landlab.io.netcdf.read

Read data from a NetCDF file into a RasterModelGrid.

Read netcdf

read_netcdf(nc_file[, grid, name, ...])

Create a RasterModelGrid from a netcdf file.
read_netcdf(nc_file, grid=None, name=None, just_grid=False, halo=0, nodata_value=-9999.0)[source]

Create a RasterModelGrid from a netcdf file.

Create a new RasterModelGrid from the netcdf file, nc_file. If the netcdf file also contains data, add that data to the grid’s fields. To create a new grid without any associated data from the netcdf file, set the just_grid keyword to True.

A halo can be added with the keyword halo.

If you want the fields to be added to an existing grid, it can be passed to the keyword argument grid.

Parameters:

  • nc_file (str) – Name of a netcdf file.

  • grid (grid , optional) – Adds data to an existing grid instead of creating a new one.

  • name (str, optional) – Add only fields with NetCDF variable name to the grid. Default is to add all NetCDF varibles to the grid.

  • just_grid (boolean, optional) – Create a new grid but don’t add value data.

  • halo (integer, optional) – Adds outer border of depth halo to the grid.

  • nodata_value (float, optional) – Value that indicates an invalid value. Default is -9999.

Returns:

A newly-created RasterModelGrid.

Return type:

RasterModelGrid

Examples

Import read_netcdf and the path to an example netcdf file included with landlab.

>>> from landlab.io.netcdf import read_netcdf

Create a new grid from the netcdf file. The example grid is a uniform rectilinear grid with 4 rows and 3 columns of nodes with unit spacing. The data file also contains data defined at the nodes for the grid for a variable called, surface__elevation.

>>> grid = read_netcdf("test-netcdf4.nc")  
>>> grid.shape == (4, 3)  
True
>>> grid.dy, grid.dx  
(1.0, 1.0)
>>> list(grid.at_node.keys())  
['surface__elevation']
>>> grid.at_node["surface__elevation"]  
array([  0.,   1.,   2.,   3.,   4.,   5.,   6.,   7.,   8.,   9.,  10.,
        11.])

read_netcdf will try to determine the format of the netcdf file. For example, the same call will also work for netcdf3-formatted files.

>>> grid = read_netcdf("test-netcdf3-64bit.nc")  
>>> grid.shape == (4, 3)  
True
>>> grid.dy, grid.dx  
(1.0, 1.0)

A more complicated example might add data with a halo to an existing grid. Note that the lower left corner must be specified correctly for the data and the grid to align correctly.

>>> from landlab import RasterModelGrid
>>> grid = RasterModelGrid((6, 5), xy_of_lower_left=(-1.0, -1.0))  
>>> grid = read_netcdf(
...     "test-netcdf4.nc",
...     grid=grid,
...     halo=1,
...     nodata_value=-1,
... )  
>>> grid.at_node["surface__elevation"].reshape(grid.shape)  
array([[ -1.,  -1.,  -1.,  -1.,  -1.],
       [ -1.,   0.,   1.,   2.,  -1.],
       [ -1.,   3.,   4.,   5.,  -1.],
       [ -1.,   6.,   7.,   8.,  -1.],
       [ -1.,   9.,  10.,  11.,  -1.],
       [ -1.,  -1.,  -1.,  -1.,  -1.]])