Add Figure.tilemap to plot XYZ tile maps #2394

weiji14 · 2023-03-04T01:02:50Z

Description of proposed changes

New tilemap function for plotting XYZ tile maps! This is essentially a convenience wrapper around pygmt.datasets.load_tile_map and pygmt.Figure.grdimage.

Preview at https://pygmt-dev--2394.org.readthedocs.build/en/2394/api/generated/pygmt.Figure.tilemap.html

This is the second part of #2115 that takes the output xarray.DataArray from pygmt.datasets.load_tile_map (added in #2125) and plots it using fig.grdimage.

Usage:

import contextily
import pygmt

fig = pygmt.Figure()
fig.tilemap(
    region=[-157.6, -157.1, 1.68, 2.08],  # West, East, South, North
    source=contextily.providers.Stamen.Watercolor,
    frame=True,
)
fig.show()

produces this watercolor map of Kiribati:

Notes:

rioxarray will be added as an optional dependency, as it is used for the xarray.DataArray to GeoTIFF conversion
~~The implementation of tilemap is a little tricky due to cyclic import issues, please suggest if there are better ways~~ fixed with Add Figure.tilemap to plot XYZ tile maps #2394 (comment)
By default, a given region with lonlat coordinates will produce a map with lonlat (OGC:WGS84) coordinates that are distorted from the original Spherical Mercator (EPSG:3857) tiles, see Add Figure.tilemap to plot XYZ tile maps #2394 (comment)
The region parameter only accepts a list like [lonmin, lonmax, latmin, latmax], which is different from other GMT/PyGMT functions that accept more types of region values, see Add Figure.tilemap to plot XYZ tile maps #2394 (comment)

Fixes #2115

Reminders

Run make format and make check to make sure the code follows the style guide.
Add tests for new features or tests that would have caught the bug that you're fixing.
Add new public functions/methods/classes to doc/api/index.rst.
Write detailed docstrings for all functions/methods.
If wrapping a new module, open a 'Wrap new GMT module' issue and submit reasonably-sized PRs.
If adding new functionality, add an example to docstrings or tutorials.
Use underscores (not hyphens) in names of Python files and directories.

Slash Commands

You can write slash commands (/command) in the first line of a comment to perform
specific operations. Supported slash commands are:

/format: automatically format and lint the code
/test-gmt-dev: run full tests on the latest GMT development version

Initial commit for adding the tilemap function for plotting XYZ tile maps. This is a wrapper around `pygmt.datasets.load_tile_map` and `pygmt.Figure.grdimage`. Aliases from `grdimage` have been copied over, and docstring for parameters from `load_tile_map` have been copied over too.

github-actions · 2023-03-04T01:19:07Z

Summary of changed images

This is an auto-generated report of images that have changed on the DVC remote

Status	Path
added	pygmt/tests/baseline/test_tilemap_no_clip_False.png
added	pygmt/tests/baseline/test_tilemap_no_clip_True.png
added	pygmt/tests/baseline/test_tilemap_ogc_wgs84.png
added	pygmt/tests/baseline/test_tilemap_web_mercator.png

Image diff(s)

Added images

pygmt/tests/baseline/test_tilemap_no_clip_False.png

pygmt/tests/baseline/test_tilemap_no_clip_True.png

pygmt/tests/baseline/test_tilemap_ogc_wgs84.png

pygmt/tests/baseline/test_tilemap_web_mercator.png

Modified images

Path	Old	New

Report last updated at commit c3fca14

Let the Continuous Integration tests run with `rioxarray`, include it in pyproject.toml and environment.yml, and document it in `doc/install.rst` as an optional dependency.

doc/install.rst

weiji14 · 2023-03-04T01:39:20Z

pygmt/src/tilemap.py

+ # R="region",
+ V="verbose",
+ n="interpolation",
+ c="panel",
+ f="coltypes",
+ p="perspective",
+ t="transparency",
+ x="cores",
+)
+@kwargs_to_strings(c="sequence_comma", p="sequence") # R="sequence",
+def tilemap(
+ self, region, zoom="auto", source=None, lonlat=True, wait=0, max_retries=2, **kwargs
+):


Currently region needs to be a list to work with load_tile_map, but I'm debating on whether to allow strings like 0/1/2/3 or other styles supported by GMT -R as mentioned in #153 (comment) and https://docs.generic-mapping-tools.org/6.4/cookbook/options.html#data-domain-or-map-region-the-r-option

other styles supported by GMT -R as mentioned in #153 (comment) and https://docs.generic-mapping-tools.org/6.4/cookbook/options.html#data-domain-or-map-region-the-r-option

Other styles are more tricky to support. For example, how can we know the boundingbox for region="US"?

