pygmt.clib.Session.virtualfile_in

Session.virtualfile_in(check_kind=None, data=None, x=None, y=None, z=None, required=True, mincols=2)[source]

Store any data inside a virtual file.

This convenience function automatically detects the kind of data passed into it, and produces a virtualfile that can be passed into GMT later on.

Parameters:

  • check_kind (str or None) – Used to validate the type of data that can be passed in. Choose from ‘raster’, ‘vector’, or None. Default is None (no validation).

  • data (default: None) – Any raster or vector data format. This could be a file name or path, a raster grid, a vector matrix/arrays, or other supported data input.

  • x/y/z (1-D arrays or None) – x, y, and z columns as numpy arrays.

  • required (bool) – Set to True when ‘data’ or (‘x’ and ‘y’) is required. Set to False when dealing with optional virtual files. Default is True.

  • mincols (default: 2) – Number of minimum required columns. Default is 2 (i.e. require x and y columns).

Returns:

file_context (contextlib._GeneratorContextManager) – The virtual file stored inside a context manager. Access the file name of this virtualfile using with file_context as fname: ....

Examples

>>> from pygmt.helpers import GMTTempFile
>>> import xarray as xr
>>> data = xr.Dataset(
...     coords=dict(index=[0, 1, 2]),
...     data_vars=dict(
...         x=("index", [9, 8, 7]),
...         y=("index", [6, 5, 4]),
...         z=("index", [3, 2, 1]),
...     ),
... )
>>> with Session() as ses:
...     with ses.virtualfile_in(check_kind="vector", data=data) as fin:
...         # Send the output to a file so that we can read it
...         with GMTTempFile() as fout:
...             ses.call_module("info", [fin, f"->{fout.name}"])
...             print(fout.read().strip())
<vector memory>: N = 3 <7/9> <4/6> <1/3>