Source code for pygmt.src.sphdistance

sphdistance - Create Voronoi distance, node,
or natural nearest-neighbor grid on a sphere
from pygmt.clib import Session
from pygmt.exceptions import GMTInvalidInput
from pygmt.helpers import (
from import load_dataarray

__doctest_skip__ = ["sphdistance"]

[docs]@fmt_docstring @use_alias( C="single_form", D="duplicate", E="quantity", G="outgrid", I="spacing", L="unit", N="node_table", Q="voronoi", R="region", V="verbose", ) @kwargs_to_strings(I="sequence", R="sequence") def sphdistance(data=None, x=None, y=None, **kwargs): r""" Create Voronoi distance, node, or natural nearest-neighbor grid on a sphere. Reads a table containing *lon, lat* columns and performs the construction of Voronoi polygons. These polygons are then processed to calculate the nearest distance to each node of the lattice and written to the specified grid. Full option list at :gmt-docs:`sphdistance.html` {aliases} Parameters ---------- data : str or {table-like} Pass in (x, y) or (longitude, latitude) values by providing a file name to an ASCII data table, a 2-D {table-classes}. x/y : 1-D arrays Arrays of x and y coordinates. outgrid : str or None The name of the output netCDF file with extension .nc to store the grid in. {spacing} {region} {verbose} single_form : bool For large data sets you can save some memory (at the expense of more processing) by only storing one form of location coordinates (geographic or Cartesian 3-D vectors) at any given time, translating from one form to the other when necessary [Default keeps both arrays in memory]. Not applicable with ``voronoi``. duplicate : bool Used to skip duplicate points since the algorithm cannot handle them. [Default assumes there are no duplicates]. quantity : str **d**\|\ **n**\|\ **z**\ [*dist*]. Specify the quantity that should be assigned to the grid nodes [Default is **d**]: - **d** - compute distances to the nearest data point - **n** - assign the ID numbers of the Voronoi polygons that each grid node is inside - **z** - assign all nodes inside the polygon the z-value of the center node for a natural nearest-neighbor grid. Optionally, append the resampling interval along Voronoi arcs in spherical degrees. unit : str Specify the unit used for distance calculations. Choose among **d** (spherical degrees), **e** (meters), **f** (feet), **k** (kilometers), **M** (miles), **n** (nautical miles), or **u** (survey feet). node_table : str Read the information pertaining to each Voronoi polygon (the unique node lon, lat and polygon area) from a separate file [Default acquires this information from the ASCII segment headers of the output file]. Required if binary input via `voronoi` is used. voronoi : str Append the name of a file with pre-calculated Voronoi polygons [Default performs the Voronoi construction on input data]. Returns ------- ret: xarray.DataArray or None Return type depends on whether the ``outgrid`` parameter is set: - :class:`xarray.DataArray` if ``outgrid`` is not set - None if ``outgrid`` is set (grid output will be stored in file set by ``outgrid``) Example ------- >>> import numpy as np >>> import pygmt >>> # Create an array of longitude/latitude coordinates >>> coords_list = [[85.5, 22.3], [82.3, 22.6], [85.8, 22.4], [86.5, 23.3]] >>> coords_array = np.array(coords_list) >>> # Perform a calculation of the distance to >>> # each point from Voronoi polygons >>> grid = pygmt.sphdistance( ... data=coords_array, spacing=[1, 2], region=[82, 87, 22, 24] ... ) """ if kwargs.get("I") is None or kwargs.get("R") is None: raise GMTInvalidInput("Both 'region' and 'spacing' must be specified.") with GMTTempFile(suffix=".nc") as tmpfile: with Session() as lib: file_context = lib.virtualfile_from_data( check_kind="vector", data=data, x=x, y=y ) with file_context as infile: if (outgrid := kwargs.get("G")) is None: kwargs["G"] = outgrid = # output to tmpfile lib.call_module( module="sphdistance", args=build_arg_string(kwargs, infile=infile) ) return load_dataarray(outgrid) if outgrid == else None