| """ |
| Utilities for comparing image results. |
| """ |
|
|
| import atexit |
| import functools |
| import hashlib |
| import logging |
| import os |
| from pathlib import Path |
| import shutil |
| import subprocess |
| import sys |
| from tempfile import TemporaryDirectory, TemporaryFile |
| import weakref |
|
|
| import numpy as np |
| from PIL import Image |
|
|
| import matplotlib as mpl |
| from matplotlib import cbook |
| from matplotlib.testing.exceptions import ImageComparisonFailure |
|
|
| _log = logging.getLogger(__name__) |
|
|
| __all__ = ['calculate_rms', 'comparable_formats', 'compare_images'] |
|
|
|
|
| def make_test_filename(fname, purpose): |
| """ |
| Make a new filename by inserting *purpose* before the file's extension. |
| """ |
| base, ext = os.path.splitext(fname) |
| return f'{base}-{purpose}{ext}' |
|
|
|
|
| def _get_cache_path(): |
| cache_dir = Path(mpl.get_cachedir(), 'test_cache') |
| cache_dir.mkdir(parents=True, exist_ok=True) |
| return cache_dir |
|
|
|
|
| def get_cache_dir(): |
| return str(_get_cache_path()) |
|
|
|
|
| def get_file_hash(path, block_size=2 ** 20): |
| md5 = hashlib.md5() |
| with open(path, 'rb') as fd: |
| while True: |
| data = fd.read(block_size) |
| if not data: |
| break |
| md5.update(data) |
|
|
| if Path(path).suffix == '.pdf': |
| md5.update(str(mpl._get_executable_info("gs").version) |
| .encode('utf-8')) |
| elif Path(path).suffix == '.svg': |
| md5.update(str(mpl._get_executable_info("inkscape").version) |
| .encode('utf-8')) |
|
|
| return md5.hexdigest() |
|
|
|
|
| class _ConverterError(Exception): |
| pass |
|
|
|
|
| class _Converter: |
| def __init__(self): |
| self._proc = None |
| |
| |
| |
| |
| atexit.register(self.__del__) |
|
|
| def __del__(self): |
| if self._proc: |
| self._proc.kill() |
| self._proc.wait() |
| for stream in filter(None, [self._proc.stdin, |
| self._proc.stdout, |
| self._proc.stderr]): |
| stream.close() |
| self._proc = None |
|
|
| def _read_until(self, terminator): |
| """Read until the prompt is reached.""" |
| buf = bytearray() |
| while True: |
| c = self._proc.stdout.read(1) |
| if not c: |
| raise _ConverterError(os.fsdecode(bytes(buf))) |
| buf.extend(c) |
| if buf.endswith(terminator): |
| return bytes(buf) |
|
|
|
|
| class _GSConverter(_Converter): |
| def __call__(self, orig, dest): |
| if not self._proc: |
| self._proc = subprocess.Popen( |
| [mpl._get_executable_info("gs").executable, |
| "-dNOSAFER", "-dNOPAUSE", "-dEPSCrop", "-sDEVICE=png16m"], |
| |
| stdin=subprocess.PIPE, stdout=subprocess.PIPE) |
| try: |
| self._read_until(b"\nGS") |
| except _ConverterError as e: |
| raise OSError(f"Failed to start Ghostscript:\n\n{e.args[0]}") from None |
|
|
| def encode_and_escape(name): |
| return (os.fsencode(name) |
| .replace(b"\\", b"\\\\") |
| .replace(b"(", br"\(") |
| .replace(b")", br"\)")) |
|
|
| self._proc.stdin.write( |
| b"<< /OutputFile (" |
| + encode_and_escape(dest) |
| + b") >> setpagedevice (" |
| + encode_and_escape(orig) |
| + b") run flush\n") |
| self._proc.stdin.flush() |
| |
| err = self._read_until((b"GS<", b"GS>")) |
| stack = self._read_until(b">") if err.endswith(b"GS<") else b"" |
| if stack or not os.path.exists(dest): |
| stack_size = int(stack[:-1]) if stack else 0 |
| self._proc.stdin.write(b"pop\n" * stack_size) |
| |
| raise ImageComparisonFailure( |
| (err + stack).decode(sys.getfilesystemencoding(), "replace")) |
|
|
|
|
| class _SVGConverter(_Converter): |
| def __call__(self, orig, dest): |
| old_inkscape = mpl._get_executable_info("inkscape").version.major < 1 |
| terminator = b"\n>" if old_inkscape else b"> " |
