Source code for pygmt.src.select

"""
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