"""
select - Select data table subsets based on multiple spatial criteria.
"""
import pandas as pd
from pygmt.clib import Session
from pygmt.helpers import (
GMTTempFile,
build_arg_string,
fmt_docstring,
kwargs_to_strings,
use_alias,
)
[docs]@fmt_docstring
@use_alias(
A="area_thresh",
# D="resolution",
# G="gridmask",
I="reverse",
J="projection",
# N="mask",
R="region",
V="verbose",
Z="z_subregion",
b="binary",
d="nodata",
e="find",
f="coltypes",
g="gap",
h="header",
i="incols",
o="outcols",
r="registration",
s="skiprows",
w="wrap",
)
@kwargs_to_strings(R="sequence", i="sequence_comma", o="sequence_comma")
def select(data=None, outfile=None, **kwargs):
r"""
Select data table subsets based on multiple spatial criteria.
This is a filter that reads (x, y) or (longitude, latitude) positions from
the first 2 columns of *data* and uses a combination of 1-7 criteria to
pass or reject the records. Records can be selected based on whether or not
they are:
1. inside a rectangular region (**region** [and **projection**])
2. within *dist* km of any point in *pointfile*
3. within *dist* km of any line in *linefile*
4. inside one of the polygons in the *polygonfile*
5. inside geographical features (based on coastlines)
6. has z-values within a given range, or
7. inside bins of a grid mask whose nodes are non-zero
The sense of the tests can be reversed for each of these 7 criteria by
using the **reverse** option.
Full option list at :gmt-docs:`gmtselect.html`
{aliases}
Parameters
----------
data : str or {table-like}
Pass in either a file name to an ASCII data table, a 2D
{table-classes}.
outfile : str
The file name for the output ASCII file.
{A}
reverse : str
[**cflrsz**].
Reverses the sense of the test for each of the criteria specified:
- **c** select records NOT inside any point's circle of influence.
- **f** select records NOT inside any of the polygons.
- **g** will pass records inside the cells with z equal zero of the
grid mask in **gridmask**.
- **l** select records NOT within the specified distance of any line.
- **r** select records NOT inside the specified rectangular region.
- **s** select records NOT considered inside as specified by **mask**
(and **area_thresh**, **resolution**).
- **z** select records NOT within the range specified by
**z_subregion**.
{J}
{R}
{V}
z_subregion : str
*min*\ [/*max*]\ [**+a**]\ [**+c**\ *col*]\ [**+i**].
Pass all records whose 3rd column (*z*; *col* = 2) lies within the
given range or is NaN (use **skiprows** to skip NaN records). If *max*
is omitted then we test if *z* equals *min* instead. This means
equality within 5 ULPs (unit of least precision;
http://en.wikipedia.org/wiki/Unit_in_the_last_place). Input file must
have at least three columns. To indicate no limit on min or max,
specify a hyphen (-). If your 3rd column is absolute time then remember
to supply ``coltypes="2T"``. To specify another column, append
**+c**\ *col*, and to specify several tests just repeat the
**z_subregion** option as many times as you have columns to test.
**Note**: When more than one **z_subregion** option is given then the
``reverse="z"`` option cannot be used. In the case of multiple tests
you may use these modifiers as well: **+a** passes any record that
passes at least one of your *z* tests [Default is all tests must pass],
and **+i** reverses the tests to pass record with *z* value NOT in the
given range. Finally, if **+c** is not used then it is automatically
incremented for each new **z_subregion** option, starting with 2.
{b}
{d}
{e}
{f}
{g}
{h}
{i}
{o}
{r}
{s}
{w}
Returns
-------
output : pandas.DataFrame or None
Return type depends on whether the ``outfile`` parameter is set:
- :class:`pandas.DataFrame` table 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=data)
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="gmtselect", 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 = data.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