Rename old API refs in JPEG 2000 tests and notebook (#1047)

Author: brendancol

examples/user_guide/35_JPEG2000_Compression.ipynb

@@ -9,7 +9,7 @@
   {
    "cell_type": "code",
    "id": "kamu534xsm",
-   "source": "import numpy as np\nimport xarray as xr\nimport matplotlib.pyplot as plt\nimport tempfile\nimport os\n\nfrom xrspatial.geotiff import read_geotiff, write_geotiff",
+   "source": "import numpy as np\nimport xarray as xr\nimport matplotlib.pyplot as plt\nimport tempfile\nimport os\n\nfrom xrspatial.geotiff import open_geotiff, to_geotiff",
    "metadata": {},
    "execution_count": null,
    "outputs": []
@@ -31,27 +31,27 @@
   {
    "cell_type": "markdown",
    "id": "8tsuyr3jbay",
-   "source": "## Write with JPEG 2000 (lossless)\n\nPass `compression='jpeg2000'` to `write_geotiff`. The default is lossless encoding.",
+   "source": "## Write with JPEG 2000 (lossless)\n\nPass `compression='jpeg2000'` to `to_geotiff`. The default is lossless encoding.",
    "metadata": {}
   },
   {
    "cell_type": "code",
    "id": "ystjp6v30d",
-   "source": "tmpdir = tempfile.mkdtemp(prefix='j2k_demo_')\n\n# Write with JPEG 2000 compression\nj2k_path = os.path.join(tmpdir, 'elevation_j2k.tif')\nwrite_geotiff(da, j2k_path, compression='jpeg2000')\n\n# Compare file sizes with deflate\ndeflate_path = os.path.join(tmpdir, 'elevation_deflate.tif')\nwrite_geotiff(da, deflate_path, compression='deflate')\n\nnone_path = os.path.join(tmpdir, 'elevation_none.tif')\nwrite_geotiff(da, none_path, compression='none')\n\nj2k_size = os.path.getsize(j2k_path)\ndeflate_size = os.path.getsize(deflate_path)\nnone_size = os.path.getsize(none_path)\n\nprint(f\"Uncompressed:  {none_size:>8,} bytes\")\nprint(f\"Deflate:       {deflate_size:>8,} bytes  ({deflate_size/none_size:.1%} of original)\")\nprint(f\"JPEG 2000:     {j2k_size:>8,} bytes  ({j2k_size/none_size:.1%} of original)\")",
+   "source": "tmpdir = tempfile.mkdtemp(prefix='j2k_demo_')\n\n# Write with JPEG 2000 compression\nj2k_path = os.path.join(tmpdir, 'elevation_j2k.tif')\nto_geotiff(da, j2k_path, compression='jpeg2000')\n\n# Compare file sizes with deflate\ndeflate_path = os.path.join(tmpdir, 'elevation_deflate.tif')\nto_geotiff(da, deflate_path, compression='deflate')\n\nnone_path = os.path.join(tmpdir, 'elevation_none.tif')\nto_geotiff(da, none_path, compression='none')\n\nj2k_size = os.path.getsize(j2k_path)\ndeflate_size = os.path.getsize(deflate_path)\nnone_size = os.path.getsize(none_path)\n\nprint(f\"Uncompressed:  {none_size:>8,} bytes\")\nprint(f\"Deflate:       {deflate_size:>8,} bytes  ({deflate_size/none_size:.1%} of original)\")\nprint(f\"JPEG 2000:     {j2k_size:>8,} bytes  ({j2k_size/none_size:.1%} of original)\")",
    "metadata": {},
    "execution_count": null,
    "outputs": []
   },
   {
    "cell_type": "markdown",
    "id": "89y9zun97nb",
-   "source": "## Read it back and verify lossless roundtrip\n\n`read_geotiff` auto-detects the compression from the TIFF header. No special arguments needed.",
+   "source": "## Read it back and verify lossless roundtrip\n\n`open_geotiff` auto-detects the compression from the TIFF header. No special arguments needed.",
    "metadata": {}
   },
   {
    "cell_type": "code",
    "id": "8vf9ljxkx03",
-   "source": "# Read back and check lossless roundtrip\nda_read = read_geotiff(j2k_path)\n\nprint(f\"Shape: {da_read.shape}\")\nprint(f\"Dtype: {da_read.dtype}\")\nprint(f\"CRS:   {da_read.attrs.get('crs')}\")\nprint(f\"Exact match: {np.array_equal(da_read.values, terrain)}\")\n\nfig, axes = plt.subplots(1, 2, figsize=(12, 5))\nda.plot(ax=axes[0], cmap='terrain')\naxes[0].set_title('Original')\nda_read.plot(ax=axes[1], cmap='terrain')\naxes[1].set_title('After JPEG 2000 roundtrip')\nplt.tight_layout()\nplt.show()",
+   "source": "# Read back and check lossless roundtrip\nda_read = open_geotiff(j2k_path)\n\nprint(f\"Shape: {da_read.shape}\")\nprint(f\"Dtype: {da_read.dtype}\")\nprint(f\"CRS:   {da_read.attrs.get('crs')}\")\nprint(f\"Exact match: {np.array_equal(da_read.values, terrain)}\")\n\nfig, axes = plt.subplots(1, 2, figsize=(12, 5))\nda.plot(ax=axes[0], cmap='terrain')\naxes[0].set_title('Original')\nda_read.plot(ax=axes[1], cmap='terrain')\naxes[1].set_title('After JPEG 2000 roundtrip')\nplt.tight_layout()\nplt.show()",
