# Licensed under a 3-clause BSD style license - see LICENSE.rst """ Facilities for diffing two FITS files. Includes objects for diffing entire FITS files, individual HDUs, FITS headers, or just FITS data. Used to implement the fitsdiff program. """ import fnmatch import glob import io import operator import os import os.path import textwrap from collections import defaultdict from inspect import signature from itertools import islice import numpy as np from astropy import __version__ from .card import Card, BLANK_CARD from .header import Header # HDUList is used in one of the doctests from .hdu.hdulist import fitsopen, HDUList # pylint: disable=W0611 from .hdu.table import _TableLikeHDU from astropy.utils.diff import (report_diff_values, fixed_width_indent, where_not_allclose, diff_values) from astropy.utils.misc import NOT_OVERWRITING_MSG __all__ = ['FITSDiff', 'HDUDiff', 'HeaderDiff', 'ImageDataDiff', 'RawDataDiff', 'TableDataDiff'] # Column attributes of interest for comparison _COL_ATTRS = [('unit', 'units'), ('null', 'null values'), ('bscale', 'bscales'), ('bzero', 'bzeros'), ('disp', 'display formats'), ('dim', 'dimensions')] class _BaseDiff: """ Base class for all FITS diff objects. When instantiating a FITS diff object, the first two arguments are always the two objects to diff (two FITS files, two FITS headers, etc.). Instantiating a ``_BaseDiff`` also causes the diff itself to be executed. The returned ``_BaseDiff`` instance has a number of attribute that describe the results of the diff operation. The most basic attribute, present on all ``_BaseDiff`` instances, is ``.identical`` which is `True` if the two objects being compared are identical according to the diff method for objects of that type. """ def __init__(self, a, b): """ The ``_BaseDiff`` class does not implement a ``_diff`` method and should not be instantiated directly. Instead instantiate the appropriate subclass of ``_BaseDiff`` for the objects being compared (for example, use `HeaderDiff` to compare two `Header` objects. """ self.a = a self.b = b # For internal use in report output self._fileobj = None self._indent = 0 self._diff() def __bool__(self): """ A ``_BaseDiff`` object acts as `True` in a boolean context if the two objects compared are identical. Otherwise it acts as `False`. """ return not self.identical @classmethod def fromdiff(cls, other, a, b): """ Returns a new Diff object of a specific subclass from an existing diff object, passing on the values for any arguments they share in common (such as ignore_keywords). For example:: >>> from astropy.io import fits >>> hdul1, hdul2 = fits.HDUList(), fits.HDUList() >>> headera, headerb = fits.Header(), fits.Header() >>> fd = fits.FITSDiff(hdul1, hdul2, ignore_keywords=['*']) >>> hd = fits.HeaderDiff.fromdiff(fd, headera, headerb) >>> list(hd.ignore_keywords) ['*'] """ sig = signature(cls.__init__) # The first 3 arguments of any Diff initializer are self, a, and b. kwargs = {} for arg in list(sig.parameters.keys())[3:]: if hasattr(other, arg): kwargs[arg] = getattr(other, arg) return cls(a, b, **kwargs) @property def identical(self): """ `True` if all the ``.diff_*`` attributes on this diff instance are empty, implying that no differences were found. Any subclass of ``_BaseDiff`` must have at least one ``.diff_*`` attribute, which contains a non-empty value if and only if some difference was found between the two objects being compared. """ return not any(getattr(self, attr) for attr in self.__dict__ if attr.startswith('diff_')) def report(self, fileobj=None, indent=0, overwrite=False): """ Generates a text report on the differences (if any) between two objects, and either returns it as a string or writes it to a file-like object. Parameters ---------- fileobj : file-like, string, or None, optional If `None`, this method returns the report as a string. Otherwise it returns `None` and writes the report to the given file-like object (which must have a ``.write()`` method at a minimum), or to a new file at the path specified. indent : int The number of 4 space tabs to indent the report. overwrite : bool, optional If ``True``, overwrite the output file if it exists. Raises an ``OSError`` if ``False`` and the output file exists. Default is ``False``. Returns ------- report : str or None """ return_string = False filepath = None if isinstance(fileobj, str): if os.path.exists(fileobj) and not overwrite: raise OSError(NOT_OVERWRITING_MSG.format(fileobj)) else: filepath = fileobj fileobj = open(filepath, 'w') elif fileobj is None: fileobj = io.StringIO() return_string = True self._fileobj = fileobj self._indent = indent # This is used internally by _writeln try: self._report() finally: if filepath: fileobj.close() if return_string: return fileobj.getvalue() def _writeln(self, text): self._fileobj.write(fixed_width_indent(text, self._indent) + '\n') def _diff(self): raise NotImplementedError def _report(self): raise NotImplementedError class FITSDiff(_BaseDiff): """Diff two FITS files by filename, or two `HDUList` objects. `FITSDiff` objects have the following diff attributes: - ``diff_hdu_count``: If the FITS files being compared have different numbers of HDUs, this contains a 2-tuple of the number of HDUs in each file. - ``diff_hdus``: If any HDUs with the same index are different, this contains a list of 2-tuples of the HDU index and the `HDUDiff` object representing the differences between the two HDUs. """ def __init__(self, a, b, ignore_hdus=[], ignore_keywords=[], ignore_comments=[], ignore_fields=[], numdiffs=10, rtol=0.0, atol=0.0, ignore_blanks=True, ignore_blank_cards=True): """ Parameters ---------- a : str or `HDUList` The filename of a FITS file on disk, or an `HDUList` object. b : str or `HDUList` The filename of a FITS file on disk, or an `HDUList` object to compare to the first