Merge the WIP implementation of GMT_IMAGE

pygmt/clib/session.py

@@ -26,7 +26,7 @@
     vectors_to_arrays,
 )
 from pygmt.clib.loading import load_libgmt
-from pygmt.datatypes import _GMT_DATASET, _GMT_GRID
+from pygmt.datatypes import _GMT_DATASET, _GMT_GRID, _GMT_IMAGE
 from pygmt.exceptions import (
     GMTCLibError,
     GMTCLibNoSessionError,
@@ -1769,7 +1769,9 @@ def virtualfile_from_data(
 
     @contextlib.contextmanager
     def virtualfile_out(
-        self, kind: Literal["dataset", "grid"] = "dataset", fname: str | None = None
+        self,
+        kind: Literal["dataset", "grid", "image"] = "dataset",
+        fname: str | None = None,
     ):
         r"""
         Create a virtual file or an actual file for storing output data.
@@ -1782,8 +1784,8 @@ def virtualfile_out(
         Parameters
         ----------
         kind
-            The data kind of the virtual file to create. Valid values are ``"dataset"``
-            and ``"grid"``. Ignored if ``fname`` is specified.
+            The data kind of the virtual file to create. Valid values are ``"dataset"``,
+            ``"grid"``, and ``"image"``. Ignored if ``fname`` is specified.
         fname
             The name of the actual file to write the output data. No virtual file will
             be created.
@@ -1826,8 +1828,11 @@ def virtualfile_out(
             family, geometry = {
                 "dataset": ("GMT_IS_DATASET", "GMT_IS_PLP"),
                 "grid": ("GMT_IS_GRID", "GMT_IS_SURFACE"),
+                "image": ("GMT_IS_IMAGE", "GMT_IS_SURFACE"),
             }[kind]
-            with self.open_virtualfile(family, geometry, "GMT_OUT", None) as vfile:
+            with self.open_virtualfile(
+                family, geometry, "GMT_OUT|GMT_IS_REFERENCE", None
+            ) as vfile:
                 yield vfile
 
     def inquire_virtualfile(self, vfname: str) -> int:
@@ -1873,7 +1878,8 @@ def read_virtualfile(
             Name of the virtual file to read.
         kind
             Cast the data into a GMT data container. Valid values are ``"dataset"``,
-            ``"grid"`` and ``None``. If ``None``, will return a ctypes void pointer.
+            ``"grid"``, ``"image"`` and ``None``. If ``None``, will return a ctypes void
+            pointer.
 
         Examples
         --------
@@ -1921,9 +1927,9 @@ def read_virtualfile(
         # _GMT_DATASET).
         if kind is None:  # Return the ctypes void pointer
             return pointer
-        if kind in {"image", "cube"}:
+        if kind == "cube":
             raise NotImplementedError(f"kind={kind} is not supported yet.")
-        dtype = {"dataset": _GMT_DATASET, "grid": _GMT_GRID}[kind]
+        dtype = {"dataset": _GMT_DATASET, "grid": _GMT_GRID, "image": _GMT_IMAGE}[kind]
         return ctp.cast(pointer, ctp.POINTER(dtype))
 
     def virtualfile_to_dataset(

pygmt/datatypes/__init__.py

@@ -4,3 +4,4 @@
 
 from pygmt.datatypes.dataset import _GMT_DATASET
 from pygmt.datatypes.grid import _GMT_GRID
+from pygmt.datatypes.image import _GMT_IMAGE

pygmt/datatypes/header.py

@@ -203,7 +203,8 @@ def data_attrs(self) -> dict[str, Any]:
         Attributes for the data variable from the grid header.
         """
         attrs: dict[str, Any] = {}
-        attrs["Conventions"] = "CF-1.7"
+        if self.type == 18:  # Grid file format: ns = GMT netCDF format
+            attrs["Conventions"] = "CF-1.7"
         attrs["title"] = self.title.decode()
         attrs["history"] = self.command.decode()
         attrs["description"] = self.remark.decode()

