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Co-authored-by: Meghan Jones <[email protected]> Co-authored-by: Dongdong Tian <[email protected]> Co-authored-by: Wei Ji <[email protected]>
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@@ -135,6 +135,7 @@ Operations on raster data | |
.. autosummary:: | ||
:toctree: generated | ||
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dimfilter | ||
grd2xyz | ||
grdclip | ||
grdcut | ||
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blockmedian, | ||
blockmode, | ||
config, | ||
dimfilter, | ||
grd2cpt, | ||
grd2xyz, | ||
grdclip, | ||
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""" | ||
dimfilter - Directional filtering of grids in the space domain. | ||
""" | ||
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from pygmt.clib import Session | ||
from pygmt.exceptions import GMTInvalidInput | ||
from pygmt.helpers import ( | ||
GMTTempFile, | ||
build_arg_string, | ||
fmt_docstring, | ||
kwargs_to_strings, | ||
use_alias, | ||
) | ||
from pygmt.io import load_dataarray | ||
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@fmt_docstring | ||
@use_alias( | ||
D="distance", | ||
F="filter", | ||
G="outgrid", | ||
I="spacing", | ||
N="sectors", | ||
R="region", | ||
V="verbose", | ||
) | ||
@kwargs_to_strings(I="sequence", R="sequence") | ||
def dimfilter(grid, **kwargs): | ||
r""" | ||
Filter a grid by dividing the filter circle. | ||
Filter a grid in the space (or time) domain by | ||
dividing the given filter circle into the given number of sectors, | ||
applying one of the selected primary convolution or non-convolution | ||
filters to each sector, and choosing the final outcome according to the | ||
selected secondary filter. It computes distances using Cartesian or | ||
Spherical geometries. The output grid can optionally be generated as a | ||
subregion of the input and/or with a new increment using ``spacing``, | ||
which may add an "extra space" in the input data to prevent edge | ||
effects for the output grid. If the filter is low-pass, then the output | ||
may be less frequently sampled than the input. **dimfilter** will not | ||
produce a smooth output as other spatial filters | ||
do because it returns a minimum median out of *N* medians of *N* | ||
sectors. The output can be rough unless the input data is noise-free. | ||
Thus, an additional filtering (e.g., Gaussian via :func:`pygmt.grdfilter`) | ||
of the DiM-filtered data is generally recommended. | ||
Full option list at :gmt-docs:`dimfilter.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. | ||
distance : int or str | ||
Distance flag tells how grid (x,y) relates to filter width, as follows: | ||
- **0**\ : grid (x,y) in 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 two 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. | ||
filter : str | ||
**x**\ *width*\ [**+l**\|\ **u**]. | ||
Sets the primary filter type. Choose among convolution and | ||
non-convolution filters. Use the filter code **x** followed by | ||
the full diameter *width*. Available convolution filters are: | ||
- (**b**) Boxcar: All weights are equal. | ||
- (**c**) Cosine Arch: Weights follow a cosine arch curve. | ||
- (**g**) Gaussian: Weights are given by the Gaussian function. | ||
Non-convolution filters are: | ||
- (**m**) Median: Returns median value. | ||
- (**p**) Maximum likelihood probability (a mode estimator): Return | ||
modal value. If more than one mode is found we return their average | ||
value. Append **+l** or **+h** to the filter width if you want | ||
to return the smallest or largest of each sector's modal values. | ||
sectors : str | ||
**x**\ *sectors*\ [**+l**\|\ **u**] | ||
Sets the secondary filter type **x** and the number of bow-tie sectors. | ||
*sectors* must be integer and larger than 0. When *sectors* is | ||
set to 1, the secondary filter is not effective. Available secondary | ||
filters **x** are: | ||
- (**l**) Lower: Return the minimum of all filtered values. | ||
- (**u**) Upper: Return the maximum of all filtered values. | ||
- (**a**) Average: Return the mean of all filtered values. | ||
- (**m**) Median: Return the median of all filtered values. | ||
- (**p**) Mode: Return the mode of all filtered values: | ||
If more than one mode is found we return their average | ||
