RasterDataset: remove plot method (#476)

* RasterDataset: remove plot method

* Remove RasterDataset plot tests

* Remove plotting tests for landsat/naip

tests/datasets/test_geo.py

@@ -196,12 +196,6 @@ def test_no_data(self, tmp_path: Path) -> None:
         with pytest.raises(FileNotFoundError, match="No RasterDataset data was found"):
             RasterDataset(str(tmp_path))
 
-    def test_plot_with_cmap(self, custom_dtype_ds: RasterDataset) -> None:
-        custom_dtype_ds.cmap = {i: (0, 0, 0, 255) for i in range(256)}
-        custom_dtype_ds.is_image = False
-        x = custom_dtype_ds[custom_dtype_ds.bounds]
-        custom_dtype_ds.plot(x["mask"])
-
 
 class TestVectorDataset:
     @pytest.fixture(scope="class")

tests/datasets/test_landsat.py

@@ -4,7 +4,6 @@
 import os
 from pathlib import Path
 
-import matplotlib.pyplot as plt
 import pytest
 import torch
 import torch.nn as nn
@@ -17,7 +16,6 @@
 class TestLandsat8:
     @pytest.fixture
     def dataset(self, monkeypatch: MonkeyPatch) -> Landsat8:
-        monkeypatch.setattr(plt, "show", lambda *args: None)
         root = os.path.join("tests", "data", "landsat8")
         bands = ["B1", "B2", "B3", "B4", "B5", "B6", "B7"]
         transforms = nn.Identity()  # type: ignore[no-untyped-call]
@@ -40,11 +38,6 @@ def test_or(self, dataset: Landsat8) -> None:
         ds = dataset | dataset
         assert isinstance(ds, UnionDataset)
 
-    def test_plot(self, dataset: Landsat8) -> None:
-        query = dataset.bounds
-        x = dataset[query]
-        dataset.plot(x["image"])
-
     def test_no_data(self, tmp_path: Path) -> None:
         with pytest.raises(FileNotFoundError, match="No Landsat8 data was found in "):
             Landsat8(str(tmp_path))

tests/datasets/test_naip.py

@@ -4,7 +4,6 @@
 import os
 from pathlib import Path
 
-import matplotlib.pyplot as plt
 import pytest
 import torch
 import torch.nn as nn
@@ -17,7 +16,6 @@
 class TestNAIP:
     @pytest.fixture
     def dataset(self, monkeypatch: MonkeyPatch) -> NAIP:
-        monkeypatch.setattr(plt, "show", lambda *args: None)
         root = os.path.join("tests", "data", "naip")
         transforms = nn.Identity()  # type: ignore[no-untyped-call]
         return NAIP(root, transforms=transforms)
@@ -36,11 +34,6 @@ def test_or(self, dataset: NAIP) -> None:
         ds = dataset | dataset
         assert isinstance(ds, UnionDataset)
 
-    def test_plot(self, dataset: NAIP) -> None:
-        query = dataset.bounds
-        x = dataset[query]
-        dataset.plot(x["image"])
-
     def test_no_data(self, tmp_path: Path) -> None:
         with pytest.raises(FileNotFoundError, match="No NAIP data was found in "):
             NAIP(str(tmp_path))

torchgeo/datasets/agb_live_woody_density.py

@@ -124,7 +124,7 @@ def _download(self) -> None:
                 item["properties"]["tile_id"] + ".tif",
             )
 
-    def plot(  # type: ignore[override]
+    def plot(
         self,
         sample: Dict[str, Any],
         show_titles: bool = True,

torchgeo/datasets/astergdem.py

@@ -92,7 +92,7 @@ def _verify(self) -> None:
             "have manually downloaded dataset tiles as suggested in the documentation."
         )
 
-    def plot(  # type: ignore[override]
+    def plot(
         self,
         sample: Dict[str, Any],
         show_titles: bool = True,

torchgeo/datasets/cdl.py

@@ -398,7 +398,7 @@ def _extract(self) -> None:
         for zipfile in glob.iglob(pathname):
             extract_archive(zipfile)
 
-    def plot(  # type: ignore[override]
+    def plot(
         self,
         sample: Dict[str, Any],
         show_titles: bool = True,

torchgeo/datasets/chesapeake.py

@@ -176,7 +176,7 @@ def _extract(self) -> None:
         """Extract the dataset."""
         extract_archive(os.path.join(self.root, self.zipfile))
 
