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Shapefile masking #5470

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3b15cd2
Working draft of shapefile masking
acchamber Sep 1, 2023
2ef0d15
Version of shapefile masking with tests and ready for preliminary review
acchamber Sep 5, 2023
6d36d05
Updated tests with proper paths and skip_tests decorator
acchamber Sep 6, 2023
befb1e5
Merge branch 'main' into shapefile_masking
acchamber Sep 7, 2023
6c2ef62
Merge branch 'main' into shapefile_masking
acchamber Oct 2, 2023
7b28fcd
Merge branch 'main' into shapefile_masking
acchamber Nov 8, 2023
6decedf
fixed some paths and removed broken code
acchamber Nov 8, 2023
d3b91d1
Merge branch 'SciTools:main' into shapefile_masking
acchamber Nov 9, 2023
d168f24
Added more tests and split into integration and unit tests. Testing w…
acchamber Nov 9, 2023
4947ffb
Merge branch 'shapefile_masking' of https://github.com/acchamber/iris…
acchamber Nov 9, 2023
1d05f63
responces to comments on utils.py for shapefile masking
acchamber Nov 20, 2023
ca363cc
tests actually pass now
acchamber Nov 20, 2023
23f3640
Moved tests to correct locations and strted changes on _shapefiles.py
acchamber Nov 20, 2023
57af617
some changes to _shapefiles to match review
acchamber Nov 20, 2023
5ba0ebc
added setUp cases to tests
acchamber Nov 20, 2023
cce3f9b
moved test names to lower_case and added acknoledgment
acchamber Nov 20, 2023
3ec7cc3
removed seperate guess_bounds function
acchamber Nov 20, 2023
7baab21
updated structure to properly call coord names/coords when optimal
acchamber Nov 22, 2023
c0aa728
sphnix improvements to docstring
acchamber Nov 22, 2023
44fe0cd
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Nov 22, 2023
28fcd44
commited dask map_blocks approach and some test improvements
acchamber Nov 23, 2023
87cc28e
replaced bounds rebasing via modulus with vectorized version
acchamber Nov 23, 2023
92d869f
Dask chunk control and some docstrings
acchamber Nov 24, 2023
4b38611
Merge branch 'shapefile_masking' of https://github.com/acchamber/iris…
acchamber Nov 27, 2023
befceeb
reverted behaviour of modulus function to ASCEND and switcher argumen…
acchamber Nov 27, 2023
e391e43
edied tests to work with flipped argument order
acchamber Nov 29, 2023
8b0e869
Improved optimisation by reading shapely docs properly and just using…
acchamber Jan 10, 2024
194aabf
Docstring updates and a 4d integration test
acchamber Feb 6, 2024
9521c2e
Merge branch 'main' into shapefile_masking
trexfeathers Feb 6, 2024
e89634b
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Feb 6, 2024
162bd45
Update lib/iris/_shapefiles.py
acchamber Feb 6, 2024
07ab745
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Feb 6, 2024
e8a23b7
improving readability from martin
acchamber Feb 6, 2024
ea5be9c
Merge branch 'shapefile_masking' of https://github.com/acchamber/iris…
acchamber Feb 6, 2024
64278ca
removed dask.delayed call
acchamber Feb 6, 2024
a46d7c9
Update lib/iris/_shapefiles.py
acchamber Feb 6, 2024
eca46c0
Update lib/iris/_shapefiles.py
acchamber Feb 6, 2024
061b76b
Update lib/iris/util.py
acchamber Feb 6, 2024
cc6016b
Added warning for possible mismatch of mask/cube coords
acchamber Feb 7, 2024
5e7d799
test for new warning
acchamber Feb 7, 2024
440f049
added test
acchamber Feb 7, 2024
3c13e1b
Update lib/iris/_shapefiles.py
acchamber Feb 7, 2024
1e1d711
Added licenses
acchamber Feb 7, 2024
22e2cf7
Merge branch 'shapefile_masking' of https://github.com/acchamber/iris…
acchamber Feb 7, 2024
9cb96b9
fixed doctest failures in example
acchamber Feb 7, 2024
deb5ff9
Improved test coverage
acchamber Feb 7, 2024
6eaa36b
fixed doctest
acchamber Feb 7, 2024
3b7384f
doctest again
acchamber Feb 7, 2024
a0aec74
Docstring tidy up.
trexfeathers Feb 7, 2024
e13e757
Merge pull request #1 from trexfeathers/docstring_tidy
acchamber Feb 7, 2024
b76dabd
fixed prime meridian bug
acchamber Feb 9, 2024
ca380ed
Update lib/iris/_shapefiles.py
acchamber Feb 9, 2024
0518a40
Merge branch 'main' into shapefile_masking
acchamber Feb 9, 2024
404474f
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Feb 9, 2024
b924795
Added first draft of user guide page
acchamber Feb 12, 2024
4ab753a
Add What's New entry.
trexfeathers Feb 13, 2024
84a8212
Merge pull request #2 from trexfeathers/shapefile_whatsnew
acchamber Feb 13, 2024
bf3c720
Merge branch 'SciTools:main' into shapefile_masking
acchamber Feb 13, 2024
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24 changes: 24 additions & 0 deletions docs/src/userguide/plotting_examples/masking_brazil_plot.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,24 @@
"""Global cube masked to Brazil and plotted with quickplot."""
import cartopy.io.shapereader as shpreader
import matplotlib.pyplot as plt

