Source code for dxtbx.imageset

from __future__ import annotations

import natsort

import boost_adaptbx.boost.python

import dxtbx.format.image  # noqa: F401, import dependency for unpickling
import dxtbx.format.Registry
from dxtbx.sequence_filenames import group_files_by_imageset, template_image_range

try:
    from .dxtbx_imageset_ext import (
        ExternalLookup,
        ExternalLookupItemBool,
        ExternalLookupItemDouble,
        ImageGrid,
        ImageSequence,
        ImageSet,
        ImageSetData,
    )
except ModuleNotFoundError:
    from dxtbx_imageset_ext import (  # type: ignore
        ExternalLookup,
        ExternalLookupItemBool,
        ExternalLookupItemDouble,
        ImageGrid,
        ImageSequence,
        ImageSet,
        ImageSetData,
    )

ext = boost_adaptbx.boost.python.import_ext("dxtbx_ext")

from typing import Iterable

__all__ = (
    "ExternalLookup",
    "ExternalLookupItemBool",
    "ExternalLookupItemDouble",
    "ImageGrid",
    "ImageSet",
    "ImageSetData",
    "ImageSetFactory",
    "ImageSetLazy",
    "ImageSequence",
    "MemReader",
)


def _expand_template_to_sorted_filenames(
    template: str, indices: Iterable[int]
) -> list[str]:
    """Expand a template string to a list of filenames.

    Args:
        template: The template string, with a block of '#' to replace
        indices:  The numeric indices to insert
    """
    pfx = template.split("#")[0]
    sfx = template.split("#")[-1]
    count = template.count("#")
    if count == 1:
        # Special handling for a template with a single "#", which does not
        # assume a zero-padded index.
        filenames = [f"{pfx}{index}{sfx}" for index in indices]
    else:
        filenames = [f"{pfx}{index:0{count}}{sfx}" for index in indices]
    return natsort.natsorted(filenames)