Other styles are more tricky to support.

Hmm, I was mostly just thinking about 0/1/2/3, and maybe np.array([0, 1, 2, 3]). Usually users would set a region variable near the top of their code, and they might find it strange why their region that works for fig.basemap doesn't work for fig.tilemap.

For example, how can we know the boundingbox for region="US"?

If only there was an API in GMT to return the bounding box for a given region 😉 Global regions like region="g" and region="d" might be easy to support, but ISO code regions (https://www.pygmt.org/v0.8.0/tutorials/basics/regions.html#iso-code) like region="JP" and `region=JP+r3" will be a bit trickier.

If only there was an API in GMT to return the bounding box for a given region Global regions like region="g" and region="d" might be easy to support, but ISO code regions (https://www.pygmt.org/v0.8.0/tutorials/basics/regions.html#iso-code) like region="JP" and `region=JP+r3" will be a bit trickier.

Open a upstream feature request in the GMT repository?

Hmm, or do you think we can use GMT_Extract_Region that's wrapped here:

pygmt/pygmt/clib/session.py

Lines 1500 to 1571 in 0b5a69b

def extract_region(self):

"""

Extract the WESN bounding box of the currently active figure.

Retrieves the information from the PostScript file, so it works for

country codes as well.

Returns

-------

* wesn : 1-D array

A numpy 1-D array with the west, east, south, and north dimensions

of the current figure.

Examples

--------

>>> import pygmt

>>> fig = pygmt.Figure()

>>> fig.coast(

... region=[0, 10, -20, -10],

... projection="M6i",

... frame=True,

... land="black",

... )

>>> with Session() as lib:

... wesn = lib.extract_region()

...

>>> print(", ".join([f"{x:.2f}" for x in wesn]))

0.00, 10.00, -20.00, -10.00

Using ISO country codes for the regions (for example ``'US.HI'`` for

Hawaii):

>>> fig = pygmt.Figure()

>>> fig.coast(

... region="US.HI", projection="M6i", frame=True, land="black"

... )

>>> with Session() as lib:

... wesn = lib.extract_region()

...

>>> print(", ".join([f"{x:.2f}" for x in wesn]))

-164.71, -154.81, 18.91, 23.58

The country codes can have an extra argument that rounds the region a

multiple of the argument (for example, ``'US.HI+r5'`` will round the

region to multiples of 5):

>>> fig = pygmt.Figure()

>>> fig.coast(

... region="US.HI+r5", projection="M6i", frame=True, land="black"

... )

>>> with Session() as lib:

... wesn = lib.extract_region()

...

>>> print(", ".join([f"{x:.2f}" for x in wesn]))

-165.00, -150.00, 15.00, 25.00

"""

c_extract_region = self.get_libgmt_func(

"GMT_Extract_Region",

argtypes=[ctp.c_void_p, ctp.c_char_p, ctp.POINTER(ctp.c_double)],

restype=ctp.c_int,

)

wesn = np.empty(4, dtype=np.float64)

wesn_pointer = wesn.ctypes.data_as(ctp.POINTER(ctp.c_double))

# The second argument to GMT_Extract_Region is a file pointer to a

# PostScript file. It's only valid in classic mode. Use None to get a

# NULL pointer instead.

status = c_extract_region(self.session_pointer, None, wesn_pointer)

if status != 0:

raise GMTCLibError("Failed to extract region from current figure.")

return wesn

Downside is that it requires a figure instance to be set up already first, before the bounding box coordinates can be extracted.

I don't think it will work. Actually, a figure instance is not enough. We have to plot something to generate the hidden PostScript file before calling extract_region.

In [1]: import pygmt In [2]: fig = pygmt.Figure() In [3]: fig.region pygmt-session [ERROR]: No hidden PS file found --------------------------------------------------------------------------- GMTCLibError Traceback (most recent call last) Cell In[3], line 1 ----> 1 fig.region File ~/OSS/gmt/pygmt/pygmt/figure.py:126, in Figure.region(self) 124 self._activate_figure() 125 with Session() as lib: --> 126 wesn = lib.extract_region() 127 return wesn File ~/OSS/gmt/pygmt/pygmt/clib/session.py:1570, in Session.extract_region(self) 1568 status = c_extract_region(self.session_pointer, None, wesn_pointer) 1569 if status != 0: -> 1570 raise GMTCLibError("Failed to extract region from current figure.") 1571 return wesn

I don't think it will work. Actually, a figure instance is not enough. We have to plot something to generate the hidden PostScript file before calling extract_region.