import iris
import iris.quickplot as qplt
from iris.util import mask_cube_from_shapefile

country_shp_reader = shpreader.Reader(
shpreader.natural_earth(
resolution="110m", category="cultural", name="admin_0_countries"
)
)
brazil_shp = [
country.geometry
for country in country_shp_reader.records()
if "Brazil" in country.attributes["NAME_LONG"]
][0]

cube = iris.load_cube(iris.sample_data_path("air_temp.pp"))
brazil_cube = mask_cube_from_shapefile(cube, brazil_shp)

qplt.pcolormesh(brazil_cube)
plt.show()
37 changes: 36 additions & 1 deletion docs/src/userguide/subsetting_a_cube.rst
Original file line number Diff line number Diff line change
Expand Up @@ -5,7 +5,8 @@ Subsetting a Cube
=================

The :doc:`loading_iris_cubes` section of the user guide showed how to load data into multidimensional Iris cubes.
However it is often necessary to reduce the dimensionality of a cube down to something more appropriate and/or manageable.
However it is often necessary to reduce the dimensionality of a cube down to something more appropriate and/or manageable,
or only examine and analyse a subset of data in a dimension.

Iris provides several ways of reducing both the amount of data and/or the number of dimensions in your cube depending on the circumstance.
In all cases **the subset of a valid cube is itself a valid cube**.
Expand Down Expand Up @@ -329,6 +330,36 @@ on bounds can be done in the following way::
The above example constrains to cells where either the upper or lower bound occur
after 1st January 2008.

Cube Masking
--------------

.. _masking-from-shapefile:

Masking from a shapefile
^^^^^^^^^^^^^^^^^^^^^^^^

Often we want to perform so kind of analysis over a complex geographical feature - only over land points or sea points:
or over a continent, a country, a river watershed or administrative region. These geographical features can often be described by shapefiles.
Shapefiles are a file format first developed for GIS software in the 1990s, and now `Natural Earth`_ maintain a large freely usable database of shapefiles of many geographical and poltical divisions,
accessible via cartopy. Users may also provide their own custom shapefiles.

These shapefiles can be used to mask an iris cube, so that any data outside the bounds of the shapefile is hidden from further analysis or plotting.

First, we load the correct shapefile from NaturalEarth via the `Cartopy`_ instructions. Here we get one for Brazil.
The `.geometry` attribute of the records in the reader contain the shapely polygon we're interested in - once we have those we just need to provide them to
the :class:`iris.util.mask_cube_from_shapefile` function. Once plotted, we can see that only our area of interest remains in the data.


.. plot:: userguide/plotting_examples/masking_brazil_plot.py
:include-source:

We can see that the dimensions of the cube haven't changed - the plot is still global. But only the data over Brazil is plotted - the rest is masked.

.. note::
While Iris will try to dynamically adjust the shapefile to mask cubes of different projections, it can struggle with rotated pole projections and cubes with Meridians not at 0°
Converting your Cube's coordinate system may help if you get a fully masked cube from this function.


Cube Iteration
--------------
It is not possible to directly iterate over an Iris cube. That is, you cannot use code such as
Expand Down Expand Up @@ -440,3 +471,7 @@ Similarly, Iris cubes have indexing capability::
# Get the second element of the first dimension and all of the second dimension
# in reverse, by steps of two.
print(cube[1, ::-2])


.. _Cartopy: https://scitools.org.uk/cartopy/docs/latest/tutorials/using_the_shapereader.html#id1
.. _Natural Earth: https://www.naturalearthdata.com/
12 changes: 11 additions & 1 deletion docs/src/whatsnew/latest.rst
Original file line number Diff line number Diff line change
Expand Up @@ -67,6 +67,12 @@ This document explains the changes made to Iris for this release
NetCDF chunking with the use of the :data:`iris.fileformats.netcdf.loader.CHUNK_CONTROL`
context manager. (:pull:`5588`)