| if not hasattr(self, "_tmpdir"): |
| self._tmpdir = TemporaryDirectory() |
| |
| |
| weakref.finalize(self._tmpdir, self.__del__) |
| if (not self._proc |
| or self._proc.poll() is not None): |
| if self._proc is not None and self._proc.poll() is not None: |
| for stream in filter(None, [self._proc.stdin, |
| self._proc.stdout, |
| self._proc.stderr]): |
| stream.close() |
| env = { |
| **os.environ, |
| |
| |
| |
| |
| |
| "DISPLAY": "", |
| |
| "INKSCAPE_PROFILE_DIR": self._tmpdir.name, |
| } |
| |
| |
| |
| |
| stderr = TemporaryFile() |
| self._proc = subprocess.Popen( |
| ["inkscape", "--without-gui", "--shell"] if old_inkscape else |
| ["inkscape", "--shell"], |
| stdin=subprocess.PIPE, stdout=subprocess.PIPE, stderr=stderr, |
| env=env, cwd=self._tmpdir.name) |
| |
| self._proc.stderr = stderr |
| try: |
| self._read_until(terminator) |
| except _ConverterError as err: |
| raise OSError( |
| "Failed to start Inkscape in interactive mode:\n\n" |
| + err.args[0]) from err |
|
|
| |
| |
| |
| inkscape_orig = Path(self._tmpdir.name, os.fsdecode(b"f.svg")) |
| inkscape_dest = Path(self._tmpdir.name, os.fsdecode(b"f.png")) |
| try: |
| inkscape_orig.symlink_to(Path(orig).resolve()) |
| except OSError: |
| shutil.copyfile(orig, inkscape_orig) |
| self._proc.stdin.write( |
| b"f.svg --export-png=f.png\n" if old_inkscape else |
| b"file-open:f.svg;export-filename:f.png;export-do;file-close\n") |
| self._proc.stdin.flush() |
| try: |
| self._read_until(terminator) |
| except _ConverterError as err: |
| |
| |
| |
| self._proc.stderr.seek(0) |
| raise ImageComparisonFailure( |
| self._proc.stderr.read().decode( |
| sys.getfilesystemencoding(), "replace")) from err |
| os.remove(inkscape_orig) |
| shutil.move(inkscape_dest, dest) |
|
|
| def __del__(self): |
| super().__del__() |
| if hasattr(self, "_tmpdir"): |
| self._tmpdir.cleanup() |
|
|
|
|
| class _SVGWithMatplotlibFontsConverter(_SVGConverter): |
| """ |
| A SVG converter which explicitly adds the fonts shipped by Matplotlib to |
| Inkspace's font search path, to better support `svg.fonttype = "none"` |
| (which is in particular used by certain mathtext tests). |
| """ |
|
|
| def __call__(self, orig, dest): |
| if not hasattr(self, "_tmpdir"): |
| self._tmpdir = TemporaryDirectory() |
| shutil.copytree(cbook._get_data_path("fonts/ttf"), |
| Path(self._tmpdir.name, "fonts")) |
| return super().__call__(orig, dest) |
|
|
|
|
| def _update_converter(): |
| try: |
| mpl._get_executable_info("gs") |
| except mpl.ExecutableNotFoundError: |
| pass |
| else: |
| converter['pdf'] = converter['eps'] = _GSConverter() |
| try: |
| mpl._get_executable_info("inkscape") |
| except mpl.ExecutableNotFoundError: |
| pass |
| else: |
| converter['svg'] = _SVGConverter() |
|
|
|
|
| |
| |
| converter = {} |
| _update_converter() |
| _svg_with_matplotlib_fonts_converter = _SVGWithMatplotlibFontsConverter() |
|
|
|
|
| def comparable_formats(): |
| """ |
| Return the list of file formats that `.compare_images` can compare |
| on this system. |
| |
| Returns |
| ------- |
| list of str |
| E.g. ``['png', 'pdf', 'svg', 'eps']``. |
| |
| """ |
| return ['png', *converter] |
|
|
|
|
| def convert(filename, cache): |
| """ |
| Convert the named file to png; return the name of the created file. |
| |
| If *cache* is True, the result of the conversion is cached in |
| `matplotlib.get_cachedir() + '/test_cache/'`. The caching is based on a |
| hash of the exact contents of the input file. Old cache entries are |
| automatically deleted as needed to keep the size of the cache capped to |
| twice the size of all baseline images. |