Hmm yeah, we would need to maybe do a fig.basemap and then fig.grdimage, but that's a bit of a hacky solution.

Let's just keep this PR simple and support only a list of [xmin, xmax, ymin, ymax] coordinates for now. There can be a follow up PR to support other region arguments (most likely after PyGMT v0.9.0) if there's interest in this 'enhancement'.

pygmt/src/tilemap.py

weiji14 · 2023-03-04T01:43:09Z

pygmt/src/tilemap.py

+ with Session() as lib:
+ lib.call_module(
+ module="grdimage", args=build_arg_string(kwargs, infile=tmpfile.name)
+ )


Note that this is not the full implementation of PyGMT's fig.grdimage, which is actually a bit more complicated to support shading (-I) with an xarray.DataArray grid

pygmt/pygmt/src/grdimage.py

Lines 179 to 192 in 8f31706

with Session() as lib:

file_context = lib.virtualfile_from_data(check_kind="raster", data=grid)

with contextlib.ExitStack() as stack:

# shading using an xr.DataArray

if kwargs.get("I") is not None and data_kind(kwargs["I"]) == "grid":

shading_context = lib.virtualfile_from_data(

check_kind="raster", data=kwargs["I"]

)

kwargs["I"] = stack.enter_context(shading_context)

fname = stack.enter_context(file_context)

lib.call_module(

module="grdimage", args=build_arg_string(kwargs, infile=fname)

)

Question is: should we support shading of the XYZ tiles with xarray.DataArray grids? Or is there a way to use the grdimage implementation above directly without code duplication?

Currently I would say no to shading.

doc/install.rst

seisman · 2023-03-04T08:10:24Z

pygmt/src/tilemap.py

+ # R="region",
+ V="verbose",
+ n="interpolation",
+ c="panel",
+ f="coltypes",
+ p="perspective",
+ t="transparency",
+ x="cores",
+)
+@kwargs_to_strings(c="sequence_comma", p="sequence") # R="sequence",
+def tilemap(
+ self, region, zoom="auto", source=None, lonlat=True, wait=0, max_retries=2, **kwargs
+):


other styles supported by GMT -R as mentioned in #153 (comment) and https://docs.generic-mapping-tools.org/6.4/cookbook/options.html#data-domain-or-map-region-the-r-option

Other styles are more tricky to support. For example, how can we know the boundingbox for region="US"?

pygmt/src/tilemap.py

Co-Authored-By: Dongdong Tian <[email protected]>

Need to go one more level down. Co-Authored-By: Dongdong Tian <[email protected]>

Running the doctest with rioxarray installed with georeference the resulting `xarray.DataArray` and add a `spatial_ref` coordinate.

Just use a global map at zoom level 0 to make the test run in about 2s instead of >10s.

doc/api/index.rst

weiji14 · 2023-03-04T09:00:31Z

pygmt/src/tilemap.py

+ N="no_clip",
+ Q="nan_transparent",
+ # R="region",


Was playing with the zoom parameter just now, and it seems that setting lower zoom levels (e.g. 0) will actually cause the area covered by contextily.bounds2img to be bigger than the original bounding box region. ~~This might come as a surprise for users, so maybe we should set no_clip to False by default? Would require a bit of extra work to get correct.~~ Edit: Sorry, got a bit confused by the double negatives, no_clip (-N) is already False by default, just needed to pass the region arguments to grdimage properly.

Alternatively, we could also do the clipping in pygmt.datasets.load_tile_map.

Added commit 17d0734 to ensure that:

The plot is clipped to the bounding box region when no_clip=False (default)

The plot extends to areas outside of the bounding box region when no_clip=True

…pes, cores Probably not needed with tilemap function.

Since `mamba` is recommended over `conda` as per #2385.

seisman · 2023-03-13T04:09:16Z

Usage:

import contextily
import pygmt

fig = pygmt.Figure()
fig.tilemap(
    region=[-157.6, -157.1, 1.68, 2.08],  # West, East, South, North
    source=contextily.providers.Stamen.Watercolor,
    frame=True,
)
fig.show()

produces this watercolor map of Kiribati:

Do we need to convert the map tiles from EPSG:3857 to longitude/latitude?

pyproject.toml

pygmt/src/tilemap.py

Co-Authored-By: Dongdong Tian <[email protected]>

GIven a region in lonlat coordinates, ensure that the output figure is also plotted in lonlat instead of Web Mercator.

weiji14 · 2023-03-20T10:04:25Z

Do we need to convert the map tiles from EPSG:3857 to longitude/latitude?

