"""
grdvolume - Calculate grid volume and area constrained by a contour.
"""
import pandas as pd
from pygmt.clib import Session
from pygmt.helpers import (
GMTTempFile,
build_arg_string,
fmt_docstring,
kwargs_to_strings,
use_alias,
validate_output_table_type,
)
__doctest_skip__ = ["grdvolume"]
[docs]
@fmt_docstring
@use_alias(
C="contour",
R="region",
S="unit",
V="verbose",
)
@kwargs_to_strings(C="sequence", R="sequence")
def grdvolume(grid, output_type="pandas", outfile=None, **kwargs):
r"""
Determine the volume between the surface of a grid and a plane.
Read a 2-D grid file and calculate the volume contained below the surface
and above the plane specified by the given contour (or zero if not given)
and return the contour, area, volume, and maximum mean height
(volume/area). Alternatively, a range of contours can be specified to
return the volume and area inside the contour for all contour values.
Full option list at :gmt-docs:`grdvolume.html`
{aliases}
Parameters
----------
{grid}
output_type : str
Determine the format the output data will be returned in [Default is
``pandas``]:
- ``numpy`` - :class:`numpy.ndarray`
- ``pandas``- :class:`pandas.DataFrame`
- ``file`` - ASCII file (requires ``outfile``)
outfile : str
The file name for the output ASCII file.
contour : str, float, or list
*cval*\|\ *low/high/delta*\|\ **r**\ *low/high*\|\ **r**\ *cval*.
Find area, volume and mean height (volume/area) inside and above the
*cval* contour. Alternatively, search using all contours from *low* to
*high* in steps of *delta*. [Default returns area, volume and mean
height of the entire grid]. The area is measured in the plane of the
contour. Adding the **r** prefix computes the volume below the grid
surface and above the planes defined by *low* and *high*, or below
*cval* and grid's minimum. Note that this is an *outside* volume
whilst the other forms compute an *inside* (below the surface) area
volume. Use this form to compute for example the volume of water
between two contours. If no *contour* is given then there is no contour
and the entire grid area, volume and the mean height is returned and
*cval* will be reported as 0.
{region}
{verbose}
Returns
-------
ret : pandas.DataFrame or numpy.ndarray or None
Return type depends on ``outfile`` and ``output_type``:
- None if ``outfile`` is set (output will be stored in file set by
``outfile``)
- :class:`pandas.DataFrame` or :class:`numpy.ndarray` if ``outfile``
is not set (depends on ``output_type`` [Default is
:class:`pandas.DataFrame`])
Example
-------
>>> import pygmt
>>> # Load a grid of @earth_relief_30m data, with a longitude range of
>>> # 10° E to 30° E, and a latitude range of 15° N to 25° N
>>> grid = pygmt.datasets.load_earth_relief(
... resolution="30m", region=[10, 30, 15, 25]
... )
>>> # Create a pandas dataframe that contains the contour, area, volume,
>>> # and maximum mean height above the plane specified by the given
>>> # contour and below the surface; set the minimum contour z-value to
>>> # 200, the maximum to 400, and the interval to 50.
>>> output_dataframe = pygmt.grdvolume(
... grid=grid, contour=[200, 400, 50], output_type="pandas"
... )
>>> print(output_dataframe)
0 1 2 3
0 200 2.323600e+12 8.523815e+14 366.836554
1 250 2.275864e+12 7.371655e+14 323.905736
2 300 2.166707e+12 6.258570e+14 288.851699
3 350 2.019284e+12 5.207732e+14 257.899955
4 400 1.870441e+12 4.236191e+14 226.480847
"""
output_type = validate_output_table_type(output_type, outfile=outfile)
with GMTTempFile() as tmpfile:
with Session() as lib:
file_context = lib.virtualfile_from_data(check_kind="raster", data=grid)
with file_context as infile:
if outfile is None:
outfile = tmpfile.name
lib.call_module(
module="grdvolume",
args=build_arg_string(kwargs, infile=infile, outfile=outfile),
)
# Read temporary csv output to a pandas table
if outfile == tmpfile.name: # if user did not set outfile, return pd.DataFrame
result = pd.read_csv(tmpfile.name, sep="\t", header=None, comment=">")
elif outfile != tmpfile.name: # return None if outfile set, output in outfile
result = None
if output_type == "numpy":
result = result.to_numpy()
return result