Source code for

# Licensed under a 3-clause BSD style license - see LICENSE.rst
An extensible ASCII table reader and writer.

Classes to read DAOphot table format

:Copyright: Smithsonian Astrophysical Observatory (2011)
:Author: Tom Aldcroft (

import itertools as itt
import re
from collections import OrderedDict, defaultdict

import numpy as np

from . import core, fixedwidth
from .misc import first_false_index, first_true_index, groupmore

class DaophotHeader(core.BaseHeader):
    Read the header from a file produced by the IRAF DAOphot routine.

    comment = r"\s*#K"

    # Regex for extracting the format strings
    re_format = re.compile(r"%-?(\d+)\.?\d?[sdfg]")
    re_header_keyword = re.compile(
        r"[#]K" r"\s+ (?P<name> \w+)" r"\s* = (?P<stuff> .+) $", re.VERBOSE
    aperture_values = ()

    def __init__(self):

    def parse_col_defs(self, grouped_lines_dict):
        Parse a series of column definition lines like below.  There may be several
        such blocks in a single file (where continuation characters have already been
        #N ID    XCENTER   YCENTER   MAG         MERR          MSKY           NITER
        #U ##    pixels    pixels    magnitudes  magnitudes    counts         ##
        #F %-9d  %-10.3f   %-10.3f   %-12.3f     %-14.3f       %-15.7g        %-6d
        line_ids = ("#N", "#U", "#F")
        coldef_dict = defaultdict(list)

        # Function to strip identifier lines
        stripper = lambda s: s[2:].strip(" \\")
        for defblock in zip(*map(grouped_lines_dict.get, line_ids)):
            for key, line in zip(line_ids, map(stripper, defblock)):

        # Save the original columns so we can use it later to reconstruct the
        # original header for writing
            # Database contains multi-aperture data.
            # Autogen column names, units, formats from last row of column headers
            last_names, last_units, last_formats = list(
                zip(*map(coldef_dict.get, line_ids))
            N_multiline = len(
            for i in np.arange(1, N_multiline + 1).astype("U2"):
                # extra column names eg. RAPERT2, SUM2 etc...
                extended_names = list(map("".join, zip(last_names, itt.repeat(i))))
                if i == "1":  # Enumerate the names starting at 1
                    coldef_dict["#N"][-1] = extended_names

        # Get column widths from column format specifiers
        get_col_width = lambda s: int([0])
        col_widths = [
            [get_col_width(f) for f in formats] for formats in coldef_dict["#F"]
        # original data format might be shorter than 80 characters and filled with spaces
        row_widths = np.fromiter(map(sum, col_widths), int)
        row_short = Daophot.table_width - row_widths
        # fix last column widths
        for w, r in zip(col_widths, row_short):
            w[-1] += r

        self.col_widths = col_widths

        # merge the multi-line header data into single line data
        coldef_dict = {k: sum(v, []) for (k, v) in coldef_dict.items()}

        return coldef_dict

    def update_meta(self, lines, meta):
        Extract table-level keywords for DAOphot table.  These are indicated by
        a leading '#K ' prefix.
        table_meta = meta["table"]

        # self.lines = self.get_header_lines(lines)
        Nlines = len(self.lines)
        if Nlines > 0:
            # Group the header lines according to their line identifiers (#K,
            # #N, #U, #F or just # (spacer line)) function that grabs the line
            # identifier
            get_line_id = lambda s: s.split(None, 1)[0]

            # Group lines by the line identifier ('#N', '#U', '#F', '#K') and
            # capture line index
            gid, groups = zip(*groupmore(get_line_id, self.lines, range(Nlines)))