[docs] class MemReader: """A reader for data already loaded in memory"""
[docs] def __init__(self, images): self._images = images
[docs] def copy(self, paths): """ Experimental implementation where a copy of the reader also copies all the data """ return MemReader(self._images)
[docs] def paths(self): return ["" for im in self._images]
[docs] def identifiers(self): return self.paths()
def __len__(self): return len(self._images)
[docs] def read(self, index): format_instance = self._images[index] return format_instance.get_raw_data()
[docs] @staticmethod def is_single_file_reader(): return False
[docs] @staticmethod def master_path(): return ""
@boost_adaptbx.boost.python.inject_into(ImageSet) class _: """ A class to inject additional methods into the imageset class """ def __getitem__(self, item): """Get an item from the image set stream. If the item is an index, read and return the image at the given index. Otherwise, if the item is a slice, then create a new ImageSet object with the given number of array indices from the slice. Params: item The index or slice Returns: An image or new ImageSet object """ if isinstance(item, slice): start = item.start or 0 stop = item.stop or len(self) if item.step is not None and item.step != 1: raise IndexError("Step must be 1") if self.data().has_single_file_reader(): reader = self.reader().copy(self.reader().paths(), stop - start) else: reader = self.reader().copy(self.reader().paths()) return self.partial_set(reader, start, stop) else: return self.get_corrected_data(item) def __iter__(self): """Iterate over the array indices and read each image in turn.""" for i in range(len(self)): yield self[i] def get_vendortype(self, index): """Get the vendor information.""" return self.data().get_vendor() def get_format_class(self): """Get format class name""" return self.data().get_format_class() def get_spectrum(self, index): """Get the spectrum if available""" kwargs = self.params() if self.data().has_single_file_reader(): format_instance = self.get_format_class().get_instance( self.data().get_master_path(), **kwargs ) else: format_instance = self.get_format_class().get_instance( self.get_path(index), **kwargs ) try: return format_instance.get_spectrum(self.indices()[index]) except TypeError: return format_instance.get_spectrum() def params(self): """Get the parameters""" return self.data().get_params() def get_detectorbase(self, index): """ A function to be injected into the imageset to get the detectorbase instance """ kwargs = self.params() if self.data().has_single_file_reader(): format_instance = self.get_format_class().get_instance( self.data().get_master_path(), **kwargs ) return format_instance.get_detectorbase(self.indices()[index]) else: format_instance = self.get_format_class().get_instance( self.get_path(index), **kwargs ) return format_instance.get_detectorbase() def reader(self): """ Return the reader """ return self.data().reader() def masker(self): """ Return the masker """ return self.data().masker() def paths(self): """ Return the list of paths """ if self.data().has_single_file_reader(): return [self.get_path(i) for i in range(len(self))] else: return [self.reader().paths()[i] for i in self.indices()]
[docs] class ImageSetLazy(ImageSet): """ Lazy ImageSet class that doesn't necessitate setting the models ahead of time. Only when a particular model (like detector or beam) for an image is requested, it sets the model using the format class and then returns the model """ def _get_item_from_parent_or_format(self, item_name, index): """ Obtain an $item_name (eg. detector, beam, ...) of the given index from the parent class using get_detector, get_beam, ... If the parent class returns None then lookup the item using the format class (if defined) and store a local reference to the item using self.set_detector, set_beam, .. """ if index is None: index = 0 item = getattr(super(), "get_" + item_name)(index) if item is None: # If check_format=False was used, then _current_instance_ will not be set, so assume a None is correct format_class = self.get_format_class() if ( hasattr(format_class, "_current_instance_") and format_class._current_instance_ is not None ): format_instance = format_class._current_instance_ getter_function = getattr(format_instance, "get_" + item_name) item = getter_function(self.indices()[index]) setter_function = getattr(self, "set_" + item_name) setter_function(item, index) return item
[docs] def get_detector(self, index=None): return self._get_item_from_parent_or_format("detector", index)
[docs] def get_beam(self, index=None): return self._get_item_from_parent_or_format("beam", index)
[docs] def get_mask(self, index=None): """ ImageSet::get_mask internally dereferences a pointer to the _detector member of ImageSetData, so we ensure the detector gets populated first. """ if getattr(super(), "get_detector")(index) is None: self._load_models(index) return self._get_item_from_parent_or_format("mask", index)
[docs] def get_goniometer(self, index=None): return self._get_item_from_parent_or_format("goniometer", index)
[docs] def get_scan(self, index=None): return self._get_item_from_parent_or_format("scan", index)
def _load_models(self, index): if index is None: index = 0 # Sets the list for detector, beam etc before being accessed by functions in imageset.h self.get_detector(index) self.get_beam(index) self.get_goniometer(index) self.get_scan(index) def __getitem__(self, item): if isinstance(item, slice): start = item.start or 0 stop = item.stop or len(self) if item.step is not None and item.step != 1: raise IndexError("Step must be 1") if self.data().has_single_file_reader(): reader = self.reader().copy(self.reader().paths(), stop - start) else: reader = self.reader().copy(self.reader().paths()) return ImageSetLazy( self.data().partial_data(reader, start, stop), indices=self.indices()[item], ) self._load_models(item) return super().__getitem__(item)
[docs] def get_corrected_data(self, index): self._load_models(index) return super().get_corrected_data(index)
[docs] def get_gain(self, index): self._load_models(index) return super().get_gain(index)