file. ignore_hdus : sequence, optional HDU names to ignore when comparing two FITS files or HDU lists; the presence of these HDUs and their contents are ignored. Wildcard strings may also be included in the list. ignore_keywords : sequence, optional Header keywords to ignore when comparing two headers; the presence of these keywords and their values are ignored. Wildcard strings may also be included in the list. ignore_comments : sequence, optional A list of header keywords whose comments should be ignored in the comparison. May contain wildcard strings as with ignore_keywords. ignore_fields : sequence, optional The (case-insensitive) names of any table columns to ignore if any table data is to be compared. numdiffs : int, optional The number of pixel/table values to output when reporting HDU data differences. Though the count of differences is the same either way, this allows controlling the number of different values that are kept in memory or output. If a negative value is given, then numdiffs is treated as unlimited (default: 10). rtol : float, optional The relative difference to allow when comparing two float values either in header values, image arrays, or table columns (default: 0.0). Values which satisfy the expression .. math:: \\left| a - b \\right| > \\text{atol} + \\text{rtol} \\cdot \\left| b \\right| are considered to be different. The underlying function used for comparison is `numpy.allclose`. .. versionadded:: 2.0 atol : float, optional The allowed absolute difference. See also ``rtol`` parameter. .. versionadded:: 2.0 ignore_blanks : bool, optional Ignore extra whitespace at the end of string values either in headers or data. Extra leading whitespace is not ignored (default: True). ignore_blank_cards : bool, optional Ignore all cards that are blank, i.e. they only contain whitespace (default: True). """ if isinstance(a, (str, os.PathLike)): try: a = fitsopen(a) except Exception as exc: raise OSError("error opening file a ({}): {}: {}".format( a, exc.__class__.__name__, exc.args[0])) close_a = True else: close_a = False if isinstance(b, (str, os.PathLike)): try: b = fitsopen(b) except Exception as exc: raise OSError("error opening file b ({}): {}: {}".format( b, exc.__class__.__name__, exc.args[0])) close_b = True else: close_b = False # Normalize keywords/fields to ignore to upper case self.ignore_hdus = set(k.upper() for k in ignore_hdus) self.ignore_keywords = set(k.upper() for k in ignore_keywords) self.ignore_comments = set(k.upper() for k in ignore_comments) self.ignore_fields = set(k.upper() for k in ignore_fields) self.numdiffs = numdiffs self.rtol = rtol self.atol = atol self.ignore_blanks = ignore_blanks self.ignore_blank_cards = ignore_blank_cards # Some hdu names may be pattern wildcards. Find them. self.ignore_hdu_patterns = set() for name in list(self.ignore_hdus): if name != '*' and glob.has_magic(name): self.ignore_hdus.remove(name) self.ignore_hdu_patterns.add(name) self.diff_hdu_count = () self.diff_hdus = [] try: super().__init__(a, b) finally: if close_a: a.close() if close_b: b.close() def _diff(self): if len(self.a) != len(self.b): self.diff_hdu_count = (len(self.a), len(self.b)) # Record filenames for use later in _report self.filenamea = self.a.filename() if not self.filenamea: self.filenamea = f'<{self.a.__class__.__name__} object at {id(self.a):#x}>' self.filenameb = self.b.filename() if not self.filenameb: self.filenameb = f'<{self.b.__class__.__name__} object at {id(self.b):#x}>' if self.ignore_hdus: self.a = HDUList([h for h in self.a if h.name not in self.ignore_hdus]) self.b = HDUList([h for h in self.b if h.name not in self.ignore_hdus]) if self.ignore_hdu_patterns: a_names = [hdu.name for hdu in self.a] b_names = [hdu.name for hdu in self.b] for pattern in self.ignore_hdu_patterns: self.a = HDUList([h for h in self.a if h.name not in fnmatch.filter( a_names, pattern)]) self.b = HDUList([h for h in self.b if h.name not in fnmatch.filter( b_names, pattern)]) # For now, just compare the extensions one by one in order. # Might allow some more sophisticated types of diffing later. # TODO: Somehow or another simplify the passing around of diff # options--this will become important as the number of options grows for idx in range(min(len(self.a), len(self.b))): hdu_diff = HDUDiff.fromdiff(self, self.a[idx], self.b[idx]) if not hdu_diff.identical: if self.a[idx].name == self.b[idx].name and self.a[idx].ver == self.b[idx].ver: self.diff_hdus.append((idx, hdu_diff, self.a[idx].name, self.a[idx].ver)) else: self.diff_hdus.append((idx, hdu_diff, "", self.a[idx].ver)) def _report(self): wrapper = textwrap.TextWrapper(initial_indent=' ', subsequent_indent=' ') self._fileobj.write('\n') self._writeln(f' fitsdiff: {__version__}') self._writeln(f' a: {self.filenamea}\n b: {self.filenameb}') if self.ignore_hdus: ignore_hdus = ' '.join(sorted(self.ignore_hdus)) self._writeln(f' HDU(s) not to be compared:\n{wrapper.fill(ignore_hdus)}') if self.ignore_hdu_patterns: ignore_hdu_patterns = ' '.join(sorted(self.ignore_hdu_patterns)) self._writeln(' HDU(s) not to be compared:\n{}' .format(wrapper.fill(ignore_hdu_patterns))) if self.ignore_keywords: ignore_keywords = ' '.join(sorted(self.ignore_keywords)) self._writeln(' Keyword(s) not to be compared:\n{}' .format(wrapper.fill(ignore_keywords))) if self.ignore_comments: ignore_comments = ' '.join(sorted(self.ignore_comments)) self._writeln(' Keyword(s) whose comments are not to be compared' ':\n{}'.format(wrapper.fill(ignore_comments))) if self.ignore_fields: ignore_fields = ' '.join(sorted(self.ignore_fields)) self._writeln(' Table column(s) not to be compared:\n{}' .format(wrapper.fill(ignore_fields))) self._writeln(' Maximum number of different data values to be ' 'reported: {}'.format(self.numdiffs)) self._writeln(' Relative tolerance: {}, Absolute tolerance: {}' .format(self.rtol, self.atol)) if self.diff_hdu_count: self._fileobj.write('\n') self._writeln('Files contain different numbers of HDUs:') self._writeln(f' a: {self.diff_hdu_count[0]}') self._writeln(f' b: {self.diff_hdu_count[1]}') if not self.diff_hdus: self._writeln('No differences found between common HDUs.') return elif not self.diff_hdus: self._fileobj.write('\n') self._writeln('No differences found.') return for idx, hdu_diff, extname, extver in self.diff_hdus: # print out the extension heading if idx == 0: self._fileobj.write('\n') self._writeln('Primary HDU:') else: self._fileobj.write('\n') if extname: self._writeln(f'Extension HDU {idx} ({extname}, {extver}):') else: self._writeln(f'Extension HDU {idx}:') hdu_diff.report(self._fileobj, indent=self._indent + 1) class HDUDiff(_BaseDiff): """ Diff two HDU objects, including their headers and their data (but only if both HDUs contain the same type of data (image, table, or unknown). `HDUDiff` objects have the following diff attributes: - ``diff_extnames``: If the two HDUs have different EXTNAME values, this contains a 2-tuple of the different extension names. - ``diff_extvers``: If the two HDUS have different EXTVER values, this contains a 2-tuple of the different extension versions. - ``diff_extlevels``: If the two HDUs have different EXTLEVEL values, this contains a 2-tuple of the different extension levels. - ``diff_extension_types``: If the two HDUs have different XTENSION values, this contains a 2-tuple of the different extension types. - ``diff_headers``: Contains a `HeaderDiff` object for the headers of the two HDUs. This will always contain an object--it may be determined whether the headers are different through ``diff_headers.identical``. - ``diff_data``: Contains either a `ImageDataDiff`, `TableDataDiff`, or `RawDataDiff` as appropriate for the data in the HDUs, and only if the two HDUs have non-empty data of the same type (`RawDataDiff` is used for HDUs containing non-empty data of an indeterminate type). """ def __init__(self, a, b, ignore_keywords=[], ignore_comments=[], ignore_fields=[], numdiffs=10, rtol=0.0, atol=0.0, ignore_blanks=True, ignore_blank_cards=True): """ Parameters ---------- a : BaseHDU An HDU object. b : BaseHDU An HDU object to compare to the first HDU object. ignore_keywords : sequence, optional Header keywords to ignore when comparing two headers; the presence of these keywords and their values are ignored. Wildcard strings may also be included in the list. ignore_comments : sequence, optional A list of header keywords whose comments should be ignored in the comparison. May contain wildcard strings as with ignore_keywords. ignore_fields : sequence, optional The (case-insensitive) names of any table columns to ignore if any table data is to be compared. numdiffs : int, optional The number of pixel/table values to output when reporting HDU data differences. Though the count of differences is the same either way, this allows controlling the number of different values that are kept in memory or output. If a negative value is given, then numdiffs is treated as unlimited (default: 10). rtol : float, optional The relative difference to allow when comparing two float values either in header values, image arrays, or table columns (default: 0.0). Values which satisfy the expression .. math:: \\left| a - b \\right| > \\text{atol} + \\text{rtol} \\cdot \\left| b \\right| are considered to be different. The underlying function used for comparison is `numpy.allclose`. .. versionadded:: 2.0 atol : float, optional The allowed absolute difference. See also ``rtol`` parameter. .. versionadded:: 2.0 ignore_blanks : bool, optional Ignore extra whitespace at the end of string values either in headers or data. Extra leading whitespace is not ignored (default: True). ignore_blank_cards : bool, optional Ignore all cards that are blank, i.e. they only contain whitespace (default: True). """ self.ignore_keywords = {k.upper() for k in ignore_keywords} self.ignore_comments = {k.upper() for k in ignore_comments} self.ignore_fields = {k.upper() for k in ignore_fields} self.rtol = rtol self.atol = atol self.numdiffs = numdiffs self.ignore_blanks = ignore_blanks self.ignore_blank_cards = ignore_blank_cards self.diff_extnames = () self.diff_extvers = () self.diff_extlevels = () self.diff_extension_types = () self.diff_headers = None self.diff_data = None super().__init__(a, b) def _diff(self): if self.a.name != self.b.name: self.diff_extnames = (self.a.name, self.b.name) if self.a.ver != self.b.ver: self.diff_extvers = (self.a.ver, self.b.ver) if self.a.level != self.b.level: self.diff_extlevels = (self.a.level, self.b.level) if self.a.header.get('XTENSION') != self.b.header.get('XTENSION'): self.diff_extension_types = (self.a.header.get('XTENSION'), self.b.header.get('XTENSION')) self.diff_headers = HeaderDiff.fromdiff(self, self.a.header.copy(), self.b.header.copy()) if self.a.data is None or self.b.data is None: # TODO: Perhaps have some means of marking this case pass elif self.a.is_image and self.b.is_image: self.diff_data = ImageDataDiff.fromdiff(self, self.a.data, self.b.data) # Clean up references to (possibly) memmapped arrays so they can # be closed by .close() self.diff_data.a = None self.diff_data.b = None elif (isinstance(self.a, _TableLikeHDU) and isinstance(self.b, _TableLikeHDU)): # TODO: Replace this if/when _BaseHDU grows a .is_table property self.diff_data = TableDataDiff.fromdiff(self, self.a.data, self.b.data) # Clean up references to (possibly) memmapped arrays so they can # be closed by .close() self.diff_data.a = None self.diff_data.b = None elif not self.diff_extension_types: # Don't diff the data for unequal extension types that are not # recognized image or table types self.diff_data = RawDataDiff.fromdiff(self, self.a.data, self.b.data) # Clean up references to (possibly) memmapped arrays so they can # be closed by .close() self.diff_data.a = None self.diff_data.b = None def _report(self): if self.identical: self._writeln(" No differences found.") if self.diff_extension_types: self._writeln(" Extension types differ:\n a: {}\n " "b: {}".format(*self.diff_extension_types)) if self.diff_extnames: self._writeln(" Extension names differ:\n a: {}\n " "b: {}".format(*self.diff_extnames)) if self.diff_extvers: self._writeln(" Extension versions differ:\n a: {}\n " "b: {}".format(*self.diff_extvers)) if self.diff_extlevels: self._writeln(" Extension levels differ:\n a: {}\n " "b: {}".format(*self.diff_extlevels)) if not self.diff_headers.identical: self._fileobj.write('\n') self._writeln(" Headers contain differences:") self.diff_headers.report(self._fileobj, indent=self._indent + 1) if self.diff_data is not None and not self.diff_data.identical: self._fileobj.write('\n') self._writeln(" Data contains differences:") self.diff_data.report(self._fileobj, indent=self._indent + 1) class HeaderDiff(_BaseDiff): """ Diff two `Header` objects. `HeaderDiff` objects have the following diff attributes: - ``diff_keyword_count``: If the two headers contain a different number of keywords, this contains a 2-tuple of the keyword count for each header. - ``diff_keywords``: If either header contains one or more keywords that don't appear at all in the other header, this contains a 2-tuple consisting of a list of the keywords only appearing in header a, and a list of the keywords only appearing in header b. - ``diff_duplicate_keywords``: If a keyword appears in both headers at least once, but contains a different number of duplicates (for example, a different number of HISTORY cards in each header), an item is added to this dict with the keyword as the key, and a 2-tuple of the different counts of that keyword as the value. For example:: {'HISTORY': (20, 19)} means that header a contains 20 HISTORY cards, while header b contains only 19 HISTORY cards. - ``diff_keyword_values``: If any of the common keyword between the two headers have different values, they appear in this dict. It has a structure similar to ``diff_duplicate_keywords``, with the keyword as the key, and a 2-tuple of the different values as the value. For example:: {'NAXIS': (2, 3)} means that the NAXIS keyword has a value of 2 in header a, and a value of 3 in header b. This excludes any keywords matched by the ``ignore_keywords`` list. - ``diff_keyword_comments``: Like ``diff_keyword_values``, but contains differences between keyword comments. `HeaderDiff` objects also have a ``common_keywords`` attribute that lists all keywords that appear in both headers. """ def __init__(self, a, b, ignore_keywords=[], ignore_comments=[], rtol=0.0, atol=0.0, ignore_blanks=True, ignore_blank_cards=True): """ Parameters ---------- a : `~astropy.io.fits.Header` or string or bytes A header. b : `~astropy.io.fits.Header` or string or bytes A header to compare to the first header. ignore_keywords : sequence, optional Header keywords to ignore when comparing two headers; the presence of these keywords and their values are ignored. Wildcard strings may also be included in the list. ignore_comments : sequence, optional A list of header keywords whose comments should be ignored in the comparison. May contain wildcard strings as with ignore_keywords. numdiffs : int, optional The number of pixel/table values to output when reporting HDU data differences. Though the count of differences is the same either way, this allows controlling the number of different values that are kept in memory or output. If a negative value is given, then numdiffs is treated as unlimited (default: 10). rtol : float, optional The relative difference to allow when comparing two float values either in header values, image arrays, or table columns (default: 0.0). Values which satisfy the expression .. math:: \\left| a - b \\right| > \\text{atol} + \\text{rtol} \\cdot \\left| b \\right| are considered to be different. The underlying function used for comparison is `numpy.allclose`. .. versionadded:: 2.0 atol : float, optional The allowed absolute difference. See also ``rtol`` parameter. .. versionadded:: 2.0 ignore_blanks : bool, optional Ignore extra whitespace at the end of string values either in headers or data. Extra leading whitespace is not ignored (default: True). ignore_blank_cards : bool, optional Ignore all cards that are blank, i.e. they only contain whitespace (default: True). """ self.ignore_keywords = {k.upper() for k in ignore_keywords} self.ignore_comments = {k.upper() for k in ignore_comments} self.rtol = rtol self.atol = atol self.ignore_blanks = ignore_blanks self.ignore_blank_cards = ignore_blank_cards self.ignore_keyword_patterns = set() self.ignore_comment_patterns = set() for keyword in list(self.ignore_keywords): keyword = keyword.upper() if keyword != '*' and glob.has_magic(keyword): self.ignore_keywords.remove(keyword) self.ignore_keyword_patterns.add(keyword) for keyword in list(self.ignore_comments): keyword = keyword.upper() if keyword != '*' and glob.has_magic(keyword): self.ignore_comments.remove(keyword) self.ignore_comment_patterns.add(keyword) # Keywords appearing in each header self.common_keywords = [] # Set to the number of keywords in each header if the counts differ self.diff_keyword_count = () # Set if the keywords common to each header (excluding ignore_keywords) # appear in different positions within the header # TODO: Implement this self.diff_keyword_positions = () # Keywords unique to each header (excluding keywords in # ignore_keywords) self.diff_keywords = () # Keywords that have different numbers of duplicates in each header # (excluding keywords in ignore_keywords) self.diff_duplicate_keywords = {} # Keywords common to each header but having different values (excluding # keywords in ignore_keywords) self.diff_keyword_values = defaultdict(list) # Keywords common to each header but having different comments # (excluding keywords in ignore_keywords or in ignore_comments) self.diff_keyword_comments = defaultdict(list) if isinstance(a, str): a = Header.fromstring(a) if isinstance(b, str): b = Header.fromstring(b) if not (isinstance(a, Header) and isinstance(b, Header)): raise TypeError('HeaderDiff can only diff astropy.io.fits.Header ' 'objects or strings containing FITS headers.') super().