"""
Functions for input and output of grids in less common formats.
"""
import numpy as np
import xarray as xr
[docs]def load_surfer(fname, dtype="float64"):
"""
Read data from a Surfer ASCII grid file.
This function reads a Surfer grid file, masks any NaNs in the data,
and outputs a :class:`xarray.DataArray` that contains easting and northing
coordinates, data values, and associated file metadata.
Surfer is a contouring, griding and surface mapping software
from GoldenSoftware. The names and logos for Surfer and Golden
Software are registered trademarks of Golden Software, Inc.
http://www.goldensoftware.com/products/surfer
Parameters
----------
fname : str or file-like object
Name or path of the Surfer grid file or an open file (or file-like)
object.
dtype : str or numpy.dtype
The type of variable used for the data. Default is ``float64``. Use
``float32`` if the data are large and precision is not an issue.
Returns
----------
data : :class:`xarray.DataArray`
A 2D grid with the data.
"""
# Surfer ASCII grid structure
# DSAA Surfer ASCII GRD ID
# nCols nRows number of columns and rows
# xMin xMax X min max
# yMin yMax Y min max
# zMin zMax Z min max
# z11 z21 z31 ... List of Z values
# Only open a file if given a path instead of a file-like object
ispath = not hasattr(fname, "readline")
if ispath:
input_file = open(fname, "r")
else:
input_file = fname
try:
grid_id, shape, region, data_range = _read_surfer_header(input_file)
field = np.loadtxt(input_file, dtype=dtype)
nans = field >= 1.70141e38
if np.any(nans):
field = np.ma.masked_where(nans, field)
_check_surfer_integrity(field, shape, data_range)
attrs = {"gridID": grid_id}
if ispath:
attrs["file"] = fname
dims = ("northing", "easting")
coords = {
"northing": np.linspace(*region[2:], shape[0]),
"easting": np.linspace(*region[:2], shape[1]),
}
data = xr.DataArray(field, coords=coords, dims=dims, attrs=attrs)
finally:
if ispath:
input_file.close()
return data
def _read_surfer_header(input_file):
"""
Parse the header record of the grid file.
The header contains information on the grid shape, region, and the minimum
and maximum data values.
Parameters
----------
input_file : file-like object
An open file to read from.
Returns
-------
grid_id : str
The ID of the Surfer ASCII grid.
shape : tuple = (n_northing, n_easting)
The number of grid points in the northing and easting dimension,
respectively.
region : tuple = (west, east, south, north)
The grid region.
data_range : list = [min, max]
The minimum and maximum data values.
"""
# DSAA is a Surfer ASCII GRD ID
grid_id = input_file.readline().strip()
# Read the grid shape (n_northing, n_easting)
shape = tuple(int(i.strip()) for i in input_file.readline().split())
# Our x points North, so the first thing we read north-south.
south, north = [float(i.strip()) for i in input_file.readline().split()]
west, east = [float(i.strip()) for i in input_file.readline().split()]
region = (west, east, south, north)
# The min and max of the data values (used for validation)
data_range = [float(i.strip()) for i in input_file.readline().split()]
return grid_id, shape, region, data_range
def _check_surfer_integrity(field, shape, data_range):
"""
Check that the grid matches the information from the header.
"""
if field.shape != shape:
raise IOError(
"Grid shape {} doesn't match shape read from header {}.".format(
field.shape, shape
)
)
field_range = [field.min(), field.max()]
if not np.allclose(field_range, data_range):
raise IOError(
"Grid data range {} doesn't match range read from header {}.".format(
field_range, data_range
)
)