-    def plot(  # type: ignore[override]
+    def plot(
         self,
         sample: Dict[str, Tensor],
         show_titles: bool = True,

torchgeo/datasets/cms_mangrove_canopy.py

@@ -251,7 +251,7 @@ def _extract(self) -> None:
         pathname = os.path.join(self.root, self.zipfile)
         extract_archive(pathname)
 
-    def plot(  # type: ignore[override]
+    def plot(
         self,
         sample: Dict[str, Any],
         show_titles: bool = True,

torchgeo/datasets/esri2020.py

@@ -137,7 +137,7 @@ def _extract(self) -> None:
         """Extract the dataset."""
         extract_archive(os.path.join(self.root, self.zipfile))
 
-    def plot(  # type: ignore[override]
+    def plot(
         self,
         sample: Dict[str, Any],
         show_titles: bool = True,

torchgeo/datasets/eudem.py

@@ -139,7 +139,7 @@ def _verify(self) -> None:
             "have manually downloaded the dataset as suggested in the documentation."
         )
 
-    def plot(  # type: ignore[override]
+    def plot(
         self,
         sample: Dict[str, Any],
         show_titles: bool = True,

torchgeo/datasets/geo.py

@@ -13,7 +13,6 @@
 
 import fiona
 import fiona.transform
-import matplotlib.pyplot as plt
 import numpy as np
 import pyproj
 import rasterio
@@ -303,10 +302,6 @@ class RasterDataset(GeoDataset):
     #: Names of RGB bands in the dataset, used for plotting
     rgb_bands: List[str] = []
 
-    #: If True, stretch the image from the 2nd percentile to the 98th percentile,
-    #: used for plotting
-    stretch = False
-
     #: Color map for the dataset, used for plotting
     cmap: Dict[int, Tuple[int, int, int, int]] = {}
 
@@ -503,53 +498,6 @@ def _load_warp_file(self, filepath: str) -> DatasetReader:
         else:
             return src
 
-    def plot(self, data: Tensor) -> None:
-        """Plot a data sample.
-
-        Args:
-            data: the data to plot
-
-        Raises:
-            AssertionError: if ``is_image`` is True and ``data`` has a different number
-                of channels than expected
-        """
-        array = data.squeeze().numpy()
-
-        if self.is_image:
-            bands = getattr(self, "bands", self.all_bands)
-            assert array.shape[0] == len(bands)
-
-            # Only plot RGB bands
-            if bands and self.rgb_bands:
-                indices: "np.typing.NDArray[np.int_]" = np.array(
-                    [bands.index(band) for band in self.rgb_bands]
-                )
-                array = array[indices]
-
-            # Convert from CxHxW to HxWxC
-            array = np.rollaxis(array, 0, 3)
-
-        if self.cmap:
-            # Convert from class labels to RGBA values
-            cmap: "np.typing.NDArray[np.int_]" = np.array(
-                [self.cmap[i] for i in range(len(self.cmap))]
-            )
-            array = cmap[array]
-
-        if self.stretch:
-            # Stretch to the range of 2nd to 98th percentile
-            per02 = np.percentile(array, 2)
-            per98 = np.percentile(array, 98)
-            array = (array - per02) / (per98 - per02)
-            array = np.clip(array, 0, 1)
-
-        # Plot the data
-        ax = plt.axes()
-        ax.imshow(array)
-        ax.axis("off")
-        plt.show()
-        plt.close()
-
 
 class VectorDataset(GeoDataset):
     """Abstract base class for :class:`GeoDataset` stored as vector files."""

torchgeo/datasets/globbiomass.py

@@ -225,7 +225,7 @@ def _verify(self) -> None:
             "have manually downloaded the dataset as suggested in the documentation."
         )
 
-    def plot(  # type: ignore[override]
+    def plot(
         self,
         sample: Dict[str, Any],
         show_titles: bool = True,

torchgeo/datasets/landsat.py

@@ -46,7 +46,6 @@ class Landsat(RasterDataset, abc.ABC):
     rgb_bands: List[str] = []
 
     separate_files = True
-    stretch = True
 
     def __init__(
         self,

torchgeo/datasets/sentinel.py

@@ -102,7 +102,7 @@ def __init__(
 
         super().__init__(root, crs, res, transforms, cache)
 
-    def plot(  # type: ignore[override]
+    def plot(
         self,
         sample: Dict[str, Tensor],
         show_titles: bool = True,