| """ |
| path = Path(filename) |
| if not path.exists(): |
| raise OSError(f"{path} does not exist") |
| if path.suffix[1:] not in converter: |
| import pytest |
| pytest.skip(f"Don't know how to convert {path.suffix} files to png") |
| newpath = path.parent / f"{path.stem}_{path.suffix[1:]}.png" |
|
|
| |
| |
| if not newpath.exists() or newpath.stat().st_mtime < path.stat().st_mtime: |
| cache_dir = _get_cache_path() if cache else None |
|
|
| if cache_dir is not None: |
| _register_conversion_cache_cleaner_once() |
| hash_value = get_file_hash(path) |
| cached_path = cache_dir / (hash_value + newpath.suffix) |
| if cached_path.exists(): |
| _log.debug("For %s: reusing cached conversion.", filename) |
| shutil.copyfile(cached_path, newpath) |
| return str(newpath) |
|
|
| _log.debug("For %s: converting to png.", filename) |
| convert = converter[path.suffix[1:]] |
| if path.suffix == ".svg": |
| contents = path.read_text() |
| if 'style="font:' in contents: |
| |
| |
| convert = _svg_with_matplotlib_fonts_converter |
| convert(path, newpath) |
|
|
| if cache_dir is not None: |
| _log.debug("For %s: caching conversion result.", filename) |
| shutil.copyfile(newpath, cached_path) |
|
|
| return str(newpath) |
|
|
|
|
| def _clean_conversion_cache(): |
| |
| |
| baseline_images_size = sum( |
| path.stat().st_size |
| for path in Path(mpl.__file__).parent.glob("**/baseline_images/**/*")) |
| |
| |
| max_cache_size = 2 * baseline_images_size |
| |
| with cbook._lock_path(_get_cache_path()): |
| cache_stat = { |
| path: path.stat() for path in _get_cache_path().glob("*")} |
| cache_size = sum(stat.st_size for stat in cache_stat.values()) |
| paths_by_atime = sorted( |
| cache_stat, key=lambda path: cache_stat[path].st_atime, |
| reverse=True) |
| while cache_size > max_cache_size: |
| path = paths_by_atime.pop() |
| cache_size -= cache_stat[path].st_size |
| path.unlink() |
|
|
|
|
| @functools.cache |
| def _register_conversion_cache_cleaner_once(): |
| atexit.register(_clean_conversion_cache) |
|
|
|
|
| def crop_to_same(actual_path, actual_image, expected_path, expected_image): |
| |
| |
| if actual_path[-7:-4] == 'eps' and expected_path[-7:-4] == 'pdf': |
| aw, ah, ad = actual_image.shape |
| ew, eh, ed = expected_image.shape |
| actual_image = actual_image[int(aw / 2 - ew / 2):int( |
| aw / 2 + ew / 2), int(ah / 2 - eh / 2):int(ah / 2 + eh / 2)] |
| return actual_image, expected_image |
|
|
|
|
| def calculate_rms(expected_image, actual_image): |
| """ |
| Calculate the per-pixel errors, then compute the root mean square error. |
| """ |
| if expected_image.shape != actual_image.shape: |
| raise ImageComparisonFailure( |
| f"Image sizes do not match expected size: {expected_image.shape} " |
| f"actual size {actual_image.shape}") |
| |
| return np.sqrt(((expected_image - actual_image).astype(float) ** 2).mean()) |
|
|
|
|
| |
| |
|
|
|
|
| def _load_image(path): |
| img = Image.open(path) |
| |
| |
| |
| if img.mode != "RGBA" or img.getextrema()[3][0] == 255: |
| img = img.convert("RGB") |
| return np.asarray(img) |
|
|
|
|
| def compare_images(expected, actual, tol, in_decorator=False): |
| """ |
| Compare two "image" files checking differences within a tolerance. |
| |
| The two given filenames may point to files which are convertible to |
| PNG via the `.converter` dictionary. The underlying RMS is calculated |
| with the `.calculate_rms` function. |
| |
| Parameters |
| ---------- |
| expected : str |
| The filename of the expected image. |
| actual : str |
| The filename of the actual image. |
| tol : float |
| The tolerance (a color value difference, where 255 is the |
