las.py

"""LAS File Reader

The main class defined here is LASReader, a class that reads a LAS file
and makes the data available as a Python object.
"""

# Copyright (c) 2011, 2014 Warren Weckesser
#
# Permission to use, copy, modify, and/or distribute this software for any
# purpose with or without fee is hereby granted, provided that the above
# copyright notice and this permission notice appear in all copies.
#
# THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES
# WITH REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF
# MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR
# ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES
# WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN
# ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF
# OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.

from __future__ import print_function

import re
import keyword

import numpy as np


def isidentifier(s):
    if s in keyword.kwlist:
        return False
    return re.match(r'^[a-z_][a-z0-9_]*$', s, re.I) is not None


def _convert_to_value(s):
    try:
        value = int(s)
    except ValueError:
        try:
            value = float(s)
        except ValueError:
            value = s
    return value


def _read_line(f, ignore_blank_lines=True):
    """Read a line from stdin, skipping blank lines and comments."""
    ignore = True
    while ignore:
        line = f.readline()
        sline = line.strip()
        ignore = sline.startswith('#') or (ignore_blank_lines and sline == '')
    return line


class LASError(Exception):
    pass


class LASItem(object):
    """This class is just a namespace, holding the attributes 'name',
    'units', 'data', 'value', and 'descr'.  'value' is the numerical
    value of 'data', if it has a numerical value (specifically, if
    int() or float() don't raise an exception when given the value
    of the 'data' attribute).

    A class method, from_line(cls, line), is provided to parse
    a line from a LAS file and create a LASItem instance.
    """
    def __init__(self, name, units='', data='', descr=''):
        self.name = name
        self.units = units
        self.data = data
        self.value = _convert_to_value(data)
        self.descr = descr

    def __str__(self):
        s = ("name='%s', units='%s', data='%s', descr='%s'" %
             (self.name, self.units, self.data, self.descr))
        return s

    def __repr__(self):
        s = str(self)
        return "LASItem(%s)" % s

    @classmethod
    def from_line(cls, line):
        first, descr = line.rsplit(':', 1)
        descr = descr.strip()
        name, mid = first.split('.', 1)
        name = name.strip()
        if mid.startswith(' '):
            # No units
            units = ''
            data = mid
        else:
            units_data = mid.split(None, 1)
            if len(units_data) == 1:
                units = units_data[0]
                data = ''
            else:
                units, data = units_data
        return LASItem(name=name, units=units, data=data.strip(),
                       descr=descr.strip())


def _read_wrapped_row(f, n):
    """Read a "row" of data from the Ascii section of a "wrapped" LAS file.

    `f` must be a file object opened for reading.
    `n` is the number of fields in the row.

    Returns the list of floats read from the file.
    """
    depth = float(f.readline().strip())
    values = [depth]
    while len(values) < n:
        new_values = [float(s) for s in f.readline().split()]
        values.extend(new_values)
    return values


def _read_wrapped_data(f, dt):
    data = []
    ncols = len(dt.names)
    while True:
        try:
            row = _read_wrapped_row(f, ncols)
        except Exception:
            break
        data.append(tuple(row))
    data = np.array(data, dtype=dt)
    return data


class LASSection(object):
    """Represents a "section" of a LAS file.

    A section is basically a collection of items, where each item has the
    attributes 'name', 'units', 'data' and 'descr'.

    Any item in the section whose name is a valid Python identifier is
    also attached to the object as an attribute.  For example, if `s` is a
    LASSection instance, and the corresponding section in the LAS file
    contained this line:

    FD   .K/M3               999.9999        :  Fluid Density

    then the item may be referred to as `s.FD` (in addition to the longer
    `s.items['FD']`).

    Attributes
    ----------
    items : dict
        The keys are the item names, and the values are LASItem instances.
    names : list
        List of item names, in the order they were read from the LAS file.

    """
    def __init__(self):
        # Note: In Python 2.7, 'items' could be an OrderedDict, and
        # then 'names' would not be necessary--one could use items.keys().
        self.items = dict()
        self.names = []

    def add_item(self, item):
        # XXX If the name is already used, this modifies item.name in place.
        original_name = item.name
        dupcount = 0
        while item.name in self.items:
            # Duplicate name.
            dupcount += 1
            item.name = original_name + str(dupcount)

        self.items[item.name] = item
        self.names.append(item.name)
        if isidentifier(item.name) and not hasattr(self, item.name):
            setattr(self, item.name, item)

    def display(self):
        for name in self.names:
            item = self.items[name]
            namestr = name
            if item.units != '':
                namestr = namestr + (" (%s)" % item.units)
            print("%-16s %-30s [%s]" % (namestr, "'" + item.data + "'",
                                        item.descr))


class LASReader(object):
    """The LASReader class holds data from a LAS file.

    This reader only handles LAS 2.0 files (as far as I know).

    Constructor
    -----------
    LASReader(f, null_subs=None)

    f : file object or string
        If f is a file object, it must be opened for reading.
        If f is a string, it must be the filename of a LAS file.
        In that case, the file will be opened and read.

    Attributes for LAS Sections
    ---------------------------
    version : LASSection instance
        This LASSection holds the items from the '~V' section.

    well : LASSection instance
        This LASSection holds the items from the '~W' section.

    curves : LASection instance
        This LASSection holds the items from the '~C' section.

    parameters : LASSection instance
        This LASSection holds the items from the '~P' section.

    other : str
        Holds the contents of the '~O' section as a single string.

    data : numpy 1D structured array
        The numerical data from the '~A' section.  The data type
        of the array is constructed from the items in the '~C'
        section.