pygmt/datatypes/image.py

@@ -0,0 +1,182 @@
+"""
+Wrapper for the GMT_IMAGE data type.
+"""
+
+import ctypes as ctp
+from typing import ClassVar
+
+import numpy as np
+import xarray as xr
+from pygmt.datatypes.header import _GMT_GRID_HEADER
+
+
+class _GMT_IMAGE(ctp.Structure):  # noqa: N801
+    """
+    GMT image data structure.
+
+    Examples
+    --------
+    >>> from pygmt.clib import Session
+    >>> import numpy as np
+    >>> import xarray as xr
+
+    >>> with Session() as lib:
+    ...     with lib.virtualfile_out(kind="image") as voutimg:
+    ...         lib.call_module("read", f"@earth_day_01d {voutimg} -Ti")
+    ...         # Read the image from the virtual file
+    ...         image = lib.read_virtualfile(vfname=voutimg, kind="image").contents
+    ...         # The image header
+    ...         header = image.header.contents
+    ...         # Access the header properties
+    ...         print(image.type, header.n_bands, header.n_rows, header.n_columns)
+    ...         print(header.pad[:])
+    ...         # The x and y coordinates
+    ...         x = image.x[: header.n_columns]
+    ...         y = image.y[: header.n_rows]
+    ...         # The data array (with paddings)
+    ...         data = np.reshape(
+    ...             image.data[: header.n_bands * header.mx * header.my],
+    ...             (header.my, header.mx, header.n_bands),
+    ...         )
+    ...         # The data array (without paddings)
+    ...         pad = header.pad[:]
+    ...         data = data[pad[2] : header.my - pad[3], pad[0] : header.mx - pad[1], :]
+    ...         print(data.shape)
+    1 3 180 360
+    [2, 2, 2, 2]
+    (180, 360, 3)
+    """
+
+    _fields_: ClassVar = [
+        # Data type, e.g. GMT_FLOAT
+        ("type", ctp.c_int),
+        # Array with color lookup values
+        ("colormap", ctp.POINTER(ctp.c_int)),
+        # Number of colors in a paletted image
+        ("n_indexed_colors", ctp.c_int),
+        # Pointer to full GMT header for the image
+        ("header", ctp.POINTER(_GMT_GRID_HEADER)),
+        # Pointer to actual image
+        ("data", ctp.POINTER(ctp.c_ubyte)),
+        # Pointer to an optional transparency layer stored in a separate variable
+        ("alpha", ctp.POINTER(ctp.c_ubyte)),
+        # Color interpolation
+        ("color_interp", ctp.c_char_p),
+        # Pointer to the x-coordinate vector
+        ("x", ctp.POINTER(ctp.c_double)),
+        # Pointer to the y-coordinate vector
+        ("y", ctp.POINTER(ctp.c_double)),
+        # Book-keeping variables "hidden" from the API
+        ("hidden", ctp.c_void_p),
+    ]
+
+    def to_dataarray(self) -> xr.DataArray:
+        """
+        Convert a _GMT_IMAGE object to an :class:`xarray.DataArray` object.
+
+        Returns
+        -------
+        dataarray
+            A :class:`xarray.DataArray` object.
+
+        Examples
+        --------
+        >>> from pygmt.clib import Session
+        >>> with Session() as lib:
+        ...     with lib.virtualfile_out(kind="image") as voutimg:
+        ...         lib.call_module("read", ["@earth_day_01d", voutimg, "-Ti"])
+        ...         # Read the image from the virtual file
+        ...         image = lib.read_virtualfile(voutimg, kind="image")
+        ...         # Convert to xarray.DataArray and use it later
+        ...         da = image.contents.to_dataarray()
+        >>> da  # doctest: +NORMALIZE_WHITESPACE, +ELLIPSIS
+        <xarray.DataArray 'z' (band: 3, y: 180, x: 360)> Size: 2MB
+        array([[[ 10,  10,  10, ...,  10,  10,  10],
+                [ 10,  10,  10, ...,  10,  10,  10],
+                [ 10,  10,  10, ...,  10,  10,  10],
+                ...,
