120x120,10,"SAR, MSI"
 `BioMassters`_,R,Sentinel-1/2 and Lidar,"CC-BY-4.0",,,256x256, 10, "SAR, MSI"

tests/conf/air_quality.yaml

@@ -0,0 +1,16 @@
+model:
+  class_path: AutoregressionTask
+  init_args:
+    loss: 'mse'
+    model: 'lstm_seq2seq'
+    input_size: 3
+    input_size_decoder: 1
+    target_indices: [2]
+    encoder_indices: [2, 12, 13]
+    decoder_indices: [2]
+data:
+  class_path: AirQualityDataModule
+  init_args:
+    batch_size: 2
+  dict_kwargs:
+    root: 'tests/data/air_quality'

tests/data/air_quality/data.csv

@@ -0,0 +1,51 @@
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+0.3579651339033103,0.3931528213665786,0.694308850254078,0.0888443615941219,0.5256240051990227,0.6624479206726026,0.9155075607574713,0.19755433532146505,0.9663940494204895,0.6553927210697587,0.22126275306401544,0.16903787409372562,0.3172952633902072,0.5486777306291436,0.9080486931469579

tests/data/air_quality/data.py

@@ -0,0 +1,33 @@
+#!/usr/bin/env python3
+
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
+
+import numpy as np
+import pandas as pd
+
+columns = [
+    'Date',
+    'Time',
+    'CO(GT)',
+    'PT08.S1(CO)',
+    'NMHC(GT)',
+    'C6H6(GT)',
+    'PT08.S2(NMHC)',
+    'NOx(GT)',
+    'PT08.S3(NOx)',
+    'NO2(GT)',
+    'PT08.S4(NO2)',
+    'PT08.S5(O3)',
+    'T',
+    'RH',
+    'AH',
+]
+
+nrows = 50
+data = np.random.rand(nrows, len(columns))
+
+df = pd.DataFrame(data, columns=columns)
+
+
+df.to_csv('data.csv', index=False)

tests/datasets/test_air_quality.py

@@ -0,0 +1,37 @@
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
+
+from pathlib import Path
+
+import pytest
+from _pytest.fixtures import SubRequest
+from pytest import MonkeyPatch
+from torch import Tensor
+
+from torchgeo.datasets import AirQuality, DatasetNotFoundError
+
+
+class TestAirQuality:
+    @pytest.fixture()
+    def dataset(
+        self, monkeypatch: MonkeyPatch, tmp_path: Path, request: SubRequest
+    ) -> AirQuality:
+        url = 'tests/data/air_quality/data.csv'
+        monkeypatch.setattr(AirQuality, 'url', url)
+        return AirQuality(tmp_path, download=True)
+
+    def test_getitem(self, dataset: AirQuality) -> None:
+        x, y = dataset[0]
+        assert isinstance(x, Tensor)
+        assert x.shape[1] == 15
+        assert x.shape[0] == dataset.num_past_steps
+        assert isinstance(y, Tensor)
+        assert y.shape[1] == 15
+        assert y.shape[0] == dataset.num_future_steps
+
+    def test_len(self, dataset: AirQuality) -> None:
+        assert len(dataset) == 46
+
+    def test_not_downloaded(self, tmp_path: Path) -> None:
+        with pytest.raises(DatasetNotFoundError, match='Dataset not found'):
+            AirQuality(tmp_path)