"""
blockm - Block average (x,y,z) data tables by mean or median estimation.
"""
import pandas as pd
from pygmt.clib import Session
from pygmt.helpers import (
GMTTempFile,
build_arg_string,
fmt_docstring,
kwargs_to_strings,
use_alias,
)
def _blockm(block_method, table, outfile, **kwargs):
r"""
Block average (x,y,z) data tables by mean or median estimation.
Reads arbitrarily located (x,y,z) triples [or optionally weighted
quadruples (x,y,z,w)] from a table and writes to the output a mean or
median (depending on ``block_method``) position and value for every
non-empty block in a grid region defined by the ``region`` and ``spacing``
parameters.
Parameters
----------
block_method : str
Name of the GMT module to call. Must be "blockmean" or "blockmedian".
Returns
-------
output : pandas.DataFrame or None
Return type depends on whether the ``outfile`` parameter is set:
- :class:`pandas.DataFrame` table with (x, y, z) columns if ``outfile``
is not set
- None if ``outfile`` is set (filtered output will be stored in file
set by ``outfile``)
"""
with GMTTempFile(suffix=".csv") as tmpfile:
with Session() as lib:
# Choose how data will be passed into the module
table_context = lib.virtualfile_from_data(check_kind="vector", data=table)
# Run blockm* on data table
with table_context as infile:
if outfile is None:
outfile = tmpfile.name
arg_str = " ".join([infile, build_arg_string(kwargs), "->" + outfile])
lib.call_module(module=block_method, args=arg_str)
# Read temporary csv output to a pandas table
if outfile == tmpfile.name: # if user did not set outfile, return pd.DataFrame
try:
column_names = table.columns.to_list()
result = pd.read_csv(tmpfile.name, sep="\t", names=column_names)
except AttributeError: # 'str' object has no attribute 'columns'
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
return result
[docs]@fmt_docstring
@use_alias(
I="spacing",
R="region",
V="verbose",
a="aspatial",
f="coltypes",
r="registration",
)
@kwargs_to_strings(R="sequence")
def blockmean(table, outfile=None, **kwargs):
r"""
Block average (x,y,z) data tables by mean estimation.
Reads arbitrarily located (x,y,z) triples [or optionally weighted
quadruples (x,y,z,w)] from a table and writes to the output a mean
position and value for every non-empty block in a grid region defined by
the ``region`` and ``spacing`` parameters.
Full option list at :gmt-docs:`blockmean.html`
{aliases}
Parameters
----------
table : str or {table-like}
Pass in (x, y, z) or (longitude, latitude, elevation) values by
providing a file name to an ASCII data table, a 2D
{table-classes}.
{I}
region : str or list
*xmin/xmax/ymin/ymax*\[\ **+r**\][**+u**\ *unit*].
Specify the region of interest.
outfile : str
The file name for the output ASCII file.
{V}
{a}
{f}
{r}
Returns
-------
output : pandas.DataFrame or None
Return type depends on whether the ``outfile`` parameter is set:
- :class:`pandas.DataFrame` table with (x, y, z) columns if ``outfile``
is not set
- None if ``outfile`` is set (filtered output will be stored in file
set by ``outfile``)
"""
return _blockm(block_method="blockmean", table=table, outfile=outfile, **kwargs)