value. Append **+l** or **+h** to the sectors if you rather want to | ||
return the smallest or largest of the modal values. | ||
spacing : str or list | ||
*x_inc* [and optionally *y_inc*] is the output Increment. Append | ||
**m** to indicate minutes, or **c** to indicate seconds. If the new | ||
*x_inc*, *y_inc* are NOT integer multiples of the old ones (in the | ||
input data), filtering will be considerably slower. [Default: Same | ||
as input.] | ||
region : str or list | ||
[*xmin*, *xmax*, *ymin*, *ymax*]. | ||
Defines the region of the output points. [Default: Same as input.] | ||
{V} | ||
Returns | ||
------- | ||
ret: xarray.DataArray or None | ||
Return type depends on whether the ``outgrid`` parameter is set: | ||
- :class:`xarray.DataArray` if ``outgrid`` is not set | ||
- None if ``outgrid`` is set (grid output will be stored in file set by | ||
``outgrid``) | ||
""" | ||
if not all(arg in kwargs for arg in ["D", "F", "N"]) and "Q" not in kwargs: | ||
raise GMTInvalidInput( | ||
"""At least one of the following parameters must be specified: | ||
distance, filters, or sectors.""" | ||
) | ||
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with GMTTempFile(suffix=".nc") as tmpfile: | ||
with Session() as lib: | ||
file_context = lib.virtualfile_from_data(check_kind=None, data=grid) | ||
with file_context as infile: | ||
if "G" not in kwargs: # 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("dimfilter", arg_str) | ||
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return load_dataarray(outgrid) if outgrid == tmpfile.name else None |
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""" | ||
Tests for dimfilter. | ||
""" | ||
import os | ||
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import pytest | ||
import xarray as xr | ||
from pygmt import dimfilter, load_dataarray | ||
from pygmt.exceptions import GMTInvalidInput | ||
from pygmt.helpers import GMTTempFile | ||
from pygmt.helpers.testing import load_static_earth_relief | ||
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@pytest.fixture(scope="module", name="grid") | ||
def fixture_grid(): | ||
""" | ||
Load the grid data from the static_earth_relief file. | ||
""" | ||
return load_static_earth_relief() | ||
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@pytest.fixture(scope="module", name="expected_grid") | ||
def fixture_grid_result(): | ||
""" | ||
Load the expected dimfilter grid result. | ||
""" | ||
return xr.DataArray( | ||
data=[ | ||
[346.0, 344.5, 349.0, 349.0], | ||
[344.5, 318.5, 344.5, 394.0], | ||
[344.5, 356.5, 345.5, 352.5], | ||
[367.5, 349.0, 385.5, 349.0], | ||
[435.0, 385.5, 413.5, 481.5], | ||
], | ||
coords=dict( | ||
lon=[-54.5, -53.5, -52.5, -51.5], | ||
lat=[-23.5, -22.5, -21.5, -20.5, -19.5], | ||
), | ||
dims=["lat", "lon"], | ||
) | ||
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def test_dimfilter_outgrid(grid, expected_grid): | ||
""" | ||
Test the required parameters for dimfilter with a set outgrid. | ||
""" | ||
with GMTTempFile(suffix=".nc") as tmpfile: | ||
result = dimfilter( | ||
grid=grid, | ||
outgrid=tmpfile.name, | ||
filter="m600", | ||
distance=4, | ||
sectors="l6", | ||
region=[-55, -51, -24, -19], | ||
) | ||
assert result is None # return value is None | ||
assert os.path.exists(path=tmpfile.name) # check that outgrid exists | ||
temp_grid = load_dataarray(tmpfile.name) | ||
xr.testing.assert_allclose(a=temp_grid, b=expected_grid) | ||
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def test_dimfilter_no_outgrid(grid, expected_grid): | ||
""" | ||
Test the required parameters for dimfilter with no set outgrid. | ||
""" | ||
result = dimfilter( | ||
grid=grid, filter="m600", distance=4, sectors="l6", region=[-55, -51, -24, -19] | ||
) | ||
assert result.dims == ("lat", "lon") | ||
assert result.gmt.gtype == 1 # Geographic grid | ||
assert result.gmt.registration == 1 # Pixel registration | ||
xr.testing.assert_allclose(a=result, b=expected_grid) | ||
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def test_dimfilter_fails(grid): | ||
""" | ||
Check that dimfilter fails correctly when not all of sectors, filters, and | ||
distance are specified. | ||
""" | ||
with pytest.raises(GMTInvalidInput): | ||
dimfilter(grid=grid, sectors="l6", distance=4) |