Yes, if lonlat=True (default), then I think the output map should be in lon/lat as well to make it intuitive. I've implemented this in fde94ad. The issue with this is that the pixels will be reprojected and distorted by default, which might not be a problem for tile maps like Stamen Terrain, but can be problematic when there are words on the tile map (e.g. for OpenStreetMap).

Xref #2436

seisman · 2023-03-20T14:12:12Z

pygmt/src/tilemap.py

+ # bounding box region was provided in lonlat
+ if lonlat and raster.rio.crs == "EPSG:3857":
+ raster = raster.rio.reproject(dst_crs="OGC:CRS84")
+ raster.gmt.gtype = 1 # set to geographic type


Setting raster.gmt.gtype = 1 is useless, because raster.rio.to_raster doesn't understand it, right?

Yes, rioxarray's .rio.to_raster won't understand .gmt.gtype, but I don't want to forget to add this after #2398 is merged 🙂

seisman · 2023-03-20T14:22:46Z

pygmt/src/tilemap.py

+ # Only set region if no_clip is False, so that plot is clipped to exact
+ # bounding box region
+ if not kwargs.get("N"):
+ kwargs["R"] = "/".join(str(coordinate) for coordinate in region)


When no_clip is not given, it defaults to None and not kwargs.get("N") is True, which means the plot is clipped. I find the code is a little difficult to understand. Do you think the following changes make it better? Or if kwargs.get("N") is in [None, False]?

Suggested change

# Only set region if no_clip is False, so that plot is clipped to exact

# bounding box region

if not kwargs.get("N"):

kwargs["R"] = "/".join(str(coordinate) for coordinate in region)

# Only set region if no_clip is False or None, so that plot is clipped to exact

# bounding box region

if kwargs.get("N") is not True:

kwargs["R"] = "/".join(str(coordinate) for coordinate in region)

Yeah, double negatives are confusing. I went with kwargs.get("N") in [None, False] at 125574e.

Co-Authored-By: Dongdong Tian <[email protected]> Co-Authored-By: Michael Grund <[email protected]>

Double negatives are confusing Co-Authored-By: Dongdong Tian <[email protected]>

seisman

This PR looks great to me.

seisman · 2023-03-24T02:30:35Z

@michaelgrund and @yvonnefroehlich It would be great if you can give this PR a final review before we merge it.

michaelgrund

Looks good! Thanks again for working on that @weiji14 😉

pygmt/src/tilemap.py

yvonnefroehlich

I am afriad I do not have the knowledge to review this PR reliable, but what I understand make sense to me.

seisman · 2023-03-27T01:06:07Z

@weiji14 OK to merge?

weiji14 · 2023-03-27T01:09:34Z

@weiji14 OK to merge?

Yes I'll merge it today. Let me incorporate #2394 (comment) first.

Co-authored-by: Yvonne Fröhlich <[email protected]>

weiji14 · 2023-03-27T01:46:19Z

Hold on, let me fix this dtype error on Windows / Python 3.11 + NumPy 1.24 at https://github.com/GenericMappingTools/pygmt/actions/runs/4527632070/jobs/7973665357?pr=2394#step:11:737. Looks similar to #2393:

_______________ [doctest] pygmt.datasets.tile_map.load_tile_map _______________
095     >>> from pygmt.datasets import load_tile_map
096     >>> raster = load_tile_map(
097     ...     region=[-180.0, 180.0, -90.0, 0.0],  # West, East, South, North
098     ...     zoom=1,  # less detailed zoom level
099     ...     source=contextily.providers.Stamen.TerrainBackground,
100     ...     lonlat=True,  # bounding box coordinates are longitude/latitude
101     ... )
102     >>> raster.sizes
103     Frozen({'band': 3, 'y': 256, 'x': 512})
104     >>> raster.coords
Differences (unified diff with -expected +actual):
    @@ -1,5 +1,5 @@
     Coordinates:
       * band         (band) uint8 0 1 2
    -  * y            (y) float64 -7.081e-10 -7.858e+04 ... -1.996e+07 ...
    +  * y            (y) float64 -7.081e-10 -7.858e+04 ... -1.996e+07 -2.004e+07
       * x            (x) float64 -2.004e+07 -1.996e+07 ... 1.996e+07 2.004e+07
    -    spatial_ref  int64 0
    +    spatial_ref  int32 0