__init__(a, b) # TODO: This doesn't pay much attention to the *order* of the keywords, # except in the case of duplicate keywords. The order should be checked # too, or at least it should be an option. def _diff(self): if self.ignore_blank_cards: cardsa = [c for c in self.a.cards if str(c) != BLANK_CARD] cardsb = [c for c in self.b.cards if str(c) != BLANK_CARD] else: cardsa = list(self.a.cards) cardsb = list(self.b.cards) # build dictionaries of keyword values and comments def get_header_values_comments(cards): values = {} comments = {} for card in cards: value = card.value if self.ignore_blanks and isinstance(value, str): value = value.rstrip() values.setdefault(card.keyword, []).append(value) comments.setdefault(card.keyword, []).append(card.comment) return values, comments valuesa, commentsa = get_header_values_comments(cardsa) valuesb, commentsb = get_header_values_comments(cardsb) # Normalize all keyword to upper-case for comparison's sake; # TODO: HIERARCH keywords should be handled case-sensitively I think keywordsa = {k.upper() for k in valuesa} keywordsb = {k.upper() for k in valuesb} self.common_keywords = sorted(keywordsa.intersection(keywordsb)) if len(cardsa) != len(cardsb): self.diff_keyword_count = (len(cardsa), len(cardsb)) # Any other diff attributes should exclude ignored keywords keywordsa = keywordsa.difference(self.ignore_keywords) keywordsb = keywordsb.difference(self.ignore_keywords) if self.ignore_keyword_patterns: for pattern in self.ignore_keyword_patterns: keywordsa = keywordsa.difference(fnmatch.filter(keywordsa, pattern)) keywordsb = keywordsb.difference(fnmatch.filter(keywordsb, pattern)) if '*' in self.ignore_keywords: # Any other differences between keywords are to be ignored return left_only_keywords = sorted(keywordsa.difference(keywordsb)) right_only_keywords = sorted(keywordsb.difference(keywordsa)) if left_only_keywords or right_only_keywords: self.diff_keywords = (left_only_keywords, right_only_keywords) # Compare count of each common keyword for keyword in self.common_keywords: if keyword in self.ignore_keywords: continue if self.ignore_keyword_patterns: skip = False for pattern in self.ignore_keyword_patterns: if fnmatch.fnmatch(keyword, pattern): skip = True break if skip: continue counta = len(valuesa[keyword]) countb = len(valuesb[keyword]) if counta != countb: self.diff_duplicate_keywords[keyword] = (counta, countb) # Compare keywords' values and comments for a, b in zip(valuesa[keyword], valuesb[keyword]): if diff_values(a, b, rtol=self.rtol, atol=self.atol): self.diff_keyword_values[keyword].append((a, b)) else: # If there are duplicate keywords we need to be able to # index each duplicate; if the values of a duplicate # are identical use None here self.diff_keyword_values[keyword].append(None) if not any(self.diff_keyword_values[keyword]): # No differences found; delete the array of Nones del self.diff_keyword_values[keyword] if '*' in self.ignore_comments or keyword in self.ignore_comments: continue if self.ignore_comment_patterns: skip = False for pattern in self.ignore_comment_patterns: if fnmatch.fnmatch(keyword, pattern): skip = True break if skip: continue for a, b in zip(commentsa[keyword], commentsb[keyword]): if diff_values(a, b): self.diff_keyword_comments[keyword].append((a, b)) else: self.diff_keyword_comments[keyword].append(None) if not any(self.diff_keyword_comments[keyword]): del self.diff_keyword_comments[keyword] def _report(self): if self.diff_keyword_count: self._writeln(' Headers have different number of cards:') self._writeln(f' a: {self.diff_keyword_count[0]}') self._writeln(f' b: {self.diff_keyword_count[1]}') if self.diff_keywords: for keyword in self.diff_keywords[0]: if keyword in Card._commentary_keywords: val = self.a[keyword][0] else: val = self.a[keyword] self._writeln(f' Extra keyword {keyword!r:8} in a: {val!r}') for keyword in self.diff_keywords[1]: if keyword in Card._commentary_keywords: val = self.b[keyword][0] else: val = self.b[keyword] self._writeln(f' Extra keyword {keyword!r:8} in b: {val!r}') if self.diff_duplicate_keywords: for keyword, count in sorted(self.diff_duplicate_keywords.items()): self._writeln(f' Inconsistent duplicates of keyword {keyword!r:8}:') self._writeln(' Occurs {} time(s) in a, {} times in (b)' .format(*count)) if self.diff_keyword_values or self.diff_keyword_comments: for keyword in self.common_keywords: report_diff_keyword_attr(self._fileobj, 'values', self.diff_keyword_values, keyword, ind=self._indent) report_diff_keyword_attr(self._fileobj, 'comments', self.diff_keyword_comments, keyword, ind=self._indent) # TODO: It might be good if there was also a threshold option for percentage of # different pixels: For example ignore if only 1% of the pixels are different # within some threshold. There are lots of possibilities here, but hold off # for now until specific cases come up. class ImageDataDiff(_BaseDiff): """ Diff two image data arrays (really any array from a PRIMARY HDU or an IMAGE extension HDU, though the data unit is assumed to be "pixels"). `ImageDataDiff` objects have the following diff attributes: - ``diff_dimensions``: If the two arrays contain either a different number of dimensions or