| maximal difference). The test fails if the average pixel |
| difference is greater than this value. |
| in_decorator : bool |
| Determines the output format. If called from image_comparison |
| decorator, this should be True. (default=False) |
| |
| Returns |
| ------- |
| None or dict or str |
| Return *None* if the images are equal within the given tolerance. |
| |
| If the images differ, the return value depends on *in_decorator*. |
| If *in_decorator* is true, a dict with the following entries is |
| returned: |
| |
| - *rms*: The RMS of the image difference. |
| - *expected*: The filename of the expected image. |
| - *actual*: The filename of the actual image. |
| - *diff_image*: The filename of the difference image. |
| - *tol*: The comparison tolerance. |
| |
| Otherwise, a human-readable multi-line string representation of this |
| information is returned. |
| |
| Examples |
| -------- |
| :: |
| |
| img1 = "./baseline/plot.png" |
| img2 = "./output/plot.png" |
| compare_images(img1, img2, 0.001) |
| |
| """ |
| actual = os.fspath(actual) |
| if not os.path.exists(actual): |
| raise Exception(f"Output image {actual} does not exist.") |
| if os.stat(actual).st_size == 0: |
| raise Exception(f"Output image file {actual} is empty.") |
|
|
| |
| expected = os.fspath(expected) |
| if not os.path.exists(expected): |
| raise OSError(f'Baseline image {expected!r} does not exist.') |
| extension = expected.split('.')[-1] |
| if extension != 'png': |
| actual = convert(actual, cache=True) |
| expected = convert(expected, cache=True) |
|
|
| |
| expected_image = _load_image(expected) |
| actual_image = _load_image(actual) |
|
|
| actual_image, expected_image = crop_to_same( |
| actual, actual_image, expected, expected_image) |
|
|
| diff_image = make_test_filename(actual, 'failed-diff') |
|
|
| if tol <= 0: |
| if np.array_equal(expected_image, actual_image): |
| return None |
|
|
| |
| |
| expected_image = expected_image.astype(np.int16) |
| actual_image = actual_image.astype(np.int16) |
|
|
| rms = calculate_rms(expected_image, actual_image) |
|
|
| if rms <= tol: |
| return None |
|
|
| save_diff_image(expected, actual, diff_image) |
|
|
| results = dict(rms=rms, expected=str(expected), |
| actual=str(actual), diff=str(diff_image), tol=tol) |
|
|
| if not in_decorator: |
| |
| template = ['Error: Image files did not match.', |
| 'RMS Value: {rms}', |
| 'Expected: \n {expected}', |
| 'Actual: \n {actual}', |
| 'Difference:\n {diff}', |
| 'Tolerance: \n {tol}', ] |
| results = '\n '.join([line.format(**results) for line in template]) |
| return results |
|
|
|
|
| def save_diff_image(expected, actual, output): |
| """ |
| Parameters |
| ---------- |
| expected : str |
| File path of expected image. |
| actual : str |
| File path of actual image. |
| output : str |
| File path to save difference image to. |
| """ |
| expected_image = _load_image(expected) |
| actual_image = _load_image(actual) |
| actual_image, expected_image = crop_to_same( |
| actual, actual_image, expected, expected_image) |
| expected_image = np.array(expected_image, float) |
| actual_image = np.array(actual_image, float) |
| if expected_image.shape != actual_image.shape: |
| raise ImageComparisonFailure( |
| f"Image sizes do not match expected size: {expected_image.shape} " |
| f"actual size {actual_image.shape}") |
| abs_diff = np.abs(expected_image - actual_image) |
|
|
| |
| abs_diff *= 10 |
| abs_diff = np.clip(abs_diff, 0, 255).astype(np.uint8) |
|
|
| if abs_diff.shape[2] == 4: |
| abs_diff[:, :, 3] = 255 |
|
|
| Image.fromarray(abs_diff).save(output, format="png") |
|
|