D:\a\pygmt\pygmt\pygmt\datasets\tile_map.py:104: DocTestFailure
============================== warnings summary ===============================

So that the `spatial_ref` CF coordinate won't be set, which would result in an int32 variable on Windows but int64 on Linux/macOS.

weiji14 · 2023-03-27T02:13:37Z

pygmt/datasets/tile_map.py

@@ -147,6 +147,6 @@ def load_tile_map(region, zoom="auto", source=None, lonlat=True, wait=0, max_ret

 # If rioxarray is installed, set the coordinate reference system
 if hasattr(dataarray, "rio"):
- dataarray = dataarray.rio.write_crs(input_crs="EPSG:3857")
+ dataarray = dataarray.rio.set_crs(input_crs="EPSG:3857")


Changed from using .rio.write_crs to .rio.set_crs to prevent the CF coordinate spatial_ref from being written to the output xarray.DataArray. This fixes the int32 on Windows bu int64 on Linux/macOS issue mentioned in #2394 (comment).

If this looks ok (and the tests pass), I'll proceed to merge in this PR.

Looks good.

weiji14 added the feature Brand new feature label Mar 4, 2023

weiji14 added this to the 0.9.0 milestone Mar 4, 2023

weiji14 self-assigned this Mar 4, 2023

Add rioxarray to CI build matrix and include it as optional dependency

1d24291

Let the Continuous Integration tests run with `rioxarray`, include it in pyproject.toml and environment.yml, and document it in `doc/install.rst` as an optional dependency.

weiji14 mentioned this pull request Mar 4, 2023

Integration with contextily to plot xyz basemaps #2115

Closed

weiji14 commented Mar 4, 2023

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seisman reviewed Mar 4, 2023

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weiji14 and others added 5 commits March 4, 2023 21:21

Fix typo on rioxarray URL

fa8641b

Co-Authored-By: Dongdong Tian <[email protected]>

Fix import-outside-toplevel for load_tile_map function

c51d9c6

Need to go one more level down. Co-Authored-By: Dongdong Tian <[email protected]>

Merge branch 'main' into tilemap

6398829

Fix doctest for load_tile_map to include spatial_ref

56f5df8

Running the doctest with rioxarray installed with georeference the resulting `xarray.DataArray` and add a `spatial_ref` coordinate.

Speed up test_tilemap by using zoom level 0

ff2fba0

Just use a global map at zoom level 0 to make the test run in about 2s instead of >10s.

weiji14 commented Mar 4, 2023

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weiji14 added 3 commits March 6, 2023 22:04

Remove aliases img_out, cmap, img_in, bit_color, interpolation, colty…

c315609

…pes, cores Probably not needed with tilemap function.

Merge branch 'main' into tilemap

fd93c67

Switch from conda install to mamba install

a1c29e4

Since `mamba` is recommended over `conda` as per #2385.

seisman reviewed Mar 13, 2023

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maxrjones mentioned this pull request Mar 14, 2023

Release PyGMT v0.9.0 #2424

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weiji14 and others added 5 commits March 20, 2023 22:07

Add trailing comma to lists in pyproject.toml

2b20535

Co-Authored-By: Dongdong Tian <[email protected]>

Reword description of fig.tilemap

7efdbfd

Move load_tile_map call out of GMTTempFile context

d503268

Co-Authored-By: Dongdong Tian <[email protected]>

Merge branch 'main' into tilemap

0a03a47

Reproject and plot map in lonlat coordinates by default

fde94ad

GIven a region in lonlat coordinates, ensure that the output figure is also plotted in lonlat instead of Web Mercator.

Switch from ModuleNotFoundError to ImportError

9158c09

Xref #2436

seisman reviewed Mar 20, 2023

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seisman mentioned this pull request Mar 20, 2023

Replace ModuleNotFoundError with the more general ImportError #2441

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weiji14 and others added 2 commits March 23, 2023 21:10

Web Mercator to Spherical Mercator and remove verbose statement

de74e3d

Co-Authored-By: Dongdong Tian <[email protected]> Co-Authored-By: Michael Grund <[email protected]>

Refactor no_clip if-condition to be a little more clear

125574e

Double negatives are confusing Co-Authored-By: Dongdong Tian <[email protected]>

seisman approved these changes Mar 23, 2023

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Merge branch 'main' into tilemap