different sizes in any dimension, this contains a 2-tuple of the shapes of each array. Currently no further comparison is performed on images that don't have the exact same dimensions. - ``diff_pixels``: If the two images contain any different pixels, this contains a list of 2-tuples of the array index where the difference was found, and another 2-tuple containing the different values. For example, if the pixel at (0, 0) contains different values this would look like:: [(0, 0), (1.1, 2.2)] where 1.1 and 2.2 are the values of that pixel in each array. This array only contains up to ``self.numdiffs`` differences, for storage efficiency. - ``diff_total``: The total number of different pixels found between the arrays. Although ``diff_pixels`` does not necessarily contain all the different pixel values, this can be used to get a count of the total number of differences found. - ``diff_ratio``: Contains the ratio of ``diff_total`` to the total number of pixels in the arrays. """ def __init__(self, a, b, numdiffs=10, rtol=0.0, atol=0.0): """ Parameters ---------- a : BaseHDU An HDU object. b : BaseHDU An HDU object to compare to the first HDU object. numdiffs : int, optional The number of pixel/table values to output when reporting HDU data differences. Though the count of differences is the same either way, this allows controlling the number of different values that are kept in memory or output. If a negative value is given, then numdiffs is treated as unlimited (default: 10). rtol : float, optional The relative difference to allow when comparing two float values either in header values, image arrays, or table columns (default: 0.0). Values which satisfy the expression .. math:: \\left| a - b \\right| > \\text{atol} + \\text{rtol} \\cdot \\left| b \\right| are considered to be different. The underlying function used for comparison is `numpy.allclose`. .. versionadded:: 2.0 atol : float, optional The allowed absolute difference. See also ``rtol`` parameter. .. versionadded:: 2.0 """ self.numdiffs = numdiffs self.rtol = rtol self.atol = atol self.diff_dimensions = () self.diff_pixels = [] self.diff_ratio = 0 # self.diff_pixels only holds up to numdiffs differing pixels, but this # self.diff_total stores the total count of differences between # the images, but not the different values self.diff_total = 0 super().__init__(a, b) def _diff(self): if self.a.shape != self.b.shape: self.diff_dimensions = (self.a.shape, self.b.shape) # Don't do any further comparison if the dimensions differ # TODO: Perhaps we could, however, diff just the intersection # between the two images return # Find the indices where the values are not equal # If neither a nor b are floating point (or complex), ignore rtol and # atol if not (np.issubdtype(self.a.dtype, np.inexact) or np.issubdtype(self.b.dtype, np.inexact)): rtol = 0 atol = 0 else: rtol = self.rtol atol = self.atol diffs = where_not_allclose(self.a, self.b, atol=atol, rtol=rtol) self.diff_total = len(diffs[0]) if self.diff_total == 0: # Then we're done return if self.numdiffs < 0: numdiffs = self.diff_total else: numdiffs = self.numdiffs self.diff_pixels = [(idx, (self.a[idx], self.b[idx])) for idx in islice(zip(*diffs), 0, numdiffs)] self.diff_ratio = float(self.diff_total) / float(len(self.a.flat)) def _report(self): if self.diff_dimensions: dimsa = ' x '.join(str(d) for d in reversed(self.diff_dimensions[0])) dimsb = ' x '.join(str(d) for d in reversed(self.diff_dimensions[1])) self._writeln(' Data dimensions differ:') self._writeln(f' a: {dimsa}') self._writeln(f' b: {dimsb}') # For now we don't do any further comparison if the dimensions # differ; though in the future it might be nice to be able to # compare at least where the images intersect self._writeln(' No further data comparison performed.') return if not self.diff_pixels: return for index, values in self.diff_pixels: index = [x + 1 for x in reversed(index)] self._writeln(f' Data differs at {index}:') report_diff_values(values[0], values[1], fileobj=self._fileobj, indent_width=self._indent + 1) if self.diff_total > self.numdiffs: self._writeln(' ...') self._writeln(' {} different pixels found ({:.2%} different).' .format(self.diff_total, self.diff_ratio)) class RawDataDiff(ImageDataDiff): """ `RawDataDiff` is just a special case of `ImageDataDiff` where the images are one-dimensional, and the data is treated as a 1-dimensional array of bytes instead of pixel values. This is used to compare the data of two non-standard extension HDUs that were not recognized as containing image or table data. `ImageDataDiff` objects have the following diff attributes: - ``diff_dimensions``: Same as the ``diff_dimensions`` attribute of `ImageDataDiff` objects. Though the "dimension" of each array is just an integer representing the number of bytes in the data. - ``diff_bytes``: Like the ``diff_pixels`` attribute of `ImageDataDiff` objects, but renamed to reflect the minor semantic difference that these are raw bytes and not pixel values. Also the indices are integers instead of tuples. - ``diff_total`` and ``diff_ratio``: Same as `ImageDataDiff`. """ def __init__(self, a, b, numdiffs=10): """ Parameters ---------- a : BaseHDU An HDU object. b : BaseHDU An HDU object to compare to the first HDU object. numdiffs : int, optional The number of pixel/table values to output when reporting HDU data differences. Though the count of differences is the same either way, this allows controlling the number of different values that are kept in memory or output. If a negative value is given, then numdiffs is treated as unlimited (default: 10). """ self.diff_dimensions = () self.diff_bytes = [] super().