#. `@acchamber`_ and `@trexfeathers`_ (reviewer) added
:func:`iris.util.mask_cube_from_shapefile`. This builds on the original work
of `@ckmo`_, `@david-bentley`_, `@jmendesmetoffice`_, `@evyve`_ and
`@pelson`_ for the UK Met Office **ASCEND** library. See
:ref:`masking-from-shapefile` for documentation. (:pull:`5470`)


🐛 Bugs Fixed
=============
Expand Down Expand Up @@ -110,7 +116,7 @@ This document explains the changes made to Iris for this release
#. `@bouweandela`_ changed :func:`iris.coords.Coord.cell` so it does not realize
all coordinate data and only loads a single cell instead. (:pull:`5693`)

#. `@rcomer`_ and `@trexfeathers`_ (reviewer) modified
#. `@rcomer`_ and `@trexfeathers`_ (reviewer) modified
:func:`~iris.analysis.stats.pearsonr` so it preserves lazy data in all cases
and also runs a little faster. (:pull:`5638`)

Expand Down Expand Up @@ -242,6 +248,10 @@ This document explains the changes made to Iris for this release
.. _@scottrobinson02: https://github.com/scottrobinson02
.. _@acchamber: https://github.com/acchamber
.. _@fazledyn-or: https://github.com/fazledyn-or
.. _@ckmo: https://github.com/ckmo
.. _@david-bentley: https://github.com/david-bentley
.. _@jmendesmetoffice: https://github.com/jmendesmetoffice
.. _@evyve: https://github.com/evyve


.. comment
Expand Down
243 changes: 243 additions & 0 deletions lib/iris/_shapefiles.py
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Original file line number Diff line number Diff line change
@@ -0,0 +1,243 @@
# Copyright Iris contributors
#
# This file is part of Iris and is released under the BSD license.
# See LICENSE in the root of the repository for full licensing details.

# Much of this code is originally based off the ASCEND library, developed in
# the Met Office by Chris Kent, Emilie Vanvyve, David Bentley, Joana Mendes
# many thanks to them. Converted to iris by Alex Chamberlain-Clay


from itertools import product
import warnings

import numpy as np
import shapely
import shapely.errors
import shapely.geometry as sgeom
import shapely.ops

from iris.exceptions import IrisDefaultingWarning, IrisUserWarning


def create_shapefile_mask(
geometry,
cube,
minimum_weight=0.0,
):
"""Make a mask for a cube from a shape.

Get the mask of the intersection between the
given shapely geometry and cube with x/y DimCoords.
Can take a minimum weight and evaluate area overlaps instead

Parameters
----------
geometry : :class:`shapely.Geometry`
cube : :class:`iris.cube.Cube`
A :class:`~iris.cube.Cube` which has 1d x and y coordinates
minimum_weight : float, default 0.0
A float between 0 and 1 determining what % of a cell
a shape must cover for the cell to remain unmasked.
eg: 0.1 means that at least 10% of the shape overlaps the cell
to be unmasked.
Requires geometry to be a Polygon or MultiPolygon
Defaults to 0.0 (eg only test intersection)

Returns
-------
:class:`np.array`
An array of the shape of the x & y coordinates of the cube, with points
to mask equal to True

"""
from iris.cube import Cube, CubeList

try:
msg = "Geometry is not a valid Shapely object"
if not shapely.is_valid(geometry):
raise TypeError(msg)
except Exception:
raise TypeError(msg)
if not isinstance(cube, Cube):
if isinstance(cube, CubeList):
msg = "Received CubeList object rather than Cube - \
to mask a CubeList iterate over each Cube"
raise TypeError(msg)
else:
msg = "Received non-Cube object where a Cube is expected"
raise TypeError(msg)
if minimum_weight > 0.0 and isinstance(
geometry,
(
sgeom.Point,
sgeom.LineString,
sgeom.LinearRing,
sgeom.MultiPoint,
sgeom.MultiLineString,
),
):
minimum_weight = 0.0
warnings.warn(
"""Shape is of invalid type for minimum weight masking,
must use a Polygon rather than Line shape.\n
Masking based off intersection instead. """,
category=IrisDefaultingWarning,
)