4d98102

weiji14 marked this pull request as ready for review March 23, 2023 09:07

weiji14 added final review call This PR requires final review and approval from a second reviewer and removed needs review This PR has higher priority and needs review. labels Mar 23, 2023

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Merge branch 'main' into tilemap

10908d5

weiji14 and others added 2 commits March 27, 2023 14:11

Edit docstring to say method instead of function

972c2c4

Co-authored-by: Yvonne Fröhlich <[email protected]>

Merge branch 'main' into tilemap

e22d012

weiji14 enabled auto-merge (squash) March 27, 2023 01:18

weiji14 disabled auto-merge March 27, 2023 01:44

Use rio.set_crs instead of rio.write_crs

c3fca14

So that the `spatial_ref` CF coordinate won't be set, which would result in an int32 variable on Windows but int64 on Linux/macOS.

weiji14 commented Mar 27, 2023

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weiji14 merged commit fad08a6 into main Mar 27, 2023

weiji14 deleted the tilemap branch March 27, 2023 03:02

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seisman mentioned this pull request Apr 18, 2023

clib.Session: Wrap the GMT_Get_Common API function #2500

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Allow passing RGB xarray.DataArray images into grdimage #2590

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Allow passing in Red, Green, Blue grids into grdimage #370

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Integrate with rioxarray and implement GMT_IMAGE to read RGB GeoTIFFs #1555

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Add Figure.tilemap to plot XYZ tile maps #2394

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	def extract_region(self):
	"""
	Extract the WESN bounding box of the currently active figure.

	Retrieves the information from the PostScript file, so it works for
	country codes as well.

	Returns
	-------
	* wesn : 1-D array
	A numpy 1-D array with the west, east, south, and north dimensions
	of the current figure.

	Examples
	--------

	>>> import pygmt
	>>> fig = pygmt.Figure()
	>>> fig.coast(
	... region=[0, 10, -20, -10],
	... projection="M6i",
	... frame=True,
	... land="black",
	... )
	>>> with Session() as lib:
	... wesn = lib.extract_region()
	...
	>>> print(", ".join([f"{x:.2f}" for x in wesn]))
	0.00, 10.00, -20.00, -10.00

	Using ISO country codes for the regions (for example ``'US.HI'`` for
	Hawaii):

	>>> fig = pygmt.Figure()
	>>> fig.coast(
	... region="US.HI", projection="M6i", frame=True, land="black"
	... )
	>>> with Session() as lib:
	... wesn = lib.extract_region()
	...
	>>> print(", ".join([f"{x:.2f}" for x in wesn]))
	-164.71, -154.81, 18.91, 23.58

	The country codes can have an extra argument that rounds the region a
	multiple of the argument (for example, ``'US.HI+r5'`` will round the
	region to multiples of 5):

	>>> fig = pygmt.Figure()
	>>> fig.coast(
	... region="US.HI+r5", projection="M6i", frame=True, land="black"
	... )
	>>> with Session() as lib:
	... wesn = lib.extract_region()
	...
	>>> print(", ".join([f"{x:.2f}" for x in wesn]))
	-165.00, -150.00, 15.00, 25.00
	"""
	c_extract_region = self.get_libgmt_func(
	"GMT_Extract_Region",
	argtypes=[ctp.c_void_p, ctp.c_char_p, ctp.POINTER(ctp.c_double)],
	restype=ctp.c_int,
	)

	wesn = np.empty(4, dtype=np.float64)
	wesn_pointer = wesn.ctypes.data_as(ctp.POINTER(ctp.c_double))
	# The second argument to GMT_Extract_Region is a file pointer to a
	# PostScript file. It's only valid in classic mode. Use None to get a
	# NULL pointer instead.
	status = c_extract_region(self.session_pointer, None, wesn_pointer)
	if status != 0:
	raise GMTCLibError("Failed to extract region from current figure.")
	return wesn

	with Session() as lib:
	file_context = lib.virtualfile_from_data(check_kind="raster", data=grid)
	with contextlib.ExitStack() as stack:
	# shading using an xr.DataArray
	if kwargs.get("I") is not None and data_kind(kwargs["I"]) == "grid":
	shading_context = lib.virtualfile_from_data(
	check_kind="raster", data=kwargs["I"]
	)
	kwargs["I"] = stack.enter_context(shading_context)

	fname = stack.enter_context(file_context)
	lib.call_module(
	module="grdimage", args=build_arg_string(kwargs, infile=fname)
	)

Add Figure.tilemap to plot XYZ tile maps #2394

Add Figure.tilemap to plot XYZ tile maps #2394

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