__init__(a, b, numdiffs=numdiffs) def _diff(self): super()._diff() if self.diff_dimensions: self.diff_dimensions = (self.diff_dimensions[0][0], self.diff_dimensions[1][0]) self.diff_bytes = [(x[0], y) for x, y in self.diff_pixels] del self.diff_pixels def _report(self): if self.diff_dimensions: self._writeln(' Data sizes differ:') self._writeln(f' a: {self.diff_dimensions[0]} bytes') self._writeln(f' b: {self.diff_dimensions[1]} bytes') # For now we don't do any further comparison if the dimensions # differ; though in the future it might be nice to be able to # compare at least where the images intersect self._writeln(' No further data comparison performed.') return if not self.diff_bytes: return for index, values in self.diff_bytes: self._writeln(f' Data differs at byte {index}:') report_diff_values(values[0], values[1], fileobj=self._fileobj, indent_width=self._indent + 1) self._writeln(' ...') self._writeln(' {} different bytes found ({:.2%} different).' .format(self.diff_total, self.diff_ratio)) class TableDataDiff(_BaseDiff): """ Diff two table data arrays. It doesn't matter whether the data originally came from a binary or ASCII table--the data should be passed in as a recarray. `TableDataDiff` objects have the following diff attributes: - ``diff_column_count``: If the tables being compared have different numbers of columns, this contains a 2-tuple of the column count in each table. Even if the tables have different column counts, an attempt is still made to compare any columns they have in common. - ``diff_columns``: If either table contains columns unique to that table, either in name or format, this contains a 2-tuple of lists. The first element is a list of columns (these are full `Column` objects) that appear only in table a. The second element is a list of tables that appear only in table b. This only lists columns with different column definitions, and has nothing to do with the data in those columns. - ``diff_column_names``: This is like ``diff_columns``, but lists only the names of columns unique to either table, rather than the full `Column` objects. - ``diff_column_attributes``: Lists columns that are in both tables but have different secondary attributes, such as TUNIT or TDISP. The format is a list of 2-tuples: The first a tuple of the column name and the attribute, the second a tuple of the different values. - ``diff_values``: `TableDataDiff` compares the data in each table on a column-by-column basis. If any different data is found, it is added to this list. The format of this list is similar to the ``diff_pixels`` attribute on `ImageDataDiff` objects, though the "index" consists of a (column_name, row) tuple. For example:: [('TARGET', 0), ('NGC1001', 'NGC1002')] shows that the tables contain different values in the 0-th row of the 'TARGET' column. - ``diff_total`` and ``diff_ratio``: Same as `ImageDataDiff`. `TableDataDiff` objects also have a ``common_columns`` attribute that lists the `Column` objects for columns that are identical in both tables, and a ``common_column_names`` attribute which contains a set of the names of those columns. """ def __init__(self, a, b, ignore_fields=[], numdiffs=10, rtol=0.0, atol=0.0): """ Parameters ---------- a : BaseHDU An HDU object. b : BaseHDU An HDU object to compare to the first HDU object. ignore_fields : sequence, optional The (case-insensitive) names of any table columns to ignore if any table data is to be compared. numdiffs : int, optional The number of pixel/table values to output when reporting HDU data differences. Though the count of differences is the same either way, this allows controlling the number of different values that are kept in memory or output. If a negative value is given, then numdiffs is treated as unlimited (default: 10). rtol : float, optional The relative difference to allow when comparing two float values either in header values, image arrays, or table columns (default: 0.0). Values which satisfy the expression .. math:: \\left| a - b \\right| > \\text{atol} + \\text{rtol} \\cdot \\left| b \\right| are considered to be different. The underlying function used for comparison is `numpy.allclose`. .. versionadded:: 2.0 atol : float, optional The allowed absolute difference. See also ``rtol`` parameter. .. versionadded:: 2.0 """ self.ignore_fields = set(ignore_fields) self.numdiffs = numdiffs self.rtol = rtol self.atol = atol self.common_columns = [] self.common_column_names = set() # self.diff_columns contains columns with different column definitions, # but not different column data. Column data is only compared in # columns that have the same definitions self.diff_rows = () self.diff_column_count = () self.diff_columns = () # If two columns have the same name+format, but other attributes are # different (such as TUNIT or such) they are listed here self.diff_column_attributes = [] # Like self.diff_columns, but just contains a list of the column names # unique to each table, and in the order they appear in the tables self.diff_column_names = () self.diff_values = [] self.diff_ratio = 0 self.diff_total = 0 super().__init__(a, b) def _diff(self): # Much of the code for comparing columns is similar to the code for # comparing headers--consider refactoring colsa = self.a.columns colsb = self.b.columns if len(colsa) != len(colsb): self.diff_column_count = (len(colsa), len(colsb)) # Even if the number of columns are unequal, we still do comparison of # any common columns colsa = {c.name.lower(): c for c in colsa} colsb = {c.name.lower(): c for c in colsb} if '*' in self.ignore_fields: # If all columns are to be ignored, ignore any further differences # between the columns return # Keep the user's original ignore_fields list for reporting purposes, # but internally use a case-insensitive version ignore_fields = {f.lower() for f in self.ignore_fields} # It might be nice if there were a cleaner way to do this, but for now # it'll do for fieldname in ignore_fields: fieldname = fieldname.lower() if