    "metadata": {},
    "execution_count": null,
    "outputs": []
@@ -65,15 +65,15 @@
   {
    "cell_type": "code",
    "id": "mgv9xhsrcen",
-   "source": "# Create a 3-band uint8 image\nrgb = np.zeros((128, 128, 3), dtype=np.uint8)\nrgb[:, :, 0] = np.linspace(0, 255, 128).astype(np.uint8)[None, :]  # red gradient\nrgb[:, :, 1] = np.linspace(0, 255, 128).astype(np.uint8)[:, None]  # green gradient\nrgb[:, :, 2] = 128  # constant blue\n\nda_rgb = xr.DataArray(\n    rgb, dims=['y', 'x', 'band'],\n    coords={'y': np.arange(128), 'x': np.arange(128), 'band': [0, 1, 2]},\n)\n\nrgb_path = os.path.join(tmpdir, 'rgb_j2k.tif')\nwrite_geotiff(da_rgb, rgb_path, compression='jpeg2000')\n\nda_rgb_read = read_geotiff(rgb_path)\nprint(f\"RGB shape: {da_rgb_read.shape}, dtype: {da_rgb_read.dtype}\")\nprint(f\"Exact match: {np.array_equal(da_rgb_read.values, rgb)}\")\n\nfig, axes = plt.subplots(1, 2, figsize=(10, 4))\naxes[0].imshow(rgb)\naxes[0].set_title('Original RGB')\naxes[1].imshow(da_rgb_read.values)\naxes[1].set_title('After J2K roundtrip')\nplt.tight_layout()\nplt.show()",
+   "source": "# Create a 3-band uint8 image\nrgb = np.zeros((128, 128, 3), dtype=np.uint8)\nrgb[:, :, 0] = np.linspace(0, 255, 128).astype(np.uint8)[None, :]  # red gradient\nrgb[:, :, 1] = np.linspace(0, 255, 128).astype(np.uint8)[:, None]  # green gradient\nrgb[:, :, 2] = 128  # constant blue\n\nda_rgb = xr.DataArray(\n    rgb, dims=['y', 'x', 'band'],\n    coords={'y': np.arange(128), 'x': np.arange(128), 'band': [0, 1, 2]},\n)\n\nrgb_path = os.path.join(tmpdir, 'rgb_j2k.tif')\nto_geotiff(da_rgb, rgb_path, compression='jpeg2000')\n\nda_rgb_read = open_geotiff(rgb_path)\nprint(f\"RGB shape: {da_rgb_read.shape}, dtype: {da_rgb_read.dtype}\")\nprint(f\"Exact match: {np.array_equal(da_rgb_read.values, rgb)}\")\n\nfig, axes = plt.subplots(1, 2, figsize=(10, 4))\naxes[0].imshow(rgb)\naxes[0].set_title('Original RGB')\naxes[1].imshow(da_rgb_read.values)\naxes[1].set_title('After J2K roundtrip')\nplt.tight_layout()\nplt.show()",
    "metadata": {},
    "execution_count": null,
    "outputs": []
   },
   {
    "cell_type": "markdown",
    "id": "zzga5hc3a99",
-   "source": "## GPU acceleration\n\nOn systems with nvJPEG2000 installed (CUDA toolkit, RAPIDS environments), pass `gpu=True` to use GPU-accelerated J2K encode/decode. The API is the same -- it falls back to CPU automatically if the library isn't found.\n\n```python\n# GPU write (nvJPEG2000 if available, else CPU fallback)\nwrite_geotiff(cupy_data, \"output.tif\", compression=\"jpeg2000\", gpu=True)\n\n# GPU read (nvJPEG2000 decode if available)\nda = read_geotiff(\"satellite.tif\", gpu=True)\n```",
+   "source": "## GPU acceleration\n\nOn systems with nvJPEG2000 installed (CUDA toolkit, RAPIDS environments), pass `gpu=True` to use GPU-accelerated J2K encode/decode. The API is the same -- it falls back to CPU automatically if the library isn't found.\n\n```python\n# GPU write (nvJPEG2000 if available, else CPU fallback)\nto_geotiff(cupy_data, \"output.tif\", compression=\"jpeg2000\", gpu=True)\n\n# GPU read (nvJPEG2000 decode if available)\nda = open_geotiff(\"satellite.tif\", gpu=True)\n```",
    "metadata": {}
   },
   {

xrspatial/geotiff/tests/test_jpeg2000.py

@@ -137,18 +137,18 @@ def test_with_geo_info(self, tmp_path):
         assert geo.crs_epsg == 4326
 
     def test_public_api_roundtrip(self, tmp_path):
-        """Test via read_geotiff / write_geotiff public API."""
+        """Test via open_geotiff / to_geotiff public API."""
         import xarray as xr
-        from xrspatial.geotiff import read_geotiff, write_geotiff
+        from xrspatial.geotiff import open_geotiff, to_geotiff
 
         data = np.arange(64, dtype=np.uint8).reshape(8, 8)
         da = xr.DataArray(data, dims=['y', 'x'],
                           coords={'y': np.arange(8), 'x': np.arange(8)},
                           attrs={'crs': 4326})
         path = str(tmp_path / 'j2k_1048_api.tif')
-        write_geotiff(da, path, compression='jpeg2000')
+        to_geotiff(da, path, compression='jpeg2000')
 
-        result = read_geotiff(path)
+        result = open_geotiff(path)
         np.testing.assert_array_equal(result.values, data)