            # Groups of lines and their indices
            grouped_lines, gix = zip(*groups)

            # Dict of line groups keyed by line identifiers
            grouped_lines_dict = dict(zip(gid, grouped_lines))

            # Update the table_meta keywords if necessary
            if "#K" in grouped_lines_dict:
                keywords = OrderedDict(
                    map(self.extract_keyword_line, grouped_lines_dict["#K"])
                table_meta["keywords"] = keywords

            coldef_dict = self.parse_col_defs(grouped_lines_dict)

            line_ids = ("#N", "#U", "#F")
            for name, unit, fmt in zip(*map(coldef_dict.get, line_ids)):
                meta["cols"][name] = {"unit": unit, "format": fmt}

            self.meta = meta
            self.names = coldef_dict["#N"]

    def extract_keyword_line(self, line):
        Extract info from a header keyword line (#K)
        m = self.re_header_keyword.match(line)
        if m:
            vals ="stuff").strip().rsplit(None, 2)
            keyword_dict = {
                "units": vals[-2],
                "format": vals[-1],
                "value": (vals[0] if len(vals) > 2 else ""),
            return"name"), keyword_dict

    def get_cols(self, lines):
        Initialize the header Column objects from the table ``lines`` for a DAOphot
        header.  The DAOphot header is specialized so that we just copy the entire BaseHeader
        get_cols routine and modify as needed.

        lines : list
            List of table lines

        col : list
            List of table Columns

        if not self.names:
            raise core.InconsistentTableError("No column names found in DAOphot header")

        # Create the list of io.ascii column objects

        # Set unit and format as needed.
        coldefs = self.meta["cols"]
        for col in self.cols:
            unit, fmt = map(coldefs[].get, ("unit", "format"))
            if unit != "##":
                col.unit = unit
            if fmt != "##":
                col.format = fmt

        # Set column start and end positions.
        col_width = sum(self.col_widths, [])
        ends = np.cumsum(col_width)
        starts = ends - col_width
        for i, col in enumerate(self.cols):
            col.start, col.end = starts[i], ends[i]
            col.span = col.end - col.start
            if hasattr(col, "format"):
                if any(x in col.format for x in "fg"):
                    col.type = core.FloatType
                elif "d" in col.format:
                    col.type = core.IntType
                elif "s" in col.format:
                    col.type = core.StrType

        # INDEF is the missing value marker"INDEF", "0"))

class DaophotData(core.BaseData):
    splitter_class = fixedwidth.FixedWidthSplitter
    start_line = 0
    comment = r"\s*#"

    def __init__(self):
        self.is_multiline = False

    def get_data_lines(self, lines):
        # Special case for multiline daophot databases. Extract the aperture
        # values from the first multiline data block
        if self.is_multiline:
            # Grab the first column of the special block (aperture values) and
            # recreate the aperture description string
            aplist = next(zip(*map(str.split, self.first_block)))
            self.header.aperture_values = tuple(map(float, aplist))

        # Set to a slice of lines contain the data rows
        core.BaseData.get_data_lines(self, lines)

class DaophotInputter(core.ContinuationLinesInputter):
    continuation_char = "\\"
    multiline_char = "*"
    replace_char = " "
    re_multiline = re.compile(r"(#?)[^\\*#]*(\*?)(\\*) ?$")

    def search_multiline(self, lines, depth=150):
        Search lines for special continuation character to determine number of
        continued rows in a datablock.  For efficiency, depth gives the upper
        limit of lines to search.

        # The list of apertures given in the #K APERTURES keyword may not be
        # complete!!  This happens if the string description of the aperture
        # list is longer than the field width of the #K APERTURES field.  In
        # this case we have to figure out how many apertures there are based on
        # the file structure.

        comment, special, cont = zip(
            *( for line in lines[:depth])

        # Find first non-comment line
        data_start = first_false_index(comment)

        # No data in lines[:depth].  This may be because there is no data in
        # the file, or because the header is really huge.  If the latter,
        # increasing the search depth should help
        if data_start is None:
            return None, None, lines[:depth]

        header_lines = lines[:data_start]