fieldname in colsa: del colsa[fieldname] if fieldname in colsb: del colsb[fieldname] colsa_set = set(colsa.values()) colsb_set = set(colsb.values()) self.common_columns = sorted(colsa_set.intersection(colsb_set), key=operator.attrgetter('name')) self.common_column_names = {col.name.lower() for col in self.common_columns} left_only_columns = {col.name.lower(): col for col in colsa_set.difference(colsb_set)} right_only_columns = {col.name.lower(): col for col in colsb_set.difference(colsa_set)} if left_only_columns or right_only_columns: self.diff_columns = (left_only_columns, right_only_columns) self.diff_column_names = ([], []) if left_only_columns: for col in self.a.columns: if col.name.lower() in left_only_columns: self.diff_column_names[0].append(col.name) if right_only_columns: for col in self.b.columns: if col.name.lower() in right_only_columns: self.diff_column_names[1].append(col.name) # If the tables have a different number of rows, we don't compare the # columns right now. # TODO: It might be nice to optionally compare the first n rows where n # is the minimum of the row counts between the two tables. if len(self.a) != len(self.b): self.diff_rows = (len(self.a), len(self.b)) return # If the tables contain no rows there's no data to compare, so we're # done at this point. (See ticket #178) if len(self.a) == len(self.b) == 0: return # Like in the old fitsdiff, compare tables on a column by column basis # The difficulty here is that, while FITS column names are meant to be # case-insensitive, Astropy still allows, for the sake of flexibility, # two columns with the same name but different case. When columns are # accessed in FITS tables, a case-sensitive is tried first, and failing # that a case-insensitive match is made. # It's conceivable that the same column could appear in both tables # being compared, but with different case. # Though it *may* lead to inconsistencies in these rare cases, this # just assumes that there are no duplicated column names in either # table, and that the column names can be treated case-insensitively. for col in self.common_columns: name_lower = col.name.lower() if name_lower in ignore_fields: continue cola = colsa[name_lower] colb = colsb[name_lower] for attr, _ in _COL_ATTRS: vala = getattr(cola, attr, None) valb = getattr(colb, attr, None) if diff_values(vala, valb): self.diff_column_attributes.append( ((col.name.upper(), attr), (vala, valb))) arra = self.a[col.name] arrb = self.b[col.name] if (np.issubdtype(arra.dtype, np.floating) and np.issubdtype(arrb.dtype, np.floating)): diffs = where_not_allclose(arra, arrb, rtol=self.rtol, atol=self.atol) elif 'P' in col.format: diffs = ([idx for idx in range(len(arra)) if not np.allclose(arra[idx], arrb[idx], rtol=self.rtol, atol=self.atol)],) else: diffs = np.where(arra != arrb) self.diff_total += len(set(diffs[0])) if self.numdiffs >= 0: if len(self.diff_values) >= self.numdiffs: # Don't save any more diff values continue # Add no more diff'd values than this max_diffs = self.numdiffs - len(self.diff_values) else: max_diffs = len(diffs[0]) last_seen_idx = None for idx in islice(diffs[0], 0, max_diffs): if idx == last_seen_idx: # Skip duplicate indices, which my occur when the column # data contains multi-dimensional values; we're only # interested in storing row-by-row differences continue last_seen_idx = idx self.diff_values.append(((col.name, idx), (arra[idx], arrb[idx]))) total_values = len(self.a) * len(self.a.dtype.fields) self.diff_ratio = float(self.diff_total) / float(total_values) def _report(self): if self.diff_column_count: self._writeln(' Tables have different number of columns:') self._writeln(f' a: {self.diff_column_count[0]}') self._writeln(f' b: {self.diff_column_count[1]}') if self.diff_column_names: # Show columns with names unique to either table for name in self.diff_column_names[0]: format = self.diff_columns[0][name.lower()].format self._writeln(f' Extra column {name} of format {format} in a') for name in self.diff_column_names[1]: format = self.diff_columns[1][name.lower()].format self._writeln(f' Extra column {name} of format {format} in b') col_attrs = dict(_COL_ATTRS) # Now go through each table again and show columns with common # names but other property differences... for col_attr, vals in self.diff_column_attributes: name, attr = col_attr self._writeln(f' Column {name} has different {col_attrs[attr]}:') report_diff_values(vals[0], vals[1], fileobj=self._fileobj, indent_width=self._indent + 1) if self.diff_rows: self._writeln(' Table rows differ:') self._writeln(f' a: {self.diff_rows[0]}') self._writeln(f' b: {self.diff_rows[1]}') self._writeln(' No further data comparison performed.') return if not self.diff_values: return # Finally, let's go through and report column data differences: for indx, values in self.diff_values: self._writeln(' Column {} data differs in row {}:'.format(*indx)) report_diff_values(values[0], values[1], fileobj=self._fileobj, indent_width=self._indent + 1) if self.diff_values and self.numdiffs < self.diff_total: self._writeln(' ...{} additional difference(s) found.'.format( self.diff_total - self.numdiffs)) if self.diff_total > self.numdiffs: self._writeln(' ...') self._writeln(' {} different table data element(s) found ' '({:.2%} different).' .format(self.diff_total, self.diff_ratio)) def report_diff_keyword_attr(fileobj, attr, diffs, keyword, ind=0): """ Write a diff between two header keyword values or comments to the specified file-like object. """ if keyword in diffs: vals = diffs[keyword] for idx, val in enumerate(vals): if val is None: continue if idx == 0: dup = '' else: dup = f'[{idx + 1}]' fileobj.write( fixed_width_indent(' Keyword {:8}{} has different {}:\n' .format(keyword, dup, attr), ind)) report_diff_values(val[0], val[1], fileobj=fileobj, indent_width=ind + 1)