CFGeom Tutorial


Installation on Windows

CFGeom relies on Shapely, and the author has had trouble installing Shapely for Python 3. You could try this to install Shapely:

  1. Download the Shapely wheel for your version of Python from Christoph Gohlke’s Unofficial Windows Binaries.
  2. In a command window, browse to your downloads folder and install Shapely using pip, e.g., pip install Shapely‑1.6.4.post1‑cp27‑cp27m‑win32.whl
  3. Open a Python prompt and verify that import shapely.geometry executes without errors.

For the author, this works for Python 2 but not Python 3. Using Anaconda for Python 3 and then conda install shapely did work for the author.

Once Shapely is installed, install CFGeom with:

  1. pip install cfgeom

Installation on other operating systems

  1. pip install cfgeom

Create a geometry container with line geometries

In CFGeom, a GeometryContainer object contains one or more geometries. Each geometry contains one or more parts. Using a polygon with a hole as an example, the outer ring of the polygon would be one part, and the hole would be a second part. It is the geometry part which stores a geometry’s x, y, and z coordinates. Use the following code to create a geometry container with a couple of line geometries.

from cfgeom import Part, Geometry, GeometryContainer

# Geometries are comprised of one or more parts
# The part holds the node coordinates
x1 = [10, 5, 0]
y1 = [0, 5, 0]
part1 = Part(x1, y1)
# Set the geometry type when you create the geometry
line1 = Geometry('line', part1)  # or 'point' or 'polygon'

# Make another line, this time with z values
x2 = [9, 5, 1]
y2 = [1, 4, 1]
z2 = [1, 1, 1]
line2 = Geometry('line', Part(x2, y2, z2))

# In NetCDF-CF, geometries belong to a geometry container
geometries = [line1, line2]
line_container = GeometryContainer(geometries)

print(len(line_container.geoms))  # 2

Create a polygon with holes

We’ll reuse the x and y coordinates from the line example to create a polygon. A polygon is similar to a line, except that the first and last nodes are assumed to be connected. Some polygon conventions require the first and last node to be spatially coincident. This would mean adding a fourth x and y value to each list, identifical to the first value in the list. The CF conventions allow this but do not require it, and so CFGeom does not require this either.

# For polygons, parts can be created as holes
exterior = Part(x1, y1)  # i.e., the part that isn't a hole
hole = Part(x2, y2, is_hole=True)
parts = [exterior, hole]  # The hole comes second
polygon = Geometry('polygon', parts)
polygon_container = GeometryContainer(polygon)

part = polygon_container.geoms[0].parts[1]
print(part.is_hole)  # True
print(part.x)  # [9, 5, 1]

Write and read netCDF

Thus far we’ve been working purely in Python. Next let’s try reading and writing geometries to a netCDF file.

Note that CF does require nodes for exterior polygon rings to be listed in anticlockwise (or counterclockwise in American English), and holes to be in clockwise order. Even though the nodes we added for the hole earlier were in anticlockwise order, they are reversed to be placed in clockwise order when writing to a netCDF file, as demonstrated below.

from cfgeom import read_netcdf

path_to_netcdf_file = ''
# The next line creates a geometry container named 'geometry_container' by
# default, along with related node variables.  The use_vlen flag indicates
# whether we want to use netCDF classic (False) or netCDF enhanced (True).
# Note that the enhanced approach uses variable length arrays to store the
# node coordinates, which is not covered under CF 1.8.
polygon_container.to_netcdf(path_to_netcdf_file, use_vlen=False)
# There could be several geometry containers in a file
containers = read_netcdf(path_to_netcdf_file)
# Get the container named 'geometry_container'
container_from_nc = containers['geometry_container']['container']

# Nodes for polygon holes are oriented clockwise when writing to netCDF
print(container_from_nc.geoms[0].parts[1].x)  # [1.0, 5.0, 9.0]

In this example, we just write the geometries without a data variable. CF requires a data variable to be in the file if you have geometries, and you can add a data variable or read an existing data variable using the netCDF4 package, which is outside the scope of this tutorial. If you already had a data variable in the file, then to be CF compliant you would just need something like the following code. NOTE: this code is just example code. It will not work unless you have an existing ‘’ that already has a streamflow variable in it.

from netCDF4 import Dataset

with Dataset('', 'a') as nc:
   # The data variable is named 'streamflow'
   nc.variables['streamflow'].geometry = 'geometry_container'

Want to inspect outside of Python? You could try Panoply.

Write and read Shapely

Shapely is one other most commonly used packages for working with geometries in Python. CFGeom includes utiilties to convert between CF geometries and Shapely geometries. Below we continue with the lines from prior examples.

from cfgeom import read_shapely

shapely_lines = line_container.to_shapely()

print(len(shapely_lines))  # 2
print(shapely_lines[0])  # LINESTRING (10 0, 5 5, 0 0)

container_from_shapely = read_shapely(shapely_lines)

print(container_from_shapely.geom_type)  # line
print(container_from_shapely.geoms[0].parts[0].x)  # [10.0, 5.0, 0.0]

Want to write your own converter? Pull requests are welcome!

What about shapefiles

Dealing with shapefile attributes and coordinate systems is currently beyond our scope, although it would be really cool if a shapefile to netCDF-CF converter was implemented! Still, using fiona, one could at least read and write the shapes from a shapefile.

See the fiona docs for installation instructions. Once you’ve got fiona installed, you could use code like this to read and write shapes in shapefiles.

import os
from shutil import copyfile

import fiona
from shapely.geometry import mapping, shape
from netCDF4 import Dataset

from cfgeom import read_shapely, read_netcdf

# Assume this is a line shapefile with COMID and GNIS_NAME attributes
ORIGINAL_SHAPEFILE = 'some/path/input_geometry/flowlines.shp'
# Assume this netCDF file has a streamflow variable and no geometries (yet)
# The output files this script will create
OUT_NETCDF_FILE = 'some/path/'
OUT_SHAPEFILE = 'some/path/output_geometry/result.shp'

# Read geometries from shapefile
with, 'r') as source:
    schema = source.schema
    in_shapes = [shape(f['geometry']) for f in source]

    # We'll cheat by caching some attributes and the coordinate system
    comids = [f['properties']['COMID'] for f in source]
    names = [f['properties']['GNIS_NAME'] for f in source]
    crs =

container_from_shapely = read_shapely(in_shapes)

geom_type = container_from_shapely.geom_type
count = str(len(container_from_shapely.geoms))
print('Found ' + count + ' ' + geom_type + ' geometries in shapefile')

# Append geometries to netCDF. Make a copy so we don't mess up the original.
with Dataset(OUT_NETCDF_FILE, 'a') as nc:
    nc.variables['streamflow'].geometry = 'geometry_container'

# Read geometries from netCDF
container_from_nc = read_netcdf(OUT_NETCDF_FILE)['geometry_container']['container']
shapely_lines = container_from_nc.to_shapely()

count = str(len(shapely_lines))
print('Created ' + count + ' shapely lines from netCDF')

# Write geometries to shapefile
directory = os.path.dirname(OUT_SHAPEFILE)
if not os.path.exists(directory):
with, 'w', 'ESRI Shapefile', schema, crs=crs) as shp:
    for i, line in enumerate(shapely_lines):
            'geometry': mapping(line),
            'properties': {'COMID': comids[i], 'GNIS_NAME': names[i]},