# prepare 2D cube
y_name, x_name = _cube_primary_xy_coord_names(cube)
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cube_2d = cube.slices([y_name, x_name]).next()
for coord in cube_2d.dim_coords:
if not coord.has_bounds():
coord.guess_bounds()
trans_geo = _transform_coord_system(geometry, cube_2d)

y_coord, x_coord = [cube_2d.coord(n) for n in (y_name, x_name)]
x_bounds = _get_mod_rebased_coord_bounds(x_coord)
y_bounds = _get_mod_rebased_coord_bounds(y_coord)
# prepare array for dark
box_template = [
sgeom.box(x[0], y[0], x[1], y[1]) for x, y in product(x_bounds, y_bounds)
]
# shapely can do lazy evaluation of intersections if it's given a list of grid box shapes
# delayed lets us do it in parallel
intersect_template = shapely.intersects(trans_geo, box_template)
# we want areas not under shapefile to be True (to mask)
intersect_template = np.invert(intersect_template)
# now calc area overlaps if doing weights and adjust mask
if minimum_weight > 0.0:
intersections = np.array(box_template)[~intersect_template]
intersect_template[~intersect_template] = [
trans_geo.intersection(box).area / box.area <= minimum_weight
for box in intersections
]
mask_template = np.reshape(intersect_template, cube_2d.shape[::-1]).T
return mask_template


def _transform_coord_system(geometry, cube, geometry_system=None):
"""Project the shape onto another coordinate system.

Parameters
----------
geometry: :class:`shapely.Geometry`
cube: :class:`iris.cube.Cube`
:class:`~iris.cube.Cube` with the coord_system to be projected to and
a x coordinate
geometry_system: :class:`iris.coord_systems`, optional
A :class:`~iris.coord_systems` object describing
the coord_system of the shapefile. Defaults to None,
which is treated as GeogCS

Returns
-------
:class:`shapely.Geometry`
A transformed copy of the provided :class:`shapely.Geometry`

"""
y_name, x_name = _cube_primary_xy_coord_names(cube)
import iris.analysis.cartography

DEFAULT_CS = iris.coord_systems.GeogCS(
iris.analysis.cartography.DEFAULT_SPHERICAL_EARTH_RADIUS
)
target_system = cube.coord_system()
if not target_system:
warnings.warn(
"Cube has no coord_system; using default GeogCS lat/lon",
category=IrisDefaultingWarning,
)
target_system = DEFAULT_CS
if geometry_system is None:
geometry_system = DEFAULT_CS
target_proj = target_system.as_cartopy_projection()
source_proj = geometry_system.as_cartopy_projection()

trans_geometry = target_proj.project_geometry(geometry, source_proj)
# A GeogCS in iris can be either -180 to 180 or 0 to 360. If cube is 0-360, shift geom to match
if (
isinstance(target_system, iris.coord_systems.GeogCS)
and cube.coord(x_name).points[-1] > 180
):
# chop geom at 0 degree line very finely then transform
prime_meridian_line = shapely.LineString([(0, 90), (0, -90)])
trans_geometry = trans_geometry.difference(prime_meridian_line.buffer(0.00001))
trans_geometry = shapely.transform(trans_geometry, _trans_func)

if (not isinstance(target_system, iris.coord_systems.GeogCS)) and cube.coord(
x_name
).points[-1] > 180:
# this may lead to incorrect masking or not depending on projection type so warn user
warnings.warn(
"""Cube has x-coordinates over 180E and a non-standard projection type.\n
This may lead to incorrect masking. \n
If the result is not as expected, you might want to transform the x coordinate points of your cube to -180-180 """,
category=IrisUserWarning,
)
return trans_geometry


def _trans_func(geometry):
"""Pocket function for transforming the x coord of a geometry from -180 to 180 to 0-360."""
for point in geometry:
if point[0] < 0:
point[0] = 360 - np.abs(point[0])
return geometry


def _cube_primary_xy_coord_names(cube):
"""Return the primary latitude and longitude coordinate names, or long names, from a cube.

Parameters
----------
cube : :class:`iris.cube.Cube`

Returns
-------
tuple of str
The names of the primary latitude and longitude coordinates

"""
latc = (
cube.coords(axis="y", dim_coords=True)[0]
if cube.coords(axis="y", dim_coords=True)
else -1
)
lonc = (
cube.coords(axis="x", dim_coords=True)[0]
if cube.coords(axis="x", dim_coords=True)
else -1
)

if -1 in (latc, lonc):
msg = "Error retrieving 1d xy coordinates in cube: {!r}"
raise ValueError(msg.format(cube))

latitude = latc.name()
longitude = lonc.name()
return latitude, longitude


def _get_mod_rebased_coord_bounds(coord):
"""Take in a coord and returns a array of the bounds of that coord rebased to the modulus.

Parameters
----------
coord : :class:`iris.coords.Coord`
An Iris coordinate with a modulus

Returns
-------
:class:`np.array`
A 1d Numpy array of [start,end] pairs for bounds of the coord

"""
modulus = coord.units.modulus
# Force realisation (rather than core_bounds) - more efficient for the
# repeated indexing happening downstream.
result = np.array(coord.bounds)
if modulus:
result[result < 0.0] = (np.abs(result[result < 0.0]) % modulus) * -1
result[np.isclose(result, modulus, 1e-10)] = 0.0
return result
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