        # Find first line ending on special row continuation character '*'
        # indexed relative to data_start
        first_special = first_true_index(special[data_start:depth])
        if first_special is None:  # no special lines
            return None, None, header_lines

        # last line ending on special '*', but not on line continue '/'
        last_special = first_false_index(special[data_start + first_special : depth])
        # index relative to first_special

        # if first_special is None: #no end of special lines within search
        # depth!  increase search depth return self.search_multiline( lines,
        # depth=2*depth )

        # indexing now relative to line[0]
        markers = np.cumsum([data_start, first_special, last_special])
        # multiline portion of first data block
        multiline_block = lines[markers[1] : markers[-1]]

        return markers, multiline_block, header_lines

    def process_lines(self, lines):
        markers, block, header = self.search_multiline(lines) = markers is not None = markers = block
        # set the header lines returned by the search as a attribute of the header = header

        if markers is not None:
            lines = lines[markers[0] :]

        continuation_char = self.continuation_char
        multiline_char = self.multiline_char
        replace_char = self.replace_char

        parts = []
        outlines = []
        for i, line in enumerate(lines):
            mo =
            if mo:
                comment, special, cont = mo.groups()
                if comment or cont:
                    line = line.replace(continuation_char, replace_char)
                if special:
                    line = line.replace(multiline_char, replace_char)
                if cont and not comment:
                if not cont:
                    parts = []
                raise core.InconsistentTableError(
                    f"multiline re could not match line {i}: {line}"

        return outlines

[docs]class Daophot(core.BaseReader): """ DAOphot format table. Example:: #K MERGERAD = INDEF scaleunit %-23.7g #K IRAF = NOAO/IRAFV2.10EXPORT version %-23s #K USER = davis name %-23s #K HOST = tucana computer %-23s # #N ID XCENTER YCENTER MAG MERR MSKY NITER \\ #U ## pixels pixels magnitudes magnitudes counts ## \\ #F %-9d %-10.3f %-10.3f %-12.3f %-14.3f %-15.7g %-6d # #N SHARPNESS CHI PIER PERROR \\ #U ## ## ## perrors \\ #F %-23.3f %-12.3f %-6d %-13s # 14 138.538 INDEF 15.461 0.003 34.85955 4 \\ -0.032 0.802 0 No_error The keywords defined in the #K records are available via the output table ``meta`` attribute:: >>> import os >>> from import ascii >>> filename = os.path.join(ascii.__path__[0], 'tests/data/daophot.dat') >>> data = >>> for name, keyword in data.meta['keywords'].items(): ... print(name, keyword['value'], keyword['units'], keyword['format']) ... MERGERAD INDEF scaleunit %-23.7g IRAF NOAO/IRAFV2.10EXPORT version %-23s USER name %-23s ... The unit and formats are available in the output table columns:: >>> for colname in data.colnames: ... col = data[colname] ... print(colname, col.unit, col.format) ... ID None %-9d XCENTER pixels %-10.3f YCENTER pixels %-10.3f ... Any column values of INDEF are interpreted as a missing value and will be masked out in the resultant table. In case of multi-aperture daophot files containing repeated entries for the last row of fields, extra unique column names will be created by suffixing corresponding field names with numbers starting from 2 to N (where N is the total number of apertures). For example, first aperture radius will be RAPERT and corresponding magnitude will be MAG, second aperture radius will be RAPERT2 and corresponding magnitude will be MAG2, third aperture radius will be RAPERT3 and corresponding magnitude will be MAG3, and so on. """ _format_name = "daophot" _io_registry_format_aliases = ["daophot"] _io_registry_can_write = False _description = "IRAF DAOphot format table" header_class = DaophotHeader data_class = DaophotData inputter_class = DaophotInputter table_width = 80 def __init__(self): core.BaseReader.__init__(self) # The inputter needs to know about the data (see DaophotInputter.process_lines) =
[docs] def write(self, table=None): raise NotImplementedError