+                [192, 193, 193, ..., 193, 192, 191],
+                [204, 206, 206, ..., 205, 206, 204],
+                [208, 210, 210, ..., 210, 210, 208]],
+        <BLANKLINE>
+               [[ 10,  10,  10, ...,  10,  10,  10],
+                [ 10,  10,  10, ...,  10,  10,  10],
+                [ 10,  10,  10, ...,  10,  10,  10],
+                ...,
+                [186, 187, 188, ..., 187, 186, 185],
+                [196, 198, 198, ..., 197, 197, 196],
+                [199, 201, 201, ..., 201, 202, 199]],
+        <BLANKLINE>
+               [[ 51,  51,  51, ...,  51,  51,  51],
+                [ 51,  51,  51, ...,  51,  51,  51],
+                [ 51,  51,  51, ...,  51,  51,  51],
+                ...,
+                [177, 179, 179, ..., 178, 177, 177],
+                [185, 187, 187, ..., 187, 186, 185],
+                [189, 191, 191, ..., 191, 191, 189]]])
+        Coordinates:
+          * x        (x) float64 3kB -179.5 -178.5 -177.5 -176.5 ... 177.5 178.5 179.5
+          * y        (y) float64 1kB 89.5 88.5 87.5 86.5 ... -86.5 -87.5 -88.5 -89.5
+          * band     (band) uint8 3B 0 1 2
+        Attributes:
+            title:
+            history:
+            description:
+            long_name:     z
+            actual_range:  [ 1.79769313e+308 -1.79769313e+308]
+
+        >>> da.coords["x"]  # doctest: +NORMALIZE_WHITESPACE, +ELLIPSIS
+        <xarray.DataArray 'x' (x: 360)> Size: 3kB
+        array([-179.5, -178.5, -177.5, ...,  177.5,  178.5,  179.5])
+        Coordinates:
+          * x        (x) float64 3kB -179.5 -178.5 -177.5 -176.5 ... 177.5 178.5 179.5
+
+        >>> da.coords["y"]  # doctest: +NORMALIZE_WHITESPACE, +ELLIPSIS
+        <xarray.DataArray 'y' (y: 180)> Size: 1kB
+        array([ 89.5,  88.5,  87.5,  86.5,  85.5,  84.5,  83.5,  82.5,  81.5,  80.5,
+                79.5,  78.5,  77.5,  76.5,  75.5,  74.5,  73.5,  72.5,  71.5,  70.5,
+                69.5,  68.5,  67.5,  66.5,  65.5,  64.5,  63.5,  62.5,  61.5,  60.5,
+                ...
+                -0.5,  -1.5,  -2.5,  -3.5,  -4.5,  -5.5,  -6.5,  -7.5,  -8.5,  -9.5,
+                ...
+               -60.5, -61.5, -62.5, -63.5, -64.5, -65.5, -66.5, -67.5, -68.5, -69.5,
+               -70.5, -71.5, -72.5, -73.5, -74.5, -75.5, -76.5, -77.5, -78.5, -79.5,
+               -80.5, -81.5, -82.5, -83.5, -84.5, -85.5, -86.5, -87.5, -88.5, -89.5])
+        Coordinates:
+          * y        (y) float64 1kB 89.5 88.5 87.5 86.5 ... -86.5 -87.5 -88.5 -89.5
+
+        >>> da.gmt.registration, da.gmt.gtype
+        (1, 0)
+        """
+
+        # Get image header
+        header: _GMT_GRID_HEADER = self.header.contents
+
+        # Get DataArray without padding
+        pad = header.pad[:]
+        data: np.ndarray = np.reshape(
+            a=self.data[: header.n_bands * header.mx * header.my],
+            newshape=(header.my, header.mx, header.n_bands),
+        )[pad[2] : header.my - pad[3], pad[0] : header.mx - pad[1], :]
+
+        # Get x and y coordinates
+        coords: dict[str, list | np.ndarray] = {
+            "x": self.x[: header.n_columns],
+            "y": self.y[: header.n_rows],
+            "band": np.array([0, 1, 2], dtype=np.uint8),
+        }
+
+        # Create the xarray.DataArray object
+        image = xr.DataArray(
+            data=data,
+            coords=coords,
+            dims=("y", "x", "band"),
+            name=header.name,
+            attrs=header.data_attrs,
+        ).transpose("band", "y", "x")
+
+        # Set GMT accessors.
+        # Must put at the end, otherwise info gets lost after certain image operations.
+        image.gmt.registration = header.registration
+        image.gmt.gtype = header.gtype
+        return image