Wrap grdfilter

doc/api/index.rst

@@ -71,6 +71,7 @@ Operations on grids:
     :toctree: generated
 
     grdcut
+    grdfilter
     grdtrack
 
 Crossover analysis with x2sys:

pygmt/__init__.py

@@ -19,7 +19,7 @@
 from .sampling import grdtrack
 from .mathops import makecpt
 from .modules import GMTDataArrayAccessor, config, info, grdinfo, which
-from .gridops import grdcut
+from .gridops import grdcut, grdfilter
 from .x2sys import x2sys_init, x2sys_cross
 from . import datasets
 

pygmt/gridops.py

@@ -116,3 +116,144 @@ def grdcut(grid, **kwargs):
             result = None  # if user sets an outgrid, return None
 
         return result
+
+
+@fmt_docstring
+@use_alias(
+    D="distance",
+    F="filter",
+    G="outgrid",
+    I="spacing",
+    N="nans",
+    R="region",
+    T="toggle",
+    V="verbose",
+)
+@kwargs_to_strings(R="sequence")
+def grdfilter(grid, **kwargs):
+    """
+    Filter a grid in the space (or time) domain.
+
+    Filter a grid file in the time domain using one of the selected convolution
+    or non-convolution isotropic or rectangular filters and compute distances
+    using Cartesian or Spherical geometries. The output grid file can
+    optionally be generated as a sub-region of the input (via *region*) and/or
+    with new increment (via *spacing*) or registration (via *toggle*). In this
+    way, one may have "extra space" in the input data so that the edges will
+    not be used and the output can be within one half-width of the input edges.
+    If the filter is low-pass, then the output may be less frequently sampled
+    than the input.
+
+    Full option list at :gmt-docs:`grdfilter.html`
+
+    {aliases}
+
+    Parameters
+    ----------
+    grid : str or xarray.DataArray
+        The file name of the input grid or the grid loaded as a DataArray.
+    outgrid : str or None
+        The name of the output netCDF file with extension .nc to store the grid
+        in.
+    filter : str
+        ``xwidth[/width2][modifiers]``.
+        Name of filter type you which to apply, followed by the width
+        b: Box Car; c: Cosine Arch; g: Gaussian; o: Operator; m: Median;
+        p: Maximum Likelihood probability; h: histogram
+        Example: F='m600' for a median filter with width of 600
+    distance : str
+        Distance *flag* tells how grid (x,y) relates to filter width as
+        follows:
+
+        p: grid (px,py) with *width* an odd number of pixels; Cartesian
+        distances.
+
+        0: grid (x,y) same units as *width*, Cartesian distances.
+
+        1: grid (x,y) in degrees, *width* in kilometers, Cartesian distances.
+
+        2: grid (x,y) in degrees, *width* in km, dx scaled by cos(middle y),
+        Cartesian distances.
+
+        The above options are fastest because they allow weight matrix to be
+        computed only once. The next three options are slower because they
+        recompute weights for each latitude.
+
+        3: grid (x,y) in degrees, *width* in km, dx scaled by cosine(y),
+        Cartesian distance calculation.
+
+        4: grid (x,y) in degrees, *width* in km, Spherical distance
+        calculation.
+
+        5: grid (x,y) in Mercator ``projection='m1'`` img units, *width* in km,
+        Spherical distance calculation.
+
+    spacing : str
+        ``xinc[+e|n][/yinc[+e|n]]``.
+        x_inc [and optionally y_inc] is the grid spacing.
+    nans : str or float
+        ``i|p|r``.
+        Determine how NaN-values in the input grid affects the filtered output.
+    {R}
+    toggle : bool
+        Toggle the node registration for the output grid so as to become the
+        opposite of the input grid. [Default gives the same registration as the
+        input grid].
+    {V}
+
+    Returns
+    -------
+    ret: xarray.DataArray or None
+        Return type depends on whether the *outgrid* parameter is set:
+        - xarray.DataArray if *outgrid* is not set
+        - None if *outgrid* is set (grid output will be stored in *outgrid*)
+
+    Examples
+    --------
+    >>> import os
+    >>> import pygmt
+
+    >>> # Apply a filter of 600km (full width) to the @earth_relief_30m file
+    >>> # and return a filtered field (saved as netcdf)
+    >>> pygmt.grdfilter(
+    ...     grid="@earth_relief_30m",
+    ...     filter="m600",
+    ...     distance="4",
+    ...     region=[150, 250, 10, 40],
+    ...     spacing=0.5,
+    ...     outgrid="filtered_pacific.nc",
+    ... )
+    >>> os.remove("filtered_pacific.nc")  # cleanup file
+
+    >>> # Apply a gaussian smoothing filter of 600 km in the input data array,
+    >>> # and returns a filtered data array with the smoothed field.
+    >>> grid = pygmt.datasets.load_earth_relief()
+    >>> smooth_field = pygmt.grdfilter(grid=grid, filter="g600", distance="4")
+
+    """
+    kind = data_kind(grid)
+
+    with GMTTempFile(suffix=".nc") as tmpfile:
+        with Session() as lib:
+            if kind == "file":
+                file_context = dummy_context(grid)
+            elif kind == "grid":
+                file_context = lib.virtualfile_from_grid(grid)
+            else:
+                raise GMTInvalidInput("Unrecognized data type: {}".format(type(grid)))
+
+            with file_context as infile:
+                if "G" not in kwargs.keys():  # if outgrid is unset, output to tempfile
+                    kwargs.update({"G": tmpfile.name})
+                outgrid = kwargs["G"]
+                arg_str = " ".join([infile, build_arg_string(kwargs)])
+                lib.call_module("grdfilter", arg_str)
+
+        if outgrid == tmpfile.name:  # if user did not set outgrid, return DataArray
+            with xr.open_dataarray(outgrid) as dataarray:
+                result = dataarray.load()
+                _ = result.gmt  # load GMTDataArray accessor information
+        else:
+            result = None  # if user sets an outgrid, return None
+
+        return result