    Other attributes
    ----------------
    data2d : numpy 2D array of floats
        The numerical data from the '~A' section, as a 2D array.
        This is a view of the same data as in the `data` attribute.

    wrap : bool
        True if the LAS file was wrapped. (More specifically, this
        attribute is True if the data field of the item with the
        name 'WRAP' in the '~V' section has the value 'YES'.)

    vers : str
        The LAS version. (More specifically, the value of the data
        field of the item with the name 'VERS' in the '~V' section).

    null : float or None
        The numerical value of the 'NULL' item in the '~W' section.
        The value will be None if the 'NULL' item was missing.

    null_subs : float or None
        The value given in the constructor, to be used as the
        replacement value of each occurrence of `null_value` in
        the log data.  The value will be None (and no substitution
        will be done) if the `null_subs` argument is not given to
        the constructor.

    start : float, or None
        Numerical value of the 'STRT' item from the '~W' section.
        The value will be None if 'STRT' was not given in the file.

    start_units : str
        Units of the 'STRT' item from the '~W' section.
        The value will be None if 'STRT' was not given in the file.

    stop : float
        Numerical value of the 'STOP' item from the '~W' section.
        The value will be None if 'STOP' was not given in the file.

    stop_units : str
        Units of the 'STOP' item from the '~W' section.
        The value will be None if 'STOP' was not given in the file.

    step : float
        Numerical value of the 'STEP' item from the '~W' section.
        The value will be None if 'STEP' was not given in the file.

    step_units : str
        Units of the 'STEP' item from the '~W' section.
        The value will be None if 'STEP' was not given in the file.

    """

    def __init__(self, f, null_subs=None):
        """f can be a filename (str) or a file object.

        If 'null_subs' is not None, its value replaces any values in the data
        that matches the NULL value specified in the Version section of the LAS
        file.
        """
        self.null = None
        self.null_subs = null_subs
        self.start = None
        self.start_units = None
        self.stop = None
        self.stop_units = None
        self.step = None
        self.step_units = None

        self.version = LASSection()
        self.well = LASSection()
        self.curves = LASSection()
        self.parameters = LASSection()
        self.other = ''
        self.data = None

        self._read_las(f)

        self.data2d = self.data.view(float).reshape(-1, len(self.curves.items))
        if null_subs is not None:
            self.data2d[self.data2d == self.null] = null_subs

    def _read_las(self, f):
        """Read a LAS file.

        Returns a dictionary with keys 'V', 'W', 'C', 'P', 'O' and 'A',
        corresponding to the sections of a LAS file.  The values associated
        with keys 'V', 'W', 'C' and 'P' will be lists of Item instances.  The
        value associated with the 'O' key is a list of strings.  The value
        associated with the 'A' key is a numpy structured array containing the
        log data.  The field names of the array are the mnemonics from the
        Curve section of the file.
        """
        opened_here = False
        try:
            string_type = basestring
        except NameError:
            string_type = str
        if isinstance(f, string_type):
            opened_here = True
            f = open(f, 'r')

        self.wrap = False

        ignore_blank_lines = True
        current_section = None
        current_section_label = ''
        line = _read_line(f, ignore_blank_lines)
        line_lstrip = line.lstrip(' ')
        while not line_lstrip.startswith('~A'):
            if line_lstrip.startswith('~'):
                if len(line_lstrip) < 2:
                    raise LASError("Missing section character after '~'.")
                current_section_label = line_lstrip[1:2]
                other = False
                if current_section_label == 'V':
                    current_section = self.version
                    ignore_blank_lines = True
                elif current_section_label == 'W':
                    current_section = self.well
                    ignore_blank_lines = True
                elif current_section_label == 'C':
                    current_section = self.curves
                    ignore_blank_lines = True
                elif current_section_label == 'P':
                    current_section = self.parameters
                    ignore_blank_lines = True
                elif current_section_label == 'O':
                    current_section = self.other
                    ignore_blank_lines = False
                    other = True
                else:
                    raise LASError("Unknown section '%s'" % line)
            elif current_section is None:
                raise LASError("Missing first section.")
            else:
                if other:
                    # The 'Other' section is just lines of text, so we
                    # assemble them into a single string.
                    self.other += line
                    current_section = self.other
                else:
                    # Parse the line into a LASItem and add it to the
                    # current section.
                    m = LASItem.from_line(line_lstrip)
                    current_section.add_item(m)
                    # Check for the required items whose values we'll
                    # store as attributes of the LASReader instance.
                    if current_section == self.version:
                        if m.name == 'WRAP':
                            if m.data.strip() == 'YES':
                                self.wrap = True
                        if m.name == 'VERS':
                            self.vers = m.data.strip()
                    if current_section == self.well:
                        if m.name == 'NULL':
                            self.null = float(m.data)
                        elif m.name == 'STRT':
                            self.start = float(m.data)
                            self.start_units = m.units
                        elif m.name == 'STOP':
                            self.stop = float(m.data)
                            self.stop_units = m.units
                        elif m.name == 'STEP':
                            self.step = float(m.data)
                            self.step_units = m.units
            line = _read_line(f, ignore_blank_lines)
            line_lstrip = line.lstrip(' ')

        # Finished reading the header--all that is left is the numerical
        # data that follows the '~A' line.  We'll construct a structured
        # data type, and, if the data is not wrapped, use numpy.loadtext
        # to read the data into an array.  For wrapped rows, we use the
        # function _read_wrapped() defined elsewhere in this module.
        # The data type is determined by the items from the '~Curves' section.
        dt = np.dtype([(name, float) for name in self.curves.names])
        if self.wrap:
            a = _read_wrapped_data(f, dt)
        else:
            a = np.loadtxt(f, dtype=dt)
        self.data = a

        if opened_here:
            f.close()