@boost_adaptbx.boost.python.inject_into(ImageSequence) class _imagesequence: def __getitem__(self, item): """Get an item from the sequence stream. If the item is an index, read and return the image at the given index. Otherwise, if the item is a slice, then create a new Sequence object with the given number of array indices from the slice. Params: item The index or slice Returns: An image or new Sequence object """ if not isinstance(item, slice): return self.get_corrected_data(item) else: if item.step is not None: raise IndexError("Sequences must be sequential") start = item.start or 0 stop = item.stop or len(self) if self.data().has_single_file_reader(): reader = self.reader().copy(self.reader().paths(), stop - start) else: reader = self.reader().copy(self.reader().paths()) return self.partial_set(reader, start, stop) def get_template(self): """Return the template""" return self.data().get_template() def _analyse_files(filenames): """Group images by filename into image sets. Params: filenames The list of filenames Returns: A list of (template, [indices], is_sequence) """ # Analyse filenames to figure out how many imagesets we have filelist_per_imageset = group_files_by_imageset(filenames) def _indices_sequential_ge_zero(indices): """Determine if indices are sequential.""" prev = indices[0] if prev < 0: return False for curr in indices[1:]: if curr != prev + 1: return False prev = curr return True def _is_imageset_a_sequence(template, indices): """Return True/False if the imageset is a sequence or not. Where more than 1 image that follow sequential numbers are given the images are catagorised as belonging to a sequence, otherwise they belong to an image set. """ if len(indices) <= 1: return False indices = sorted(indices) return _indices_sequential_ge_zero(indices) # Label each group as either an imageset or a sequence. file_groups = [] for template, indices in filelist_per_imageset.items(): # Check if this imageset is a sequence is_sequence = _is_imageset_a_sequence(template, indices) # Append the items to the group list file_groups.append((template, indices, is_sequence)) return file_groups # FIXME Lots of duplication in this class, need to tidy up
[docs] class ImageSetFactory: """Factory to create imagesets and sequences."""
[docs] @staticmethod def new(filenames, check_headers=False, ignore_unknown=False): """Create an imageset or sequence Params: filenames A list of filenames check_headers Check the headers to ensure all images are valid ignore_unknown Ignore unknown formats Returns: A list of imagesets """ # Ensure we have enough images if isinstance(filenames, list): assert filenames elif isinstance(filenames, str): filenames = [filenames] else: raise RuntimeError("unknown argument passed to ImageSetFactory") # Analyse the filenames and group the images into imagesets. filelist_per_imageset = _analyse_files(filenames) # For each file list denoting an image set, create the imageset # and return as a list of imagesets. N.B sequences and image sets are # returned in the same list. imagesetlist = [] for filelist in filelist_per_imageset: try: if filelist[2] is True: iset = ImageSetFactory._create_sequence(filelist, check_headers) else: iset = ImageSetFactory._create_imageset(filelist, check_headers) imagesetlist.append(iset) except Exception: if not ignore_unknown: raise return imagesetlist
[docs] @staticmethod def from_template( template, image_range=None, check_headers=False, check_format=True, beam=None, detector=None, goniometer=None, scan=None, ): """Create a new sequence from a template. Params: template The template argument image_range The image range check_headers Check the headers to ensure all images are valid Returns: A list of sequences """ if not check_format: assert not check_headers # Check the template is valid if "#" in template: # Get the template image range if image_range is None: image_range = template_image_range(template) # Set the image range indices = range(image_range[0], image_range[1] + 1) filenames = _expand_template_to_sorted_filenames(template, indices) else: if "master" not in template: raise ValueError("Invalid template") filenames = [template] # Import here as Format and Imageset have cyclic dependencies from dxtbx.format.Format import Format # Get the format class if check_format: format_class = dxtbx.format.Registry.get_format_class_for_file(filenames[0]) else: format_class = Format # Create the sequence object sequence = format_class.get_imageset( filenames, template=template, as_sequence=True, beam=beam, detector=detector, goniometer=goniometer, scan=scan, check_format=check_format, ) return [sequence]
@staticmethod def _create_imageset(filelist, check_headers): """Create an image set""" # Extract info from filelist template, indices, is_sequence = filelist # Get the template format if "#" in template: filenames = _expand_template_to_sorted_filenames(template, indices) else: filenames = [template] # Get the format object format_class = dxtbx.format.Registry.get_format_class_for_file(filenames[0]) # Create and return the imageset return format_class.get_imageset(filenames, as_imageset=True) @staticmethod def _create_sequence(filelist, check_headers): """Create a sequence""" template, indices, is_sequence = filelist # Expand the template if necessary if "#" in template: filenames = _expand_template_to_sorted_filenames(template, indices) else: filenames = [template] # Get the format object format_class = dxtbx.format.Registry.get_format_class_for_file(filenames[0]) return format_class.get_imageset(filenames, template=template, as_sequence=True)
[docs] @staticmethod def make_imageset( filenames, format_class=None, check_format=True, single_file_indices=None, format_kwargs=None, ): """Create an image set""" # Import here as Format and Imageset have cyclic dependencies from dxtbx.format.Format import Format # So does FormatMultiImage from dxtbx.format.FormatMultiImage import FormatMultiImage # Get the format object if format_class is None: if check_format: format_class = dxtbx.format.Registry.get_format_class_for_file( filenames[0] ) else: if single_file_indices is None or len(single_file_indices) == 0: format_class = Format else: format_class = FormatMultiImage return format_class.get_imageset( filenames, single_file_indices=single_file_indices, as_imageset=True, format_kwargs=format_kwargs, check_format=check_format, )
[docs] @staticmethod def make_sequence( template, indices, format_class=None, beam=None, detector=None, goniometer=None, scan=None, check_format=True, format_kwargs=None, ): """Create a sequence""" indices = sorted(indices) # Get the template format if "#" in template: filenames = _expand_template_to_sorted_filenames(template, indices) else: filenames = [template] # Set the image range array_range = (min(indices) - 1, max(indices)) if scan is not None: assert array_range == scan.get_array_range() scan.set_batch_offset(array_range[0]) # Get the format object and reader if format_class is None: # Import here as Format and Imageset have cyclic dependencies from dxtbx.format.Format import Format if check_format: format_class = dxtbx.format.Registry.get_format_class_for_file( filenames[0] ) else: format_class = Format return format_class.get_imageset( filenames, beam=beam, detector=detector, goniometer=goniometer, scan=scan, format_kwargs=format_kwargs, template=template, as_sequence=True, check_format=check_format, single_file_indices=list(range(*array_range)), )
[docs] @staticmethod def imageset_from_anyset(imageset): """Create a new ImageSet object from an imageset object. Converts ImageSequence to ImageSet.""" if isinstance(imageset, ImageSetLazy): return ImageSetLazy(imageset.data(), imageset.indices()) elif isinstance(imageset, ImageSequence) or isinstance(imageset, ImageSet): return ImageSet(imageset.data(), imageset.indices()) else: raise ValueError("Unrecognized imageset type: %s" % str(type(imageset)))